xszheng2020/the_stack_dedup_python_hits_0 · Datasets at Hugging Face

ed42fcb801fa38e9585e0b02fe9fd71eff57af66

1,863

py

Python

histogram.py

ccfelius/queueing

c38bd2fe230e52d6166a94449cec28f82e245ec2

[ "MIT" ]

1

2020-12-10T17:36:40.000Z

histogram.py

ccfelius/queueing

c38bd2fe230e52d6166a94449cec28f82e245ec2

[ "MIT" ]

null

histogram.py

ccfelius/queueing

c38bd2fe230e52d6166a94449cec28f82e245ec2

[ "MIT" ]

1

2021-01-05T13:08:03.000Z

import matplotlib.pyplot as plt import pandas as pd import math import numpy as np from scipy import stats import seaborn as sns data = pd.read_csv("data/500-4.txt", sep="\t") # example1 = data[data["SIM_TIME"] == 500] simulations = 500 simtimes = [5, 50, 150, 500, 1000] # for i in [1, 2, 4]: # data = pd.read_csv(f"data/500-{i}.txt", sep="\t") # example = data[data["SIM_TIME"] == simtime] rhos = [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 0.975] print("DONE") print("\n START MEAN, STDEV, CONF INT") data = pd.read_csv(f"data/500-2.txt", sep="\t") example = data[data["SIM_TIME"] == 150] example1 = data[data["SIM_TIME"] == 500] ex = example[example['RHO'] == 0.1]['AVG_WAIT'] ex2 = example1[example1['RHO'] == 0.1]['AVG_WAIT'] ex_9 = example[example['RHO'] == 0.9]['AVG_WAIT'] ex2_9 = example1[example1['RHO'] == 0.9]['AVG_WAIT'] print("\nMEAN 150, 500, rho 0.1, rho 0.9") print(ex.mean(), ex2.mean()) print(ex_9.mean(), ex2_9.mean()) print("\nSTDEV 150, 500, rho 0.1, rho 0.9") print(ex.std(), ex2.std()) print(ex_9.std(), ex2_9.std()) fig = plt.figure(facecolor='w') ax = fig.add_subplot(111, facecolor='whitesmoke', axisbelow=True) ax.hist(ex_9, bins = 100, alpha=0.8, color = 'cornflowerblue', label="Simtime=150") ax.hist(ex2_9, bins = 100, alpha = 0.5, color='springgreen', label="Simtime=500") # sns.displot(ex_9,) # sns.displot(ex2_9) ax.set_xlabel('Mean waiting time / time unit', fontsize=12) ax.set_ylabel('Density', fontsize=12) ax.set_title('Distribution mean waiting time', fontsize = 14) ax.yaxis.set_tick_params(length=0) ax.xaxis.set_tick_params(length=0) ax.grid(b=True, which='major', c='w', lw=2, ls='-') legend = ax.legend() legend.get_frame().set_alpha(0.5) for spine in ('top', 'right', 'bottom', 'left'): ax.spines[spine].set_visible(False) plt.savefig("plots/histogram-150-500-01.png", dpi=300) plt.show()

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1,863

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null

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null

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1

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ed4391eec6c0ca45d66a840d1a081ef7d248ea7e

558

py

Python

python/1931.py

zheedong/BaekJoon

7f9e00085276a337d18ee3bb90c98126f7af4d3a

[ "MIT" ]

null

python/1931.py

zheedong/BaekJoon

7f9e00085276a337d18ee3bb90c98126f7af4d3a

[ "MIT" ]

null

python/1931.py

zheedong/BaekJoon

7f9e00085276a337d18ee3bb90c98126f7af4d3a

[ "MIT" ]

null

n = int(input()) conf_set = [] for _ in range(n): conf_set.append(tuple(map(int, input().split()))) conf_set.sort(key=lambda x : (x[1], x[0])) # 끝나는 시간을 기준으로 정렬 # 시작과 종료가 같은 경우를 포함하기 위해선, 시작 시간도 오름차순으로 정렬해 줘야 한다 solution_list = [conf_set[0]] # Greedy Algorithm for conf in conf_set[1:]: last_conf = solution_list[-1] _, last_end_time = last_conf new_start_time, _ = conf # 정렬된 회의의 list의 마지막 값의 시작 시간과, 정답 list 마지막의 종료 시간을 비교한다 if new_start_time >= last_end_time: solution_list.append(conf) print(len(solution_list))

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null

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null

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1

0

ed446ef71ae2d9e250f77adc4d3e36a498ecb373

3,239

py

Python

egs2/mr_openslr64/asr1/local/data_prep.py

texpomru13/espnet

7ef005e832e2fb033f356c16f54e0f08762fb4b0

[ "Apache-2.0" ]

1

2022-03-25T14:41:05.000Z

egs2/mr_openslr64/asr1/local/data_prep.py

texpomru13/espnet

7ef005e832e2fb033f356c16f54e0f08762fb4b0

[ "Apache-2.0" ]

2

2019-04-23T04:43:33.000Z

2019-05-13T13:06:52.000Z

egs2/mr_openslr64/asr1/local/data_prep.py

texpomru13/espnet

7ef005e832e2fb033f356c16f54e0f08762fb4b0

[ "Apache-2.0" ]

null

#!/usr/bin/env python3 # Copyright 2021 Carnegie Mellon University (Peter Wu) # Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0) import argparse import os import random if __name__ == "__main__": parser = argparse.ArgumentParser() parser.add_argument("-d", help="downloads directory", type=str, default="downloads") args = parser.parse_args() tsv_path = "%s/line_index.tsv" % args.d with open(tsv_path, "r") as inf: tsv_lines = inf.readlines() tsv_lines = [line.strip() for line in tsv_lines] spk2utt = {} utt2text = {} for line in tsv_lines: l_list = line.split("\t") fid = l_list[0] spk = l_list[0].split("_")[1] text = l_list[1] path = "%s/%s.wav" % (args.d, fid) if os.path.exists(path): utt2text[fid] = text if spk in spk2utt: spk2utt[spk].append(fid) else: spk2utt[spk] = [fid] spks = sorted(list(spk2utt.keys())) num_fids = 0 num_test_spks = 0 for spk in spks: num_test_spks += 1 fids = sorted(list(set(spk2utt[spk]))) num_fids += len(fids) if num_fids >= 2000: break num_test_spks = 2 test_spks = spks[:num_test_spks] train_dev_spks = spks[num_test_spks:] random.Random(0).shuffle(train_dev_spks) num_train = int(len(train_dev_spks) * 0.9) train_spks = train_dev_spks[:num_train] dev_spks = train_dev_spks[num_train:] spks_by_phase = {"train": train_spks, "dev": dev_spks, "test": test_spks} flac_dir = "%s" % args.d sr = 16000 for phase in spks_by_phase: spks = spks_by_phase[phase] text_strs = [] wav_scp_strs = [] spk2utt_strs = [] num_fids = 0 for spk in spks: fids = sorted(list(set(spk2utt[spk]))) num_fids += len(fids) if phase == "test" and num_fids > 2000: curr_num_fids = num_fids - 2000 random.Random(1).shuffle(fids) fids = fids[:curr_num_fids] utts = [spk + "-" + f for f in fids] utts_str = " ".join(utts) spk2utt_strs.append("%s %s" % (spk, utts_str)) for fid, utt in zip(fids, utts): cmd = "ffmpeg -i %s/%s.wav -f wav -ar %d -ab 16 -ac 1 - |" % ( flac_dir, fid, sr, ) text_strs.append("%s %s" % (utt, utt2text[fid])) wav_scp_strs.append("%s %s" % (utt, cmd)) phase_dir = "data/marathi_%s" % phase if not os.path.exists(phase_dir): os.makedirs(phase_dir) text_strs = sorted(text_strs) wav_scp_strs = sorted(wav_scp_strs) spk2utt_strs = sorted(spk2utt_strs) with open(os.path.join(phase_dir, "text"), "w+") as ouf: for s in text_strs: ouf.write("%s\n" % s) with open(os.path.join(phase_dir, "wav.scp"), "w+") as ouf: for s in wav_scp_strs: ouf.write("%s\n" % s) with open(os.path.join(phase_dir, "spk2utt"), "w+") as ouf: for s in spk2utt_strs: ouf.write("%s\n" % s)

32.39

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0.036145

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null

0

null

0

1

0

ed45225f06a1a8cadf577895bd9772f8a5fae7c7

1,240

py

Python

src/napari_geojson/_tests/test_writer.py

NHPatterson/napari-geojson

8e7925dc7600608673d489e24e8760c4669eaa0b

[ "BSD-3-Clause" ]

null

src/napari_geojson/_tests/test_writer.py

NHPatterson/napari-geojson

8e7925dc7600608673d489e24e8760c4669eaa0b

[ "BSD-3-Clause" ]

6

2021-12-31T06:04:05.000Z

2022-02-27T15:19:29.000Z

src/napari_geojson/_tests/test_writer.py

NHPatterson/napari-geojson

8e7925dc7600608673d489e24e8760c4669eaa0b

[ "BSD-3-Clause" ]

1

2022-02-22T20:35:07.000Z

import geojson import pytest from napari_geojson import write_shapes ellipse = [[[0, 0], [0, 5], [5, 5], [5, 0]], "ellipse", "Polygon"] line = [[[0, 0], [5, 5]], "line", "LineString"] polygon = [[[0, 0], [5, 5], [0, 10]], "polygon", "Polygon"] polyline = [[[0, 0], [5, 5], [0, 10]], "path", "LineString"] rectangle = [[[0, 0], [0, 5], [5, 5], [5, 0]], "rectangle", "Polygon"] sample_shapes = [ellipse, line, polygon, polyline, rectangle] sample_shapes_ids = ["ellipse", "line", "polygon", "polyline", "rectangle"] @pytest.mark.parametrize( "coords,shape_type,expected", sample_shapes, ids=sample_shapes_ids ) def test_write_each_shape( make_napari_viewer, tmp_path, coords, shape_type, expected ): # noqa E501 """Writer writes a shapes layer as GeoJSON.""" fname = str(tmp_path / "sample.geojson") viewer = make_napari_viewer() shapes_layer = viewer.add_shapes(coords, shape_type=shape_type) # shape was written assert len(shapes_layer.data) == 1 data, meta, _ = shapes_layer.as_layer_data_tuple() write_shapes(fname, data, meta) # read back with open(fname) as fp: collection = geojson.load(fp) geom = collection["geometries"][0] assert geom.type == expected

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null

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null

0

1

0

ed487e9bb61e7b47c76c3fe0f4b895d4d0e7a7e7

12,688

py

Python

pgmpy/models/ClusterGraph.py

echoyi/pgmpy

c37dda4401f23ec73fc5d17d957867cd62e588d3

[ "MIT" ]

null

pgmpy/models/ClusterGraph.py

echoyi/pgmpy

c37dda4401f23ec73fc5d17d957867cd62e588d3

[ "MIT" ]

null

pgmpy/models/ClusterGraph.py

echoyi/pgmpy

c37dda4401f23ec73fc5d17d957867cd62e588d3

[ "MIT" ]

null

#!/usr/bin/env python3 from collections import defaultdict import numpy as np from pgmpy.base import UndirectedGraph from pgmpy.factors import factor_product class ClusterGraph(UndirectedGraph): r""" Base class for representing Cluster Graph. Cluster graph is an undirected graph which is associated with a subset of variables. The graph contains undirected edges that connects clusters whose scopes have a non-empty intersection. Formally, a cluster graph is :math:`\mathcal{U}` for a set of factors :math:`\Phi` over :math:`\mathcal{X}` is an undirected graph, each of whose nodes :math:`i` is associated with a subset :math:`C_i \subseteq X`. A cluster graph must be family-preserving - each factor :math:`\phi \in \Phi` must be associated with a cluster C, denoted :math:`\alpha(\phi)`, such that :math:`Scope[\phi] \subseteq C_i`. Each edge between a pair of clusters :math:`C_i` and :math:`C_j` is associated with a sepset :math:`S_{i,j} \subseteq C_i \cap C_j`. Parameters ---------- data: input graph Data to initialize graph. If data=None (default) an empty graph is created. The data is an edge list Examples -------- Create an empty ClusterGraph with no nodes and no edges >>> from pgmpy.models import ClusterGraph >>> G = ClusterGraph() G can be grown by adding clique nodes. **Nodes:** Add a tuple (or list or set) of nodes as single clique node. >>> G.add_node(('a', 'b', 'c')) >>> G.add_nodes_from([('a', 'b'), ('a', 'b', 'c')]) **Edges:** G can also be grown by adding edges. >>> G.add_edge(('a', 'b', 'c'), ('a', 'b')) or a list of edges >>> G.add_edges_from([(('a', 'b', 'c'), ('a', 'b')), ... (('a', 'b', 'c'), ('a', 'c'))]) """ def __init__(self, ebunch=None): super(ClusterGraph, self).__init__() if ebunch: self.add_edges_from(ebunch) self.factors = [] def add_node(self, node, **kwargs): """ Add a single node to the cluster graph. Parameters ---------- node: node A node should be a collection of nodes forming a clique. It can be a list, set or tuple of nodes Examples -------- >>> from pgmpy.models import ClusterGraph >>> G = ClusterGraph() >>> G.add_node(('a', 'b', 'c')) """ if not isinstance(node, (list, set, tuple)): raise TypeError( "Node can only be a list, set or tuple of nodes forming a clique" ) node = tuple(node) super(ClusterGraph, self).add_node(node, **kwargs) def add_nodes_from(self, nodes, **kwargs): """ Add multiple nodes to the cluster graph. Parameters ---------- nodes: iterable container A container of nodes (list, dict, set, etc.). Examples -------- >>> from pgmpy.models import ClusterGraph >>> G = ClusterGraph() >>> G.add_nodes_from([('a', 'b'), ('a', 'b', 'c')]) """ for node in nodes: self.add_node(node, **kwargs) def add_edge(self, u, v, **kwargs): """ Add an edge between two clique nodes. Parameters ---------- u, v: nodes Nodes can be any list or set or tuple of nodes forming a clique. Examples -------- >>> from pgmpy.models import ClusterGraph >>> G = ClusterGraph() >>> G.add_nodes_from([('a', 'b', 'c'), ('a', 'b'), ('a', 'c')]) >>> G.add_edges_from([(('a', 'b', 'c'), ('a', 'b')), ... (('a', 'b', 'c'), ('a', 'c'))]) """ set_u = set(u) set_v = set(v) if set_u.isdisjoint(set_v): raise ValueError("No sepset found between these two edges.") super(ClusterGraph, self).add_edge(u, v) def add_factors(self, *factors): """ Associate a factor to the graph. See factors class for the order of potential values Parameters ---------- *factor: pgmpy.factors.factors object A factor object on any subset of the variables of the model which is to be associated with the model. Returns ------- None Examples -------- >>> from pgmpy.models import ClusterGraph >>> from pgmpy.factors.discrete import DiscreteFactor >>> student = ClusterGraph() >>> student.add_node(('Alice', 'Bob')) >>> factor = DiscreteFactor(['Alice', 'Bob'], cardinality=[3, 2], ... values=np.random.rand(6)) >>> student.add_factors(factor) """ for factor in factors: factor_scope = set(factor.scope()) nodes = [set(node) for node in self.nodes()] if factor_scope not in nodes: raise ValueError( "Factors defined on clusters of variable not" "present in model" ) self.factors.append(factor) def get_factors(self, node=None): """ Return the factors that have been added till now to the graph. If node is not None, it would return the factor corresponding to the given node. Examples -------- >>> from pgmpy.models import ClusterGraph >>> from pgmpy.factors.discrete import DiscreteFactor >>> G = ClusterGraph() >>> G.add_nodes_from([('a', 'b', 'c'), ('a', 'b'), ('a', 'c')]) >>> G.add_edges_from([(('a', 'b', 'c'), ('a', 'b')), ... (('a', 'b', 'c'), ('a', 'c'))]) >>> phi1 = DiscreteFactor(['a', 'b', 'c'], [2, 2, 2], np.random.rand(8)) >>> phi2 = DiscreteFactor(['a', 'b'], [2, 2], np.random.rand(4)) >>> phi3 = DiscreteFactor(['a', 'c'], [2, 2], np.random.rand(4)) >>> G.add_factors(phi1, phi2, phi3) >>> G.get_factors() >>> G.get_factors(node=('a', 'b', 'c')) """ if node is None: return self.factors else: nodes = [set(n) for n in self.nodes()] if set(node) not in nodes: raise ValueError("Node not present in Cluster Graph") factors = filter(lambda x: set(x.scope()) == set(node), self.factors) return next(factors) def remove_factors(self, *factors): """ Removes the given factors from the added factors. Examples -------- >>> from pgmpy.models import ClusterGraph >>> from pgmpy.factors.discrete import DiscreteFactor >>> student = ClusterGraph() >>> factor = DiscreteFactor(['Alice', 'Bob'], cardinality=[2, 2], ... value=np.random.rand(4)) >>> student.add_factors(factor) >>> student.remove_factors(factor) """ for factor in factors: self.factors.remove(factor) def get_cardinality(self, node=None): """ Returns the cardinality of the node Parameters ---------- node: any hashable python object (optional) The node whose cardinality we want. If node is not specified returns a dictionary with the given variable as keys and their respective cardinality as values. Returns ------- int or dict : If node is specified returns the cardinality of the node. If node is not specified returns a dictionary with the given variable as keys and their respective cardinality as values. Examples -------- >>> from pgmpy.models import ClusterGraph >>> from pgmpy.factors.discrete import DiscreteFactor >>> student = ClusterGraph() >>> factor = DiscreteFactor(['Alice', 'Bob'], cardinality=[2, 2], ... values=np.random.rand(4)) >>> student.add_node(('Alice', 'Bob')) >>> student.add_factors(factor) >>> student.get_cardinality() defaultdict(<class 'int'>, {'Bob': 2, 'Alice': 2}) >>> student.get_cardinality(node='Alice') 2 """ if node: for factor in self.factors: for variable, cardinality in zip(factor.scope(), factor.cardinality): if node == variable: return cardinality else: cardinalities = defaultdict(int) for factor in self.factors: for variable, cardinality in zip(factor.scope(), factor.cardinality): cardinalities[variable] = cardinality return cardinalities def get_partition_function(self): r""" Returns the partition function for a given undirected graph. A partition function is defined as .. math:: \sum_{X}(\prod_{i=1}^{m} \phi_i) where m is the number of factors present in the graph and X are all the random variables present. Examples -------- >>> from pgmpy.models import ClusterGraph >>> from pgmpy.factors.discrete import DiscreteFactor >>> G = ClusterGraph() >>> G.add_nodes_from([('a', 'b', 'c'), ('a', 'b'), ('a', 'c')]) >>> G.add_edges_from([(('a', 'b', 'c'), ('a', 'b')), ... (('a', 'b', 'c'), ('a', 'c'))]) >>> phi1 = DiscreteFactor(['a', 'b', 'c'], [2, 2, 2], np.random.rand(8)) >>> phi2 = DiscreteFactor(['a', 'b'], [2, 2], np.random.rand(4)) >>> phi3 = DiscreteFactor(['a', 'c'], [2, 2], np.random.rand(4)) >>> G.add_factors(phi1, phi2, phi3) >>> G.get_partition_function() """ if self.check_model(): factor = self.factors[0] factor = factor_product( factor, *[self.factors[i] for i in range(1, len(self.factors))] ) return np.sum(factor.values) def check_model(self): """ Check the model for various errors. This method checks for the following errors. * Checks if factors are defined for all the cliques or not. * Check for running intersection property is not done explicitly over here as it done in the add_edges method. * Checks if cardinality information for all the variables is availble or not. If not it raises an error. * Check if cardinality of random variable remains same across all the factors. Returns ------- check: boolean True if all the checks are passed """ for clique in self.nodes(): factors = filter(lambda x: set(x.scope()) == set(clique), self.factors) if not any(factors): raise ValueError("Factors for all the cliques or clusters not defined.") cardinalities = self.get_cardinality() if len(set((x for clique in self.nodes() for x in clique))) != len( cardinalities ): raise ValueError("Factors for all the variables not defined.") for factor in self.factors: for variable, cardinality in zip(factor.scope(), factor.cardinality): if cardinalities[variable] != cardinality: raise ValueError( "Cardinality of variable {var} not matching among factors".format( var=variable ) ) return True def copy(self): """ Returns a copy of ClusterGraph. Returns ------- ClusterGraph: copy of ClusterGraph Examples -------- >>> from pgmpy.factors.discrete import DiscreteFactor >>> G = ClusterGraph() >>> G.add_nodes_from([('a', 'b'), ('b', 'c')]) >>> G.add_edge(('a', 'b'), ('b', 'c')) >>> phi1 = DiscreteFactor(['a', 'b'], [2, 2], np.random.rand(4)) >>> phi2 = DiscreteFactor(['b', 'c'], [2, 2], np.random.rand(4)) >>> G.add_factors(phi1, phi2) >>> graph_copy = G.copy() >>> graph_copy.factors [<DiscreteFactor representing phi(a:2, b:2) at 0xb71b19cc>, <DiscreteFactor representing phi(b:2, c:2) at 0xb4eaf3ac>] >>> graph_copy.edges() [(('a', 'b'), ('b', 'c'))] >>> graph_copy.nodes() [('a', 'b'), ('b', 'c')] """ copy = ClusterGraph(self.edges()) if self.factors: factors_copy = [factor.copy() for factor in self.factors] copy.add_factors(*factors_copy) return copy

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0

ed48aebeb275b2b66a2ca1e46510e44f4c833499

1,474

py

Python

plugins/commands_window/plugin.py

stonewell/eim

50fc4bb6e265ed8a5eb84577fd203e83934d55a7

[ "MIT" ]

null

plugins/commands_window/plugin.py

stonewell/eim

50fc4bb6e265ed8a5eb84577fd203e83934d55a7

[ "MIT" ]

null

plugins/commands_window/plugin.py

stonewell/eim

50fc4bb6e265ed8a5eb84577fd203e83934d55a7

[ "MIT" ]

null

from PySide6.QtWidgets import QListWidgetItem from yapsy.IPlugin import IPlugin class Plugin(IPlugin): def __init__(self): IPlugin.__init__(self) def activate(self): IPlugin.activate(self) return def deactivate(self): IPlugin.deactivate(self) def set_current_window(self, editor): self.editor_ = editor self.ctx.register_command('commands_list', self.show_commands_window, None, False) self.ctx.bind_key('Alt+X', 'commands_list') def show_commands_window(self, ctx): self.commands_ = ctx.get_commands() self.content_window_ = cw = ctx.create_list_content_window() self.list_widget_ = l = cw.list_widget_ self.text_edit_ = t = cw.text_edit_ self.list_items_ = [] f_c = self.ctx.get_theme_def_color('default', 'foreground') b_c = self.ctx.get_theme_def_color('default', 'background') for cmd in self.commands_: item = QListWidgetItem(cmd, l) item.setForeground(f_c) item.setBackground(b_c) self.list_items_.append(item) t.returnPressed.connect(self.execute_command) l.itemDoubleClicked[QListWidgetItem].connect(self.execute_command) self.content_window_.select_first_visible_item() cw.show() def execute_command(self): self.item_double_clicked(self.list_widget_.currentItem()) def item_double_clicked(self, item): self.ctx.run_command(item.text())

25.859649

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0.683853

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1,474

5.075269

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0.044492

0.038136

0.023305

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0

0.000862

0.213026

1,474

56

81

26.321429

0.812931

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0

1

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false

0

0.055556

0

0.305556

0

null

0

null

0

1

0

ed493a7b9c217715b159a3e6f8cf67b68a3aa7f3

478

py

Python

custom_components/helpers.py

zroger49/broadlink_custom_component

c7b0f9648f1dbaad64e573561e852b689be5a755

[ "MIT" ]

null

custom_components/helpers.py

zroger49/broadlink_custom_component

c7b0f9648f1dbaad64e573561e852b689be5a755

[ "MIT" ]

2

2022-01-30T15:29:17.000Z

2022-03-13T10:54:58.000Z

custom_components/helpers.py

racelandshop/broadlink_custom_component

c7b0f9648f1dbaad64e573561e852b689be5a755

[ "MIT" ]

1

2022-01-16T16:05:24.000Z

"""Helpers for the Broadlink remote.""" from base64 import b64decode from homeassistant.helpers import config_validation as cv def decode_packet(value): """Decode a data packet given for a Broadlink remote.""" value = cv.string(value) extra = len(value) % 4 if extra > 0: value = value + ("=" * (4 - extra)) return b64decode(value) def format_mac(mac): """Format a MAC address.""" return ":".join([format(octet, "02x") for octet in mac])

26.555556

60

0.65272

65

478

4.753846

0.538462

0.097087

0

0.029255

0.213389

478

17

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0.6

0

null

0

null

0

1

0

ed49cff59f1ab26e4ca17666763624af983410cc

8,641

py

Python

examples/pybullet/gym/pybullet_envs/bullet/kukaCamGymEnv.py

motionfigures/bullet3

4a66d6c80b38a87ecbdf2fd5c4d281f0b5913d22

[ "Zlib" ]

51

2018-11-11T12:47:38.000Z

2022-03-06T08:39:43.000Z

examples/pybullet/gym/pybullet_envs/bullet/kukaCamGymEnv.py

motionfigures/bullet3

4a66d6c80b38a87ecbdf2fd5c4d281f0b5913d22

[ "Zlib" ]

2

2019-11-15T03:21:45.000Z

2020-09-10T11:53:58.000Z

examples/pybullet/gym/pybullet_envs/bullet/kukaCamGymEnv.py

motionfigures/bullet3

4a66d6c80b38a87ecbdf2fd5c4d281f0b5913d22

[ "Zlib" ]

14

2018-12-12T09:12:14.000Z

2021-10-17T14:30:25.000Z

import os, inspect currentdir = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe()))) parentdir = os.path.dirname(os.path.dirname(currentdir)) os.sys.path.insert(0,parentdir) import math import gym from gym import spaces from gym.utils import seeding import numpy as np import time import pybullet as p from . import kuka import random import pybullet_data from pkg_resources import parse_version maxSteps = 1000 RENDER_HEIGHT = 720 RENDER_WIDTH = 960 class KukaCamGymEnv(gym.Env): metadata = { 'render.modes': ['human', 'rgb_array'], 'video.frames_per_second' : 50 } def __init__(self, urdfRoot=pybullet_data.getDataPath(), actionRepeat=1, isEnableSelfCollision=True, renders=False, isDiscrete=False): self._timeStep = 1./240. self._urdfRoot = urdfRoot self._actionRepeat = actionRepeat self._isEnableSelfCollision = isEnableSelfCollision self._observation = [] self._envStepCounter = 0 self._renders = renders self._width = 341 self._height = 256 self._isDiscrete=isDiscrete self.terminated = 0 self._p = p if self._renders: cid = p.connect(p.SHARED_MEMORY) if (cid<0): p.connect(p.GUI) p.resetDebugVisualizerCamera(1.3,180,-41,[0.52,-0.2,-0.33]) else: p.connect(p.DIRECT) #timinglog = p.startStateLogging(p.STATE_LOGGING_PROFILE_TIMINGS, "kukaTimings.json") self._seed() self.reset() observationDim = len(self.getExtendedObservation()) #print("observationDim") #print(observationDim) observation_high = np.array([np.finfo(np.float32).max] * observationDim) if (self._isDiscrete): self.action_space = spaces.Discrete(7) else: action_dim = 3 self._action_bound = 1 action_high = np.array([self._action_bound] * action_dim) self.action_space = spaces.Box(-action_high, action_high) self.observation_space = spaces.Box(low=0, high=255, shape=(self._height, self._width, 4)) self.viewer = None def _reset(self): self.terminated = 0 p.resetSimulation() p.setPhysicsEngineParameter(numSolverIterations=150) p.setTimeStep(self._timeStep) p.loadURDF(os.path.join(self._urdfRoot,"plane.urdf"),[0,0,-1]) p.loadURDF(os.path.join(self._urdfRoot,"table/table.urdf"), 0.5000000,0.00000,-.820000,0.000000,0.000000,0.0,1.0) xpos = 0.5 +0.2*random.random() ypos = 0 +0.25*random.random() ang = 3.1415925438*random.random() orn = p.getQuaternionFromEuler([0,0,ang]) self.blockUid =p.loadURDF(os.path.join(self._urdfRoot,"block.urdf"), xpos,ypos,-0.1,orn[0],orn[1],orn[2],orn[3]) p.setGravity(0,0,-10) self._kuka = kuka.Kuka(urdfRootPath=self._urdfRoot, timeStep=self._timeStep) self._envStepCounter = 0 p.stepSimulation() self._observation = self.getExtendedObservation() return np.array(self._observation) def __del__(self): p.disconnect() def _seed(self, seed=None): self.np_random, seed = seeding.np_random(seed) return [seed] def getExtendedObservation(self): #camEyePos = [0.03,0.236,0.54] #distance = 1.06 #pitch=-56 #yaw = 258 #roll=0 #upAxisIndex = 2 #camInfo = p.getDebugVisualizerCamera() #print("width,height") #print(camInfo[0]) #print(camInfo[1]) #print("viewMatrix") #print(camInfo[2]) #print("projectionMatrix") #print(camInfo[3]) #viewMat = camInfo[2] #viewMat = p.computeViewMatrixFromYawPitchRoll(camEyePos,distance,yaw, pitch,roll,upAxisIndex) viewMat = [-0.5120397806167603, 0.7171027660369873, -0.47284144163131714, 0.0, -0.8589617609977722, -0.42747554183006287, 0.28186774253845215, 0.0, 0.0, 0.5504802465438843, 0.8348482847213745, 0.0, 0.1925382763147354, -0.24935829639434814, -0.4401884973049164, 1.0] #projMatrix = camInfo[3]#[0.7499999403953552, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, -1.0000200271606445, -1.0, 0.0, 0.0, -0.02000020071864128, 0.0] projMatrix = [0.75, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, -1.0000200271606445, -1.0, 0.0, 0.0, -0.02000020071864128, 0.0] img_arr = p.getCameraImage(width=self._width,height=self._height,viewMatrix=viewMat,projectionMatrix=projMatrix) rgb=img_arr[2] np_img_arr = np.reshape(rgb, (self._height, self._width, 4)) self._observation = np_img_arr return self._observation def _step(self, action): if (self._isDiscrete): dv = 0.01 dx = [0,-dv,dv,0,0,0,0][action] dy = [0,0,0,-dv,dv,0,0][action] da = [0,0,0,0,0,-0.1,0.1][action] f = 0.3 realAction = [dx,dy,-0.002,da,f] else: dv = 0.01 dx = action[0] * dv dy = action[1] * dv da = action[2] * 0.1 f = 0.3 realAction = [dx,dy,-0.002,da,f] return self.step2( realAction) def step2(self, action): for i in range(self._actionRepeat): self._kuka.applyAction(action) p.stepSimulation() if self._termination(): break #self._observation = self.getExtendedObservation() self._envStepCounter += 1 self._observation = self.getExtendedObservation() if self._renders: time.sleep(self._timeStep) #print("self._envStepCounter") #print(self._envStepCounter) done = self._termination() reward = self._reward() #print("len=%r" % len(self._observation)) return np.array(self._observation), reward, done, {} def _render(self, mode='human', close=False): if mode != "rgb_array": return np.array([]) base_pos,orn = self._p.getBasePositionAndOrientation(self._racecar.racecarUniqueId) view_matrix = self._p.computeViewMatrixFromYawPitchRoll( cameraTargetPosition=base_pos, distance=self._cam_dist, yaw=self._cam_yaw, pitch=self._cam_pitch, roll=0, upAxisIndex=2) proj_matrix = self._p.computeProjectionMatrixFOV( fov=60, aspect=float(RENDER_WIDTH)/RENDER_HEIGHT, nearVal=0.1, farVal=100.0) (_, _, px, _, _) = self._p.getCameraImage( width=RENDER_WIDTH, height=RENDER_HEIGHT, viewMatrix=view_matrix, projectionMatrix=proj_matrix, renderer=pybullet.ER_BULLET_HARDWARE_OPENGL) rgb_array = np.array(px) rgb_array = rgb_array[:, :, :3] return rgb_array def _termination(self): #print (self._kuka.endEffectorPos[2]) state = p.getLinkState(self._kuka.kukaUid,self._kuka.kukaEndEffectorIndex) actualEndEffectorPos = state[0] #print("self._envStepCounter") #print(self._envStepCounter) if (self.terminated or self._envStepCounter>maxSteps): self._observation = self.getExtendedObservation() return True maxDist = 0.005 closestPoints = p.getClosestPoints(self._kuka.trayUid, self._kuka.kukaUid,maxDist) if (len(closestPoints)):#(actualEndEffectorPos[2] <= -0.43): self.terminated = 1 #print("closing gripper, attempting grasp") #start grasp and terminate fingerAngle = 0.3 for i in range (100): graspAction = [0,0,0.0001,0,fingerAngle] self._kuka.applyAction(graspAction) p.stepSimulation() fingerAngle = fingerAngle-(0.3/100.) if (fingerAngle<0): fingerAngle=0 for i in range (1000): graspAction = [0,0,0.001,0,fingerAngle] self._kuka.applyAction(graspAction) p.stepSimulation() blockPos,blockOrn=p.getBasePositionAndOrientation(self.blockUid) if (blockPos[2] > 0.23): #print("BLOCKPOS!") #print(blockPos[2]) break state = p.getLinkState(self._kuka.kukaUid,self._kuka.kukaEndEffectorIndex) actualEndEffectorPos = state[0] if (actualEndEffectorPos[2]>0.5): break self._observation = self.getExtendedObservation() return True return False def _reward(self): #rewards is height of target object blockPos,blockOrn=p.getBasePositionAndOrientation(self.blockUid) closestPoints = p.getClosestPoints(self.blockUid,self._kuka.kukaUid,1000, -1, self._kuka.kukaEndEffectorIndex) reward = -1000 numPt = len(closestPoints) #print(numPt) if (numPt>0): #print("reward:") reward = -closestPoints[0][8]*10 if (blockPos[2] >0.2): #print("grasped a block!!!") #print("self._envStepCounter") #print(self._envStepCounter) reward = reward+1000 #print("reward") #print(reward) return reward if parse_version(gym.__version__)>=parse_version('0.9.6'): render = _render reset = _reset seed = _seed step = _step

32.731061

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8,641

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0.18617

0

null

0

null

0

1

0

ed4a2840446404d2f282a8452d7b98f961fd5554

6,392

py

Python

hi-ml-histopathology/src/histopathology/preprocessing/tiling.py

kumar-pratik/hi-ml

a108cf4ea244a76127adedc0ca60f0a5afdfb3e8

[ "MIT" ]

402

2020-09-22T16:38:16.000Z

2022-03-30T09:56:03.000Z

hi-ml-histopathology/src/histopathology/preprocessing/tiling.py

kumar-pratik/hi-ml

a108cf4ea244a76127adedc0ca60f0a5afdfb3e8

[ "MIT" ]

259

2020-09-23T09:32:33.000Z

2022-03-30T18:15:01.000Z

hi-ml-histopathology/src/histopathology/preprocessing/tiling.py

kumar-pratik/hi-ml

a108cf4ea244a76127adedc0ca60f0a5afdfb3e8

[ "MIT" ]

112

2020-09-23T00:12:58.000Z

2022-03-31T07:39:55.000Z

# ------------------------------------------------------------------------------------------ # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License (MIT). See LICENSE in the repo root for license information. # ------------------------------------------------------------------------------------------ # These tiling implementations are adapted from PANDA Kaggle solutions, for example: # https://github.com/kentaroy47/Kaggle-PANDA-1st-place-solution/blob/master/src/data_process/a00_save_tiles.py from typing import Any, Optional, Tuple import numpy as np def get_1d_padding(length: int, tile_size: int) -> Tuple[int, int]: """Computes symmetric padding for `length` to be divisible by `tile_size`.""" pad = (tile_size - length % tile_size) % tile_size return (pad // 2, pad - pad // 2) def pad_for_tiling_2d(array: np.ndarray, tile_size: int, channels_first: Optional[bool] = True, **pad_kwargs: Any) -> Tuple[np.ndarray, np.ndarray]: """Symmetrically pads a 2D `array` such that both dimensions are divisible by `tile_size`. :param array: 2D image array. :param tile_size: Width/height of each tile in pixels. :param channels_first: Whether `array` is in CHW (`True`, default) or HWC (`False`) layout. :param pad_kwargs: Keyword arguments to be passed to `np.pad()` (e.g. `constant_values=0`). :return: A tuple containing: - `padded_array`: Resulting array, in the same CHW/HWC layout as the input. - `offset`: XY offset introduced by the padding. Add this to coordinates relative to the original array to obtain indices for the padded array. """ height, width = array.shape[1:] if channels_first else array.shape[:-1] padding_h = get_1d_padding(height, tile_size) padding_w = get_1d_padding(width, tile_size) padding = [padding_h, padding_w] channels_axis = 0 if channels_first else 2 padding.insert(channels_axis, (0, 0)) # zero padding on channels axis padded_array = np.pad(array, padding, **pad_kwargs) offset = (padding_w[0], padding_h[0]) return padded_array, np.array(offset) def tile_array_2d(array: np.ndarray, tile_size: int, channels_first: Optional[bool] = True, **pad_kwargs: Any) -> Tuple[np.ndarray, np.ndarray]: """Split an image array into square non-overlapping tiles. The array will be padded symmetrically if its dimensions are not exact multiples of `tile_size`. :param array: Image array. :param tile_size: Width/height of each tile in pixels. :param pad_kwargs: Keyword arguments to be passed to `np.pad()` (e.g. `constant_values=0`). :param channels_first: Whether `array` is in CHW (`True`, default) or HWC (`False`) layout. :return: A tuple containing: - `tiles`: A batch of tiles in NCHW layout. - `coords`: XY coordinates of each tile, in the same order. """ padded_array, (offset_w, offset_h) = pad_for_tiling_2d(array, tile_size, channels_first, **pad_kwargs) if channels_first: channels, height, width = padded_array.shape else: height, width, channels = padded_array.shape n_tiles_h = height // tile_size n_tiles_w = width // tile_size if channels_first: intermediate_shape = (channels, n_tiles_h, tile_size, n_tiles_w, tile_size) axis_order = (1, 3, 0, 2, 4) # (n_tiles_h, n_tiles_w, channels, tile_size, tile_size) output_shape = (n_tiles_h * n_tiles_w, channels, tile_size, tile_size) else: intermediate_shape = (n_tiles_h, tile_size, n_tiles_w, tile_size, channels) axis_order = (0, 2, 1, 3, 4) # (n_tiles_h, n_tiles_w, tile_size, tile_size, channels) output_shape = (n_tiles_h * n_tiles_w, tile_size, tile_size, channels) tiles = padded_array.reshape(intermediate_shape) # Split width and height axes tiles = tiles.transpose(axis_order) tiles = tiles.reshape(output_shape) # Flatten tile batch dimension # Compute top-left coordinates of every tile, relative to the original array's origin coords_h = tile_size * np.arange(n_tiles_h) - offset_h coords_w = tile_size * np.arange(n_tiles_w) - offset_w # Shape: (n_tiles_h * n_tiles_w, 2) coords = np.stack(np.meshgrid(coords_w, coords_h), axis=-1).reshape(-1, 2) return tiles, coords def assemble_tiles_2d(tiles: np.ndarray, coords: np.ndarray, fill_value: Optional[float] = np.nan, channels_first: Optional[bool] = True) -> Tuple[np.ndarray, np.ndarray]: """Assembles a 2D array from sequences of tiles and coordinates. :param tiles: Stack of tiles with batch dimension first. :param coords: XY tile coordinates, assumed to be spaced by multiples of `tile_size` (shape: [N, 2]). :param tile_size: Size of each tile; must be >0. :param fill_value: Value to assign to empty elements (default: `NaN`). :param channels_first: Whether each tile is in CHW (`True`, default) or HWC (`False`) layout. :return: A tuple containing: - `array`: The reassembled 2D array with the smallest dimensions to contain all given tiles. - `offset`: The lowest XY coordinates. - `offset`: XY offset introduced by the assembly. Add this to tile coordinates to obtain indices for the assembled array. """ if coords.shape[0] != tiles.shape[0]: raise ValueError(f"Tile coordinates and values must have the same length, " f"got {coords.shape[0]} and {tiles.shape[0]}") if channels_first: n_tiles, channels, tile_size, _ = tiles.shape else: n_tiles, tile_size, _, channels = tiles.shape tile_xs, tile_ys = coords.T x_min, x_max = min(tile_xs), max(tile_xs + tile_size) y_min, y_max = min(tile_ys), max(tile_ys + tile_size) width = x_max - x_min height = y_max - y_min output_shape = (channels, height, width) if channels_first else (height, width, channels) array = np.full(output_shape, fill_value) offset = np.array([-x_min, -y_min]) for idx in range(n_tiles): row = coords[idx, 1] + offset[1] col = coords[idx, 0] + offset[0] if channels_first: array[:, row:row + tile_size, col:col + tile_size] = tiles[idx] else: array[row:row + tile_size, col:col + tile_size, :] = tiles[idx] return array, offset

49.550388

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4.35914

0.22043

0.078934

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0.019734

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6,392

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0.153846

0

null

0

null

0

1

0

ed4a5900145229cd2e22ae9792f8a8881bfd83d3

9,697

py

Python

miniapp/miniapp/hartreefock/hf.py

savcardamone/tyche-

ea89edea89a607291e4fe0ba738d75522f54dc1a

[ "MIT" ]

null

miniapp/miniapp/hartreefock/hf.py

savcardamone/tyche-

ea89edea89a607291e4fe0ba738d75522f54dc1a

[ "MIT" ]

1

2018-12-28T13:30:16.000Z

2018-12-29T10:30:33.000Z

miniapp/miniapp/hartreefock/hf.py

savcardamone/tyche

ea89edea89a607291e4fe0ba738d75522f54dc1a

[ "MIT" ]

null

from math import pi from numpy import array, ndarray, divide, sqrt, argsort, sort, diag, trace from numpy.linalg import eig, norm class HartreeFock(): zeta = array([38.474970, 5.782948, 1.242567, 0.298073]) num_aos = len(zeta) num_mos = 0 energy_tolerance = 0.0001; density_tolerance = 0.001 prev_energy = 0 prev_density = [] def __init__(self, num_elec): # Make sure we can pair electrons if num_elec % 2 != 0: raise Exception("Can't do a RHF with", num_elec, "electrons.") else: print("Restricted Hartree-Fock with", num_elec, "electron(s).") # We're RHF, so pair up spins in each molecular orbital self.num_mos = int(num_elec / 2) if self.num_mos > self.num_aos: raise Exception("Can't create", self.num_mos, "molecular orbital(s) from", self.num_aos, "atomic orbital(s).") else: print(self.num_aos, "atomic orbital(s) and", self.num_mos, "molecular orbital(s).") print("Zeta: ", self.zeta) self.prev_density = ndarray(shape=(self.num_aos,self.num_aos),dtype=float, order='C') def one_electron_integrals(self): def overlap_kernel(zeta_i, zeta_j): return pow(pi / (zeta_i + zeta_j), 1.5) def kinetic_kernel(zeta_i, zeta_j): return 3 * pow(pi, 1.5) * (zeta_i * zeta_j) / pow(zeta_i + zeta_j, 2.5) def nucattr_kernel(zeta_i, zeta_j): return (-4 * pi) / (zeta_i + zeta_j) # Initialise our matrices overlap = ndarray(shape=(self.num_aos,self.num_aos), dtype=float, order='C') kinetic = ndarray(shape=(self.num_aos,self.num_aos), dtype=float, order='C') nucattr = ndarray(shape=(self.num_aos,self.num_aos), dtype=float, order='C') for i_ao in range(self.num_aos): for j_ao in range(self.num_aos): overlap[i_ao,j_ao] = overlap_kernel(self.zeta[i_ao], self.zeta[j_ao]) kinetic[i_ao,j_ao] = kinetic_kernel(self.zeta[i_ao], self.zeta[j_ao]) nucattr[i_ao,j_ao] = nucattr_kernel(self.zeta[i_ao], self.zeta[j_ao]) return overlap, kinetic, nucattr def two_electron_integrals(self): def tei_kernel(zeta_i, zeta_j, zeta_k, zeta_l): temp_1 = (zeta_i + zeta_j) * (zeta_k + zeta_l) temp_2 = sqrt(zeta_i + zeta_j + zeta_k + zeta_l) return 2 * pow(pi, 2.5) / (temp_1 * temp_2) teis = ndarray(shape=(self.num_aos,self.num_aos,self.num_aos,self.num_aos), dtype=float, order='C') for i_ao in range(self.num_aos): for j_ao in range(self.num_aos): for k_ao in range(self.num_aos): for l_ao in range(self.num_aos): teis[i_ao,j_ao,k_ao,l_ao] = tei_kernel(self.zeta[i_ao], self.zeta[j_ao], self.zeta[k_ao], self.zeta[l_ao]) return teis def basis_transformation_matrix(self, overlap): # Get the eigenvalues and eigenvectors of the overlap matrix overlap_evals, overlap_evecs = eig(overlap) # Create diagonal matrix with entries given by inverse of eigenvalues of # overlap matrix try: inv_sqrt_evals = diag(divide(1., sqrt(overlap_evals))) except: raise Exception("Overlap matrix is not positive definite.") # Construct the basis transformation matrix and return it return overlap_evecs @ inv_sqrt_evals @ overlap_evecs.T def fock_matrix(self, core_hamiltonian, teis, density): fock = ndarray(shape=density.shape, dtype=float, order='C') for i_ao in range(self.num_aos): for j_ao in range(self.num_aos): fock[i_ao,j_ao] = core_hamiltonian[i_ao,j_ao] for k_ao in range(self.num_aos): for l_ao in range(self.num_aos): coulomb = teis[i_ao,k_ao,j_ao,l_ao] exchange = teis[i_ao,k_ao,l_ao,j_ao] fock[i_ao,j_ao] += density[k_ao,l_ao] * (coulomb - 0.5*exchange) return fock def density_matrix(self, overlap, basis_transform, fock): def ordered_eigensystem(matrix): # Generate the eigenvalues and eigenvectors of the matrix evals, evecs = eig(matrix) # Sort the eigenvalues in ascending order and keep a track of what index they # were originally assigned ordered_indices = argsort(evals) ordered_evals = sort(evals) # Order the eigenvectors in asceding order of their corresponding eigenvalues ordered_evecs = ndarray(shape=evecs.shape, dtype=float, order='C') ordered_transform = ndarray(shape=evecs.shape, dtype=float, order='C') for i_evec in range(len(ordered_evals)): ordered_evecs[:,i_evec] = evecs[:,ordered_indices[i_evec]] ordered_transform[i_evec,:] = basis_transform[ordered_indices[i_evec],:] # Return the ordered eigenvalues and corresponding eigenvectors return ordered_evals, ordered_evecs, ordered_transform # Transform Fock matrix to orthogonal basis fock = basis_transform.T @ fock @ basis_transform # Get the eigenvalues and eigenvectors of the input Fock matrix fock_evals, fock_evecs, new_transform = ordered_eigensystem(fock) # Transform the eigenvectors of the Fock matrix back to the original basis fock_evecs = new_transform @ fock_evecs # First of all we make sure the eigenvectors of the Fock matrix are normalised by the # overlap matrix (these are molecular orbitals, afterall) for i_mo in range(self.num_aos): ao_coeffs = fock_evecs[:,i_mo] norm = ao_coeffs.T @ overlap @ ao_coeffs fock_evecs[:,i_mo] /= sqrt(norm) # Initialise the density matrix density = ndarray(shape=overlap.shape, dtype=float, order='C') # Loop over all elements in the density matrix and accumulate for i_ao in range(self.num_aos): for j_ao in range(self.num_aos): density[i_ao,j_ao] = 0.0 # We accumulate only over occupied molecular orbitals! Note that we also have # access to the virtual orbitals at this point, but they're effectively discarded for i_mo in range(self.num_mos): density[i_ao,j_ao] += 2 * fock_evecs[i_ao,i_mo] * fock_evecs[j_ao,i_mo] return fock_evecs, density def scf_energy(self, density, core_hamiltonian, fock): energy = 0.0 for i_ao in range(self.num_aos): for j_ao in range(self.num_aos): energy += 0.5 * density[i_ao,j_ao] * (core_hamiltonian[i_ao,j_ao] + fock[i_ao,j_ao]) return energy def check_convergence(self, energy, density): if abs(energy - self.prev_energy) < self.energy_tolerance: energy_converged = True else: energy_converged = False self.prev_energy = energy if norm(density - self.prev_density) < self.density_tolerance: density_converged = True else: density_converged = False self.prev_density = density return energy_converged, density_converged def mulliken(self, overlap, density): return trace(density @ overlap) def run(self, num_cycles): print("Hartree-Fock will run for a maximum of", num_cycles, "SCF iteration(s).") overlap, kinetic, nucattr = self.one_electron_integrals() core_hamiltonian = kinetic + nucattr teis = self.two_electron_integrals() basis_transform = self.basis_transformation_matrix(overlap) _, density = self.density_matrix(overlap, basis_transform, core_hamiltonian) energy = self.scf_energy(density, core_hamiltonian, core_hamiltonian) for i in range(num_cycles): fock = self.fock_matrix(core_hamiltonian, teis, density) fock_evecs, density = self.density_matrix(overlap, basis_transform, fock) energy = self.scf_energy(density, core_hamiltonian, fock) print("Iteration", i, "SCF Energy:", energy) energy_converged, density_converged = self.check_convergence(energy, density) if energy_converged and density_converged: print("SCF has converged!") for i_mo in range(self.num_mos): print("Molecular Orbital", i_mo, "Coefficients :", fock_evecs[:,i_mo]) print("Mulliken charge:", self.mulliken(overlap, density)) break if i == num_cycles - 1: print("SCF failed to converge.") print("Energy Convergence Check:", energy_converged) print("Density Convergence Check:", density_converged) fock_mo_basis = ndarray(shape=(self.num_mos,self.num_mos), dtype=float, order='C') for i_mo in range(self.num_mos): for j_mo in range(self.num_mos): fock_mo_basis[i_mo,j_mo] = 0.0 for i_ao in range(self.num_aos): for j_ao in range(self.num_aos): fock_mo_basis[i_mo,j_mo] += fock_evecs[i_ao,j_mo] * fock_evecs[j_ao,i_mo] * fock[i_ao,j_ao] print(fock_mo_basis) if __name__ == "__main__": hf = HartreeFock(4) hf.run(2000)

39.579592

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0.05265

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0.299165

9,697

245

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39.579592

0.810477

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false

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null

0

null

0

1

0

ed4d3cea76d6d1815b54c52a975d47ddfb5f8c99

7,496

py

Python

server/djangoapp/restapis.py

christiansencq/ibm_capstone

d445fd40c0267be0948a5d85e9d43828b908641c

[ "Apache-2.0" ]

null

server/djangoapp/restapis.py

christiansencq/ibm_capstone

d445fd40c0267be0948a5d85e9d43828b908641c

[ "Apache-2.0" ]

null

server/djangoapp/restapis.py

christiansencq/ibm_capstone

d445fd40c0267be0948a5d85e9d43828b908641c

[ "Apache-2.0" ]

null

import requests import json # import related models here from .models import CarDealer, DealerReview from requests.auth import HTTPBasicAuth import logging logger = logging.getLogger(__name__) # Create a `get_request` to make HTTP GET requests # e.g., response = requests.get(url, params=params, headers={'Content-Type': 'application/json'}, # auth=HTTPBasicAuth('apikey', api_key)) def get_request(url, api_key, **kwargs): print("GET from {}".format(url)) print(kwargs) try: if api_key is not None: response = requests.get(url, headers={'Content-Type': 'application/json'}, params=kwargs, auth=HTTPBasicAuth('apikey', api_key)) else: response = requests.get(url, headers={'Content-Type': 'application/json'}, params=kwargs) except: print("Network Error") status_code = response.status_code print("With status code {}".format(status_code)) json_data = json.loads(response.text) return json_data, status_code # Create a `post_request` to make HTTP POST requests # e.g., response = requests.post(url, params=kwargs, json=payload) def post_request(url, json_payload, **kwargs): print("Post to url: {} ".format(url)) print(kwargs) print(json_payload) response = requests.post(url, headers={'Content-Type': 'application/json'}, params=kwargs, json=json_payload) status_code = response.status_code print("With status code {}".format(status_code)) json_data = json.loads(response.text) return json_data, status_code # Create a get_dealers_from_cf method to get dealers from a cloud function def get_dealers_from_cf(url, **kwargs): info = [] result = "ok" # - Call get_request() with specified arguments logger.info("Get Dealers from CF Called!") json_result, status_code = get_request(url, None) if status_code == 200 and json_result: dealers = json_result['rows'] logger.info(len(dealers)) for dealer in dealers: dlr_data = dealer['doc'] #print('ADDRESS', dlr_data["address"]) if dlr_data.get('address'): # Create a CarDealer object with values in `doc` object dealer_obj = CarDealer(address=dlr_data.get("address"), city=dlr_data.get("city"), full_name=dlr_data.get("full_name"), id=dlr_data.get("id"), lat=dlr_data.get("lat"), long=dlr_data.get("long"), short_name=dlr_data.get("short_name"), state=dlr_data.get("state"), st=dlr_data.get("st"), zip=dlr_data.get("zip")) # dealer_obj = CarDealer(address=dealer["doc"]["address"], city=dealer["doc"]["city"], full_name=dealer["doc"]["full_name"], # id=dealer["doc"]["id"], lat=dealer["doc"]["lat"], long=dealer["doc"]["long"], # short_name=dealer["doc"]["short_name"], # st=dealer["doc"]["st"], state=dealer["doc"]["state"], zip=dealer["doc"]["zip"]) info.append(dealer_obj) elif json_result: result = json_result["message"] else: result = "Unknown error" return info, result def get_dealer_by_id(url, dealerId): # Call get_request with a URL parameter info = None result = "ok" json_result, status_code = get_request(url, None, dealerId=dealerId) # json_result, status_code = get_request(url, None, dealerId=dealerId) if status_code == 200 and json_result: # Get the row list in JSON as dealers dealers = json_result["rows"] for dealer in dealers: # Create a CarDealer object with values in `doc` object info = CarDealer(address=dealer.get("address"), city=dealer.get("city"), full_name=dealer.get("full_name"), id=dealer.get("id"), lat=dealer.get("lat"), long=dealer.get("long"), short_name=dealer.get("short_name"), st=dealer.get("st"), state=dealer.get("state"), zip=dealer.get("zip")) # info = CarDealer(address=dealer["address"], city=dealer["city"], full_name=dealer["full_name"], # id=dealer["id"], lat=dealer["lat"], long=dealer["long"], # short_name=dealer["short_name"], state=dealer["state"], # st=dealer["st"], zip=dealer["zip"]) elif json_result: result = json_result["message"] else: result = "Unknown error" return info, result def get_dealers_by_state (url, state): info = [] result = "ok" # Call get_request with a URL parameter json_result, status_code = get_request(url, None, state=state) if status_code == 200 and json_result: # Get the row list in JSON as dealers dealers = json_result["rows"] # For each dealer object for dealer in dealers: # dlr_data = dealer["doc"] # Create a CarDealer object with values in `doc` object dealer_obj = CarDealer(address=dealer.get("address"), city=dealer.get("city"), full_name=dealer.get("full_name"), id=dealer.get("id"), lat=dealer.get("lat"), long=dealer.get("long"), short_name=dealer.get("short_name"), state=dealer.get("state"), st=dealer.get("st"), zip=dealer.get("zip")) # dealer_obj = CarDealer(address=dlr_data.get("address"), city=dlr_data.get("city"), full_name=dlr_data.get("full_name"), # id=dlr_data.get("id"), lat=dlr_data.get("lat"), long=dlr_data.get("long"), # short_name=dlr_data.get("short_name"), state=dlr_data.get("state"), # st=dlr_data.get("st"), zip=dlr_data.get("zip")) info.append(dealer_obj) elif json_result: result = json_result["message"] else: result = "Unknown error" return info, result def get_dealer_reviews_from_cf (url, dealerId): info = [] result = "ok" # Call get_request with a URL parameter json_result, status_code = get_request(url, None, dealerId=dealerId) if status_code == 200 and json_result: # Get the row list in JSON as reviews reviews = json_result["body"]["data"] # For each review object for review in reviews: if (dealerId == review.get("dealership")): # Create a DealerReview object with values in object #sentiment = analyze_review_sentiments(review["review"]) review_obj = DealerReview( id=review.get("id"), name=review.get("name"), review=review.get("review"), purchase=review.get("purchase"), car_make=review.get("car_make", None), car_model=review.get("car_model", None), car_year=review.get("car_year", None), purchase_date=review.get("purchase_date", None)) info.append(review_obj) elif json_result: result = json_result["message"] else: result = "Unknown error" return info, result # Create an `analyze_review_sentiments` method to call Watson NLU and analyze text # def analyze_review_sentiments(text): # - Call get_request() with specified arguments # - Get the returned sentiment label such as Positive or Negative

46.271605

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0.603522

939

7,496

4.654952

0.13099

0.038435

0.048044

0.02059

0.58911

0.555022

0.535575

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0.48021

0.470373

0

0.00218

0.265608

7,496

161

141

46.559006

0.791826

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0

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false

0

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0.168317

0.079208

0

null

0

null

0

1

0

ed4d8f444cbb7eba10514b86dbcd28fb80cd5824

2,035

py

Python

examples/python/upload.py

oslokommune/okdata-data-uploader

fc006ae90440b267613260bba90235799bf0cf6e

[ "MIT" ]

null

examples/python/upload.py

oslokommune/okdata-data-uploader

fc006ae90440b267613260bba90235799bf0cf6e

[ "MIT" ]

null

examples/python/upload.py

oslokommune/okdata-data-uploader

fc006ae90440b267613260bba90235799bf0cf6e

[ "MIT" ]

null

import logging from configparser import ConfigParser from sdk.data_uploader import DataUploader logging.basicConfig(level=logging.INFO) log = logging.getLogger() config = ConfigParser() config.read("config.ini") ##### # Datasets to be added to metadata API datasetData = { "title": "Test", "description": "Test data", "keywords": ["test"], "accessRights": "non-public", "objective": "Formålsbeskrivelse", "contactPoint": { "name": "Tim", "email": "tim@example.org", "phone": "12345678", }, "publisher": "Tim", } datasetVersionData = {"version": "6", "schema": {}, "transformation": {}} datasetVersionEditionData = { "edition": "2019-05-28T15:37:00+02:00", "description": "Data for one hour", "startTime": "2018-12-21T08:00:00+01:00", "endTime": "2018-12-21T09:00:00+01:00", } ###### # The dataset* variables are optional, if these are set in config.ini this script will # not run the relevant DataUploader function datasetId = config.get("dataUploader", "datasetId", fallback=None) datasetVersion = config.get("dataUploader", "datasetVersion", fallback=None) datasetVersionEdition = config.get( "dataUploader", "datasetVersionEdition", fallback=None ) upload = DataUploader(config) try: log.info("Uploading a file to S3") upload.login() if datasetId is None: upload.createDataset(datasetData) if datasetVersion is None: upload.createVersion(datasetVersionData) if datasetVersionEdition is None: upload.createEdition(datasetVersionEditionData) log.info(f"Dataset: {upload.datasetId}") log.info(f"Version: {upload.datasetVersion}") log.info(f"Edition: {upload.datasetVersionEdition}") if upload.upload("README.md"): log.info("Done... go brew some coffee") else: log.error("Could not upload file....") except Exception as e: log.exception(f">> Something went horrible wrong:\n{e}") # To upload with curl: cmd = upload.curl("tmp3.zip") # Max upload size for now is 5GB

30.373134

86

0.678624

234

2,035

5.897436

0.538462

0.025362

0.045652

0.011594

0

0.039262

0.173956

2,035

66

87

30.833333

0.781678

0.121867

0

0.348588

0.084181

0

1

0

false

0

0.058824

0

0.058824

0

null

0

null

0

1

0

ed4f8a612b9b05faf17087ad729a1b5925503103

1,358

py

Python

setup.py

xmedius/xmedius-mailrelayserver

44bb55c4b543e96bb23a45499d281c1bbab18abf

[ "MIT" ]

null

setup.py

xmedius/xmedius-mailrelayserver

44bb55c4b543e96bb23a45499d281c1bbab18abf

[ "MIT" ]

null

setup.py

xmedius/xmedius-mailrelayserver

44bb55c4b543e96bb23a45499d281c1bbab18abf

[ "MIT" ]

null

from setuptools import setup from setuptools.command.install import install class PostInstallCommand(install): user_options = install.user_options + [ ('noservice', None, None), ] def initialize_options(self): install.initialize_options(self) self.noservice = None def finalize_options(self): install.finalize_options(self) def run(self): install.run(self) if not self.noservice: from xmediusmailrelayserver import console console.install_service(['--startup', 'auto', 'install']) setup( name='xmediusmailrelayserver', version='1.0.0', description='The Python module to be used to relay mail to different servers depending on patterns', long_description='See https://github.com/xmedius/xmedius-mailrelayserver for more information', url='https://github.com/xmedius/xmedius-mailrelayserver/', author='XMedius R&D', license='MIT', classifiers=[ 'Programming Language :: Python :: 3.6', 'Environment :: Win32 (MS Windows)', 'Operating System :: Microsoft :: Windows' ], cmdclass={ 'install': PostInstallCommand }, packages=['xmediusmailrelayserver'], package_data={'xmediusmailrelayserver': ['config.yml']}, install_requires=['pyyaml', 'aiosmtpd'], dependency_links=[] )

30.863636

104

0.667158

138

1,358

6.485507

0.586957

0.049162

0.040223

0.046927

0.096089

0

0.006542

0.212077

1,358

43

105

31.581395

0.829907

0

0.343405

0.048637

0

1

0.081081

false

0

0.081081

0

0.216216

0

null

0

null

0

1

0

ed502bad0b09f0685ca1ff615fe9d8b7f8ad7287

1,554

py

Python

143.py

tsbxmw/leetcode

e751311b8b5f2769874351717a22c35c19b48a36

[ "MIT" ]

null

143.py

tsbxmw/leetcode

e751311b8b5f2769874351717a22c35c19b48a36

[ "MIT" ]

null

143.py

tsbxmw/leetcode

e751311b8b5f2769874351717a22c35c19b48a36

[ "MIT" ]

null

# 143. 重排链表 # 给定一个单链表 L：L0→L1→…→Ln-1→Ln ， # 将其重新排列后变为： L0→Ln→L1→Ln-1→L2→Ln-2→… # 你不能只是单纯的改变节点内部的值，而是需要实际的进行节点交换。 # 示例 1: # 给定链表 1->2->3->4, 重新排列为 1->4->2->3. # 示例 2: # 给定链表 1->2->3->4->5, 重新排列为 1->5->2->4->3. # Definition for singly-linked list. # class ListNode: # def __init__(self, x): # self.val = x # self.next = None # Definition for singly-linked list. # class ListNode: # def __init__(self, x): # self.val = x # self.next = None ## 整体上是交换，使用递归，先找到最后节点 ## 1 -》 2 -》 3 -》 4 -》 5 ## | | ## temp = 1.next == 2 ## 1.next = 4.next == 5 ## 4.next = None ## 1.next.next == 5.next = 2 ## now = 2 ## last = 3.next class Solution: def reorderList(self, head: ListNode) -> None: """ Do not return anything, modify head in-place instead. """ if not head: return self.pre = head self.flag = True def test(node): if not node.next: # 如果 node.next 是 None，就不需要交换了 return test(node.next) if not self.flag: return if not self.pre.next: self.flag = False return if self.pre == node: self.flag = False return temp = self.pre.next self.pre.next = node.next self.pre.next.next = temp self.pre = temp node.next = None test(self.pre)

24.28125

62

0.462677

209

1,554

3.478469

0.301435

0.077029

0.060523

0.016506

0.233838

0.203576

0

0.050647

0.402831

1,554

64

63

24.28125

0.715517

0.441441

0

0.291667

0

1

0.083333

false

0

0.333333

0

null

0

null

0

1

0

ed510f09d28e1fdb65727ee044b934fd67984f9c

2,555

py

Python

onmt/bin/build_vocab.py

comydream/OpenNMT-py

2f3c810069ca03b752d9886782648e576b39a06d

[ "MIT" ]

1

2021-10-01T15:03:35.000Z

onmt/bin/build_vocab.py

urialon/OpenNMT-py

bdca05a3fac8f864b21c86a8ad03c09895212e70

[ "MIT" ]

null

onmt/bin/build_vocab.py

urialon/OpenNMT-py

bdca05a3fac8f864b21c86a8ad03c09895212e70

[ "MIT" ]

null

#!/usr/bin/env python """Get vocabulary coutings from transformed corpora samples.""" from onmt.utils.logging import init_logger from onmt.utils.misc import set_random_seed, check_path from onmt.utils.parse import ArgumentParser from onmt.opts import dynamic_prepare_opts from onmt.inputters.corpus import build_vocab from onmt.transforms import make_transforms, get_transforms_cls def build_vocab_main(opts): """Apply transforms to samples of specified data and build vocab from it. Transforms that need vocab will be disabled in this. Built vocab is saved in plain text format as following and can be pass as `-src_vocab` (and `-tgt_vocab`) when training: ``` <tok_0>\t<count_0> <tok_1>\t<count_1> ``` """ ArgumentParser.validate_prepare_opts(opts, build_vocab_only=True) assert opts.n_sample == -1 or opts.n_sample > 1, \ f"Illegal argument n_sample={opts.n_sample}." logger = init_logger() set_random_seed(opts.seed, False) transforms_cls = get_transforms_cls(opts._all_transform) fields = None transforms = make_transforms(opts, transforms_cls, fields) logger.info(f"Counter vocab from {opts.n_sample} samples.") src_counter, tgt_counter, src_feats_counter = build_vocab( opts, transforms, n_sample=opts.n_sample) logger.info(f"Counters src:{len(src_counter)}") logger.info(f"Counters tgt:{len(tgt_counter)}") for feat_name, feat_counter in src_feats_counter.items(): logger.info(f"Counters {feat_name}:{len(feat_counter)}") def save_counter(counter, save_path): check_path(save_path, exist_ok=opts.overwrite, log=logger.warning) with open(save_path, "w", encoding="utf8") as fo: for tok, count in counter.most_common(): fo.write(tok + "\t" + str(count) + "\n") if opts.share_vocab: src_counter += tgt_counter tgt_counter = src_counter logger.info(f"Counters after share:{len(src_counter)}") save_counter(src_counter, opts.src_vocab) else: save_counter(src_counter, opts.src_vocab) save_counter(tgt_counter, opts.tgt_vocab) for k, v in src_feats_counter.items(): save_counter(v, opts.src_feats_vocab[k]) def _get_parser(): parser = ArgumentParser(description='build_vocab.py') dynamic_prepare_opts(parser, build_vocab_only=True) return parser def main(): parser = _get_parser() opts, unknown = parser.parse_known_args() build_vocab_main(opts) if __name__ == '__main__': main()

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4.661202

0.336066

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0.126612

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0.003378

0.189041

2,555

75

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0.819981

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null

0

null

0

1

0

ed51b4414d9639f63dd9eb5d177b6130aa8d5108

2,756

py

Python

schools3/ml/experiments/feat_pruning_experiment.py

dssg/mlpolicylab_fall20_schools3_public

f8eff4c56e9bada1eb81ddaca03686d7ef53c2c4

[ "MIT" ]

null

schools3/ml/experiments/feat_pruning_experiment.py

dssg/mlpolicylab_fall20_schools3_public

f8eff4c56e9bada1eb81ddaca03686d7ef53c2c4

[ "MIT" ]

null

schools3/ml/experiments/feat_pruning_experiment.py

dssg/mlpolicylab_fall20_schools3_public

f8eff4c56e9bada1eb81ddaca03686d7ef53c2c4

[ "MIT" ]

null

import numpy as np import pandas as pd from schools3.ml.experiments.models_experiment import ModelsExperiment from schools3.data.base.cohort import Cohort from schools3.config import main_config from schools3.config import global_config from schools3.data.datasets.dataset import Dataset from schools3.ml.experiments.feat_importances_experiment import FeatureImportancesExperiment from schools3.ml.experiments.single_dataset_experiment import SingleDatasetExperiment from schools3.ml.models.tfkeras_model import TFKerasModel from schools3.ml.models.sklearn_model import SklearnModel import schools3.config.ml.experiments.feat_pruning_experiment_config as config from schools3.config.data.datasets import dataset_config # an experiment that trains models with subsets of the features according to their permutation importance rank # like SingleDatasetExperiment, this works on a specific grade class FeaturePruningExperiment(ModelsExperiment): def __init__( self, name='ignore', features_list=main_config.features, labels=main_config.labels, models=main_config.models, metrics=main_config.metrics, use_cache=main_config.use_cache ): super(FeaturePruningExperiment, self).__init__( name, features_list, labels, models, metrics, use_cache=use_cache ) def perform( self, grade=main_config.single_grade, train_years=main_config.train_years, test_years=main_config.test_years, compute_train_metrics=False, **kwargs ): train_cohort = Cohort(grade, train_years) df = pd.DataFrame() for model in self.models: if not (isinstance(model, SklearnModel) or isinstance(model, TFKerasModel)): continue train_data = Dataset(train_cohort, self.features_list, model.get_feature_processor(), self.labels) model.train(train_data) feats_exp = FeatureImportancesExperiment('ignore', self.features_list, self.labels, [model], self.metrics) feature_names, _, sorted_idxs = feats_exp.get_feature_importances(model, train_data) feats = np.flip(feature_names[sorted_idxs]) for i in config.num_feats: dataset_config.feat_whitelist.clear() for feat in feats[:i]: dataset_config.feat_whitelist.append(feat) exp = SingleDatasetExperiment('ignore', self.features_list, self.labels, [model], self.metrics) cur_df = exp.perform(grade, train_years, test_years, compute_train_metrics=compute_train_metrics, **kwargs) cur_df['num_feats'] = i df = pd.concat([df, cur_df], ignore_index=True) return df

43.746032

123

0.717707

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0.036842

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0.08

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0

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0.209724

2,756

62

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null

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null

0

1

0

ed51e5aefc8aa4c007f752784c838fb5f4f57c1c

2,297

py

Python

network/dataset/image_loading.py

imsb-uke/podometric_u_net

a33afcc186d618889df73c7ab2941dfbb63574ac

[ "MIT" ]

null

network/dataset/image_loading.py

imsb-uke/podometric_u_net

a33afcc186d618889df73c7ab2941dfbb63574ac

[ "MIT" ]

null

network/dataset/image_loading.py

imsb-uke/podometric_u_net

a33afcc186d618889df73c7ab2941dfbb63574ac

[ "MIT" ]

null

import os import numpy as np from skimage.io import imread def get_file_count(paths, image_format='.tif'): total_count = 0 for path in paths: try: path_list = [_ for _ in os.listdir(path) if _.endswith(image_format)] total_count += len(path_list) except OSError: print("Directory does not exist. Returned file count for this path will be 0") return total_count # Function to load image def load_image(img_path): img = imread(img_path) if img.shape[2] == 4: img = img[:, :, :-1] # img = np.roll(img, shift=1, axis=2) # CHECK IMAGE FORMAT return img # Function to load mask def load_mask(mask_path): mask = imread(mask_path) return mask def load_mask_from_img(cfg, img_path, img_name, suffixes): a_mask = imread(os.path.join(img_path, img_name + suffixes[0])) msk = np.zeros((a_mask.shape[0], a_mask.shape[1], len(suffixes) * cfg.NUMBER_MSK_CHANNELS)) i = 0 for suffix in suffixes: msk_channel = imread(os.path.join(img_path, img_name + suffix)) if len(msk_channel.shape) == 2: msk_channel = np.expand_dims(msk_channel, axis=-1) if len(msk_channel.shape) != 3: raise ValueError("Mask must be 3-dim here. Does your mask have 1 or more than 3 dimensions? " "Check the masks.") msk[:, :, i:i+cfg.NUMBER_MSK_CHANNELS] = msk_channel i += cfg.NUMBER_MSK_CHANNELS # print(msk, msk.shape) return msk def load_weights(cfg, img_path, img_name, weight_suffixes): a_weights = np.load(os.path.join(img_path, img_name + weight_suffixes[0])) weights = np.zeros((a_weights.shape[0], a_weights.shape[1], len(weight_suffixes) * cfg.NUMBER_MSK_CHANNELS)) i = 0 for suffix in weight_suffixes: weights_channel = np.load(os.path.join(img_path, img_name + suffix)) if len(weights_channel.shape) == 2: weights_channel = np.expand_dims(weights_channel, axis=-1) if len(weights_channel.shape) != 3: raise ValueError("Weights must be 3-dim here. Has your weights 1 or more than 3 dimensions? Check the weights.") weights[:, :, i:i+cfg.NUMBER_MSK_CHANNELS] = weights_channel i += cfg.NUMBER_MSK_CHANNELS return weights

37.048387

124

0.652155

348

2,297

4.103448

0.241379

0.039216

0.04902

0.058824

0.436975

0.298319

0.19888

0.131653

0.106443

0

0.015437

0.238572

2,297

62

125

37.048387

0.801029

0.053548

0

0.085106

0

0.021277

0.117566

0

1

0.106383

false

0

0.06383

0

0.276596

0.021277

0

null

0

null

0

1

0

ed52fe7003cd3391400a3e6ca8a3b67edfc17d59

6,769

py

Python

series/simple/numeric_series.py

kefir/snakee

a17734d4b2d7dfd3e6c7b195baa128fbc84d197b

[ "MIT" ]

null

series/simple/numeric_series.py

kefir/snakee

a17734d4b2d7dfd3e6c7b195baa128fbc84d197b

[ "MIT" ]

null

series/simple/numeric_series.py

kefir/snakee

a17734d4b2d7dfd3e6c7b195baa128fbc84d197b

[ "MIT" ]

null

from typing import Optional, Callable try: # Assume we're a sub-module in a package. from series import series_classes as sc from utils import numeric as nm except ImportError: # Apparently no higher-level package has been imported, fall back to a local import. from .. import series_classes as sc from ...utils import numeric as nm Native = sc.AnySeries DEFAULT_NUMERIC = True WINDOW_DEFAULT = (-1, 0, 1) WINDOW_WO_CENTER = (-2, -1, 0, 1, 2) WINDOW_NEIGHBORS = (-1, 0) class NumericSeries(sc.AnySeries): def __init__( self, values=[], validate=False, name=None, ): super().__init__( values=values, validate=validate, name=name, ) @staticmethod def get_distance_func(): return nm.diff def get_errors(self): yield from super().get_errors() if not self.has_valid_items(): yield 'Values of {} must be numeric'.format(self.get_class_name()) def has_valid_items(self): for v in self.get_values(): if not isinstance(v, (int, float)): return False return True def is_numeric(self, check=False): if check: return self.has_valid_items() else: return DEFAULT_NUMERIC def get_sum(self): return sum( self.filter_values_defined().get_values(), ) def get_mean(self): values_defined = self.filter_values_defined().get_values() if values_defined: return sum(values_defined) / len(values_defined) def norm(self, rate=None, default=None): if rate is None: rate = self.get_mean() return self.map_values(lambda v: v / rate if rate else default) def divide(self, series, default=None, extend=False): return self.map_optionally_extend_zip_values( lambda x, y: x / y if y else default, extend, series, ) def subtract(self, series, default=None, extend=False): return self.map_optionally_extend_zip_values( lambda x, y: x - y if x is not None and y is not None else default, extend, series, ) def derivative(self, extend=False, default=0): if extend: return self.preface(None).subtract( self, extend=True, default=default, ).crop(0, 1) else: return self.slice(0, -1).subtract( self.shift(-1) ) def get_sliding_window(self, window=WINDOW_DEFAULT, extend=True, default=None, as_series=True): if extend: n_min = 0 n_max = self.get_count() else: n_min = - min(window) n_max = self.get_count() - max(window) for center in range(n_min, n_max): sliding_window = [center + n for n in window] if as_series: yield self.value_series().items_no(sliding_window, extend=extend, default=default) else: yield self.value_series().get_items_no(sliding_window, extend=extend, default=default) def apply_window_func( self, function: Callable, window=WINDOW_DEFAULT, extend=True, default=None, as_series=False, inplace: bool = False, ) -> Optional[Native]: values = map(function, self.get_sliding_window(window, extend=extend, default=default, as_series=as_series)) return self.set_values(values, inplace=inplace) def mark_local_extremums(self, local_min=True, local_max=True): return self.apply_window_func( lambda a: nm.is_local_extremum(*a, local_min=local_min, local_max=local_max), window=WINDOW_DEFAULT, extend=True, default=False, ) def mark_local_max(self): return self.mark_local_extremums(local_min=False, local_max=True) def mark_local_min(self): return self.mark_local_extremums(local_min=True, local_max=False) def deviation_from_neighbors(self, window=WINDOW_NEIGHBORS, rel=False): smoothed_series = self.smooth(window=window) deviation = self.subtract(smoothed_series) if rel: deviation = deviation.divide(smoothed_series, default=0) return deviation # @deprecated def smooth_simple_linear(self, window_len=3, exclude_center=False): center = int((window_len - 1) / 2) count = self.get_count() result = self.new() for n in self.get_range_numbers(): is_edge = n < center or n >= count - center if is_edge: result.append(self.get_item_no(n), inplace=True) else: sub_series = self.slice(n - center, n + center + 1) if exclude_center: sub_series = sub_series.drop_item_no(center) result.append(sub_series.get_mean(), inplace=True) return result def smooth(self, how='linear', *args, **kwargs): method_name = 'smooth_{}'.format(how) smooth_method = self.__getattribute__(method_name) return smooth_method(*args, **kwargs) def smooth_multiple(self, list_kwargs=[]): series = self for kwargs in list_kwargs: series = series.smooth(**kwargs) return series def smooth_linear(self, window=WINDOW_DEFAULT): return self.apply_window_func( lambda s: s.get_mean(), window=window, extend=True, default=None, as_series=True, ) def smooth_spikes(self, threshold, window=WINDOW_WO_CENTER, local_min=False, local_max=True, whitelist=None): spikes = self.mark_spikes(threshold, local_min=local_min, local_max=local_max) if whitelist: spikes = spikes.map_zip_values( lambda a, b: a and not b, whitelist, ) return self.map_zip_values( lambda v, t, s: s if t else v, spikes, self.smooth(window=window), ) def mark_spikes(self, threshold, window=WINDOW_NEIGHBORS, local_min=False, local_max=True): deviation = self.deviation_from_neighbors(window=window, rel=True) if local_min or local_max: deviation = deviation.map_zip_values( lambda x, m: x if m else None, self.mark_local_extremums(local_min=local_min, local_max=local_max), ) spikes = deviation.map_values( lambda x: abs(x or 0) > threshold, ) return spikes def plot(self, fmt='-'): nm.plot(self.get_range_numbers(), self.get_values(), fmt=fmt)

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116

0.601418

850

6,769

4.571765

0.177647

0.026763

0.020072

0.012352

0.289243

0.235203

0.170612

0.161091

0.092126

0.067422

0

0.004893

0.30551

6,769

197

117

34.360406

0.82174

0.019796

0

0.113772

0

0.006636

0

1

0.143713

false

0

0.035928

0.047904

0.323353

0

null

0

null

0

1

0

ed548c718f56038d0a32759b322ccf9c4f9f5e93

29,735

py

Python

python/OpenGeoTile.py

scoofy/open-geotiling

0b1305d4482d6df46104135662ffe4565f92f9f0

[ "Apache-2.0" ]

null

python/OpenGeoTile.py

scoofy/open-geotiling

0b1305d4482d6df46104135662ffe4565f92f9f0

[ "Apache-2.0" ]

null

python/OpenGeoTile.py

scoofy/open-geotiling

0b1305d4482d6df46104135662ffe4565f92f9f0

[ "Apache-2.0" ]

null

from openlocationcode import openlocationcode as olc from enum import Enum import math, re class TileSize(Enum): ''' An area of 20° x 20°. The side length of this tile varies with its location on the globe, but can be up to approximately 2200km. Tile addresses will be 2 characters long.''' GLOBAL = (2, 20.0) ''' An area of 1° x 1°. The side length of this tile varies with its location on the globe, but can be up to approximately 110km. Tile addresses will be 4 characters long.''' REGION = (4, 1.0) ''' An area of 0.05° x 0.05°. The side length of this tile varies with its location on the globe, but can be up to approximately 5.5km. Tile addresses will be 6 characters long.''' DISTRICT = (6, 0.05) ''' An area of 0.0025° x 0.0025°. The side length of this tile varies with its location on the globe, but can be up to approximately 275m. Tile addresses will be 8 characters long.''' NEIGHBORHOOD = (8, 0.0025) ''' An area of 0.000125° x 0.000125°. The side length of this tile varies with its location on the globe, but can be up to approximately 14m. Tile addresses will be 10 characters long.''' PINPOINT = (10, 0.000125) def __init__(self, code_length, coordinate_increment): self.code_length = code_length self.coordinate_increment = coordinate_increment def getCodeLength(self): '''get 0th value''' return self.code_length def getCoordinateIncrement(self): '''get 1th value''' return self.coordinate_increment # Copy from OpenLocationCode.java # A separator used to break the code into two parts to aid memorability. SEPARATOR = '+' # Copy from OpenLocationCode.java # The character used to pad codes. PADDING_CHARACTER = '0' PADDING_2 = "00" PADDING_4 = "0000" PADDING_6 = "000000" CODE_ALPHABET = olc.CODE_ALPHABET_ BASE_20_SET = {x+y for x in CODE_ALPHABET for y in CODE_ALPHABET} BASE_20_BORDER_SET = {x for x in BASE_20_SET if x[0] in ['2', 'X'] or x[1] in ['2', 'X']} NORTH_DIGITS = {x for x in BASE_20_BORDER_SET if x[0] == 'X'} EAST_DIGITS = {x for x in BASE_20_BORDER_SET if x[1] == 'X'} SOUTH_DIGITS = {x for x in BASE_20_BORDER_SET if x[0] == '2'} WEST_DIGITS = {x for x in BASE_20_BORDER_SET if x[1] == '2'} memoized_digit_dict = { "N1": NORTH_DIGITS, "E1": EAST_DIGITS, "S1": SOUTH_DIGITS, "W1": WEST_DIGITS, } def is_padded(plus_code): return plus_code.find(PADDING_CHARACTER) != -1 def is_tile_address(plus_code): return plus_code.find(SEPARATOR) == -1 def return_code_of_tile_size(too_precise_plus_code, desired_tile_size): code = too_precise_plus_code if not is_tile_address(code): code = code.replace(SEPARATOR, '') if is_padded(code): if code.find(PADDING_CHARACTER) < desired_tile_size.getCodeLength(): raise Exception("OLC padding larger than allowed by desired_tile_size") code_address = code[:desired_tile_size.getCodeLength()] full_length = TileSize.PINPOINT.getCodeLength() code = code_address + ("0" * (full_length - len(code_address))) if desired_tile_size == TileSize.PINPOINT: code = code[:-2] + SEPARATOR + code[-2:] else: code = code[:-2] + SEPARATOR return code def return_set_of_subaddresses(set_of_addresses): for address in set_of_addresses: if len(address) == TileSize.PINPOINT.getCodeLength(): ''' address already minimum possible size ''' return None return {address+base for address in set_of_addresses for base in BASE_20_SET} class OpenGeoTile(): ''' /** * A wrapper around an {@code OpenLocationCode} object, focusing on the area identified by a prefix * of the given OpenLocationCode. * * Using this wrapper class allows to determine whether two locations are in the same or adjacent * "tiles", to determine all neighboring tiles of a given one, to calculate a distance in tiles etc. * * Open Location Code is a technology developed by Google and licensed under the Apache License 2.0. * For more information, see https://github.com/google/open-location-code * * @author Andreas Bartels * @version 0.1.0 */ Ported by scoofy on 08.31.21 ''' def __init__(self, code=None, tile_size=None, lat=None, long=None, ): if not (code or (code and tile_size) or (lat and long)): raise Exception("Invalid OpenGeoTile constructor arguments") if lat and long: self.constructTileFromLatLong(lat, long, tile_size) elif code and tile_size: self.constructTileFromCodeAndSize(code, tile_size) elif code: if is_tile_address(code): self.constructTileFromTileAddress(code) else: self.constructTileFromCode(code) self.tile_address = self.code.replace(SEPARATOR, "")[0: self.tile_size.getCodeLength()] def constructTileFromCode(self, plus_code): '''/** * Creates a new OpenGeoTile from an existing * {@link com.google.openlocationcode.OpenLocationCode}. * @param olc OpenLocationCode for the current location. This can be a padded code, in which * case the resulting OpenGeoTile will have a larger TileSize. * @throws IllegalArgumentException if olc is not a full code */''' if not olc.isFull(plus_code): raise Exception("Only full OLC supported. Use olc.recoverNearest().") self.code = plus_code.upper() if is_padded(plus_code): code_length = plus_code.find(PADDING_CHARACTER) else: code_length = min(len(plus_code)-1, 10) if code_length == TileSize.GLOBAL.getCodeLength(): self.tile_size = TileSize.GLOBAL elif code_length == TileSize.REGION.getCodeLength(): self.tile_size = TileSize.REGION elif code_length == TileSize.DISTRICT.getCodeLength(): self.tile_size = TileSize.DISTRICT elif code_length == TileSize.NEIGHBORHOOD.getCodeLength(): self.tile_size = TileSize.NEIGHBORHOOD elif code_length == TileSize.PINPOINT.getCodeLength(): self.tile_size = TileSize.PINPOINT else: raise Exception("Too precise, sort this later") def constructTileFromCodeAndSize(self, plus_code, tile_size): ''' Creates a new OpenGeoTile from an existing {@link com.google.openlocationcode.OpenLocationCode}. @param olc OpenLocationCode for the current location @param tile_size tile size to use for this OpenGeoTile @throws IllegalArgumentException when trying to pass a short (non-full) OLC, or if OLC has too much padding for given tile_size ''' if not olc.isFull(plus_code): raise Exception("Only full OLC supported. Use recover().") modified_plus_code = return_code_of_tile_size(plus_code, tile_size) self.code = modified_plus_code.upper() self.tile_size = tile_size def constructTileFromLatLong(self, lat: float, long: float, tile_size=None): '''/** * Creates a new OpenGeoTile from lat/long coordinates. * @param latitude latitude of the location * @param longitude longitude of the location * @param tile_size tile size to use for this OpenGeoTile * @throws IllegalArgumentException passed through from * {@link OpenLocationCode#OpenLocationCode(double, double, int)} */''' if not tile_size: tile_size = TileSize.PINPOINT self.code = olc.encode(lat, long, tile_size.getCodeLength()).upper() self.tile_size = tile_size def constructTileFromTileAddress(self, tileAddress): '''/** * Creates a new OpenGeoTile from a tile address. * @param tileAddress a tile address is a [2/4/6/8/10]-character string that corresponds to a * valid {@link com.google.openlocationcode.OpenLocationCode} after removing * '+' and an additional number of trailing characters; tile size is * determined by the length of this address * @throws IllegalArgumentException passed through from * {@link OpenLocationCode#OpenLocationCode(String)} or thrown if tileAddress is of * invalid length */''' detectedTileSize = None olcBuilder = "" if len(tileAddress) == TileSize.GLOBAL.getCodeLength(): detectedTileSize = TileSize.GLOBAL olcBuilder += tileAddress + PADDING_6 + SEPARATOR if len(tileAddress) == TileSize.REGION.getCodeLength(): detectedTileSize = TileSize.REGION olcBuilder += tileAddress + PADDING_4 + SEPARATOR if len(tileAddress) == TileSize.DISTRICT.getCodeLength(): detectedTileSize = TileSize.DISTRICT olcBuilder += tileAddress + PADDING_2 + SEPARATOR if len(tileAddress) == TileSize.NEIGHBORHOOD.getCodeLength(): detectedTileSize = TileSize.NEIGHBORHOOD olcBuilder += tileAddress + SEPARATOR if len(tileAddress) == TileSize.PINPOINT.getCodeLength(): detectedTileSize = TileSize.PINPOINT olcBuilder += tileAddress[0:8] + SEPARATOR + tileAddress[8:10] if detectedTileSize == None: print(tileAddress) raise Exception("Invalid tile address") self.tile_size = detectedTileSize self.code = olcBuilder.upper() def getWrappedOpenLocationCode(self): # this code is effectively redundant as python has no wrapping '''/** * The exact {@link com.google.openlocationcode.OpenLocationCode} wrapped by this OpenGeoTile. * For the plus code of the whole tile, see {@link #getTileOpenLocationCode()}. * @return the exact plus code wrapped by this OpenGeoTile */''' return self.code def returnCode(self): return self.code def getTileSize(self): '''/** * Get the {@link TileSize} of this OpenGeoTile. * @return the {@link TileSize} of this OpenGeoTile */''' return self.tile_size def getTileAddress(self): '''/** * A tile address is a string of length 2, 4, 6, 8, or 10, which corresponds to a valid * {@link com.google.openlocationcode.OpenLocationCode} after padding with an appropriate * number of '0' and '+' characters. Example: Address "CVXW" corresponds to OLC "CVXW0000+" * @return the tile address of this OpenGeoTile; */''' return self.tile_address def getTileAddressPrefix(self): '''/** * The prefix of a tile address is the address of the next biggest tile at this location. * @return this tile's address with the final two characters removed. In case of a GLOBAL tile, * returns the empty string. */''' if self.tile_size == TileSize.GLOBAL: return "" else: return self.getTileAddress()[0: self.tile_size.getCodeLength()-2] def getParentTileAddress(self): return self.getTileAddressPrefix() def getTileOpenLocationCode(self): # this code is redundant '''/** * The full {@link com.google.openlocationcode.OpenLocationCode} for this tile. Other than * {@link #getWrappedOpenLocationCode()}, this will return a full plus code for the whole tile. * @return a plus code for the whole tile, probably padded with '0' characters */''' return self.getWrappedOpenLocationCode() def getNeighbors(self, eight_point_direction=None): '''/** * Get an array of the typically 8 neighboring tiles of the same size. * @return an array of the typically 8 neighboring tiles of the same size; * may return less than 8 neighbors for tiles near the poles. */''' # deltas = [20.0, 1.0, 0.05, 0.0025, 0.000125] delta = self.getTileSize().getCoordinateIncrement() code_area = olc.decode(self.code) latitude = code_area.latitudeCenter longitude = code_area.longitudeCenter '''directions_list included to keep ordered data''' directions_list = ["NW", "N", "NE", "E", "SE", "S", "SW", "W"] direction_dict = { "NW": [+1, -1], "N": [+1, 0], "NE": [+1, +1], "W": [ 0, -1], "E": [ 0, +1], "SW": [-1, -1], "S": [-1, 0], "SE": [-1, +1], } #lat_diff = [+1, +1, +1, 0, -1, -1, -1, 0] #long_diff = [-1, 0, +1, +1, +1, 0, -1, -1] if not type(eight_point_direction) in [type(None), list, str]: raise Exception("eight_point_direction must be of type list or str") if eight_point_direction is None: directions = directions_list elif isinstance(eight_point_direction, str): directions = [] if eight_point_direction.upper() in directions_list: directions.append(eight_point_direction.upper()) else: ''' this list construction keeps directions in the order above ''' uppercase_input_directions = [d.upper() for d in eight_point_direction] directions = [direction for direction in directions_list if direction in uppercase_input_directions] neighbors = set() for direction in directions: lat_diff, long_diff = direction_dict.get(direction) ''' //OLC constructor clips and normalizes, //so we don't have to deal with invalid lat/long values directly''' neighborLatitude = latitude + (delta * lat_diff) neighborLongitude = longitude + (delta * long_diff) new_OpenGeoTile = OpenGeoTile(lat=neighborLatitude, long=neighborLongitude, tile_size=self.getTileSize()) if not self.isSameTile(new_OpenGeoTile): '''//don't add tiles that are the same as this one due to clipping near the poles''' neighbors.add(new_OpenGeoTile) return neighbors def isSameTile(self, potentialSameTile): '''/** * Check if a tile describes the same area as this one. * @param potentialSameTile the OpenGeoTile to check * @return true if tile sizes and addresses are the same; false if not */''' if potentialSameTile.getTileSize() != self.getTileSize(): return False return potentialSameTile.getTileAddress() == self.getTileAddress() def isNeighbor(self, potentialNeighbor): '''/** * Check if a tile is neighboring this one. * @param potentialNeighbor the OpenGeoTile to check * @return true if this and potentialNeighbor are adjacent (8-neighborhood); * false if not */''' if potentialNeighbor.getTileSize() == self.getTileSize(): '''//avoid iterating over neighbors for same tile''' if self.isSameTile(potentialNeighbor): return False neighbors = self.getNeighbors() for neighbor in neighbors: if potentialNeighbor.isSameTile(neighbor): return True return False else: '''//tiles of different size are adjacent if at least one neighbor of the smaller tile, //but not the smaller tile itself, is contained within the bigger tile''' if potentialNeighbor.getTileSize().getCodeLength() > self.tile_size.getCodeLength(): smallerTile = potentialNeighbor biggerTile = self else: smallerTile = self biggerTile = potentialNeighbor if biggerTile.contains(smallerTile): return False neighbors = smallerTile.getNeighbors() for neighbor in neighbors: if biggerTile.contains(neighbor): return True return False def contains(self, potentialMember): '''/** * Check if this tile contains another one. * @param potentialMember the OpenGeoTile to check * @return true if the area potentialMember falls within the area of this tile, including cases * where both are the same; false if not */''' # //if A contains B, then B's address has A's address as a prefix return potentialMember.getTileAddress().startswith(self.getTileAddress()) def getManhattanTileDistanceTo(self, otherTile): '''/** * Calculates the Manhattan (city block) distance between this and another tile of the same size. * @param otherTile another tile of the same size as this one * @return an integer value corresponding to the number of tiles of the given size that need to * be traversed getting from one to the other tile * @throws IllegalArgumentException thrown if otherTile has different {@link TileSize} */''' if otherTile.getTileSize() != self.getTileSize(): raise Exception("Tile sizes don't match") return self.getLatitudinalTileDistance(otherTile, True) + self.getLongitudinalTileDistance(otherTile, True) def getChebyshevTileDistanceTo(self, otherTile): '''/** * Calculates the Chebyshev (chessboard) distance between this and another tile of the same size. * @param otherTile another tile of the same size as this one * @return an integer value corresponding to the number of tiles of the given size that need to * be traversed getting from one to the other tile * @throws IllegalArgumentException thrown if otherTile has different {@link TileSize} */''' if otherTile.getTileSize() != self.getTileSize(): raise Exception("Tile sizes don't match") return max(self.getLatitudinalTileDistance(otherTile, True), self.getLongitudinalTileDistance(otherTile, True)) def getDirection(self, otherTile): '''/** * Returns the approximate direction of the other tile relative to this. The return value can * have a large margin of error, especially for big or far away tiles, so this should only be * interpreted as a very rough approximation and used as such. * @param otherTile another tile of the same size as this one * @return an angle in radians, 0 being an eastward direction, +/- PI being westward direction * @throws IllegalArgumentException thrown if otherTile has different {@link TileSize} */''' if otherTile.getTileSize() != self.getTileSize(): raise Exception("Tile sizes don't match") xDiff = int(self.getLongitudinalTileDistance(otherTile, False)) yDiff = int(self.getLatitudinalTileDistance(otherTile, False)) return math.atan2(yDiff, xDiff) def getEightPointDirectionOfNeighbor(self, neighborTile): ''' returns neighbor's direction, to assist in expanding tile areas ''' if not self.isNeighbor(neighborTile): raise Exception("neighborTile must be neighbor") if neighborTile.getTileSize() != self.getTileSize(): raise Exception("Tile sizes don't match") self_tile_x = self.getTileAddress()[-2] self_tile_y = self.getTileAddress()[-1] other_tile_x = neighborTile.getTileAddress()[-2] other_tile_y = neighborTile.getTileAddress()[-1] direction = "" north_south = None if self_tile_x != other_tile_x: ''' one tile is above the other ''' if CODE_ALPHABET.find(self_tile_x) in [0, len(CODE_ALPHABET)-1] and CODE_ALPHABET.find(other_tile_x) in [0, len(CODE_ALPHABET)-1]: ''' ajacent parent tiles ''' if CODE_ALPHABET.find(other_tile_x) == 0: ''' other tile is above -> neighborTile is north ''' direction = direction + 'N' else: direction = direction + 'S' else: if CODE_ALPHABET.find(self_tile_x) < CODE_ALPHABET.find(other_tile_x): ''' other tile is above -> neighborTile is north ''' direction = direction + 'N' else: ''' other tile is below -> neighborTile is south ''' direction = direction + 'S' if self_tile_y != other_tile_y: ''' one tile is above the other ''' if CODE_ALPHABET.find(self_tile_y) in [0, len(CODE_ALPHABET)-1] and CODE_ALPHABET.find(other_tile_y) in [0, len(CODE_ALPHABET)-1]: ''' ajacent parent tiles ''' if CODE_ALPHABET.find(other_tile_y) == 0: ''' other tile is right -> neighborTile is east ''' direction = direction + 'E' else: ''' other tile is left -> neighborTile is west ''' direction = direction + 'W' else: if CODE_ALPHABET.find(self_tile_y) < CODE_ALPHABET.find(other_tile_y): ''' other tile is right -> neighborTile is east ''' direction = direction + 'E' else: ''' other tile is left -> neighborTile is west ''' direction = direction + 'W' return direction def getCharacterIndex(self, c): '''//following definitions copied from OpenLocationCode.java''' index = "23456789CFGHJMPQRVWX".find(c.upper()) if index == -1: raise Exception("Character does not exist in alphabet") return index def characterDistance(self, c1, c2): return self.getCharacterIndex(c1) - self.getCharacterIndex(c2) def getLatitudinalTileDistance(self, otherTile, absolute_value_bool): if otherTile.getTileSize() != self.getTileSize(): raise Exception("Tile sizes don't match") numIterations = self.tile_size.getCodeLength()/2 #1..5 tileDistance = 0 for i in range(int(numIterations)): tileDistance *= 20 c1 = self.getTileAddress()[i*2] c2 = otherTile.getTileAddress()[i*2] tileDistance += self.characterDistance(c1,c2) if absolute_value_bool: return abs(tileDistance) return tileDistance def getLongitudinalTileDistance(self, otherTile, absolute_value_bool): if otherTile.getTileSize() != self.getTileSize(): raise Exception("Tile sizes don't match") numIterations = self.tile_size.getCodeLength()/2 #; //1..5 tileDistance = 0 for i in range(int(numIterations)): tileDistance *= 20 c1 = self.getTileAddress()[i*2 + 1] c2 = otherTile.getTileAddress()[i*2 + 1] if i == 0: '''//for the first longitudinal value, we need to take care of wrapping - basically, //if it's shorter to go the other way around, do so''' firstDiff = self.characterDistance(c1, c2) NUM_CHARACTERS_USED = 18 #; //360°/20° = 18 if abs(firstDiff) > NUM_CHARACTERS_USED/2: if firstDiff > 0: firstDiff -= NUM_CHARACTERS_USED else: firstDiff += NUM_CHARACTERS_USED tileDistance += firstDiff else: tileDistance += self.characterDistance(c1, c2) if absolute_value_bool: return abs(tileDistance) return tileDistance def returnSetOfSubtiles(self, desired_tile_size=TileSize.PINPOINT): if self.tile_size.getCodeLength() == desired_tile_size.getCodeLength(): ''' tile is desired size ''' return self elif self.tile_size.getCodeLength() > desired_tile_size.getCodeLength(): 'desired_tile_size is too big' raise Exception("OLC padding larger than allowed by desired_tile_size") iterations_needed = desired_tile_size.getCodeLength()/2 - self.tile_size.getCodeLength()/2 address_set = set([self.getTileAddress()]) for i in range(int(iterations_needed)): address_set = return_set_of_subaddresses(address_set) tile_set = {OpenGeoTile(address) for address in address_set} return tile_set def returnSetOfBorderSubtiles(self, desired_tile_size=TileSize.PINPOINT, eight_point_direction=None): address = self.getTileAddress() if len(address) == TileSize.PINPOINT.getCodeLength(): ''' address already minimum possible size ''' return None elif self.tile_size.getCodeLength() > desired_tile_size.getCodeLength(): 'desired_tile_size is too big' raise Exception("OLC padding larger than allowed by desired_tile_size") iterations_needed = int(desired_tile_size.getCodeLength()/2 - self.tile_size.getCodeLength()/2) north_set = set() east_set = set() south_set = set() west_set = set() if isinstance(eight_point_direction, str): eight_point_direction = eight_point_direction.upper() set_of_border_subaddresses = set() if eight_point_direction is None: ''' all borders ''' ''' traveling salesman problem ''' ''' let's do it once, and try to reduce by swaping digits ''' all_border_set = memoized_digit_dict.get(f"A{iterations_needed}") if not all_border_set: north_base_set = memoized_digit_dict.get(f"N{iterations_needed}") if not north_base_set: self.memoizeDigitDict("N", iterations_needed) north_set = memoized_digit_dict.get(f"N{iterations_needed}") east_set = memoized_digit_dict.get(f"E{iterations_needed}", set()) south_set = memoized_digit_dict.get(f"S{iterations_needed}", set()) west_set = memoized_digit_dict.get(f"W{iterations_needed}", set()) east_exists = east_set != set() south_exists = south_set != set() west_exists = west_set != set() for base in north_set: east_base = "" south_base = "" west_base = "" base_tuple_list = re.findall('..', base) ''' north will be Xd east dX south 2d west d2''' for n_tuple in base_tuple_list: relevant_digit = n_tuple[1] if not east_exists: east_base += relevant_digit + "X" if not south_exists: south_base += "2" + relevant_digit if not west_exists: west_base += relevant_digit + "2" if not east_exists: east_set.add(east_base) if not south_exists: south_set.add(south_base) if not west_exists: west_set.add(west_base) memoized_digit_dict[f"E{iterations_needed}"] = east_set memoized_digit_dict[f"S{iterations_needed}"] = south_set memoized_digit_dict[f"W{iterations_needed}"] = west_set all_border_set = north_set | east_set | south_set | west_set memoized_digit_dict[f"A{iterations_needed}"] = all_border_set return {OpenGeoTile(address+base) for base in all_border_set} elif len(eight_point_direction) == 1: ''' North, South, East, or West ''' base_set = memoized_digit_dict.get(f"{eight_point_direction}{iterations_needed}") if not base_set: self.memoizeDigitDict(eight_point_direction, iterations_needed) base_set = memoized_digit_dict.get(f'{eight_point_direction}{iterations_needed}') return {OpenGeoTile(address + base) for base in base_set} elif len(eight_point_direction) == 2: ''' NW, NE, SW, SE... should return only one tile''' ordinal_digit_dict = { 'NW': 'X2', 'NE': 'XX', 'SE': '2X', 'SW': '22' } base = '' for i in range(iterations_needed): base += ordinal_digit_dict.get(eight_point_direction) return {OpenGeoTile(address + base)} def memoizeDigitDict(self, eight_point_direction, iterations_needed): base_set = memoized_digit_dict.get(f"{eight_point_direction}{iterations_needed}") if not base_set: quickest_i = 0 for i in reversed(range(iterations_needed)): if memoized_digit_dict.get(f"{eight_point_direction}{i + 1}"): quickest_i = i break for i in range(quickest_i, iterations_needed): existing_bases = memoized_digit_dict.get(f"{eight_point_direction}{i + 1}") next_set = {existing_base + base for existing_base in existing_bases for base in memoized_digit_dict.get(f"{eight_point_direction}1")} memoized_digit_dict[f"{eight_point_direction}{i + 2}"] = next_set

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ed57f1712b86394159992dc11fd79688181d493e

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bzl

Python

tensorflow_probability/python/build_defs.bzl

jbergmanster/probability

e15b307066e7485b8fe9faf3d289c739ab8d3806

[ "Apache-2.0" ]

null

tensorflow_probability/python/build_defs.bzl

jbergmanster/probability

e15b307066e7485b8fe9faf3d289c739ab8d3806

[ "Apache-2.0" ]

null

tensorflow_probability/python/build_defs.bzl

jbergmanster/probability

e15b307066e7485b8fe9faf3d289c739ab8d3806

[ "Apache-2.0" ]

null

# Copyright 2019 The TensorFlow Probability Authors. # # 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. # ============================================================================ """Build defs for TF/NumPy/JAX-variadic libraries & tests.""" # [internal] load python3.bzl NO_REWRITE_NEEDED = [ "internal:all_util", "internal:docstring_util", "internal:reparameterization", "layers", "platform_google", ] REWRITER_TARGET = "//tensorflow_probability/substrates/meta:rewrite" RUNFILES_ROOT = "tensorflow_probability/" def _substrate_src(src, substrate): """Rewrite a single src filename for the given substrate.""" return "_{}/_generated_{}".format(substrate, src) def _substrate_srcs(srcs, substrate): """Rewrite src filenames for the given substrate.""" return [_substrate_src(src, substrate) for src in srcs] def _substrate_dep(dep, substrate): """Convert a single dep to one appropriate for the given substrate.""" dep_to_check = dep if dep.startswith(":"): dep_to_check = "{}{}".format(native.package_name(), dep) for no_rewrite in NO_REWRITE_NEEDED: if no_rewrite in dep_to_check: return dep if "tensorflow_probability/" in dep or dep.startswith(":"): if "internal/backend" in dep: return dep if ":" in dep: return "{}.{}".format(dep, substrate) return "{}:{}.{}".format(dep, dep.split("/")[-1], substrate) return dep def _substrate_deps(deps, substrate): """Convert deps to those appropriate for the given substrate.""" new_deps = [_substrate_dep(dep, substrate) for dep in deps] backend_dep = "//tensorflow_probability/python/internal/backend/{}".format(substrate) if backend_dep not in new_deps: new_deps.append(backend_dep) return new_deps # This is needed for the transitional period during which we have the internal # py2and3_test and py_test comingling in BUILD files. Otherwise the OSS export # rewrite process becomes irreversible. def py3_test(*args, **kwargs): """Internal/external reversibility, denotes py3-only vs py2+3 tests. Args: *args: Passed to underlying py_test. **kwargs: Passed to underlying py_test. srcs_version and python_version are added (with value `"PY3"`) if not specified. """ kwargs = dict(kwargs) if "srcs_version" not in kwargs: kwargs["srcs_version"] = "PY3" if "python_version" not in kwargs: kwargs["python_version"] = "PY3" native.py_test(*args, **kwargs) def _resolve_omit_dep(dep): """Resolves a `substrates_omit_deps` item to full target.""" if ":" not in dep: dep = "{}:{}".format(dep, dep.split("/")[-1]) if dep.startswith(":"): dep = "{}{}".format(native.package_name(), dep) return dep def _substrate_runfiles_symlinks_impl(ctx): """A custom BUILD rule to generate python runfiles symlinks. A custom build rule which adds runfiles symlinks for files matching a substrate genrule file pattern, i.e. `'_jax/_generated_normal.py'`. This rule will aggregate and pass along deps while adding the given symlinks to the runfiles structure. Build rule attributes: - substrate: One of 'jax' or 'numpy'; which substrate this applies to. - deps: A list of py_library labels. These are passed along. Args: ctx: Rule analysis context. Returns: Info objects to propagate deps and add runfiles symlinks. """ # Aggregate the depset inputs to resolve transitive dependencies. transitive_sources = [] uses_shared_libraries = [] imports = [] has_py2_only_sources = [] has_py3_only_sources = [] cc_infos = [] for dep in ctx.attr.deps: if PyInfo in dep: transitive_sources.append(dep[PyInfo].transitive_sources) uses_shared_libraries.append(dep[PyInfo].uses_shared_libraries) imports.append(dep[PyInfo].imports) has_py2_only_sources.append(dep[PyInfo].has_py2_only_sources) has_py3_only_sources.append(dep[PyInfo].has_py3_only_sources) # if PyCcLinkParamsProvider in dep: # DisableOnExport # cc_infos.append(dep[PyCcLinkParamsProvider].cc_info) # DisableOnExport if CcInfo in dep: cc_infos.append(dep[CcInfo]) # Determine the set of symlinks to generate. transitive_sources = depset(transitive = transitive_sources) runfiles_dict = {} substrate = ctx.attr.substrate file_substr = "_{}/_generated_".format(substrate) for f in transitive_sources.to_list(): if "tensorflow_probability" in f.dirname and file_substr in f.short_path: pre, post = f.short_path.split("/python/") out_path = "{}/substrates/{}/{}".format( pre, substrate, post.replace(file_substr, ""), ) runfiles_dict[RUNFILES_ROOT + out_path] = f # Construct the output structures to pass along Python srcs/deps/etc. py_info = PyInfo( transitive_sources = transitive_sources, uses_shared_libraries = any(uses_shared_libraries), imports = depset(transitive = imports), has_py2_only_sources = any(has_py2_only_sources), has_py3_only_sources = any(has_py3_only_sources), ) py_cc_link_info = cc_common.merge_cc_infos(cc_infos = cc_infos) py_runfiles = depset( transitive = [depset(transitive = [ dep[DefaultInfo].data_runfiles.files, dep[DefaultInfo].default_runfiles.files, ]) for dep in ctx.attr.deps], ) runfiles = DefaultInfo(runfiles = ctx.runfiles( transitive_files = py_runfiles, root_symlinks = runfiles_dict, )) return py_info, py_cc_link_info, runfiles # See documentation at: # https://docs.bazel.build/versions/3.4.0/skylark/rules.html substrate_runfiles_symlinks = rule( implementation = _substrate_runfiles_symlinks_impl, attrs = { "substrate": attr.string(), "deps": attr.label_list(), }, ) def multi_substrate_py_library( name, srcs = [], deps = [], substrates_omit_deps = [], jax_omit_deps = [], numpy_omit_deps = [], testonly = 0, srcs_version = "PY2AND3"): """A TFP `py_library` for each of TF, NumPy, and JAX. Args: name: The TF `py_library` name. NumPy and JAX libraries have '.numpy' and '.jax' appended. srcs: As with `py_library`. A `genrule` is used to rewrite srcs for NumPy and JAX substrates. deps: As with `py_library`. The list is rewritten to depend on substrate-specific libraries for substrate variants. substrates_omit_deps: List of deps to omit if those libraries are not rewritten for the substrates. jax_omit_deps: List of deps to omit for the JAX substrate. numpy_omit_deps: List of deps to omit for the NumPy substrate. testonly: As with `py_library`. srcs_version: As with `py_library`. """ native.py_library( name = name, srcs = srcs, deps = deps, srcs_version = srcs_version, testonly = testonly, ) remove_deps = [ "//third_party/py/tensorflow", "//third_party/py/tensorflow:tensorflow", ] trimmed_deps = [dep for dep in deps if (dep not in substrates_omit_deps and dep not in remove_deps)] resolved_omit_deps_numpy = [ _resolve_omit_dep(dep) for dep in substrates_omit_deps + numpy_omit_deps ] for src in srcs: native.genrule( name = "rewrite_{}_numpy".format(src.replace(".", "_")), srcs = [src], outs = [_substrate_src(src, "numpy")], cmd = "$(location {}) $(SRCS) --omit_deps={} > $@".format( REWRITER_TARGET, ",".join(resolved_omit_deps_numpy), ), tools = [REWRITER_TARGET], ) native.py_library( name = "{}.numpy.raw".format(name), srcs = _substrate_srcs(srcs, "numpy"), deps = _substrate_deps(trimmed_deps, "numpy"), srcs_version = srcs_version, testonly = testonly, ) # Add symlinks under tfp/substrates/numpy. substrate_runfiles_symlinks( name = "{}.numpy".format(name), substrate = "numpy", deps = [":{}.numpy.raw".format(name)], testonly = testonly, ) resolved_omit_deps_jax = [ _resolve_omit_dep(dep) for dep in substrates_omit_deps + jax_omit_deps ] jax_srcs = _substrate_srcs(srcs, "jax") for src in srcs: native.genrule( name = "rewrite_{}_jax".format(src.replace(".", "_")), srcs = [src], outs = [_substrate_src(src, "jax")], cmd = "$(location {}) $(SRCS) --omit_deps={} --numpy_to_jax > $@".format( REWRITER_TARGET, ",".join(resolved_omit_deps_jax), ), tools = [REWRITER_TARGET], ) native.py_library( name = "{}.jax.raw".format(name), srcs = jax_srcs, deps = _substrate_deps(trimmed_deps, "jax"), srcs_version = srcs_version, testonly = testonly, ) # Add symlinks under tfp/substrates/jax. substrate_runfiles_symlinks( name = "{}.jax".format(name), substrate = "jax", deps = [":{}.jax.raw".format(name)], testonly = testonly, ) def multi_substrate_py_test( name, size = "small", jax_size = None, numpy_size = None, srcs = [], deps = [], tags = [], numpy_tags = [], jax_tags = [], disabled_substrates = [], srcs_version = "PY2AND3", timeout = None, shard_count = None): """A TFP `py2and3_test` for each of TF, NumPy, and JAX. Args: name: Name of the `test_suite` which covers TF, NumPy and JAX variants of the test. Each substrate will have a dedicated `py2and3_test` suffixed with '.tf', '.numpy', or '.jax' as appropriate. size: As with `py_test`. jax_size: A size override for the JAX target. numpy_size: A size override for the numpy target. srcs: As with `py_test`. These will have a `genrule` emitted to rewrite NumPy and JAX variants, writing the test file into a subdirectory. deps: As with `py_test`. The list is rewritten to depend on substrate-specific libraries for substrate variants. tags: Tags global to this test target. NumPy also gets a `'tfp_numpy'` tag, and JAX gets a `'tfp_jax'` tag. A `f'_{name}'` tag is used to produce the `test_suite`. numpy_tags: Tags specific to the NumPy test. (e.g. `"notap"`). jax_tags: Tags specific to the JAX test. (e.g. `"notap"`). disabled_substrates: Iterable of substrates to disable, items from ["numpy", "jax"]. srcs_version: As with `py_test`. timeout: As with `py_test`. shard_count: As with `py_test`. """ name_tag = "_{}".format(name) tags = [t for t in tags] tags.append(name_tag) tags.append("multi_substrate") native.py_test( name = "{}.tf".format(name), size = size, srcs = srcs, main = "{}.py".format(name), deps = deps, tags = tags, srcs_version = srcs_version, timeout = timeout, shard_count = shard_count, ) if "numpy" not in disabled_substrates: numpy_srcs = _substrate_srcs(srcs, "numpy") native.genrule( name = "rewrite_{}_numpy".format(name), srcs = srcs, outs = numpy_srcs, cmd = "$(location {}) $(SRCS) > $@".format(REWRITER_TARGET), tools = [REWRITER_TARGET], ) py3_test( name = "{}.numpy".format(name), size = numpy_size or size, srcs = numpy_srcs, main = _substrate_src("{}.py".format(name), "numpy"), deps = _substrate_deps(deps, "numpy"), tags = tags + ["tfp_numpy"] + numpy_tags, srcs_version = srcs_version, python_version = "PY3", timeout = timeout, shard_count = shard_count, ) if "jax" not in disabled_substrates: jax_srcs = _substrate_srcs(srcs, "jax") native.genrule( name = "rewrite_{}_jax".format(name), srcs = srcs, outs = jax_srcs, cmd = "$(location {}) $(SRCS) --numpy_to_jax > $@".format(REWRITER_TARGET), tools = [REWRITER_TARGET], ) jax_deps = _substrate_deps(deps, "jax") # [internal] Add JAX build dep py3_test( name = "{}.jax".format(name), size = jax_size or size, srcs = jax_srcs, main = _substrate_src("{}.py".format(name), "jax"), deps = jax_deps, tags = tags + ["tfp_jax"] + jax_tags, srcs_version = srcs_version, python_version = "PY3", timeout = timeout, shard_count = shard_count, ) native.test_suite( name = name, tags = [name_tag], )

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null

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null

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ed583ccefc13cf5fca32a4b108662e62505e92e1

5,425

py

Python

src/wikidated/wikidata/wikidata_dump.py

lschmelzeisen/wikidata-history-analyzer

8673639b61839d2dca271fbbaf2feb8563b75f2d

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

6

2021-06-10T09:26:44.000Z

2021-07-07T13:49:00.000Z

src/wikidated/wikidata/wikidata_dump.py

lschmelzeisen/wikidata-history-analyzer

8673639b61839d2dca271fbbaf2feb8563b75f2d

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

null

src/wikidated/wikidata/wikidata_dump.py

lschmelzeisen/wikidata-history-analyzer

8673639b61839d2dca271fbbaf2feb8563b75f2d

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

null

# # Copyright 2021 Lukas Schmelzeisen # # 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 __future__ import annotations import json from datetime import date, datetime from logging import getLogger from pathlib import Path from typing import Mapping, MutableSequence, Sequence, Type, TypeVar import requests from pydantic import BaseModel as PydanticModel from pydantic import validator from tqdm import tqdm # type: ignore from typing_extensions import Final from wikidated._utils import RangeMap from wikidated.wikidata.wikidata_dump_file import WikidataDumpFile from wikidated.wikidata.wikidata_dump_pages_meta_history import ( WikidataDumpPagesMetaHistory, ) from wikidated.wikidata.wikidata_dump_sites_table import WikidataDumpSitesTable _LOGGER = getLogger(__name__) _T_WikidataDumpFile = TypeVar("_T_WikidataDumpFile", bound=WikidataDumpFile) class WikidataDump: def __init__( self, dump_dir: Path, version: date, *, mirror: str = "https://dumps.wikimedia.org", ) -> None: self._dump_dir = dump_dir self.version: Final = version self.mirror: Final = mirror self._dump_status = _WikidataDumpStatus.load( self._dump_dir, self.version, self.mirror ) self.sites_table: Final = self._construct_dumps( WikidataDumpSitesTable, "sitestable" )[0] self.pages_meta_history: Final = RangeMap[WikidataDumpPagesMetaHistory]() for dump_file in self._construct_dumps( WikidataDumpPagesMetaHistory, "metahistory7zdump" ): self.pages_meta_history[dump_file.page_ids] = dump_file def download( self, *, sites_table: bool = True, pages_meta_history: bool = True ) -> None: _LOGGER.info( f"Downloading Wikidata dump {self.version:%4Y%2m%2d} from '{self.mirror}'." ) dump_files: MutableSequence[WikidataDumpFile] = [] if sites_table: dump_files.append(self.sites_table) if pages_meta_history: dump_files.extend(self.pages_meta_history.values()) with tqdm( desc=f"Wikidata dump {self.version:%4Y%2m%2d} files", total=len(dump_files), dynamic_ncols=True, position=1, ) as progress_bar_files, tqdm( desc=f"Wikidata dump {self.version:%4Y%2m%2d} bytes", total=sum(dump_file.size for dump_file in dump_files), dynamic_ncols=True, position=2, unit="B", unit_scale=True, unit_divisor=1024, ) as progress_bar_size: for dump_file in dump_files: dump_file.download() progress_bar_files.update(1) progress_bar_size.update(dump_file.size) _LOGGER.info(f"Done downloading Wikidata dump {self.version:%4Y%2m%2d}.") def _construct_dumps( self, dump_type: Type[_T_WikidataDumpFile], dump_type_id: str ) -> Sequence[_T_WikidataDumpFile]: return [ dump_type( path=self._dump_dir / path, url=self.mirror + dump_status_file.url, sha1=dump_status_file.sha1, size=dump_status_file.size, ) for path, dump_status_file in self._dump_status.jobs[ dump_type_id ].files.items() ] class _WikidataDumpStatusFile(PydanticModel): size: int url: str md5: str sha1: str class _WikidataDumpStatusJob(PydanticModel): status: str updated: datetime files: Mapping[str, _WikidataDumpStatusFile] @validator("updated", pre=True) def _parse_datetime(cls, value: str) -> datetime: # noqa: N805 return datetime.strptime(value, "%Y-%m-%d %H:%M:%S") class _WikidataDumpStatus(PydanticModel): jobs: Mapping[str, _WikidataDumpStatusJob] version: str @classmethod def load(cls, dump_dir: Path, version: date, mirror: str) -> _WikidataDumpStatus: path = dump_dir / f"wikidatawiki-{version:%4Y%2m%2d}-dumpstatus.json" if not path.exists(): url = f"{mirror}/wikidatawiki/{version:%4Y%2m%2d}/dumpstatus.json" _LOGGER.debug(f"Downloading Wikidata dump status from '{url}'.") response = requests.get(url) response.raise_for_status() path.parent.mkdir(exist_ok=True, parents=True) with path.open("w", encoding="UTF-8") as fd: fd.write(json.dumps(response.json(), indent=2) + "\n") _LOGGER.debug("Done downloading Wikidata dump status.") dump_status = _WikidataDumpStatus.parse_file(path) for job_name, job in dump_status.jobs.items(): if job.status != "done": path.unlink() raise Exception(f"Job '{job_name}' is not 'done', but '{job.status}'.") return dump_status

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5.325545

0.323988

0.032173

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0.045627

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0

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0.305085

0

null

0

null

0

1

0

ed58570015c33daeb7f03921904a43571a44e66f

18,726

py

Python

tcapygen/layoutgen.py

Ahrvo-Trading-Systems/tcapy

df8439aa5c754fc9a7fde463c44c489b27112f76

[ "Apache-2.0" ]

189

2020-03-20T17:03:04.000Z

2022-03-30T13:33:27.000Z

tcapygen/layoutgen.py

Ahrvo-Trading-Systems/tcapy

df8439aa5c754fc9a7fde463c44c489b27112f76

[ "Apache-2.0" ]

4

2020-06-06T14:58:21.000Z

2022-03-10T22:31:15.000Z

tcapygen/layoutgen.py

Ahrvo-Trading-Systems/tcapy

df8439aa5c754fc9a7fde463c44c489b27112f76

[ "Apache-2.0" ]

60

2020-03-20T17:06:56.000Z

2022-03-26T02:48:58.000Z

from __future__ import division, print_function __author__ = 'saeedamen' # Saeed Amen / saeed@cuemacro.com # # Copyright 2017 Cuemacro Ltd. - http//www.cuemacro.com / @cuemacro # # See the License for the specific language governing permissions and limitations under the License. # ## Web server components import dash_core_components as dcc import dash_html_components as html import base64 import os ## Date/time components import pandas as pd import datetime from datetime import timedelta from collections import OrderedDict from pandas.tseries.offsets import * from tcapy.vis.layoutdash import LayoutDash ######################################################################################################################## class LayoutDashImplGen(LayoutDash): """This implements the LayoutDash abstract class, to create the web based GUI for the tcapy application. It creates two web pages - detailed_page - for doing detailed tcapy analysis for a specific currency pair - aggregated_page - for more aggregated style analysis across multiple currency pairs and over multiple time periods """ def __init__(self, app=None, constants=None, url_prefix=''): super(LayoutDashImplGen, self).__init__(app=app, constants=constants, url_prefix=url_prefix) available_dates = pd.date_range( datetime.datetime.today().date() - timedelta(days=self._constants.gui_lookback_window), datetime.datetime.today().date(), freq=BDay()) times = pd.date_range("0:00", "23:59", freq="15min") ### create the possible values for drop down boxes on both pages # Reverse date list (for both detailed and aggregated pages) self.available_dates = [x.date() for x in available_dates[::-1]] # For detailed page only self.available_times = [t.strftime("%H:%M") for t in times] self.available_tickers = self._constants.available_tickers_dictionary['All'] self.available_venues = self._constants.available_venues_dictionary['All'] self.available_brokers = self._constants.available_brokers_dictionary['All'] self.available_algos = self._constants.available_algos_dictionary['All'] self.available_market_data = self._constants.available_market_data self.available_order_plot_lines = ['candlestick', 'mid', 'bid', 'ask', 'arrival', 'twap', 'vwap', 'buy trade', 'sell trade'] self.available_execution_plot_lines = ['candlestick', 'mid', 'bid', 'ask', 'buy trade', 'sell trade'] self.available_slippage_bounds = ['0.25', '0.5', '1.0', '1.25', '1.5', '2.0', 'bid/ask'] # For aggregated page only self.available_grouped_tickers = self._flatten_dictionary(self._constants.available_tickers_dictionary) self.available_grouped_venues = self._flatten_dictionary(self._constants.available_venues_dictionary) self.available_grouped_brokers = self._flatten_dictionary(self._constants.available_brokers_dictionary) self.available_grouped_algos = self._flatten_dictionary(self._constants.available_algos_dictionary) self.available_event_types = self._constants.available_event_types self.available_metrics = self._constants.available_metrics self.available_reload = ['no', 'yes'] self.available_visualization = ['yes', 'no'] self.construct_layout() def _flatten_dictionary(self, dictionary): available = dictionary['All'] available_groups = self._util_func.dict_key_list(dictionary.keys()) return self.flatten_list_of_strings([available_groups, available]) def construct_layout(self): self.page_content = html.Div([ dcc.Location(id='url', refresh=False), html.Div(id='page-content') ]) link_bar_dict = {'Detailed' : 'detailed', 'Aggregated' : 'aggregated', 'Compliance' : 'compliance'} trade_outliers_cols = ['Date', 'ticker', 'side', 'notional cur', 'benchmark', 'exec not', 'exec not in rep cur', 'slippage'] broker_cols = ['Date', 'by broker notional (rep cur)'] # Main page for detailed analysing of (eg. over the course of a few days) self.pages['detailed'] = html.Div([ self._sc.header_bar('FX: Detailed - Trader Analysis', img='logo.png'), self._sc.link_bar(link_bar_dict), self._sc.width_row_cell(html.B("Status: ok", id='detailed-status'), margin_left=5), self._sc.horizontal_bar(), # Dropdown selection boxes html.Div([ self._sc.drop_down(caption='Start Date', id={'start-date-val' : self.available_dates, 'start-time-val' : self.available_times}, prefix_id='detailed'), self._sc.drop_down(caption='Finish Date', id=OrderedDict([('finish-date-val', self.available_dates), ('finish-time-val', self.available_times)]), prefix_id='detailed'), self._sc.drop_down(caption='Ticker', id='ticker-val', prefix_id='detailed', drop_down_values=self.available_tickers), self._sc.drop_down(caption='Broker', id='broker-val', prefix_id='detailed', drop_down_values=self.available_grouped_brokers), self._sc.drop_down(caption='Algo', id='algo-val', prefix_id='detailed', drop_down_values=self.available_grouped_algos), self._sc.drop_down(caption='Venue', id='venue-val', prefix_id='detailed', drop_down_values=self.available_grouped_venues), self._sc.drop_down(caption='Market Data', id='market-data-val', prefix_id='detailed', drop_down_values=self.available_market_data), self._sc.drop_down(caption='Metric', id='metric-val', prefix_id='detailed', drop_down_values=self.available_metrics) ]), self._sc.horizontal_bar(), self._sc.button(caption='Calculate', id='calculation-button', prefix_id='detailed'), # self.button(caption = 'Print PDF', id = 'detailed-print-pdf-button', className = 'no-print'), # Orders self._sc.horizontal_bar(), self._sc.plot(caption='Orders: Timeline', id='order-candle-timeline-plot', prefix_id='detailed', element_add=self._sc.timeline_dropdown('detailed-order-candle-timeline-plot', self.available_order_plot_lines), downloadplot_caption='Download CSV', downloadplot_tag='order-candle-timeline-download-link', download_file='download_order_candle_timeline', height=500), self._sc.plot(caption='Orders: Markout', id='order-markout-plot', prefix_id='detailed', height=500), self._sc.plot(caption='Orders: Histogram vs PDF fit', id='order-dist-plot', prefix_id='detailed', height=500), # Execution trades self._sc.horizontal_bar(), self._sc.plot(caption='Executions: Timeline', id='execution-candle-timeline-plot', prefix_id='detailed', element_add=self._sc.timeline_dropdown('detailed-execution-candle-timeline-plot', self.available_execution_plot_lines), downloadplot_caption='Download CSV', downloadplot_tag='execution-candle-timeline-download-link', download_file='download_execution_candle_timeline.csv', height=500), self._sc.plot(caption='Executions: Markout', id='execution-markout-plot', prefix_id='detailed', height=500), self._sc.plot(caption='Executions: Histogram vs PDF fit', id='execution-dist-plot', prefix_id='detailed', height=500), # Detailed tcapy markout table for executions html.Div([ html.H3('Executions: Markout Table'), html.Div(id='detailed-execution-table') ], style={'width': '1000px', 'display': 'inline-block', 'marginBottom': 5, 'marginTop': 5, 'marginLeft': 5, 'marginRight': 5}), ], style={'width': '1000px', 'marginRight': 'auto', 'marginLeft': 'auto'}) ################################################################################################################ # Secondary page for analysing aggregated statistics over long periods of time, eg. who is the best broker? self.pages['aggregated'] = html.Div([ self._sc.header_bar('FX: Aggregated - Trader Analysis', img='logo.png'), self._sc.link_bar(link_bar_dict), self._sc.width_row_cell(html.B("Status: ok", id='aggregated-status'), margin_left=5), self._sc.horizontal_bar(), # dropdown selection boxes html.Div([ self._sc.drop_down(caption='Start Date', id='start-date-val', prefix_id='aggregated', drop_down_values=self.available_dates), self._sc.drop_down(caption='Finish Date', id='finish-date-val', prefix_id='aggregated', drop_down_values=self.available_dates), self._sc.drop_down(caption='Ticker', id='ticker-val', prefix_id='aggregated', drop_down_values=self.available_grouped_tickers, multiselect=True), self._sc.drop_down(caption='Broker', id='broker-val', prefix_id='aggregated', drop_down_values=self.available_grouped_brokers, multiselect=True), self._sc.drop_down(caption='Algo', id='algo-val', prefix_id='aggregated', drop_down_values=self.available_grouped_algos, multiselect=True), self._sc.drop_down(caption='Venue', id='venue-val', prefix_id='aggregated', drop_down_values=self.available_grouped_venues, multiselect=True), self._sc.drop_down(caption='Reload', id='reload-val', prefix_id='aggregated', drop_down_values=self.available_reload), self._sc.drop_down(caption='Market Data', id='market-data-val', prefix_id='aggregated', drop_down_values=self.available_market_data), self._sc.drop_down(caption='Event Type', id='event-type-val', prefix_id='aggregated', drop_down_values=self.available_event_types), self._sc.drop_down(caption='Metric', id='metric-val', prefix_id='aggregated', drop_down_values=self.available_metrics), ]), self._sc.horizontal_bar(), self._sc.button(caption='Calculate', id='calculation-button', prefix_id='aggregated'), # , msg_id='aggregated-status'), self._sc.horizontal_bar(), # self.date_picker_range(caption='Start/Finish Dates', id='aggregated-date-val', offset=[-7,-1]), self._sc.plot(caption='Aggregated Trader: Summary', id=['execution-by-ticker-bar-plot', 'execution-by-venue-bar-plot'], prefix_id='aggregated', height=500), self._sc.horizontal_bar(), self._sc.plot(caption='Aggregated Trader: Timeline', id='execution-by-ticker-timeline-plot', prefix_id='aggregated', height=500), self._sc.horizontal_bar(), self._sc.plot(caption='Aggregated Trader: PDF fit (' + self._constants.reporting_currency + ' notional)', id=['execution-by-ticker-dist-plot', 'execution-by-venue-dist-plot'], prefix_id='aggregated', height=500), self._sc.horizontal_bar() ], style={'width': '1000px', 'marginRight': 'auto', 'marginLeft': 'auto'}) ################################################################################################################ self.pages['compliance'] = html.Div([ self._sc.header_bar('FX: Compliance Analysis', img='logo.png'), self._sc.link_bar(link_bar_dict), self._sc.width_row_cell(html.B("Status: ok", id='compliance-status'), margin_left=5), self._sc.horizontal_bar(), # Dropdown selection boxes html.Div([ self._sc.drop_down(caption='Start Date', id='start-date-val', prefix_id='compliance', drop_down_values=self.available_dates), self._sc.drop_down(caption='Finish Date', id='finish-date-val', prefix_id='compliance', drop_down_values=self.available_dates), self._sc.drop_down(caption='Ticker', id='ticker-val', prefix_id='compliance', drop_down_values=self.available_grouped_tickers, multiselect=True), self._sc.drop_down(caption='Broker', id='broker-val', prefix_id='compliance', drop_down_values=self.available_grouped_brokers, multiselect=True), self._sc.drop_down(caption='Algo', id='algo-val', prefix_id='compliance', drop_down_values=self.available_grouped_algos, multiselect=True), self._sc.drop_down(caption='Venue', id='venue-val', prefix_id='compliance', drop_down_values=self.available_grouped_venues, multiselect=True), self._sc.drop_down(caption='Reload', id='reload-val', prefix_id='compliance', drop_down_values=self.available_reload), self._sc.drop_down(caption='Market Data', id='market-data-val', prefix_id='compliance', drop_down_values=self.available_market_data), self._sc.drop_down(caption='Filter by Time', id='filter-time-of-day-val', prefix_id='compliance', drop_down_values=self.available_reload), self._sc.drop_down(caption='Start Time of Day', id='start-time-of-day-val', prefix_id='compliance', drop_down_values=self.available_times), self._sc.drop_down(caption='Finish Time of Day', id='finish-time-of-day-val', prefix_id='compliance', drop_down_values=self.available_times), self._sc.drop_down(caption='Slippage to Mid (bp)', id='slippage-bounds-val', prefix_id='compliance', drop_down_values=self.available_slippage_bounds), self._sc.drop_down(caption='Visualization', id='visualization-val', prefix_id='compliance', drop_down_values=self.available_visualization) ]), self._sc.horizontal_bar(), html.Div([ self._sc.button(caption='Calculate', id='calculation-button', prefix_id='compliance'), # self.date_picker(caption='Start Date', id='start-date-dtpicker', prefix_id='compliance'), # self.date_picker(caption='Finish Date', id='finish-date-dtpicker', prefix_id='compliance'), ]), self._sc.horizontal_bar(), self._sc.table(caption='Compliance: Trade Outliers', id='execution-by-anomalous-table', prefix_id='compliance', columns=trade_outliers_cols, downloadplot_caption='Trade outliers CSV', downloadplot_tag='execution-by-anomalous-download-link', download_file='download_execution_by_anomalous.csv'), self._sc.table(caption='Compliance: Totals by Broker', id='summary-by-broker-table', prefix_id='compliance', columns=broker_cols, downloadplot_caption='Download broker CSV', downloadplot_tag='summary-by-broker-download-link', download_file='download_broker.csv' ), self._sc.horizontal_bar() ], style={'width': '1000px', 'marginRight': 'auto', 'marginLeft': 'auto'}) # ID flags self.id_flags = { # Detailed trader page # 'timeline_trade_orders' : {'client-orders': 'order', 'executions': 'trade'}, # 'markout_trade_orders' : {'client-orders': 'order_df', 'executions': 'trade_df'}, 'detailed_candle_timeline_trade_order': {'execution': 'sparse_market_trade_df', 'order': 'sparse_market_order_df'}, 'detailed_markout_trade_order': {'execution': 'trade_df', 'order': 'order_df'}, 'detailed_table_trade_order': {'execution': 'table_trade_df_markout_by_all'}, 'detailed_dist_trade_order': {'execution': 'dist_trade_df_by/pdf/side', 'order': 'dist_order_df_by/pdf/side'}, 'detailed_download_link_trade_order': {'execution-candle-timeline': 'sparse_market_trade_df', 'order-candle-timeline': 'sparse_market_order_df'}, # Aggregated trader page 'aggregated_bar_trade_order': {'execution-by-ticker': 'bar_trade_df_by/mean/ticker', 'execution-by-venue': 'bar_trade_df_by/mean/venue'}, 'aggregated_timeline_trade_order': {'execution-by-ticker': 'timeline_trade_df_by/mean_date/ticker', 'execution-by-venue': 'timeline_trade_df_by/mean_date/venue'}, 'aggregated_dist_trade_order': {'execution-by-ticker': 'dist_trade_df_by/pdf/ticker', 'execution-by-venue': 'dist_trade_df_by/pdf/venue'}, # Compliance page 'compliance_metric_table_trade_order': {'execution-by-anomalous': 'table_trade_df_slippage_by_worst_all', 'summary-by-broker': 'bar_trade_df_executed_notional_in_reporting_currency_by_broker_id'}, 'compliance_download_link_trade_order': {'execution-by-anomalous': 'table_trade_df_slippage_by_worst_all', 'summary-by-broker': 'bar_trade_df_executed_notional_in_reporting_currency_by_broker_id'}, }

58.51875

154

0.595215

2,030

18,726

5.20936

0.139409

0.039716

0.029314

0.04104

0.618345

0.518676

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0.006055

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18,726

319

155

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0.072072

0.004505

0

null

0

null

0

1

0

ed587bf56577619d8ec39ef62825f11e9ce7e776

3,511

py

Python

projects/MAE/utils/weight_convert.py

Oneflow-Inc/libai

e473bd3962f07b1e37232d2be39c8257df0ec0f3

[ "Apache-2.0" ]

55

2021-12-10T08:47:06.000Z

2022-03-28T09:02:15.000Z

projects/MAE/utils/weight_convert.py

Oneflow-Inc/libai

e473bd3962f07b1e37232d2be39c8257df0ec0f3

[ "Apache-2.0" ]

106

2021-11-03T05:16:45.000Z

2022-03-31T06:16:23.000Z

projects/MAE/utils/weight_convert.py

Oneflow-Inc/libai

e473bd3962f07b1e37232d2be39c8257df0ec0f3

[ "Apache-2.0" ]

13

2021-12-29T08:12:08.000Z

2022-03-28T06:59:45.000Z

# coding=utf-8 # Copyright 2021 The OneFlow Authors. All rights reserved. # # 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 logging import oneflow as flow import torch logger = logging.getLogger(__name__) def convert_qkv_weight(cfg, value): """ Convert qkv.weight to be compatible with LiBai transformer layer Args: cfg: config file value: qkv.weight in the loaded checkpoint """ num_heads = cfg.model.num_heads hidden_size = cfg.model.embed_dim head_size = int(hidden_size / num_heads) qkv_weight = ( value.view([3, num_heads, head_size, hidden_size]) .permute(1, 0, 2, 3) .contiguous() .view(hidden_size * 3, hidden_size) ) return qkv_weight def convert_qkv_bias(cfg, value): """ Convert qkv.bias to be compatible with LiBai transformer layer Args: cfg: config file value: qkv.bias in the loaded checkpoint """ num_heads = cfg.model.num_heads hidden_size = cfg.model.embed_dim head_size = int(hidden_size / num_heads) qkv_bias = ( value.view(3, num_heads, head_size).permute(1, 0, 2).contiguous().view(hidden_size * 3) ) return qkv_bias def filter_keys(key, value, cfg): """ Filtering the state_dict keys and values to match LiBai's MAE model """ if "norm1" in key: key = key.replace("norm1", "input_layernorm") elif "attn.qkv" in key: key = key.replace("attn.qkv", "self_attention.query_key_value") if "weight" in key: value = convert_qkv_weight(cfg, value) if "bias" in key: value = convert_qkv_bias(cfg, value) elif "attn.proj" in key: key = key.replace("attn.proj", "self_attention.dense") elif "norm2" in key: key = key.replace("norm2", "post_attention_layernorm") elif "mlp.fc1" in key: key = key.replace("mlp.fc1", "mlp.dense_h_to_4h") elif "mlp.fc2" in key: key = key.replace("mlp.fc2", "mlp.dense_4h_to_h") elif "fc_norm" in key: key = key.replace("fc_norm", "norm") return key, value def load_torch_checkpoint(model, cfg, path="./mae_finetuned_vit_base.pth", strict=False): """ Load checkpoint from the given torch weights. Torch weight can be downloaded from the original repo: https://github.com/facebookresearch/mae """ torch_dict = torch.load(path, map_location="cpu")["model"] parameters = torch_dict new_parameters = dict() for key, value in parameters.items(): if "num_batches_tracked" not in key: # to global tensor key, val = filter_keys(key, value, cfg) val = val.detach().cpu().numpy() val = flow.tensor(val).to_global( sbp=flow.sbp.broadcast, placement=flow.placement("cuda", ranks=[0]) ) new_parameters[key] = val model.load_state_dict(new_parameters, strict=strict) print("Successfully load torch mae checkpoint.") return model

32.509259

95

0.656508

494

3,511

4.520243

0.3583

0.037618

0.025078

0.034483

0.337662

0.211375

0.172862

0.149575

0

0.011606

0.239248

3,511

107

96

32.813084

0.82441

0.312731

0

0.103448

0

0.143539

0.035559

0

1

0.068966

false

0

0.051724

0

0.189655

0.017241

0

null

0

null

0

1

0

ed5a4c9715fe0f81c7675d25ae101b58391d1929

8,462

py

Python

spot/level1.py

K0gata/SGLI_Python_output_tool

1368e0408edd737a5109d0523db6c147faa80b97

[ "MIT" ]

1

2020-08-04T04:17:49.000Z

spot/level1.py

K0gata/SGLI_Python_Open_Tool

1368e0408edd737a5109d0523db6c147faa80b97

[ "MIT" ]

null

spot/level1.py

K0gata/SGLI_Python_Open_Tool

1368e0408edd737a5109d0523db6c147faa80b97

[ "MIT" ]

null

import numpy as np import logging from decimal import Decimal, ROUND_HALF_UP from abc import ABC, abstractmethod, abstractproperty from spot.utility import bilin_2d from spot.config import PROJ_TYPE # ============================= # Level-1 template class # ============================= class L1Interface(ABC): @property @abstractmethod def PROJECTION_TYPE(self): raise NotImplementedError() @property @abstractmethod def ALLOW_PROJECTION_TYPE(self): return NotImplementedError() def __init__(self, h5_file, product_id): self.h5_file = h5_file self.product_id = product_id geo_data_grp_attrs = self.h5_file['Geometry_data'].attrs self.geo_n_pix = geo_data_grp_attrs['Number_of_pixels'][0] self.geo_n_lin = geo_data_grp_attrs['Number_of_lines'][0] img_data_grp_attrs = self.h5_file['Image_data'].attrs self.img_n_pix = img_data_grp_attrs['Number_of_pixels'][0] self.img_n_lin = img_data_grp_attrs['Number_of_lines'][0] def get_product_data(self, prod_name:str): dset = self.h5_file['Image_data/' + prod_name] # Return uint16 type data if the product is QA_flag or Line_tai93 if 'QA_flag' == prod_name or 'Line_tai93' == prod_name: return dset[:] # Validate data = dset[:].astype(np.float32) if 'Error_DN' in dset.attrs: data[data == dset.attrs['Error_DN'][0]] = np.NaN with np.warnings.catch_warnings(): np.warnings.filterwarnings('ignore', r'invalid value encountered in (greater|less)') if 'Maximum_valid_DN' in dset.attrs: data[data > dset.attrs['Maximum_valid_DN'][0]] = np.NaN if 'Minimum_valid_DN' in dset.attrs: data[data < dset.attrs['Minimum_valid_DN'][0]] = np.NaN # Convert DN to physical value data = data * dset.attrs['Slope'][0] + dset.attrs['Offset'][0] return data @abstractmethod def get_geometry_data(self, data_name:str, **kwargs): raise NotImplementedError() @abstractmethod def get_geometry_data_list(self): raise NotImplementedError() def get_product_data_list(self): return list(self.h5_file['/Image_data'].keys()) def get_unit(self, prod_name: str): if 'Rt_' in prod_name: return 'NA' # Get attrs set unit_name = 'Unit' attrs = self.h5_file['/Image_data/' + prod_name].attrs # Get unit if unit_name not in attrs: return 'NA' return attrs[unit_name][0].decode('UTF-8') # ============================= # Level-1 map-projection class # ============================= class Scene(L1Interface): PROJECTION_TYPE = PROJ_TYPE.SCENE.name ALLOW_PROJECTION_TYPE = [PROJECTION_TYPE, PROJ_TYPE.EQR.name] def __init__(self, h5_file, product_id): super().__init__(h5_file, product_id) self.scene_number = h5_file['/Global_attributes'].attrs['Scene_number'][0] self.path_number = h5_file['/Global_attributes'].attrs['RSP_path_number'][0] img_data_grp_attrs = self.h5_file['Image_data'].attrs self.img_spatial_reso = img_data_grp_attrs['Grid_interval'][0] def get_geometry_data(self, data_name: str, **kwargs): interval = kwargs['interval'] dset = self.h5_file['Geometry_data/' + data_name] data = dset[:] if 'Latitude' is not data_name and 'Longitude' is not data_name: data = data.astype(np.float32) * dset.attrs['Slope'][0] + dset.attrs['Offset'][0] # Finish if interval is none if interval is None or interval == 'none': return data # Interpolate raw data if interval == 'auto': interp_interval = dset.attrs['Resampling_interval'][0] else: interp_interval = interval lon_mode = False if 'Longitude' == data_name: lon_mode = True if interp_interval > 1: data = bilin_2d(data, interp_interval, lon_mode) # Trim away the excess pixel/line (data_size_lin, data_size_pxl) = data.shape if (kwargs['fit_img_size'] is True) and (self.img_n_lin <= data_size_lin) and (self.img_n_pix <= data_size_pxl): data = data[:self.img_n_lin, :self.img_n_pix] return data def get_geometry_data_list(self): return list(self.h5_file['/Geometry_data'].keys()) def get_allow_projection_type(self): return self.ALLOW_PROJECTION_TYPE # ============================= # Level-1 sub-processing level class # ============================= class L1B(Scene): # ----------------------------- # Public # ----------------------------- def get_product_data(self, prod_name:str): if 'Land_water_flag' in prod_name: return self._get_land_water_flag() if 'Lt_' in prod_name: return self._get_Lt(prod_name) if 'Rt_' in prod_name: return self._get_Rt(prod_name) if 'Stray_light_correction_flag_' in prod_name: return self._get_stray_light_correction_flag(prod_name) return super().get_product_data(prod_name) # ----------------------------- # Private # ----------------------------- def _get_land_water_flag(self): dset = self.h5_file['Image_data/Land_water_flag'] data = dset[:].astype(np.float32) if 'Error_DN' in dset.attrs: data[data == dset.attrs['Error_value'][0]] = np.NaN with np.warnings.catch_warnings(): np.warnings.filterwarnings('ignore', r'invalid value encountered in (greater|less)') data[data > dset.attrs['Maximum_valid_value'][0]] = np.NaN data[data < dset.attrs['Minimum_valid_value'][0]] = np.NaN return data def _get_Lt(self, prod_name): dset = self.h5_file['Image_data/' + prod_name] dn_data = dset[:] mask = dset.attrs['Mask'][0] data = np.bitwise_and(dn_data, mask).astype(np.float32) data = data * dset.attrs['Slope'] + dset.attrs['Offset'] data[dn_data == dset.attrs['Error_DN']] = np.NaN with np.warnings.catch_warnings(): np.warnings.filterwarnings('ignore', r'invalid value encountered in (greater|less)') data[data > dset.attrs['Maximum_valid_DN'][0]] = np.NaN data[data < dset.attrs['Minimum_valid_DN'][0]] = np.NaN return data def _get_Rt(self, prod_name): prod_name = prod_name.replace('Rt_', 'Lt_') dset = self.h5_file['Image_data/' + prod_name] dn_data = dset[:] mask = dset.attrs['Mask'][0] data = np.bitwise_and(dn_data, mask).astype(np.float32) data = data * dset.attrs['Slope_reflectance'] + dset.attrs['Offset_reflectance'] data[dn_data == dset.attrs['Error_DN']] = np.NaN with np.warnings.catch_warnings(): np.warnings.filterwarnings('ignore', r'invalid value encountered in (greater|less)') data[data > dset.attrs['Maximum_valid_DN'][0]] = np.NaN data[data < dset.attrs['Minimum_valid_DN'][0]] = np.NaN cos_theta_0 = np.cos(np.deg2rad(self.get_geometry_data('Solar_zenith', interval='auto', fit_img_size=True))) data = data / cos_theta_0 return data def _get_stray_light_correction_flag(self, prod_name): prod_name = prod_name.replace('Stray_light_correction_flag_', 'Lt_') dset = self.h5_file['Image_data/' + prod_name] dn_data = dset[:] data = np.bitwise_and(dn_data, 0x8000) data[dn_data == dset.attrs['Error_DN']] = 0 return data > 0 class VNRL1B(L1B): def get_product_data_list(self): prod_list = super().get_product_data_list() for prod in prod_list: if 'Lt_' in prod: prod_list.append(prod.replace('Lt', 'Rt')) prod_list.append(prod.replace('Lt', 'Stray_light_correction_flag')) prod_list = sorted(prod_list) return prod_list class IRSL1B(L1B): def get_product_data_list(self): prod_list = super().get_product_data_list() for prod in prod_list: if 'Lt_SW' in prod: prod_list.append(prod.replace('Lt', 'Rt')) prod_list.append(prod.replace('Lt', 'Stray_light_correction_flag')) prod_list = sorted(prod_list) return prod_list # EOF

34.538776

120

0.610021

1,113

8,462

4.337826

0.150045

0.052196

0.043082

0.045775

0.600249

0.547639

0.490472

0.439105

0.36599

0.335128

0

0.013121

0.243441

8,462

244

121

34.680328

0.741018

0.072205

0

0.462963

0

0.136852

0.017378

0

0.000767

0

1

0.117284

false

0

0.037037

0.024691

0.333333

0

null

0

null

0

1

0

ed5a7dc4339280b02e5e632da64cfe3100fda887

345

py

Python

168. Excel Sheet Column Title.py

Alvin1994/leetcode-python3-

ba2bde873c925554cc39f2bd13be81967713477d

[ "Apache-2.0" ]

null

168. Excel Sheet Column Title.py

Alvin1994/leetcode-python3-

ba2bde873c925554cc39f2bd13be81967713477d

[ "Apache-2.0" ]

null

168. Excel Sheet Column Title.py

Alvin1994/leetcode-python3-

ba2bde873c925554cc39f2bd13be81967713477d

[ "Apache-2.0" ]

null

class Solution: # @return a string def convertToTitle(self, n: int) -> str: capitals = [chr(x) for x in range(ord('A'), ord('Z')+1)] result = [] while n > 0: result.insert(0, capitals[(n-1)%len(capitals)]) n = (n-1) % len(capitals) # result.reverse() return ''.join(result)

34.5

64

0.510145

45

345

3.911111

0.6

0.102273

0.056818

0.147727

0

0.021186

0.315942

345

10

65

34.5

0.724576

0.095652

0

0.006452

0

1

0.125

false

0

0.375

0

null

0

null

0

1

0

ed5ab9e7476a3e24312d9ef871509f4e43e86312

18,788

py

Python

devil/devil/utils/cmd_helper.py

Martijnve23/catapult

5c63b19d221af6a12889e8727acc85d93892cab7

[ "BSD-3-Clause" ]

1,894

2015-04-17T18:29:53.000Z

2022-03-28T22:41:06.000Z

devil/devil/utils/cmd_helper.py

Martijnve23/catapult

5c63b19d221af6a12889e8727acc85d93892cab7

[ "BSD-3-Clause" ]

4,640

2015-07-08T16:19:08.000Z

2019-12-02T15:01:27.000Z

infra/services/android_docker/third_party/devil/utils/cmd_helper.py

NDevTK/chromium-infra

d38e088e158d81f7f2065a38aa1ea1894f735ec4

[ "BSD-3-Clause" ]

698

2015-06-02T19:18:35.000Z

2022-03-29T16:57:15.000Z

# Copyright (c) 2012 The Chromium Authors. All rights reserved. # Use of this source code is governed by a BSD-style license that can be # found in the LICENSE file. """A wrapper for subprocess to make calling shell commands easier.""" import codecs import logging import os import pipes import select import signal import string import subprocess import sys import time CATAPULT_ROOT_PATH = os.path.abspath( os.path.join(os.path.dirname(__file__), '..', '..', '..')) SIX_PATH = os.path.join(CATAPULT_ROOT_PATH, 'third_party', 'six') if SIX_PATH not in sys.path: sys.path.append(SIX_PATH) import six from devil import base_error logger = logging.getLogger(__name__) _SafeShellChars = frozenset(string.ascii_letters + string.digits + '@%_-+=:,./') # Cache the string-escape codec to ensure subprocess can find it # later. Return value doesn't matter. if six.PY2: codecs.lookup('string-escape') def SingleQuote(s): """Return an shell-escaped version of the string using single quotes. Reliably quote a string which may contain unsafe characters (e.g. space, quote, or other special characters such as '$'). The returned value can be used in a shell command line as one token that gets to be interpreted literally. Args: s: The string to quote. Return: The string quoted using single quotes. """ return pipes.quote(s) def DoubleQuote(s): """Return an shell-escaped version of the string using double quotes. Reliably quote a string which may contain unsafe characters (e.g. space or quote characters), while retaining some shell features such as variable interpolation. The returned value can be used in a shell command line as one token that gets to be further interpreted by the shell. The set of characters that retain their special meaning may depend on the shell implementation. This set usually includes: '$', '`', '\', '!', '*', and '@'. Args: s: The string to quote. Return: The string quoted using double quotes. """ if not s: return '""' elif all(c in _SafeShellChars for c in s): return s else: return '"' + s.replace('"', '\\"') + '"' def ShrinkToSnippet(cmd_parts, var_name, var_value): """Constructs a shell snippet for a command using a variable to shrink it. Takes into account all quoting that needs to happen. Args: cmd_parts: A list of command arguments. var_name: The variable that holds var_value. var_value: The string to replace in cmd_parts with $var_name Returns: A shell snippet that does not include setting the variable. """ def shrink(value): parts = (x and SingleQuote(x) for x in value.split(var_value)) with_substitutions = ('"$%s"' % var_name).join(parts) return with_substitutions or "''" return ' '.join(shrink(part) for part in cmd_parts) def Popen(args, stdin=None, stdout=None, stderr=None, shell=None, cwd=None, env=None): # preexec_fn isn't supported on windows. # pylint: disable=unexpected-keyword-arg if sys.platform == 'win32': close_fds = (stdin is None and stdout is None and stderr is None) preexec_fn = None else: close_fds = True preexec_fn = lambda: signal.signal(signal.SIGPIPE, signal.SIG_DFL) if six.PY2: return subprocess.Popen( args=args, cwd=cwd, stdin=stdin, stdout=stdout, stderr=stderr, shell=shell, close_fds=close_fds, env=env, preexec_fn=preexec_fn ) else: # opens stdout in text mode, so that caller side always get 'str', # and there will be no type mismatch error. # Ignore any decoding error, so that caller will not crash due to # uncaught exception. Decoding errors are unavoidable, as we # do not know the encoding of the output, and in some output there # will be multiple encodings (e.g. adb logcat) return subprocess.Popen( args=args, cwd=cwd, stdin=stdin, stdout=stdout, stderr=stderr, shell=shell, close_fds=close_fds, env=env, preexec_fn=preexec_fn, universal_newlines=True, encoding='utf-8', errors='ignore' ) def Call(args, stdout=None, stderr=None, shell=None, cwd=None, env=None): pipe = Popen( args, stdout=stdout, stderr=stderr, shell=shell, cwd=cwd, env=env) pipe.communicate() return pipe.wait() def RunCmd(args, cwd=None): """Opens a subprocess to execute a program and returns its return value. Args: args: A string or a sequence of program arguments. The program to execute is the string or the first item in the args sequence. cwd: If not None, the subprocess's current directory will be changed to |cwd| before it's executed. Returns: Return code from the command execution. """ logger.debug(str(args) + ' ' + (cwd or '')) return Call(args, cwd=cwd) def GetCmdOutput(args, cwd=None, shell=False, env=None): """Open a subprocess to execute a program and returns its output. Args: args: A string or a sequence of program arguments. The program to execute is the string or the first item in the args sequence. cwd: If not None, the subprocess's current directory will be changed to |cwd| before it's executed. shell: Whether to execute args as a shell command. env: If not None, a mapping that defines environment variables for the subprocess. Returns: Captures and returns the command's stdout. Prints the command's stderr to logger (which defaults to stdout). """ (_, output) = GetCmdStatusAndOutput(args, cwd, shell, env) return output def _ValidateAndLogCommand(args, cwd, shell): if isinstance(args, six.string_types): if not shell: raise Exception('string args must be run with shell=True') else: if shell: raise Exception('array args must be run with shell=False') args = ' '.join(SingleQuote(str(c)) for c in args) if cwd is None: cwd = '' else: cwd = ':' + cwd logger.debug('[host]%s> %s', cwd, args) return args def GetCmdStatusAndOutput(args, cwd=None, shell=False, env=None, merge_stderr=False): """Executes a subprocess and returns its exit code and output. Args: args: A string or a sequence of program arguments. The program to execute is the string or the first item in the args sequence. cwd: If not None, the subprocess's current directory will be changed to |cwd| before it's executed. shell: Whether to execute args as a shell command. Must be True if args is a string and False if args is a sequence. env: If not None, a mapping that defines environment variables for the subprocess. merge_stderr: If True, captures stderr as part of stdout. Returns: The 2-tuple (exit code, stdout). """ status, stdout, stderr = GetCmdStatusOutputAndError( args, cwd=cwd, shell=shell, env=env, merge_stderr=merge_stderr) if stderr: logger.critical('STDERR: %s', stderr) logger.debug('STDOUT: %s%s', stdout[:4096].rstrip(), '<truncated>' if len(stdout) > 4096 else '') return (status, stdout) def StartCmd(args, cwd=None, shell=False, env=None): """Starts a subprocess and returns a handle to the process. Args: args: A string or a sequence of program arguments. The program to execute is the string or the first item in the args sequence. cwd: If not None, the subprocess's current directory will be changed to |cwd| before it's executed. shell: Whether to execute args as a shell command. Must be True if args is a string and False if args is a sequence. env: If not None, a mapping that defines environment variables for the subprocess. Returns: A process handle from subprocess.Popen. """ _ValidateAndLogCommand(args, cwd, shell) return Popen( args, stdout=subprocess.PIPE, stderr=subprocess.PIPE, shell=shell, cwd=cwd, env=env) def GetCmdStatusOutputAndError(args, cwd=None, shell=False, env=None, merge_stderr=False): """Executes a subprocess and returns its exit code, output, and errors. Args: args: A string or a sequence of program arguments. The program to execute is the string or the first item in the args sequence. cwd: If not None, the subprocess's current directory will be changed to |cwd| before it's executed. shell: Whether to execute args as a shell command. Must be True if args is a string and False if args is a sequence. env: If not None, a mapping that defines environment variables for the subprocess. merge_stderr: If True, captures stderr as part of stdout. Returns: The 3-tuple (exit code, stdout, stderr). """ _ValidateAndLogCommand(args, cwd, shell) stderr = subprocess.STDOUT if merge_stderr else subprocess.PIPE pipe = Popen( args, stdout=subprocess.PIPE, stderr=stderr, shell=shell, cwd=cwd, env=env) stdout, stderr = pipe.communicate() return (pipe.returncode, stdout, stderr) class TimeoutError(base_error.BaseError): """Module-specific timeout exception.""" def __init__(self, output=None): super(TimeoutError, self).__init__('Timeout') self._output = output @property def output(self): return self._output def _read_and_decode(fd, buffer_size): data = os.read(fd, buffer_size) if data and six.PY3: data = data.decode('utf-8', errors='ignore') return data def _IterProcessStdoutFcntl(process, iter_timeout=None, timeout=None, buffer_size=4096, poll_interval=1): """An fcntl-based implementation of _IterProcessStdout.""" # pylint: disable=too-many-nested-blocks import fcntl try: # Enable non-blocking reads from the child's stdout. child_fd = process.stdout.fileno() fl = fcntl.fcntl(child_fd, fcntl.F_GETFL) fcntl.fcntl(child_fd, fcntl.F_SETFL, fl | os.O_NONBLOCK) end_time = (time.time() + timeout) if timeout else None iter_end_time = (time.time() + iter_timeout) if iter_timeout else None while True: if end_time and time.time() > end_time: raise TimeoutError() if iter_end_time and time.time() > iter_end_time: yield None iter_end_time = time.time() + iter_timeout if iter_end_time: iter_aware_poll_interval = min(poll_interval, max(0, iter_end_time - time.time())) else: iter_aware_poll_interval = poll_interval read_fds, _, _ = select.select([child_fd], [], [], iter_aware_poll_interval) if child_fd in read_fds: data = _read_and_decode(child_fd, buffer_size) if not data: break yield data if process.poll() is not None: # If process is closed, keep checking for output data (because of timing # issues). while True: read_fds, _, _ = select.select([child_fd], [], [], iter_aware_poll_interval) if child_fd in read_fds: data = _read_and_decode(child_fd, buffer_size) if data: yield data continue break break finally: try: if process.returncode is None: # Make sure the process doesn't stick around if we fail with an # exception. process.kill() except OSError: pass process.wait() def _IterProcessStdoutQueue(process, iter_timeout=None, timeout=None, buffer_size=4096, poll_interval=1): """A Queue.Queue-based implementation of _IterProcessStdout. TODO(jbudorick): Evaluate whether this is a suitable replacement for _IterProcessStdoutFcntl on all platforms. """ # pylint: disable=unused-argument if six.PY3: import queue else: import Queue as queue import threading stdout_queue = queue.Queue() def read_process_stdout(): # TODO(jbudorick): Pick an appropriate read size here. while True: try: output_chunk = _read_and_decode(process.stdout.fileno(), buffer_size) except IOError: break stdout_queue.put(output_chunk, True) if not output_chunk and process.poll() is not None: break reader_thread = threading.Thread(target=read_process_stdout) reader_thread.start() end_time = (time.time() + timeout) if timeout else None try: while True: if end_time and time.time() > end_time: raise TimeoutError() try: s = stdout_queue.get(True, iter_timeout) if not s: break yield s except queue.Empty: yield None finally: try: if process.returncode is None: # Make sure the process doesn't stick around if we fail with an # exception. process.kill() except OSError: pass process.wait() reader_thread.join() _IterProcessStdout = (_IterProcessStdoutQueue if sys.platform == 'win32' else _IterProcessStdoutFcntl) """Iterate over a process's stdout. This is intentionally not public. Args: process: The process in question. iter_timeout: An optional length of time, in seconds, to wait in between each iteration. If no output is received in the given time, this generator will yield None. timeout: An optional length of time, in seconds, during which the process must finish. If it fails to do so, a TimeoutError will be raised. buffer_size: The maximum number of bytes to read (and thus yield) at once. poll_interval: The length of time to wait in calls to `select.select`. If iter_timeout is set, the remaining length of time in the iteration may take precedence. Raises: TimeoutError: if timeout is set and the process does not complete. Yields: basestrings of data or None. """ def GetCmdStatusAndOutputWithTimeout(args, timeout, cwd=None, shell=False, logfile=None, env=None): """Executes a subprocess with a timeout. Args: args: List of arguments to the program, the program to execute is the first element. timeout: the timeout in seconds or None to wait forever. cwd: If not None, the subprocess's current directory will be changed to |cwd| before it's executed. shell: Whether to execute args as a shell command. Must be True if args is a string and False if args is a sequence. logfile: Optional file-like object that will receive output from the command as it is running. env: If not None, a mapping that defines environment variables for the subprocess. Returns: The 2-tuple (exit code, output). Raises: TimeoutError on timeout. """ _ValidateAndLogCommand(args, cwd, shell) output = six.StringIO() process = Popen( args, cwd=cwd, shell=shell, stdout=subprocess.PIPE, stderr=subprocess.STDOUT, env=env) try: for data in _IterProcessStdout(process, timeout=timeout): if logfile: logfile.write(data) output.write(data) except TimeoutError: raise TimeoutError(output.getvalue()) str_output = output.getvalue() logger.debug('STDOUT+STDERR: %s%s', str_output[:4096].rstrip(), '<truncated>' if len(str_output) > 4096 else '') return process.returncode, str_output def IterCmdOutputLines(args, iter_timeout=None, timeout=None, cwd=None, shell=False, env=None, check_status=True): """Executes a subprocess and continuously yields lines from its output. Args: args: List of arguments to the program, the program to execute is the first element. iter_timeout: Timeout for each iteration, in seconds. timeout: Timeout for the entire command, in seconds. cwd: If not None, the subprocess's current directory will be changed to |cwd| before it's executed. shell: Whether to execute args as a shell command. Must be True if args is a string and False if args is a sequence. env: If not None, a mapping that defines environment variables for the subprocess. check_status: A boolean indicating whether to check the exit status of the process after all output has been read. Yields: The output of the subprocess, line by line. Raises: CalledProcessError if check_status is True and the process exited with a non-zero exit status. """ cmd = _ValidateAndLogCommand(args, cwd, shell) process = Popen( args, cwd=cwd, shell=shell, env=env, stdout=subprocess.PIPE, stderr=subprocess.STDOUT) return _IterCmdOutputLines( process, cmd, iter_timeout=iter_timeout, timeout=timeout, check_status=check_status) def _IterCmdOutputLines(process, cmd, iter_timeout=None, timeout=None, check_status=True): buffer_output = '' iter_end = None cur_iter_timeout = None if iter_timeout: iter_end = time.time() + iter_timeout cur_iter_timeout = iter_timeout for data in _IterProcessStdout( process, iter_timeout=cur_iter_timeout, timeout=timeout): if iter_timeout: # Check whether the current iteration has timed out. cur_iter_timeout = iter_end - time.time() if data is None or cur_iter_timeout < 0: yield None iter_end = time.time() + iter_timeout continue else: assert data is not None, ( 'Iteration received no data despite no iter_timeout being set. ' 'cmd: %s' % cmd) # Construct lines to yield from raw data. buffer_output += data has_incomplete_line = buffer_output[-1] not in '\r\n' lines = buffer_output.splitlines() buffer_output = lines.pop() if has_incomplete_line else '' for line in lines: yield line if iter_timeout: iter_end = time.time() + iter_timeout if buffer_output: yield buffer_output if check_status and process.returncode: raise subprocess.CalledProcessError(process.returncode, cmd)

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null

0

null

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1

0

ed5b5860c856a4418e7eeb1cf777cb4c10722142

2,845

py

Python

api/to_astm.py

urchinpro/L2-forms

37f33386984efbb2d1e92c73d915256247801109

[ "MIT" ]

null

api/to_astm.py

urchinpro/L2-forms

37f33386984efbb2d1e92c73d915256247801109

[ "MIT" ]

null

api/to_astm.py

urchinpro/L2-forms

37f33386984efbb2d1e92c73d915256247801109

[ "MIT" ]

null

import itertools from astm import codec from collections import defaultdict from django.utils import timezone import directions.models as directions import directory.models as directory import api.models as api import simplejson as json def get_astm_header() -> list: return ['H|\\^&', None, None, ['1', '2.00'], None, None, None, None, None, None, 'P', '1.00', timezone.now().strftime("%Y%m%d%H%M%S")] def get_leave() -> list: return ['L', 1, 'N'] def get_patient() -> list: return ['P', 1] def get_iss_direction(direction: directions.Napravleniya, analyzer: api.Analyzer, full=False) -> list: r = [] n = 0 iss_list = directions.Issledovaniya.objects.filter(napravleniye=direction) if not full: iss_list = iss_list.filter(doc_confirmation__isnull=True) for i in iss_list: researches = defaultdict(list) for fraction in directory.Fractions.objects.filter(research=i.research, relationfractionastm__analyzer=analyzer, hide=False): rel = api.RelationFractionASTM.objects.filter(fraction=fraction, analyzer=analyzer) if not rel.exists(): continue rel = rel[0] tube = directions.TubesRegistration.objects.filter(type__fractions=fraction) if not tube.exists(): continue tube = tube[0] researches[tube.pk].append(rel.astm_field) for tpk in researches: n += 1 r.append(['O', n, tpk, None, [[None, x, None, None] for x in researches[tpk]]]) return r def encode(m) -> str: return codec.iter_encode(m) def get_astm(directions_list, analyzer: api.Analyzer, full=False, out=None) -> str: iss = [get_iss_direction(x, analyzer, full) for x in directions_list] m = [get_astm_header(), get_patient()] m = list(itertools.chain(m, *iss)) m.append(get_leave()) if out: out.write(json.dumps(m)) return encode(m) def get_iss_astm(issledovaniya: list, app: api.Application, need_astm=False): m = [get_astm_header(), get_patient()] n = 0 researches = defaultdict(list) for row in issledovaniya: k = row["pk"] i = row["iss"] for fraction in directory.Fractions.objects.filter(research=i.research, relationfractionastm__application_api=app, hide=False): rel = api.RelationFractionASTM.objects.filter(fraction=fraction, application_api=app) if not rel.exists(): continue rel = rel[0] if rel.is_code: researches[k].append([None, None, None, rel.astm_field]) else: researches[k].append([None, rel.astm_field, None, None]) for tpk in researches: n += 1 m.append(['O', n, tpk, None, researches[tpk]]) m.append(get_leave()) return encode(m)

34.277108

138

0.636555

372

2,845

4.755376

0.247312

0.049746

0.033917

0.027134

0.308649

0.246467

0.196721

0.163934

0.091577

0

0.007404

0.240422

2,845

82

139

34.695122

0.811199

0

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0

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0

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false

0

0.119403

0.059701

0.328358

0

null

0

null

0

1

0

ed5c8a4473db3e1f846fdf5ddd27546849b2b2e4

3,091

py

Python

src/compas_plotters/artists/lineartist.py

XingxinHE/compas

d2901dbbacdaf4694e5adae78ba8f093f10532bf

[ "MIT" ]

null

src/compas_plotters/artists/lineartist.py

XingxinHE/compas

d2901dbbacdaf4694e5adae78ba8f093f10532bf

[ "MIT" ]

null

src/compas_plotters/artists/lineartist.py

XingxinHE/compas

d2901dbbacdaf4694e5adae78ba8f093f10532bf

[ "MIT" ]

null

from compas_plotters.artists import Artist from matplotlib.lines import Line2D from compas.geometry import intersection_line_box_xy __all__ = ['LineArtist'] class LineArtist(Artist): """""" zorder = 1000 def __init__(self, line, draw_points=False, draw_as_segment=False, linewidth=1.0, linestyle='solid', color=(0, 0, 0)): super(LineArtist, self).__init__(line) self._mpl_line = None self._start_artist = None self._end_artist = None self._segment_artist = None self._draw_points = draw_points self._draw_as_segment = draw_as_segment self.line = line self.linewidth = linewidth self.linestyle = linestyle self.color = color def clip(self): xlim, ylim = self.plotter.viewbox xmin, xmax = xlim ymin, ymax = ylim box = [[xmin, ymin], [xmax, ymin], [xmax, ymax], [xmin, ymax]] return intersection_line_box_xy(self.line, box) @property def data(self): return [self.line.start[:2], self.line.end[:2]] def draw(self): if self._draw_as_segment: x0, y0 = self.line.start[:2] x1, y1 = self.line.end[:2] line2d = Line2D([x0, x1], [y0, y1], linewidth=self.linewidth, linestyle=self.linestyle, color=self.color, zorder=self.zorder) self._mpl_line = self.plotter.axes.add_line(line2d) if self._draw_points: self._start_artist = self.plotter.add(self.line.start) self._end_artist = self.plotter.add(self.line.end) else: points = self.clip() if points: p0, p1 = points x0, y0 = p0[:2] x1, y1 = p1[:2] line2d = Line2D([x0, x1], [y0, y1], linewidth=self.linewidth, linestyle=self.linestyle, color=self.color, zorder=self.zorder) self._mpl_line = self.plotter.axes.add_line(line2d) if self._draw_points: self._start_artist = self.plotter.add(self.line.start) self._end_artist = self.plotter.add(self.line.end) def redraw(self): if self._draw_as_segment: x0, y0 = self.line.start[:2] x1, y1 = self.line.end[:2] self._mpl_line.set_xdata([x0, x1]) self._mpl_line.set_ydata([y0, y1]) self._mpl_line.set_color(self.color) self._mpl_line.set_linewidth(self.linewidth) else: points = self.clip() if points: p0, p1 = points x0, y0 = p0[:2] x1, y1 = p1[:2] self._mpl_line.set_xdata([x0, x1]) self._mpl_line.set_ydata([y0, y1]) self._mpl_line.set_color(self.color) self._mpl_line.set_linewidth(self.linewidth)

36.364706

122

0.530573

363

3,091

4.280992

0.179063

0.066924

0.077864

0.072072

0.574003

0

0.033486

0.362342

3,091

84

123

36.797619

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0

1

0.068493

false

0

0.041096

0.013699

0.164384

0

null

0

null

0

1

0

ed5d3821ab68704ffac0f126c20afbf8dae239de

1,018

py

Python

plot2d_artificial_dataset1_silvq.py

manome/python-silvq

b50d7486e970fbe9a5b66dd3fc5beb8b5de8ca2f

[ "BSD-3-Clause" ]

null

plot2d_artificial_dataset1_silvq.py

manome/python-silvq

b50d7486e970fbe9a5b66dd3fc5beb8b5de8ca2f

[ "BSD-3-Clause" ]

null

plot2d_artificial_dataset1_silvq.py

manome/python-silvq

b50d7486e970fbe9a5b66dd3fc5beb8b5de8ca2f

[ "BSD-3-Clause" ]

null

# -*- encoding: utf8 -*- import numpy as np from sklearn.metrics import accuracy_score from sklearn.model_selection import train_test_split from lvq import SilvqModel from lvq.utils import plot2d def main(): # Load dataset dataset = np.loadtxt('data/artificial_dataset1.csv', delimiter=',') x = dataset[:, :-1].astype('float64') y = dataset[:, -1].astype('int64') # Split dataset into training set and test set x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.2, random_state=3, shuffle=True, stratify=y) # Generating model model = SilvqModel(x.shape[1], theta=0.8, bias_type='ls') # Training the model model.fit(x_train, y_train, epochs=30) # Predict the response for test dataset y_predict = model.predict(x_test) # Evaluating the model print('Accuracy: %.3f' %accuracy_score(y_test, y_predict)) # Plot prediction results and prototypes plot2d(model, x, y, title='Artificial dataset1') if __name__ == '__main__': main()

30.848485

118

0.697446

147

1,018

4.632653

0.496599

0.022026

0.041116

0

0.024038

0.182711

1,018

32

119

31.8125

0.794471

0.210216

0

0.10566

0.03522

0

1

0.058824

false

0

0.294118

0

0.352941

0.058824

0

null

0

null

0

1

0

ed5d69e17539392ab832fd82b04ce64e261c7b31

7,727

py

Python

classification_experiments/Fine-Tuned-ResNet-50/Fine-Tuned-ResNet-50.py

ifr1m/hyper-kvasir

21cc366e78c0cb4e180a26a0e441d6c0d5171da9

[ "CC-BY-4.0" ]

38

2019-12-20T13:17:09.000Z

2022-03-20T08:39:40.000Z

classification_experiments/Fine-Tuned-ResNet-50/Fine-Tuned-ResNet-50.py

smaranjitghose/hyper-kvasir

b4815d151ef90cffa1bbc8fbf97cd091a20ce600

[ "CC-BY-4.0" ]

2

2021-01-12T10:45:13.000Z

2021-01-28T06:14:45.000Z

classification_experiments/Fine-Tuned-ResNet-50/Fine-Tuned-ResNet-50.py

smaranjitghose/hyper-kvasir

b4815d151ef90cffa1bbc8fbf97cd091a20ce600

[ "CC-BY-4.0" ]

11

2020-03-24T17:58:04.000Z

2021-12-09T16:12:16.000Z

#!/usr/bin/env python # coding: utf-8 # In[ ]: #Importing all required libraries # In[ ]: from __future__ import absolute_import, division, print_function, unicode_literals # In[ ]: #Checking for correct cuda and tf versions from tensorflow.python.platform import build_info as tf_build_info print(tf_build_info.cuda_version_number) # 9.0 in v1.10.0 print(tf_build_info.cudnn_version_number) # 7 in v1.10.0 # In[ ]: import tensorflow as tf import pathlib from tensorflow.keras.models import Sequential from tensorflow.keras.layers import Dense, Conv2D, Flatten, Dropout, MaxPooling2D from tensorflow.keras.preprocessing.image import ImageDataGenerator import os import numpy as np import matplotlib.pyplot as plt # In[ ]: AUTOTUNE = tf.data.experimental.AUTOTUNE # In[ ]: import IPython.display as display from PIL import Image import numpy as np import matplotlib.pyplot as plt import os # In[ ]: tf.__version__ # In[ ]: #Train and test data folder train_data_dir = "\\hyper-kvasir\\splits\\all\\1" test_data_dir = "\\hyper-kvasir\\splits\\all\\0" # In[ ]: train_data_dir = pathlib.Path(train_data_dir) test_data_dir = pathlib.Path(test_data_dir) # In[ ]: #count how many images are there image_count = len(list(train_data_dir.glob('*/*.jpg'))) image_count # In[ ]: total_train = len(list(train_data_dir.glob('*/*.jpg'))) total_val = len(list(test_data_dir.glob('*/*.jpg'))) # In[ ]: #get the class names CLASS_NAMES = np.array([item.name for item in train_data_dir.glob('*') if item.name != "LICENSE.txt"]) CLASS_NAMES # In[ ]: #Define parameter for training batch_size = 32 IMG_HEIGHT = 224 IMG_WIDTH = 224 STEPS_PER_EPOCH = np.ceil(image_count/batch_size) epochs = 8 num_classes = len(CLASS_NAMES) #23 # In[ ]: #We use image data generators to load the images and prepare them for the training train_image_generator = ImageDataGenerator() # Generator for our training data validation_image_generator = ImageDataGenerator() # Generator for our validation data train_data_gen = train_image_generator.flow_from_directory(directory=str(train_data_dir), batch_size=batch_size, shuffle=True, target_size=(IMG_HEIGHT, IMG_WIDTH), classes = list(CLASS_NAMES), class_mode='categorical' ) val_data_gen = validation_image_generator.flow_from_directory(directory=str(test_data_dir), batch_size=batch_size, shuffle=True, target_size=(IMG_HEIGHT, IMG_WIDTH), class_mode='categorical', classes = list(CLASS_NAMES) ) #get class order from directories print(train_data_gen.class_indices.keys()) print(val_data_gen.class_indices.keys()) # In[ ]: IMG_SIZE = 224 IMG_SHAPE = (IMG_SIZE, IMG_SIZE, 3) # base model from the pre-trained model. Resnet 50 in this case base_model = tf.keras.applications.ResNet50(input_shape=IMG_SHAPE, include_top=False, weights='imagenet') base_model.trainable = False # In[ ]: #add new classification layer x = base_model.output x = tf.keras.layers.GlobalAveragePooling2D()(x) x = tf.keras.layers.Dense(num_classes,activation='softmax')(x) model = tf.keras.models.Model(inputs=base_model.input, outputs=x) base_learning_rate = 0.001 model.compile(optimizer=tf.keras.optimizers.Adam(lr=base_learning_rate), loss='categorical_crossentropy', metrics=['accuracy']) # In[ ]: #fit the model history = model.fit_generator( train_data_gen, steps_per_epoch=total_train // batch_size, epochs=epochs, validation_data=val_data_gen, validation_steps=total_val // batch_size ) # In[ ]: #create training plots history acc = history.history['accuracy'] val_acc = history.history['val_accuracy'] loss = history.history['loss'] val_loss = history.history['val_loss'] epochs_range = range(epochs) plt.figure(figsize=(8, 8)) plt.subplot(1, 2, 1) plt.plot(epochs_range, acc, label='Training Accuracy') plt.plot(epochs_range, val_acc, label='Validation Accuracy') plt.legend(loc='lower right') plt.title('Training and Validation Accuracy') plt.subplot(1, 2, 2) plt.plot(epochs_range, loss, label='Training Loss') plt.plot(epochs_range, val_loss, label='Validation Loss') plt.legend(loc='upper right') plt.title('Training and Validation Loss') plt.show() # In[ ]: base_model.trainable = True #now we want to train the base model # In[ ]: # How many layers are in the base model print("Layers base model: ", len(base_model.layers)) # Fine tune from layer x fine_tune_at = 100 # Freeze all the layers before the fine tune starting layer for layer in base_model.layers[:fine_tune_at]: layer.trainable = False # In[ ]: model.compile(loss='categorical_crossentropy', optimizer = tf.keras.optimizers.RMSprop(lr=base_learning_rate/10), metrics=['accuracy']) # In[ ]: model.summary() # In[ ]: #Fine tune step initial_epochs = 7 fine_tune_epochs = 3 total_epochs = initial_epochs + fine_tune_epochs train_batches = total_train // batch_size print(total_val // batch_size) validation_batches = total_val // batch_size history_fine = model.fit_generator( train_data_gen, steps_per_epoch=total_train // batch_size, epochs=total_epochs, initial_epoch = history.epoch[-1], validation_data=val_data_gen, validation_steps=total_val // batch_size ) # In[ ]: acc += history_fine.history['accuracy'] val_acc += history_fine.history['val_accuracy'] loss += history_fine.history['loss'] val_loss += history_fine.history['val_loss'] # In[ ]: #Plot fine tuning plt.figure(figsize=(8, 8)) plt.subplot(2, 1, 1) plt.plot(acc, label='Training Accuracy') plt.plot(val_acc, label='Validation Accuracy') plt.ylim([0.8, 1]) plt.plot([initial_epochs-1,initial_epochs-1], plt.ylim(), label='Start Fine Tuning') plt.legend(loc='lower right') plt.title('Training and Validation Accuracy') plt.subplot(2, 1, 2) plt.plot(loss, label='Training Loss') plt.plot(val_loss, label='Validation Loss') plt.ylim([0, 1.0]) plt.plot([initial_epochs-1,initial_epochs-1], plt.ylim(), label='Start Fine Tuning') plt.legend(loc='upper right') plt.title('Training and Validation Loss') plt.xlabel('epoch') plt.show() # In[ ]: #model save and load import os # In[ ]: #some time stamp from datetime import datetime # current date and time. now = datetime.now() timestamp = datetime.timestamp(now) print("timestamp =", timestamp) # In[ ]: mode_filename = str(timestamp)+'mymodel.h5' model.save(model_filename) # In[ ]: #To apply the model on new data new_model = tf.keras.models.load_model(model_filename) # Show the model architecture new_model.summary() # In[ ]: from tensorflow.keras.preprocessing import image #image directory containing images to test img_dir="\\polyps" for i,img in enumerate(os.listdir(img_dir)): tmpimage = image.load_img(os.path.join(img_dir,img), target_size=(IMG_SIZE,IMG_SIZE)) tmpimage = np.expand_dims(tmpimage, axis=0).astype('float32') result_class=new_model.predict(tmpimage) print(img,";",CLASS_NAMES[result_class.argmax(axis=-1)])

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0.237452

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0

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0

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0

null

0

null

0

1

0

ed5f32dd2cd9143c086d6a609f05220bf9f92fde

12,380

py

Python

test/functional/fantasygold_opcall.py

FantasyGold/FantasyGold-Core

afff8871e770045e468e2f536ede9db0dff889d5

[ "MIT" ]

13

2018-04-30T21:43:40.000Z

2020-12-07T11:06:47.000Z

test/functional/fantasygold_opcall.py

donoel2/FantasyGold-Core

afff8871e770045e468e2f536ede9db0dff889d5

[ "MIT" ]

4

2018-05-10T00:18:18.000Z

2019-07-08T23:12:54.000Z

test/functional/fantasygold_opcall.py

donoel2/FantasyGold-Core

afff8871e770045e468e2f536ede9db0dff889d5

[ "MIT" ]

13

2018-04-30T17:41:54.000Z

2020-12-08T18:24:06.000Z

#!/usr/bin/env python3 # Copyright (c) 2015-2016 The Bitcoin Core developers # Distributed under the MIT software license, see the accompanying # file COPYING or http://www.opensource.org/licenses/mit-license.php. from test_framework.test_framework import BitcoinTestFramework from test_framework.util import * from test_framework.script import * from test_framework.mininode import * from test_framework.fantasygold import * from test_framework.fantasygoldconfig import * import sys class OpCallTest(BitcoinTestFramework): def set_test_params(self): self.setup_clean_chain = True self.num_nodes = 2 self.extra_args = [['-txindex=1']]*2 def send_one_op_call_tx_with_counter_check(self, outputs, counter_should_increase_by=0, input_value=500000000, should_throw=False): # 61bc221a counter() old_out = int(self.node.callcontract(self.contract_address, "61bc221a")['executionResult']['output'], 16) inpt = make_vin(self.node, input_value) tx = make_transaction(self.node, [inpt], outputs) if should_throw: try: self.node.sendrawtransaction(tx) assert(False) except JSONRPCException as e: print(e) pass else: self.node.sendrawtransaction(tx) self.node.generate(1) sync_blocks(self.nodes) for i in range(2): # 61bc221a counter() out = int(self.nodes[i].callcontract(self.contract_address, "61bc221a")['executionResult']['output'], 16) assert(out-old_out == counter_should_increase_by) def send_multiple_op_call_txs_with_counter_check(self, num_txs, outputs, counter_should_increase_by): # 61bc221a counter() old_out = int(self.node.callcontract(self.contract_address, "61bc221a")['executionResult']['output'], 16) i = 0 unspents = self.node.listunspent() while i < num_txs and len(unspents) > 0: # Select as input a tx which has at least 5 fantasygold spendable for tx_i in range(len(unspents)): if int(unspents[tx_i]['amount']*COIN) == 1000000*FGC_MIN_GAS_PRICE and unspents[tx_i]['spendable']: break else: assert(False) inpt = CTxIn(COutPoint(int(unspents[tx_i]['txid'], 16), unspents[tx_i]['vout']), nSequence=0) tx = make_transaction(self.node, [inpt], outputs) txid = self.node.sendrawtransaction(tx) unspents = self.node.listunspent() i += 1 self.node.generate(1) sync_blocks(self.nodes) for i in range(2): # 61bc221a counter() out = int(self.nodes[i].callcontract(self.contract_address, "61bc221a")['executionResult']['output'], 16) assert(out-old_out == counter_should_increase_by) # Deploy the testing contract def create_contract_test(self): """ pragma solidity ^0.4.10; contract Example { uint public counter; function inc() public { counter += 1; } function getBalance() public { return this.balance; } } """ contract_data = self.node.createcontract("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", 1000000) self.contract_address = contract_data['address'] block_height = self.node.getblockcount() self.node.generate(1) sync_blocks(self.nodes) for i in range(2): assert(self.nodes[i].getblockcount() == block_height+1) assert(len(self.nodes[i].listcontracts()) == 1+NUM_DEFAULT_DGP_CONTRACTS) # Sends a tx containing 2 op_call outputs calling inc() def many_calls_in_same_tx_test(self): outputs = [] outputs.append(make_op_call_output(0, b"\x04", CScriptNum(1000000), CScriptNum(FGC_MIN_GAS_PRICE), bytes.fromhex("371303c0"), bytes.fromhex(self.contract_address))) outputs.append(make_op_call_output(0, b"\x04", CScriptNum(1000000), CScriptNum(FGC_MIN_GAS_PRICE), bytes.fromhex("371303c0"), bytes.fromhex(self.contract_address))) self.send_one_op_call_tx_with_counter_check(outputs, counter_should_increase_by=2, input_value=2*1000000*FGC_MIN_GAS_PRICE) # Sends a normal raw op_call tx with a single output. def normal_op_call_output_test(self): outputs = [] outputs.append(make_op_call_output(0, b"\x04", b"\xff\x7f", CScriptNum(FGC_MIN_GAS_PRICE), bytes.fromhex("371303c0"), bytes.fromhex(self.contract_address))) self.send_one_op_call_tx_with_counter_check(outputs, counter_should_increase_by=1, input_value=0x7fff*FGC_MIN_GAS_PRICE) # Sends a tx containing 1 op_call output where txfee == gas_price*gas_limit. def gas_equal_to_tx_fee_test(self): outputs = [] outputs.append(make_op_call_output(0, b"\x04", CScriptNum(1000000), CScriptNum(FGC_MIN_GAS_PRICE), bytes.fromhex("371303c0"), bytes.fromhex(self.contract_address))) self.send_one_op_call_tx_with_counter_check(outputs, counter_should_increase_by=1, input_value=1000000*FGC_MIN_GAS_PRICE) # Sends a tx containing 1 op_call output where txfee < gas_price*gas_limit. def gas_exceeding_tx_fee_100001_1_test(self): outputs = [] outputs.append(make_op_call_output(0, b"\x04", CScriptNum(10000001), CScriptNum(FGC_MIN_GAS_PRICE), bytes.fromhex("371303c0"), bytes.fromhex(self.contract_address))) self.send_one_op_call_tx_with_counter_check(outputs, input_value=1000001*FGC_MIN_GAS_PRICE-1, should_throw=True) # Sends a tx containing 1 op_call output where txfee < gas_price*gas_limit. def gas_exceeding_tx_fee_100001_2_test(self): outputs = [] outputs.append(make_op_call_output(0, b"\x04", CScriptNum(1000001), CScriptNum(FGC_MIN_GAS_PRICE), bytes.fromhex("371303c0"), bytes.fromhex(self.contract_address))) self.send_one_op_call_tx_with_counter_check(outputs, input_value=1000000*FGC_MIN_GAS_PRICE, should_throw=True) # Sends a tx containing 2 op_call outputs that has a combined gas_price*gas_limit exceeding the tx fee. # This tx should be rejected since executing such a tx would be unable to pay for its potential execution costs in the same way as a tx with one output where txfee < gas_price*gas_limit. def two_calls_in_same_tx_exceeding_tx_fee_test(self): outputs = [] outputs.append(make_op_call_output(0, b"\x04", CScriptNum(1000000), CScriptNum(FGC_MIN_GAS_PRICE), bytes.fromhex("371303c0"), bytes.fromhex(self.contract_address))) outputs.append(make_op_call_output(0, b"\x04", CScriptNum(1000000), CScriptNum(FGC_MIN_GAS_PRICE), bytes.fromhex("371303c0"), bytes.fromhex(self.contract_address))) self.send_one_op_call_tx_with_counter_check(outputs, input_value=2000000*FGC_MIN_GAS_PRICE-1, should_throw=True) # sends a tx containing 1 op_call output with a (if interpreted with a signed integer) negative gas limit calling inc() def gas_limit_signedness_test(self): outputs = [] gas_limit = b"\xff" while len(gas_limit) < 20: outputs.append(make_op_call_output(0, b"\x04", gas_limit, CScriptNum(FGC_MIN_GAS_PRICE), bytes.fromhex("371303c0"), bytes.fromhex(self.contract_address))) self.send_one_op_call_tx_with_counter_check(outputs, should_throw=True, input_value=min(max(int(bytes_to_hex_str(gas_limit), 16)*FGC_MIN_GAS_PRICE, 10000000), 1000000000)) gas_limit += b"\xff" # sends a tx containing 1 op_call output with a (if interpreted with a signed integer) negative gas limit calling inc() def gas_limit_signedness_one_valid_test(self): outputs = [] gas_limit = b"\xff" outputs.append(make_op_call_output(0, b"\x04", b"\xff\xff\x00", CScriptNum(FGC_MIN_GAS_PRICE), bytes.fromhex("371303c0"), bytes.fromhex(self.contract_address))) outputs.append(make_op_call_output(0, b"\x04", b"\xff\xff", CScriptNum(FGC_MIN_GAS_PRICE), bytes.fromhex("371303c0"), bytes.fromhex(self.contract_address))) self.send_one_op_call_tx_with_counter_check(outputs, should_throw=True, input_value=2*0xffff*FGC_MIN_GAS_PRICE) # sends a tx containing 1 op_call output with a (if interpreted with a signed integer) negative gas price calling inc() def gas_price_signedness_test(self): outputs = [] outputs.append(make_op_call_output(0, b"\x04", b"\x01\x00", b"\xff\xff", bytes.fromhex("371303c0"), bytes.fromhex(self.contract_address))) self.send_one_op_call_tx_with_counter_check(outputs, should_throw=True, input_value=10000000) # sends a tx containing 1 op_call output with a possible negative gas limit and price calling inc() def gas_limit_and_price_signedness_test(self): outputs = [] outputs.append(make_op_call_output(0, b"\x04", b"\xff\xff", b"\xff", bytes.fromhex("371303c0"), bytes.fromhex(self.contract_address))) self.send_one_op_call_tx_with_counter_check(outputs, should_throw=True, input_value=0xff*0xffff) # Sends 100 valid op_call txs def send_100_txs_test(self): outputs = [] outputs.append(make_op_call_output(0, b"\x04", CScriptNum(1000000), CScriptNum(FGC_MIN_GAS_PRICE), bytes.fromhex("371303c0"), bytes.fromhex(self.contract_address))) self.send_multiple_op_call_txs_with_counter_check(100, outputs, 100) def send_tx_with_value_test(self): outputs = [] # d0e30db0 deposit() outputs.append(make_op_call_output(100000000, b"\x04", CScriptNum(1000000), CScriptNum(FGC_MIN_GAS_PRICE), bytes.fromhex("d0e30db0"), bytes.fromhex(self.contract_address))) self.send_one_op_call_tx_with_counter_check(outputs, counter_should_increase_by=0, input_value=100000000+1000000*FGC_MIN_GAS_PRICE) # 12065fe0 getBalance() balance = int(self.node.callcontract(self.contract_address, "12065fe0")['executionResult']['output'], 16) assert(balance == 100000000) def run_test(self): self.node = self.nodes[0] connect_nodes(self.nodes[0], 1) self.nodes[0].generate(200+COINBASE_MATURITY) self.node.sendmany("", {self.node.getnewaddress(): 1000000*FGC_MIN_GAS_PRICE / Decimal('100000000') for i in range(200)}) print("Creating contract") self.create_contract_test() print("Calling inc() in two outputs") self.many_calls_in_same_tx_test() print("Calling inc() in one output") self.normal_op_call_output_test() print("Calling inc() in one output with txfee equal to gas_limit*gas_price") self.gas_equal_to_tx_fee_test() print("Calling inc() in one output with txfee < gas_limit*gas_price") self.gas_exceeding_tx_fee_100001_1_test() print("Second test of inc() in one outputs with txfee < gas_limit*gas_price") self.gas_exceeding_tx_fee_100001_2_test() print("Second test of inc() in one output with txfee < gas_limit*gas_price") self.two_calls_in_same_tx_exceeding_tx_fee_test() print("Mining a block with 100 txs each with an output calling inc()") self.send_100_txs_test() print("Checking that the value of txs are correctly updated") self.send_tx_with_value_test() print("Checking gas limit signedness where one tx is valid") self.gas_limit_signedness_one_valid_test() print("Checking gas limit signedness") self.gas_limit_signedness_test() print("Checking gas price signedness") self.gas_price_signedness_test() print("Checking gas limit and gas price signedness") self.gas_limit_and_price_signedness_test() if __name__ == '__main__': OpCallTest().main()

57.581395

689

0.714943

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12,380

5.10061

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0.025822

0.040167

0.634429

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0.532337

0.496234

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0

0.102193

0.185864

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57.581395

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0.09396

0

null

0

null

0

1

0

ed5fdee808e9a889711f8e8007e05b2a81263072

1,883

py

Python

intake_sklearn/source.py

AlbertDeFusco/intake-sklearn

6cd0e11b26703712eb338032518e5c55b725c48f

[ "BSD-3-Clause" ]

1

2022-02-23T09:00:38.000Z

intake_sklearn/source.py

AlbertDeFusco/intake-sklearn

6cd0e11b26703712eb338032518e5c55b725c48f

[ "BSD-3-Clause" ]

1

2019-10-14T12:25:26.000Z

2019-10-25T13:55:59.000Z

intake_sklearn/source.py

AlbertDeFusco/intake-sklearn

6cd0e11b26703712eb338032518e5c55b725c48f

[ "BSD-3-Clause" ]

1

2021-07-28T17:49:36.000Z

from intake.source.base import DataSource, Schema import joblib import fsspec import sklearn import re from . import __version__ class SklearnModelSource(DataSource): container = 'python' name = 'sklearn' version = __version__ partition_access = False def __init__(self, urlpath, storage_options=None, metadata=None): """ Parameters ---------- urlpath: str, location of model pkl file Either the absolute or relative path to the file or URL to be opened. Some examples: - ``{{ CATALOG_DIR }}/models/model.pkl`` - ``s3://some-bucket/models/model.pkl`` """ self._urlpath = urlpath self._storage_options = storage_options or {} super().__init__(metadata=metadata) def _load(self): with fsspec.open(self._urlpath, mode='rb', **self._storage_options) as f: return f.read() def _get_schema(self): as_binary = self._load() s = re.search(b'_sklearn_versionq(.*\x00)((\d+\.)?(\d+\.)?(\*|\d+))q', as_binary) if s: sklearn_version = s.group(2).decode() else: sklearn_version = None self._schema = Schema( npartitions=1, extra_metadata={ 'sklearn_version':sklearn_version } ) return self._schema def read(self): self._load_metadata() if not self.metadata['sklearn_version'] == sklearn.__version__: msg = ('The model was created with Scikit-Learn version {} ' 'but version {} has been installed in your current environment.' ).format(self.metadata['sklearn_version'], sklearn.__version__) raise RuntimeError(msg) with fsspec.open(self._urlpath, **self._storage_options) as f: return joblib.load(f)

27.691176

89

0.591609

208

1,883

5.086538

0.461538

0.119093

0.05104

0.082231

0.20794

0.126654

0

0.003762

0.294211

1,883

67

90

28.104478

0.792325

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0

0.142676

0.032974

0

1

0.097561

false

0

0.146341

0

0.439024

0

null

0

null

0

1

0

ed607bad1d48fdf5da41de44d6ec206f2716afe4

4,915

py

Python

jedi/evaluate/dynamic.py

hatamov/jedi

10df0f933f931a8e0e70304d823f6df0dc3000bd

[ "MIT" ]

null

jedi/evaluate/dynamic.py

hatamov/jedi

10df0f933f931a8e0e70304d823f6df0dc3000bd

[ "MIT" ]

null

jedi/evaluate/dynamic.py

hatamov/jedi

10df0f933f931a8e0e70304d823f6df0dc3000bd

[ "MIT" ]

null

""" One of the really important features of |jedi| is to have an option to understand code like this:: def foo(bar): bar. # completion here foo(1) There's no doubt wheter bar is an ``int`` or not, but if there's also a call like ``foo('str')``, what would happen? Well, we'll just show both. Because that's what a human would expect. It works as follows: - |Jedi| sees a param - search for function calls named ``foo`` - execute these calls and check the input. This work with a ``ParamListener``. """ from itertools import chain from jedi._compatibility import unicode from jedi.parser import tree as pr from jedi import settings from jedi import debug from jedi.evaluate.cache import memoize_default from jedi.evaluate import imports class ParamListener(object): """ This listener is used to get the params for a function. """ def __init__(self): self.param_possibilities = [] def execute(self, params): self.param_possibilities += params @debug.increase_indent def search_params(evaluator, param): """ A dynamic search for param values. If you try to complete a type: >>> def func(foo): ... foo >>> func(1) >>> func("") It is not known what the type ``foo`` without analysing the whole code. You have to look for all calls to ``func`` to find out what ``foo`` possibly is. """ if not settings.dynamic_params: return [] debug.dbg('Dynamic param search for %s', param) func = param.get_parent_until(pr.Function) # Compare the param names. names = [n for n in search_function_call(evaluator, func) if n.value == param.name.value] # Evaluate the ExecutedParams to types. result = list(chain.from_iterable(n.parent.eval(evaluator) for n in names)) debug.dbg('Dynamic param result %s', result) return result @memoize_default([], evaluator_is_first_arg=True) def search_function_call(evaluator, func): """ Returns a list of param names. """ from jedi.evaluate import representation as er def get_params_for_module(module): """ Returns the values of a param, or an empty array. """ @memoize_default([], evaluator_is_first_arg=True) def get_posibilities(evaluator, module, func_name): try: names = module.used_names[func_name] except KeyError: return [] for name in names: parent = name.parent if pr.is_node(parent, 'trailer'): parent = parent.parent trailer = None if pr.is_node(parent, 'power'): for t in parent.children[1:]: if t == '**': break if t.start_pos > name.start_pos and t.children[0] == '(': trailer = t break if trailer is not None: types = evaluator.goto_definition(name) # We have to remove decorators, because they are not the # "original" functions, this way we can easily compare. # At the same time we also have to remove InstanceElements. undec = [] for escope in types: if escope.isinstance(er.Function, er.Instance) \ and escope.decorates is not None: undec.append(escope.decorates) elif isinstance(escope, er.InstanceElement): undec.append(escope.var) else: undec.append(escope) if er.wrap(evaluator, compare) in undec: # Only if we have the correct function we execute # it, otherwise just ignore it. evaluator.eval_trailer(types, trailer) return listener.param_possibilities return get_posibilities(evaluator, module, func_name) current_module = func.get_parent_until() func_name = unicode(func.name) compare = func if func_name == '__init__': cls = func.get_parent_scope() if isinstance(cls, pr.Class): func_name = unicode(cls.name) compare = cls # add the listener listener = ParamListener() func.listeners.add(listener) try: result = [] # This is like backtracking: Get the first possible result. for mod in imports.get_modules_containing_name(evaluator, [current_module], func_name): result = get_params_for_module(mod) if result: break finally: # cleanup: remove the listener; important: should not stick. func.listeners.remove(listener) return result

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0.584334

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4.738617

0.32715

0.022776

0.017082

0.015658

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4,915

146

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0

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0

0.278481

0

null

0

null

0

1

0

ed614dd2f553e42b3e9876c261fcf0d4bfb4705a

2,245

py

Python

steamcheck/views.py

moird/linux-game-report

8c3204d857134b0685bc3c213cd9d9e9f9a5f2fd

[ "MIT" ]

null

steamcheck/views.py

moird/linux-game-report

8c3204d857134b0685bc3c213cd9d9e9f9a5f2fd

[ "MIT" ]

null

steamcheck/views.py

moird/linux-game-report

8c3204d857134b0685bc3c213cd9d9e9f9a5f2fd

[ "MIT" ]

null

from steamcheck import app from flask import jsonify, render_template import os import steamapi import json @app.route('/') def index(): return render_template("index.html") @app.route('/report/<name>') def report(name=None): """ This will generate the report based on the users Steam ID. Returns JSON :param name: Steam ID (either numerical ID or vanity url: steamcommunity.com/id/moird :return: Json object that contains listing of all linux games and general information about them: { "steamuser": "real steam name", "image": "steam user image url", "games": [{'gametitle', {"linux":true}}] "error": "" } """ process_report = {} try: # See if we are running on heroku or not. Could probably set an environment variable for this as well. if os.path.exists('/app/assets/GAMES.json'): linux_game_list = '/app/assets/GAMES.json' winehq_list = '/app/assets/winehq.json' else: linux_game_list = './assets/GAMES.json' winehq_list = './assets/winehq.json' with open(linux_game_list) as linux_game_list_raw: linux_games = json.load(linux_game_list_raw) with open(winehq_list) as winehq_raw: winehq_apps = json.load(winehq_raw) steam_connection = steamapi.core.APIConnection(api_key=os.environ['steam_api_key']) try: user = steamapi.user.SteamUser(userid=int(name)) except ValueError: # When we get further this as a fallback will be taken out, really don't want to do this. user = steamapi.user.SteamUser(userurl=name) process_report['steamuser'] = user.name process_report['image'] = user.avatar process_report['games'] = {} for game in user.games: linux = False winehq = False if str(game.id) in linux_games: linux = True if game.name in winehq_apps: winehq = winehq_apps[game.name] process_report['games'][game.id] = {"name": game.name, "linux": linux, "winehq":winehq} except Exception as e: process_report['error'] = e return jsonify(**process_report)

35.634921

111

0.623163

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2,245

4.736111

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0.066716

0.047654

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0

0.270379

2,245

63

112

35.634921

0.832723

0.260579

0

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0.116625

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0

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0

0.121951

0.02439

0.219512

0

null

0

null

0

1

0

ed6236b34ab65a1e059ca45441d455cec6bd4e90

516

py

Python

validator/delphi_validator/run.py

benjaminysmith/covidcast-indicators

b1474cd68a1497166fefe4beffd4d5ff867b9a61

[ "MIT" ]

null

validator/delphi_validator/run.py

benjaminysmith/covidcast-indicators

b1474cd68a1497166fefe4beffd4d5ff867b9a61

[ "MIT" ]

null

validator/delphi_validator/run.py

benjaminysmith/covidcast-indicators

b1474cd68a1497166fefe4beffd4d5ff867b9a61

[ "MIT" ]

null

# -*- coding: utf-8 -*- """Functions to call when running the tool. This module should contain a function called `run_module`, that is executed when the module is run with `python -m delphi_validator`. """ from delphi_utils import read_params from .validate import Validator def run_module(): """Run the validator as a module.""" parent_params = read_params() params = parent_params['validation'] validator = Validator(params) validator.validate(parent_params["export_dir"]).print_and_exit()

28.666667

75

0.732558

71

516

5.15493

0.577465

0.098361

0

0.002309

0.160853

516

17

76

30.352941

0.842956

0.443798

0

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0

1

0.142857

false

0

0.285714

0

0.428571

0.142857

0

null

0

null

0

1

0

ed62a0f3bd61d82280e96fe9d14711d5df97f622

1,876

py

Python

datasets/validation_folders.py

zenithfang/supervised_dispnet

f81dfccfdc944e015d8fae17e24b3e664bec14d6

[ "MIT" ]

39

2020-01-17T18:33:42.000Z

2021-11-14T02:36:32.000Z

datasets/validation_folders.py

zenithfang/supervised_dispnet

f81dfccfdc944e015d8fae17e24b3e664bec14d6

[ "MIT" ]

7

2020-01-10T14:52:44.000Z

2021-03-15T18:55:35.000Z

datasets/validation_folders.py

zenithfang/supervised_dispnet

f81dfccfdc944e015d8fae17e24b3e664bec14d6

[ "MIT" ]

10

2020-03-01T11:35:50.000Z

2022-01-18T10:54:04.000Z

import torch.utils.data as data import numpy as np from imageio import imread from path import Path import pdb def crawl_folders(folders_list): imgs = [] depth = [] for folder in folders_list: current_imgs = sorted(folder.files('*.jpg')) current_depth = [] for img in current_imgs: d = img.dirname()/(img.name[:-4] + '.npy') assert(d.isfile()), "depth file {} not found".format(str(d)) depth.append(d) imgs.extend(current_imgs) depth.extend(current_depth) return imgs, depth def load_as_float(path): return imread(path).astype(np.float32) class ValidationSet(data.Dataset): """A sequence data loader where the files are arranged in this way: root/scene_1/0000000.jpg root/scene_1/0000000.npy root/scene_1/0000001.jpg root/scene_1/0000001.npy .. root/scene_2/0000000.jpg root/scene_2/0000000.npy . transform functions must take in a list a images and a numpy array which can be None """ def __init__(self, root, transform=None): self.root = Path(root) scene_list_path = self.root/'val.txt' self.scenes = [self.root/folder[:-1] for folder in open(scene_list_path)] self.imgs, self.depth = crawl_folders(self.scenes) self.transform = transform def __getitem__(self, index): img = load_as_float(self.imgs[index]) depth = np.load(self.depth[index]).astype(np.float32) #;pdb.set_trace() if self.transform is not None: img, _, _ = self.transform([img], depth, None); #this depth is just used to fill the compose transform that is shared(no need for the result) img = img[0] return img, depth def __len__(self): return len(self.imgs)

32.912281

153

0.615672

257

1,876

4.346304

0.381323

0.056401

0.03581

0.030439

0

0.04068

0.279318

1,876

56

154

33.5

0.785503

0.220682

0

0.028302

0

0.027778

1

0.138889

false

0

0.138889

0.055556

0.416667

0

null

0

null

0

1

0

ed6310e1d8d83cf871e0d32a527ca7f1529b58ca

1,302

py

Python

pysaurus/database/special_properties.py

notoraptor/pysaurus

3bf5fe8c15e0e0e580e5edaea05b4a1298641367

[ "MIT" ]

null

pysaurus/database/special_properties.py

notoraptor/pysaurus

3bf5fe8c15e0e0e580e5edaea05b4a1298641367

[ "MIT" ]

4

2021-08-13T14:03:02.000Z

2022-03-05T16:02:45.000Z

pysaurus/database/special_properties.py

notoraptor/pysaurus

3bf5fe8c15e0e0e580e5edaea05b4a1298641367

[ "MIT" ]

null

from abc import abstractmethod from pysaurus.database.properties import PropType from pysaurus.database.video import Video class SpecialPropType(PropType): __slots__ = () @abstractmethod def get(self, video: Video): raise NotImplementedError() class PropError(SpecialPropType): __slots__ = () def __init__(self): super().__init__("<error>", "", True) def get(self, video: Video): return sorted(set(video.errors) | set(video.properties.get(self.name, ()))) class SpecialProperties: properties = [PropError()] @classmethod def install(cls, database): to_save = False for expected in cls.properties: if ( not database.has_prop_type(expected.name) or database.get_prop_type(expected.name) != expected ): database.remove_prop_type(expected.name) database.add_prop_type(expected) to_save = True if to_save: database.save() @classmethod def all_in(cls, video: Video): return all(prop.name in video.properties for prop in cls.properties) @classmethod def set(cls, video: Video): for prop in cls.properties: video.properties[prop.name] = prop.get(video)

26.04

83

0.627496

144

1,302

5.479167

0.319444

0.050697

0.081115

0.076046

0.106464

0

0.274962

1,302

49

84

26.571429

0.835805

0

0.194444

0

0.005376

0

1

0.166667

false

0

0.083333

0.055556

0.472222

0

null

0

null

0

1

0

ed65a740d0a6c0e521ed5a04db6b899535f0bcde

19,613

py

Python

patrole_tempest_plugin/rbac_utils.py

openstack/patrole

fa0ee135121a5e86301ad5ee1854b3a0bd70b69b

[ "Apache-2.0" ]

14

2017-01-03T15:07:18.000Z

2020-09-17T18:07:39.000Z

patrole_tempest_plugin/rbac_utils.py

openstack/patrole

fa0ee135121a5e86301ad5ee1854b3a0bd70b69b

[ "Apache-2.0" ]

null

patrole_tempest_plugin/rbac_utils.py

openstack/patrole

fa0ee135121a5e86301ad5ee1854b3a0bd70b69b

[ "Apache-2.0" ]

12

2017-02-28T20:08:48.000Z

2020-12-30T09:31:51.000Z

# Copyright 2017 AT&T Corporation. # All Rights Reserved. # # 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 contextlib import sys import time from oslo_log import log as logging from oslo_utils import excutils from tempest import config from tempest.lib import exceptions as lib_exc from patrole_tempest_plugin import rbac_exceptions CONF = config.CONF LOG = logging.getLogger(__name__) class _ValidateListContext(object): """Context class responsible for validation of the list functions. This class is used in ``override_role_and_validate_list`` function and the result of a list function must be assigned to the ``ctx.resources`` variable. Example:: with self.override_role_and_validate_list(...) as ctx: ctx.resources = list_function() """ def __init__(self, admin_resources=None, admin_resource_id=None): """Constructor for ``ValidateListContext``. Either ``admin_resources`` or ``admin_resource_id`` should be used, not both. :param list admin_resources: The list of resources received before calling the ``override_role_and_validate_list`` function. To validate will be used the ``_validate_len`` function. :param UUID admin_resource_id: An ID of a resource created before calling the ``override_role_and_validate_list`` function. To validate will be used the ``_validate_resource`` function. :raises RbacValidateListException: if both ``admin_resources`` and ``admin_resource_id`` are set or unset. """ self.resources = None if admin_resources is not None and not admin_resource_id: self._admin_len = len(admin_resources) if not self._admin_len: raise rbac_exceptions.RbacValidateListException( reason="the list of admin resources cannot be empty") self._validate_func = self._validate_len elif admin_resource_id and admin_resources is None: self._admin_resource_id = admin_resource_id self._validate_func = self._validate_resource else: raise rbac_exceptions.RbacValidateListException( reason="admin_resources and admin_resource_id are mutually " "exclusive") def _validate_len(self): """Validates that the number of resources is less than admin resources. """ if not len(self.resources): raise rbac_exceptions.RbacEmptyResponseBody() elif self._admin_len > len(self.resources): raise rbac_exceptions.RbacPartialResponseBody(body=self.resources) def _validate_resource(self): """Validates that the admin resource is present in the resources. """ for resource in self.resources: if resource['id'] == self._admin_resource_id: return raise rbac_exceptions.RbacPartialResponseBody(body=self.resources) def _validate(self): """Calls the proper validation function. :raises RbacValidateListException: if the ``ctx.resources`` variable is not assigned. """ if self.resources is None: raise rbac_exceptions.RbacValidateListException( reason="ctx.resources is not assigned") self._validate_func() class RbacUtilsMixin(object): """Utility mixin responsible for switching ``os_primary`` role. Should be used as a mixin class alongside an instance of :py:class:`tempest.test.BaseTestCase` to perform Patrole class setup for a base RBAC class. Child classes should not use this mixin. Example:: class BaseRbacTest(rbac_utils.RbacUtilsMixin, base.BaseV2ComputeTest): @classmethod def setup_clients(cls): super(BaseRbacTest, cls).setup_clients() cls.hosts_client = cls.os_primary.hosts_client ... This class is responsible for overriding the value of the primary Tempest credential's role (i.e. ``os_primary`` role). By doing so, it is possible to seamlessly swap between admin credentials, needed for setup and clean up, and primary credentials, needed to perform the API call which does policy enforcement. The primary credentials always cycle between roles defined by ``CONF.identity.admin_role`` and ``CONF.patrole.rbac_test_roles``. """ credentials = ['primary', 'admin'] def __init__(self, *args, **kwargs): super(RbacUtilsMixin, self).__init__(*args, **kwargs) # Shows if override_role was called. self.__override_role_called = False # Shows if exception raised during override_role. self.__override_role_caught_exc = False _admin_role_id = None _rbac_role_ids = None _project_id = None _user_id = None _role_map = None _role_inferences_mapping = None _orig_roles = [] admin_roles_client = None @classmethod def restore_roles(cls): if cls._orig_roles: LOG.info("Restoring original roles %s", cls._orig_roles) roles_already_present = cls._list_and_clear_user_roles_on_project( cls._orig_roles) if not roles_already_present: cls._create_user_role_on_project(cls._orig_roles) @classmethod def setup_clients(cls): if CONF.identity_feature_enabled.api_v3: admin_roles_client = cls.os_admin.roles_v3_client else: raise lib_exc.InvalidConfiguration( "Patrole role overriding only supports v3 identity API.") cls.admin_roles_client = admin_roles_client cls._project_id = cls.os_primary.credentials.tenant_id cls._user_id = cls.os_primary.credentials.user_id cls._role_inferences_mapping = cls._prepare_role_inferences_mapping() cls._init_roles() # Store the user's original roles and rollback after testing. roles = cls.admin_roles_client.list_user_roles_on_project( cls._project_id, cls._user_id)['roles'] cls._orig_roles = [role['id'] for role in roles] cls.addClassResourceCleanup(cls.restore_roles) # Change default role to admin cls._override_role(False) super(RbacUtilsMixin, cls).setup_clients() @classmethod def _prepare_role_inferences_mapping(cls): """Preparing roles mapping to support role inferences Making query to `list-all-role-inference-rules`_ keystone API returns all inference rules, which makes it possible to prepare roles mapping. It walks recursively through the raw data:: {"role_inferences": [ { "implies": [{"id": "3", "name": "reader"}], "prior_role": {"id": "2", "name": "member"} }, { "implies": [{"id": "2", "name": "member"}], "prior_role": {"id": "1", "name": "admin"} } ] } and converts it to the mapping:: { "2": ["3"], # "member": ["reader"], "1": ["2", "3"] # "admin": ["member", "reader"] } .. _list-all-role-inference-rules: https://docs.openstack.org/api-ref/identity/v3/#list-all-role-inference-rules """ # noqa: E501 def process_roles(role_id, data): roles = data.get(role_id, set()) for rid in roles.copy(): roles.update(process_roles(rid, data)) return roles def convert_data(data): res = {} for rule in data: prior_role = rule['prior_role']['id'] implies = {r['id'] for r in rule['implies']} res[prior_role] = implies return res raw_data = cls.admin_roles_client.list_all_role_inference_rules() data = convert_data(raw_data['role_inferences']) res = {} for role_id in data: res[role_id] = process_roles(role_id, data) return res def get_all_needed_roles(self, roles): """Extending given roles with roles from mapping Examples:: ["admin"] >> ["admin", "member", "reader"] ["member"] >> ["member", "reader"] ["reader"] >> ["reader"] ["custom_role"] >> ["custom_role"] :param roles: list of roles :return: extended list of roles """ res = set(r for r in roles) for role in res.copy(): role_id = self.__class__._role_map.get(role) implied_roles = self.__class__._role_inferences_mapping.get( role_id, set()) role_names = {self.__class__._role_map[rid] for rid in implied_roles} res.update(role_names) LOG.debug('All needed roles: %s; Base roles: %s', res, roles) return list(res) @contextlib.contextmanager def override_role(self): """Override the role used by ``os_primary`` Tempest credentials. Temporarily change the role used by ``os_primary`` credentials to: * ``[patrole] rbac_test_roles`` before test execution * ``[identity] admin_role`` after test execution Automatically switches to admin role after test execution. :returns: None .. warning:: This function can alter user roles for pre-provisioned credentials. Work is underway to safely clean up after this function. Example:: @rbac_rule_validation.action(service='test', rules=['a:test:rule']) def test_foo(self): # Allocate test-level resources here. with self.override_role(): # The role for `os_primary` has now been overridden. Within # this block, call the API endpoint that enforces the # expected policy specified by "rule" in the decorator. self.foo_service.bar_api_call() # The role is switched back to admin automatically. Note that # if the API call above threw an exception, any code below this # point in the test is not executed. """ self._set_override_role_called() self._override_role(True) try: # Execute the test. yield finally: # Check whether an exception was raised. If so, remember that # for future validation. exc = sys.exc_info()[0] if exc is not None: self._set_override_role_caught_exc() # This code block is always executed, no matter the result of the # test. Automatically switch back to the admin role for test clean # up. self._override_role(False) @classmethod def _override_role(cls, toggle_rbac_role=False): """Private helper for overriding ``os_primary`` Tempest credentials. :param toggle_rbac_role: Boolean value that controls the role that overrides default role of ``os_primary`` credentials. * If True: role is set to ``[patrole] rbac_test_role`` * If False: role is set to ``[identity] admin_role`` """ LOG.debug('Overriding role to: %s.', toggle_rbac_role) roles_already_present = False try: target_roles = (cls._rbac_role_ids if toggle_rbac_role else [cls._admin_role_id]) roles_already_present = cls._list_and_clear_user_roles_on_project( target_roles) # Do not override roles if `target_role` already exists. if not roles_already_present: cls._create_user_role_on_project(target_roles) except Exception as exp: with excutils.save_and_reraise_exception(): LOG.exception(exp) finally: auth_providers = cls.get_auth_providers() for provider in auth_providers: provider.clear_auth() # Fernet tokens are not subsecond aware so sleep to ensure we are # passing the second boundary before attempting to authenticate. # Only sleep if a token revocation occurred as a result of role # overriding. This will optimize test runtime in the case where # ``[identity] admin_role`` == ``[patrole] rbac_test_roles``. if not roles_already_present: time.sleep(1) for provider in auth_providers: provider.set_auth() @classmethod def _init_roles(cls): available_roles = cls.admin_roles_client.list_roles()['roles'] cls._role_map = {r['name']: r['id'] for r in available_roles} LOG.debug('Available roles: %s', cls._role_map.keys()) rbac_role_ids = [] roles = CONF.patrole.rbac_test_roles # TODO(vegasq) drop once CONF.patrole.rbac_test_role is removed if CONF.patrole.rbac_test_role: if not roles: roles.append(CONF.patrole.rbac_test_role) for role_name in roles: rbac_role_ids.append(cls._role_map.get(role_name)) admin_role_id = cls._role_map.get(CONF.identity.admin_role) if not all([admin_role_id, all(rbac_role_ids)]): missing_roles = [] msg = ("Could not find `[patrole] rbac_test_roles` or " "`[identity] admin_role`, both of which are required for " "RBAC testing.") if not admin_role_id: missing_roles.append(CONF.identity.admin_role) if not all(rbac_role_ids): missing_roles += [role_name for role_name in roles if role_name not in cls._role_map] msg += " Following roles were not found: %s." % ( ", ".join(missing_roles)) msg += " Available roles: %s." % ", ".join(cls._role_map) raise rbac_exceptions.RbacResourceSetupFailed(msg) cls._admin_role_id = admin_role_id cls._rbac_role_ids = rbac_role_ids # Adding backward mapping cls._role_map.update({v: k for k, v in cls._role_map.items()}) @classmethod def _create_user_role_on_project(cls, role_ids): for role_id in role_ids: cls.admin_roles_client.create_user_role_on_project( cls._project_id, cls._user_id, role_id) @classmethod def _list_and_clear_user_roles_on_project(cls, role_ids): roles = cls.admin_roles_client.list_user_roles_on_project( cls._project_id, cls._user_id)['roles'] all_role_ids = [role['id'] for role in roles] # NOTE(felipemonteiro): We do not use ``role_id in all_role_ids`` here # to avoid over-permission errors: if the current list of roles on the # project includes "admin" and "Member", and we are switching to the # "Member" role, then we must delete the "admin" role. Thus, we only # return early if the user's roles on the project are an exact match. if set(role_ids) == set(all_role_ids): return True for role in roles: cls.admin_roles_client.delete_role_from_user_on_project( cls._project_id, cls._user_id, role['id']) return False @contextlib.contextmanager def override_role_and_validate_list(self, admin_resources=None, admin_resource_id=None): """Call ``override_role`` and validate RBAC for a list API action. List actions usually do soft authorization: partial or empty response bodies are returned instead of exceptions. This helper validates that unauthorized roles only return a subset of the available resources. Should only be used for validating list API actions. :param test_obj: Instance of ``tempest.test.BaseTestCase``. :param list admin_resources: The list of resources received before calling the ``override_role_and_validate_list`` function. :param UUID admin_resource_id: An ID of a resource created before calling the ``override_role_and_validate_list`` function. :return: py:class:`_ValidateListContext` object. Example:: # the resource created by admin admin_resource_id = ( self.ntp_client.create_dscp_marking_rule() ["dscp_marking_rule"]["id']) with self.override_role_and_validate_list( admin_resource_id=admin_resource_id) as ctx: # the list of resources available for member role ctx.resources = self.ntp_client.list_dscp_marking_rules( policy_id=self.policy_id)["dscp_marking_rules"] """ ctx = _ValidateListContext(admin_resources, admin_resource_id) with self.override_role(): yield ctx ctx._validate() @classmethod def get_auth_providers(cls): """Returns list of auth_providers used within test. Tests may redefine this method to include their own or third party client auth_providers. """ return [cls.os_primary.auth_provider] def _set_override_role_called(self): """Helper for tracking whether ``override_role`` was called.""" self.__override_role_called = True def _set_override_role_caught_exc(self): """Helper for tracking whether exception was thrown inside ``override_role``. """ self.__override_role_caught_exc = True def _validate_override_role_called(self): """Idempotently validate that ``override_role`` is called and reset its value to False for sequential tests. """ was_called = self.__override_role_called self.__override_role_called = False return was_called def _validate_override_role_caught_exc(self): """Idempotently validate that exception was caught inside ``override_role``, so that, by process of elimination, it can be determined whether one was thrown outside (which is invalid). """ caught_exception = self.__override_role_caught_exc self.__override_role_caught_exc = False return caught_exception def is_admin(): """Verifies whether the current test role equals the admin role. :returns: True if ``rbac_test_roles`` contain the admin role. """ roles = CONF.patrole.rbac_test_roles # TODO(vegasq) drop once CONF.patrole.rbac_test_role is removed if CONF.patrole.rbac_test_role: roles.append(CONF.patrole.rbac_test_role) roles = list(set(roles)) # TODO(felipemonteiro): Make this more robust via a context is admin # lookup. return CONF.identity.admin_role in roles

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null

0

null

0

1

0

ed66f473c8ee9e1a4cbf088bc3dc94834ee24ff9

6,029

py

Python

core/my_widgets/drug_picker.py

kimera1999/pmpktn

5307b6684a08bac4b88617f097017b5ea4192ab2

[ "MIT" ]

null

core/my_widgets/drug_picker.py

kimera1999/pmpktn

5307b6684a08bac4b88617f097017b5ea4192ab2

[ "MIT" ]

null

core/my_widgets/drug_picker.py

kimera1999/pmpktn

5307b6684a08bac4b88617f097017b5ea4192ab2

[ "MIT" ]

1

2020-05-16T14:28:59.000Z

from initialize import * from core.db.db_func import query_linedrug_list import os import wx class DrugPopup(wx.ComboPopup): def __init__(self, parent): super().__init__() self.lc = None self.mv = parent.mv self.init_d_l = query_linedrug_list(self.mv.sess).all() self.d_l = [] def Create(self, parent): self.lc = wx.ListCtrl( parent, style=wx.LC_REPORT | wx.LC_SINGLE_SEL | wx.SIMPLE_BORDER) self.lc.AppendColumn('Thuốc', width=200) self.lc.AppendColumn('Thành phần', width=150) self.lc.AppendColumn('Số lượng') self.lc.AppendColumn('Đơn giá') self.lc.AppendColumn('Cách dùng', width=100) self.lc.Bind(wx.EVT_MOTION, self.OnMotion) self.lc.Bind(wx.EVT_LEFT_DOWN, self.OnLeftDown) self.lc.Bind(wx.EVT_KEY_DOWN, self.onKeyPress) self.Update() return True def Init(self): self.value = -1 self.curitem = -1 def GetControl(self): return self.lc def SetStringValue(self, val): idx = self.lc.FindItem(-1, val) if idx != wx.NOT_FOUND: self.lc.Select(idx) def GetStringValue(self): if self.value >= 0: return self.lc.GetItemText(self.value, col=0) return "" def GetAdjustedSize(self, minWidth, prefHeight, maxHeight): return super().GetAdjustedSize(*popup_size) def Update(self, s=''): self.lc.DeleteAllItems() self.d_l = list(filter( lambda x: s.casefold() in x.name.casefold() or s.casefold() in x.element.casefold(), self.init_d_l)) for index, item in enumerate(self.d_l): self.lc.Append( [item.name, item.element, item.quantity, item.sale_price, item.usage]) if item.quantity <= user_setting["so_luong_thuoc_toi_thieu_de_bao_dong_do"]: self.lc.SetItemTextColour(index, wx.Colour(252, 3, 57, 255)) def OnMotion(self, e): item, flags = self.lc.HitTest(e.GetPosition()) if item >= 0: self.lc.Select(item) self.curitem = item def OnLeftDown(self, e): try: self.value = self.curitem self.ComboCtrl.drugWH = self.d_l[self.value] self.Dismiss() self.ComboCtrl.SelectAll() self.ComboCtrl.SetInsertionPointEnd() except IndexError: self.Dismiss() def OnPopup(self): self.Init() self.Update(self.ComboCtrl.Value) if self.lc.ItemCount > 0: if self.curitem < (self.lc.ItemCount - 1): self.curitem += 1 self.lc.Select(self.curitem) self.lc.EnsureVisible(self.curitem) def KeyDown(self): if self.lc.ItemCount > 0: if self.curitem < (self.lc.ItemCount - 1): self.curitem += 1 self.lc.Select(self.curitem) self.lc.EnsureVisible(self.curitem) def KeyUp(self): if self.lc.ItemCount > 0: if self.curitem > 0: self.curitem -= 1 self.lc.Select(self.curitem) self.lc.EnsureVisible(self.curitem) else: self.KeyESC() def KeyESC(self): a = self.ComboCtrl.Value self.Dismiss() self.ComboCtrl.ChangeValue(a) self.ComboCtrl.SetInsertionPointEnd() def KeyReturn(self): self.OnLeftDown(None) def onKeyPress(self, e): c = e.GetKeyCode() if c == wx.WXK_DOWN: self.KeyDown() elif c == wx.WXK_UP: self.KeyUp() elif c == wx.WXK_ESCAPE: self.KeyESC() elif c == wx.WXK_RETURN: self.KeyReturn() class DrugPicker(wx.ComboCtrl): def __init__(self, parent): super().__init__(parent, size=drugctrl_size, style=wx.TE_PROCESS_ENTER) self.mv = parent.mv self.drug_popup = DrugPopup(self) self.SetPopupControl(self.drug_popup) self.Bind(wx.EVT_KEY_DOWN, self.onKeyPress) self.Bind(wx.EVT_TEXT, self.onTextChange) self.SetHint("Nhấn Enter để search thuốc") self._drugWH = None self.EnablePopupAnimation(enable=False) @property def drugWH(self): return self._drugWH @drugWH.setter def drugWH(self, dwh): self._drugWH = dwh pg = self.Parent if dwh: pg.usage_unit.Label = dwh.usage_unit + " " pg.sale_unit.Label = dwh.sale_unit + " " else: self.ChangeValue('') pg.dosage_per.ChangeValue('') pg.usage_unit.Label = '{Đơn vị} ' pg.times.ChangeValue("") pg.quantity.ChangeValue("") pg.sale_unit.Label = '{Đơn vị} ' pg.usage.ChangeValue("") def onKeyPress(self, e): if os.name == "posix": if e.GetKeyCode() in [wx.WXK_RETURN, wx.WXK_DOWN]: if not self.IsPopupShown(): self.Popup() else: e.Skip() else: if e.GetKeyCode() not in [wx.WXK_RETURN, wx.WXK_UP, wx.WXK_DOWN, wx.WXK_ESCAPE]: if self.IsPopupShown(): a = self.Value self.Dismiss() self.ChangeValue(a) self.SetInsertionPointEnd() e.Skip() def onTextChange(self, e): if os.name == "nt": if e.String == "": self.Clear() elif len(e.String) >= 1: if not self.IsPopupShown(): self.Popup() self.SetInsertionPointEnd() if os.name == "posix": if e.String == "": self.Clear() def Clear(self): self.drugWH = None def refreshPopup(self): self.drug_popup.init_d_l = query_linedrug_list(self.mv.sess).all()

31.238342

96

0.543208

705

6,029

4.52766

0.255319

0.056391

0.028195

0.026629

0.280388

0.204887

0.148496

0.127193

0.114975

0

0.008551

0.340521

6,029

192

97

31.401042

0.794266

0

0.272727

0

0.022558

0.006469

0

1

0.139394

false

0

0.024242

0.018182

0.212121

0

null

0

null

0

1

0

ed6710b9dafd0dadb8b0c6608676f1c2e79ad2c8

615

py

Python

em Python/Roteiro4/Roteiro4__grafos.py

GuilhermeEsdras/Grafos

b6556c3d679496d576f65b798a1a584cd73e40f4

[ "MIT" ]

null

em Python/Roteiro4/Roteiro4__grafos.py

GuilhermeEsdras/Grafos

b6556c3d679496d576f65b798a1a584cd73e40f4

[ "MIT" ]

null

em Python/Roteiro4/Roteiro4__grafos.py

GuilhermeEsdras/Grafos

b6556c3d679496d576f65b798a1a584cd73e40f4

[ "MIT" ]

null

from Roteiro4.Roteiro4__funcoes import Grafo class Grafos: # Grafo da Paraíba paraiba = Grafo(['J', 'C', 'E', 'P', 'M', 'T', 'Z']) for aresta in ['J-C', 'C-E', 'C-E', 'C-P', 'C-P', 'C-M', 'C-T', 'M-T', 'T-Z']: paraiba.adicionaAresta(aresta) # --- # # Grafo Completo grafo_completo = Grafo(['J', 'C', 'E', 'P']) for aresta in ['J-C', 'J-P', 'J-E', 'C-E', 'C-P', 'P-E']: grafo_completo.adicionaAresta(aresta) # --- # # K3 k3 = Grafo(['A', 'B', 'C']) for aresta in ['A-B', 'B-C', 'C-A']: k3.adicionaAresta(aresta) # --- #

23.653846

82

0.461789

90

615

3.111111

0.277778

0.035714

0.117857

0.057143

0.192857

0

0.011236

0.276423

615

25

83

24.6

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0.078049

0

0.122302

0

1

0

false

0

0.090909

0

0.454545

0

null

0

null

0

1

0

ed67b3786dc5aa973280b427220b99a230def591

464

py

Python

flask/app.py

yatsu/react-flask-graphql-example

18a38b7602c81a85a3cc38c74440ce34d63fc32a

[ "MIT" ]

21

2017-06-24T15:29:30.000Z

2021-03-03T06:58:41.000Z

flask/app.py

yatsu/react-flask-graphql-example

18a38b7602c81a85a3cc38c74440ce34d63fc32a

[ "MIT" ]

null

flask/app.py

yatsu/react-flask-graphql-example

18a38b7602c81a85a3cc38c74440ce34d63fc32a

[ "MIT" ]

6

2018-01-15T06:36:11.000Z

2022-03-18T07:57:39.000Z

from flask import Flask from flask_cors import CORS from flask_graphql import GraphQLView from schema import Schema def create_app(**kwargs): app = Flask(__name__) app.debug = True app.add_url_rule( '/graphql', view_func=GraphQLView.as_view('graphql', schema=Schema, **kwargs) ) return app if __name__ == '__main__': app = create_app(graphiql=True) CORS(app, resources={r'/graphql': {'origins': '*'}}) app.run()

22.095238

73

0.668103

60

464

4.833333

0.466667

0.093103

0

0.206897

464

20

74

23.2

0.788043

0

0.084052

0

1

0.0625

false

0

0.25

0

0.375

0

null

0

null

0

1

0

ed69c7e1252a3ec3f75d6d65d353de14affd6d0c

1,628

py

Python

bluesky/tests/utils.py

AbbyGi/bluesky

759f9c55dce97dc47513cca749a69dd861bdf58d

[ "BSD-3-Clause" ]

43

2015-08-04T20:13:41.000Z

2019-04-12T17:21:36.000Z

bluesky/tests/utils.py

AbbyGi/bluesky

759f9c55dce97dc47513cca749a69dd861bdf58d

[ "BSD-3-Clause" ]

966

2015-07-29T16:43:21.000Z

2019-05-09T21:02:28.000Z

bluesky/tests/utils.py

AbbyGi/bluesky

759f9c55dce97dc47513cca749a69dd861bdf58d

[ "BSD-3-Clause" ]

48

2019-05-15T18:01:06.000Z

2022-03-03T18:53:43.000Z

from collections import defaultdict import contextlib import tempfile import sys import threading import asyncio @contextlib.contextmanager def _print_redirect(): old_stdout = sys.stdout try: fout = tempfile.TemporaryFile(mode="w+", encoding="utf-8") sys.stdout = fout yield fout finally: sys.stdout = old_stdout class MsgCollector: def __init__(self, msg_hook=None): self.msgs = [] self.msg_hook = msg_hook def __call__(self, msg): self.msgs.append(msg) if self.msg_hook: self.msg_hook(msg) class DocCollector: def __init__(self): self.start = [] self.stop = {} self.descriptor = defaultdict(list) self.event = {} def insert(self, name, doc): if name == "start": self.start.append(doc) elif name == "stop": self.stop[doc["run_start"]] = doc elif name == "descriptor": self.descriptor[doc["run_start"]].append(doc) self.event[doc["uid"]] = [] elif name == 'bulk_events': for k, v in doc.items(): self.event[k].extend(v) else: self.event[doc["descriptor"]].append(doc) def _fabricate_asycio_event(loop): th_ev = threading.Event() aio_event = None def really_make_the_event(): nonlocal aio_event aio_event = asyncio.Event() th_ev.set() h = loop.call_soon_threadsafe(really_make_the_event) if not th_ev.wait(0.1): h.cancel() raise Exception("failed to make asyncio event") return aio_event

23.941176

66

0.594595

200

1,628

4.63

0.405

0.037797

0.047516

0.030238

0

0.002604

0.292383

1,628

67

24.298507

0.801215

0

0.058968

0

1

0.12963

false

0

0.111111

0

0.296296

0.018519

0

null

0

null

0

1

0

ed69da856e9dae34d6443933a8a9df258e7f8e95

1,116

py

Python

cli/check_json.py

MJJojo97/openslides-backend

af0d1edb0070e352d46f285a1ba0bbe3702d49ae

[ "MIT" ]

null

cli/check_json.py

MJJojo97/openslides-backend

af0d1edb0070e352d46f285a1ba0bbe3702d49ae

[ "MIT" ]

null

cli/check_json.py

MJJojo97/openslides-backend

af0d1edb0070e352d46f285a1ba0bbe3702d49ae

[ "MIT" ]

null

import json import sys from openslides_backend.models.checker import Checker, CheckException def main() -> int: files = sys.argv[1:] if not files: print("No files specified.") return 1 possible_modes = tuple(f"--{mode}" for mode in Checker.modes) modes = tuple(mode[2:] for mode in possible_modes if mode in files) if len(modes) == 0: mode = "all" elif len(modes) > 1: print(f"You can only choose one mode of {', '.join(possible_modes)}.") exit(1) else: mode = modes[0] if len(modes): files = [x for x in files if x not in possible_modes] failed = False for f in files: with open(f) as data: try: Checker( json.load(data), mode=mode, ).run_check() except CheckException as e: print(f"Check for {f} failed:\n", e) failed = True else: print(f"Check for {f} successful.") return 1 if failed else 0 if __name__ == "__main__": sys.exit(main())

24.8

78

0.53405

147

1,116

3.959184

0.401361

0.089347

0.030928

0.04811

0.051546

0

0.012605

0.360215

1,116

44

79

25.363636

0.802521

0

0.057143

0

0.130824

0.021505

0

1

0.028571

false

0

0.085714

0

0.171429

0.114286

0

null

0

null

0

1

0

ed6b5de7ad69456fafac8a04559f11ef56300d5e

24,607

bzl

Python

web/repositories.bzl

Ubehebe/rules_webtesting

c231866a3bccc0f27b31050a57dc2b4a700ad64e

[ "Apache-2.0" ]

null

web/repositories.bzl

Ubehebe/rules_webtesting

c231866a3bccc0f27b31050a57dc2b4a700ad64e

[ "Apache-2.0" ]

null

web/repositories.bzl

Ubehebe/rules_webtesting

c231866a3bccc0f27b31050a57dc2b4a700ad64e

[ "Apache-2.0" ]

null

# Copyright 2016 Google 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. """Defines external repositories needed by rules_webtesting.""" load("//web/internal:platform_http_file.bzl", "platform_http_file") load("@bazel_gazelle//:deps.bzl", "go_repository") load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive") load("@bazel_tools//tools/build_defs/repo:java.bzl", "java_import_external") # NOTE: URLs are mirrored by an asynchronous review process. They must # be greppable for that to happen. It's OK to submit broken mirror # URLs, so long as they're correctly formatted. Bazel's downloader # has fast failover. def web_test_repositories(**kwargs): """Defines external repositories required by Webtesting Rules. This function exists for other Bazel projects to call from their WORKSPACE file when depending on rules_webtesting using http_archive. This function makes it easy to import these transitive dependencies into the parent workspace. This will check to see if a repository has been previously defined before defining a new repository. Alternatively, individual dependencies may be excluded with an "omit_" + name parameter. This is useful for users who want to be rigorous about declaring their own direct dependencies, or when another Bazel project is depended upon (e.g. rules_closure) that defines the same dependencies as this one (e.g. com_google_guava.) Alternatively, a whitelist model may be used by calling the individual functions this method references. Please note that while these dependencies are defined, they are not actually downloaded, unless a target is built that depends on them. Args: **kwargs: omit_... parameters used to prevent importing specific dependencies. """ if should_create_repository("bazel_skylib", kwargs): bazel_skylib() if should_create_repository("com_github_blang_semver", kwargs): com_github_blang_semver() if should_create_repository("com_github_gorilla_context", kwargs): com_github_gorilla_context() if should_create_repository("com_github_gorilla_mux", kwargs): com_github_gorilla_mux() if should_create_repository("com_github_tebeka_selenium", kwargs): com_github_tebeka_selenium() if should_create_repository("com_github_urllib3", kwargs): com_github_urllib3() if should_create_repository("com_google_code_findbugs_jsr305", kwargs): com_google_code_findbugs_jsr305() if should_create_repository("com_google_code_gson", kwargs): com_google_code_gson() if should_create_repository( "com_google_errorprone_error_prone_annotations", kwargs, ): com_google_errorprone_error_prone_annotations() if should_create_repository("com_google_guava", kwargs): com_google_guava() if should_create_repository("com_squareup_okhttp3_okhttp", kwargs): com_squareup_okhttp3_okhttp() if should_create_repository("com_squareup_okio", kwargs): com_squareup_okio() if should_create_repository("commons_codec", kwargs): commons_codec() if should_create_repository("commons_logging", kwargs): commons_logging() if should_create_repository("junit", kwargs): junit() if should_create_repository("net_bytebuddy", kwargs): net_bytebuddy() if should_create_repository("org_apache_commons_exec", kwargs): org_apache_commons_exec() if should_create_repository("org_apache_httpcomponents_httpclient", kwargs): org_apache_httpcomponents_httpclient() if should_create_repository("org_apache_httpcomponents_httpcore", kwargs): org_apache_httpcomponents_httpcore() if should_create_repository("org_hamcrest_core", kwargs): org_hamcrest_core() if should_create_repository("org_jetbrains_kotlin_stdlib", kwargs): org_jetbrains_kotlin_stdlib() if should_create_repository("org_json", kwargs): org_json() if should_create_repository("org_seleniumhq_py", kwargs): org_seleniumhq_py() if should_create_repository("org_seleniumhq_selenium_api", kwargs): org_seleniumhq_selenium_api() if should_create_repository("org_seleniumhq_selenium_remote_driver", kwargs): org_seleniumhq_selenium_remote_driver() if kwargs.keys(): print("The following parameters are unknown: " + str(kwargs.keys())) def should_create_repository(name, args): """Returns whether the name repository should be created. This allows creation of a repository to be disabled by either an "omit_" _+ name parameter or by previously defining a rule for the repository. The args dict will be mutated to remove "omit_" + name. Args: name: The name of the repository that should be checked. args: A dictionary that contains "omit_...": bool pairs. Returns: boolean indicating whether the repository should be created. """ key = "omit_" + name if key in args: val = args.pop(key) if val: return False if native.existing_rule(name): return False return True def browser_repositories(firefox = False, chromium = False, sauce = False): """Sets up repositories for browsers defined in //browsers/.... This should only be used on an experimental basis; projects should define their own browsers. Args: firefox: Configure repositories for //browsers:firefox-native. chromium: Configure repositories for //browsers:chromium-native. sauce: Configure repositories for //browser/sauce:chrome-win10. """ if chromium: org_chromium_chromedriver() org_chromium_chromium() if firefox: org_mozilla_firefox() org_mozilla_geckodriver() if sauce: com_saucelabs_sauce_connect() def bazel_skylib(): http_archive( name = "bazel_skylib", sha256 = "", strip_prefix = "bazel-skylib-e9fc4750d427196754bebb0e2e1e38d68893490a", urls = [ "https://mirror.bazel.build/github.com/bazelbuild/bazel-skylib/archive/e9fc4750d427196754bebb0e2e1e38d68893490a.tar.gz", "https://github.com/bazelbuild/bazel-skylib/archive/e9fc4750d427196754bebb0e2e1e38d68893490a.tar.gz", ], ) def com_github_blang_semver(): go_repository( name = "com_github_blang_semver", importpath = "github.com/blang/semver", sha256 = "3d9da53f4c2d3169bfa9b25f2f36f301a37556a47259c870881524c643c69c57", strip_prefix = "semver-3.5.1", urls = [ "https://mirror.bazel.build/github.com/blang/semver/archive/v3.5.1.tar.gz", "https://github.com/blang/semver/archive/v3.5.1.tar.gz", ], ) def com_github_gorilla_context(): go_repository( name = "com_github_gorilla_context", importpath = "github.com/gorilla/context", sha256 = "2dfdd051c238695bf9ebfed0bf6a8c533507ac0893bce23be5930e973736bb03", strip_prefix = "context-1.1.1", urls = [ "https://mirror.bazel.build/github.com/gorilla/context/archive/v1.1.1.tar.gz", "https://github.com/gorilla/context/archive/v1.1.1.tar.gz", ], ) def com_github_gorilla_mux(): go_repository( name = "com_github_gorilla_mux", importpath = "github.com/gorilla/mux", sha256 = "0dc18fb09413efea7393e9c2bd8b5b442ce08e729058f5f7e328d912c6c3d3e3", strip_prefix = "mux-1.6.2", urls = [ "https://mirror.bazel.build/github.com/gorilla/mux/archive/v1.6.2.tar.gz", "https://github.com/gorilla/mux/archive/v1.6.2.tar.gz", ], ) def com_github_tebeka_selenium(): go_repository( name = "com_github_tebeka_selenium", importpath = "github.com/tebeka/selenium", sha256 = "c506637fd690f4125136233a3ea405908b8255e2d7aa2aa9d3b746d96df50dcd", strip_prefix = "selenium-a49cf4b98a36c2b21b1ccb012852bd142d5fc04a", urls = [ "https://mirror.bazel.build/github.com/tebeka/selenium/archive/a49cf4b98a36c2b21b1ccb012852bd142d5fc04a.tar.gz", "https://github.com/tebeka/selenium/archive/a49cf4b98a36c2b21b1ccb012852bd142d5fc04a.tar.gz", ], ) def com_github_urllib3(): http_archive( name = "com_github_urllib3", build_file = str(Label("//build_files:com_github_urllib3.BUILD")), sha256 = "a68ac5e15e76e7e5dd2b8f94007233e01effe3e50e8daddf69acfd81cb686baf", strip_prefix = "urllib3-1.23", urls = [ "https://files.pythonhosted.org/packages/3c/d2/dc5471622bd200db1cd9319e02e71bc655e9ea27b8e0ce65fc69de0dac15/urllib3-1.23.tar.gz", ], ) def com_google_code_findbugs_jsr305(): java_import_external( name = "com_google_code_findbugs_jsr305", jar_urls = [ "https://mirror.bazel.build/repo1.maven.org/maven2/com/google/code/findbugs/jsr305/3.0.2/jsr305-3.0.2.jar", "https://repo1.maven.org/maven2/com/google/code/findbugs/jsr305/3.0.2/jsr305-3.0.2.jar", ], jar_sha256 = "766ad2a0783f2687962c8ad74ceecc38a28b9f72a2d085ee438b7813e928d0c7", licenses = ["notice"], # BSD 3-clause ) def com_google_code_gson(): java_import_external( name = "com_google_code_gson", jar_sha256 = "233a0149fc365c9f6edbd683cfe266b19bdc773be98eabdaf6b3c924b48e7d81", jar_urls = [ "https://mirror.bazel.build/repo1.maven.org/maven2/com/google/code/gson/gson/2.8.5/gson-2.8.5.jar", "https://repo1.maven.org/maven2/com/google/code/gson/gson/2.8.5/gson-2.8.5.jar", ], licenses = ["notice"], # The Apache Software License, Version 2.0 ) def com_google_errorprone_error_prone_annotations(): java_import_external( name = "com_google_errorprone_error_prone_annotations", jar_sha256 = "10a5949aa0f95c8de4fd47edfe20534d2acefd8c224f8afea1f607e112816120", jar_urls = [ "https://mirror.bazel.build/repo1.maven.org/maven2/com/google/errorprone/error_prone_annotations/2.3.1/error_prone_annotations-2.3.1.jar", "https://repo1.maven.org/maven2/com/google/errorprone/error_prone_annotations/2.3.1/error_prone_annotations-2.3.1.jar", ], licenses = ["notice"], # Apache 2.0 ) def com_google_guava(): java_import_external( name = "com_google_guava", jar_sha256 = "a0e9cabad665bc20bcd2b01f108e5fc03f756e13aea80abaadb9f407033bea2c", jar_urls = [ "https://mirror.bazel.build/repo1.maven.org/maven2/com/google/guava/guava/26.0-jre/guava-26.9-jre.jar", "https://repo1.maven.org/maven2/com/google/guava/guava/26.0-jre/guava-26.0-jre.jar", ], licenses = ["notice"], # Apache 2.0 exports = [ "@com_google_code_findbugs_jsr305", "@com_google_errorprone_error_prone_annotations", ], ) def com_saucelabs_sauce_connect(): platform_http_file( name = "com_saucelabs_sauce_connect", licenses = ["by_exception_only"], # SauceLabs EULA amd64_sha256 = "dd53f2cdcec489fbc2443942b853b51bf44af39f230600573119cdd315ddee52", amd64_urls = [ "https://saucelabs.com/downloads/sc-4.5.1-linux.tar.gz", ], macos_sha256 = "920ae7bd5657bccdcd27bb596593588654a2820486043e9a12c9062700697e66", macos_urls = [ "https://saucelabs.com/downloads/sc-4.5.1-osx.zip", ], windows_sha256 = "ec11b4ee029c9f0cba316820995df6ab5a4f394053102e1871b9f9589d0a9eb5", windows_urls = [ "https://saucelabs.com/downloads/sc-4.4.12-win32.zip", ], ) def com_squareup_okhttp3_okhttp(): java_import_external( name = "com_squareup_okhttp3_okhttp", jar_urls = [ "https://mirror.bazel.build/repo1.maven.org/maven2/com/squareup/okhttp3/okhttp/3.9.1/okhttp-3.9.1.jar", "https://repo1.maven.org/maven2/com/squareup/okhttp3/okhttp/3.9.1/okhttp-3.9.1.jar", ], jar_sha256 = "a0d01017a42bba26e507fc6d448bb36e536f4b6e612f7c42de30bbdac2b7785e", licenses = ["notice"], # Apache 2.0 deps = [ "@com_squareup_okio", "@com_google_code_findbugs_jsr305", ], ) def com_squareup_okio(): java_import_external( name = "com_squareup_okio", jar_sha256 = "79b948cf77504750fdf7aeaf362b5060415136ab6635e5113bd22925e0e9e737", jar_urls = [ "https://mirror.bazel.build/repo1.maven.org/maven2/com/squareup/okio/okio/2.0.0/okio-2.0.0.jar", "https://repo1.maven.org/maven2/com/squareup/okio/okio/2.0.0/okio-2.0.0.jar", ], licenses = ["notice"], # Apache 2.0 deps = [ "@com_google_code_findbugs_jsr305", "@org_jetbrains_kotlin_stdlib", ], ) def commons_codec(): java_import_external( name = "commons_codec", jar_sha256 = "e599d5318e97aa48f42136a2927e6dfa4e8881dff0e6c8e3109ddbbff51d7b7d", jar_urls = [ "https://mirror.bazel.build/repo1.maven.org/maven2/commons-codec/commons-codec/1.11/commons-codec-1.11.jar", "https://repo1.maven.org/maven2/commons-codec/commons-codec/1.11/commons-codec-1.11.jar", ], licenses = ["notice"], # Apache License, Version 2.0 ) def commons_logging(): java_import_external( name = "commons_logging", jar_sha256 = "daddea1ea0be0f56978ab3006b8ac92834afeefbd9b7e4e6316fca57df0fa636", jar_urls = [ "https://mirror.bazel.build/repo1.maven.org/maven2/commons-logging/commons-logging/1.2/commons-logging-1.2.jar", "https://repo1.maven.org/maven2/commons-logging/commons-logging/1.2/commons-logging-1.2.jar", ], licenses = ["notice"], # The Apache Software License, Version 2.0 ) def junit(): java_import_external( name = "junit", jar_sha256 = "59721f0805e223d84b90677887d9ff567dc534d7c502ca903c0c2b17f05c116a", jar_urls = [ "https://mirror.bazel.build/repo1.maven.org/maven2/junit/junit/4.12/junit-4.12.jar", "https://repo1.maven.org/maven2/junit/junit/4.12/junit-4.12.jar", ], licenses = ["reciprocal"], # Eclipse Public License 1.0 testonly_ = 1, deps = ["@org_hamcrest_core"], ) def net_bytebuddy(): java_import_external( name = "net_bytebuddy", jar_sha256 = "4b87ad52a8f64a1197508e176e84076584160e3d65229ff757efee870cd4a8e2", jar_urls = [ "https://mirror.bazel.build/repo1.maven.org/maven2/net/bytebuddy/byte-buddy/1.8.19/byte-buddy-1.8.19.jar", "https://repo1.maven.org/maven2/net/bytebuddy/byte-buddy/1.8.19/byte-buddy-1.8.19.jar", ], licenses = ["notice"], # Apache 2.0 deps = ["@com_google_code_findbugs_jsr305"], ) def org_apache_commons_exec(): java_import_external( name = "org_apache_commons_exec", jar_sha256 = "cb49812dc1bfb0ea4f20f398bcae1a88c6406e213e67f7524fb10d4f8ad9347b", jar_urls = [ "https://mirror.bazel.build/repo1.maven.org/maven2/org/apache/commons/commons-exec/1.3/commons-exec-1.3.jar", "https://repo1.maven.org/maven2/org/apache/commons/commons-exec/1.3/commons-exec-1.3.jar", ], licenses = ["notice"], # Apache License, Version 2.0 ) def org_apache_httpcomponents_httpclient(): java_import_external( name = "org_apache_httpcomponents_httpclient", jar_sha256 = "c03f813195e7a80e3608d0ddd8da80b21696a4c92a6a2298865bf149071551c7", jar_urls = [ "https://mirror.bazel.build/repo1.maven.org/maven2/org/apache/httpcomponents/httpclient/4.5.6/httpclient-4.5.6.jar", "https://repo1.maven.org/maven2/org/apache/httpcomponents/httpclient/4.5.6/httpclient-4.5.6.jar", ], licenses = ["notice"], # Apache License, Version 2.0 deps = [ "@org_apache_httpcomponents_httpcore", "@commons_logging", "@commons_codec", ], ) def org_apache_httpcomponents_httpcore(): java_import_external( name = "org_apache_httpcomponents_httpcore", jar_sha256 = "1b4a1c0b9b4222eda70108d3c6e2befd4a6be3d9f78ff53dd7a94966fdf51fc5", jar_urls = [ "https://mirror.bazel.build/repo1.maven.org/maven2/org/apache/httpcomponents/httpcore/4.4.9/httpcore-4.4.9.jar", "https://repo1.maven.org/maven2/org/apache/httpcomponents/httpcore/4.4.9/httpcore-4.4.9.jar", ], licenses = ["notice"], # Apache License, Version 2.0 ) def org_chromium_chromedriver(): platform_http_file( name = "org_chromium_chromedriver", licenses = ["reciprocal"], # BSD 3-clause, ICU, MPL 1.1, libpng (BSD/MIT-like), Academic Free License v. 2.0, BSD 2-clause, MIT amd64_sha256 = "71eafe087900dbca4bc0b354a1d172df48b31a4a502e21f7c7b156d7e76c95c7", amd64_urls = [ "https://chromedriver.storage.googleapis.com/2.41/chromedriver_linux64.zip", ], macos_sha256 = "fd32a27148f44796a55f5ce3397015c89ebd9f600d9dda2bcaca54575e2497ae", macos_urls = [ "https://chromedriver.storage.googleapis.com/2.41/chromedriver_mac64.zip", ], windows_sha256 = "a8fa028acebef7b931ef9cb093f02865f9f7495e49351f556e919f7be77f072e", windows_urls = [ "https://chromedriver.storage.googleapis.com/2.38/chromedriver_win32.zip", ], ) def org_chromium_chromium(): platform_http_file( name = "org_chromium_chromium", licenses = ["notice"], # BSD 3-clause (maybe more?) amd64_sha256 = "6933d0afce6e17304b62029fbbd246cbe9e130eb0d90d7682d3765d3dbc8e1c8", amd64_urls = [ "https://commondatastorage.googleapis.com/chromium-browser-snapshots/Linux_x64/561732/chrome-linux.zip", ], macos_sha256 = "084884e91841a923d7b6e81101f0105bbc3b0026f9f6f7a3477f5b313ee89e32", macos_urls = [ "https://commondatastorage.googleapis.com/chromium-browser-snapshots/Mac/561733/chrome-mac.zip", ], windows_sha256 = "d1bb728118c12ea436d8ea07dba980789e7d860aa664dd1fad78bc20e8d9391c", windows_urls = [ "https://commondatastorage.googleapis.com/chromium-browser-snapshots/Win_x64/540270/chrome-win32.zip", ], ) def org_hamcrest_core(): java_import_external( name = "org_hamcrest_core", jar_sha256 = "66fdef91e9739348df7a096aa384a5685f4e875584cce89386a7a47251c4d8e9", jar_urls = [ "https://mirror.bazel.build/repo1.maven.org/maven2/org/hamcrest/hamcrest-core/1.3/hamcrest-core-1.3.jar", "https://repo1.maven.org/maven2/org/hamcrest/hamcrest-core/1.3/hamcrest-core-1.3.jar", ], licenses = ["notice"], # New BSD License testonly_ = 1, ) def org_jetbrains_kotlin_stdlib(): java_import_external( name = "org_jetbrains_kotlin_stdlib", jar_sha256 = "62eaf9cc6e746cef4593abe7cdb4dd48694ef5f817c852e0d9fbbd11fcfc564e", jar_urls = [ "https://mirror.bazel.build/repo1.maven.org/maven2/org/jetbrains/kotlin/kotlin-stdlib/1.2.61/kotlin-stdlib-1.2.61.jar", "https://repo1.maven.org/maven2/org/jetbrains/kotlin/kotlin-stdlib/1.2.61/kotlin-stdlib-1.2.61.jar", ], licenses = ["notice"], # The Apache Software License, Version 2.0 ) def org_json(): java_import_external( name = "org_json", jar_sha256 = "518080049ba83181914419d11a25d9bc9833a2d729b6a6e7469fa52851356da8", jar_urls = [ "https://mirror.bazel.build/repo1.maven.org/maven2/org/json/json/20180813/json-20180813.jar", "https://repo1.maven.org/maven2/org/json/json/20180813/json-20180813.jar", ], licenses = ["notice"], # MIT-style license ) def org_mozilla_firefox(): platform_http_file( name = "org_mozilla_firefox", licenses = ["reciprocal"], # MPL 2.0 amd64_sha256 = "3a729ddcb1e0f5d63933177a35177ac6172f12edbf9fbbbf45305f49333608de", amd64_urls = [ "https://mirror.bazel.build/ftp.mozilla.org/pub/firefox/releases/61.0.2/linux-x86_64/en-US/firefox-61.0.2.tar.bz2", "https://ftp.mozilla.org/pub/firefox/releases/61.0.2/linux-x86_64/en-US/firefox-61.0.2.tar.bz2", ], macos_sha256 = "bf23f659ae34832605dd0576affcca060d1077b7bf7395bc9874f62b84936dc5", macos_urls = [ "https://mirror.bazel.build/ftp.mozilla.org/pub/firefox/releases/61.0.2/mac/en-US/Firefox%2061.0.2.dmg", "https://ftp.mozilla.org/pub/firefox/releases/61.0.2/mac/en-US/Firefox%2061.0.2.dmg", ], ) def org_mozilla_geckodriver(): platform_http_file( name = "org_mozilla_geckodriver", licenses = ["reciprocal"], # MPL 2.0 amd64_sha256 = "c9ae92348cf00aa719be6337a608fae8304691a95668e8e338d92623ba9e0ec6", amd64_urls = [ "https://mirror.bazel.build/github.com/mozilla/geckodriver/releases/download/v0.21.0/geckodriver-v0.21.0-linux64.tar.gz", "https://github.com/mozilla/geckodriver/releases/download/v0.21.0/geckodriver-v0.21.0-linux64.tar.gz", ], macos_sha256 = "ce4a3e9d706db94e8760988de1ad562630412fa8cf898819572522be584f01ce", macos_urls = [ "https://mirror.bazel.build/github.com/mozilla/geckodriver/releases/download/v0.21.0/geckodriver-v0.21.0-macos.tar.gz", "https://github.com/mozilla/geckodriver/releases/download/v0.21.0/geckodriver-v0.21.0-macos.tar.gz", ], ) def org_seleniumhq_py(): http_archive( name = "org_seleniumhq_py", build_file = str(Label("//build_files:org_seleniumhq_py.BUILD")), sha256 = "f9ca21919b564a0a86012cd2177923e3a7f37c4a574207086e710192452a7c40", strip_prefix = "selenium-3.14.0", urls = [ "https://files.pythonhosted.org/packages/af/7c/3f76140976b1c8f8a6b437ccd1f04efaed37bdc2600530e76ba981c677b9/selenium-3.14.0.tar.gz", ], ) def org_seleniumhq_selenium_api(): java_import_external( name = "org_seleniumhq_selenium_api", jar_sha256 = "1fc941f86ba4fefeae9a705c1468e65beeaeb63688e19ad3fcbda74cc883ee5b", jar_urls = [ "https://mirror.bazel.build/repo1.maven.org/maven2/org/seleniumhq/selenium/selenium-api/3.14.0/selenium-api-3.14.0.jar", "https://repo1.maven.org/maven2/org/seleniumhq/selenium/selenium-api/3.14.0/selenium-api-3.14.0.jar", ], licenses = ["notice"], # The Apache Software License, Version 2.0 testonly_ = 1, ) def org_seleniumhq_selenium_remote_driver(): java_import_external( name = "org_seleniumhq_selenium_remote_driver", jar_sha256 = "284cb4ea043539353bd5ecd774cbd726b705d423ea4569376c863d0b66e5eaf2", jar_urls = [ "https://mirror.bazel.build/repo1.maven.org/maven2/org/seleniumhq/selenium/selenium-remote-driver/3.14.0/selenium-remote-driver-3.14.0.jar", "https://repo1.maven.org/maven2/org/seleniumhq/selenium/selenium-remote-driver/3.14.0/selenium-remote-driver-3.14.0.jar", ], licenses = ["notice"], # The Apache Software License, Version 2.0 testonly_ = 1, deps = [ "@com_google_code_gson", "@com_google_guava", "@net_bytebuddy", "@com_squareup_okhttp3_okhttp", "@com_squareup_okio", "@commons_codec", "@commons_logging", "@org_apache_commons_exec", "@org_apache_httpcomponents_httpclient", "@org_apache_httpcomponents_httpcore", "@org_seleniumhq_selenium_api", ], )

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Python

code/tools/run_viz_single_task.py

santomon/taskonomy

4b22087a2686172b21b61589831061e7a386fe36

[ "MIT" ]

789

2018-03-21T05:28:38.000Z

2022-03-29T19:32:47.000Z

code/tools/run_viz_single_task.py

santomon/taskonomy

4b22087a2686172b21b61589831061e7a386fe36

[ "MIT" ]

46

2018-05-03T07:11:10.000Z

2022-03-11T23:26:03.000Z

code/tools/run_viz_single_task.py

santomon/taskonomy

4b22087a2686172b21b61589831061e7a386fe36

[ "MIT" ]

152

2018-03-24T10:20:44.000Z

2022-02-09T02:38:10.000Z

from __future__ import absolute_import, division, print_function import argparse import importlib import itertools import time from multiprocessing import Pool import numpy as np import os import pdb import pickle import subprocess import sys import tensorflow as tf import tensorflow.contrib.slim as slim import threading import init_paths from models.sample_models import * target_tasks = "autoencoder colorization curvature denoise edge2d edge3d ego_motion fix_pose impainting_whole jigsaw keypoint2d keypoint3d non_fixated_pose point_match reshade rgb2depth rgb2mist rgb2sfnorm room_layout segment25d segment2d vanishing_point_well_defined segmentsemantic_rb class_selected class_1000" list_of_tasks = target_tasks.split(" ") ON_TEST_SET = True IN_TRAIN_MODE = False parser = argparse.ArgumentParser(description='Viz Single Task') parser.add_argument('--idx', dest='idx', help='Task to run', type=int) parser.add_argument('--hs', dest='hs', help='Hidden size to use', type=int) parser.add_argument('--n-parallel', dest='n_parallel', help='Number of models to run in parallel', type=int) parser.set_defaults(n_parallel=1) tf.logging.set_verbosity(tf.logging.ERROR) ipython_std_out = sys.stdout # Disabe def blockPrint(): sys.stdout = open(os.devnull, 'w') # Restore def enablePrint(): sys.stdout = ipython_std_out # Force Print def forcePrint(str): enablePrint() print(str) sys.stdout.flush() blockPrint() def remove_dups(seq): seen = set() seen_add = seen.add return [x for x in seq if not (x in seen or seen_add(x))] pairs = list(itertools.product(list_of_tasks, list_of_tasks)) args = parser.parse_args() idx_to_run = args.idx if idx_to_run == -1: pairs_to_run = pairs else: pairs_to_run = pairs[idx_to_run:idx_to_run+1] def run_to_task(task_to): import general_utils from general_utils import RuntimeDeterminedEnviromentVars import models.architectures as architectures from data.load_ops import resize_rescale_image import utils from data.task_data_loading import load_and_specify_preprocessors_for_representation_extraction import lib.data.load_ops as load_ops tf.logging.set_verbosity(tf.logging.ERROR) all_outputs = {} pickle_dir = 'viz_output_single_task.pkl' import os if os.path.isfile(pickle_dir): with open( pickle_dir, 'rb') as fp: all_outputs = pickle.load(fp) for task in list_of_tasks: if task in all_outputs: print("{} already exists....\n\n\n".format(task)) continue print("Doing {task}".format(task=task)) general_utils = importlib.reload(general_utils) tf.reset_default_graph() training_runners = { 'sess': tf.InteractiveSession(), 'coord': tf.train.Coordinator() } # task = '{f}__{t}__{hs}'.format(f=task_from, t=task_to, hs=args.hs) CONFIG_DIR = '/home/ubuntu/task-taxonomy-331b/experiments/final/{TASK}'.format(TASK=task) ############## Load Configs ############## cfg = utils.load_config( CONFIG_DIR, nopause=True ) RuntimeDeterminedEnviromentVars.register_dict( cfg ) split_file = cfg['test_filenames'] if ON_TEST_SET else cfg['val_filenames'] cfg['train_filenames'] = split_file cfg['val_filenames'] = split_file cfg['test_filenames'] = split_file cfg['num_epochs'] = 1 cfg['randomize'] = False root_dir = cfg['root_dir'] cfg['num_read_threads'] = 1 print(cfg['log_root']) if task == 'jigsaw': continue cfg['model_path'] = os.path.join( cfg['log_root'], task, 'model.permanent-ckpt' ) print( cfg['model_path']) if cfg['model_path'] is None: continue ############## Set Up Inputs ############## # tf.logging.set_verbosity( tf.logging.INFO ) inputs = utils.setup_input( cfg, is_training=ON_TEST_SET, use_filename_queue=False ) # is_training determines whether to use train/validaiton RuntimeDeterminedEnviromentVars.load_dynamic_variables( inputs, cfg ) RuntimeDeterminedEnviromentVars.populate_registered_variables() start_time = time.time() # utils.print_start_info( cfg, inputs[ 'max_steps' ], is_training=False ) ############## Set Up Model ############## model = utils.setup_model( inputs, cfg, is_training=IN_TRAIN_MODE ) m = model[ 'model' ] model[ 'saver_op' ].restore( training_runners[ 'sess' ], cfg[ 'model_path' ] ) ############## Start dataloading workers ############## data_prefetch_init_fn = utils.get_data_prefetch_threads_init_fn( inputs, cfg, is_training=ON_TEST_SET, use_filename_queue=False ) prefetch_threads = threading.Thread( target=data_prefetch_init_fn, args=( training_runners[ 'sess' ], training_runners[ 'coord' ] )) prefetch_threads.start() ############## Run First Batch ############## if not hasattr(m, 'masks'): ( input_batch, target_batch, data_idx, predicted, loss, ) = training_runners['sess'].run( [ m.input_images, m.targets, model[ 'data_idxs' ], m.decoder_output, m.total_loss] ) mask_batch = 1. else: ( input_batch, target_batch, mask_batch, data_idx, predicted, loss, ) = training_runners['sess'].run( [ m.input_images, m.targets, m.masks, model[ 'data_idxs' ], m.decoder_output, m.total_loss] ) if task == 'segment2d' or task == 'segment25d': from sklearn.decomposition import PCA x = np.zeros((32,256,256,3), dtype='float') for i in range(predicted.shape[0]): embedding_flattened = np.squeeze(predicted[i]).reshape((-1,64)) pca = PCA(n_components=3) pca.fit(embedding_flattened) lower_dim = pca.transform(embedding_flattened).reshape((256,256,-1)) lower_dim = (lower_dim - lower_dim.min()) / (lower_dim.max() - lower_dim.min()) x[i] = lower_dim predicted = x ############## Clean Up ############## training_runners[ 'coord' ].request_stop() training_runners[ 'coord' ].join() # if os.path.isfile(pickle_dir): # with open(pickle_dir, 'rb') as fp: # all_outputs = pickle.load(fp) ############## Store to dict ############## to_store = { 'input': input_batch, 'target': target_batch, 'mask': mask_batch, 'data_idx':data_idx, 'output':predicted} all_outputs[task] = to_store print("Done: {}".format(task)) # os.system("sudo cp {d} /home/ubuntu/s3/model_log".format(d=pickle_dir)) ############## Reset graph and paths ############## tf.reset_default_graph() training_runners['sess'].close() try: del sys.modules[ 'config' ] except: pass sys.path = remove_dups(sys.path) print("FINISHED: {}\n\n\n\n\n\n".format(task)) pickle_dir = 'viz_output_single_task.pkl' with open( pickle_dir, 'wb') as fp: pickle.dump(all_outputs, fp) try: subprocess.call("aws s3 cp {} s3://task-preprocessing-512-oregon/visualizations/".format(pickle_dir), shell=True) except: subprocess.call("sudo cp {} /home/ubuntu/s3/visualizations/".format(pickle_dir), shell=True) return if __name__ == '__main__': run_to_task(None) # with Pool(args.n_parallel) as p: # p.map(run_to_task, list_of_tasks)

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ed6bae7a17f418cda8c2e6d4ee817869bb64ec62

35,884

bzl

Python

stratum/portage/build_defs.bzl

cholve/stratum

09ddb5acb604f7e694a6b7d2fe93fea79f801794

[ "Apache-2.0" ]

267

2019-09-11T15:01:37.000Z

2022-03-28T11:14:29.000Z

stratum/portage/build_defs.bzl

cholve/stratum

09ddb5acb604f7e694a6b7d2fe93fea79f801794

[ "Apache-2.0" ]

906

2019-09-18T03:37:08.000Z

2022-03-30T00:59:53.000Z

stratum/portage/build_defs.bzl

cholve/stratum

09ddb5acb604f7e694a6b7d2fe93fea79f801794

[ "Apache-2.0" ]

107

2019-09-16T07:30:53.000Z

2022-03-18T09:53:03.000Z

# Copyright 2018 Google LLC # Copyright 2018-present Open Networking Foundation # SPDX-License-Identifier: Apache-2.0 """A portable build system for Stratum P4 switch stack. To use this, load() this file in a BUILD file, specifying the symbols needed. The public symbols are the macros: decorate(path) sc_cc_lib Declare a portable Library. sc_proto_lib Declare a portable .proto Library. sc_cc_bin Declare a portable Binary. sc_package Declare a portable tarball package. and the variables/lists: ALL_ARCHES All known arches. EMBEDDED_ARCHES All embedded arches. EMBEDDED_PPC Name of PowerPC arch - "ppc". EMBEDDED_X86 Name of "x86" arch. HOST_ARCH Name of default "host" arch. HOST_ARCHES All host arches. STRATUM_INTERNAL For declaring Stratum internal visibility. The macros are like cc_library(), proto_library(), and cc_binary(), but with different options and some restrictions. The key difference: you can supply lists of architectures for which they should be compiled - defaults to all if left unstated. Internally, libraries and binaries are generated for every listed architecture. The names are decorated to keep them different and allow all to be generated and addressed independently. This aspect of the system is suboptimal - something along the lines of augmenting context with a user defined configuration fragment would be a much cleaner solution. Currently supported architectures: ppc x86 """ load("//tools/build_defs/label:def.bzl", "parse_label") load( "//devtools/build_cleaner/skylark:build_defs.bzl", "register_extension_info", ) load("@rules_proto//proto:defs.bzl", "proto_library") load("@rules_cc//cc:defs.bzl", "cc_binary", "cc_library", "cc_test") # Generic path & label helpers. ============================================ def _normpath(path): """Normalize a path. Normalizes a path by removing unnecessary path-up segments and its corresponding directories. Providing own implementation because import os is not allowed in build defs. For example ../../dir/to/deeply/nested/path/../../../other/path will become ../../dir/to/other/path Args: path: A valid absolute or relative path to normalize. Returns: A path equivalent to the input path with minimal use of path-up segments. Invalid input paths will stay invalid. """ sep = "/" level = 0 result = [] for d in path.split(sep): if d in ("", "."): if result: continue elif d == "..": if level > 0: result.pop() level += -1 continue else: level += 1 result.append(d) return sep.join(result) # Adds a suffix to a label, expanding implicit targets if needed. def decorate(label, suffix): if label.endswith(":"): # .../bar: -> .../bar label = label[:-1] if ":" in label: # .../bar:bat -> .../bar:bat_suffix return "%s_%s" % (label, suffix) elif label.startswith("//"): # //foo/bar -> //foo/bar:bar_suffix return "%s:%s_%s" % (label, label.split("/")[-1], suffix) else: # bar -> bar_suffix return "%s_%s" % (label, suffix) # Creates a relative filename from a label, replacing "//" and ":". def _make_filename(label): if label.startswith("//"): # //foo/bar:bat/baz -> google3_foo/bar/bat/baz return label.replace("//", "google3/").replace(":", "/") elif label.startswith(":"): # :bat/baz -> bat/baz return label[1:] else: # bat/baz -> bat/baz return label # Adds dquotes around a string. def dquote(s): return '"' + s + '"' # Adds squotes around a string. def squote(s): return "'" + s + "'" # Emulate Python 2.5+ str(startswith([prefix ...]) def starts_with(s, prefix_list): for prefix in prefix_list: if s.startswith(prefix): return prefix return None def sc_platform_select(host = None, ppc = None, x86 = None, default = None): """Public macro to alter blaze rules based on the platform architecture. Generates a blaze select(...) statement that can be used in most contexts to alter a blaze rule based on the target platform architecture. If no selection is provided for a given platform, {default} is used instead. A specific value or default must be provided for every target platform. Args: host: The value to use for host builds. ppc: The value to use for ppc builds. x86: The value to use for x86 builds. default: The value to use for any of {host,ppc,x86} that isn't specified. Returns: The requested selector. """ if default == None and (host == None or ppc == None or x86 == None): fail("Missing a select value for at least one platform in " + "sc_platform_select. Please add.") config_label_prefix = "//stratum:stratum_" return select({ "//conditions:default": (host or default), config_label_prefix + "ppc": (ppc or default), config_label_prefix + "x86": (x86 or default), }) # Generates an sc_platform_select based on a textual list of arches. def sc_platform_filter(value, default, arches): return sc_platform_select( host = value if "host" in arches else default, ppc = value if "ppc" in arches else default, x86 = value if "x86" in arches else default, ) def sc_platform_alias( name, host = None, ppc = None, x86 = None, default = None, visibility = None): """Public macro to create an alias that changes based on target arch. Generates a blaze alias that will select the appropriate target. If no selection is provided for a given platform and no default is set, a dummy default target is used instead. Args: name: The name of the alias target. host: The result of the alias for host builds. ppc: The result of the alias for ppc builds. x86: The result of the alias for x86 builds. default: The result of the alias for any of {host,ppc,x86} that isn't specified. visibility: The visibility of the alias target. """ native.alias( name = name, actual = sc_platform_select( default = default or "//stratum/portage:dummy", host = host, ppc = ppc, x86 = x86, ), visibility = visibility, ) # Embedded build definitions. ============================================== EMBEDDED_PPC = "ppc" EMBEDDED_X86 = "x86" EMBEDDED_ARCHES = [ EMBEDDED_PPC, EMBEDDED_X86, ] HOST_ARCH = "host" HOST_ARCHES = [HOST_ARCH] ALL_ARCHES = EMBEDDED_ARCHES + HOST_ARCHES # Identify Stratum platform arch for .pb.h shims and other portability hacks. _ARCH_DEFINES = sc_platform_select( default = ["STRATUM_ARCH_HOST"], ppc = ["STRATUM_ARCH_PPC"], x86 = ["STRATUM_ARCH_X86"], ) STRATUM_INTERNAL = [ "//stratum:__subpackages__", ] # # Build options for all embedded architectures # # Set _TRACE_SRCS to show sources in embedded sc_cc_lib compile steps. # This is more general than it may seem: genrule doesn't have hdrs or deps # attributes, so all embedded dependencies appear as a `src'. # TODO(unknown): if useful again then inject from cmdline else kill feature. _TRACE_SRCS = False # Used for all gcc invocations. _EMBEDDED_FLAGS = [ "-O0", # Don't use this for program-sizing build #-- "-Os", # Use this for program-sizing build "-g", # Don't use this for program-sizing build "-Wall", "-Werror", # Warn lots, and force fixing warnings. "-no-canonical-prefixes", # Don't mangle paths and confuse blaze. "-fno-builtin-malloc", # We'll use tcmalloc "-fno-builtin-calloc", "-fno-builtin-realloc", "-fno-builtin-free", "-D__STDC_FORMAT_MACROS=1", # TODO(unknown): Figure out how we can use $(CC_FLAGS) instead of this. "-D__GOOGLE_STL_LEGACY_COMPATIBILITY", ] # Used for C and C++ compiler invocations. _EMBEDDED_CFLAGS = [ "-I$(GENDIR)", ] # Used for C++ compiler invocations. _EMBEDDED_CXXFLAGS = [ "-std=gnu++11", # Allow C++11 features _and_ GNU extensions. ] # Used for linking binaries. _EMBEDDED_LDFLAGS = [ # "-static", # Use this for program-sizing build # "-Wl,--gc-sections,--no-wchar-size-warning", # Use this for program-sizing build ] # PPC ====================================================================== _PPC_GRTE = "//unsupported_toolchains/crosstoolng_powerpc32_8540/sysroot" # X86 ====================================================================== _X86_GRTE = "//grte/v4_x86/release/usr/grte/v4" # Portability definitions =================================================== def sc_cc_test( name, size = None, srcs = None, deps = None, data = None, defines = None, copts = None, linkopts = None, visibility = None): """Creates a cc_test rule that interacts safely with Stratum builds. Generates a cc_test rule that doesn't break the build when an embedded arch is selected. During embedded builds this target will generate a dummy binary and will not attempt to build any dependencies. Args: name: Analogous to cc_test name argument. size: Analogous to cc_test size argument. srcs: Analogous to cc_test srcs argument. deps: Analogous to cc_test deps argument. data: Analogous to cc_test data argument. defines: Analogous to cc_test defines argument. copts: Analogous to cc_test copts argument. linkopts: Analogous to cc_test linkopts argument. visibility: Analogous to cc_test visibility argument. """ cc_test( name = name, size = size or "small", srcs = sc_platform_select(host = srcs or [], default = []), deps = sc_platform_select( host = deps or [], default = ["//stratum/portage:dummy_with_main"], ), data = data or [], defines = defines, copts = copts, linkopts = linkopts, visibility = visibility, ) register_extension_info( extension_name = "sc_cc_test", label_regex_for_dep = "{extension_name}", ) def sc_cc_lib( name, deps = None, srcs = None, hdrs = None, arches = None, copts = None, defines = None, includes = None, include_prefix = None, strip_include_prefix = None, data = None, testonly = None, textual_hdrs = None, visibility = None, xdeps = None): """Creates rules for the given portable library and arches. Args: name: Analogous to cc_library name argument. deps: Analogous to cc_library deps argument. srcs: Analogous to cc_library srcs argument. hdrs: Analogous to cc_library hdrs argument. arches: List of architectures to generate this way. copts: Analogous to cc_library copts argument. defines: Symbols added as "-D" compilation options. includes: Paths to add as "-I" compilation options. include_prefix: Analogous to cc_library include_prefix argument. strip_include_prefix: Analogous to cc_library strip_include_prefix argument. data: Files to provide as data at runtime (host builds only). testonly: Standard blaze testonly parameter. textual_hdrs: Analogous to cc_library. visibility: Standard blaze visibility parameter. xdeps: External (file) dependencies of this library - no decorations assumed, used and exported as header, not for flags, libs, etc. """ alwayslink = 0 deps = depset(deps or []) srcs = depset(srcs or []) hdrs = depset(hdrs or []) xdeps = depset(xdeps or []) copts = depset(copts or []) includes = depset(includes or []) data = depset(data or []) textual_hdrs = depset(textual_hdrs or []) if srcs: if [s for s in srcs.to_list() if not s.endswith(".h")]: alwayslink = 1 if not arches: arches = ALL_ARCHES defs_plus = (defines or []) + _ARCH_DEFINES textual_plus = textual_hdrs | depset(deps.to_list()) cc_library( name = name, deps = sc_platform_filter(deps, [], arches), srcs = sc_platform_filter(srcs, [], arches), hdrs = sc_platform_filter(hdrs, [], arches), alwayslink = alwayslink, copts = sc_platform_filter(copts, [], arches), defines = defs_plus, includes = sc_platform_filter(includes, [], arches), include_prefix = include_prefix, strip_include_prefix = strip_include_prefix, testonly = testonly, textual_hdrs = sc_platform_filter( textual_plus | xdeps, [], arches, ), data = sc_platform_filter(data, [], arches), visibility = visibility, ) register_extension_info( extension_name = "sc_cc_lib", label_regex_for_dep = "{extension_name}", ) def sc_cc_bin( name, deps = None, srcs = None, arches = None, copts = None, defines = None, includes = None, testonly = None, visibility = None): """Creates rules for the given portable binary and arches. Args: name: Analogous to cc_binary name argument. deps: Analogous to cc_binary deps argument. srcs: Analogous to cc_binary srcs argument. arches: List of architectures to generate this way. copts: Analogous to cc_binary copts argument. defines: Symbols added as "-D" compilation options. includes: Paths to add as "-I" compilation options. testonly: Standard blaze testonly parameter. visibility: Standard blaze visibility parameter. """ deps = depset(deps or []) srcs = depset(srcs or []) if not arches: arches = ALL_ARCHES defs_plus = (defines or []) + _ARCH_DEFINES cc_binary( name = name, deps = sc_platform_filter( deps, ["//stratum/portage:dummy_with_main"], arches, ), srcs = sc_platform_filter(srcs, [], arches), copts = copts, defines = defs_plus, includes = includes, linkopts = ["-ldl", "-lutil"], testonly = testonly, visibility = visibility, ) register_extension_info( extension_name = "sc_cc_bin", label_regex_for_dep = "{extension_name}", ) # Protobuf ================================================================= _SC_GRPC_DEPS = [ "//sandblaze/prebuilt/grpc", "//sandblaze/prebuilt/grpc:grpc++_codegen_base", "//sandblaze/prebuilt/grpc:grpc++_codegen_proto_lib", ] _PROTOC = "@com_google_protobuf//:protobuf:protoc" _PROTOBUF = "@com_google_protobuf//:protobuf" _SC_GRPC_PLUGIN = "//sandblaze/prebuilt/protobuf:grpc_cpp_plugin" _GRPC_PLUGIN = "//grpc:grpc_cpp_plugin" def _loc(target): """Return target location for constructing commands. Args: target: Blaze target name available to this build. Returns: $(location target) """ return "$(location %s)" % target def _gen_proto_lib( name, srcs, hdrs, deps, arch, visibility, testonly, proto_include, grpc_shim_rule): """Creates rules and filegroups for embedded protobuf library. For every given ${src}.proto, generate: :${src}_${arch}.pb rule to run protoc ${src}.proto => ${src}.${arch}.pb.{h,cc} :${src}_${arch}.grpc.pb rule to run protoc w/ erpc plugin: ${src}.proto => ${src}.${arch}.grpc.pb.{h,cc} :${src}_${arch}_proto_rollup collects include options for protoc: ${src}_${arch}_proto_rollup.flags Feed each set into sc_cc_lib to wrap them them up into a usable library; note that ${src}_${arch}_erpc_proto depends on ${src}_${arch}_proto. Args: name: Base name for this library. srcs: List of proto files hdrs: More files to build into this library, but also exported for dependent rules to utilize. deps: List of deps for this library arch: Which architecture to build this library for. visibility: Standard blaze visibility parameter, passed through to subsequent rules. testonly: Standard blaze testonly parameter. proto_include: Include path for generated sc_cc_libs. grpc_shim_rule: If needed, the name of the grpc shim for this proto lib. """ bash_vars = ["g3=$${PWD}"] # TODO(unknown): Switch protobuf to using the proto_include mechanism protoc_label = _PROTOC protobuf_label = _PROTOBUF protobuf_hdrs = "%s:well_known_types_srcs" % protobuf_label protobuf_srcs = [protobuf_hdrs] protobuf_include = "$${g3}/protobuf/src" if arch in EMBEDDED_ARCHES: grpc_plugin = _SC_GRPC_PLUGIN else: grpc_plugin = _GRPC_PLUGIN protoc_deps = [] for dep in deps: if dep.endswith("_proto"): protoc_deps.append("%s_%s_headers" % (dep, arch)) name_arch = decorate(name, arch) # We use this filegroup to accumulate the set of .proto files needed to # compile this proto. native.filegroup( name = decorate(name_arch, "headers"), srcs = hdrs + protoc_deps, visibility = visibility, ) my_proto_rollup = decorate(name_arch, "proto_rollup.flags") protoc_srcs_set = (srcs + hdrs + protoc_deps + protobuf_srcs + [my_proto_rollup]) gen_srcs = [] gen_hdrs = [] grpc_gen_hdrs = [] grpc_gen_srcs = [] tools = [protoc_label] grpc_tools = [protoc_label, grpc_plugin] protoc = "$${g3}/%s" % _loc(protoc_label) grpc_plugin = "$${g3}/%s" % _loc(grpc_plugin) cpp_out = "$${g3}/$(GENDIR)/%s/%s" % (native.package_name(), arch) accum_flags = [] full_proto_include = None if proto_include == ".": full_proto_include = native.package_name() elif proto_include: full_proto_include = "%s/%s" % (native.package_name(), proto_include) if full_proto_include: temp_prefix = "%s/%s" % (cpp_out, native.package_name()[len(full_proto_include):]) # We do a bit of extra work with these include flags to avoid generating # warnings. accum_flags.append( "$$(if [[ -e $(GENDIR)/%s ]]; then echo -IG3LOC/$(GENDIR)/%s; fi)" % (full_proto_include, full_proto_include), ) accum_flags.append( "$$(if [[ -e %s ]]; then echo -IG3LOC/%s; fi)" % (full_proto_include, full_proto_include), ) else: temp_prefix = "%s/%s" % (cpp_out, native.package_name()) proto_rollups = [ decorate(decorate(dep, arch), "proto_rollup.flags") for dep in deps if dep.endswith("_proto") ] proto_rollup_cmds = ["printf '%%s\n' %s" % flag for flag in accum_flags] proto_rollup_cmds.append("cat $(SRCS)") proto_rollup_cmd = "{ %s; } | sort -u -o $(@)" % "; ".join(proto_rollup_cmds) native.genrule( name = decorate(name_arch, "proto_rollup"), srcs = proto_rollups, outs = [my_proto_rollup], cmd = proto_rollup_cmd, visibility = visibility, testonly = testonly, ) for src in srcs + hdrs: if src.endswith(".proto"): src_stem = src[0:-6] src_arch = "%s_%s" % (src_stem, arch) temp_stem = "%s/%s" % (temp_prefix, src_stem) gen_stem = "%s.%s" % (src_stem, arch) # We can't use $${PWD} until this step, because our rollup command # might be generated on another forge server. proto_path_cmds = ["rollup=$$(sed \"s,G3LOC,$${PWD},g\" %s)" % _loc(my_proto_rollup)] proto_rollup_flags = ["$${rollup}"] if proto_include: # We'll be cd-ing to another directory before protoc, so # adjust our .proto path accordingly. proto_src_loc = "%s/%s" % (native.package_name(), src) if proto_src_loc.startswith(full_proto_include + "/"): proto_src_loc = proto_src_loc[len(full_proto_include) + 1:] else: print("Invalid proto include '%s' doesn't match src %s" % (full_proto_include, proto_src_loc)) # By cd-ing to another directory, we force protoc to produce # different symbols. Careful, our proto might be in GENDIR! proto_path_cmds.append("; ".join([ "if [[ -e %s ]]" % ("%s/%s" % (full_proto_include, proto_src_loc)), "then cd %s" % full_proto_include, "else cd $(GENDIR)/%s" % full_proto_include, "fi", ])) gendir_include = ["-I$${g3}/$(GENDIR)", "-I$${g3}", "-I."] else: proto_src_loc = "%s/%s" % (native.package_name(), src) proto_path_cmds.append("[[ -e %s ]] || cd $(GENDIR)" % proto_src_loc) gendir_include = ["-I$(GENDIR)", "-I."] # Generate messages gen_pb_h = gen_stem + ".pb.h" gen_pb_cc = gen_stem + ".pb.cc" gen_hdrs.append(gen_pb_h) gen_srcs.append(gen_pb_cc) cmds = bash_vars + [ "mkdir -p %s" % temp_prefix, ] + proto_path_cmds + [ " ".join([protoc] + gendir_include + proto_rollup_flags + [ "-I%s" % protobuf_include, "--cpp_out=%s" % cpp_out, proto_src_loc, ]), "cd $${g3}", "cp %s.pb.h %s" % (temp_stem, _loc(gen_pb_h)), "cp %s.pb.cc %s" % (temp_stem, _loc(gen_pb_cc)), ] pb_outs = [gen_pb_h, gen_pb_cc] native.genrule( name = src_arch + ".pb", srcs = protoc_srcs_set, outs = pb_outs, tools = tools, cmd = " && ".join(cmds), heuristic_label_expansion = 0, visibility = visibility, ) # Generate GRPC if grpc_shim_rule: gen_grpc_pb_h = gen_stem + ".grpc.pb.h" gen_grpc_pb_cc = gen_stem + ".grpc.pb.cc" grpc_gen_hdrs.append(gen_grpc_pb_h) grpc_gen_srcs.append(gen_grpc_pb_cc) cmds = bash_vars + [ "mkdir -p %s" % temp_prefix, ] + proto_path_cmds + [ " ".join([ protoc, "--plugin=protoc-gen-grpc-cpp=%s" % grpc_plugin, ] + gendir_include + proto_rollup_flags + [ "-I%s" % protobuf_include, "--grpc-cpp_out=%s" % cpp_out, proto_src_loc, ]), "cd $${g3}", "cp %s.grpc.pb.h %s" % (temp_stem, _loc(gen_grpc_pb_h)), "cp %s.grpc.pb.cc %s" % (temp_stem, _loc(gen_grpc_pb_cc)), ] grpc_pb_outs = [gen_grpc_pb_h, gen_grpc_pb_cc] native.genrule( name = src_arch + ".grpc.pb", srcs = protoc_srcs_set, outs = grpc_pb_outs, tools = grpc_tools, cmd = " && ".join(cmds), heuristic_label_expansion = 0, visibility = visibility, ) dep_set = depset(deps) | [protobuf_label] includes = [] if proto_include: includes = [proto_include] # Note: Public sc_proto_lib invokes this once per (listed) arch; # which then calls sc_cc_lib with same name for each arch; # multiple such calls are OK as long as the arches are disjoint. sc_cc_lib( name = decorate(name, arch), deps = dep_set, srcs = gen_srcs, hdrs = hdrs + gen_hdrs, arches = [arch], copts = [], includes = includes, testonly = testonly, textual_hdrs = gen_hdrs, visibility = visibility, ) if grpc_shim_rule: grpc_name = name[:-6] + "_grpc_proto" grpc_dep_set = dep_set | [name] | _SC_GRPC_DEPS grpc_gen_hdrs_plus = grpc_gen_hdrs + gen_hdrs sc_cc_lib( name = decorate(grpc_name, arch), deps = grpc_dep_set, srcs = grpc_gen_srcs, hdrs = hdrs + grpc_gen_hdrs_plus + [grpc_shim_rule], arches = [arch], copts = [], includes = includes, testonly = testonly, textual_hdrs = grpc_gen_hdrs_plus, visibility = visibility, ) def _gen_proto_shims(name, pb_modifier, srcs, arches, visibility): """Macro to build .pb.h multi-arch master switch for sc_proto_lib. For each src path.proto, generates path.pb.h consisting of: #ifdef logic to select path.${arch}.pb.h Also generates an alias that will select the appropriate proto target based on the currently selected platform architecture. Args: name: Base name for this library. pb_modifier: protoc plugin-dependent file extension (e.g.: .pb) srcs: List of proto files. arches: List of arches this shim should support. visibility: The blaze visibility of the generated alias. Returns: Name of shim rule for use in follow-on hdrs and/or src lists. """ outs = [] cmds = [] hdr_ext = pb_modifier + ".h" for src in srcs: pkg, filename = parse_label(src) if not filename.endswith(".proto"): continue hdr_stem = filename[0:-6] new_hdr_name = hdr_stem + hdr_ext outs.append(new_hdr_name) # Generate lines for shim switch file. # Lines expand inside squotes, so quote accordingly. include_fmt = "#include " + dquote(pkg + "/" + hdr_stem + ".%s" + hdr_ext) lines = [ "#if defined(STRATUM_ARCH_%s)" % "PPC", include_fmt % "ppc", "#elif defined(STRATUM_ARCH_%s)" % "X86", include_fmt % "x86", "#elif defined(STRATUM_ARCH_%s)" % "HOST", include_fmt % "host", "#else", "#error Unknown STRATUM_ARCH", "#endif", ] gen_cmds = [("printf '%%s\\n' '%s'" % line) for line in lines] new_hdr_loc = "$(location %s)" % new_hdr_name cmds.append("{ %s; } > %s" % (" && ".join(gen_cmds), new_hdr_loc)) shim_rule = decorate(name, "shims") native.genrule( name = shim_rule, srcs = srcs, outs = outs, cmd = " && ".join(cmds) or "true", ) sc_platform_alias( name = name, host = decorate(name, "host") if "host" in arches else None, ppc = decorate(name, "ppc") if "ppc" in arches else None, x86 = decorate(name, "x86") if "x86" in arches else None, visibility = visibility, ) return shim_rule def _gen_py_proto_lib(name, srcs, deps, visibility, testonly): """Creates a py_proto_library from the given srcs. There's no clean way to make python protos work with sc_proto_lib's proto_include field, so we keep this simple. For library "name", generates: * ${name}_default_pb, a regular proto library. * ${name}_py, a py_proto_library based on ${name}_default_pb. Args: name: Standard blaze name argument. srcs: Standard blaze srcs argument. deps: Standard blaze deps argument. visibility: Standard blaze visibility argument. testonly: Standard blaze testonly argument. """ regular_proto_name = decorate(name, "default_pb") py_name = decorate(name, "py") proto_library( name = regular_proto_name, srcs = srcs, deps = [decorate(dep, "default_pb") for dep in deps], visibility = visibility, testonly = testonly, ) native.py_proto_library( name = py_name, api_version = 2, deps = [regular_proto_name], visibility = visibility, testonly = testonly, ) # TODO(unknown): Add support for depending on normal proto_library rules. def sc_proto_lib( name = None, srcs = [], hdrs = [], deps = [], arches = [], visibility = None, testonly = None, proto_include = None, python_support = False, services = []): """Public macro to build multi-arch library from Message protobuf(s). For library "name", generates: * ${name}_shim aka .pb.h master switch - see _gen_proto_shims, above. * ${name}_${arch}_pb protobuf compile rules - one for each arch. * sc_cc_lib(name) with those as input. * ${name}_py a py_proto_library version of this library. Only generated if python_support == True. Args: name: Base name for this library. srcs: List of .proto files - private to this library. hdrs: As above, but also exported for dependent rules to utilize. deps: List of deps for this library arches: Which architectures to build this library for, None => ALL. visibility: Standard blaze visibility parameter, passed through to subsequent rules. testonly: Standard blaze testonly parameter. proto_include: Path to add to include path. This will affect the symbols generated by protoc, as well as the include paths used for both sc_cc_lib and sc_proto_lib rules that depend on this rule. Typically "." python_support: Defaults to False. If True, generate a python proto library from this rule. Any sc_proto_lib with python support may only depend on sc_proto_libs that also have python support, and may not use the proto_include field in this rule. services: List of services to enable {"grpc", "rpc"}; Only "grpc" is supported. So "rpc" and "grpc" are equivalent. """ if not arches: if testonly: arches = HOST_ARCHES else: arches = ALL_ARCHES service_enable = { "grpc": 0, } for service in services or []: if service == "grpc": service_enable["grpc"] = 1 elif service == "rpc": service_enable["grpc"] = 1 else: fail("service='%s' not in (grpc, rpc)" % service) deps = depset(deps or []) shim_rule = _gen_proto_shims( name = name, pb_modifier = ".pb", srcs = srcs + hdrs, arches = arches, visibility = visibility, ) grpc_shim_rule = None if (service_enable["grpc"]): grpc_shim_rule = _gen_proto_shims( name = decorate(name[:-6], "grpc_proto"), pb_modifier = ".grpc.pb", srcs = srcs + hdrs, arches = arches, visibility = visibility, ) for arch in arches: _gen_proto_lib( name = name, srcs = srcs, hdrs = [shim_rule] + hdrs, deps = deps, arch = arch, visibility = visibility, testonly = testonly, proto_include = proto_include, grpc_shim_rule = grpc_shim_rule, ) if python_support: if proto_include: fail("Cannot use proto_include on an sc_proto_lib with python support.") _gen_py_proto_lib( name = name, srcs = depset(srcs + hdrs), deps = deps, visibility = visibility, testonly = testonly, ) register_extension_info( extension_name = "sc_proto_lib", label_regex_for_dep = "{extension_name}", ) def sc_package( name = None, bins = None, data = None, deps = None, arches = None, visibility = None): """Public macro to package binaries and data for deployment. For package "name", generates: * ${name}_${arch}_bin and ${name}_${arch}_data filesets containing respectively all of the binaries and all of the data needed for this package and all dependency packages. * ${name}_${arch} fileset containing the corresponding bin and data filesets, mapped to bin/ and share/ respectively. * ${name}_${arch}_tarball rule builds that .tar.gz package. Args: name: Base name for this package. bins: List of sc_cc_bin rules to be packaged. data: List of files (and file producing rules) to be packaged. deps: List of other sc_packages to add to this package. arches: Which architectures to build this library for, None => EMBEDDED_ARCHES (HOST_ARCHES not generally supported). visibility: Standard blaze visibility parameter, passed through to all filesets. """ bins = depset(bins or []) data = depset(data or []) deps = depset(deps or []) if not arches: arches = EMBEDDED_ARCHES fileset_name = decorate(name, "fs") for extension, inputs in [ ("bin", ["%s.stripped" % b for b in bins.to_list()]), ("data", data), ]: native.Fileset( name = decorate(fileset_name, extension), out = decorate(name, extension), entries = [ native.FilesetEntry( files = inputs, ), ] + [ native.FilesetEntry(srcdir = decorate(dep, extension)) for dep in deps.to_list() ], visibility = visibility, ) # Add any platform specific files to the final tarball. platform_entries = sc_platform_select( # We use a different ppc toolchain for Stratum. # This means that we must provide portable shared libs for our ppc # executables. ppc = [native.FilesetEntry( srcdir = "%s:BUILD" % _PPC_GRTE, files = [":libs"], destdir = "lib/stratum", symlinks = "dereference", )], default = [], ) native.Fileset( name = fileset_name, out = name, entries = [ native.FilesetEntry( srcdir = decorate(name, "bin"), destdir = "bin", ), native.FilesetEntry( srcdir = decorate(name, "data"), destdir = "share", ), ] + platform_entries, visibility = visibility, ) outs = ["%s.tar.gz" % name] # Copy our files into a temporary directory and make any necessary changes # before tarballing. cmds = [ "TEMP_DIR=$(@D)/stratum_packaging_temp", "mkdir $${TEMP_DIR}", "cp -r %s $${TEMP_DIR}/tarball" % _loc(fileset_name), "if [[ -e $${TEMP_DIR}/tarball/bin ]]", "then for f in $${TEMP_DIR}/tarball/bin/*.stripped", " do mv $${f} $${f%.stripped}", # rename not available. "done", "fi", "tar czf %s -h -C $${TEMP_DIR}/tarball ." % _loc(name + ".tar.gz"), "rm -rf $${TEMP_DIR}", ] native.genrule( name = decorate(name, "tarball"), srcs = [":%s" % fileset_name], outs = outs, cmd = "; ".join(cmds), visibility = visibility, )

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ed6c12390ca654e898450e0424a1c59a124edd59

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Python

src/genie/libs/parser/ios/tests/test_show_platform.py

miuvlad/genieparser

60b1151e3c67c6b55d75e30359d0bf52825efad8

[ "Apache-2.0" ]

null

src/genie/libs/parser/ios/tests/test_show_platform.py

miuvlad/genieparser

60b1151e3c67c6b55d75e30359d0bf52825efad8

[ "Apache-2.0" ]

null

src/genie/libs/parser/ios/tests/test_show_platform.py

miuvlad/genieparser

60b1151e3c67c6b55d75e30359d0bf52825efad8

[ "Apache-2.0" ]

null

#!/bin/env python import unittest from unittest.mock import Mock from pyats.topology import Device from genie.metaparser.util.exceptions import SchemaEmptyParserError,\ SchemaMissingKeyError from genie.libs.parser.ios.show_platform import ShowVersion,\ Dir,\ ShowRedundancy,\ ShowInventory,\ ShowBootvar, \ ShowProcessesCpuSorted,\ ShowProcessesCpu,\ ShowVersionRp,\ ShowPlatform,\ ShowPlatformPower,\ ShowProcessesCpuHistory,\ ShowProcessesCpuPlatform,\ ShowPlatformSoftwareStatusControl,\ ShowPlatformSoftwareSlotActiveMonitorMem,\ ShowPlatformHardware,\ ShowPlatformHardwarePlim,\ ShowPlatformHardwareQfpBqsOpmMapping,\ ShowPlatformHardwareQfpBqsIpmMapping,\ ShowPlatformHardwareSerdes,\ ShowPlatformHardwareSerdesInternal,\ ShowPlatformHardwareQfpBqsStatisticsChannelAll,\ ShowPlatformHardwareQfpInterfaceIfnameStatistics,\ ShowPlatformHardwareQfpStatisticsDrop,\ ShowEnvironment,\ ShowModule,\ ShowSwitch, ShowSwitchDetail from genie.libs.parser.iosxe.tests.test_show_platform import TestShowPlatform as test_show_platform_iosxe,\ TestShowPlatformPower as test_show_platform_power_iosxe,\ TestShowVersionRp as test_show_version_rp_iosxe,\ TestShowProcessesCpu as test_show_processes_cpu_iosxe,\ TestShowProcessesCpuHistory as test_show_processes_cpu_history_iosxe,\ TestShowProcessesCpuPlatform as test_show_processes_cpu_platform_iosxe,\ TestShowPlatformSoftwareStatusControlProcessorBrief as test_show_platform_software_status_control_processor_brief_iosxe,\ TestShowPlatformSoftwareSlotActiveMonitorMemSwap as test_show_platform_software_slot_active_monitor_Mem_iosxe,\ TestShowPlatformHardware as test_show_platform_hardware_iosxe,\ TestShowPlatformHardwarePlim as test_show_platform_hardware_plim_iosxe,\ TestShowPlatformHardwareQfpBqsOpmMapping as test_show_platform_hardware_qfp_bqs_opm_mapping_iosxe,\ TestShowPlatformHardwareQfpBqsIpmMapping as test_show_platform_hardware_qfp_bqs_ipm_mapping_iosxe,\ TestShowPlatformHardwareSerdesStatistics as test_show_platform_hardware_serdes_statistics_iosxe,\ TestShowPlatformHardwareSerdesStatisticsInternal as test_show_platform_hardware_serdes_statistics_internal_iosxe,\ ShowPlatformHardwareQfpBqsStatisticsChannelAll as show_platform_hardware_qfp_bqs_statistics_channel_all_iosxe,\ ShowPlatformHardwareQfpInterface as show_platform_hardware_qfp_interface_iosxe,\ TestShowPlatformHardwareQfpStatisticsDrop as test_show_platform_hardware_qfp_statistics_drop_iosxe,\ TestShowEnv as test_show_env_iosxe,\ TestShowModule as test_show_module_iosxe,\ TestShowSwitch as test_show_switch_iosxe,\ TestShowSwitchDetail as test_show_switch_detail_iosxe class TestShowVersion(unittest.TestCase): dev1 = Device(name='empty') dev_iosv = Device(name='iosv') empty_output = {'execute.return_value': ''} semi_empty_output = {'execute.return_value': '''\ ROM: Bootstrap program is IOSv '''} golden_parsed_output_iosv = { "version": { "last_reload_reason": "Unknown reason", "hostname": "N95_1", "os": "IOS", "version_short": "15.6", "number_of_intfs": { "Gigabit Ethernet": "6" }, "version": "15.6(3)M2", "rtr_type": "IOSv", "chassis_sn": "9K66Z7TOKAACDEQA24N7S", "chassis": "IOSv", "image_id": "VIOS-ADVENTERPRISEK9-M", 'compiled_by': 'prod_rel_team', 'compiled_date': 'Wed 29-Mar-17 14:05', "processor_type": "revision 1.0", "platform": "IOSv", "image_type": "production image", 'processor_board_flash': '10080K', 'returned_to_rom_by': 'reload', "main_mem": "435457", "mem_size": { "non-volatile configuration": "256" }, "system_image": "flash0:/vios-adventerprisek9-m", "curr_config_register": "0x0", "rom": "Bootstrap program is IOSv", "uptime": "1 day, 16 hours, 42 minutes" } } golden_output_iosv = {'execute.return_value': '''\ Cisco IOS Software, IOSv Software (VIOS-ADVENTERPRISEK9-M), Version 15.6(3)M2, RELEASE SOFTWARE (fc2) Technical Support: http://www.cisco.com/techsupport Copyright (c) 1986-2017 by Cisco Systems, Inc. Compiled Wed 29-Mar-17 14:05 by prod_rel_team ROM: Bootstrap program is IOSv N95_1 uptime is 1 day, 16 hours, 42 minutes System returned to ROM by reload System image file is "flash0:/vios-adventerprisek9-m" Last reload reason: Unknown reason This product contains cryptographic features and is subject to United States and local country laws governing import, export, transfer and use. Delivery of Cisco cryptographic products does not imply third-party authority to import, export, distribute or use encryption. Importers, exporters, distributors and users are responsible for compliance with U.S. and local country laws. By using this product you agree to comply with applicable laws and regulations. If you are unable to comply with U.S. and local laws, return this product immediately. A summary of U.S. laws governing Cisco cryptographic products may be found at: http://www.cisco.com/wwl/export/crypto/tool/stqrg.html If you require further assistance please contact us by sending email to export@cisco.com. Cisco IOSv (revision 1.0) with with 435457K/87040K bytes of memory. Processor board ID 9K66Z7TOKAACDEQA24N7S 6 Gigabit Ethernet interfaces DRAM configuration is 72 bits wide with parity disabled. 256K bytes of non-volatile configuration memory. 2097152K bytes of ATA System CompactFlash 0 (Read/Write) 0K bytes of ATA CompactFlash 1 (Read/Write) 0K bytes of ATA CompactFlash 2 (Read/Write) 10080K bytes of ATA CompactFlash 3 (Read/Write) Configuration register is 0x0'''} golden_parsed_output_ios = { 'version': {'bootldr': 'C3750E Boot Loader (C3750X-HBOOT-M) Version ' '15.2(3r)E, RELEASE SOFTWARE (fc1)', 'chassis': 'WS-C3750X-24P', 'chassis_sn': 'FDO2028F1WK', 'curr_config_register': '0xF', 'compiled_by': 'prod_rel_team', 'compiled_date': 'Wed 26-Jun-13 09:56', 'hostname': 'R5', 'image_id': 'C3750E-UNIVERSALK9-M', 'image_type': 'production image', 'last_reload_reason': 'power-on', 'license_level': 'ipservices', 'license_type': 'Permanent', 'main_mem': '262144', 'mem_size': {'flash-simulated non-volatile configuration': '512'}, 'next_reload_license_level': 'ipservices', 'number_of_intfs': {'Gigabit Ethernet': '28', 'Ten Gigabit Ethernet': '2', 'Virtual Ethernet': '2', 'Gigabit Ethernet': '28', 'FastEthernet': '1' }, 'os': 'IOS', 'platform': 'C3750E', 'processor_type': 'PowerPC405', 'returned_to_rom_by': 'power-on', 'rom': 'Bootstrap program is C3750E boot loader', 'rtr_type': 'WS-C3750X-24P', 'system_image': 'flash:c3750e-universalk9-mz', 'system_restarted_at': '12:22:21 PDT Mon Sep 10 2018', 'uptime': '9 weeks, 4 days, 2 hours, 3 minutes', 'version': '12.2(55)SE8', 'version_short': '12.2' } } golden_output_ios = {'execute.return_value': '''\ Cisco IOS Software, C3750E Software (C3750E-UNIVERSALK9-M), Version 12.2(55)SE8, RELEASE SOFTWARE (fc2) Technical Support: http://www.cisco.com/techsupport Copyright (c) 1986-2013 by Cisco Systems, Inc. Compiled Wed 26-Jun-13 09:56 by prod_rel_team Image text-base: 0x00003000, data-base: 0x02800000 ROM: Bootstrap program is C3750E boot loader BOOTLDR: C3750E Boot Loader (C3750X-HBOOT-M) Version 15.2(3r)E, RELEASE SOFTWARE (fc1) R5 uptime is 9 weeks, 4 days, 2 hours, 3 minutes System returned to ROM by power-on System restarted at 12:22:21 PDT Mon Sep 10 2018 System image file is "flash:c3750e-universalk9-mz" This product contains cryptographic features and is subject to United States and local country laws governing import, export, transfer and use. Delivery of Cisco cryptographic products does not imply third-party authority to import, export, distribute or use encryption. Importers, exporters, distributors and users are responsible for compliance with U.S. and local country laws. By using this product you agree to comply with applicable laws and regulations. If you are unable to comply with U.S. and local laws, return this product immediately. A summary of U.S. laws governing Cisco cryptographic products may be found at: http://www.cisco.com/wwl/export/crypto/tool/stqrg.html If you require further assistance please contact us by sending email to export@cisco.com. License Level: ipservices License Type: Permanent Next reload license Level: ipservices cisco WS-C3750X-24P (PowerPC405) processor (revision W0) with 262144K bytes of memory. Processor board ID FDO2028F1WK Last reset from power-on 2 Virtual Ethernet interfaces 1 FastEthernet interface 28 Gigabit Ethernet interfaces 2 Ten Gigabit Ethernet interfaces The password-recovery mechanism is enabled. 512K bytes of flash-simulated non-volatile configuration memory. Base ethernet MAC Address : 84:3D:C6:FF:F1:B8 Motherboard assembly number : 73-15476-04 Motherboard serial number : FDO202907UH Model revision number : W0 Motherboard revision number : B0 Model number : WS-C3750X-24P-L Daughterboard assembly number : 800-32727-03 Daughterboard serial number : FDO202823P8 System serial number : FDO2028F1WK Top Assembly Part Number : 800-38990-01 Top Assembly Revision Number : F0 Version ID : V07 CLEI Code Number : CMMPP00DRB Hardware Board Revision Number : 0x05 Switch Ports Model SW Version SW Image ------ ----- ----- ---------- ---------- * 1 30 WS-C3750X-24P 12.2(55)SE8 C3750E-UNIVERSALK9-M Configuration register is 0xF '''} golden_parsed_output_ios_cat6k = { "version": { "os": "IOS", "version_short": "12.2", "platform": "s72033_rp", "version": "12.2(18)SXF7", "image_id": "s72033_rp-ADVENTERPRISEK9_WAN-M", 'compiled_by': 'kellythw', 'compiled_date': 'Thu 23-Nov-06 06:26', "image_type": "production image", "rom": "System Bootstrap, Version 12.2(17r)S4, RELEASE SOFTWARE (fc1)", "bootldr": "s72033_rp Software (s72033_rp-ADVENTERPRISEK9_WAN-M), Version 12.2(18)SXF7, RELEASE SOFTWARE (fc1)", "hostname": "cat6k_tb1", "uptime": "10 weeks, 5 days, 5 hours, 16 minutes", "system_image": "disk0:s72033-adventerprisek9_wan-mz.122-18.SXF7", "chassis": "WS-C6503-E", "main_mem": "983008", "processor_type": "R7000", 'sp_by': 'power on', 'returned_to_rom_at': '21:57:23 UTC Sat Aug 28 2010', 'returned_to_rom_by': 'power cycle', "rtr_type": "WS-C6503-E", "chassis_sn": "FXS1821Q2H9", "last_reload_reason": "s/w reset", 'processor_board_flash': '65536K', "number_of_intfs": { "Gigabit Ethernet/IEEE 802.3": "50", 'Virtual Ethernet/IEEE 802.3': '1' }, "mem_size": {"non-volatile configuration": "1917", "packet buffer": "8192"}, "curr_config_register": "0x2102", } } golden_output_ios_cat6k = {'execute.return_value': ''' show version Cisco Internetwork Operating System Software IOS (tm) s72033_rp Software (s72033_rp-ADVENTERPRISEK9_WAN-M), Version 12.2(18)SXF7, RELEASE SOFTWARE (fc1) Technical Support: http://www.cisco.com/techsupport Copyright (c) 1986-2006 by cisco Systems, Inc. Compiled Thu 23-Nov-06 06:26 by kellythw Image text-base: 0x40101040, data-base: 0x42D98000 ROM: System Bootstrap, Version 12.2(17r)S4, RELEASE SOFTWARE (fc1) BOOTLDR: s72033_rp Software (s72033_rp-ADVENTERPRISEK9_WAN-M), Version 12.2(18)SXF7, RELEASE SOFTWARE (fc1) cat6k_tb1 uptime is 10 weeks, 5 days, 5 hours, 16 minutes Time since cat6k_tb1 switched to active is 10 weeks, 5 days, 5 hours, 15 minutes System returned to ROM by power cycle at 21:57:23 UTC Sat Aug 28 2010 (SP by power on) System image file is "disk0:s72033-adventerprisek9_wan-mz.122-18.SXF7" This product contains cryptographic features and is subject to United States and local country laws governing import, export, transfer and use. Delivery of Cisco cryptographic products does not imply third-party authority to import, export, distribute or use encryption. Importers, exporters, distributors and users are responsible for compliance with U.S. and local country laws. By using this product you agree to comply with applicable laws and regulations. If you are unable to comply with U.S. and local laws, return this product immediately. A summary of U.S. laws governing Cisco cryptographic products may be found at: http://www.cisco.com/wwl/export/crypto/tool/stqrg.html If you require further assistance please contact us by sending email to export@cisco.com. cisco WS-C6503-E (R7000) processor (revision 1.4) with 983008K/65536K bytes of memory. Processor board ID FXS1821Q2H9 SR71000 CPU at 600Mhz, Implementation 0x504, Rev 1.2, 512KB L2 Cache Last reset from s/w reset SuperLAT software (copyright 1990 by Meridian Technology Corp). X.25 software, Version 3.0.0. Bridging software. TN3270 Emulation software. 1 Virtual Ethernet/IEEE 802.3 interface 50 Gigabit Ethernet/IEEE 802.3 interfaces 1917K bytes of non-volatile configuration memory. 8192K bytes of packet buffer memory. 65536K bytes of Flash internal SIMM (Sector size 512K). Configuration register is 0x2102 '''} golden_output_ios_1 = {'execute.return_value': '''\ Cisco IOS Software, C3750E Software (C3750E-UNIVERSALK9-M), Version 15.2(2)E8, RELEASE SOFTWARE (fc1) Technical Support: http://www.cisco.com/techsupport Copyright (c) 1986-2018 by Cisco Systems, Inc. Compiled Mon 22-Jan-18 04:07 by prod_rel_team ROM: Bootstrap program is C3750E boot loader BOOTLDR: C3750E Boot Loader (C3750X-HBOOT-M) Version 12.2(58r)SE, RELEASE SOFTWARE (fc1) sample_switch uptime is 8 weeks, 3 days, 10 hours, 27 minutes System returned to ROM by power-on System restarted at 05:06:40 GMT Tue Sep 10 2019 System image file is "flash:c3750e-universalk9-mz.152-2.E8.bin" Last reload reason: Reload command This product contains cryptographic features and is subject to United States and local country laws governing import, export, transfer and use. Delivery of Cisco cryptographic products does not imply third-party authority to import, export, distribute or use encryption. Importers, exporters, distributors and users are responsible for compliance with U.S. and local country laws. By using this product you agree to comply with applicable laws and regulations. If you are unable to comply with U.S. and local laws, return this product immediately. A summary of U.S. laws governing Cisco cryptographic products may be found at: http://www.cisco.com/wwl/export/crypto/tool/stqrg.html If you require further assistance please contact us by sending email to export@cisco.com. License Level: ipservices License Type: Permanent Next reload license Level: ipservices cisco WS-C3750X-24S (PowerPC405) processor (revision A0) with 524288K bytes of memory. Processor board ID FDO1633Q14S Last reset from power-on 14 Virtual Ethernet interfaces 1 FastEthernet interface 28 Gigabit Ethernet interfaces 2 Ten Gigabit Ethernet interfaces The password-recovery mechanism is enabled. 512K bytes of flash-simulated non-volatile configuration memory. Base ethernet MAC Address : AC:F2:C5:FF:55:E7 Motherboard assembly number : 73-13061-04 Motherboard serial number : FDO1633Q14M Model revision number : A0 Motherboard revision number : A0 Model number : WS-C3750X-24S-E Daughterboard assembly number : 800-32727-03 Daughterboard serial number : FDO172217ED System serial number : FDO1633Q14S Top Assembly Part Number : 800-33746-04 Top Assembly Revision Number : B0 Version ID : V03 CLEI Code Number : CMMFF00ARC Hardware Board Revision Number : 0x04 Switch Ports Model SW Version SW Image ------ ----- ----- ---------- ---------- * 1 30 WS-C3750X-24S 15.2(2)E8 C3750E-UNIVERSALK9-M Configuration register is 0xF '''} golden_parsed_output_ios_1 = { 'version': {'version_short': '15.2', 'platform': 'C3750E', 'version': '15.2(2)E8', 'image_id': 'C3750E-UNIVERSALK9-M', 'os': 'IOS', 'image_type': 'production image', 'compiled_date': 'Mon 22-Jan-18 04:07', 'compiled_by': 'prod_rel_team', 'rom': 'Bootstrap program is C3750E boot loader', 'bootldr': 'C3750E Boot Loader (C3750X-HBOOT-M) Version 12.2(58r)SE, RELEASE SOFTWARE (fc1)', 'hostname': 'sample_switch', 'uptime': '8 weeks, 3 days, 10 hours, 27 minutes', 'returned_to_rom_by': 'power-on', 'system_restarted_at': '05:06:40 GMT Tue Sep 10 2019', 'system_image': 'flash:c3750e-universalk9-mz.152-2.E8.bin', 'last_reload_reason': 'power-on', 'license_level': 'ipservices', 'license_type': 'Permanent', 'next_reload_license_level': 'ipservices', 'chassis': 'WS-C3750X-24S', 'main_mem': '524288', 'processor_type': 'PowerPC405', 'rtr_type': 'WS-C3750X-24S', 'chassis_sn': 'FDO1633Q14S', 'number_of_intfs': { 'Virtual Ethernet': '14', 'FastEthernet': '1', 'Gigabit Ethernet': '28', 'Ten Gigabit Ethernet': '2' }, 'mem_size': { 'flash-simulated non-volatile configuration': '512' }, 'curr_config_register': '0xF' } } device_output = {'execute.return_value':''' best-c3945-IOS3#show version Cisco IOS Software, C3900 Software (C3900-UNIVERSALK9-M), Version 15.0(1)M7, RELEASE SOFTWARE (fc2) Technical Support: http://www.cisco.com/techsupport Copyright (c) 1986-2011 by Cisco Systems, Inc. Compiled Fri 05-Aug-11 00:32 by prod_rel_team ROM: System Bootstrap, Version 15.0(1r)M13, RELEASE SOFTWARE (fc1) best-c3945-IOS3 uptime is 1 hour, 20 minutes System returned to ROM by reload at 10:26:47 EST Mon Dec 9 2019 System restarted at 10:27:57 EST Mon Dec 9 2019 System image file is "flash0:c3900-universalk9-mz.SPA.150-1.M7.bin" Last reload type: Normal Reload Last reload reason: Reload Command This product contains cryptographic features and is subject to United States and local country laws governing import, export, transfer and use. Delivery of Cisco cryptographic products does not imply third-party authority to import, export, distribute or use encryption. Importers, exporters, distributors and users are responsible for compliance with U.S. and local country laws. By using this product you agree to comply with applicable laws and regulations. If you are unable to comply with U.S. and local laws, return this product immediately. A summary of U.S. laws governing Cisco cryptographic products may be found at: http://www.cisco.com/wwl/export/crypto/tool/stqrg.html If you require further assistance please contact us by sending email to export@cisco.com. Cisco CISCO3945-CHASSIS (revision 1.1) with C3900-SPE150/K9 with 2027520K/69632K bytes of memory. Processor board ID FGL161010K8 2 FastEthernet interfaces 3 Gigabit Ethernet interfaces 1 Virtual Private Network (VPN) Module DRAM configuration is 72 bits wide with parity enabled. 255K bytes of non-volatile configuration memory. 2000880K bytes of ATA System CompactFlash 0 (Read/Write) License Info: License UDI: ------------------------------------------------- Device# PID SN ------------------------------------------------- *0 C3900-SPE150/K9 FOC16050QP6 Technology Package License Information for Module:'c3900' ----------------------------------------------------------------- Technology Technology-package Technology-package Current Type Next reboot ------------------------------------------------------------------ ipbase ipbasek9 Permanent ipbasek9 security securityk9 Permanent securityk9 uc None None None data datak9 Permanent datak9 Configuration register is 0x2102 '''} parsed_output = { 'version': { 'chassis': 'CISCO3945-CHASSIS', 'chassis_sn': 'FGL161010K8', 'compiled_by': 'prod_rel_team', 'compiled_date': 'Fri 05-Aug-11 00:32', 'curr_config_register': '0x2102', 'hostname': 'best-c3945-IOS3', 'image_id': 'C3900-UNIVERSALK9-M', 'image_type': 'production image', 'last_reload_reason': 'Reload Command', 'last_reload_type': 'Normal Reload', 'license_udi': { 'device_num': { '*0': { 'pid': 'C3900-SPE150/K9', 'sn': 'FOC16050QP6' } } }, 'license_package': { 'data': { 'license_level': 'datak9', 'license_type': 'Permanent', 'next_reload_license_level': 'datak9', }, 'ipbase': { 'license_level': 'ipbasek9', 'license_type': 'Permanent', 'next_reload_license_level': 'ipbasek9', }, 'security': { 'license_level': 'securityk9', 'license_type': 'Permanent', 'next_reload_license_level': 'securityk9', }, 'uc': { 'license_level': 'None', 'license_type': 'None', 'next_reload_license_level': 'None', }, }, 'main_mem': '2027520', 'mem_size': { 'non-volatile configuration': '255', }, 'number_of_intfs': { 'FastEthernet': '2', 'Gigabit Ethernet': '3', }, 'os': 'IOS', 'platform': 'C3900', 'processor_board_flash': '2000880K', 'processor_type': 'C3900-SPE150/K9', 'returned_to_rom_at': '10:26:47 EST Mon Dec 9 2019', 'returned_to_rom_by': 'reload', 'rom': 'System Bootstrap, Version 15.0(1r)M13, RELEASE SOFTWARE (fc1)', 'rtr_type': 'CISCO3945-CHASSIS', 'system_image': 'flash0:c3900-universalk9-mz.SPA.150-1.M7.bin', 'system_restarted_at': '10:27:57 EST Mon Dec 9 2019', 'uptime': '1 hour, 20 minutes', 'version': '15.0(1)M7', 'version_short': '15.0', }, } def test_empty(self): self.dev1 = Mock(**self.empty_output) version_obj = ShowVersion(device=self.dev1) with self.assertRaises(AttributeError): parsered_output = version_obj.parse() def test_semi_empty(self): self.dev1 = Mock(**self.semi_empty_output) version_obj = ShowVersion(device=self.dev1) with self.assertRaises(KeyError): parsed_output = version_obj.parse() def test_golden_iosv(self): self.maxDiff = None self.dev_iosv = Mock(**self.golden_output_iosv) version_obj = ShowVersion(device=self.dev_iosv) parsed_output = version_obj.parse() self.assertEqual(parsed_output, self.golden_parsed_output_iosv) def test_golden_ios(self): self.maxDiff = None self.dev_iosv = Mock(**self.golden_output_ios) version_obj = ShowVersion(device=self.dev_iosv) parsed_output = version_obj.parse() self.assertEqual(parsed_output, self.golden_parsed_output_ios) def test_golden_ios_cat6k(self): self.maxDiff = None self.dev_iosv = Mock(**self.golden_output_ios_cat6k) version_obj = ShowVersion(device=self.dev_iosv) parsed_output = version_obj.parse() self.assertEqual(parsed_output, self.golden_parsed_output_ios_cat6k) def test_golden_ios_1(self): self.maxDiff = None self.dev_iosv = Mock(**self.golden_output_ios_1) version_obj = ShowVersion(device=self.dev_iosv) parsed_output = version_obj.parse() self.assertEqual(parsed_output, self.golden_parsed_output_ios_1) def test_golden_ios_2(self): self.maxDiff = None self.dev_iosv = Mock(**self.device_output) version_obj = ShowVersion(device=self.dev_iosv) parsed_output = version_obj.parse() self.assertEqual(parsed_output, self.parsed_output) class test_dir(unittest.TestCase): dev1 = Device(name='empty') dev_iosv = Device(name='iosv') empty_output = {'execute.return_value': ''} semi_empty_output = {'execute.return_value': '''\ Directory of flash:/ '''} golden_parsed_output_iosv = { "dir": { "flash0:/": { "files": { "e1000_bia.txt": { "last_modified_date": "Oct 17 2018 18:57:18 +00:00", "index": "269", "size": "119", "permissions": "-rw-" }, "config": { "last_modified_date": "Oct 14 2013 00:00:00 +00:00", "index": "264", "size": "0", "permissions": "drw-" }, "nvram": { "last_modified_date": "Oct 17 2018 18:57:10 +00:00", "index": "268", "size": "524288", "permissions": "-rw-" }, "boot": { "last_modified_date": "Jan 30 2013 00:00:00 +00:00", "index": "1", "size": "0", "permissions": "drw-" }, "vios-adventerprisek9-m": { "last_modified_date": "Mar 29 2017 00:00:00 +00:00", "index": "267", "size": "147988420", "permissions": "-rw-" } }, "bytes_total": "2142715904", "bytes_free": "1989595136" }, "dir": "flash0:/" } } golden_output_iosv = {'execute.return_value': '''\ Directory of flash0:/ 1 drw- 0 Jan 30 2013 00:00:00 +00:00 boot 264 drw- 0 Oct 14 2013 00:00:00 +00:00 config 267 -rw- 147988420 Mar 29 2017 00:00:00 +00:00 vios-adventerprisek9-m 268 -rw- 524288 Oct 17 2018 18:57:10 +00:00 nvram 269 -rw- 119 Oct 17 2018 18:57:18 +00:00 e1000_bia.txt 2142715904 bytes total (1989595136 bytes free) '''} def test_empty(self): self.dev1 = Mock(**self.empty_output) dir_obj = Dir(device=self.dev1) with self.assertRaises(SchemaEmptyParserError): parsered_output = dir_obj.parse() def test_semi_empty(self): self.dev1 = Mock(**self.semi_empty_output) dir_obj = Dir(device=self.dev1) with self.assertRaises(SchemaMissingKeyError): parsed_output = dir_obj.parse() def test_golden_iosv(self): self.maxDiff = None self.dev_iosv = Mock(**self.golden_output_iosv) dir_obj = Dir(device=self.dev_iosv) parsed_output = dir_obj.parse() self.assertEqual(parsed_output, self.golden_parsed_output_iosv) class test_show_redundancy(unittest.TestCase): dev1 = Device(name='empty') dev_iosv = Device(name='iosv') empty_output = {'execute.return_value': ''} golden_parsed_output_iosv = { "red_sys_info": { "last_switchover_reason": "unsupported", "maint_mode": "Disabled", "switchovers_system_experienced": "0", "available_system_uptime": "0 minutes", "communications": "Down", "hw_mode": "Simplex", "communications_reason": "Failure", "standby_failures": "0" }, "slot": { "slot 0": { "image_ver": "Cisco IOS Software, IOSv Software (VIOS-ADVENTERPRISEK9-M), Version 15.6(3)M2, RELEASE SOFTWARE (fc2)", "uptime_in_curr_state": "1 day, 16 hours, 42 minutes", "config_register": "0x0", "curr_sw_state": "ACTIVE" } } } golden_output_iosv = {'execute.return_value': '''\ Redundant System Information : ------------------------------ Available system uptime = 0 minutes Switchovers system experienced = 0 Standby failures = 0 Last switchover reason = unsupported Hardware Mode = Simplex Maintenance Mode = Disabled Communications = Down Reason: Failure Current Processor Information : ------------------------------- Active Location = slot 0 Current Software state = ACTIVE Uptime in current state = 1 day, 16 hours, 42 minutes Image Version = Cisco IOS Software, IOSv Software (VIOS-ADVENTERPRISEK9-M), Version 15.6(3)M2, RELEASE SOFTWARE (fc2) Technical Support: http://www.cisco.com/techsupport Copyright (c) 1986-2017 by Cisco Systems, Inc. Compiled Wed 29-Mar-17 14:05 by prod_rel_team Configuration register = 0x0 Peer (slot: 0) information is not available because it is in 'DISABLED' state '''} def test_empty(self): self.dev1 = Mock(**self.empty_output) redundancy_obj = ShowRedundancy(device=self.dev1) with self.assertRaises(SchemaEmptyParserError): parsed_output = redundancy_obj.parse() def test_golden_iosv(self): self.maxDiff = None self.dev_iosv = Mock(**self.golden_output_iosv) redundancy_obj = ShowRedundancy(device=self.dev_iosv) parsed_output = redundancy_obj.parse() self.assertEqual(parsed_output, self.golden_parsed_output_iosv) class TestShowInventory(unittest.TestCase): dev1 = Device(name='empty') dev_iosv = Device(name='iosv') empty_output = {'execute.return_value': ''} golden_parsed_output_iosv = { 'main': { 'chassis': { 'IOSv': { 'descr': 'IOSv chassis, Hw Serial#: 9K66Z7TOKAACDEQA24N7S, Hw Revision: 1.0', 'name': 'IOSv', 'pid': 'IOSv', 'sn': '9K66Z7TOKAACDEQA24N7S', 'vid': '1.0', }, }, }, } golden_output_iosv = {'execute.return_value': '''\ NAME: "IOSv", DESCR: "IOSv chassis, Hw Serial#: 9K66Z7TOKAACDEQA24N7S, Hw Revision: 1.0" PID: IOSv , VID: 1.0, SN: 9K66Z7TOKAACDEQA24N7S '''} golden_parsed_output_2 = { "main": { "chassis": { "WS-C6504-E": { "name": "WS-C6504-E", "descr": "Cisco Systems Cisco 6500 4-slot Chassis System", "pid": "WS-C6504-E", "vid": "V01", "sn": "FXS1712Q1R8", } } }, "slot": { "CLK-7600 1": { "other": { "CLK-7600 1": { "name": "CLK-7600 1", "descr": "OSR-7600 Clock FRU 1", "pid": "CLK-7600", "vid": "", "sn": "FXS170802GL", } } }, "CLK-7600 2": { "other": { "CLK-7600 2": { "name": "CLK-7600 2", "descr": "OSR-7600 Clock FRU 2", "pid": "CLK-7600", "vid": "", "sn": "FXS170802GL", } } }, "FAN-MOD-4HS 1": { "other": { "FAN-MOD-4HS 1": { "name": "FAN-MOD-4HS 1", "descr": "High Speed Fan Module for CISCO7604 1", "pid": "FAN-MOD-4HS", "vid": "V01", "sn": "DCH170900PF", } } }, "PS 1 PWR-2700-AC/4": { "other": { "PS 1 PWR-2700-AC/4": { "name": "PS 1 PWR-2700-AC/4", "descr": "2700W AC power supply for CISCO7604 1", "pid": "PWR-2700-AC/4", "vid": "V03", "sn": "APS1707008Y", } } }, "PS 2 PWR-2700-AC/4": { "other": { "PS 2 PWR-2700-AC/4": { "name": "PS 2 PWR-2700-AC/4", "descr": "2700W AC power supply for CISCO7604 2", "pid": "PWR-2700-AC/4", "vid": "V03", "sn": "APS17070093", } } }, "1": { "rp": { "VS-SUP2T-10G": { "name": "1", "descr": "VS-SUP2T-10G 5 ports Supervisor Engine 2T 10GE w/ CTS Rev. 1.5", "pid": "VS-SUP2T-10G", "vid": "V05", "sn": "SAL17152N0F", "subslot": { "0": { "VS-F6K-MSFC5": { "descr": "VS-F6K-MSFC5 CPU Daughterboard Rev. 2.0", "name": "msfc sub-module of 1", "pid": "VS-F6K-MSFC5", "sn": "SAL17142D06", "vid": "", }, "VS-F6K-PFC4": { "descr": "VS-F6K-PFC4 Policy Feature Card 4 Rev. 2.0", "name": "VS-F6K-PFC4 Policy Feature Card 4 EARL sub-module of 1", "pid": "VS-F6K-PFC4", "sn": "SAL17163901", "vid": "V03", }, }, "4": { "X2-10GB-SR": { "descr": "X2 Transceiver 10Gbase-SR Te1/4", "name": "Transceiver Te1/4", "pid": "X2-10GB-SR", "sn": "ONT170202T1", "vid": "V06 ", } }, "5": { "X2-10GB-SR": { "descr": "X2 Transceiver 10Gbase-SR Te1/5", "name": "Transceiver Te1/5", "pid": "X2-10GB-SR", "sn": "ONT1702033D", "vid": "V06 ", } }, }, } } }, "2": { "lc": { "WS-X6816-10GE": { "name": "2", "descr": "WS-X6816-10GE CEF720 16 port 10GE Rev. 2.0", "pid": "WS-X6816-10GE", "vid": "V02", "sn": "SAL17152QB3", "subslot": { "0": { "WS-F6K-DFC4-E": { "descr": "WS-F6K-DFC4-E Distributed Forwarding Card 4 Rev. 1.2", "name": "WS-F6K-DFC4-E Distributed Forwarding Card 4 EARL sub-module of 2", "pid": "WS-F6K-DFC4-E", "sn": "SAL171846RF", "vid": "V02", } }, "1": { "X2-10GB-SR": { "descr": "X2 Transceiver 10Gbase-SR Te2/1", "name": "Transceiver Te2/1", "pid": "X2-10GB-SR", "sn": "ONT17020338", "vid": "V06 ", } }, "2": { "X2-10GB-SR": { "descr": "X2 Transceiver 10Gbase-SR Te2/2", "name": "Transceiver Te2/2", "pid": "X2-10GB-SR", "sn": "ONT1702020H", "vid": "V06 ", } }, "3": { "X2-10GB-SR": { "descr": "X2 Transceiver 10Gbase-SR Te2/3", "name": "Transceiver Te2/3", "pid": "X2-10GB-SR", "sn": "ONT170202UU", "vid": "V06 ", } }, "4": { "X2-10GB-SR": { "descr": "X2 Transceiver 10Gbase-SR Te2/4", "name": "Transceiver Te2/4", "pid": "X2-10GB-SR", "sn": "ONT170202T5", "vid": "V06 ", } }, "5": { "X2-10GB-SR": { "descr": "X2 Transceiver 10Gbase-SR Te2/5", "name": "Transceiver Te2/5", "pid": "X2-10GB-SR", "sn": "AGA1515XZE2", "vid": "V05 ", } }, "6": { "X2-10GB-SR": { "descr": "X2 Transceiver 10Gbase-SR Te2/6", "name": "Transceiver Te2/6", "pid": "X2-10GB-SR", "sn": "FNS153920YJ", "vid": "V06 ", } }, "16": { "X2-10GB-SR": { "descr": "X2 Transceiver 10Gbase-SR Te2/16", "name": "Transceiver Te2/16", "pid": "X2-10GB-SR", "sn": "ONT170201TT", "vid": "V06 ", } }, }, } } }, "3": { "lc": { "WS-X6824-SFP": { "name": "3", "descr": "WS-X6824-SFP CEF720 24 port 1000mb SFP Rev. 1.0", "pid": "WS-X6824-SFP", "vid": "V01", "sn": "SAL17152EG9", "subslot": { "0": { "WS-F6K-DFC4-A": { "descr": "WS-F6K-DFC4-A Distributed Forwarding Card 4 Rev. 1.0", "name": "WS-F6K-DFC4-A Distributed Forwarding Card 4 EARL sub-module of 3", "pid": "WS-F6K-DFC4-A", "sn": "SAL171848KL", "vid": "V04", } } }, } } }, "4": { "lc": { "WS-X6748-GE-TX": { "name": "4", "descr": "WS-X6748-GE-TX CEF720 48 port 10/100/1000mb Ethernet Rev. 3.4", "pid": "WS-X6748-GE-TX", "vid": "V04", "sn": "SAL14017TWF", "subslot": { "0": { "WS-F6700-CFC": { "descr": "WS-F6700-CFC Centralized Forwarding Card Rev. 4.1", "name": "WS-F6700-CFC Centralized Forwarding Card EARL sub-module of 4", "pid": "WS-F6700-CFC", "sn": "SAL13516QS8", "vid": "V06", } } }, } } }, }, } golden_output_2 = {'execute.return_value': ''' NAME: "WS-C6504-E", DESCR: "Cisco Systems Cisco 6500 4-slot Chassis System" PID: WS-C6504-E , VID: V01, SN: FXS1712Q1R8 NAME: "CLK-7600 1", DESCR: "OSR-7600 Clock FRU 1" PID: CLK-7600 , VID: , SN: FXS170802GL NAME: "CLK-7600 2", DESCR: "OSR-7600 Clock FRU 2" PID: CLK-7600 , VID: , SN: FXS170802GL NAME: "1", DESCR: "VS-SUP2T-10G 5 ports Supervisor Engine 2T 10GE w/ CTS Rev. 1.5" PID: VS-SUP2T-10G , VID: V05, SN: SAL17152N0F NAME: "msfc sub-module of 1", DESCR: "VS-F6K-MSFC5 CPU Daughterboard Rev. 2.0" PID: VS-F6K-MSFC5 , VID: , SN: SAL17142D06 NAME: "VS-F6K-PFC4 Policy Feature Card 4 EARL sub-module of 1", DESCR: "VS-F6K-PFC4 Policy Feature Card 4 Rev. 2.0" PID: VS-F6K-PFC4 , VID: V03, SN: SAL17163901 NAME: "Transceiver Te1/4", DESCR: "X2 Transceiver 10Gbase-SR Te1/4" PID: X2-10GB-SR , VID: V06 , SN: ONT170202T1 NAME: "Transceiver Te1/5", DESCR: "X2 Transceiver 10Gbase-SR Te1/5" PID: X2-10GB-SR , VID: V06 , SN: ONT1702033D NAME: "2", DESCR: "WS-X6816-10GE CEF720 16 port 10GE Rev. 2.0" PID: WS-X6816-10GE , VID: V02, SN: SAL17152QB3 NAME: "WS-F6K-DFC4-E Distributed Forwarding Card 4 EARL sub-module of 2", DESCR: "WS-F6K-DFC4-E Distributed Forwarding Card 4 Rev. 1.2" PID: WS-F6K-DFC4-E , VID: V02, SN: SAL171846RF NAME: "Transceiver Te2/1", DESCR: "X2 Transceiver 10Gbase-SR Te2/1" PID: X2-10GB-SR , VID: V06 , SN: ONT17020338 NAME: "Transceiver Te2/2", DESCR: "X2 Transceiver 10Gbase-SR Te2/2" PID: X2-10GB-SR , VID: V06 , SN: ONT1702020H NAME: "Transceiver Te2/3", DESCR: "X2 Transceiver 10Gbase-SR Te2/3" PID: X2-10GB-SR , VID: V06 , SN: ONT170202UU NAME: "Transceiver Te2/4", DESCR: "X2 Transceiver 10Gbase-SR Te2/4" PID: X2-10GB-SR , VID: V06 , SN: ONT170202T5 NAME: "Transceiver Te2/5", DESCR: "X2 Transceiver 10Gbase-SR Te2/5" PID: X2-10GB-SR , VID: V05 , SN: AGA1515XZE2 NAME: "Transceiver Te2/6", DESCR: "X2 Transceiver 10Gbase-SR Te2/6" PID: X2-10GB-SR , VID: V06 , SN: FNS153920YJ NAME: "Transceiver Te2/16", DESCR: "X2 Transceiver 10Gbase-SR Te2/16" PID: X2-10GB-SR , VID: V06 , SN: ONT170201TT NAME: "3", DESCR: "WS-X6824-SFP CEF720 24 port 1000mb SFP Rev. 1.0" PID: WS-X6824-SFP , VID: V01, SN: SAL17152EG9 NAME: "WS-F6K-DFC4-A Distributed Forwarding Card 4 EARL sub-module of 3", DESCR: "WS-F6K-DFC4-A Distributed Forwarding Card 4 Rev. 1.0" PID: WS-F6K-DFC4-A , VID: V04, SN: SAL171848KL NAME: "4", DESCR: "WS-X6748-GE-TX CEF720 48 port 10/100/1000mb Ethernet Rev. 3.4" PID: WS-X6748-GE-TX , VID: V04, SN: SAL14017TWF NAME: "WS-F6700-CFC Centralized Forwarding Card EARL sub-module of 4", DESCR: "WS-F6700-CFC Centralized Forwarding Card Rev. 4.1" PID: WS-F6700-CFC , VID: V06, SN: SAL13516QS8 NAME: "FAN-MOD-4HS 1", DESCR: "High Speed Fan Module for CISCO7604 1" PID: FAN-MOD-4HS , VID: V01, SN: DCH170900PF NAME: "PS 1 PWR-2700-AC/4", DESCR: "2700W AC power supply for CISCO7604 1" PID: PWR-2700-AC/4 , VID: V03, SN: APS1707008Y NAME: "PS 2 PWR-2700-AC/4", DESCR: "2700W AC power supply for CISCO7604 2" PID: PWR-2700-AC/4 , VID: V03, SN: APS17070093 '''} golden_parsed_output_3 = { "main": { "chassis": { "WS-C6503-E": { "name": "WS-C6503-E", "descr": "Cisco Systems Catalyst 6500 3-slot Chassis System", "pid": "WS-C6503-E", "vid": "V03", "sn": "FXS1821Q2H9", } } }, "slot": { "CLK-7600 1": { "other": { "CLK-7600 1": { "name": "CLK-7600 1", "descr": "OSR-7600 Clock FRU 1", "pid": "CLK-7600", "vid": "", "sn": "FXS181101V4", } } }, "CLK-7600 2": { "other": { "CLK-7600 2": { "name": "CLK-7600 2", "descr": "OSR-7600 Clock FRU 2", "pid": "CLK-7600", "vid": "", "sn": "FXS181101V4", } } }, "1": { "rp": { "WS-SUP720-3BXL": { "name": "1", "descr": "WS-SUP720-3BXL 2 ports Supervisor Engine 720 Rev. 5.6", "pid": "WS-SUP720-3BXL", "vid": "V05", "sn": "SAL11434P2C", "subslot": { "0": { "WS-SUP720": { "descr": "WS-SUP720 MSFC3 Daughterboard Rev. 3.1", "name": "msfc sub-module of 1", "pid": "WS-SUP720", "sn": "SAL11434N9G", "vid": "", }, "WS-F6K-PFC3BXL": { "descr": "WS-F6K-PFC3BXL Policy Feature Card 3 Rev. 1.8", "name": "switching engine sub-module of 1", "pid": "WS-F6K-PFC3BXL", "sn": "SAL11434LYG", "vid": "V01", }, } }, } } }, "2": { "lc": { "WS-X6748-GE-TX": { "name": "2", "descr": "WS-X6748-GE-TX CEF720 48 port 10/100/1000mb Ethernet Rev. 2.6", "pid": "WS-X6748-GE-TX", "vid": "V02", "sn": "SAL1128UPQ9", "subslot": { "0": { "WS-F6700-DFC3CXL": { "descr": "WS-F6700-DFC3CXL Distributed Forwarding Card 3 Rev. 1.1", "name": "switching engine sub-module of 2", "pid": "WS-F6700-DFC3CXL", "sn": "SAL1214LAG5", "vid": "V01", } } }, } } }, "WS-C6503-E-FAN 1": { "other": { "WS-C6503-E-FAN 1": { "name": "WS-C6503-E-FAN 1", "descr": "Enhanced 3-slot Fan Tray 1", "pid": "WS-C6503-E-FAN", "vid": "V02", "sn": "DCH183500KW", } } }, "PS 1 PWR-1400-AC": { "other": { "PS 1 PWR-1400-AC": { "name": "PS 1 PWR-1400-AC", "descr": "AC power supply, 1400 watt 1", "pid": "PWR-1400-AC", "vid": "V01", "sn": "ABC0830J127", } } }, }, } golden_output_3 = {'execute.return_value': ''' # show inventory NAME: "WS-C6503-E", DESCR: "Cisco Systems Catalyst 6500 3-slot Chassis System" PID: WS-C6503-E , VID: V03, SN: FXS1821Q2H9 NAME: "CLK-7600 1", DESCR: "OSR-7600 Clock FRU 1" PID: CLK-7600 , VID: , SN: FXS181101V4 NAME: "CLK-7600 2", DESCR: "OSR-7600 Clock FRU 2" PID: CLK-7600 , VID: , SN: FXS181101V4 NAME: "1", DESCR: "WS-SUP720-3BXL 2 ports Supervisor Engine 720 Rev. 5.6" PID: WS-SUP720-3BXL , VID: V05, SN: SAL11434P2C NAME: "msfc sub-module of 1", DESCR: "WS-SUP720 MSFC3 Daughterboard Rev. 3.1" PID: WS-SUP720 , VID: , SN: SAL11434N9G NAME: "switching engine sub-module of 1", DESCR: "WS-F6K-PFC3BXL Policy Feature Card 3 Rev. 1.8" PID: WS-F6K-PFC3BXL , VID: V01, SN: SAL11434LYG NAME: "2", DESCR: "WS-X6748-GE-TX CEF720 48 port 10/100/1000mb Ethernet Rev. 2.6" PID: WS-X6748-GE-TX , VID: V02, SN: SAL1128UPQ9 NAME: "switching engine sub-module of 2", DESCR: "WS-F6700-DFC3CXL Distributed Forwarding Card 3 Rev. 1.1" PID: WS-F6700-DFC3CXL , VID: V01, SN: SAL1214LAG5 NAME: "WS-C6503-E-FAN 1", DESCR: "Enhanced 3-slot Fan Tray 1" PID: WS-C6503-E-FAN , VID: V02, SN: DCH183500KW NAME: "PS 1 PWR-1400-AC", DESCR: "AC power supply, 1400 watt 1" PID: PWR-1400-AC , VID: V01, SN: ABC0830J127 '''} golden_output_4 = {'execute.return_value': ''' NAME: "1", DESCR: "WS-C8888X-88" PID: WS-C0123X-45T-S , VID: V00 , SN: FDO123R12W NAME: "Switch 1 - Power Supply 1", DESCR: "ABC Power Supply" PID: C3KX-PWR-350WAC , VID: V01D , SN: DTN1504L0E9 NAME: "TenGigabitEthernet1/1/1", DESCR: "SFP-10GBase-SR" PID: SFP-10G-SR , VID: V03 , SN: SPC1519005V NAME: "2", DESCR: "WS-C3210X-48" PID: WS-C3210X-48T-S , VID: V02 , SN: FD5678Z90P NAME: "Switch 2 - Power Supply 1", DESCR: "BCA Power Supply" PID: C3KX-PWR-007CBA , VID: V01L , SN: LTP13579L3R NAME: "TenGigabitEthernet2/1/1", DESCR: "SFP-10GBase-LR" PID: SFP-10G-LR , VID: V02 , SN: ONT182746GZ NAME: "1", DESCR: "WS-C1010XR-48FPS-I" PID: WS-C1010XR-48FPS-I, VID: V05 , SN: FD2043B0K3 NAME: "Switch 1 - Power Supply 1", DESCR: "LLL Power Supply" PID: PWR-C2-2929WAC , VID: V02L , SN: LIT03728KKK NAME: "Switch 1 - FlexStackPlus Module", DESCR: "Stacking Module" PID: C1010X-STACK , VID: V02 , SN: FD232323XXZ NAME: "GigabitEthernet1/0/49", DESCR: "1000BaseSX SFP" PID: GLC-SX-MMD , VID: V01 , SN: ACW102938VS '''} golden_parsed_output_4 = { 'slot': { '1': { 'rp': { 'WS-C0123X-45T-S': { 'descr': 'WS-C8888X-88', 'name': '1', 'pid': 'WS-C0123X-45T-S', 'sn': 'FDO123R12W', 'subslot': { '1': { 'C3KX-PWR-350WAC': { 'descr': 'ABC Power Supply', 'name': 'Switch 1 - Power Supply 1', 'pid': 'C3KX-PWR-350WAC', 'sn': 'DTN1504L0E9', 'vid': 'V01D ', }, }, '1/1/1': { 'SFP-10G-SR': { 'descr': 'SFP-10GBase-SR', 'name': 'TenGigabitEthernet1/1/1', 'pid': 'SFP-10G-SR', 'sn': 'SPC1519005V', 'vid': 'V03 ', }, }, }, 'vid': 'V00 ', }, 'WS-C1010XR-48FPS-I': { 'descr': 'WS-C1010XR-48FPS-I', 'name': '1', 'pid': 'WS-C1010XR-48FPS-I', 'sn': 'FD2043B0K3', 'subslot': { '1': { 'C1010X-STACK': { 'descr': 'Stacking Module', 'name': 'Switch 1 - FlexStackPlus Module', 'pid': 'C1010X-STACK', 'sn': 'FD232323XXZ', 'vid': 'V02 ', }, 'PWR-C2-2929WAC': { 'descr': 'LLL Power Supply', 'name': 'Switch 1 - Power Supply 1', 'pid': 'PWR-C2-2929WAC', 'sn': 'LIT03728KKK', 'vid': 'V02L ', }, }, '1/0/49': { 'GLC-SX-MMD': { 'descr': '1000BaseSX SFP', 'name': 'GigabitEthernet1/0/49', 'pid': 'GLC-SX-MMD', 'sn': 'ACW102938VS', 'vid': 'V01 ', }, }, }, 'vid': 'V05 ', }, }, }, '2': { 'rp': { 'WS-C3210X-48T-S': { 'descr': 'WS-C3210X-48', 'name': '2', 'pid': 'WS-C3210X-48T-S', 'sn': 'FD5678Z90P', 'subslot': { '2': { 'C3KX-PWR-007CBA': { 'descr': 'BCA Power Supply', 'name': 'Switch 2 - Power Supply 1', 'pid': 'C3KX-PWR-007CBA', 'sn': 'LTP13579L3R', 'vid': 'V01L ', }, }, '2/1/1': { 'SFP-10G-LR': { 'descr': 'SFP-10GBase-LR', 'name': 'TenGigabitEthernet2/1/1', 'pid': 'SFP-10G-LR', 'sn': 'ONT182746GZ', 'vid': 'V02 ', }, }, }, 'vid': 'V02 ', }, }, }, }, } golden_output_5 = {'execute.return_value': ''' best-c3945-IOS3#show inventory NAME: "CISCO3945-CHASSIS", DESCR: "CISCO3945-CHASSIS" PID: CISCO3945-CHASSIS , VID: V05 , SN: FGL161010K8 NAME: "Cisco Services Performance Engine 150 for Cisco 3900 ISR on Slot 0", DESCR: "Cisco Services Performance Engine 150 for Cisco 3900 ISR" PID: C3900-SPE150/K9 , VID: V05 , SN: FOC16050QP6 NAME: "Two-Port Fast Ethernet High Speed WAN Interface Card on Slot 0 SubSlot 3", DESCR: "Two-Port Fast Ethernet High Speed WAN Interface Card" PID: HWIC-2FE , VID: V02 , SN: FOC16062824 NAME: "C3900 AC Power Supply 1", DESCR: "C3900 AC Power Supply 1" PID: PWR-3900-AC , VID: V03 , SN: QCS1604P0BT '''} golden_parsed_output_5 = { 'main': { 'chassis': { 'CISCO3945-CHASSIS': { 'descr': 'CISCO3945-CHASSIS', 'name': 'CISCO3945-CHASSIS', 'pid': 'CISCO3945-CHASSIS', 'sn': 'FGL161010K8', 'vid': 'V05 ', }, }, }, 'slot': { '0': { 'rp': { 'C3900-SPE150/K9': { 'descr': 'Cisco Services Performance Engine 150 for Cisco 3900 ISR', 'name': 'Cisco Services Performance Engine 150 for Cisco 3900 ISR on Slot 0', 'pid': 'C3900-SPE150/K9', 'sn': 'FOC16050QP6', 'subslot': { '3': { 'HWIC-2FE': { 'descr': 'Two-Port Fast Ethernet High Speed WAN Interface Card', 'name': 'Two-Port Fast Ethernet High Speed WAN Interface Card on Slot 0 SubSlot 3', 'pid': 'HWIC-2FE', 'sn': 'FOC16062824', 'vid': 'V02 ', }, }, }, 'vid': 'V05 ', }, }, }, 'C3900 AC Power Supply 1': { 'other': { 'C3900 AC Power Supply 1': { 'descr': 'C3900 AC Power Supply 1', 'name': 'C3900 AC Power Supply 1', 'pid': 'PWR-3900-AC', 'sn': 'QCS1604P0BT', 'vid': 'V03 ', }, }, }, }, } golden_output_6 = {'execute.return_value': ''' NAME: "1", DESCR: "SM-ES2-16-P" PID: SM-ES2-16-P , VID: , SN: FOC09876NP3 '''} golden_parsed_output_6 = { 'slot': { '1': { 'lc': { 'SM-ES2-16-P': { 'descr': 'SM-ES2-16-P', 'name': '1', 'pid': 'SM-ES2-16-P', 'sn': 'FOC09876NP3', 'vid': '', }, }, }, }, } golden_output_7 = {'execute.return_value': ''' NAME: "2821 chassis", DESCR: "2821 chassis" PID: CISCO2821 , VID: V07 , SN: FTX1234AMWT NAME: "VWIC2-2MFT-T1/E1 - 2-Port RJ-48 Multiflex Trunk - T1/E1 on Slot 0 SubSlot 0", DESCR: "VWIC2-2MFT-T1/E1 - 2-Port RJ-48 Multiflex Trunk - T1/E1" PID: VWIC2-2MFT-T1/E1 , VID: V01 , SN: FOC98675U0D NAME: "VWIC2-2MFT-T1/E1 - 2-Port RJ-48 Multiflex Trunk - T1/E1 on Slot 0 SubSlot 1", DESCR: "VWIC2-2MFT-T1/E1 - 2-Port RJ-48 Multiflex Trunk - T1/E1" PID: VWIC2-2MFT-T1/E1 , VID: V01 , SN: FOC98675W3E NAME: "Virtual Private Network (VPN) Module on Slot 0", DESCR: "Encryption AIM Element" PID: AIM-VPN/SSL-2 , VID: V01, SN: FOC2837465E '''} golden_parsed_output_7 = { 'main': { 'chassis': { 'CISCO2821': { 'descr': '2821 chassis', 'name': '2821 chassis', 'pid': 'CISCO2821', 'sn': 'FTX1234AMWT', 'vid': 'V07 ', }, }, }, 'slot': { '0': { 'other': { 'AIM-VPN/SSL-2': { 'descr': 'Encryption AIM Element', 'name': 'Virtual Private Network (VPN) Module on Slot 0', 'pid': 'AIM-VPN/SSL-2', 'sn': 'FOC2837465E', 'vid': 'V01', 'subslot': { '0': { 'VWIC2-2MFT-T1/E1': { 'descr': 'VWIC2-2MFT-T1/E1 - 2-Port RJ-48 Multiflex Trunk - T1/E1', 'name': 'VWIC2-2MFT-T1/E1 - 2-Port RJ-48 Multiflex Trunk - T1/E1 on Slot 0 SubSlot 0', 'pid': 'VWIC2-2MFT-T1/E1', 'sn': 'FOC98675U0D', 'vid': 'V01 ', }, }, '1': { 'VWIC2-2MFT-T1/E1': { 'descr': 'VWIC2-2MFT-T1/E1 - 2-Port RJ-48 Multiflex Trunk - T1/E1', 'name': 'VWIC2-2MFT-T1/E1 - 2-Port RJ-48 Multiflex Trunk - T1/E1 on Slot 0 SubSlot 1', 'pid': 'VWIC2-2MFT-T1/E1', 'sn': 'FOC98675W3E', 'vid': 'V01 ', }, }, }, }, }, }, }, } golden_output_8 = {'execute.return_value': ''' NAME: "3825 chassis", DESCR: "3825 chassis" PID: CISCO3825 , VID: V05 , SN: FTX7908A3RQ NAME: "VWIC2-2MFT-T1/E1 - 2-Port RJ-48 Multiflex Trunk - T1/E1 on Slot 0 SubSlot 0", DESCR: "VWIC2-2MFT-T1/E1 - 2-Port RJ-48 Multiflex Trunk - T1/E1" PID: VWIC2-2MFT-T1/E1 , VID: V01 , SN: FOC65428K9F NAME: "Wan Interface Card BRI U (2091, 3086) on Slot 0 SubSlot 1", DESCR: "Wan Interface Card BRI U (2091, 3086)" PID: WIC-1B-U-V2 , VID: V01, SN: 10293847 NAME: "PVDMII DSP SIMM with four DSPs on Slot 0 SubSlot 4", DESCR: "PVDMII DSP SIMM with four DSPs" PID: PVDM2-64 , VID: V01 , SN: FOC63358WSI NAME: "High Density Voice Module - 8FXS/DID on Slot 1", DESCR: "High Density Voice Module - 8FXS/DID" PID: EVM-HD-8FXS/DID , VID: V04 , SN: FOC65798TG8 NAME: "Six port FXO voice interface daughtercard on Slot 1 SubSlot 1", DESCR: "Six port FXO voice interface daughtercard" PID: EM-HDA-6FXO , VID: V03 , SN: FOC85389QXB '''} golden_parsed_output_8 = { 'main': { 'chassis': { 'CISCO3825': { 'descr': '3825 chassis', 'name': '3825 chassis', 'pid': 'CISCO3825', 'sn': 'FTX7908A3RQ', 'vid': 'V05 ', }, }, }, 'slot': { '0': { 'rp': { 'CISCO3825': { 'subslot': { '0': { 'VWIC2-2MFT-T1/E1': { 'descr': 'VWIC2-2MFT-T1/E1 - 2-Port RJ-48 Multiflex Trunk - T1/E1', 'name': 'VWIC2-2MFT-T1/E1 - 2-Port RJ-48 Multiflex Trunk - T1/E1 on Slot 0 SubSlot 0', 'pid': 'VWIC2-2MFT-T1/E1', 'sn': 'FOC65428K9F', 'vid': 'V01 ', }, }, '1': { 'WIC-1B-U-V2': { 'descr': 'Wan Interface Card BRI U (2091, 3086)', 'name': 'Wan Interface Card BRI U (2091, 3086) on Slot 0 SubSlot 1', 'pid': 'WIC-1B-U-V2', 'sn': '10293847', 'vid': 'V01', }, }, '4': { 'PVDM2-64': { 'descr': 'PVDMII DSP SIMM with four DSPs', 'name': 'PVDMII DSP SIMM with four DSPs on Slot 0 SubSlot 4', 'pid': 'PVDM2-64', 'sn': 'FOC63358WSI', 'vid': 'V01 ', }, }, }, }, }, }, '1': { 'other': { 'EVM-HD-8FXS/DID': { 'descr': 'High Density Voice Module - 8FXS/DID', 'name': 'High Density Voice Module - 8FXS/DID on Slot 1', 'pid': 'EVM-HD-8FXS/DID', 'sn': 'FOC65798TG8', 'subslot': { '1': { 'EM-HDA-6FXO': { 'descr': 'Six port FXO voice interface daughtercard', 'name': 'Six port FXO voice interface daughtercard on Slot 1 SubSlot 1', 'pid': 'EM-HDA-6FXO', 'sn': 'FOC85389QXB', 'vid': 'V03 ', }, }, }, 'vid': 'V04 ', }, }, }, }, } golden_output_9 = {'execute.return_value': ''' NAME: "3845 chassis", DESCR: "3845 chassis" PID: CISCO3845 , VID: V05 , SN: FTX6666ARJ9 NAME: "c3845 Motherboard with Gigabit Ethernet on Slot 0", DESCR: "c3845 Motherboard with Gigabit Ethernet" PID: CISCO3845-MB , VID: V09 , SN: FOC729346GQ NAME: "Virtual Private Network (VPN) Module on Slot 0", DESCR: "Encryption AIM Element" PID: AIM-VPN/SSL-3 , VID: V01, SN: FOC758693YO NAME: "Clear/Subrate T3/E3 WAN on Slot 1", DESCR: "Clear/Subrate T3/E3 WAN" PID: NM-1T3/E3= , VID: V01 , SN: FOC28476ADM NAME: "16 Port 10BaseT/100BaseTX EtherSwitch on Slot 2", DESCR: "16 Port 10BaseT/100BaseTX EtherSwitch" PID: NM-16ESW , VID: V01 , SN: FOC135464KO NAME: "Gigabit(1000BaseT) module for EtherSwitch NM on Slot 2 SubSlot 0", DESCR: "Gigabit(1000BaseT) module for EtherSwitch NM" PID: GE-DCARD-ESW , VID: V01 , SN: FOC91864MNN '''} golden_parsed_output_9 = { 'main': { 'chassis': { 'CISCO3845': { 'descr': '3845 chassis', 'name': '3845 chassis', 'pid': 'CISCO3845', 'sn': 'FTX6666ARJ9', 'vid': 'V05 ', }, }, }, 'slot': { '0': { 'lc': { 'CISCO3845-MB': { 'descr': 'c3845 Motherboard with Gigabit Ethernet', 'name': 'c3845 Motherboard with Gigabit Ethernet on Slot 0', 'pid': 'CISCO3845-MB', 'sn': 'FOC729346GQ', 'vid': 'V09 ', }, }, 'other': { 'AIM-VPN/SSL-3': { 'descr': 'Encryption AIM Element', 'name': 'Virtual Private Network (VPN) Module on Slot 0', 'pid': 'AIM-VPN/SSL-3', 'sn': 'FOC758693YO', 'vid': 'V01', }, }, }, '1': { 'lc': { 'NM-1T3/E3=': { 'descr': 'Clear/Subrate T3/E3 WAN', 'name': 'Clear/Subrate T3/E3 WAN on Slot 1', 'pid': 'NM-1T3/E3=', 'sn': 'FOC28476ADM', 'vid': 'V01 ', }, }, }, '16': { 'lc': { 'NM-16ESW': { 'descr': '16 Port 10BaseT/100BaseTX EtherSwitch', 'name': '16 Port 10BaseT/100BaseTX EtherSwitch on Slot 2', 'pid': 'NM-16ESW', 'sn': 'FOC135464KO', 'subslot': { '0': { 'GE-DCARD-ESW': { 'descr': 'Gigabit(1000BaseT) module for EtherSwitch NM', 'name': 'Gigabit(1000BaseT) module for EtherSwitch NM on Slot 2 SubSlot 0', 'pid': 'GE-DCARD-ESW', 'sn': 'FOC91864MNN', 'vid': 'V01 ', }, }, }, 'vid': 'V01 ', }, }, }, }, } def test_empty(self): self.dev1 = Mock(**self.empty_output) inventory_obj = ShowInventory(device=self.dev1) with self.assertRaises(SchemaEmptyParserError): parsed_output = inventory_obj.parse() def test_golden_iosv(self): self.maxDiff = None self.dev_iosv = Mock(**self.golden_output_iosv) inventory_obj = ShowInventory(device=self.dev_iosv) parsed_output = inventory_obj.parse() self.assertEqual(parsed_output, self.golden_parsed_output_iosv) def test_golden_output_2(self): self.maxDiff = None self.device = Mock(**self.golden_output_2) obj = ShowInventory(device=self.device) parsed_output = obj.parse() self.assertEqual(parsed_output, self.golden_parsed_output_2) def test_golden_output_3(self): self.maxDiff = None self.device = Mock(**self.golden_output_3) obj = ShowInventory(device=self.device) parsed_output = obj.parse() self.assertEqual(parsed_output, self.golden_parsed_output_3) def test_golden_output_4(self): self.maxDiff = None self.device = Mock(**self.golden_output_4) obj = ShowInventory(device=self.device) parsed_output = obj.parse() self.assertEqual(parsed_output, self.golden_parsed_output_4) def test_golden_output_5(self): self.maxDiff = None self.device = Mock(**self.golden_output_5) obj = ShowInventory(device=self.device) parsed_output = obj.parse() self.assertEqual(parsed_output, self.golden_parsed_output_5) def test_golden_output_6(self): self.maxDiff = None self.device = Mock(**self.golden_output_6) obj = ShowInventory(device=self.device) parsed_output = obj.parse() self.assertEqual(parsed_output, self.golden_parsed_output_6) def test_golden_output_7(self): self.maxDiff = None self.device = Mock(**self.golden_output_7) obj = ShowInventory(device=self.device) parsed_output = obj.parse() self.assertEqual(parsed_output, self.golden_parsed_output_7) def test_golden_output_8(self): self.maxDiff = None self.device = Mock(**self.golden_output_8) obj = ShowInventory(device=self.device) parsed_output = obj.parse() self.assertEqual(parsed_output, self.golden_parsed_output_8) def test_golden_output_9(self): self.maxDiff = None self.device = Mock(**self.golden_output_9) obj = ShowInventory(device=self.device) parsed_output = obj.parse() self.assertEqual(parsed_output, self.golden_parsed_output_9) class test_show_bootvar(unittest.TestCase): dev = Device(name='ios') dev_iosv = Device(name='iosv') empty_output = {'execute.return_value': ''} golden_parsed_output_iosv = { "active": { "boot_variable": "disk0:s72033-adventerprisek9-mz.122-33.SRE0a-ssr-nxos-76k-1,12", "configuration_register": "0x2012" }, "next_reload_boot_variable": "disk0:s72033-adventerprisek9-mz.122-33.SRE0a-ssr-nxos-76k-1,12" } golden_output_iosv = {'execute.return_value': '''\ BOOT variable = disk0:s72033-adventerprisek9-mz.122-33.SRE0a-ssr-nxos-76k-1,12; CONFIG_FILE variable = BOOTLDR variable = Configuration register is 0x2012 Standby not ready to show bootvar '''} def test_empty(self): self.dev = Mock(**self.empty_output) platform_obj = ShowBootvar(device=self.dev) with self.assertRaises(SchemaEmptyParserError): parsed_output = platform_obj.parse() def test_golden(self): self.maxDiff = None self.dev_iosv = Mock(**self.golden_output_iosv) platform_obj = ShowBootvar(device=self.dev_iosv) parsed_output = platform_obj.parse() self.assertEqual(parsed_output, self.golden_parsed_output_iosv) class test_show_processes_cpu_sorted_CPU(unittest.TestCase): dev = Device(name='c3850') empty_output = {'execute.return_value': ''} golden_parsed_output = { "five_sec_cpu_total": 13, "five_min_cpu": 15, "one_min_cpu": 23, "five_sec_cpu_interrupts": 0 } golden_output = {'execute.return_value': '''\ show processes cpu sorted 5min | inc CPU CPU utilization for five seconds: 13%/0%; one minute: 23%; five minutes: 15% '''} golden_parsed_output_1 = { "sort": { 1: { "invoked": 3321960, "usecs": 109, "tty": 0, "one_min_cpu": 0.54, "process": "PIM Process", "five_min_cpu": 0.48, "runtime": 362874, "pid": 368, "five_sec_cpu": 1.03 }, 2: { "invoked": 1466728, "usecs": 2442, "tty": 0, "one_min_cpu": 0.87, "process": "IOSv e1000", "five_min_cpu": 2.77, "runtime": 3582279, "pid": 84, "five_sec_cpu": 0.55 }, 3: { "invoked": 116196, "usecs": 976, "tty": 0, "one_min_cpu": 0.07, "process": "OSPF-1 Hello", "five_min_cpu": 0.07, "runtime": 113457, "pid": 412, "five_sec_cpu": 0.15 } }, "five_sec_cpu_total": 4, "five_min_cpu": 9, "one_min_cpu": 4, "nonzero_cpu_processes": [ "PIM Process", "IOSv e1000", "OSPF-1 Hello" ], "five_sec_cpu_interrupts": 0 } golden_output_1 = {'execute.return_value': ''' CPU utilization for five seconds: 4%/0%; one minute: 4%; five minutes: 9% PID Runtime(ms) Invoked uSecs 5Sec 1Min 5Min TTY Process 368 362874 3321960 109 1.03% 0.54% 0.48% 0 PIM Process 84 3582279 1466728 2442 0.55% 0.87% 2.77% 0 IOSv e1000 412 113457 116196 976 0.15% 0.07% 0.07% 0 OSPF-1 Hello '''} def test_empty(self): self.dev = Mock(**self.empty_output) obj = ShowProcessesCpuSorted(device=self.dev) with self.assertRaises(SchemaEmptyParserError): parsered_output = obj.parse() def test_golden(self): self.maxDiff = None self.dev = Mock(**self.golden_output) obj = ShowProcessesCpuSorted(device=self.dev) parsed_output = obj.parse(key_word='CPU', sort_time='5min') self.assertEqual(parsed_output, self.golden_parsed_output) def test_golden_1(self): self.maxDiff = None self.dev = Mock(**self.golden_output_1) obj = ShowProcessesCpuSorted(device=self.dev) parsed_output = obj.parse() self.assertEqual(parsed_output, self.golden_parsed_output_1) class test_show_processes_cpu(test_show_processes_cpu_iosxe): def test_golden(self): self.device = Mock(**self.golden_output) obj = ShowProcessesCpu(device=self.device) parsed_output = obj.parse() self.maxDiff = None self.assertEqual(parsed_output, self.golden_parsed_output) def test_golden_1(self): self.maxDiff = None self.device = Mock(**self.golden_output_1) obj = ShowProcessesCpu(device=self.device) parsed_output = obj.parse(key_word='process') self.assertEqual(parsed_output, self.golden_parsed_output_1) def test_empty(self): self.device1 = Mock(**self.empty_output) obj = ShowProcessesCpu(device=self.device1) with self.assertRaises(SchemaEmptyParserError): parsed_output = obj.parse() class test_show_version_rp(test_show_version_rp_iosxe): def test_golden_active(self): self.device = Mock(**self.golden_output_active) obj = ShowVersionRp(device=self.device) parsed_output = obj.parse(rp='active', status='running') self.maxDiff = None self.assertEqual(parsed_output, self.golden_parsed_output_active) def test_golden_standby(self): self.device = Mock(**self.golden_output_standby) obj = ShowVersionRp(device=self.device) parsed_output = obj.parse(rp='standby', status='running') self.maxDiff = None self.assertEqual(parsed_output, self.golden_parsed_output_standby) def test_golden_standby_offline(self): self.device = Mock(**self.golden_output_standby_offline) obj = ShowVersionRp(device=self.device) self.maxDiff = None with self.assertRaises(SchemaEmptyParserError): parsed_output = obj.parse(rp='standby', status='running') def test_empty(self): self.device1 = Mock(**self.empty_output) obj = ShowVersionRp(device=self.device1) with self.assertRaises(SchemaEmptyParserError): parsed_output = obj.parse() class test_show_platform(test_show_platform_iosxe): def test_empty(self): self.dev1 = Mock(**self.empty_output) platform_obj = ShowPlatform(device=self.dev1) with self.assertRaises(SchemaEmptyParserError): parsed_output = platform_obj.parse() def test_semi_empty(self): self.dev2 = Mock(**self.semi_empty_output) platform_obj = ShowPlatform(device=self.dev2) with self.assertRaises(SchemaEmptyParserError): parsed_output = platform_obj.parse() def test_golden_c3850(self): self.maxDiff = None self.dev_c3850 = Mock(**self.golden_output_c3850) platform_obj = ShowPlatform(device=self.dev_c3850) parsed_output = platform_obj.parse() self.assertEqual(parsed_output, self.golden_parsed_output_c3850) def test_golden_asr1k(self): self.maxDiff = None self.dev_asr1k = Mock(**self.golden_output_asr1k) platform_obj = ShowPlatform(device=self.dev_asr1k) parsed_output = platform_obj.parse() self.assertEqual(parsed_output, self.golden_parsed_output_asr1k) class test_show_platform_power(test_show_platform_power_iosxe): def test_empty(self): self.device = Mock(**self.empty_output) platform_obj = ShowPlatformPower(device=self.device) with self.assertRaises(SchemaEmptyParserError): parsed_output = platform_obj.parse() def test_golden(self): self.maxDiff = None self.device = Mock(**self.golden_output) platform_obj = ShowPlatformPower(device=self.device) parsed_output = platform_obj.parse() self.assertEqual(parsed_output, self.golden_parsed_output) class test_show_processes_cpu_history(test_show_processes_cpu_history_iosxe): def test_empty(self): self.device = Mock(**self.empty_output) platform_obj = ShowProcessesCpuHistory(device=self.device) with self.assertRaises(SchemaEmptyParserError): parsed_output = platform_obj.parse() def test_golden(self): self.maxDiff = None self.device = Mock(**self.golden_output) platform_obj = ShowProcessesCpuHistory(device=self.device) parsed_output = platform_obj.parse() self.assertEqual(parsed_output, self.golden_parsed_output) class test_show_processes_cpu_platform(test_show_processes_cpu_platform_iosxe): def test_golden(self): self.device = Mock(**self.golden_output) cpu_platform_obj = ShowProcessesCpuPlatform(device=self.device) parsed_output = cpu_platform_obj.parse() self.maxDiff = None self.assertEqual(parsed_output, self.golden_parsed_output) def test_empty(self): self.device1 = Mock(**self.empty_output) cpu_platform_obj = ShowProcessesCpuPlatform(device=self.device1) with self.assertRaises(SchemaEmptyParserError): parsed_output = cpu_platform_obj.parse() class test_show_platform_software_status_control_processor_brief(test_show_platform_software_status_control_processor_brief_iosxe): def test_empty(self): self.dev = Mock(**self.empty_output) obj = ShowPlatformSoftwareStatusControl(device=self.dev) with self.assertRaises(SchemaEmptyParserError): parsered_output = obj.parse() def test_golden(self): self.maxDiff = None self.dev = Mock(**self.golden_output) obj = ShowPlatformSoftwareStatusControl(device=self.dev) parsed_output = obj.parse() self.assertEqual(parsed_output, self.golden_parsed_output) class test_show_platform_software_slot_active_monitor_Mem(test_show_platform_software_slot_active_monitor_Mem_iosxe): def test_empty(self): self.dev = Mock(**self.empty_output) obj = ShowPlatformSoftwareSlotActiveMonitorMem(device=self.dev) with self.assertRaises(SchemaEmptyParserError): parsered_output = obj.parse() def test_golden(self): self.maxDiff = None self.dev = Mock(**self.golden_output) obj = ShowPlatformSoftwareSlotActiveMonitorMem(device=self.dev) parsed_output = obj.parse() self.assertEqual(parsed_output, self.golden_parsed_output) class test_show_platform_hardware(test_show_platform_hardware_iosxe): def test_golden_active(self): self.device = Mock(**self.golden_output_active) obj = ShowPlatformHardware(device=self.device) parsed_output = obj.parse() self.maxDiff = None self.assertEqual(parsed_output, self.golden_parsed_output_active) def test_empty(self): self.device1 = Mock(**self.empty_output) obj = ShowPlatformHardware(device=self.device1) with self.assertRaises(SchemaEmptyParserError): parsed_output = obj.parse() class test_show_platform_hardware_plim(test_show_platform_hardware_plim_iosxe): def test_golden_port(self): self.device = Mock(**self.golden_output_port) obj = ShowPlatformHardwarePlim(device=self.device) parsed_output = obj.parse(port='0/0/0') self.maxDiff = None self.assertEqual(parsed_output, self.golden_parsed_output_port) def test_golden_slot(self): self.device = Mock(**self.golden_output_slot) obj = ShowPlatformHardwarePlim(device=self.device) parsed_output = obj.parse(slot='0') self.maxDiff = None self.assertEqual(parsed_output, self.golden_parsed_output_slot) def test_golden_subslot(self): self.device = Mock(**self.golden_output_subslot) obj = ShowPlatformHardwarePlim(device=self.device) parsed_output = obj.parse(subslot='0/1') self.maxDiff = None self.assertEqual(parsed_output, self.golden_parsed_output_subslot) def test_golden_slot_internal(self): self.device = Mock(**self.golden_output_slot_internal) obj = ShowPlatformHardwarePlim(device=self.device) parsed_output = obj.parse(slot='0', internal=True) self.maxDiff = None self.assertEqual( parsed_output, self.golden_parsed_output_slot_internal) def test_empty(self): self.device1 = Mock(**self.empty_output) obj = ShowPlatformHardwarePlim(device=self.device1) with self.assertRaises(SchemaEmptyParserError): parsed_output = obj.parse(port='0/0/0') class test_show_platform_hardware_qfp_bqs_opm_mapping(test_show_platform_hardware_qfp_bqs_opm_mapping_iosxe): def test_golden_active_opm(self): self.device = Mock(**self.golden_output_active_opm) obj = ShowPlatformHardwareQfpBqsOpmMapping(device=self.device) parsed_output = obj.parse(status='active', slot='0') self.maxDiff = None self.assertEqual(parsed_output, self.golden_parsed_output_active_opm) def test_empty(self): self.device1 = Mock(**self.empty_output) obj = ShowPlatformHardwareQfpBqsOpmMapping(device=self.device1) with self.assertRaises(SchemaEmptyParserError): parsed_output = obj.parse(status='active', slot='0') class test_show_platform_hardware_qfp_bqs_ipm_mapping(test_show_platform_hardware_qfp_bqs_ipm_mapping_iosxe): def test_golden_active_ipm(self): self.device = Mock(**self.golden_output_active_ipm) obj = ShowPlatformHardwareQfpBqsIpmMapping(device=self.device) parsed_output = obj.parse(status='active', slot='0') self.maxDiff = None self.assertEqual(parsed_output, self.golden_parsed_output_active_ipm) def test_empty(self): self.device1 = Mock(**self.empty_output) obj = ShowPlatformHardwareQfpBqsIpmMapping(device=self.device1) with self.assertRaises(SchemaEmptyParserError): parsed_output = obj.parse(status='active', slot='0') class test_show_platform_hardware_serdes_statistics(test_show_platform_hardware_serdes_statistics_iosxe): def test_golden_serdes(self): self.device = Mock(**self.golden_output_serdes) obj = ShowPlatformHardwareSerdes(device=self.device) parsed_output = obj.parse(slot='0') self.maxDiff = None self.assertEqual(parsed_output, self.golden_parsed_output_serdes) def test_empty(self): self.device1 = Mock(**self.empty_output) obj = ShowPlatformHardwareSerdes(device=self.device1) with self.assertRaises(SchemaEmptyParserError): parsed_output = obj.parse(slot='0') class test_show_platform_hardware_serdes_statistics_internal(test_show_platform_hardware_serdes_statistics_internal_iosxe): def test_golden(self): self.device = Mock(**self.golden_output_serdes_internal) obj = ShowPlatformHardwareSerdesInternal(device=self.device) parsed_output = obj.parse(slot='0') self.maxDiff = None self.assertEqual( parsed_output, self.golden_parsed_output_serdes_internal) def test_empty(self): self.device1 = Mock(**self.empty_output) obj = ShowPlatformHardwareSerdesInternal(device=self.device1) with self.assertRaises(SchemaEmptyParserError): parsed_output = obj.parse(slot='0') class show_platform_hardware_qfp_bqs_statistics_channel_all(show_platform_hardware_qfp_bqs_statistics_channel_all_iosxe): def test_empty(self): self.device = Mock(**self.empty_output) platform_obj = ShowPlatformHardwareQfpBqsStatisticsChannelAll( device=self.device) with self.assertRaises(SchemaEmptyParserError): parsed_output = platform_obj.parse( status='active', slot='0', iotype='ipm') def test_golden_active_ipm(self): self.maxDiff = None self.device = Mock(**self.golden_output_active_ipm) platform_obj = ShowPlatformHardwareQfpBqsStatisticsChannelAll( device=self.device) parsed_output = platform_obj.parse( status='active', slot='0', iotype='ipm') self.assertEqual(parsed_output, self.golden_parsed_output_active_ipm) def test_golden_active_opm(self): self.maxDiff = None self.device = Mock(**self.golden_output_active_opm) platform_obj = ShowPlatformHardwareQfpBqsStatisticsChannelAll( device=self.device) parsed_output = platform_obj.parse( status='active', slot='0', iotype='opm') self.assertEqual(parsed_output, self.golden_parsed_output_active_opm) class show_platform_hardware_qfp_interface(show_platform_hardware_qfp_interface_iosxe): def test_empty(self): self.device = Mock(**self.empty_output) platform_obj = ShowPlatformHardwareQfpInterfaceIfnameStatistics( device=self.device) with self.assertRaises(SchemaEmptyParserError): parsed_output = platform_obj.parse( status='active', interface='gigabitEthernet 0/0/0') def test_golden(self): self.maxDiff = None self.device = Mock(**self.golden_output) platform_obj = ShowPlatformHardwareQfpInterfaceIfnameStatistics( device=self.device) parsed_output = platform_obj.parse( status='active', interface='gigabitEthernet 0/0/0') self.assertEqual(parsed_output, self.golden_parsed_output) class test_show_platform_hardware_qfp_statistics_drop(test_show_platform_hardware_qfp_statistics_drop_iosxe): def test_empty(self): self.device = Mock(**self.empty_output) platform_obj = ShowPlatformHardwareQfpStatisticsDrop( device=self.device) with self.assertRaises(SchemaEmptyParserError): parsed_output = platform_obj.parse(status='active') def test_golden_active(self): self.maxDiff = None self.device = Mock(**self.golden_output_active) platform_obj = ShowPlatformHardwareQfpStatisticsDrop( device=self.device) parsed_output = platform_obj.parse(status='active') self.assertEqual(parsed_output, self.golden_parsed_output_active) class test_show_env(test_show_env_iosxe): def test_empty(self): self.dev = Mock(**self.empty_output) obj = ShowEnvironment(device=self.dev) with self.assertRaises(SchemaEmptyParserError): parsered_output = obj.parse() def test_golden(self): self.maxDiff = None self.dev = Mock(**self.golden_output) obj = ShowEnvironment(device=self.dev) parsed_output = obj.parse() self.assertEqual(parsed_output, self.golden_parsed_output) class test_show_module(test_show_module_iosxe): def test_empty(self): self.dev1 = Mock(**self.empty_output) platform_obj = ShowModule(device=self.dev1) with self.assertRaises(SchemaEmptyParserError): parsed_output = platform_obj.parse() def test_golden(self): self.maxDiff = None self.dev_c3850 = Mock(**self.golden_output_c3850) platform_obj = ShowModule(device=self.dev_c3850) parsed_output = platform_obj.parse() self.assertEqual(parsed_output,self.golden_parsed_output_c3850) class test_show_switch(test_show_switch_iosxe): def test_empty(self): self.dev1 = Mock(**self.empty_output) platform_obj = ShowSwitch(device=self.dev1) with self.assertRaises(SchemaEmptyParserError): parsed_output = platform_obj.parse() def test_golden(self): self.maxDiff = None self.dev_c3850 = Mock(**self.golden_output_c3850) platform_obj = ShowSwitch(device=self.dev_c3850) parsed_output = platform_obj.parse() self.assertEqual(parsed_output,self.golden_parsed_output_c3850) class test_show_switch_detail(test_show_switch_detail_iosxe): def test_empty(self): self.dev1 = Mock(**self.empty_output) platform_obj = ShowSwitchDetail(device=self.dev1) with self.assertRaises(SchemaEmptyParserError): parsed_output = platform_obj.parse() def test_golden(self): self.maxDiff = None self.dev_c3850 = Mock(**self.golden_output_c3850) platform_obj = ShowSwitchDetail(device=self.dev_c3850) parsed_output = platform_obj.parse() self.assertEqual(parsed_output,self.golden_parsed_output_c3850) if __name__ == '__main__': unittest.main()

41.307956

153

0.510582

9,787

96,578

4.897415

0.092061

0.046317

0.024035

0.018631

0.736601

0.685652

0.636623

0.588513

0.549874

0.503119

0

0.08707

0.381857

96,578

2,337

154

41.325631

0.715808

0.000166

0

0.40197

0

0.031527

0.425099

0.019666

0

0.00117

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0.038424

1

0.038424

false

0.000985

0.010345

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0.090148

0

null

0

null

0

1

0

ed6c1e66e6a96e129aa7826692f68edb943e0fae

9,245

py

Python

Analytics/resources/themes/test_subthemes.py

thanosbnt/SharingCitiesDashboard

5d123691d1f25d0b85e20e4e8293266bf23c9f8a

[ "Apache-2.0" ]

4

2018-11-21T14:42:18.000Z

2020-05-11T10:52:59.000Z

Analytics/resources/themes/test_subthemes.py

thanosbnt/SharingCitiesDashboard

5d123691d1f25d0b85e20e4e8293266bf23c9f8a

[ "Apache-2.0" ]

60

2018-11-21T15:11:59.000Z

2019-12-02T10:46:44.000Z

Analytics/resources/themes/test_subthemes.py

thanosbnt/SharingCitiesDashboard

5d123691d1f25d0b85e20e4e8293266bf23c9f8a

[ "Apache-2.0" ]

7

2018-11-21T14:42:44.000Z

2019-11-28T16:24:14.000Z

import unittest from http import HTTPStatus from unittest import TestCase import bcrypt from flask.ctx import AppContext from flask.testing import FlaskClient from app import create_app from models.theme import Theme, SubTheme from models.users import Users class TestSubTemes(TestCase): """ Unittest for the creation, renaming and deleting of Themes """ def setUp(self): """ Setup a FlaskClient for testing, creates an admin user and creates the authorization header for requests to the Flask Client and a dummy theme """ self.client, self.app_context = self.create_test_client() self.user = self.create_admin_user() self.auth_header = self.get_auth_header() self.theme = Theme.get_by_name("_test_add_Subtheme_") if not self.theme: self.theme = Theme("_test_add_Subtheme_") self.theme.save() self.theme.commit() self.theme = Theme.get_by_name("_test_add_Subtheme_") self.subtheme = self.create_dummy_subtheme() def create_test_client(self) -> (FlaskClient, AppContext): """ Create flask testing client :return: FlaskClient for tests and AppContext """ test_app = create_app(DATABASE_NAME='test_analysis', TESTING=True) testing_client = test_app.test_client() test_app_context = test_app.app_context() test_app_context.push() return testing_client, test_app_context def create_dummy_subtheme(self) -> SubTheme: """ Create SubTheme for tests :return: SubTheme for tests """ subtheme = SubTheme.get_by_name('_TEST_SUB_THEME_') if not subtheme: subtheme = SubTheme(self.theme.id, '_TEST_SUB_THEME_') subtheme.save() subtheme.commit() subtheme = SubTheme.get_by_name('_TEST_SUB_THEME_') return subtheme def create_admin_user(self) -> Users: """ Create Admin user for tests :return: an admin user for tests """ password_hash = bcrypt.hashpw("wfnbqk".encode("utf-8"), bcrypt.gensalt()) user = Users.find_by_email("admin@FCC.com") if not user: user = Users("Admin", "admin@FCC.com", password_hash.decode("utf8"), True, True) try: user.save() user.commit() except Exception as e: pass return user def get_auth_header(self) -> {str: str}: """ Create an Authorization header for test :return: An authorization header """ response_login = self.client.post('/login', data=dict(email=self.user.email, password="wfnbqk", remember=True), follow_redirects=True) response_login_json = response_login.get_json() return {'Authorization': 'Bearer {}'.format(response_login_json["access_token"])} def test_add_subtheme(self): """ Create a new SubTheme and check the client response status code for http status 200 (OK) Check JSON response data for the expected message 'New theme created' and Theme name """ response = self.client.post('/admin/themes/add_subtheme', json={"theme_id": self.theme.id, "subtheme": "_TEST_SUB_THEME_2"}, headers=self.auth_header) self.assertEqual(response.status_code, HTTPStatus.OK) json_response = response.get_json() self.assertEqual(json_response["message"], "sub theme created") self.assertEqual(json_response["theme_id"], self.theme.id) self.assertEqual(json_response["subtheme"], "_TEST_SUB_THEME_2") def test_rename_subtheme_theme_id(self): """ Rename a SubTheme by theme_id and check the clients response status code for http status 200 (OK) Check response data for the expected message 'Subtheme renamed' and the Subtheme name has been changed """ if not self.subtheme: self.subtheme = self.create_dummy_subtheme() current_name = self.subtheme.name response = self.client.post('/admin/themes/rename_subtheme', json={"theme_id": self.subtheme.t_id, "current_name": current_name, "new_name": "new_name_not_1" }, headers=self.auth_header) self.assertEqual(response.status_code, HTTPStatus.OK) response = response.get_json() self.assertEqual(response["id"], self.subtheme.id) self.assertEqual(response["message"], "Subtheme renamed") self.assertEqual(response["old_name"], current_name) self.assertEqual(response["new_name"], "new_name_not_1") def test_rename_subtheme_id(self): """ Rename a SubTheme by id and check the clients response status code for http status 200 (OK) Check response data for the expected message 'Subtheme renamed' and the Subtheme name has been changed """ if not self.subtheme: self.subtheme = self.create_dummy_subtheme() current_name = self.subtheme.name response = self.client.post('/admin/themes/rename_subtheme', json={"id": self.subtheme.id, "current_name": current_name, "new_name": "new_name_not_1" }, headers=self.auth_header) self.assertEqual(response.status_code, HTTPStatus.OK) response = response.get_json() self.assertEqual(response["id"], self.subtheme.id) self.assertEqual(response["message"], "Subtheme renamed") self.assertEqual(response["old_name"], current_name) self.assertEqual(response["new_name"], "new_name_not_1") def test_rename_non_existant_subtheme(self): """ Rename a SubTheme that does not exist and check the clients response status code for http status 404 (OK) """ response = self.client.post('/admin/themes/rename_subtheme', json={"theme_id": -1, "current_name": "a3d4f5g6h7j8k0", "new_name": "new_name_not_1" }, headers=self.auth_header) self.assertEqual(response.status_code, HTTPStatus.NOT_FOUND) def test_delete_non_exsitant_subtheme(self): """ Delete a SubTheme that does not exist and check the client response status code for http status 404 """ if not self.subtheme: self.subtheme = self.create_dummy_subtheme() response = self.client.post('/admin/themes/delete_subtheme', json={"name": "weA_gfj24fhurtyui", "theme_id": -1}, headers=self.auth_header) self.assertEqual(response.status_code, HTTPStatus.NOT_FOUND) def test_delete_subtheme_by_id(self): """ Delete a SubTheme by id and check the client response status code for http status 204 (NO_CONTENT) """ if not self.subtheme: self.subtheme = self.create_dummy_subtheme() response = self.client.post('/admin/themes/delete_subtheme', json={"id": self.subtheme.id}, headers=self.auth_header) self.assertEqual(response.status_code, HTTPStatus.NO_CONTENT) def test_delete_subtheme_by_theme_id_and_name(self): """ Delete a SubTheme by theme_id and name: check the client response status code for http status 204 (NO_CONTENT) """ if not self.subtheme: self.subtheme = self.create_dummy_subtheme() response = self.client.post('/admin/themes/delete_subtheme', json={"theme_id": self.subtheme.t_id, "name": self.subtheme.name}, headers=self.auth_header) self.assertEqual(response.status_code, HTTPStatus.NO_CONTENT) def tearDown(self): """ Handle the cleanup after tests""" self.subtheme = SubTheme.get_by_name("new_name_not_1") if not self.subtheme: self.subtheme = SubTheme.get_by_name("_TEST_SUB_THEME_") if self.subtheme: self.subtheme.delete() self.subtheme.commit() test_sub = SubTheme.get_by_name("_TEST_SUB_THEME_2") if test_sub: test_sub.delete() test_sub.commit() if self.theme: self.theme.delete() self.theme.commit() self.client.post('/logout', headers=self.auth_header) if self.user: self.user.delete() self.user.commit() self.app_context.pop() if __name__ == '__main__': unittest.main()

42.800926

119

0.589508

1,038

9,245

5.026012

0.133911

0.062105

0.06613

0.027602

0.575618

0.548591

0.502588

0.477477

0.463676

0.422657

0

0.006824

0.318442

9,245

215

120

43

0.82114

0.160087

0

0.377778

0

0.115056

0.027104

0

0.133333

1

0.096296

false

0.02963

0.066667

0

0.2

0

null

0

null

0

1

0

ed6ced72ed9bc083484bd7a8ca32221ff538be8a

12,541

py

Python

python2.7libs/hammer_tools/content_browser.py

anvdev/Hammer-Tools

0211ec837da6754e537c98624ecd07c23abab28e

[ "Apache-2.0" ]

19

2019-10-09T13:48:11.000Z

2021-06-14T01:25:23.000Z

python2.7libs/hammer_tools/content_browser.py

anvdev/Hammer-Tools

0211ec837da6754e537c98624ecd07c23abab28e

[ "Apache-2.0" ]

219

2019-10-08T14:44:48.000Z

2021-06-19T06:27:46.000Z

python2.7libs/hammer_tools/content_browser.py

anvdev/Hammer-Tools

0211ec837da6754e537c98624ecd07c23abab28e

[ "Apache-2.0" ]

3

2020-02-14T06:18:06.000Z

2020-11-25T20:47:06.000Z

from __future__ import print_function try: from PyQt5.QtWidgets import * from PyQt5.QtGui import * from PyQt5.QtCore import * except ImportError: from PySide2.QtWidgets import * from PySide2.QtGui import * from PySide2.QtCore import * import hou from hammer_tools.utils import createAction def isRevertToDefaultEvent(event): return event.modifiers() == Qt.ControlModifier and event.button() == Qt.MiddleButton class Slider(QSlider): def __init__(self, orientation=Qt.Horizontal, parent=None): super(Slider, self).__init__(orientation, parent) self.defaultValue = 0 self.valueLadderMode = False def revertToDefault(self): self.setValue(self.defaultValue) def setDefaultValue(self, value, reset=True): self.defaultValue = value if reset: self.revertToDefault() def mousePressEvent(self, event): if False: # Type hint event = QMouseEvent if event.button() == Qt.MiddleButton: return elif event.button() == Qt.LeftButton: event = QMouseEvent(QEvent.MouseButtonPress, event.pos(), Qt.MiddleButton, Qt.MiddleButton, Qt.NoModifier) super(Slider, self).mousePressEvent(event) def mouseMoveEvent(self, event): if False: # Type hint event = QMouseEvent if not self.valueLadderMode and event.buttons() == Qt.MiddleButton: try: hou.ui.openValueLadder(self.value(), self.setValue, data_type=hou.valueLadderDataType.Int) except hou.OperationFailed: return else: self.valueLadderMode = True elif self.valueLadderMode: hou.ui.updateValueLadder(event.globalX(), event.globalY(), bool(event.modifiers() & Qt.AltModifier), bool(event.modifiers() & Qt.ShiftModifier)) else: super(Slider, self).mouseMoveEvent(event) def mouseReleaseEvent(self, event): if False: # Type hint event = QMouseEvent if self.valueLadderMode and event.button() == Qt.MiddleButton: hou.ui.closeValueLadder() self.valueLadderMode = False elif isRevertToDefaultEvent(event): self.revertToDefault() else: super(Slider, self).mouseReleaseEvent(event) class SearchField(QComboBox): def __init__(self, parent=None): super(SearchField, self).__init__(parent) self.setEditable(True) edit = self.lineEdit() edit.setPlaceholderText('Search...') edit.installEventFilter(self) edit.setFont(QFont('Segoe UI')) self.setFixedHeight(26) comp = self.completer() comp.setCompletionMode(QCompleter.PopupCompletion) comp.setFilterMode(Qt.MatchContains) comp.setModelSorting(QCompleter.CaseInsensitivelySortedModel) comp.setMaxVisibleItems(5) popup = comp.popup() popup.setStyleSheet(hou.qt.styleSheet()) def mouseReleaseEvent(self, event): if False: # Type hint event = QMouseEvent if isRevertToDefaultEvent(event): self.clearEditText() def eventFilter(self, watched, event): if False: # Type hint watched = QObject event = QEvent if watched == self.lineEdit(): if event.type() == QEvent.MouseButtonRelease and isRevertToDefaultEvent(event): self.clearEditText() event.accept() return True return False def keyPressEvent(self, event): if False: # Type hint event = QKeyEvent key = event.key() mod = event.modifiers() if mod == Qt.NoModifier and key == Qt.Key_Escape: self.clearEditText() else: super(SearchField, self).keyPressEvent(event) def hidePopup(self): super(SearchField, self).hidePopup() self.lineEdit().setFocus() link_or_state_icon = 'BUTTONS_link' embedded_icon = 'BUTTONS_pinned' class BrowserMode(QStandardItemModel): def __init__(self): super(BrowserMode, self).__init__() class BrowserTreeView(QTreeView): def __init__(self, parent=None): super(BrowserTreeView, self).__init__(parent) self.setAlternatingRowColors(True) class BrowserTableView(QListView): def __init__(self, parent=None): super(BrowserTableView, self).__init__(parent) self.setViewMode(QListView.IconMode) self.setResizeMode(QListView.Adjust) self.setSelectionMode(QAbstractItemView.ExtendedSelection) self.setVerticalScrollMode(QAbstractItemView.ScrollPerPixel) self.setIconSize(QSize(120, 90)) self.setUniformItemSizes(True) self.setContextMenuPolicy(Qt.CustomContextMenu) class ContentBrowser(QWidget): def __init__(self, parent=None): super(ContentBrowser, self).__init__(parent) self.setWindowTitle('Content Browser') self.setProperty('houdiniStyle', True) topLayout = QHBoxLayout() topLayout.setContentsMargins(4, 4, 4, 2) topLayout.setSpacing(2) self.refreshButton = QPushButton() self.refreshButton.setFixedSize(26, 26) self.refreshButton.setToolTip('Update\tF5') self.refreshButton.setIcon(hou.qt.Icon('BUTTONS_reload', 18, 18)) self.refreshButton.setIconSize(QSize(18, 18)) topLayout.addWidget(self.refreshButton) sep = hou.qt.Separator() if False: # Type hint sep = QFrame sep.setFixedWidth(2) sep.setFrameShape(QFrame.VLine) topLayout.addWidget(sep) viewModeButtonGroup = QButtonGroup(self) viewModeButtonGroup.setExclusive(True) self.treeViewButton = QPushButton() self.treeViewButton.setFixedSize(26, 26) self.treeViewButton.setToolTip('Tree View\t\tCtrl+1') self.treeViewButton.setIcon(hou.qt.Icon('BUTTONS_tree', 18, 18)) self.treeViewButton.setIconSize(QSize(18, 18)) self.treeViewButton.setCheckable(True) viewModeButtonGroup.addButton(self.treeViewButton) topLayout.addWidget(self.treeViewButton) self.tableViewButton = QPushButton() self.tableViewButton.setFixedSize(26, 26) self.tableViewButton.setToolTip('Table View\tCtrl+2') self.tableViewButton.setIcon(hou.qt.Icon('NETVIEW_shape_palette', 18, 18)) self.tableViewButton.setIconSize(QSize(18, 18)) self.tableViewButton.setCheckable(True) self.tableViewButton.toggle() viewModeButtonGroup.addButton(self.tableViewButton) topLayout.addWidget(self.tableViewButton) topLayout.addWidget(sep) self.searchField = SearchField() self.searchField.setToolTip('Search\tCtrl+F, F3') topLayout.addWidget(self.searchField) searchModeButtonGroup = QButtonGroup(self) searchModeButtonGroup.setExclusive(True) self.wholeSearchButton = QPushButton() self.wholeSearchButton.setFixedSize(26, 26) self.wholeSearchButton.setCheckable(True) self.wholeSearchButton.setToolTip('Whole word search') self.wholeSearchButton.setIcon(hou.qt.Icon('VOP_titlecase', 18, 18)) self.wholeSearchButton.setIconSize(QSize(18, 18)) searchModeButtonGroup.addButton(self.wholeSearchButton) topLayout.addWidget(self.wholeSearchButton) self.fuzzySearchButton = QPushButton() self.fuzzySearchButton.setFixedSize(26, 26) self.fuzzySearchButton.setCheckable(True) self.fuzzySearchButton.toggle() self.fuzzySearchButton.setToolTip('Fuzzy search') self.fuzzySearchButton.setIcon(hou.qt.Icon('VOP_endswith', 18, 18)) self.fuzzySearchButton.setIconSize(QSize(18, 18)) searchModeButtonGroup.addButton(self.fuzzySearchButton) topLayout.addWidget(self.fuzzySearchButton) self.patternSearchButton = QPushButton() self.patternSearchButton.setFixedSize(26, 26) self.patternSearchButton.setCheckable(True) self.patternSearchButton.setToolTip('Search by Pattern') self.patternSearchButton.setIcon(hou.qt.Icon('VOP_isalpha', 18, 18)) self.patternSearchButton.setIconSize(QSize(18, 18)) searchModeButtonGroup.addButton(self.patternSearchButton) topLayout.addWidget(self.patternSearchButton) self.regexSearchButton = QPushButton() self.regexSearchButton.setFixedSize(26, 26) self.regexSearchButton.setCheckable(True) self.regexSearchButton.setToolTip('Search by Regular Expression') self.regexSearchButton.setIcon(hou.qt.Icon('VOP_regex_match', 18, 18)) self.regexSearchButton.setIconSize(QSize(18, 18)) searchModeButtonGroup.addButton(self.regexSearchButton) topLayout.addWidget(self.regexSearchButton) topLayout.addWidget(sep) topLayout.addWidget(hou.qt.HelpButton('/hammer/content_browser', 'Show Help\tF1')) middleLayout = QHBoxLayout() middleLayout.setContentsMargins(4, 0, 0, 4) middleLayout.setSpacing(4) self.viewLayout = QStackedLayout(middleLayout) model = QFileSystemModel() model.setRootPath('C:/') treeView = BrowserTreeView() treeView.setModel(model) treeView.setRootIndex(model.index('C:/')) self.viewLayout.addWidget(treeView) tableView = BrowserTableView() tableView.setModel(model) tableView.setRootIndex(model.index('C:/')) tableView.setSelectionModel(treeView.selectionModel()) self.viewLayout.addWidget(tableView) self.viewLayout.setCurrentIndex(1) self.treeViewButton.clicked.connect(self.switchToTreeView) self.addAction(createAction(self, 'Tree View', self.switchToTreeView, shortcut='Ctrl+1')) self.tableViewButton.clicked.connect(self.switchToTableView) self.addAction(createAction(self, 'Table View', self.switchToTableView, shortcut='Ctrl+2')) bottomLayout = QHBoxLayout() bottomLayout.setContentsMargins(4, 0, 4, 4) bottomLayout.setSpacing(2) settingsButton = QPushButton() settingsButton.setFixedSize(26, 26) settingsButton.setToolTip('Settings') settingsButton.setIcon(hou.qt.Icon('BUTTONS_gear_mini', 18, 18)) settingsButton.setIconSize(QSize(18, 18)) bottomLayout.addWidget(settingsButton) spacer = QSpacerItem(0, 0, QSizePolicy.Expanding, QSizePolicy.Ignored) bottomLayout.addSpacerItem(spacer) self.scaleSlider = Slider() self.scaleSlider.setDefaultValue(50) self.scaleSlider.setFixedWidth(120) self.scaleSlider.valueChanged.connect(lambda v: tableView.setIconSize(QSize(120, 90) * v / 100)) bottomLayout.addWidget(self.scaleSlider) mainLayout = QVBoxLayout(self) mainLayout.setContentsMargins(0, 0, 0, 0) mainLayout.setSpacing(4) mainLayout.addLayout(topLayout) mainLayout.addLayout(middleLayout) mainLayout.addLayout(bottomLayout) def switchToTreeView(self): self.viewLayout.setCurrentIndex(0) self.scaleSlider.hide() self.treeViewButton.setChecked(True) def switchToTableView(self): self.viewLayout.setCurrentIndex(1) self.scaleSlider.show() self.tableViewButton.setChecked(True) def keyPressEvent(self, event): if False: # Type hint event = QKeyEvent key = event.key() mod = event.modifiers() if mod == Qt.NoModifier and key == Qt.Key_F5: pass elif mod == Qt.ControlModifier and key == Qt.Key_F: self.searchField.setFocus() elif mod == Qt.NoModifier and key == Qt.Key_F3: self.searchField.setFocus() elif mod == Qt.ControlModifier and key == Qt.Key_Equal: pass elif mod == Qt.ControlModifier and key == Qt.Key_Minus: pass elif mod == Qt.ControlModifier and key == Qt.Key_1: pass elif mod == Qt.ControlModifier and key == Qt.Key_2: pass elif mod == Qt.NoModifier and key == Qt.Key_F1: pass else: super(ContentBrowser, self).keyPressEvent(event) if __name__ == '__main__': app = QApplication([]) window = ContentBrowser() window.show() app.exec_()

37.21365

106

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0.007811

0.008787

0.012082

0.16866

0.127532

0.109226

0.082866

0.071272

0.041982

0

0.016994

0.239853

12,541

336

107

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0.842547

0.006299

0

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0

0.033406

0.003533

0

1

0.0681

false

0.021505

0.035842

0.003584

0.143369

0.003584

0

null

0

null

0

1

0

ed6cf42a0947849b7e11a5ffae5ba378599d9f7e

1,106

py

Python

rt-thread/applications/server/udp_sender.py

luhuadong/stm32f769-disco-demo

c7fb0d627b02c3f87959f43f1447bc79f62a7099

[ "Apache-2.0" ]

null

rt-thread/applications/server/udp_sender.py

luhuadong/stm32f769-disco-demo

c7fb0d627b02c3f87959f43f1447bc79f62a7099

[ "Apache-2.0" ]

null

rt-thread/applications/server/udp_sender.py

luhuadong/stm32f769-disco-demo

c7fb0d627b02c3f87959f43f1447bc79f62a7099

[ "Apache-2.0" ]

null

#!/usr/bin/python3 """ UDP sender """ import socket import time import sys smsg = b'\xaa\x08\xfe\x00\xc9\xe6\x5f\xee' def main(): ip_port = ('192.168.3.188', 8888) if len(sys.argv) < 2: port = 8888 else: port = int(sys.argv[1]) # 1. 创建 udp 套接字 udp_socket = socket.socket(socket.AF_INET, socket.SOCK_DGRAM) # 2. 绑定本地信息 udp_socket.bind(('', port)) cnt = 100 loop = 4 print("send %d...", cnt*loop) # 3. 接收发送的数据 while cnt > 0: #loop = 10 #while loop > 0: for i in range(0, loop): udp_socket.sendto(smsg, ip_port) print('.', end=' ') #loop = loop -1 #recv_data = udp_socket.recvfrom(1024) #print(recv_data.decode('gbk')) #print(recv_data.decode('utf-8')) #print('.', end=' ') #data = recv_data.decode('utf-8') #print('0x%x'%data) cnt = cnt - 1 time.sleep(0.005) print("") print("finished") # 7. 关闭套接字 udp_socket.close() print("close") if __name__ == '__main__': main()

17.83871

65

0.513562

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null

0

1

0

ed6e6d96a4c0121238dbb61b6a4a506e75d9c0bd

1,007

py

Python

chemmltoolkit/tensorflow/callbacks/variableScheduler.py

Andy-Wilkinson/ChemMLToolk

83efc7ea66d2def860a3e04ccd70d77fb689fddc

[ "MIT" ]

1

2019-10-30T03:43:24.000Z

chemmltoolkit/tensorflow/callbacks/variableScheduler.py

Andy-Wilkinson/ChemMLToolk

83efc7ea66d2def860a3e04ccd70d77fb689fddc

[ "MIT" ]

2

2021-11-28T21:09:30.000Z

2021-11-28T21:09:39.000Z

chemmltoolkit/tensorflow/callbacks/variableScheduler.py

Andy-Wilkinson/ChemMLToolkit

83efc7ea66d2def860a3e04ccd70d77fb689fddc

[ "MIT" ]

null

import tensorflow as tf class VariableScheduler(tf.keras.callbacks.Callback): """Schedules an arbitary variable during training. Arguments: variable: The variable to modify the value of. schedule: A function that takes an epoch index (integer, indexed from 0) and current variable value as input and returns a new value to assign to the variable as output. verbose: int. 0: quiet, 1: update messages. """ def __init__(self, variable, schedule, verbose=0): super(VariableScheduler, self).__init__() self.variable = variable self.schedule = schedule self.verbose = verbose def on_epoch_begin(self, epoch, logs=None): value = self.variable.read_value() value = self.schedule(epoch, value) self.variable.assign(value) if self.verbose > 0: print(f'\nEpoch {epoch + 1}: VariableScheduler assigning ' f'variable {self.variable.name} to {value}.')

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null

0

null

0

1

0

ed71593db0e5552171798bc1852cca8f7c4d9f3e

2,285

py

Python

components/dash-core-components/tests/integration/dropdown/test_dynamic_options.py

mastermind88/dash

760af721980e18d91bdbc4e204d1d063c7ed325c

[ "MIT" ]

null

components/dash-core-components/tests/integration/dropdown/test_dynamic_options.py

mastermind88/dash

760af721980e18d91bdbc4e204d1d063c7ed325c

[ "MIT" ]

null

components/dash-core-components/tests/integration/dropdown/test_dynamic_options.py

mastermind88/dash

760af721980e18d91bdbc4e204d1d063c7ed325c

[ "MIT" ]

null

from dash import Dash, Input, Output, dcc, html from dash.exceptions import PreventUpdate def test_dddo001_dynamic_options(dash_dcc): dropdown_options = [ {"label": "New York City", "value": "NYC"}, {"label": "Montreal", "value": "MTL"}, {"label": "San Francisco", "value": "SF"}, ] app = Dash(__name__) app.layout = dcc.Dropdown(id="my-dynamic-dropdown", options=[]) @app.callback( Output("my-dynamic-dropdown", "options"), [Input("my-dynamic-dropdown", "search_value")], ) def update_options(search_value): if not search_value: raise PreventUpdate return [o for o in dropdown_options if search_value in o["label"]] dash_dcc.start_server(app) # Get the inner input used for search value. input_ = dash_dcc.find_element("#my-dynamic-dropdown input") # Focus on the input to open the options menu input_.send_keys("x") # No options to be found with `x` in them, should show the empty message. dash_dcc.wait_for_text_to_equal(".Select-noresults", "No results found") input_.clear() input_.send_keys("o") options = dash_dcc.find_elements("#my-dynamic-dropdown .VirtualizedSelectOption") # Should show all options. assert len(options) == 3 # Searching for `on` input_.send_keys("n") options = dash_dcc.find_elements("#my-dynamic-dropdown .VirtualizedSelectOption") assert len(options) == 1 print(options) assert options[0].text == "Montreal" assert dash_dcc.get_logs() == [] def test_dddo002_array_comma_value(dash_dcc): app = Dash(__name__) dropdown = dcc.Dropdown( options=["New York, NY", "Montreal, QC", "San Francisco, CA"], value=["San Francisco, CA"], multi=True, ) app.layout = html.Div(dropdown) dash_dcc.start_server(app) dash_dcc.wait_for_text_to_equal("#react-select-2--value-0", "San Francisco, CA\n ") assert dash_dcc.get_logs() == [] def test_dddo003_value_no_options(dash_dcc): app = Dash(__name__) app.layout = html.Div( [ dcc.Dropdown(value="foobar", id="dropdown"), ] ) dash_dcc.start_server(app) assert dash_dcc.get_logs() == [] dash_dcc.wait_for_element("#dropdown")

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null

0

null

0

1

0

ed725c3c070133c88aad862a90d3bfcbc58edf09

768

py

Python

Server.py

dipghoshraj/live-video-streming-with-web-socket

dda924e22a4c40d225ec39dd94ee1e489233c403

[ "BSD-2-Clause" ]

3

2020-06-30T03:49:46.000Z

2021-07-17T16:15:55.000Z

Server.py

dipghoshraj/live-video-streming-with-web-socket

dda924e22a4c40d225ec39dd94ee1e489233c403

[ "BSD-2-Clause" ]

null

Server.py

dipghoshraj/live-video-streming-with-web-socket

dda924e22a4c40d225ec39dd94ee1e489233c403

[ "BSD-2-Clause" ]

null

import cv2 import io import socket import struct import time import pickle import zlib client_socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM) client_socket.connect(('127.0.0.1', 8485)) connection = client_socket.makefile('wb') cam = cv2.VideoCapture("E:/songs/Attention Charlie Puth(GabbarWorld.com) 1080p.mp4") cam.set(3, 320) cam.set(4, 240) img_counter = 0 encode_param = [int(cv2.IMWRITE_JPEG_QUALITY), 90] while True: ret, frame = cam.read() result, frame = cv2.imencode('.jpg', frame, encode_param) # data = zlib.compress(pickle.dumps(frame, 0)) data = pickle.dumps(frame, 0) size = len(data) print("{}: {}".format(img_counter, size)) client_socket.sendall(struct.pack(">L", size) + data) img_counter += 1 cam.release()

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null

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null

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1

0

ed74d0762a12ab84a6b4c685f57a0a532e003b99

7,059

py

Python

hal/agent/tf2_utils.py

gunpowder78/google-research

d41bbaca1eb9bfd980ec2b3fd201c3ddb4d1f2e5

[ "Apache-2.0" ]

1

2022-03-13T21:48:52.000Z

hal/agent/tf2_utils.py

gunpowder78/google-research

d41bbaca1eb9bfd980ec2b3fd201c3ddb4d1f2e5

[ "Apache-2.0" ]

null

hal/agent/tf2_utils.py

gunpowder78/google-research

d41bbaca1eb9bfd980ec2b3fd201c3ddb4d1f2e5

[ "Apache-2.0" ]

1

2022-03-30T07:20:29.000Z

# coding=utf-8 # Copyright 2022 The Google Research Authors. # # 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. """Utilities for Tensorflow 2.0. Partially adapted from: https://www.tensorflow.org/tutorials/text/image_captioning """ # Lint as: python3 # pylint: disable=invalid-name from __future__ import absolute_import from __future__ import division import tensorflow as tf def film_params(sentence_embedding, n_layer_channel): """Generate FiLM parameters from a sentence embedding. Generate FiLM parameters from a sentence embedding. This method assumes a batch dimension exists. Args: sentence_embedding: a tensor containing batched sentenced embedding to be transformed n_layer_channel: a list of integers specifying how many channels are at each hidden layer to be FiLM'ed Returns: a tuple of tensors the same length as n_layer_channel. Each element contains all gamma_i and beta_i for a single hidden layer. """ n_total = sum(n_layer_channel) * 2 all_params = tf.layers.dense(sentence_embedding, n_total) all_params = tf.keras.layers.Dense( 2 * sum * (n_layer_channel), activation=tf.nn.relu) return tf.split(all_params, [c * 2 for c in n_layer_channel], 1) def stack_conv_layer(layer_cfg, padding='same'): """Stack convolution layers per layer_cfg. Args: layer_cfg: list of integer tuples specifying the parameter each layer; each tuple should be (channel, kernel size, strides) padding: what kind of padding the conv layers use Returns: the keras model with stacked conv layers """ layers = [] for cfg in layer_cfg[:-1]: layers.append( tf.keras.layers.Conv2D( filters=cfg[0], kernel_size=cfg[1], strides=cfg[2], activation=tf.nn.relu, padding=padding)) final_cfg = layer_cfg[-1] layers.append( tf.keras.layers.Conv2D( final_cfg[0], final_cfg[1], final_cfg[2], padding=padding)) return tf.keras.Sequential(layers) def stack_dense_layer(layer_cfg): """Stack Dense layers. Args: layer_cfg: list of integer specifying the number of units at each layer Returns: the keras model with stacked dense layers """ layers = [] for cfg in layer_cfg[:-1]: layers.append(tf.keras.layers.Dense(cfg, activation=tf.nn.relu)) layers.append(tf.keras.layers.Dense(layer_cfg[-1])) return tf.keras.Sequential(layers) def soft_variables_update(source_variables, target_variables, polyak_rate=1.0): """Update the target variables using exponential moving average. Specifically, v_s' = v_s * polyak_rate + (1-polyak_rate) * v_t Args: source_variables: the moving average variables target_variables: the new observations polyak_rate: rate of moving average Returns: Operation that does the update """ updates = [] for (v_s, v_t) in zip(source_variables, target_variables): v_t.shape.assert_is_compatible_with(v_s.shape) def update_fn(v1, v2): """Update variables.""" # For not trainable variables do hard updates. return v1.assign(polyak_rate * v1 + (1 - polyak_rate) * v2) update = update_fn(v_t, v_s) updates.append(update) return updates def vector_tensor_product(a, b): """"Returns keras layer that perfrom a outer product between a and b.""" # a shape: [B, ?, d], b shape: [B, ?, d] shape_layer = tf.keras.layers.Lambda(tf.shape) shape = shape_layer(b) shape_numpy = b.get_shape() variable_length = shape[1] # variable_len = ? expand_dims_layer_1 = tf.keras.layers.Reshape((-1, 1, shape_numpy[-1])) expand_dims_layer_2 = tf.keras.layers.Reshape((-1, 1, shape_numpy[-1])) a = expand_dims_layer_1(a) # a shape: [B, ?, 1, d] b = expand_dims_layer_2(b) # a shape: [B, ?, 1, d] tile_layer = tf.keras.layers.Lambda( lambda inputs: tf.tile(inputs[0], multiples=inputs[1])) a = tile_layer((a, [1, 1, variable_length, 1])) # a shape: [B, ?, ?, d] b = tile_layer((b, [1, 1, variable_length, 1])) # b shape: [B, ?, ?, d] b = tf.keras.layers.Permute((2, 1, 3))(b) # b shape: [B, ?, ?, d] return tf.keras.layers.concatenate([a, b]) # shape: [B, ?, ?, 2*d] class BahdanauAttention(tf.keras.Model): """Bahdanau Attention Layer. Attributes: w1: weights that process the feature w2: weights that process the memory state v: projection layer that project score vector to scalar """ def __init__(self, units): """Initialize Bahdanau attention layer. Args: units: size of the dense layers """ super(BahdanauAttention, self).__init__() self.W1 = tf.keras.layers.Dense(units) self.W2 = tf.keras.layers.Dense(units) self.V = tf.keras.layers.Dense(1) def call(self, features, hidden): # features(CNN_encoder output) shape == (batch_size, 64, embedding_dim) # hidden shape == (batch_size, hidden_size) # hidden_with_time_axis shape == (batch_size, 1, hidden_size) hidden_with_time_axis = tf.expand_dims(hidden, 1) # score shape == (batch_size, 64, hidden_size) score = tf.nn.tanh(self.W1(features) + self.W2(hidden_with_time_axis)) # attention_weights shape == (batch_size, 64, 1) # you get 1 at the last axis because you are applying score to self.V attention_weights = tf.nn.softmax(self.V(score), axis=1) # context_vector shape after sum == (batch_size, hidden_size) context_vector = attention_weights * features context_vector = tf.reduce_sum(context_vector, axis=1) return context_vector, attention_weights class GRUEnecoder(tf.keras.Model): """TF2.0 GRE encoder. Attributes: embedding: word embedding matrix gru: the GRU layer """ def __init__(self, embedding_dim, units, vocab_size): """Initialize the GRU encoder. Args: embedding_dim: dimension of word emebdding units: number of units of the memory state vocab_size: total number of vocabulary """ super(GRUEnecoder, self).__init__() self._units = units self.embedding = tf.keras.layers.Embedding(vocab_size, embedding_dim) self.gru = tf.keras.layers.GRU( self.units, return_sequences=True, return_state=True, recurrent_initializer='glorot_uniform') def call(self, x, hidden): # x shape after passing through embedding == (batch_size, 1, embedding_dim) x = self.embedding(x) # passing the concatenated vector to the GRU output, state = self.gru(x) return output, state def reset_state(self, batch_size): return tf.zeros((batch_size, self._units))

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null

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1

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ed753328e567a24c6d1169588942c86a984af1ee

4,437

py

Python

wolk/logger_factory.py

Wolkabout/WolkConnect-Python-

11412e3f88911170f587b5e857d07ab41c8f52b5

[ "Apache-2.0" ]

6

2016-12-19T13:36:44.000Z

2018-05-10T15:08:15.000Z

wolk/logger_factory.py

Wolkabout/WolkConnect-Python

11412e3f88911170f587b5e857d07ab41c8f52b5

[ "Apache-2.0" ]

5

2019-02-23T09:37:12.000Z

2021-09-17T13:54:58.000Z

wolk/logger_factory.py

Wolkabout/WolkConnect-Python-

11412e3f88911170f587b5e857d07ab41c8f52b5

[ "Apache-2.0" ]

3

2016-08-15T22:19:00.000Z

2017-12-28T09:48:37.000Z

"""LoggerFactory Module.""" # Copyright 2020 WolkAbout Technology s.r.o. # # 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 logging from typing import List from typing import Optional class LoggerFactory: """Factory for issuing ready to use loggers in other modules.""" def __init__(self, level=logging.INFO, console=True, log_file=None): # type: ignore """ Create a factory that will give loggers through calls to get_logger(). :param level: Set the desired logging level :type level: int or None :param console: Should the log messages be outputted to the console :type console: bool or None :param log_file: Name of the log file to output to :type log_file: str or None """ self.level = level self.device_key = None self.console = console self.log_file = log_file self.loggers: List[logging.Logger] = [] def set_device_key(self, device_key: str) -> None: """ Set device key. :param device_key: Device key :type device_key: str """ self.device_key = device_key def get_logger( self, name: str, level: Optional[int] = None ) -> logging.Logger: """ Return a ready to use logger instance. :param name: Name of the logger :type name: str :param level: Override the log level :type level: int or None :returns: Logger instance :rtype: logger """ logger = logging.getLogger(name) if level is not None: logger.setLevel(level) else: logger.setLevel(self.level) if self.device_key is not None: formatter = logging.Formatter( "%(asctime)s - '" + str(self.device_key) + "' - %(levelname)s [%(filename)s:%(lineno)s" + " - %(funcName)s()] - %(message)s" ) else: formatter = logging.Formatter( "%(asctime)s - %(levelname)s [%(filename)s:%(lineno)s" + " - %(funcName)s()] - %(message)s" ) if self.console: console_handler = logging.StreamHandler() if level is not None: console_handler.setLevel(level) else: console_handler.setLevel(self.level) console_handler.setFormatter(formatter) logger.addHandler(console_handler) if self.log_file is not None: file_handler = logging.FileHandler(self.log_file) if level is not None: file_handler.setLevel(level) else: file_handler.setLevel(self.level) file_handler.setFormatter(formatter) logger.addHandler(file_handler) self.loggers.append(logger) return logger # Logging levels available: NOTSET, INFO, DEBUG logger_factory = LoggerFactory(level=logging.INFO) LEVELS = { "debug": logging.DEBUG, "info": logging.INFO, "warning": logging.WARNING, "error": logging.ERROR, "critical": logging.CRITICAL, "notset": logging.NOTSET, } def logging_config(level: str, log_file: Optional[str] = None) -> None: """ Set desired log level and designate a log file. :param level: Available levels : debug, info, notset :type level: str :param log_file: path to log file :type log_file: str or None """ if log_file is not None: logger_factory.log_file = log_file if level not in LEVELS: print(f"Invalid level '{level}'") return if LEVELS[level] == logger_factory.level: return logger_factory.level = LEVELS[level] for logger in logger_factory.loggers: logger.setLevel(logger_factory.level) for handler in logger.handlers: handler.setLevel(logger_factory.level)

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null

0

null

0

1

0

ed7563752fb4afab443eb59eb4484ffff4182b40

1,830

py

Python

raw.py

andre-marcos-perez/data-pipeline-demo

2647cce6e90d39798eda352608dc0f6d6ab5255a

[ "MIT" ]

3

2021-05-20T23:24:13.000Z

2021-08-20T12:23:18.000Z

raw.py

andre-marcos-perez/data-pipeline-demo

2647cce6e90d39798eda352608dc0f6d6ab5255a

[ "MIT" ]

null

raw.py

andre-marcos-perez/data-pipeline-demo

2647cce6e90d39798eda352608dc0f6d6ab5255a

[ "MIT" ]

3

2021-05-26T14:49:20.000Z

2022-03-21T23:17:54.000Z

import json import gzip import requests from datetime import datetime import pendulum import boto3 from botocore.exceptions import ClientError from util.log import Log from settings.aws_settings import AWSSettings from settings.telegram_settings import TelegramSettings def lambda_handler(event: dict, context: dict) -> dict: log = Log.setup(name='logger') aws_settings = AWSSettings() telegram_settings = TelegramSettings() timezone = pendulum.timezone('America/Sao_Paulo') date = datetime.now(tz=timezone).strftime('%Y-%m-%d') timestamp = datetime.now(tz=timezone).strftime('%Y%m%d%H%M%S') try: token = telegram_settings.access_token base_url = f"https://api.telegram.org/bot{token}" data = json.loads(event["body"]) chat_id = data["message"]["chat"]["id"] if chat_id == telegram_settings.chat_id: client = boto3.client('s3') bucket = aws_settings.raw_bucket root_path = aws_settings.root_path try: with open(f"{root_path}/{timestamp}.json", mode='w', encoding='utf8') as fp: json.dump(data, fp) client.upload_file(f"{root_path}/{timestamp}.json", bucket, f"{date}/{timestamp}.json") except ClientError as exc: raise exc else: text = "I can't talk to strangers, sorry mate!" data = {"text": text, "chat_id": chat_id} data = gzip.compress(json.dumps(data).encode('utf-8')) headers = {'content-type': 'application/json', 'content-encoding': 'gzip'} url = base_url + "/sendMessage" requests.post(url=url, data=data, headers=headers) except Exception as exc: log.error(msg=exc) finally: return dict(statusCode="200")

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null

0

null

0

1

0

ed75b8a825782f227e671daaa305387cdcbcd9d0

2,688

py

Python

v2_hier/site_stat.py

ruslan-ok/ruslan

fc402e53d2683581e13f4d6c69a6f21e5c2ca1f8

[ "MIT" ]

null

v2_hier/site_stat.py

ruslan-ok/ruslan

fc402e53d2683581e13f4d6c69a6f21e5c2ca1f8

[ "MIT" ]

null

v2_hier/site_stat.py

ruslan-ok/ruslan

fc402e53d2683581e13f4d6c69a6f21e5c2ca1f8

[ "MIT" ]

null

"""Collecting statistics of site visits.""" import collections from datetime import datetime from functools import reduce from django.utils.translation import gettext_lazy as _ from hier.models import IPInfo, AccessLog, SiteStat from v2_hier.utils import APPS def get_site_stat(user): """Processing a new portion of log file records. The site applications that users have visited and information about their IP addresses will be shown. """ TOTAL_IP = _('total different').capitalize() + ' IP' TOTAL_LOG = _('total log records').capitalize() NEW_LOG = _('new log records').capitalize() cnt = collections.Counter() cnt[TOTAL_IP] = len(IPInfo.objects.all()) cnt[TOTAL_LOG] = len(AccessLog.objects.all()) #Determining the last previously processed log file entry last = datetime.min site_stat = None if SiteStat.objects.filter(user=user.id).exists(): site_stat = SiteStat.objects.filter(user = user.id).get() if site_stat.record and site_stat.record.event: last = site_stat.record.event # New records records = AccessLog.objects.filter(event__gt=last).order_by('-event') cnt[NEW_LOG] += len(records) # Save last processed log record last_rec = None if (len(records) > 0): last_rec = records[0] if site_stat: site_stat.record = last_rec site_stat.save() else: SiteStat.objects.create(user=user, record=last_rec) #raise Exception(last_rec.event) apps = {} for rec in records: uri = valid_uri(rec) if not uri: continue # Determining the access to the site application a_app = list(filter(lambda x: '/{}/'.format(x) in uri, APPS)) if not a_app: continue app = a_app[0] if not app in apps: apps[app] = {} host = str(rec.host.info()) #raise Exception('aaa = ', aaa) if not host in apps[app]: apps[app][host] = [] page = '{} {}'.format(rec.method, uri) if not page in apps[app][host]: apps[app][host].append(page) return cnt.most_common(), apps def valid_uri(rec): if (rec.status >= 400) or (rec.status == 301): return None if 'favicon.ico' in rec.uri or '/static/' in rec.uri or '/jsi18n/' in rec.uri or '/photo/get_mini/' in rec.uri: return None if ('/?' in rec.uri) and (rec.method != 'POST'): uri = rec.uri.split('?')[0] else: uri = rec.uri uri = uri.replace('/ru/', '/').replace('/en/', '/') if (uri == '/'): return None return uri

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ed75ce190b9f65a6716720968d522d43762ebdb0

16,643

py

Python

cli/pcluster/utils.py

mkosmo/cfncluster

f1817cc187f2b92127d48f16debb4b7ea4f4a80f

[ "Apache-2.0" ]

1

2021-04-08T05:08:07.000Z

cli/pcluster/utils.py

mkosmo/cfncluster

f1817cc187f2b92127d48f16debb4b7ea4f4a80f

[ "Apache-2.0" ]

null

cli/pcluster/utils.py

mkosmo/cfncluster

f1817cc187f2b92127d48f16debb4b7ea4f4a80f

[ "Apache-2.0" ]

1

2019-05-10T16:03:19.000Z

# Copyright 2018 Amazon.com, Inc. or its affiliates. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"). You may not use this file except in compliance with # the License. A copy of the License is located at # # http://aws.amazon.com/apache2.0/ # # or in the "LICENSE.txt" file accompanying this file. This file is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES # OR CONDITIONS OF ANY KIND, express or implied. See the License for the specific language governing permissions and # limitations under the License. # fmt: off from __future__ import absolute_import, print_function # isort:skip from future import standard_library # isort:skip standard_library.install_aliases() # fmt: on import json import logging import os import sys import time import urllib.request import zipfile from io import BytesIO import boto3 import pkg_resources from botocore.exceptions import ClientError LOGGER = logging.getLogger(__name__) PCLUSTER_STACK_PREFIX = "parallelcluster-" PCLUSTER_ISSUES_LINK = "https://github.com/aws/aws-parallelcluster/issues" def get_stack_name(cluster_name): return PCLUSTER_STACK_PREFIX + cluster_name def get_region(): """Get AWS_DEFAULT_REGION from the environment.""" return os.environ.get("AWS_DEFAULT_REGION") def get_partition(): """Get partition for the AWS_DEFAULT_REGION set in the environment.""" return "aws-us-gov" if get_region().startswith("us-gov") else "aws" def paginate_boto3(method, **kwargs): """ Return a generator for a boto3 call, this allows pagination over an arbitrary number of responses. :param method: boto3 method :param kwargs: arguments to method :return: generator with boto3 results """ client = method.__self__ paginator = client.get_paginator(method.__name__) for page in paginator.paginate(**kwargs).result_key_iters(): for result in page: yield result def create_s3_bucket(bucket_name, region): """ Create a new S3 bucket. :param bucket_name: name of the S3 bucket to create :param region: aws region """ s3_client = boto3.client("s3") """ :type : pyboto3.s3 """ try: if region != "us-east-1": s3_client.create_bucket(Bucket=bucket_name, CreateBucketConfiguration={"LocationConstraint": region}) else: s3_client.create_bucket(Bucket=bucket_name) except s3_client.exceptions.BucketAlreadyOwnedByYou: print("Bucket already exists") def delete_s3_bucket(bucket_name): """ Delete an S3 bucket together with all stored objects. :param bucket_name: name of the S3 bucket to delete """ try: bucket = boto3.resource("s3").Bucket(bucket_name) bucket.objects.all().delete() bucket.delete() except boto3.client("s3").exceptions.NoSuchBucket: pass except ClientError: print("Failed to delete bucket %s. Please delete it manually." % bucket_name) def zip_dir(path): """ Create a zip archive containing all files and dirs rooted in path. The archive is created in memory and a file handler is returned by the function. :param path: directory containing the resources to archive. :return file handler pointing to the compressed archive. """ file_out = BytesIO() with zipfile.ZipFile(file_out, "w", zipfile.ZIP_DEFLATED) as ziph: for root, _, files in os.walk(path): for file in files: ziph.write(os.path.join(root, file), os.path.relpath(os.path.join(root, file), start=path)) file_out.seek(0) return file_out def upload_resources_artifacts(bucket_name, root): """ Upload to the specified S3 bucket the content of the directory rooted in root path. All dirs contained in root dir will be uploaded as zip files to $bucket_name/$dir_name/artifacts.zip. All files contained in root dir will be uploaded to $bucket_name. :param bucket_name: name of the S3 bucket where files are uploaded :param root: root directory containing the resources to upload. """ bucket = boto3.resource("s3").Bucket(bucket_name) for res in os.listdir(root): if os.path.isdir(os.path.join(root, res)): bucket.upload_fileobj(zip_dir(os.path.join(root, res)), "%s/artifacts.zip" % res) elif os.path.isfile(os.path.join(root, res)): bucket.upload_file(os.path.join(root, res), res) def _get_json_from_s3(region, file_name): """ Get pricing file (if none) and parse content as json. :param region: AWS Region :param file_name the object name to get :return: a json object representing the file content :raises ClientError if unable to download the file :raises ValueError if unable to decode the file content """ bucket_name = "{0}-aws-parallelcluster".format(region) file_contents = boto3.resource("s3").Object(bucket_name, file_name).get()["Body"].read().decode("utf-8") return json.loads(file_contents) def get_supported_features(region, feature): """ Get a json object containing the attributes supported by a feature, for example. { "Features": { "efa": { "instances": ["c5n.18xlarge", "p3dn.24xlarge", "i3en.24xlarge"], "baseos": ["alinux", "centos7"], "schedulers": ["sge", "slurm", "torque"] }, "batch": { "instances": ["r3.8xlarge", ..., "m5.4xlarge"] } } } :param region: AWS Region :param feature: the feature to search for, i.e. "efa" "awsbatch" :return: json object containing all the attributes supported by feature """ try: features = _get_json_from_s3(region, "features/feature_whitelist.json") supported_features = features.get("Features").get(feature) except (ValueError, ClientError, KeyError) as e: if isinstance(e, ClientError): code = e.response.get("Error").get("Code") if code == "InvalidAccessKeyId": error(e.response.get("Error").get("Message")) error( "Failed validate {0}. This is probably a bug on our end. " "Please submit an issue {1}".format(feature, PCLUSTER_ISSUES_LINK) ) return supported_features def get_instance_vcpus(region, instance_type): """ Get number of vcpus for the given instance type. :param region: AWS Region :param instance_type: the instance type to search for. :return: the number of vcpus or -1 if the instance type cannot be found or the pricing file cannot be retrieved/parsed """ try: instances = _get_json_from_s3(region, "instances/instances.json") vcpus = int(instances[instance_type]["vcpus"]) except (KeyError, ValueError, ClientError): vcpus = -1 return vcpus def get_supported_os(scheduler): """ Return a tuple of the os supported by parallelcluster for the specific scheduler. :param scheduler: the scheduler for which we want to know the supported os :return: a tuple of strings of the supported os """ return "alinux" if scheduler == "awsbatch" else "alinux", "centos6", "centos7", "ubuntu1604", "ubuntu1804" def get_supported_schedulers(): """ Return a tuple of the scheduler supported by parallelcluster. :return: a tuple of strings of the supported scheduler """ return "sge", "torque", "slurm", "awsbatch" def get_stack_output_value(stack_outputs, output_key): """ Get output value from Cloudformation Stack Output. :param stack_outputs: Cloudformation Stack Outputs :param output_key: Output Key :return: OutputValue if that output exists, otherwise None """ return next((o.get("OutputValue") for o in stack_outputs if o.get("OutputKey") == output_key), None) def get_stack(stack_name, cfn_client=None): """ Get the output for a DescribeStacks action for the given Stack. :param stack_name: the CFN Stack name :param cfn_client: boto3 cloudformation client :return: the Stack data type """ try: if not cfn_client: cfn_client = boto3.client("cloudformation") return cfn_client.describe_stacks(StackName=stack_name).get("Stacks")[0] except (ClientError, IndexError) as e: error(e.response.get("Error").get("Message")) def verify_stack_creation(stack_name, cfn_client): """ Wait for the stack creation to be completed and notify if the stack creation fails. :param stack_name: the stack name that we should verify :param cfn_client: the CloudFormation client to use to verify stack status :return: True if the creation was successful, false otherwise. """ status = get_stack(stack_name, cfn_client).get("StackStatus") resource_status = "" while status == "CREATE_IN_PROGRESS": status = get_stack(stack_name, cfn_client).get("StackStatus") events = cfn_client.describe_stack_events(StackName=stack_name).get("StackEvents")[0] resource_status = ("Status: %s - %s" % (events.get("LogicalResourceId"), events.get("ResourceStatus"))).ljust( 80 ) sys.stdout.write("\r%s" % resource_status) sys.stdout.flush() time.sleep(5) # print the last status update in the logs if resource_status != "": LOGGER.debug(resource_status) if status != "CREATE_COMPLETE": LOGGER.critical("\nCluster creation failed. Failed events:") events = cfn_client.describe_stack_events(StackName=stack_name).get("StackEvents") for event in events: if event.get("ResourceStatus") == "CREATE_FAILED": LOGGER.info( " - %s %s %s", event.get("ResourceType"), event.get("LogicalResourceId"), event.get("ResourceStatusReason"), ) return False return True def get_templates_bucket_path(): """Return a string containing the path of bucket.""" region = get_region() s3_suffix = ".cn" if region.startswith("cn") else "" return "https://s3.{REGION}.amazonaws.com{S3_SUFFIX}/{REGION}-aws-parallelcluster/templates/".format( REGION=region, S3_SUFFIX=s3_suffix ) def get_installed_version(): """Get the version of the installed aws-parallelcluster package.""" return pkg_resources.get_distribution("aws-parallelcluster").version def check_if_latest_version(): """Check if the current package version is the latest one.""" try: latest = json.loads(urllib.request.urlopen("https://pypi.python.org/pypi/aws-parallelcluster/json").read())[ "info" ]["version"] if get_installed_version() < latest: print("Info: There is a newer version %s of AWS ParallelCluster available." % latest) except Exception: pass def warn(message): """Print a warning message.""" print("WARNING: {0}".format(message)) def error(message, fail_on_error=True): """Print an error message and Raise SystemExit exception to the stderr if fail_on_error is true.""" if fail_on_error: sys.exit("ERROR: {0}".format(message)) else: print("ERROR: {0}".format(message)) def get_cfn_param(params, key_name): """ Get parameter value from Cloudformation Stack Parameters. :param params: Cloudformation Stack Parameters :param key_name: Parameter Key :return: ParameterValue if that parameter exists, otherwise None """ param_value = next((i.get("ParameterValue") for i in params if i.get("ParameterKey") == key_name), "NONE") return param_value.strip() def get_efs_mount_target_id(efs_fs_id, avail_zone): """ Search for a Mount Target Id in given availability zone for the given EFS file system id. :param efs_fs_id: EFS file system Id :param avail_zone: Availability zone to verify :return: the mount_target_id or None """ mount_target_id = None if efs_fs_id: mount_targets = boto3.client("efs").describe_mount_targets(FileSystemId=efs_fs_id) for mount_target in mount_targets.get("MountTargets"): # Check to see if there is an existing mt in the az of the stack mount_target_subnet = mount_target.get("SubnetId") if avail_zone == get_avail_zone(mount_target_subnet): mount_target_id = mount_target.get("MountTargetId") return mount_target_id def get_avail_zone(subnet_id): avail_zone = None try: avail_zone = ( boto3.client("ec2").describe_subnets(SubnetIds=[subnet_id]).get("Subnets")[0].get("AvailabilityZone") ) except ClientError as e: LOGGER.debug( "Unable to detect availability zone for subnet {0}.\n{1}".format( subnet_id, e.response.get("Error").get("Message") ) ) return avail_zone def get_latest_alinux_ami_id(): """Get latest alinux ami id.""" try: alinux_ami_id = ( boto3.client("ssm") .get_parameters_by_path(Path="/aws/service/ami-amazon-linux-latest") .get("Parameters")[0] .get("Value") ) except ClientError as e: error("Unable to retrieve Amazon Linux AMI id.\n{0}".format(e.response.get("Error").get("Message"))) return alinux_ami_id def list_ec2_instance_types(): """Return a list of all the instance types available on EC2, independent by the region.""" return boto3.client("ec2").meta.service_model.shape_for("InstanceType").enum def get_master_server_id(stack_name): """Return the physical id of the master server, or [] if no master server.""" try: resources = boto3.client("cloudformation").describe_stack_resource( StackName=stack_name, LogicalResourceId="MasterServer" ) return resources.get("StackResourceDetail").get("PhysicalResourceId") except ClientError as e: error(e.response.get("Error").get("Message")) def _get_master_server_ip(stack_name): """ Get the IP Address of the MasterServer. :param stack_name: The name of the cloudformation stack :param config: Config object :return private/public ip address """ ec2 = boto3.client("ec2") master_id = get_master_server_id(stack_name) if not master_id: error("MasterServer not running. Can't SSH") instance = ec2.describe_instances(InstanceIds=[master_id]).get("Reservations")[0].get("Instances")[0] ip_address = instance.get("PublicIpAddress") if ip_address is None: ip_address = instance.get("PrivateIpAddress") state = instance.get("State").get("Name") if state != "running" or ip_address is None: error("MasterServer: %s\nCannot get ip address.", state.upper()) return ip_address def get_master_ip_and_username(cluster_name): cfn = boto3.client("cloudformation") try: stack_name = get_stack_name(cluster_name) stack_result = cfn.describe_stacks(StackName=stack_name).get("Stacks")[0] stack_status = stack_result.get("StackStatus") valid_status = ["CREATE_COMPLETE", "UPDATE_COMPLETE", "UPDATE_ROLLBACK_COMPLETE"] invalid_status = ["DELETE_COMPLETE", "DELETE_IN_PROGRESS"] if stack_status in invalid_status: error("Unable to retrieve master_ip and username for a stack in the status: {0}".format(stack_status)) elif stack_status in valid_status: outputs = stack_result.get("Outputs") master_ip = get_stack_output_value(outputs, "MasterPublicIP") or _get_master_server_ip(stack_name) username = get_stack_output_value(outputs, "ClusterUser") else: # Stack is in CREATING, CREATED_FAILED, or ROLLBACK_COMPLETE but MasterServer is running master_ip = _get_master_server_ip(stack_name) template = cfn.get_template(StackName=stack_name) mappings = template.get("TemplateBody").get("Mappings").get("OSFeatures") base_os = get_cfn_param(stack_result.get("Parameters"), "BaseOS") username = mappings.get(base_os).get("User") if not master_ip: error("Failed to get cluster {0} ip.".format(cluster_name)) if not username: error("Failed to get cluster {0} username.".format(cluster_name)) except ClientError as e: error(e.response.get("Error").get("Message")) return master_ip, username def get_cli_log_file(): return os.path.expanduser(os.path.join("~", ".parallelcluster", "pcluster-cli.log"))

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0

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false

0.008368

0.054393

0.008368

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0.025105

0

null

0

null

0

1

0

ed7707a9a93d2eb459c06d85459c2db5718ad3cc

3,963

py

Python

tools/telemetry/telemetry/core/platform/android_device_unittest.py

kjthegod/chromium

cf940f7f418436b77e15b1ea23e6fa100ca1c91a

[ "BSD-3-Clause-No-Nuclear-License-2014", "BSD-3-Clause" ]

1

2019-11-28T10:46:52.000Z

tools/telemetry/telemetry/core/platform/android_device_unittest.py

kjthegod/chromium

cf940f7f418436b77e15b1ea23e6fa100ca1c91a

[ "BSD-3-Clause-No-Nuclear-License-2014", "BSD-3-Clause" ]

null

tools/telemetry/telemetry/core/platform/android_device_unittest.py

kjthegod/chromium

cf940f7f418436b77e15b1ea23e6fa100ca1c91a

[ "BSD-3-Clause-No-Nuclear-License-2014", "BSD-3-Clause" ]

2

2015-03-27T11:15:39.000Z

2016-08-17T14:19:56.000Z

# Copyright 2014 The Chromium Authors. All rights reserved. # Use of this source code is governed by a BSD-style license that can be # found in the LICENSE file. import unittest from telemetry import benchmark from telemetry.core import browser_options from telemetry.core.platform import android_device from telemetry.core.platform import android_platform_backend from telemetry.unittest_util import system_stub class AndroidDeviceTest(unittest.TestCase): def setUp(self): self._android_device_stub = system_stub.Override( android_device, ['adb_commands']) def testGetAllAttachedAndroidDevices(self): self._android_device_stub.adb_commands.attached_devices = [ '01', '02'] self.assertEquals( set(['01', '02']), set(device.device_id for device in android_device.AndroidDevice.GetAllConnectedDevices() )) def tearDown(self): self._android_device_stub.Restore() class GetDeviceTest(unittest.TestCase): def setUp(self): self._android_device_stub = system_stub.Override( android_device, ['adb_commands', 'os', 'subprocess', 'logging']) self._apb_stub = system_stub.Override( android_platform_backend, ['adb_commands']) def tearDown(self): self._android_device_stub.Restore() self._apb_stub.Restore() def testNoAdbReturnsNone(self): finder_options = browser_options.BrowserFinderOptions() def NoAdb(*_, **__): raise OSError('not found') self._android_device_stub.subprocess.Popen = NoAdb self.assertEquals([], self._android_device_stub.logging.warnings) self.assertIsNone(android_device.GetDevice(finder_options)) def testAdbNoDevicesReturnsNone(self): finder_options = browser_options.BrowserFinderOptions() self.assertEquals([], self._android_device_stub.logging.warnings) self.assertIsNone(android_device.GetDevice(finder_options)) def testAdbPermissionsErrorReturnsNone(self): finder_options = browser_options.BrowserFinderOptions() self._android_device_stub.subprocess.Popen.communicate_result = ( 'List of devices attached\n????????????\tno permissions\n', '* daemon not running. starting it now on port 5037 *\n' '* daemon started successfully *\n') device = android_device.GetDevice(finder_options) self.assertEquals([ 'adb devices gave a permissions error. Consider running adb as root:', ' adb kill-server', ' sudo `which adb` devices\n\n'], self._android_device_stub.logging.warnings) self.assertIsNone(device) def testAdbTwoDevicesReturnsNone(self): finder_options = browser_options.BrowserFinderOptions() self._android_device_stub.adb_commands.attached_devices = [ '015d14fec128220c', '015d14fec128220d'] device = android_device.GetDevice(finder_options) self.assertEquals([ 'Multiple devices attached. Please specify one of the following:\n' ' --device=015d14fec128220c\n' ' --device=015d14fec128220d'], self._android_device_stub.logging.warnings) self.assertIsNone(device) def testAdbPickOneDeviceReturnsDeviceInstance(self): finder_options = browser_options.BrowserFinderOptions() finder_options.android_device = '555d14fecddddddd' # pick one self._android_device_stub.adb_commands.attached_devices = [ '015d14fec128220c', '555d14fecddddddd'] device = android_device.GetDevice(finder_options) self.assertEquals([], self._android_device_stub.logging.warnings) self.assertEquals('555d14fecddddddd', device.device_id) def testAdbOneDeviceReturnsDeviceInstance(self): finder_options = browser_options.BrowserFinderOptions() self._android_device_stub.adb_commands.attached_devices = ( ['015d14fec128220c']) device = android_device.GetDevice(finder_options) self.assertEquals([], self._android_device_stub.logging.warnings) self.assertEquals('015d14fec128220c', device.device_id)

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0.095573

0.11806

0.582221

0.570625

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0

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0.253165

0

null

0

null

0

1

0

ed7911d27c0fa532add30880dc5c7b6aaf924408

1,265

py

Python

logger.py

bekaaa/xgboost_tuner

2d93f6cc751b3a8778420a88caf73fd1dc8ef2ce

[ "MIT" ]

null

logger.py

bekaaa/xgboost_tuner

2d93f6cc751b3a8778420a88caf73fd1dc8ef2ce

[ "MIT" ]

null

logger.py

bekaaa/xgboost_tuner

2d93f6cc751b3a8778420a88caf73fd1dc8ef2ce

[ "MIT" ]

1

2019-03-16T14:30:07.000Z

#! /usr/bin/env python import logging #--------------------------------------- class logger : ''' A ready to use logging class. All you need to do is set an object with the parameters (log_filename, directory to save it) then whenever you want to add text, type obj.add("some text"). The function obj.close() is not important, I just added it for coverage. You can edit any of the below configuration to whatever you like. ''' def __init__(self, filename, log_dir='../data/log'): self.log = None self.handler = None LOG_PATH = log_dir assert type(filename) == str or filename != '' self.logger = logging.getLogger(); self.logger.setLevel(logging.INFO) filename = LOG_PATH + str(filename) self.handler = logging.FileHandler(filename) self.handler.setLevel(logging.INFO) formatter = logging.Formatter( fmt='%(asctime)s : %(message)s', datefmt='%d-%m %H:%M' ) self.handler.setFormatter(formatter) self.logger.addHandler(self.handler) return #------------------------------------ def add(self, message): assert type(message) == str self.logger.info(message); return #------------------------------------ def close(self): self.logger.removeHandler(self.handler) return #----------------------------------------

31.625

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0

0.307692

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null

0

null

0

1

0

ed79b8872d0353b944045d77a3b550a09342bdbf

5,536

py

Python

baselines/prep_baseline.py

lessleslie/slm-code-generation

017ac0828faf3467e9f85883e27be09ec3898b14

[ "MIT" ]

64

2020-06-23T06:27:42.000Z

2022-03-30T07:44:52.000Z

baselines/prep_baseline.py

lessleslie/slm-code-generation

017ac0828faf3467e9f85883e27be09ec3898b14

[ "MIT" ]

11

2020-07-14T23:29:31.000Z

2021-09-17T15:17:49.000Z

baselines/prep_baseline.py

tech-srl/slm-code-generation

15fe4e1df82e49587f725577f870ca12dc42903a

[ "MIT" ]

6

2020-07-09T08:42:04.000Z

2021-03-02T14:35:31.000Z

import json import multiprocessing as mp import re from argparse import ArgumentParser from enum import Enum, auto import javalang from functools import partial PRED_TOKEN = 'PRED' modifiers = ['public', 'private', 'protected', 'static'] class TargetType(Enum): seq = auto() tree = auto() @staticmethod def from_string(s): try: return TargetType[s] except KeyError: raise ValueError() target_type = TargetType.seq RE_WORDS = re.compile(r''' # Find words in a string. Order matters! [A-Z]+(?=[A-Z][a-z]) | # All upper case before a capitalized word [A-Z]?[a-z]+ | # Capitalized words / all lower case [A-Z]+ | # All upper case \d+ | # Numbers _ | \" | .+ ''', re.VERBOSE) TREE_SPLIT = re.compile(r'([(),])') def split_subtokens(str): return [subtok for subtok in RE_WORDS.findall(str) if not subtok == '_'] def subtokenize(s): failed = False try: tokens = list(javalang.tokenizer.tokenize(s)) except: try: tokens = list(javalang.tokenizer.tokenize(s + '()'))[:-2] except: try: tokens = list(javalang.tokenizer.tokenize('(' + s + ')'))[1:-1] except: tokens = s.split() failed = True if failed: return [' _ '.join(split_subtokens(i)) for i in tokens if not i in modifiers] else: return [' _ '.join(split_subtokens(i.value)) for i in tokens if not i.value in modifiers] def subtokenize_tree(s): return ' '.join([sub for sub in re.split(TREE_SPLIT, s) if len(sub) > 0]) def process_line(target_type, max_targets, max_nodes, line): obj = json.loads(line) left_context = obj['left_context'] right_context = obj['right_context'] target_seq = obj['target_seq'] num_targets = obj['num_targets'] num_nodes = obj['num_nodes'] if max_targets is not None and num_targets > max_targets: return None, None if max_nodes is not None and num_nodes > max_nodes: return None, None if target_type is TargetType.seq: target_pred = ' '.join(subtokenize(target_seq)).lower() elif target_type is TargetType.tree: target_pred = subtokenize_tree(obj['linearized_tree']) source = '{} {} {}'.format(' '.join(subtokenize(left_context)[-200:]).lower(), PRED_TOKEN, ' '.join(subtokenize(right_context)[:200]).lower()) return source, target_pred def process_file(file_path, data_file_role, dataset_name, target_type, max_targets, max_nodes): total_examples = 0 source_output_path = '{}.{}.{}.source.txt'.format(dataset_name, target_type, data_file_role) target_output_path = '{}.{}.{}.target.txt'.format(dataset_name, target_type, data_file_role) with open(source_output_path, 'w') as source_output_file: with open(target_output_path, 'w') as target_output_file: with open(file_path, 'r') as file: subtokenize_line = partial(process_line, target_type, max_targets, max_nodes) with mp.Pool(64) as pool: if data_file_role in ['test', 'val']: examples = [process_line(target_type, max_targets, max_nodes, line) for line in file] else: examples = pool.imap_unordered(subtokenize_line, file, chunksize=100) #examples = [process_line(target_type, max_targets, max_nodes, line) for line in file] for source_seq, target_seq in examples: if source_seq is None or target_seq is None: continue source_output_file.write(source_seq + '\n') target_output_file.write(target_seq + '\n') total_examples += 1 #print(source_seq, target_seq) print('File: ' + file_path) print('Total examples: ' + str(total_examples)) if __name__ == '__main__': parser = ArgumentParser() parser.add_argument("-trd", "--train_data", dest="train_data_path", help="path to training data file", required=True) parser.add_argument("-ted", "--test_data", dest="test_data_path", help="path to test data file", required=True) parser.add_argument("-vd", "--val_data", dest="val_data_path", help="path to validation data file", required=True) parser.add_argument("-o", "--output_name", dest="output_name", help="output name - the base name for the created dataset", metavar="FILE", required=True, default='data') parser.add_argument("--target_type", dest="target_type", type=TargetType.from_string, choices=list(TargetType), required=True) parser.add_argument("--max_targets", dest="max_targets", type=int, required=False, default=40) parser.add_argument("--max_nodes", dest="max_nodes", type=int, required=False, default=None) parser.add_argument('--local', action='store_true') args = parser.parse_args() train_data_path = args.train_data_path test_data_path = args.test_data_path val_data_path = args.val_data_path for data_file_path, data_role in zip([train_data_path, test_data_path, val_data_path], ['train', 'test', 'val']): process_file(file_path=data_file_path, data_file_role=data_role, dataset_name=args.output_name, target_type=args.target_type, max_targets=args.max_targets, max_nodes=args.max_nodes)

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0.04115

0.036309

0.302874

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0.077156

0.038729

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0.248013

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40.705882

0.789335

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0.054054

false

0

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0.216216

0.018018

0

null

0

null

0

1

0

ed7d572858561992a56ab8312f08925dad1d2745

6,260

py

Python

ebay.py

SpironoZeppeli/Magic-The-Scannening

93c595a4c98fb725a79eeddfaba99cb0409d41fb

[ "MIT" ]

null

ebay.py

SpironoZeppeli/Magic-The-Scannening

93c595a4c98fb725a79eeddfaba99cb0409d41fb

[ "MIT" ]

null

ebay.py

SpironoZeppeli/Magic-The-Scannening

93c595a4c98fb725a79eeddfaba99cb0409d41fb

[ "MIT" ]

null

import requests import urllib.request import urllib.parse import PIL import re import configparser import json from PIL import Image from ebaysdk.trading import Connection as Trading from ebaysdk.exception import ConnectionError from yaml import load from PyQt5.QtWidgets import QMessageBox class EbaySeller: def __init__(self): self.api = Trading() config = configparser.ConfigParser() config.read('config.ini') with open('details.yaml', 'r') as file: self.yaml_config = load(file) def upload_card(self, card_name, eu_card_price, us_card_price, card_id): if us_card_price != 0: card_price = us_card_price * 0.8 else: card_price = eu_card_price if card_price < 1: card_price = 1 card_price = str(round(card_price, 2)) try: card_image = 'http://gatherer.wizards.com/Handlers/Image.ashx?multiverseid=' + card_id + '&type=card' except: self.msg = QMessageBox() self.msg.setWindowTitle("Upload Failed") self.msg.setText("Upload Failed, wizards gatherer error") self.msg.setStandardButtons(QMessageBox.Ok) self.msg.exec() urllib.request.urlretrieve(card_image, 'temp.jpg') # Resize card base_height = 500 img = Image.open('temp.jpg') height_percent = (base_height / float(img.size[1])) wsize = int((float(img.size[0]) * float(height_percent))) img = img.resize((wsize, base_height), PIL.Image.ANTIALIAS) img.save('temp.png') # Upload to PictShare files = {'file': open('temp.png', 'rb')} try: r = requests.post('https://pictshare.net/api/upload.php', files=files) except: self.msg = QMessageBox() self.msg.setWindowTitle("Upload Failed") self.msg.setText("Upload Failed, PictShare error") self.msg.setStandardButtons(QMessageBox.Ok) self.msg.exec() print(r) r = r.text r = json.loads(r) print(r) r = r['url'] # Fix using regular expression, may not be needed at a later date r = re.sub('\\.net', '.net/', r) r = re.sub('\\.net//', '.net/', r) print(r) try: image = self.api.execute('UploadSiteHostedPictures', {'ExternalPictureURL': r}) image = image.dict() image = image['SiteHostedPictureDetails']['FullURL'] print(image) # Upload to ebay response = self.api.execute('AddFixedPriceItem', { 'Item': {'Title': card_name + ' MTG - NM/M', 'Description': card_name + ' MTG - NM/M', 'Quantity': '1', 'PictureDetails': {'PictureURL': image}, 'ReturnPolicy': {'ReturnsAcceptedOption': 'ReturnsNotAccepted'}, 'DispatchTimeMax': '3', 'ConditionID': '1000', 'StartPrice': card_price, 'PostalCode': self.yaml_config["PostalCode"], 'Currency': self.yaml_config["Currency"], 'Country': 'GB', 'ListingDuration': 'Days_30', 'PaymentMethods': 'PayPal', 'PayPalEmailAddress': self.yaml_config["PayPalEmailAddress"], 'PrimaryCategory': {'CategoryID': '38292'}, 'ShippingDetails': {'ShippingType': 'Flat', 'ShippingServiceOptions': {'ShippingServicePriority': '1', 'ShippingService': self.yaml_config[ "ShippingService"], 'ShippingServiceCost': '1'}}}}) print(response.dict()) print(response.reply) self.msg = QMessageBox() if response.reply.Ack == 'Failure': self.msg.setWindowTitle("Upload Failed") self.msg.setText("Upload Complete, please check log.txt") self.msg.setStandardButtons(QMessageBox.Ok) with open('log.txt', 'a+') as log_file: log_file.write(response.reply) else: self.msg.setWindowTitle("Upload Complete") self.msg.setText("Upload Complete, please check your ebay account to confirm") self.msg.setStandardButtons(QMessageBox.Ok) self.msg.exec() except ConnectionError as e: print(e) print(e.response.dict()) def get_multiverse_id(self, name): try: name = re.sub(' ', '%20', name) r = requests.get('https://api.scryfall.com/cards/named?exact=' + name) r = json.loads(r.text) return r['multiverse_ids'][0] except: self.msg = QMessageBox() self.msg.setWindowTitle("Upload Failed") self.msg.setText("Upload Failed, scryfall error") self.msg.setStandardButtons(QMessageBox.Ok) self.msg.exec() def get_card_info_and_sell(self, name): try: multiverse_id = self.get_multiverse_id(name) r = requests.get('http://api.cardsearch.nl/v1/prices?key=W00dw0rk$&mids[]=' + str(multiverse_id)) r = json.loads(r.text) r = r[0] card_name = r.get('name') eu_card_price = r.get('price_normal') us_card_price = r.get('us_normal') card_set = r.get('set_id') card_set_name = r.get('set_name') card_id = r.get('multiverse_id') # Display card info in CLI print('Name: ' + card_name) print('Set: ' + card_set) print('Set name: ' + card_set_name) print('Card ID: ' + str(card_id)) self.upload_card(card_name, eu_card_price, us_card_price, card_id) except: self.msg = QMessageBox() self.msg.setWindowTitle("Upload Failed") self.msg.setText("Upload Failed, card name not valid") self.msg.setStandardButtons(QMessageBox.Ok) self.msg.exec()

42.013423

119

0.546486

657

6,260

5.086758

0.295282

0.058648

0.037702

0.048474

0.283064

0.239677

0.231897

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0.185218

0.120886

0

0.008375

0.332428

6,260

148

120

42.297297

0.791338

0.021566

0

0.284615

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0.204609

0.018631

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0.030769

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0.092308

0

null

0

null

0

1

0

ed7de0c98f16f1e656d840a2c9ad1e60a28cfa7f

3,175

py

Python

bot/exts/github/github.py

v1nam/gurkbot

a0f5e05a5f65e6169accc90271fca58f4df211fe

[ "MIT" ]

24

2020-12-18T07:26:14.000Z

2022-03-30T22:56:49.000Z

bot/exts/github/github.py

v1nam/gurkbot

a0f5e05a5f65e6169accc90271fca58f4df211fe

[ "MIT" ]

143

2020-12-18T09:13:51.000Z

2022-03-02T19:27:44.000Z

bot/exts/github/github.py

v1nam/gurkbot

a0f5e05a5f65e6169accc90271fca58f4df211fe

[ "MIT" ]

44

2020-12-18T09:05:29.000Z

2022-03-02T20:06:23.000Z

import typing from bot.constants import BOT_REPO_URL from discord import Embed from discord.ext import commands from discord.ext.commands.cooldowns import BucketType from . import _issues, _profile, _source class Github(commands.Cog): """ Github Category cog, which contains commands related to github. Commands: ├ profile Fetches a user's GitHub information. ├ issue Command to retrieve issue(s) from a GitHub repository. └ source Displays information about the bot's source code. """ def __init__(self, bot: commands.Bot) -> None: self.bot = bot @commands.group(name="github", aliases=("gh",), invoke_without_command=True) async def github_group(self, ctx: commands.Context) -> None: """Commands for Github.""" await ctx.send_help(ctx.command) @github_group.command(name="profile") @commands.cooldown(1, 10, BucketType.user) async def profile(self, ctx: commands.Context, username: str) -> None: """ Fetches a user's GitHub information. Username is optional and sends the help command if not specified. """ github_profile = _profile.GithubInfo(self.bot.http_session) embed = await github_profile.get_github_info(username) await ctx.send(embed=embed) @github_group.command(name="issue", aliases=("pr",)) async def issue( self, ctx: commands.Context, numbers: commands.Greedy[int], repository: typing.Optional[str] = None, ) -> None: """Command to retrieve issue(s) from a GitHub repository.""" github_issue = _issues.Issues(self.bot.http_session) if not numbers: raise commands.MissingRequiredArgument(ctx.command.clean_params["numbers"]) if repository is None: user = "gurkult" else: user, _, repository = repository.rpartition("/") if user == "": user = "gurkult" embed = await github_issue.issue(ctx.message.channel, numbers, repository, user) await ctx.send(embed=embed) @github_group.command(name="source", aliases=("src", "inspect")) async def source_command( self, ctx: commands.Context, *, source_item: typing.Optional[str] = None ) -> None: """Displays information about the bot's source code.""" if source_item is None: embed = Embed(title="Gurkbot's GitHub Repository") embed.add_field(name="Repository", value=f"[Go to GitHub]({BOT_REPO_URL})") embed.set_thumbnail(url=self.bot.user.avatar_url) await ctx.send(embed=embed) return elif not ctx.bot.get_command(source_item): raise commands.BadArgument( f"Unable to convert `{source_item}` to valid command or Cog." ) github_source = _source.Source(self.bot.http_session, self.bot.user.avatar_url) embed = await github_source.inspect(cmd=ctx.bot.get_command(source_item)) await ctx.send(embed=embed) def setup(bot: commands.Bot) -> None: """Load the Github cog.""" bot.add_cog(Github(bot))

34.89011

88

0.640945

391

3,175

5.092072

0.28133

0.024611

0.030136

0.044199

0.253139

0.185836

0.129583

0.088398

0

0.001258

0.249134

3,175

90

89

35.277778

0.832634

0.093543

0

0.145455

0

0.072125

0.008967

0

1

0.036364

false

0

0.109091

0

0.181818

0

null

0

null

0

1

0

ed7de7f5235ff8dd0c5f7e122b59415ab3622dc6

1,154

py

Python

log/slack_sender.py

SmashKs/BarBarian

b308dcb9e24ec621abbbc121847923e14e5b6a4b

[ "MIT" ]

null

log/slack_sender.py

SmashKs/BarBarian

b308dcb9e24ec621abbbc121847923e14e5b6a4b

[ "MIT" ]

2

2020-06-05T19:25:24.000Z

2021-06-10T20:56:57.000Z

log/slack_sender.py

SmashKs/BarBarian

b308dcb9e24ec621abbbc121847923e14e5b6a4b

[ "MIT" ]

null

from slackclient import SlackClient from external import SLACK_API_KEY class SlackBot: API_CHAT_MSG = 'chat.postMessage' BOT_NAME = 'News Bot' DEFAULT_CHANNEL = 'news_notification' def __new__(cls, *p, **k): if '_the_instance' not in cls.__dict__: cls._the_instance = object.__new__(cls) return cls._the_instance def __init__(self): self.__slack_client = SlackClient(SLACK_API_KEY) def send_msg_to(self, text='', channel=DEFAULT_CHANNEL): self.__slack_client.api_call(SlackBot.API_CHAT_MSG, username=SlackBot.BOT_NAME, channel=channel, text=text) def send_formatted_msg_to(self, text='', channel=DEFAULT_CHANNEL): self.__slack_client.api_call(SlackBot.API_CHAT_MSG, username=SlackBot.BOT_NAME, mrkdwn=True, channel=channel, text=text) if __name__ == '__main__': SlackBot().send_msg_to('hello world!!')

32.971429

70

0.559792

121

1,154

4.801653

0.371901

0.056799

0.077453

0.092943

0.333907

0

0.358752

1,154

34

71

33.941176

0.785135

0

0.32

0

0.064991

0

1

0.16

false

0

0.08

0

0.44

0

null

0

null

0

1

0

ed7e4d3da4d7bdad5eca61e8c5160dfe0d14608f

2,379

py

Python

src/pytezos/block/forge.py

miracle2k/pytezos

e6b99f00f342d9a05b0c36a9883040961fd6d58e

[ "MIT" ]

98

2019-02-07T16:33:38.000Z

2022-03-31T15:53:41.000Z

src/pytezos/block/forge.py

miracle2k/pytezos

e6b99f00f342d9a05b0c36a9883040961fd6d58e

[ "MIT" ]

152

2019-05-20T16:38:56.000Z

2022-03-30T14:24:38.000Z

src/pytezos/block/forge.py

miracle2k/pytezos

e6b99f00f342d9a05b0c36a9883040961fd6d58e

[ "MIT" ]

34

2019-07-25T12:03:51.000Z

2021-11-11T22:23:38.000Z

from typing import Any, Dict, List, Tuple from pytezos.michelson.forge import forge_array, forge_base58, optimize_timestamp def bump_fitness(fitness: Tuple[str, str]) -> Tuple[str, str]: if len(fitness) == 0: major = 0 minor = 1 else: major = int.from_bytes(bytes.fromhex(fitness[0]), 'big') minor = int.from_bytes(bytes.fromhex(fitness[1]), 'big') + 1 return major.to_bytes(1, 'big').hex(), minor.to_bytes(8, 'big').hex() def forge_int_fixed(value: int, length: int) -> bytes: return value.to_bytes(length, 'big') def forge_command(command: str) -> bytes: if command == 'activate': return b'\x00' raise NotImplementedError(command) def forge_fitness(fitness: List[str]) -> bytes: return forge_array(b''.join(map(lambda x: forge_array(bytes.fromhex(x)), fitness))) def forge_priority(priority: int) -> bytes: return priority.to_bytes(2, 'big') def forge_content(content: Dict[str, Any]) -> bytes: res = b'' res += forge_command(content['command']) res += forge_base58(content['hash']) res += forge_fitness(content['fitness']) res += bytes.fromhex(content['protocol_parameters']) return res def forge_protocol_data(protocol_data: Dict[str, Any]) -> bytes: res = b'' if protocol_data.get('content'): res += forge_content(protocol_data['content']) else: res += forge_priority(protocol_data['priority']) res += bytes.fromhex(protocol_data['proof_of_work_nonce']) if protocol_data.get('seed_nonce_hash'): res += b'\xFF' res += forge_base58(protocol_data['seed_nonce_hash']) else: res += b'\x00' res += b'\xFF' if protocol_data['liquidity_baking_escape_vote'] else b'\x00' return res def forge_block_header(shell_header: Dict[str, Any]) -> bytes: res = forge_int_fixed(shell_header['level'], 4) res += forge_int_fixed(shell_header['proto'], 1) res += forge_base58(shell_header['predecessor']) res += forge_int_fixed(optimize_timestamp(shell_header['timestamp']), 8) res += forge_int_fixed(shell_header['validation_pass'], 1) res += forge_base58(shell_header['operations_hash']) res += forge_fitness(shell_header['fitness']) res += forge_base58(shell_header['context']) res += bytes.fromhex(shell_header['protocol_data']) return res

33.985714

87

0.666246

320

2,379

4.725

0.2375

0.074074

0.042989

0.042328

0.180556

0.154101

0

0.016021

0.186633

2,379

69

88

34.478261

0.765375

0

0.153846

0

0.113073

0.01177

0

1

0.153846

false

0.019231

0.038462

0.057692

0.346154

0

null

0

null

0

1

0

ed7f467835f32242a9650f226b4a5ad9d6d87af4

5,321

py

Python

python/paddle/fluid/tests/unittests/test_roi_pool_op.py

jichangjichang/Paddle

4fa3cee5499c6df0ad6043b0cfa220d09f2034e8

[ "Apache-2.0" ]

9

2017-12-04T02:58:01.000Z

2020-12-03T14:46:30.000Z

python/paddle/fluid/tests/unittests/test_roi_pool_op.py

jichangjichang/Paddle

4fa3cee5499c6df0ad6043b0cfa220d09f2034e8

[ "Apache-2.0" ]

7

2017-12-05T20:29:08.000Z

2018-10-15T08:57:40.000Z

python/paddle/fluid/tests/unittests/test_roi_pool_op.py

jichangjichang/Paddle

4fa3cee5499c6df0ad6043b0cfa220d09f2034e8

[ "Apache-2.0" ]

6

2018-03-19T22:38:46.000Z

2019-11-01T22:28:27.000Z

# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved. # # 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 __future__ import print_function import unittest import numpy as np import math import sys import paddle.compat as cpt from op_test import OpTest class TestROIPoolOp(OpTest): def set_data(self): self.init_test_case() self.make_rois() self.calc_roi_pool() self.inputs = {'X': self.x, 'ROIs': (self.rois[:, 1:5], self.rois_lod)} self.attrs = { 'spatial_scale': self.spatial_scale, 'pooled_height': self.pooled_height, 'pooled_width': self.pooled_width } self.outputs = {'Out': self.outs, 'Argmax': self.argmaxes} def init_test_case(self): self.batch_size = 3 self.channels = 3 self.height = 6 self.width = 4 # n, c, h, w self.x_dim = (self.batch_size, self.channels, self.height, self.width) self.spatial_scale = 1.0 / 4.0 self.pooled_height = 2 self.pooled_width = 2 self.x = np.random.random(self.x_dim).astype('float32') def calc_roi_pool(self): out_data = np.zeros((self.rois_num, self.channels, self.pooled_height, self.pooled_width)) argmax_data = np.zeros((self.rois_num, self.channels, self.pooled_height, self.pooled_width)) for i in range(self.rois_num): roi = self.rois[i] roi_batch_id = roi[0] roi_start_w = int(cpt.round(roi[1] * self.spatial_scale)) roi_start_h = int(cpt.round(roi[2] * self.spatial_scale)) roi_end_w = int(cpt.round(roi[3] * self.spatial_scale)) roi_end_h = int(cpt.round(roi[4] * self.spatial_scale)) roi_height = int(max(roi_end_h - roi_start_h + 1, 1)) roi_width = int(max(roi_end_w - roi_start_w + 1, 1)) x_i = self.x[roi_batch_id] bin_size_h = float(roi_height) / float(self.pooled_height) bin_size_w = float(roi_width) / float(self.pooled_width) for c in range(self.channels): for ph in range(self.pooled_height): for pw in range(self.pooled_width): hstart = int(math.floor(ph * bin_size_h)) wstart = int(math.floor(pw * bin_size_w)) hend = int(math.ceil((ph + 1) * bin_size_h)) wend = int(math.ceil((pw + 1) * bin_size_w)) hstart = min(max(hstart + roi_start_h, 0), self.height) hend = min(max(hend + roi_start_h, 0), self.height) wstart = min(max(wstart + roi_start_w, 0), self.width) wend = min(max(wend + roi_start_w, 0), self.width) is_empty = (hend <= hstart) or (wend <= wstart) if is_empty: out_data[i, c, ph, pw] = 0 else: out_data[i, c, ph, pw] = -sys.float_info.max argmax_data[i, c, ph, pw] = -1 for h in range(hstart, hend): for w in range(wstart, wend): if x_i[c, h, w] > out_data[i, c, ph, pw]: out_data[i, c, ph, pw] = x_i[c, h, w] argmax_data[i, c, ph, pw] = h * self.width + w self.outs = out_data.astype('float32') self.argmaxes = argmax_data.astype('int64') def make_rois(self): rois = [] self.rois_lod = [[]] for bno in range(self.batch_size): self.rois_lod[0].append(bno + 1) for i in range(bno + 1): x1 = np.random.random_integers( 0, self.width // self.spatial_scale - self.pooled_width) y1 = np.random.random_integers( 0, self.height // self.spatial_scale - self.pooled_height) x2 = np.random.random_integers(x1 + self.pooled_width, self.width // self.spatial_scale) y2 = np.random.random_integers( y1 + self.pooled_height, self.height // self.spatial_scale) roi = [bno, x1, y1, x2, y2] rois.append(roi) self.rois_num = len(rois) self.rois = np.array(rois).astype("int64") def setUp(self): self.op_type = "roi_pool" self.set_data() def test_check_output(self): self.check_output() def test_check_grad(self): self.check_grad(['X'], 'Out') if __name__ == '__main__': unittest.main()

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0

null

0

null

0

1

0

ed801190784fa836d2752af1e6b10b54a93fa361

2,518

py

Python

Day20.py

SheepiCagio/Advent-of-Code-2021

52f0035da2cb258810d8947cbf56b51b65a9fe8b

[ "MIT" ]

null

Day20.py

SheepiCagio/Advent-of-Code-2021

52f0035da2cb258810d8947cbf56b51b65a9fe8b

[ "MIT" ]

null

Day20.py

SheepiCagio/Advent-of-Code-2021

52f0035da2cb258810d8947cbf56b51b65a9fe8b

[ "MIT" ]

null

import numpy as np raw = open("inputs/20.txt","r").readlines() input_array= [(i.replace('\n', '').replace('.','0').replace('#', '1')) for i in raw] test_raw = open("inputs/20_test.txt","r").readlines() test_array= [(i.replace('\n', '').replace('.','0').replace('#', '1')) for i in test_raw] def addLayerZero(grid): #if sum(np.asarray(grid)[:,0]) > 0: grid = np.hstack((np.zeros(len(grid), dtype=int)[:, np.newaxis],grid)) #if sum(np.asarray(grid)[0,:]) > 0: grid = np.vstack((np.zeros(len(grid[0]), dtype=int)[np.newaxis,:],grid)) # if sum(np.asarray(grid)[:,-1]) > 0: grid = np.hstack((grid,np.zeros(len(grid), dtype=int)[:, np.newaxis])) # if sum(np.asarray(grid)[-1,:]) > 0: grid = np.vstack((grid, np.zeros(len(grid[0]), dtype=int)[np.newaxis,:])) return grid def addLayerOnes(grid): #if sum(np.asarray(grid)[:,0]) > 0: grid = np.hstack((np.ones(len(grid), dtype=int)[:, np.newaxis],grid)) #if sum(np.asarray(grid)[0,:]) > 0: grid = np.vstack((np.ones(len(grid[0]), dtype=int)[np.newaxis,:],grid)) # if sum(np.asarray(grid)[:,-1]) > 0: grid = np.hstack((grid,np.ones(len(grid), dtype=int)[:, np.newaxis])) # if sum(np.asarray(grid)[-1,:]) > 0: grid = np.vstack((grid, np.ones(len(grid[0]), dtype=int)[np.newaxis,:])) return grid def pictureEnhancer(input_array,iter): splitvalue = False index_string = '' grid = [] for i in input_array: if i == '': splitvalue = True continue if not splitvalue: index_string += i else: grid.append(list(i)) grid = [[int(i) for i in row] for row in grid] for x in range(1,iter+1): grid = enhancer(grid, index_string,x) print('The number of lit pixels is:', sum(sum(grid))) def enhancer(grid, index_string,iter): print(iter) if iter == 1 or index_string[0] == '0' or (iter % 2 == 1 and index_string[511] == '0'): grid = addLayerZero(grid) output_grid = np.zeros((len(grid),len(grid[0])),dtype=int) grid = addLayerZero(grid) elif (index_string[0] == '1' and index_string [511] == '1') or (iter % 2 == 0 and index_string[511] == '0'): grid = addLayerOnes(grid) output_grid = np.ones((len(grid),len(grid[0])),dtype=int) grid = addLayerOnes(grid) for i in range(1,len(grid)-1): for j in range(1, len(grid[i])-1): binStr = '' for k in range(-1,2): for l in range(-1,2): binStr += str(grid[i+k][j+l]) output_grid[i-1][j-1] = index_string[int(binStr,2)] return output_grid #pictureEnhancer(test_array,2) #pictureEnhancer(input_array,2) pictureEnhancer(test_array,50) pictureEnhancer(input_array,50)

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2,518

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null

0

null

0

1

0

ed8134024179e7e4607f23c5ef95e9da1da3820b

1,674

py

Python

questions/53349623/main.py

sesu089/stackoverflow

6fae69be6fa74fba9d554e6b5f387e5d3c1aad73

[ "MIT" ]

302

2017-03-04T00:05:23.000Z

2022-03-28T22:51:29.000Z

questions/53349623/main.py

sesu089/stackoverflow

6fae69be6fa74fba9d554e6b5f387e5d3c1aad73

[ "MIT" ]

30

2017-12-02T19:26:43.000Z

2022-03-28T07:40:36.000Z

questions/53349623/main.py

sesu089/stackoverflow

6fae69be6fa74fba9d554e6b5f387e5d3c1aad73

[ "MIT" ]

388

2017-07-04T16:53:12.000Z

2022-03-18T22:20:19.000Z

import sys from PyQt5 import QtCore, QtGui, QtWidgets class Demo(QtWidgets.QWidget): def __init__(self): super(Demo, self).__init__() self.button = QtWidgets.QPushButton() self.label = QtWidgets.QLabel(alignment=QtCore.Qt.AlignCenter) self.combo = QtWidgets.QComboBox(self) self.combo.currentIndexChanged.connect(self.change_func) self.trans = QtCore.QTranslator(self) self.v_layout = QtWidgets.QVBoxLayout(self) self.v_layout.addWidget(self.combo) self.v_layout.addWidget(self.button) self.v_layout.addWidget(self.label) options = ([('English', ''), ('français', 'eng-fr' ), ('中文', 'eng-chs'), ]) for i, (text, lang) in enumerate(options): self.combo.addItem(text) self.combo.setItemData(i, lang) self.retranslateUi() @QtCore.pyqtSlot(int) def change_func(self, index): data = self.combo.itemData(index) if data: self.trans.load(data) QtWidgets.QApplication.instance().installTranslator(self.trans) else: QtWidgets.QApplication.instance().removeTranslator(self.trans) def changeEvent(self, event): if event.type() == QtCore.QEvent.LanguageChange: self.retranslateUi() super(Demo, self).changeEvent(event) def retranslateUi(self): self.button.setText(QtWidgets.QApplication.translate('Demo', 'Start')) self.label.setText(QtWidgets.QApplication.translate('Demo', 'Hello, World')) if __name__ == '__main__': app = QtWidgets.QApplication(sys.argv) demo = Demo() demo.show() sys.exit(app.exec_())

32.823529

84

0.642772

183

1,674

5.754098

0.42623

0.051282

0.041785

0.05698

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0.224612

1,674

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0.179487

0

null

0

null

0

1

0

ed81492b65a1f232ede7d038b4670a415f3f191c

1,638

py

Python

tests/test_error_descriptions_from_raises.py

iterait/apistrap

e83460fa97f13a95a928971b0d2defe0ac611911

[ "MIT" ]

6

2018-09-06T18:32:48.000Z

2021-05-28T01:03:32.000Z

tests/test_error_descriptions_from_raises.py

iterait/apistrap

e83460fa97f13a95a928971b0d2defe0ac611911

[ "MIT" ]

53

2018-09-06T16:16:53.000Z

2021-05-19T14:36:58.000Z

tests/test_error_descriptions_from_raises.py

iterait/apistrap

e83460fa97f13a95a928971b0d2defe0ac611911

[ "MIT" ]

null

import pytest from apistrap.flask import FlaskApistrap from apistrap.schemas import ErrorResponse @pytest.fixture() def app_with_raises(app): oapi = FlaskApistrap() @app.route("/", methods=["GET"]) def view(): """ Something something. :raises KeyError: KeyError description """ oapi.init_app(app) @pytest.fixture() def app_with_raises_and_handler(app): oapi = FlaskApistrap() oapi.add_error_handler(KeyError, 515, lambda e: ErrorResponse()) @app.route("/", methods=["GET"]) def view(): """ Something something. :raises KeyError: KeyError description """ oapi.init_app(app) def test_error_descriptions_from_raises(app_with_raises, client): response = client.get("/spec.json") assert response.json["paths"]["/"]["get"]["responses"] == { "500": { "description": "KeyError description", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ErrorResponse" } } } } } def test_http_code_from_handler(app_with_raises_and_handler, client): response = client.get("/spec.json") assert response.json["paths"]["/"]["get"]["responses"] == { "515": { "description": "KeyError description", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ErrorResponse" } } } } }

23.4

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0.333333

1,638

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0.760989

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0

0.204545

0

null

0

null

0

1

0

ed82dc9fed173aeada3cbab76076165a4c9b3932

1,126

py

Python

projects/api/UsersApi.py

chamathshashika/projects-python-wrappers

33e9f6bccba16a581b115c582033a93d43bb159c

[ "MIT" ]

null

projects/api/UsersApi.py

chamathshashika/projects-python-wrappers

33e9f6bccba16a581b115c582033a93d43bb159c

[ "MIT" ]

null

projects/api/UsersApi.py

chamathshashika/projects-python-wrappers

33e9f6bccba16a581b115c582033a93d43bb159c

[ "MIT" ]

null

#$Id$ from projects.util.ZohoHttpClient import ZohoHttpClient from projects.api.Api import Api from projects.parser.UsersParser import UsersParser base_url = Api().base_url zoho_http_client = ZohoHttpClient() parser = UsersParser() class UsersApi: """Users Api class is used to 1.Get all the users in the given project. """ def __init__(self, authtoken, portal_id): """Initialize Users api using user's authtoken and portal id. Args: authtoken(str): User's authtoken. portal_id(str): User's portal id. """ self.details = { 'authtoken': authtoken } self.portal_id = portal_id def get_users(self, project_id): """Get all the users in the given project. Args: project_id(long): Project id. Returns: list of instance: List of users object. """ url = base_url + 'portal/' + str(self.portal_id) + '/projects/' + str(project_id) + '/users/' response = zoho_http_client.get(url, self.details) return parser.get_users(response)

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null

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null

0

1

0

ed82e608ff9e5d51a3d3e7cab08afa27210afbdb

11,340

py

Python

useless/tuck_arms.py

leader1313/Baxter_teleoperation_system

856d999acd73e6c1dc15a342cb6c4fcd1a482863

[ "Apache-2.0" ]

null

useless/tuck_arms.py

leader1313/Baxter_teleoperation_system

856d999acd73e6c1dc15a342cb6c4fcd1a482863

[ "Apache-2.0" ]

2

2019-10-15T07:24:24.000Z

2019-10-15T07:28:19.000Z

useless/tuck_arms.py

leader1313/Baxter_teleoperation_system

856d999acd73e6c1dc15a342cb6c4fcd1a482863

[ "Apache-2.0" ]

1

2020-09-15T12:37:13.000Z

#!/usr/bin/env python # Copyright (c) 2013-2015, Rethink Robotics # 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. # 3. Neither the name of the Rethink Robotics nor the names of its # contributors may be used to endorse or promote products derived from # this software without specific prior written permission. # # 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 OWNER 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. """ Tool to tuck/untuck Baxter's arms to/from the shipping pose """ import argparse from copy import deepcopy import rospy from std_msgs.msg import ( Empty, Bool, ) import baxter_interface from baxter_core_msgs.msg import ( CollisionAvoidanceState, ) from baxter_interface import CHECK_VERSION class Tuck(object): def __init__(self, tuck_cmd): self._done = False self._limbs = ('left', 'right') self._arms = { 'left': baxter_interface.Limb('left'), 'right': baxter_interface.Limb('right'), } self._tuck = tuck_cmd self._tuck_rate = rospy.Rate(20.0) # Hz self._tuck_threshold = 0.2 # radians self._peak_angle = -1.6 # radians self._arm_state = { 'tuck': {'left': 'none', 'right': 'none'}, 'collide': {'left': False, 'right': False}, 'flipped': {'left': False, 'right': False} } self._joint_moves = { 'tuck': { 'left': [-1.0, -2.07, 3.0, 2.55, 0.0, 0.01, 0.0], 'right': [1.0, -2.07, -3.0, 2.55, -0.0, 0.01, 0.0] }, 'untuck': { 'left': [-0.08, -1.0, -1.19, 1.94, 0.67, 1.03, -0.50], 'right': [0.08, -1.0, 1.19, 1.94, -0.67, 1.03, 0.50] } } self._collide_lsub = rospy.Subscriber( 'robot/limb/left/collision_avoidance_state', CollisionAvoidanceState, self._update_collision, 'left') self._collide_rsub = rospy.Subscriber( 'robot/limb/right/collision_avoidance_state', CollisionAvoidanceState, self._update_collision, 'right') self._disable_pub = { 'left': rospy.Publisher( 'robot/limb/left/suppress_collision_avoidance', Empty, queue_size=10), 'right': rospy.Publisher( 'robot/limb/right/suppress_collision_avoidance', Empty, queue_size=10) } self._rs = baxter_interface.RobotEnable(CHECK_VERSION) self._enable_pub = rospy.Publisher('robot/set_super_enable', Bool, queue_size=10) def _update_collision(self, data, limb): self._arm_state['collide'][limb] = len(data.collision_object) > 0 self._check_arm_state() def _check_arm_state(self): """ Check for goals and behind collision field. If s1 joint is over the peak, collision will need to be disabled to get the arm around the head-arm collision force-field. """ diff_check = lambda a, b: abs(a - b) <= self._tuck_threshold for limb in self._limbs: angles = [self._arms[limb].joint_angle(joint) for joint in self._arms[limb].joint_names()] # Check if in a goal position untuck_goal = map(diff_check, angles, self._joint_moves['untuck'][limb]) tuck_goal = map(diff_check, angles[0:2], self._joint_moves['tuck'][limb][0:2]) if all(untuck_goal): self._arm_state['tuck'][limb] = 'untuck' elif all(tuck_goal): self._arm_state['tuck'][limb] = 'tuck' else: self._arm_state['tuck'][limb] = 'none' # Check if shoulder is flipped over peak self._arm_state['flipped'][limb] = ( self._arms[limb].joint_angle(limb + '_s1') <= self._peak_angle) def _prepare_to_tuck(self): # If arms are in "tucked" state, disable collision avoidance # before enabling robot, to avoid arm jerking from "force-field". head = baxter_interface.Head() start_disabled = not self._rs.state().enabled at_goal = lambda: (abs(head.pan()) <= baxter_interface.settings.HEAD_PAN_ANGLE_TOLERANCE) rospy.loginfo("Moving head to neutral position") while not at_goal() and not rospy.is_shutdown(): if start_disabled: [pub.publish(Empty()) for pub in self._disable_pub.values()] if not self._rs.state().enabled: self._enable_pub.publish(True) head.set_pan(0.0, 0.5, timeout=0) self._tuck_rate.sleep() if start_disabled: while self._rs.state().enabled == True and not rospy.is_shutdown(): [pub.publish(Empty()) for pub in self._disable_pub.values()] self._enable_pub.publish(False) self._tuck_rate.sleep() def _move_to(self, tuck, disabled): if any(disabled.values()): [pub.publish(Empty()) for pub in self._disable_pub.values()] while (any(self._arm_state['tuck'][limb] != goal for limb, goal in tuck.viewitems()) and not rospy.is_shutdown()): if self._rs.state().enabled == False: self._enable_pub.publish(True) for limb in self._limbs: if disabled[limb]: self._disable_pub[limb].publish(Empty()) if limb in tuck: self._arms[limb].set_joint_positions(dict(zip( self._arms[limb].joint_names(), self._joint_moves[tuck[limb]][limb]))) self._check_arm_state() self._tuck_rate.sleep() if any(self._arm_state['collide'].values()): self._rs.disable() return def supervised_tuck(self): # Update our starting state to check if arms are tucked self._prepare_to_tuck() self._check_arm_state() # Tuck Arms if self._tuck == True: # If arms are already tucked, report this to user and exit. if all(self._arm_state['tuck'][limb] == 'tuck' for limb in self._limbs): rospy.loginfo("Tucking: Arms already in 'Tucked' position.") self._done = True return else: rospy.loginfo("Tucking: One or more arms not Tucked.") any_flipped = not all(self._arm_state['flipped'].values()) if any_flipped: rospy.loginfo( "Moving to neutral start position with collision %s.", "on" if any_flipped else "off") # Move to neutral pose before tucking arms to avoid damage self._check_arm_state() actions = dict() disabled = {'left': True, 'right': True} for limb in self._limbs: if not self._arm_state['flipped'][limb]: actions[limb] = 'untuck' disabled[limb] = False self._move_to(actions, disabled) # Disable collision and Tuck Arms rospy.loginfo("Tucking: Tucking with collision avoidance off.") actions = {'left': 'tuck', 'right': 'tuck'} disabled = {'left': True, 'right': True} self._move_to(actions, disabled) self._done = True return # Untuck Arms else: # If arms are tucked disable collision and untuck arms if any(self._arm_state['flipped'].values()): rospy.loginfo("Untucking: One or more arms Tucked;" " Disabling Collision Avoidance and untucking.") self._check_arm_state() suppress = deepcopy(self._arm_state['flipped']) actions = {'left': 'untuck', 'right': 'untuck'} self._move_to(actions, suppress) self._done = True return # If arms already untucked, move to neutral location else: rospy.loginfo("Untucking: Arms already Untucked;" " Moving to neutral position.") self._check_arm_state() suppress = deepcopy(self._arm_state['flipped']) actions = {'left': 'untuck', 'right': 'untuck'} self._move_to(actions, suppress) self._done = True return def clean_shutdown(self): """Handles ROS shutdown (Ctrl-C) safely.""" if not self._done: rospy.logwarn('Aborting: Shutting down safely...') if any(self._arm_state['collide'].values()): while self._rs.state().enabled != False: [pub.publish(Empty()) for pub in self._disable_pub.values()] self._enable_pub.publish(False) self._tuck_rate.sleep() def main(): parser = argparse.ArgumentParser() tuck_group = parser.add_mutually_exclusive_group(required=True) tuck_group.add_argument("-t","--tuck", dest="tuck", action='store_true', default=False, help="tuck arms") tuck_group.add_argument("-u", "--untuck", dest="untuck", action='store_true', default=False, help="untuck arms") args = parser.parse_args(rospy.myargv()[1:]) tuck = args.tuck rospy.loginfo("Initializing node... ") rospy.init_node("rsdk_tuck_arms") rospy.loginfo("%sucking arms" % ("T" if tuck else "Unt",)) tucker = Tuck(tuck) rospy.on_shutdown(tucker.clean_shutdown) tucker.supervised_tuck() rospy.loginfo("Finished tuck") if __name__ == "__main__": main()

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0.237879

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0.312429

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266

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42.631579

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0

0.109948

0

null

0

null

0

1

0

ed849abb775e5f57be3b9019dbf370e35893e0b2

606

py

Python

Python/leetcode.031.next-permutation.py

tedye/leetcode

975d7e3b8cb9b6be9e80e07febf4bcf6414acd46

[ "MIT" ]

4

2015-10-10T00:30:55.000Z

2020-07-27T19:45:54.000Z

Python/leetcode.031.next-permutation.py

tedye/leetcode

975d7e3b8cb9b6be9e80e07febf4bcf6414acd46

[ "MIT" ]

null

Python/leetcode.031.next-permutation.py

tedye/leetcode

975d7e3b8cb9b6be9e80e07febf4bcf6414acd46

[ "MIT" ]

null

class Solution(object): def nextPermutation(self, nums): """ :type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead. """ if not nums: return n = len(nums)-1 while n > 0 and nums[n-1] >= nums[n]: n -= 1 t = n if t == 0: nums[:] = nums[::-1] return x = nums[n-1] while t < len(nums) and x < nums[t]: t += 1 temp = nums[t-1] nums[t-1] = nums[n-1] nums[n-1] = temp nums[n:] = nums[n:][::-1] return

27.545455

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0.429043

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0.134615

0.115385

0.076923

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0.420792

606

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false

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0.222222

0

null

0

null

0

1

0

ed86102b88fe53e5292e7840680746dc239293e9

4,883

py

Python

test/unit/app/tools/test_select_parameters.py

beatrizserrano/galaxy

e149d9d32e1bca6c07c38b1a9cdabfee60323610

[ "CC-BY-3.0" ]

null

test/unit/app/tools/test_select_parameters.py

beatrizserrano/galaxy

e149d9d32e1bca6c07c38b1a9cdabfee60323610

[ "CC-BY-3.0" ]

6

2021-11-11T20:57:49.000Z

2021-12-10T15:30:33.000Z

test/unit/app/tools/test_select_parameters.py

beatrizserrano/galaxy

e149d9d32e1bca6c07c38b1a9cdabfee60323610

[ "CC-BY-3.0" ]

null

from unittest.mock import Mock import pytest from galaxy import model from galaxy.tools.parameters import basic from .util import BaseParameterTestCase class SelectToolParameterTestCase(BaseParameterTestCase): def test_validated_values(self): self.options_xml = """<options><filter type="data_meta" ref="input_bam" key="dbkey"/></options>""" with pytest.raises(ValueError) as exc_info: self.param.from_json("42", self.trans, {"input_bam": model.HistoryDatasetAssociation()}) assert str(exc_info.value) == "parameter 'my_name': requires a value, but no legal values defined" def test_validated_values_missing_dependency(self): self.options_xml = """<options><filter type="data_meta" ref="input_bam" key="dbkey"/></options>""" with pytest.raises(ValueError) as exc_info: self.param.from_json("42", self.trans) assert str(exc_info.value) == "parameter 'my_name': requires a value, but no legal values defined" def test_unvalidated_values(self): self.options_xml = """<options><filter type="data_meta" ref="input_bam" key="dbkey"/></options>""" self.trans.workflow_building_mode = True assert self.param.from_json("42", self.trans) == "42" def test_validated_datasets(self): self.options_xml = """<options><filter type="data_meta" ref="input_bam" key="dbkey"/></options>""" with pytest.raises(ValueError) as exc_info: self.param.from_json(model.HistoryDatasetAssociation(), self.trans, {"input_bam": None}) assert str(exc_info.value) == "parameter 'my_name': requires a value, but no legal values defined" def test_unvalidated_datasets(self): self.options_xml = """<options><filter type="data_meta" ref="input_bam" key="dbkey"/></options>""" self.trans.workflow_building_mode = True assert isinstance( self.param.from_json(model.HistoryDatasetAssociation(), self.trans, {"input_bam": basic.RuntimeValue()}), model.HistoryDatasetAssociation, ) def test_filter_param_value(self): self.options_xml = """<options from_data_table="test_table"><filter type="param_value" ref="input_bam" column="0" /></options>""" assert ("testname1", "testpath1", False) in self.param.get_options(self.trans, {"input_bam": "testname1"}) assert ("testname2", "testpath2", False) in self.param.get_options(self.trans, {"input_bam": "testname2"}) assert len(self.param.get_options(self.trans, {"input_bam": "testname3"})) == 0 def test_filter_param_value2(self): # Same test as above, but filtering on a different column. self.options_xml = """<options from_data_table="test_table"><filter type="param_value" ref="input_bam" column="1" /></options>""" assert ("testname1", "testpath1", False) in self.param.get_options(self.trans, {"input_bam": "testpath1"}) assert ("testname2", "testpath2", False) in self.param.get_options(self.trans, {"input_bam": "testpath2"}) assert len(self.param.get_options(self.trans, {"input_bam": "testpath3"})) == 0 # TODO: Good deal of overlap here with DataToolParameterTestCase, # refactor. def setUp(self): super().setUp() self.test_history = model.History() self.app.model.context.add(self.test_history) self.app.model.context.flush() self.app.tool_data_tables["test_table"] = MockToolDataTable() self.trans = Mock( app=self.app, get_history=lambda: self.test_history, get_current_user_roles=lambda: [], workflow_building_mode=False, webapp=Mock(name="galaxy"), ) self.type = "select" self.set_data_ref = False self.multiple = False self.optional = False self.options_xml = "" self._param = None @property def param(self): if not self._param: multi_text = "" if self.multiple: multi_text = 'multiple="True"' optional_text = "" if self.optional: optional_text = 'optional="True"' options_text = self.options_xml data_ref_text = "" if self.set_data_ref: data_ref_text = 'data_ref="input_bam"' template_xml = """<param name="my_name" type="%s" %s %s %s>%s</param>""" param_str = template_xml % (self.type, data_ref_text, multi_text, optional_text, options_text) self._param = self._parameter_for(xml=param_str) return self._param class MockToolDataTable: def __init__(self): self.columns = dict( name=0, value=1, ) self.missing_index_file = None def get_fields(self): return [["testname1", "testpath1"], ["testname2", "testpath2"]]

45.635514

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4,883

5.089527

0.212838

0.045138

0.041819

0.05078

0.537006

0.51842

0.509127

0

0.008698

0.223019

4,883

106

138

46.066038

0.785451

0.026623

0

0.149425

0

0.034483

0.241103

0.039377

0

0.009434

0.126437

1

0.126437

false

0

0.057471

0.011494

0.229885

0

null

0

null

0

1

0

ed8c04e174410b92850aae3e034c73bb05a4abae

4,351

py

Python

src/selfdroid/appstorage/crud/AppAdder.py

vitlabuda/selfdroid-web-app

9eac9ee2c34038de13e179b6afb3d530a086e7b2

[ "Apache-2.0", "BSD-3-Clause" ]

1

2022-03-13T14:57:04.000Z

src/selfdroid/appstorage/crud/AppAdder.py

vitlabuda/selfdroid-web-app

9eac9ee2c34038de13e179b6afb3d530a086e7b2

[ "Apache-2.0", "BSD-3-Clause" ]

null

src/selfdroid/appstorage/crud/AppAdder.py

vitlabuda/selfdroid-web-app

9eac9ee2c34038de13e179b6afb3d530a086e7b2

[ "Apache-2.0", "BSD-3-Clause" ]

null

# SPDX-License-Identifier: BSD-3-Clause # # Copyright (c) 2021 Vít Labuda. 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. # 3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote # products derived from this software without specific prior written permission. # # 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 os import sqlalchemy.exc from selfdroid.appstorage.AppMetadata import AppMetadata from selfdroid.appstorage.AppMetadataDBModel import AppMetadataDBModel from selfdroid.appstorage.AppStorageConsistencyEnsurer import AppStorageConsistencyEnsurer from selfdroid.appstorage.apk.APKParser import APKParser from selfdroid.appstorage.apk.ParsedAPK import ParsedAPK from selfdroid.appstorage.crud.AppAdderException import AppAdderException from selfdroid.web.WebStatusMessageCollector import WebStatusMessageCollector from selfdroid import db class AppAdder: """ This class must be instantiated and have its public methods called in a locked context! """ def __init__(self, uploaded_apk_path: str): self._uploaded_apk_path: str = uploaded_apk_path self._parsed_apk: ParsedAPK = APKParser(self._uploaded_apk_path).parsed_apk def add_app_while_locked(self) -> AppMetadata: """ :return: The metadata of the added app. """ try: app_metadata = self._add_app_while_locked_with_exceptions_handled() except (sqlalchemy.exc.SQLAlchemyError, OSError): db.session.rollback() raise AppAdderException("An error occurred while adding the app!") finally: AppStorageConsistencyEnsurer().ensure_consistency_while_locked() return app_metadata def _add_app_while_locked_with_exceptions_handled(self) -> AppMetadata: self._check_if_app_can_be_added() return self._perform_app_addition() def _check_if_app_can_be_added(self) -> None: an_app_with_the_same_package_name = AppMetadataDBModel.query.filter_by(package_name=self._parsed_apk.package_name).first() if an_app_with_the_same_package_name is not None: html_message = WebStatusMessageCollector.format_html_message("An app with the same package name <i>({})</i> is already present on the server! You should update the app instead of adding it!", self._parsed_apk.package_name) raise AppAdderException(html_message) def _perform_app_addition(self) -> AppMetadata: # An UserReadableException mustn't be raised in this method! # 1. Database db_model = self._parsed_apk.create_new_db_model_with_metadata() db.session.add(db_model) db.session.commit() assert isinstance(db_model.id, int) app_metadata = AppMetadata.from_db_model(db_model) # 2. APK apk_path = app_metadata.get_apk_path() os.rename(self._uploaded_apk_path, apk_path) # 3. Icon icon_path = app_metadata.get_icon_path() with open(icon_path, "wb") as icon_file: icon_file.write(self._parsed_apk.uniform_png_app_icon) return app_metadata

44.397959

234

0.75385

576

4,351

5.493056

0.401042

0.03287

0.043616

0.02402

0.156764

0.105247

0.092604

0.042984

0

0.00311

0.187083

4,351

97

235

44.85567

0.891433

0.400598

0

0.046512

0

0.023256

0.065986

0

0.023256

1

0.116279

false

0

0.232558

0

0.44186

0

null

0

null

0

1

0

71ebf7fd79d9cbf3e546f3b0a0480b99be5ed04d

3,549

py

Python

websockets.py

ejojmjn/indiana-phone

5d666ac651d3e02291806f24c265564002912e00

[ "MIT" ]

null

websockets.py

ejojmjn/indiana-phone

5d666ac651d3e02291806f24c265564002912e00

[ "MIT" ]

null

websockets.py

ejojmjn/indiana-phone

5d666ac651d3e02291806f24c265564002912e00

[ "MIT" ]

null

#from gevent import monkey #monkey.patch_all() from flask import Flask, render_template, json from flask_socketio import SocketIO, emit from pydbus import SystemBus from gi.repository import GLib import threading import json app = Flask(__name__) app.config['SECRET_KEY'] = 'secret!' socketio = SocketIO(app, async_mode='threading') #socketio = SocketIO(app) #Message: (':1.654', '/hfp/org/bluez/hci0/dev_94_65_2D_84_61_99', 'org.ofono.Modem', 'PropertyChanged', ('Powered', False)) #Data: Powered bus = SystemBus() def cb_server_signal_emission(*args): print("Message: ", args) makedev = lambda path : path.split('/')[-1] iface = args[2] if 'org.ofono.Modem' in iface: if 'PropertyChanged' in args[3]: message = { 'source': 'modem', 'event': 'property_change', 'device': makedev(args[1]), 'property': args[4][0], 'property_value': args[4][1] } else: message = {'unknown_signal': args } elif 'org.ofono.NetworkRegistration' in iface: if 'PropertyChanged' in args[3]: message = { 'source': 'network', 'event': 'property_change', 'device': makedev(args[1]), 'property': args[4][0], 'property_value': args[4][1] } else: message = {'unknown_signal': args } elif 'ofono.VoiceCallManager' in iface: if 'CallAdded' in args[3]: message = { 'source': 'callmgr', 'event': 'call_added', 'device': makedev(args[1]), 'properties': args[4][1] } elif 'CallRemoved' in args[3]: message = { 'source': 'callmgr', 'event': 'call_removed', 'device': makedev(args[1]) } else: message = {'unknown_signal': args } elif 'ofono.VoiceCall' in iface: if 'PropertyChanged' in args[3]: message = { 'source': 'call', 'event': 'property_change', 'device': makedev(args[1]), 'property': args[4][0], 'property_value': args[4][1] } else: message = {'unknown_signal': args } socketio.emit('message', json.dumps(message)) def dbus_monitor(): bus.subscribe(iface = 'org.ofono.Modem', signal_fired = cb_server_signal_emission) bus.subscribe(iface = 'org.ofono.NetworkRegistration', signal_fired = cb_server_signal_emission) print(bus) bus.subscribe(iface = 'org.ofono.VoiceCallManager', signal_fired = cb_server_signal_emission) print(bus) bus.subscribe(iface = 'org.ofono.VoiceCall', signal_fired = cb_server_signal_emission) loop = GLib.MainLoop() loop.run() @app.route('/') def index(): return ''' <html> <head> <script type="text/javascript" src="//cdnjs.cloudflare.com/ajax/libs/socket.io/1.3.6/socket.io.min.js"></script> <script type="text/javascript" charset="utf-8"> var socket = io.connect('http://' + document.domain + ':' + location.port); socket.on('connect', function() { socket.emit('connected', {data: 'Client connected!'}); }); socket.on('message', function(message) { console.log('The server has a message for you: ' + message); var t = document.getElementById("logbox"); t.value = t.value + 'MESSAGE: ' + message + '\\n'; }); </script> </head> <body> <textarea id="logbox" width="100" rows="10"></textarea> <br> <button onclick="document.getElementById('logbox').value='';">Clear</button> </body> </html> ''' @socketio.on('my event') def handle_my_custom_event(arg1): emit('message', {'data': 42}) if __name__ == '__main__': t = threading.Thread(target=dbus_monitor) t.daemon = True t.start() socketio.run(app, host='0.0.0.0', port=5001)

32.263636

151

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446

3,549

4.973094

0.360987

0.025248

0.03156

0.049594

0.359333

0.33679

0.307033

0.255185

0.195672

0

0.021372

0.182587

3,549

109

152

32.559633

0.743192

0.057481

0

0.228916

0

0.012048

0.419539

0.113275

0

1

0.048193

false

0

0.072289

0.012048

0.13253

0.036145

0

null

0

null

0

1

0

71ecbe30760d8ff6d5c97c8f6cb9ae037d64dc1b

39,956

py

Python

sc2/bot_ai.py

Lexa307/PhotonDefender

a08dc652e5c64e3ccb33b7cfa206846dca0575bd

[ "MIT" ]

2

2019-07-17T13:00:32.000Z

2019-07-17T13:09:30.000Z

sc2/bot_ai.py

Lexa307/PhotonDefender

a08dc652e5c64e3ccb33b7cfa206846dca0575bd

[ "MIT" ]

null

sc2/bot_ai.py

Lexa307/PhotonDefender

a08dc652e5c64e3ccb33b7cfa206846dca0575bd

[ "MIT" ]

null

import itertools import logging import math import random from collections import Counter from typing import Any, Dict, List, Optional, Set, Tuple, Union # mypy type checking from .cache import property_cache_forever, property_cache_once_per_frame from .data import ActionResult, Alert, Race, Result, Target, race_gas, race_townhalls, race_worker from .data import ActionResult, Attribute, Race, race_worker, race_townhalls, race_gas, Target, Result from .game_data import AbilityData, GameData # imports for mypy and pycharm autocomplete from .game_state import GameState from .game_data import GameData, AbilityData from .ids.ability_id import AbilityId from .ids.unit_typeid import UnitTypeId from .ids.upgrade_id import UpgradeId from .pixel_map import PixelMap from .position import Point2, Point3 from .unit import Unit from .units import Units logger = logging.getLogger(__name__) class BotAI: """Base class for bots.""" EXPANSION_GAP_THRESHOLD = 15 def __init__(self): # Specific opponent bot ID used in sc2ai ladder games http://sc2ai.net/ # The bot ID will stay the same each game so your bot can "adapt" to the opponent self.opponent_id: int = None self.units: Units = None self.workers: Units = None self.townhalls: Units = None self.geysers: Units = None self.minerals: int = None self.vespene: int = None self.supply_army: Union[float, int] = None self.supply_workers: Union[float, int] = None # Doesn't include workers in production self.supply_cap: Union[float, int] = None self.supply_used: Union[float, int] = None self.supply_left: Union[float, int] = None self.idle_worker_count: int = None self.army_count: int = None self.warp_gate_count: int = None self.larva_count: int = None self.cached_known_enemy_structures = None self.cached_known_enemy_units = None @property def enemy_race(self) -> Race: assert len(self._game_info.player_races) == 2, "enemy_race not available" self.enemy_id = 3 - self.player_id return Race(self._game_info.player_races[self.enemy_id]) @property def time(self) -> Union[int, float]: """ Returns time in seconds, assumes the game is played on 'faster' """ return self.state.game_loop / 22.4 # / (1/1.4) * (1/16) @property def time_formatted(self) -> str: """ Returns time as string in min:sec format """ t = self.time return f"{int(t // 60):02}:{int(t % 60):02}" @property def game_info(self) -> "GameInfo": return self._game_info def alert(self, alert_code: Alert) -> bool: """ Check if alert is triggered in the current step. Example use: from sc2.data import Alert if self.alert(Alert.AddOnComplete): print("Addon Complete") Alert codes: AlertError AddOnComplete BuildingComplete BuildingUnderAttack LarvaHatched MergeComplete MineralsExhausted MorphComplete MothershipComplete MULEExpired NuclearLaunchDetected NukeComplete NydusWormDetected ResearchComplete TrainError TrainUnitComplete TrainWorkerComplete TransformationComplete UnitUnderAttack UpgradeComplete VespeneExhausted WarpInComplete """ assert isinstance(alert_code, Alert), f"alert_code {alert_code} is no Alert" return alert_code.value in self.state.alerts @property def start_location(self) -> Point2: return self._game_info.player_start_location @property def enemy_start_locations(self) -> List[Point2]: """Possible start locations for enemies.""" return self._game_info.start_locations @property_cache_once_per_frame def known_enemy_units(self) -> Units: """List of known enemy units, including structures.""" return self.state.enemy_units @property_cache_once_per_frame def known_enemy_structures(self) -> Units: """List of known enemy units, structures only.""" return self.state.enemy_units.structure @property def main_base_ramp(self) -> "Ramp": """ Returns the Ramp instance of the closest main-ramp to start location. Look in game_info.py for more information """ if hasattr(self, "cached_main_base_ramp"): return self.cached_main_base_ramp # The reason for len(ramp.upper) in {2, 5} is: # ParaSite map has 5 upper points, and most other maps have 2 upper points at the main ramp. # The map Acolyte has 4 upper points at the wrong ramp (which is closest to the start position). try: self.cached_main_base_ramp = min( (ramp for ramp in self.game_info.map_ramps if len(ramp.upper) in {2, 5}), key=lambda r: self.start_location.distance_to(r.top_center), ) except ValueError: # Hardcoded hotfix for Honorgrounds LE map, as that map has a large main base ramp with inbase natural self.cached_main_base_ramp = min( (ramp for ramp in self.game_info.map_ramps if len(ramp.upper) in {4, 9}), key=lambda r: self.start_location.distance_to(r.top_center), ) return self.cached_main_base_ramp @property_cache_forever def expansion_locations(self) -> Dict[Point2, Units]: """ Returns dict with the correct expansion position Point2 object as key, resources (mineral field and vespene geyser) as value. """ # Idea: create a group for every resource, then merge these groups if # any resource in a group is closer than 6 to any resource of another group # Distance we group resources by RESOURCE_SPREAD_THRESHOLD = 8.5 geysers = self.state.vespene_geyser # Create a group for every resource resource_groups = [[resource] for resource in self.state.resources] # Loop the merging process as long as we change something found_something = True while found_something: found_something = False # Check every combination of two groups for group_a, group_b in itertools.combinations(resource_groups, 2): # Check if any pair of resource of these groups is closer than threshold together if any( resource_a.distance_to(resource_b) <= RESOURCE_SPREAD_THRESHOLD for resource_a, resource_b in itertools.product(group_a, group_b) ): # Remove the single groups and add the merged group resource_groups.remove(group_a) resource_groups.remove(group_b) resource_groups.append(group_a + group_b) found_something = True break # Distance offsets we apply to center of each resource group to find expansion position offset_range = 7 offsets = [ (x, y) for x, y in itertools.product(range(-offset_range, offset_range + 1), repeat=2) if math.hypot(x, y) <= 8 ] # Dict we want to return centers = {} # For every resource group: for resources in resource_groups: # Possible expansion points amount = len(resources) # Calculate center, round and add 0.5 because expansion location will have (x.5, y.5) # coordinates because bases have size 5. center_x = int(sum(resource.position.x for resource in resources) / amount) + 0.5 center_y = int(sum(resource.position.y for resource in resources) / amount) + 0.5 possible_points = (Point2((offset[0] + center_x, offset[1] + center_y)) for offset in offsets) # Filter out points that are too near possible_points = ( point for point in possible_points # Check if point can be built on if self._game_info.placement_grid[point.rounded] == 1 # Check if all resources have enough space to point and all(point.distance_to(resource) > (7 if resource in geysers else 6) for resource in resources) ) # Choose best fitting point result = min(possible_points, key=lambda point: sum(point.distance_to(resource) for resource in resources)) centers[result] = resources return centers def _correct_zerg_supply(self): """ The client incorrectly rounds zerg supply down instead of up (see https://github.com/Blizzard/s2client-proto/issues/123), so self.supply_used and friends return the wrong value when there are an odd number of zerglings and banelings. This function corrects the bad values. """ # TODO: remove when Blizzard/sc2client-proto#123 gets fixed. half_supply_units = { UnitTypeId.ZERGLING, UnitTypeId.ZERGLINGBURROWED, UnitTypeId.BANELING, UnitTypeId.BANELINGBURROWED, UnitTypeId.BANELINGCOCOON, } correction = self.units(half_supply_units).amount % 2 self.supply_used += correction self.supply_army += correction self.supply_left -= correction async def get_available_abilities( self, units: Union[List[Unit], Units], ignore_resource_requirements=False ) -> List[List[AbilityId]]: """ Returns available abilities of one or more units. Right know only checks cooldown, energy cost, and whether the ability has been researched. Example usage: units_abilities = await self.get_available_abilities(self.units) or units_abilities = await self.get_available_abilities([self.units.random]) """ return await self._client.query_available_abilities(units, ignore_resource_requirements) async def expand_now( self, building: UnitTypeId = None, max_distance: Union[int, float] = 10, location: Optional[Point2] = None ): """ Not recommended as this function uses 'self.do' (reduces performance). Finds the next possible expansion via 'self.get_next_expansion()'. If the target expansion is blocked (e.g. an enemy unit), it will misplace the expansion. """ if not building: # self.race is never Race.Random start_townhall_type = { Race.Protoss: UnitTypeId.NEXUS, Race.Terran: UnitTypeId.COMMANDCENTER, Race.Zerg: UnitTypeId.HATCHERY, } building = start_townhall_type[self.race] assert isinstance(building, UnitTypeId) if not location: location = await self.get_next_expansion() await self.build(building, near=location, max_distance=max_distance, random_alternative=False, placement_step=1) async def get_next_expansion(self) -> Optional[Point2]: """Find next expansion location.""" closest = None distance = math.inf for el in self.expansion_locations: def is_near_to_expansion(t): return t.distance_to(el) < self.EXPANSION_GAP_THRESHOLD if any(map(is_near_to_expansion, self.townhalls)): # already taken continue startp = self._game_info.player_start_location d = await self._client.query_pathing(startp, el) if d is None: continue if d < distance: distance = d closest = el return closest async def distribute_workers(self, resource_ratio: float = 2): """ Distributes workers across all the bases taken. Keyword `resource_ratio` takes a float. If the current minerals to gas ratio is bigger than `resource_ratio`, this function prefer filling geysers first, if it is lower, it will prefer sending workers to minerals first. This is only for workers that need to be moved anyways, it will NOT will geysers on its own. NOTE: This function is far from optimal, if you really want to have refined worker control, you should write your own distribution function. For example long distance mining control and moving workers if a base was killed are not being handled. WARNING: This is quite slow when there are lots of workers or multiple bases. """ if not self.state.mineral_field or not self.workers or not self.townhalls.ready: return actions = [] worker_pool = [worker for worker in self.workers.idle] bases = self.townhalls.ready geysers = self.geysers.ready # list of places that need more workers deficit_mining_places = [] for mining_place in bases | geysers: difference = mining_place.surplus_harvesters # perfect amount of workers, skip mining place if not difference: continue if mining_place.is_vespene_geyser: # get all workers that target the gas extraction site # or are on their way back from it local_workers = self.workers.filter( lambda unit: unit.order_target == mining_place.tag or (unit.is_carrying_vespene and unit.order_target == bases.closest_to(mining_place).tag) ) else: # get tags of minerals around expansion local_minerals_tags = { mineral.tag for mineral in self.state.mineral_field if mineral.distance_to(mining_place) <= 8 } # get all target tags a worker can have # tags of the minerals he could mine at that base # get workers that work at that gather site local_workers = self.workers.filter( lambda unit: unit.order_target in local_minerals_tags or (unit.is_carrying_minerals and unit.order_target == mining_place.tag) ) # too many workers if difference > 0: for worker in local_workers[:difference]: worker_pool.append(worker) # too few workers # add mining place to deficit bases for every missing worker else: deficit_mining_places += [mining_place for _ in range(-difference)] # prepare all minerals near a base if we have too many workers # and need to send them to the closest patch if len(worker_pool) > len(deficit_mining_places): all_minerals_near_base = [ mineral for mineral in self.state.mineral_field if any(mineral.distance_to(base) <= 8 for base in self.townhalls.ready) ] # distribute every worker in the pool for worker in worker_pool: # as long as have workers and mining places if deficit_mining_places: # choose only mineral fields first if current mineral to gas ratio is less than target ratio if self.vespene and self.minerals / self.vespene < resource_ratio: possible_mining_places = [place for place in deficit_mining_places if not place.vespene_contents] # else prefer gas else: possible_mining_places = [place for place in deficit_mining_places if place.vespene_contents] # if preferred type is not available any more, get all other places if not possible_mining_places: possible_mining_places = deficit_mining_places # find closest mining place current_place = min(deficit_mining_places, key=lambda place: place.distance_to(worker)) # remove it from the list deficit_mining_places.remove(current_place) # if current place is a gas extraction site, go there if current_place.vespene_contents: actions.append(worker.gather(current_place)) # if current place is a gas extraction site, # go to the mineral field that is near and has the most minerals left else: local_minerals = [ mineral for mineral in self.state.mineral_field if mineral.distance_to(current_place) <= 8 ] target_mineral = max(local_minerals, key=lambda mineral: mineral.mineral_contents) actions.append(worker.gather(target_mineral)) # more workers to distribute than free mining spots # send to closest if worker is doing nothing elif worker.is_idle and all_minerals_near_base: target_mineral = min(all_minerals_near_base, key=lambda mineral: mineral.distance_to(worker)) actions.append(worker.gather(target_mineral)) else: # there are no deficit mining places and worker is not idle # so dont move him pass await self.do_actions(actions) @property def owned_expansions(self) -> Dict[Point2, Unit]: """List of expansions owned by the player.""" owned = {} for el in self.expansion_locations: def is_near_to_expansion(t): return t.distance_to(el) < self.EXPANSION_GAP_THRESHOLD th = next((x for x in self.townhalls if is_near_to_expansion(x)), None) if th: owned[el] = th return owned def can_feed(self, unit_type: UnitTypeId) -> bool: """ Checks if you have enough free supply to build the unit """ required = self._game_data.units[unit_type.value]._proto.food_required return required == 0 or self.supply_left >= required def can_afford( self, item_id: Union[UnitTypeId, UpgradeId, AbilityId], check_supply_cost: bool = True ) -> "CanAffordWrapper": """Tests if the player has enough resources to build a unit or cast an ability.""" enough_supply = True if isinstance(item_id, UnitTypeId): unit = self._game_data.units[item_id.value] cost = self._game_data.calculate_ability_cost(unit.creation_ability) if check_supply_cost: enough_supply = self.can_feed(item_id) elif isinstance(item_id, UpgradeId): cost = self._game_data.upgrades[item_id.value].cost else: cost = self._game_data.calculate_ability_cost(item_id) return CanAffordWrapper(cost.minerals <= self.minerals, cost.vespene <= self.vespene, enough_supply) async def can_cast( self, unit: Unit, ability_id: AbilityId, target: Optional[Union[Unit, Point2, Point3]] = None, only_check_energy_and_cooldown: bool = False, cached_abilities_of_unit: List[AbilityId] = None, ) -> bool: """Tests if a unit has an ability available and enough energy to cast it. See data_pb2.py (line 161) for the numbers 1-5 to make sense""" assert isinstance(unit, Unit) assert isinstance(ability_id, AbilityId) assert isinstance(target, (type(None), Unit, Point2, Point3)) # check if unit has enough energy to cast or if ability is on cooldown if cached_abilities_of_unit: abilities = cached_abilities_of_unit else: abilities = (await self.get_available_abilities([unit]))[0] if ability_id in abilities: if only_check_energy_and_cooldown: return True cast_range = self._game_data.abilities[ability_id.value]._proto.cast_range ability_target = self._game_data.abilities[ability_id.value]._proto.target # Check if target is in range (or is a self cast like stimpack) if ( ability_target == 1 or ability_target == Target.PointOrNone.value and isinstance(target, (Point2, Point3)) and unit.distance_to(target) <= cast_range ): # cant replace 1 with "Target.None.value" because ".None" doesnt seem to be a valid enum name return True # Check if able to use ability on a unit elif ( ability_target in {Target.Unit.value, Target.PointOrUnit.value} and isinstance(target, Unit) and unit.distance_to(target) <= cast_range ): return True # Check if able to use ability on a position elif ( ability_target in {Target.Point.value, Target.PointOrUnit.value} and isinstance(target, (Point2, Point3)) and unit.distance_to(target) <= cast_range ): return True return False def select_build_worker(self, pos: Union[Unit, Point2, Point3], force: bool = False) -> Optional[Unit]: """Select a worker to build a building with.""" workers = ( self.workers.filter(lambda w: (w.is_gathering or w.is_idle) and w.distance_to(pos) < 20) or self.workers ) if workers: for worker in workers.sorted_by_distance_to(pos).prefer_idle: if ( not worker.orders or len(worker.orders) == 1 and worker.orders[0].ability.id in {AbilityId.MOVE, AbilityId.HARVEST_GATHER} ): return worker return workers.random if force else None async def can_place(self, building: Union[AbilityData, AbilityId, UnitTypeId], position: Point2) -> bool: """Tests if a building can be placed in the given location.""" building_type = type(building) assert building_type in {AbilityData, AbilityId, UnitTypeId} if building_type == UnitTypeId: building = self._game_data.units[building.value].creation_ability elif building_type == AbilityId: building = self._game_data.abilities[building.value] r = await self._client.query_building_placement(building, [position]) return r[0] == ActionResult.Success async def find_placement( self, building: UnitTypeId, near: Union[Unit, Point2, Point3], max_distance: int = 20, random_alternative: bool = True, placement_step: int = 2, ) -> Optional[Point2]: """Finds a placement location for building.""" assert isinstance(building, (AbilityId, UnitTypeId)) assert isinstance(near, Point2) if isinstance(building, UnitTypeId): building = self._game_data.units[building.value].creation_ability else: # AbilityId building = self._game_data.abilities[building.value] if await self.can_place(building, near): return near if max_distance == 0: return None for distance in range(placement_step, max_distance, placement_step): possible_positions = [ Point2(p).offset(near).to2 for p in ( [(dx, -distance) for dx in range(-distance, distance + 1, placement_step)] + [(dx, distance) for dx in range(-distance, distance + 1, placement_step)] + [(-distance, dy) for dy in range(-distance, distance + 1, placement_step)] + [(distance, dy) for dy in range(-distance, distance + 1, placement_step)] ) ] res = await self._client.query_building_placement(building, possible_positions) possible = [p for r, p in zip(res, possible_positions) if r == ActionResult.Success] if not possible: continue if random_alternative: return random.choice(possible) else: return min(possible, key=lambda p: p.distance_to_point2(near)) return None def already_pending_upgrade(self, upgrade_type: UpgradeId) -> Union[int, float]: """ Check if an upgrade is being researched Return values: 0: not started 0 < x < 1: researching 1: finished """ assert isinstance(upgrade_type, UpgradeId) if upgrade_type in self.state.upgrades: return 1 level = None if "LEVEL" in upgrade_type.name: level = upgrade_type.name[-1] creationAbilityID = self._game_data.upgrades[upgrade_type.value].research_ability.id for structure in self.units.filter(lambda unit: unit.is_structure and unit.is_ready): for order in structure.orders: if order.ability.id is creationAbilityID: if level and order.ability.button_name[-1] != level: return 0 return order.progress return 0 @property_cache_once_per_frame def _abilities_all_units(self) -> Counter: """ Cache for the already_pending function, includes protoss units warping in, and all units in production, and all structures, and all morphs """ abilities_amount = Counter() for unit in self.units: # type: Unit for order in unit.orders: abilities_amount[order.ability] += 1 if not unit.is_ready: if self.race != Race.Terran or not unit.is_structure: # If an SCV is constructing a building, already_pending would count this structure twice (once from the SCV order, and once from "not structure.is_ready") abilities_amount[self._game_data.units[unit.type_id.value].creation_ability] += 1 return abilities_amount @property_cache_once_per_frame def _abilities_workers_and_eggs(self) -> Counter: """ Cache for the already_pending function, includes all worker orders (including pending). Zerg units in production (except queens and morphing units) and structures in production, counts double for terran """ abilities_amount = Counter() for worker in self.workers: # type: Unit for order in worker.orders: abilities_amount[order.ability] += 1 if self.race == Race.Zerg: for egg in self.units(UnitTypeId.EGG): # type: Unit for order in egg.orders: abilities_amount[order.ability] += 1 if self.race != Race.Terran: # If an SCV is constructing a building, already_pending would count this structure twice # (once from the SCV order, and once from "not structure.is_ready") for unit in self.units.structure.not_ready: # type: Unit abilities_amount[self._game_data.units[unit.type_id.value].creation_ability] += 1 return abilities_amount def already_pending(self, unit_type: Union[UpgradeId, UnitTypeId], all_units: bool = True) -> int: """ Returns a number of buildings or units already in progress, or if a worker is en route to build it. This also includes queued orders for workers and build queues of buildings. If all_units==True, then build queues of other units (such as Carriers (Interceptors) or Oracles (Stasis Ward)) are also included. """ # TODO / FIXME: SCV building a structure might be counted as two units if isinstance(unit_type, UpgradeId): return self.already_pending_upgrade(unit_type) ability = self._game_data.units[unit_type.value].creation_ability amount = len(self.units(unit_type).not_ready) if all_units: amount += sum([o.ability == ability for u in self.units for o in u.orders]) else: amount += sum([o.ability == ability for w in self.workers for o in w.orders]) amount += sum([egg.orders[0].ability == ability for egg in self.units(UnitTypeId.EGG)]) return amount async def build(self, building: UnitTypeId, near: Union[Point2, Point3], max_distance: int=20, unit: Optional[Unit]=None, random_alternative: bool=True, placement_step: int=2): """Build a building.""" if isinstance(near, Unit): near = near.position.to2 elif near is not None: near = near.to2 else: return p = await self.find_placement(building, near.rounded, max_distance, random_alternative, placement_step) if p is None: return ActionResult.CantFindPlacementLocation unit = unit or self.select_build_worker(p) if unit is None or not self.can_afford(building): return ActionResult.Error return await self.do(unit.build(building, p)) async def do(self, action): if not self.can_afford(action): logger.warning(f"Cannot afford action {action}") return ActionResult.Error r = await self._client.actions(action) if not r: # success cost = self._game_data.calculate_ability_cost(action.ability) self.minerals -= cost.minerals self.vespene -= cost.vespene else: logger.error(f"Error: {r} (action: {action})") return r async def do_actions(self, actions: List["UnitCommand"], prevent_double=True): """ Unlike 'self.do()', this function does not instantly subtract minerals and vespene. """ if not actions: return None if prevent_double: actions = list(filter(self.prevent_double_actions, actions)) for action in actions: cost = self._game_data.calculate_ability_cost(action.ability) self.minerals -= cost.minerals self.vespene -= cost.vespene return await self._client.actions(actions) def prevent_double_actions(self, action): # always add actions if queued if action.queue: return True if action.unit.orders: # action: UnitCommand # current_action: UnitOrder current_action = action.unit.orders[0] if current_action.ability.id != action.ability: # different action, return true return True try: if current_action.target == action.target.tag: # same action, remove action if same target unit return False except AttributeError: pass try: if action.target.x == current_action.target.x and action.target.y == current_action.target.y: # same action, remove action if same target position return False except AttributeError: pass return True return True async def chat_send(self, message: str): """ Send a chat message. """ assert isinstance(message, str), f"{message} is no string" await self._client.chat_send(message, False) # For the functions below, make sure you are inside the boundries of the map size. def get_terrain_height(self, pos: Union[Point2, Point3, Unit]) -> int: """ Returns terrain height at a position. Caution: terrain height is different from a unit's z-coordinate. """ assert isinstance(pos, (Point2, Point3, Unit)), f"pos is not of type Point2, Point3 or Unit" pos = pos.position.to2.rounded return self._game_info.terrain_height[pos] # returns int def get_terrain_z_height(self, pos: Union[Point2, Point3, Unit]) -> int: """ Returns terrain z-height at a position. """ assert isinstance(pos, (Point2, Point3, Unit)), f"pos is not of type Point2, Point3 or Unit" pos = pos.position.to2.rounded return -16 + 32 * self._game_info.terrain_height[pos] / 255 def in_placement_grid(self, pos: Union[Point2, Point3, Unit]) -> bool: """ Returns True if you can place something at a position. Remember, buildings usually use 2x2, 3x3 or 5x5 of these grid points. Caution: some x and y offset might be required, see ramp code: https://github.com/Dentosal/python-sc2/blob/master/sc2/game_info.py#L17-L18 """ assert isinstance(pos, (Point2, Point3, Unit)) pos = pos.position.to2.rounded return self._game_info.placement_grid[pos] == 1 def in_pathing_grid(self, pos: Union[Point2, Point3, Unit]) -> bool: """ Returns True if a unit can pass through a grid point. """ assert isinstance(pos, (Point2, Point3, Unit)) pos = pos.position.to2.rounded return self._game_info.pathing_grid[pos] == 1 def is_visible(self, pos: Union[Point2, Point3, Unit]) -> bool: """ Returns True if you have vision on a grid point. """ # more info: https://github.com/Blizzard/s2client-proto/blob/9906df71d6909511907d8419b33acc1a3bd51ec0/s2clientprotocol/spatial.proto#L19 assert isinstance(pos, (Point2, Point3, Unit)) pos = pos.position.to2.rounded return self.state.visibility[pos] == 2 def has_creep(self, pos: Union[Point2, Point3, Unit]) -> bool: """ Returns True if there is creep on the grid point. """ assert isinstance(pos, (Point2, Point3, Unit)) pos = pos.position.to2.rounded return self.state.creep[pos] == 1 def _prepare_start(self, client, player_id, game_info, game_data): """Ran until game start to set game and player data.""" self._client: "Client" = client self._game_info: "GameInfo" = game_info self._game_data: GameData = game_data self.player_id: int = player_id self.race: Race = Race(self._game_info.player_races[self.player_id]) self._units_previous_map: dict = dict() self._previous_upgrades: Set[UpgradeId] = set() self.units: Units = Units([]) def _prepare_first_step(self): """First step extra preparations. Must not be called before _prepare_step.""" if self.townhalls: self._game_info.player_start_location = self.townhalls.first.position self._game_info.map_ramps, self._game_info.vision_blockers = self._game_info._find_ramps_and_vision_blockers() def _prepare_step(self, state, proto_game_info): # Set attributes from new state before on_step.""" self.state: GameState = state # See game_state.py # update pathing grid self._game_info.pathing_grid: PixelMap = PixelMap( proto_game_info.game_info.start_raw.pathing_grid, in_bits=True, mirrored=False ) # Required for events self._units_previous_map: Dict = {unit.tag: unit for unit in self.units} self.units: Units = state.own_units self.workers: Units = self.units(race_worker[self.race]) self.townhalls: Units = self.units(race_townhalls[self.race]) self.geysers: Units = self.units(race_gas[self.race]) self.minerals: int = state.common.minerals self.vespene: int = state.common.vespene self.supply_army: int = state.common.food_army self.supply_workers: int = state.common.food_workers # Doesn't include workers in production self.supply_cap: int = state.common.food_cap self.supply_used: int = state.common.food_used self.supply_left: int = self.supply_cap - self.supply_used if self.race == Race.Zerg: self.larva_count: int = state.common.larva_count # Workaround Zerg supply rounding bug self._correct_zerg_supply() elif self.race == Race.Protoss: self.warp_gate_count: int = state.common.warp_gate_count self.idle_worker_count: int = state.common.idle_worker_count self.army_count: int = state.common.army_count # reset cached values self.cached_known_enemy_structures = None self.cached_known_enemy_units = None async def issue_events(self): """ This function will be automatically run from main.py and triggers the following functions: - on_unit_created - on_unit_destroyed - on_building_construction_complete """ await self._issue_unit_dead_events() await self._issue_unit_added_events() for unit in self.units.structure: await self._issue_building_complete_event(unit) if len(self._previous_upgrades) != len(self.state.upgrades): for upgrade_completed in self.state.upgrades - self._previous_upgrades: await self.on_upgrade_complete(upgrade_completed) self._previous_upgrades = self.state.upgrades async def _issue_unit_added_events(self): for unit in self.units.not_structure: if unit.tag not in self._units_previous_map: await self.on_unit_created(unit) for unit in self.units.structure: if unit.tag not in self._units_previous_map: await self.on_building_construction_started(unit) async def _issue_building_complete_event(self, unit): if unit.build_progress < 1: return if unit.tag not in self._units_previous_map: return unit_prev = self._units_previous_map[unit.tag] if unit_prev.build_progress < 1: await self.on_building_construction_complete(unit) async def _issue_unit_dead_events(self): for unit_tag in self.state.dead_units: await self.on_unit_destroyed(unit_tag) async def on_unit_destroyed(self, unit_tag): """ Override this in your bot class. Note that this function uses unit tags because the unit does not exist any more. """ async def on_unit_created(self, unit: Unit): """ Override this in your bot class. """ async def on_building_construction_started(self, unit: Unit): """ Override this in your bot class. """ async def on_building_construction_complete(self, unit: Unit): """ Override this in your bot class. Note that this function is also triggered at the start of the game for the starting base building.""" async def on_upgrade_complete(self, upgrade: UpgradeId): """ Override this in your bot class. """ def on_start(self): """ Allows initializing the bot when the game data is available. """ async def on_start_async(self): """ This function is run after "on_start". At this point, game_data, game_info and the first iteration of game_state (self.state) are available. """ async def on_step(self, iteration: int): """Ran on every game step (looped in realtime mode).""" raise NotImplementedError def on_end(self, game_result: Result): """ Triggered at the end of a game. """ class CanAffordWrapper: def __init__(self, can_afford_minerals, can_afford_vespene, have_enough_supply): self.can_afford_minerals = can_afford_minerals self.can_afford_vespene = can_afford_vespene self.have_enough_supply = have_enough_supply def __bool__(self): return self.can_afford_minerals and self.can_afford_vespene and self.have_enough_supply @property def action_result(self): if not self.can_afford_vespene: return ActionResult.NotEnoughVespene elif not self.can_afford_minerals: return ActionResult.NotEnoughMinerals elif not self.have_enough_supply: return ActionResult.NotEnoughFood else: return None

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0.633922

4,991

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4.908636

0.140453

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0.004857

0.273562

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0.219931

0

null

0

null

0

1

0

71ecddbb1bd02f445d97d4e77a4a4128c68a4abe

4,260

py

Python

src/python/pants/jvm/resolve/lockfile_metadata.py

xyzst/pants

d6a357fe67ee7e8e1aefeae625e107f5609f1717

[ "Apache-2.0" ]

null

src/python/pants/jvm/resolve/lockfile_metadata.py

xyzst/pants

d6a357fe67ee7e8e1aefeae625e107f5609f1717

[ "Apache-2.0" ]

6

2022-01-25T15:49:26.000Z

2022-02-09T11:21:13.000Z

src/python/pants/jvm/resolve/lockfile_metadata.py

thejcannon/pants

7c24f42cb78cc462b63698cef736eda7a85c40e0

[ "Apache-2.0" ]

null

# Copyright 2022 Pants project contributors (see CONTRIBUTORS.md). # Licensed under the Apache License, Version 2.0 (see LICENSE). from __future__ import annotations from dataclasses import dataclass from enum import Enum from typing import Any, Iterable, cast from pants.core.util_rules.lockfile_metadata import ( LockfileMetadata, LockfileMetadataValidation, LockfileScope, _get_metadata, lockfile_metadata_registrar, ) from pants.jvm.resolve.common import ArtifactRequirement from pants.util.ordered_set import FrozenOrderedSet _jvm_lockfile_metadata = lockfile_metadata_registrar(LockfileScope.JVM) class InvalidJVMLockfileReason(Enum): REQUIREMENTS_MISMATCH = "requirements_mismatch" @dataclass(frozen=True) class JVMLockfileMetadata(LockfileMetadata): scope = LockfileScope.JVM @staticmethod def new( requirements: Iterable[ArtifactRequirement], ) -> JVMLockfileMetadata: """Call the most recent version of the `LockfileMetadata` class to construct a concrete instance. This static method should be used in place of the `LockfileMetadata` constructor. This gives calling sites a predictable method to call to construct a new `LockfileMetadata` for writing, while still allowing us to support _reading_ older, deprecated metadata versions. """ return JVMLockfileMetadataV1.from_artifact_requirements(requirements) @classmethod def from_lockfile( cls, lockfile: bytes, lockfile_path: str | None = None, resolve_name: str | None = None ) -> JVMLockfileMetadataV1: return cast( JVMLockfileMetadataV1, LockfileMetadata.from_lockfile_for_scope( LockfileScope.JVM, lockfile, lockfile_path, resolve_name ), ) def is_valid_for( self, requirements: Iterable[ArtifactRequirement] | None, ) -> LockfileMetadataValidation: """Returns Truthy if this `JVMLockfileMetadata` can be used in the current execution context.""" raise NotImplementedError("call `is_valid_for` on subclasses only") @_jvm_lockfile_metadata(1) @dataclass(frozen=True) class JVMLockfileMetadataV1(JVMLockfileMetadata): """Lockfile version that permits specifying a requirements as a set rather than a digest. Validity is tested by the set of requirements strings being the same in the user requirements as those in the stored requirements. """ requirements: FrozenOrderedSet[str] @classmethod def from_artifact_requirements( cls, requirements: Iterable[ArtifactRequirement] ) -> JVMLockfileMetadataV1: return cls(FrozenOrderedSet(i.to_metadata_str() for i in requirements)) @classmethod def _from_json_dict( cls: type[JVMLockfileMetadataV1], json_dict: dict[Any, Any], lockfile_description: str, error_suffix: str, ) -> JVMLockfileMetadataV1: metadata = _get_metadata(json_dict, lockfile_description, error_suffix) requirements = metadata( "generated_with_requirements", FrozenOrderedSet[str], FrozenOrderedSet, ) return JVMLockfileMetadataV1(requirements) @classmethod def additional_header_attrs(cls, instance: LockfileMetadata) -> dict[Any, Any]: instance = cast(JVMLockfileMetadataV1, instance) return { "generated_with_requirements": ( sorted(instance.requirements) if instance.requirements is not None else None ) } def is_valid_for( self, requirements: Iterable[ArtifactRequirement] | None, ) -> LockfileMetadataValidation: """Returns a truthy object if the request requirements match the metadata requirements. For this version, "match" is defined as the request requirements being a non-strict subset of the metadata requirements. """ failure_reasons: set[InvalidJVMLockfileReason] = set() if not self.requirements.issuperset(i.to_metadata_str() for i in requirements or []): failure_reasons.add(InvalidJVMLockfileReason.REQUIREMENTS_MISMATCH) return LockfileMetadataValidation(failure_reasons)

33.809524

100

0.711268

431

4,260

6.87703

0.361949

0.026991

0.052632

0.022267

0.084345

0.062753

0

0.004841

0.224178

4,260

125

101

34.08

0.891982

0.236854

0

0.217949

0

0.035964

0.02387

0

1

0.089744

false

0

0.089744

0.025641

0.333333

0

null

0

null

0

1

0

71ece1b40046a77ed95f80492a330f22d42912ee

1,528

py

Python

generator/generator.py

GregorKikelj/opendbc

a20ed24ea2593e5d019adf538dc0cecfc7ef8709

[ "MIT" ]

1,059

2017-05-31T06:33:27.000Z

2022-03-31T23:02:29.000Z

generator/generator.py

DIMO-Network/opendbc

9a1fbe581846f9d0191f142f498ef3f1c35826ea

[ "MIT" ]

248

2017-07-14T01:45:40.000Z

2022-03-21T17:55:26.000Z

generator/generator.py

DIMO-Network/opendbc

9a1fbe581846f9d0191f142f498ef3f1c35826ea

[ "MIT" ]

940

2017-06-02T16:40:42.000Z

2022-03-29T16:49:58.000Z

#!/usr/bin/env python3 import os import re cur_path = os.path.dirname(os.path.realpath(__file__)) opendbc_root = os.path.join(cur_path, '../') include_pattern = re.compile(r'CM_ "IMPORT (.*?)";') def read_dbc(src_dir, filename): with open(os.path.join(src_dir, filename)) as file_in: return file_in.read() def create_dbc(src_dir, filename, output_path): dbc_file_in = read_dbc(src_dir, filename) includes = include_pattern.findall(dbc_file_in) output_filename = filename.replace('.dbc', '_generated.dbc') output_file_location = os.path.join(output_path, output_filename) with open(output_file_location, 'w') as dbc_file_out: dbc_file_out.write('CM_ "AUTOGENERATED FILE, DO NOT EDIT";\n') for include_filename in includes: include_file_header = '\n\nCM_ "Imported file %s starts here";\n' % include_filename dbc_file_out.write(include_file_header) include_file = read_dbc(src_dir, include_filename) dbc_file_out.write(include_file) dbc_file_out.write('\nCM_ "%s starts here";\n' % filename) core_dbc = include_pattern.sub('', dbc_file_in) dbc_file_out.write(core_dbc) def create_all(output_path): for src_dir, _, filenames in os.walk(cur_path): if src_dir == cur_path: continue #print(src_dir) for filename in filenames: if filename.startswith('_') or not filename.endswith('.dbc'): continue #print(filename) create_dbc(src_dir, filename, output_path) if __name__ == "__main__": create_all(opendbc_root)

28.296296

90

0.716623

228

1,528

4.429825

0.289474

0.053465

0.059406

0.074257

0.188119

0.146535

0.081188

0

0.000781

0.161649

1,528

53

91

28.830189

0.787666

0.032723

0

0.060606

0

0.108475

0

1

0.090909

false

0

0.121212

0

0.242424

0

null

0

null

0

1

0

71ef13879f7d9412c115fe5712bcdcce5a10b758

4,067

py

Python

src/ripper.py

jg-rivera/cert-ripper

2bab5e02cd2da8e92a1c308640917b6f5ee729cb

[ "MIT" ]

null

src/ripper.py

jg-rivera/cert-ripper

2bab5e02cd2da8e92a1c308640917b6f5ee729cb

[ "MIT" ]

null

src/ripper.py

jg-rivera/cert-ripper

2bab5e02cd2da8e92a1c308640917b6f5ee729cb

[ "MIT" ]

null

from dotenv import load_dotenv from PyPDF2 import PdfFileReader, PdfFileWriter import os import json class CertRipper: def __init__( self, start_page_index=0, master_pdf_path=None, json_points_path=None, ripped_certs_path=None, ripped_cert_file_name=None, ): self.start_page_index = start_page_index self.master_pdf_path = master_pdf_path self.pdf = PdfFileReader(master_pdf_path) self.pdf_length = self.pdf.getNumPages() self.json_points_path = json_points_path self.ripped_certs_path = ripped_certs_path self.ripped_cert_file_name = ripped_cert_file_name def process(self): recipient_groups = self.get_recipient_groups_from_points() self.extract_pdf_from_master(recipient_groups) def extract_pdf_from_master(self, recipient_groups): current_page_index = self.start_page_index process_index = 0 for recipient_group in recipient_groups: recipient_group_name = recipient_group["name"] recipient_group_tag = recipient_group["tag"] recipient_slugs = recipient_group["recipient_slugs"] print( f"[*] Ripping \x1b[93m{recipient_group_name}\x1b[0m group ...") for recipient_slug in recipient_slugs: page = self.pdf.getPage(current_page_index) file_name = self.ripped_cert_file_name.format( index=current_page_index + 1, tag=recipient_group_tag, recipient=recipient_slug ) pdf_writer = PdfFileWriter() pdf_writer.addPage(page) output_file_name = f"{self.ripped_certs_path}\\{file_name}.pdf" with open(output_file_name, "wb") as out: pdf_writer.write(out) print( f"\x1b[95m[{process_index}]\x1b[0m Ripped \x1b[92m[{file_name}]\x1b[0m from \x1b[94mpage {current_page_index + 1}\x1b[0m of master") current_page_index += 1 process_index += 1 def get_recipient_groups_from_points(self): recipient_groups = [] total_recipients = 0 with open(self.json_points_path, "r") as json_file: points = json.load(json_file) for point in points: point_name = point["name"] point_tag = point["tag"] point_recipients = point["recipients"] point_recipient_slugs = [] for point_recipient in point_recipients: recipient_name = point_recipient["name"] recipient_name_slug = "_".join(recipient_name.split()) point_recipient_slugs.append(recipient_name_slug) total_recipients += 1 recipient_groups.append({ "name": point_name, "tag": point_tag, "recipient_slugs": point_recipient_slugs }) total_groups = len(recipient_groups) self.__check_pdf_length(total_recipients) print( f"Read \x1b[95m{total_groups} groups(s)\x1b[0m and \x1b[95m{total_recipients} recipient(s)\x1b[0m from JSON points") return recipient_groups def __check_pdf_length(self, recipients_length): pdf_length = self.pdf_length - (self.start_page_index) if pdf_length != recipients_length: raise ValueError( f"Number of recipients ({recipients_length}) does not match with PDF length ({pdf_length})" ) if __name__ == "__main__": load_dotenv() ripper = CertRipper( start_page_index=os.getenv("START_PAGE_INDEX"), master_pdf_path=os.getenv("MASTER_PDF_PATH"), json_points_path=os.getenv("JSON_POINTS_PATH"), ripped_certs_path=os.getenv("RIPPED_CERTS_PATH"), ripped_cert_file_name=os.getenv("RIPPED_CERT_FILE_NAME"), ) ripper.process()

35.060345

152

0.614212

469

4,067

4.921109

0.185501

0.046794

0.042461

0.046794

0.110919

0.02773

0

0.013786

0.304401

4,067

115

153

35.365217

0.80205

0

0.033708

0

0.022472

0.14507

0.056061

0

1

0.05618

false

0

0.044944

0

0.123596

0.033708

0

null

0

null

0

1

0

71ef7b545410fc717e2f36b835e68675481e1947

2,192

py

Python

venv/Lib/site-packages/tests/test_111_FieldNumAddCol.py

shehzadulislam/Assignment4

a9cced70be6ae5d2685027d68032d5849f638301

[ "Apache-2.0" ]

null

venv/Lib/site-packages/tests/test_111_FieldNumAddCol.py

shehzadulislam/Assignment4

a9cced70be6ae5d2685027d68032d5849f638301

[ "Apache-2.0" ]

null

venv/Lib/site-packages/tests/test_111_FieldNumAddCol.py

shehzadulislam/Assignment4

a9cced70be6ae5d2685027d68032d5849f638301

[ "Apache-2.0" ]

null

# # Licensed Materials - Property of IBM # # (c) Copyright IBM Corp. 2007-2008 # import unittest, sys import ibm_db import config from testfunctions import IbmDbTestFunctions class IbmDbTestCase(unittest.TestCase): def test_111_FieldNumAddCol(self): obj = IbmDbTestFunctions() obj.assert_expect(self.run_test_111) def run_test_111(self): conn = ibm_db.connect(config.database, config.user, config.password) server = ibm_db.server_info( conn ) if conn: ibm_db.autocommit(conn, ibm_db.SQL_AUTOCOMMIT_OFF) insert = "INSERT INTO animals values (7, 'cat', 'Benji', 5.1)" ibm_db.exec_immediate(conn, insert) stmt = ibm_db.exec_immediate(conn, "SELECT breed, COUNT(breed) AS number FROM animals GROUP BY breed ORDER BY breed") if (server.DBMS_NAME[0:3] == 'IDS'): num1 = ibm_db.field_num(stmt, "id") num2 = ibm_db.field_num(stmt, "breed") num3 = ibm_db.field_num(stmt, "number") num4 = ibm_db.field_num(stmt, "NUMBER") num5 = ibm_db.field_num(stmt, "bREED") num6 = ibm_db.field_num(stmt, 8) num7 = ibm_db.field_num(stmt, 1) num8 = ibm_db.field_num(stmt, "WEIGHT") else: num1 = ibm_db.field_num(stmt, "ID") num2 = ibm_db.field_num(stmt, "BREED") num3 = ibm_db.field_num(stmt, "NUMBER") num4 = ibm_db.field_num(stmt, "number") num5 = ibm_db.field_num(stmt, "Breed") num6 = ibm_db.field_num(stmt, 8) num7 = ibm_db.field_num(stmt, 1) num8 = ibm_db.field_num(stmt, "weight") print("%s" % num1) print("int(%d)" % num2) print("int(%d)" % num3) print("%s" % num4) print("%s" % num5) print("%s" % num6) print("int(%d)" % num7) print("%s" % num8) ibm_db.rollback(conn) else: print("Connection failed.") #__END__ #__LUW_EXPECTED__ #False #int(0) #int(1) #False #False #False #int(1) #False #__ZOS_EXPECTED__ #False #int(0) #int(1) #False #False #False #int(1) #False #__SYSTEMI_EXPECTED__ #False #int(0) #int(1) #False #False #False #int(1) #False #__IDS_EXPECTED__ #False #int(0) #int(1) #False #False #False #int(1) #False

21.92

123

0.629562

317

2,192

4.11041

0.293375

0.092095

0.122794

0.159632

0.478895

0.445127

0

0.0366

0.22719

2,192

99

124

22.141414

0.732586

0.145073

0

0.133333

0

0.132313

0

0.022222

1

0.044444

false

0.022222

0.088889

0

0.155556

0.2

0

null

0

null

0

1

0

71f05726793fa3f17f84622c2fdc4b1adae30d42

2,382

py

Python

foundation/djangocms_pagebanner/cms_toolbar.py

Mindelirium/foundation

2d07e430915d696ca7376afea633692119c4d30e

[ "MIT" ]

null

foundation/djangocms_pagebanner/cms_toolbar.py

Mindelirium/foundation

2d07e430915d696ca7376afea633692119c4d30e

[ "MIT" ]

null

foundation/djangocms_pagebanner/cms_toolbar.py

Mindelirium/foundation

2d07e430915d696ca7376afea633692119c4d30e

[ "MIT" ]

null

from cms.api import get_page_draft from cms.toolbar_pool import toolbar_pool from cms.toolbar_base import CMSToolbar from cms.utils import get_cms_setting from cms.utils.permissions import has_page_change_permission from django.core.urlresolvers import reverse, NoReverseMatch from django.utils.translation import ugettext_lazy as _ from .models import PageBannerExtension _banner_change_url = 'admin:djangocms_pagebanner_pagebannerextension_change' _banner_add_url = 'admin:djangocms_pagebanner_pagebannerextension_add' @toolbar_pool.register class PageBannerExtensionToolbar(CMSToolbar): def populate(self): # always use draft if we have a page self.page = get_page_draft(self.request.current_page) if not self.page: # Nothing to do return # check global permissions if CMS_PERMISSIONS is active if get_cms_setting('PERMISSION'): has_global_current_page_change_permission = \ has_page_change_permission(self.request) else: has_global_current_page_change_permission = False # check if user has page edit permission can_change = (self.request.current_page and self.request.current_page.has_change_permission( self.request)) if has_global_current_page_change_permission or can_change: try: page_banner_extension = PageBannerExtension.objects.get( extended_object_id=self.page.id) except PageBannerExtension.DoesNotExist: page_banner_extension = None try: if page_banner_extension: url = reverse(_banner_change_url, args=(page_banner_extension.pk,)) else: url = (reverse(_banner_add_url) + '?extended_object=%s' % self.page.pk) except NoReverseMatch: # not in urls pass else: not_edit_mode = not self.toolbar.edit_mode current_page_menu = self.toolbar.get_or_create_menu('page') current_page_menu.add_modal_item(_('Page banner'), url=url, disabled=not_edit_mode)

41.789474

76

0.625105

257

2,382

5.455253

0.330739

0.062767

0.071327

0.047076

0.142653

0.077033

0

0.321998

2,382

56

77

42.535714

0.868111

0.064232

0

0.111111

0

0.066127

0.046334

0

1

0.022222

false

0.022222

0.177778

0

0.244444

0

null

0

null

0

1

0

71f0694c1e4dfc112a543268e37e44700697d2ed

7,346

py

Python

tasks/lm/models/lm.py

etri-edgeai/nn-comp-discblock

6e00a019c223508797ca91a7d5ffec7917b12c6d

[ "Apache-2.0" ]

10

2021-11-19T06:24:51.000Z

2022-02-09T15:44:00.000Z

tasks/lm/models/lm.py

etri-edgeai/nn-comp-discblock

6e00a019c223508797ca91a7d5ffec7917b12c6d

[ "Apache-2.0" ]

9

2021-10-01T11:06:27.000Z

2021-12-23T02:10:52.000Z

tasks/lm/models/lm.py

etri-edgeai/nn-comp-discblock

6e00a019c223508797ca91a7d5ffec7917b12c6d

[ "Apache-2.0" ]

2

2021-09-14T04:08:36.000Z

2021-11-19T06:24:54.000Z

import math import torch import torch.nn as nn import torch.nn.functional as F class RNNModel(nn.Module): """Container module with an encoder, a recurrent module, and a decoder.""" def __init__(self, rnn_type, ntoken, ninp, nhid, nlayers, dropout=0.5, tie_weights=False, encoder=None, decoder=None): super(RNNModel, self).__init__() self.ntoken = ntoken self.drop = nn.Dropout(dropout) if encoder is None: self.encoder = nn.Embedding(ntoken, ninp) else: self.encoder = encoder if rnn_type in ['LSTM', 'GRU']: self.rnn = getattr(nn, rnn_type)(ninp, nhid, nlayers, dropout=dropout) else: try: nonlinearity = {'RNN_TANH': 'tanh', 'RNN_RELU': 'relu'}[rnn_type] except KeyError: raise ValueError( """An invalid option for `--model` was supplied, options are ['LSTM', 'GRU', 'RNN_TANH' or 'RNN_RELU']""") self.rnn = nn.RNN(ninp, nhid, nlayers, nonlinearity=nonlinearity, dropout=dropout) if decoder is None: self.decoder = nn.Linear(nhid, ntoken) else: self.decoder = decoder # Optionally tie weights as in: # "Using the Output Embedding to Improve Language Models" (Press & Wolf 2016) # https://arxiv.org/abs/1608.05859 # and # "Tying Word Vectors and Word Classifiers: A Loss Framework for Language Modeling" (Inan et al. 2016) # https://arxiv.org/abs/1611.01462 if tie_weights: if nhid != ninp: raise ValueError('When using the tied flag, nhid must be equal to emsize') self.decoder.weight = self.encoder.weight self.rnn_type = rnn_type self.nhid = nhid self.nlayers = nlayers def init_weights(self): initrange = 0.1 if self.encoder.__class__.__name__ == "Embedding": self.encoder.weight.data.uniform_(-initrange, initrange) else: self.encoder.init_weights() if self.decoder.__class__.__name__ == "Linear": self.decoder.bias.data.zero_() self.decoder.weight.data.uniform_(-initrange, initrange) else: self.decoder.init_weights() def forward(self, input, hidden): emb = self.drop(self.encoder(input)) hidden_ = [] for h in hidden: if isinstance(h, torch.LongTensor) or isinstance(h, torch.cuda.LongTensor): h = h.to(torch.float) hidden_.append(h) output, hidden = self.rnn(emb, tuple(hidden_)) output = self.drop(output) decoded = self.decoder(output) decoded = decoded.view(-1, self.ntoken) return F.log_softmax(decoded, dim=1), hidden def init_hidden(self, bsz): weight = next(self.parameters()) if self.rnn_type == 'LSTM': return (weight.new_zeros(self.nlayers, bsz, self.nhid), weight.new_zeros(self.nlayers, bsz, self.nhid)) else: return weight.new_zeros(self.nlayers, bsz, self.nhid) # Temporarily leave PositionalEncoding module here. Will be moved somewhere else. class PositionalEncoding(nn.Module): r"""Inject some information about the relative or absolute position of the tokens in the sequence. The positional encodings have the same dimension as the embeddings, so that the two can be summed. Here, we use sine and cosine functions of different frequencies. .. math:: \text{PosEncoder}(pos, 2i) = sin(pos/10000^(2i/d_model)) \text{PosEncoder}(pos, 2i+1) = cos(pos/10000^(2i/d_model)) \text{where pos is the word position and i is the embed idx) Args: d_model: the embed dim (required). dropout: the dropout value (default=0.1). max_len: the max. length of the incoming sequence (default=5000). Examples: >>> pos_encoder = PositionalEncoding(d_model) """ def __init__(self, d_model, dropout=0.1, max_len=5000): super(PositionalEncoding, self).__init__() self.dropout = nn.Dropout(p=dropout) pe = torch.zeros(max_len, d_model) position = torch.arange(0, max_len, dtype=torch.float).unsqueeze(1) div_term = torch.exp(torch.arange(0, d_model, 2).float() * (-math.log(10000.0) / d_model)) pe[:, 0::2] = torch.sin(position * div_term) pe[:, 1::2] = torch.cos(position * div_term) pe = pe.unsqueeze(0).transpose(0, 1) self.register_buffer('pe', pe) def forward(self, x): r"""Inputs of forward function Args: x: the sequence fed to the positional encoder model (required). Shape: x: [sequence length, batch size, embed dim] output: [sequence length, batch size, embed dim] Examples: >>> output = pos_encoder(x) """ x = x + self.pe[:x.size(0), :] return self.dropout(x) class TransformerModel(nn.Module): """Container module with an encoder, a recurrent or transformer module, and a decoder.""" def __init__(self, ntoken, ninp, nhead, nhid, nlayers, dropout=0.5, encoder=None, decoder=None): super(TransformerModel, self).__init__() try: from torch.nn import TransformerEncoder, TransformerEncoderLayer except: raise ImportError('TransformerEncoder module does not exist in PyTorch 1.1 or lower.') self.model_type = 'Transformer' self.src_mask = None self.pos_encoder = PositionalEncoding(ninp, dropout) encoder_layers = TransformerEncoderLayer(ninp, nhead, nhid, dropout) self.transformer_encoder = TransformerEncoder(encoder_layers, nlayers) if encoder is None: self.encoder = nn.Embedding(ntoken, ninp) else: self.encoder = encoder self.ninp = ninp if decoder is None: self.decoder = nn.Linear(nhid, ntoken) else: self.decoder = decoder def _generate_square_subsequent_mask(self, sz): mask = (torch.triu(torch.ones(sz, sz)) == 1).transpose(0, 1) mask = mask.float().masked_fill(mask == 0, float('-inf')).masked_fill(mask == 1, float(0.0)) return mask def init_weights(self): initrange = 0.1 if self.encoder.__class__.__name__ == "Embedding": self.encoder.weight.data.uniform_(-initrange, initrange) else: self.encoder.init_weights() if self.decoder.__class__.__name__ == "Linear": self.decoder.bias.data.zero_() self.decoder.weight.data.uniform_(-initrange, initrange) else: self.decoder.init_weights() def forward(self, src, has_mask=True): if has_mask: device = src.device if self.src_mask is None or self.src_mask.size(0) != len(src): mask = self._generate_square_subsequent_mask(len(src)).to(device) self.src_mask = mask else: self.src_mask = None src = self.encoder(src) * math.sqrt(self.ninp) src = self.pos_encoder(src) output = self.transformer_encoder(src, self.src_mask) output = self.decoder(output) return F.log_softmax(output, dim=-1)

40.585635

122

0.611081

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7,346

4.745098

0.253813

0.037879

0.015152

0.023875

0.301194

0.270432

0.247016

0.23416

0.225895

0.185491

0

0.017345

0.277974

7,346

180

123

40.811111

0.803922

0.197659

0

0.351563

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0.057963

0

1

0.078125

false

0

0.046875

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0.195313

0

null

0

null

0

1

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71f3dc5d5c4a8e087378f18d43a8168ef202c67c

30,964

py

Python

pytype/analyze.py

hatal175/pytype

22150dd56c2a11f3d385a1cbb28eed985df31d72

[ "Apache-2.0" ]

null

pytype/analyze.py

hatal175/pytype

22150dd56c2a11f3d385a1cbb28eed985df31d72

[ "Apache-2.0" ]

null

pytype/analyze.py

hatal175/pytype

22150dd56c2a11f3d385a1cbb28eed985df31d72

[ "Apache-2.0" ]

null

"""Code for checking and inferring types.""" import collections import logging import re import subprocess from typing import Any, Dict, Union from pytype import abstract from pytype import abstract_utils from pytype import convert_structural from pytype import debug from pytype import function from pytype import metrics from pytype import output from pytype import special_builtins from pytype import state as frame_state from pytype import vm from pytype.overlays import typing_overlay from pytype.pytd import builtins from pytype.pytd import escape from pytype.pytd import optimize from pytype.pytd import pytd from pytype.pytd import pytd_utils from pytype.pytd import visitors from pytype.typegraph import cfg log = logging.getLogger(__name__) # Most interpreter functions (including lambdas) need to be analyzed as # stand-alone functions. The exceptions are comprehensions and generators, which # have names like "<listcomp>" and "<genexpr>". _SKIP_FUNCTION_RE = re.compile("<(?!lambda).+>$") CallRecord = collections.namedtuple( "CallRecord", ["node", "function", "signatures", "positional_arguments", "keyword_arguments", "return_value"]) # How deep to follow call chains: INIT_MAXIMUM_DEPTH = 4 # during module loading MAXIMUM_DEPTH = 3 # during non-quick analysis QUICK_CHECK_MAXIMUM_DEPTH = 2 # during quick checking QUICK_INFER_MAXIMUM_DEPTH = 1 # during quick inference class _Initializing: pass class CallTracer(vm.VirtualMachine): """Virtual machine that records all function calls. Attributes: exitpoint: A CFG node representing the program exit. Needs to be set before analyze_types. """ _CONSTRUCTORS = ("__new__", "__init__") def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) self._unknowns = {} self._calls = set() self._method_calls = set() # Used by init_class. self._instance_cache: Dict[Any, Union[_Initializing, cfg.Variable]] = {} # Used by call_init. Can differ from _instance_cache because we also call # __init__ on classes not initialized via init_class. self._initialized_instances = set() self._interpreter_functions = [] self._interpreter_classes = [] self._analyzed_functions = set() self._analyzed_classes = set() self._generated_classes = {} self.exitpoint = None def create_varargs(self, node): value = abstract.Instance(self.convert.tuple_type, self) value.merge_instance_type_parameter( node, abstract_utils.T, self.convert.create_new_unknown(node)) return value.to_variable(node) def create_kwargs(self, node): key_type = self.convert.primitive_class_instances[str].to_variable(node) value_type = self.convert.create_new_unknown(node) kwargs = abstract.Instance(self.convert.dict_type, self) kwargs.merge_instance_type_parameter(node, abstract_utils.K, key_type) kwargs.merge_instance_type_parameter(node, abstract_utils.V, value_type) return kwargs.to_variable(node) def create_method_arguments(self, node, method, use_defaults=False): """Create arguments for the given method. Creates Unknown objects as arguments for the given method. Note that we don't need to take parameter annotations into account as InterpreterFunction.call() will take care of that. Args: node: The current node. method: An abstract.InterpreterFunction. use_defaults: Whether to use parameter defaults for arguments. When True, unknown arguments are created with force=False, as it is fine to use Unsolvable rather than Unknown objects for type-checking defaults. Returns: A tuple of a node and a function.Args object. """ args = [] num_posargs = method.argcount(node) num_posargs_no_default = num_posargs - len(method.defaults) for i in range(num_posargs): default_idx = i - num_posargs_no_default if use_defaults and default_idx >= 0: arg = method.defaults[default_idx] else: arg = self.convert.create_new_unknown(node, force=not use_defaults) args.append(arg) kws = {} for key in method.signature.kwonly_params: if use_defaults and key in method.kw_defaults: kws[key] = method.kw_defaults[key] else: kws[key] = self.convert.create_new_unknown(node, force=not use_defaults) starargs = self.create_varargs(node) if method.has_varargs() else None starstarargs = self.create_kwargs(node) if method.has_kwargs() else None return node, function.Args(posargs=tuple(args), namedargs=kws, starargs=starargs, starstarargs=starstarargs) def call_function_with_args(self, node, val, args): """Call a function. Args: node: The given node. val: A cfg.Binding containing the function. args: A function.Args object. Returns: A tuple of (1) a node and (2) a cfg.Variable of the return value. """ fvar = val.AssignToNewVariable(node) with val.data.record_calls(): new_node, ret = self.call_function_in_frame(node, fvar, *args) return new_node, ret def call_function_in_frame(self, node, var, args, kwargs, starargs, starstarargs): frame = frame_state.SimpleFrame(node=node) self.push_frame(frame) log.info("Analyzing %r", [v.name for v in var.data]) state = frame_state.FrameState.init(node, self) state, ret = self.call_function_with_state( state, var, args, kwargs, starargs, starstarargs) self.pop_frame(frame) return state.node, ret def _maybe_fix_classmethod_cls_arg(self, node, cls, func, args): sig = func.signature if (args.posargs and sig.param_names and (sig.param_names[0] not in sig.annotations)): # fix "cls" parameter return args._replace( posargs=(cls.AssignToNewVariable(node),) + args.posargs[1:]) else: return args def maybe_analyze_method(self, node, val, cls=None): method = val.data fname = val.data.name if isinstance(method, abstract.INTERPRETER_FUNCTION_TYPES): self._analyzed_functions.add(method.get_first_opcode()) if (not self.options.analyze_annotated and (method.signature.has_return_annotation or method.has_overloads) and fname.rsplit(".", 1)[-1] not in self._CONSTRUCTORS): log.info("%r has annotations, not analyzing further.", fname) else: for f in method.iter_signature_functions(): node, args = self.create_method_arguments(node, f) if f.is_classmethod and cls: args = self._maybe_fix_classmethod_cls_arg(node, cls, f, args) node, _ = self.call_function_with_args(node, val, args) return node def _call_with_fake_args(self, node0, funcv): """Attempt to call the given function with made-up arguments.""" # TODO(tsudol): If expand this beyond __init__, need to handle # DictKeyMissing nodes = [] rets = [] for funcb in funcv.bindings: func = funcb.data log.info("Trying %s with fake arguments", func) if isinstance(func, abstract.INTERPRETER_FUNCTION_TYPES): node1, args = self.create_method_arguments(node0, func) # Once the args are generated, try calling the function. # call_function will check fallback_to_unsolvable if a DictKeyMissing or # FailedFunctionCall error is raised when the target function is called. # DictKeyMissing doesn't trigger call_with_fake_args, so that shouldn't # be raised again, and generating fake arguments should avoid any # FailedFunctionCall errors. To prevent an infinite recursion loop, set # fallback_to_unsolvable to False just in case. # This means any additional errors that may be raised will be passed to # the call_function that called this method in the first place. node2, ret = self.call_function(node1, funcb.AssignToNewVariable(), args, fallback_to_unsolvable=False) nodes.append(node2) rets.append(ret) if nodes: ret = self.join_variables(node0, rets) node = self.join_cfg_nodes(nodes) if ret.bindings: return node, ret else: node = node0 log.info("Unable to generate fake arguments for %s", funcv) return node, self.new_unsolvable(node) def analyze_method_var(self, node0, name, var, cls=None): log.info("Analyzing %s", name) node1 = node0.ConnectNew(name) for val in var.bindings: node2 = self.maybe_analyze_method(node1, val, cls) node2.ConnectTo(node0) return node0 def bind_method(self, node, name, methodvar, instance_var): bound = self.program.NewVariable() for m in methodvar.Data(node): if isinstance(m, special_builtins.ClassMethodInstance): m = m.func.data[0] is_cls = True else: is_cls = (m.isinstance_InterpreterFunction() and m.is_classmethod) bound.AddBinding(m.property_get(instance_var, is_cls), [], node) return bound def _instantiate_binding(self, node0, cls, container): """Instantiate a class binding.""" node1, new = cls.data.get_own_new(node0, cls) if not new or ( any(not isinstance(f, abstract.InterpreterFunction) for f in new.data)): # This assumes that any inherited __new__ method defined in a pyi file # returns an instance of the current class. return node0, cls.data.instantiate(node0, container=container) instance = self.program.NewVariable() nodes = [] for b in new.bindings: self._analyzed_functions.add(b.data.get_first_opcode()) node2, args = self.create_method_arguments(node1, b.data) args = self._maybe_fix_classmethod_cls_arg(node0, cls, b.data, args) node3 = node2.ConnectNew() node4, ret = self.call_function_with_args(node3, b, args) instance.PasteVariable(ret) nodes.append(node4) return self.join_cfg_nodes(nodes), instance def _instantiate_var(self, node, clsv, container): """Build an (dummy) instance from a class, for analyzing it.""" n = self.program.NewVariable() for cls in clsv.Bindings(node, strict=False): node, var = self._instantiate_binding(node, cls, container) n.PasteVariable(var) return node, n def _mark_maybe_missing_members(self, values): """Set maybe_missing_members to True on these values and their type params. Args: values: A list of BaseValue objects. On every instance among the values, recursively set maybe_missing_members to True on the instance and its type parameters. """ values = list(values) seen = set() while values: v = values.pop(0) if v not in seen: seen.add(v) if isinstance(v, abstract.SimpleValue): v.maybe_missing_members = True for child in v.instance_type_parameters.values(): values.extend(child.data) def init_class(self, node, cls, container=None, extra_key=None): """Instantiate a class, and also call __init__. Calling __init__ can be expensive, so this method caches its created instances. If you don't need __init__ called, use cls.instantiate instead. Args: node: The current node. cls: The class to instantiate. container: Optionally, a container to pass to the class's instantiate() method, so that type parameters in the container's template are instantiated to TypeParameterInstance. extra_key: Optionally, extra information about the location at which the instantion occurs. By default, this method keys on the current opcode and the class, which sometimes isn't enough to disambiguate callers that shouldn't get back the same cached instance. Returns: A tuple of node and instance variable. """ key = (self.frame and self.frame.current_opcode, extra_key, cls) instance = self._instance_cache.get(key) if not instance or isinstance(instance, _Initializing): clsvar = cls.to_variable(node) node, instance = self._instantiate_var(node, clsvar, container) if key in self._instance_cache: # We've encountered a recursive pattern such as # class A: # def __init__(self, x: "A"): ... # Calling __init__ again would lead to an infinite loop, so # we instead create an incomplete instance that will be # overwritten later. Note that we have to create a new # instance rather than using the one that we're already in # the process of initializing - otherwise, setting # maybe_missing_members to True would cause pytype to ignore # all attribute errors on self in __init__. self._mark_maybe_missing_members(instance.data) else: self._instance_cache[key] = _Initializing() node = self.call_init(node, instance) self._instance_cache[key] = instance return node, instance def _call_method(self, node, binding, method_name): node, method = self.attribute_handler.get_attribute( node, binding.data.get_class(), method_name, binding) if method: bound_method = self.bind_method( node, method_name, method, binding.AssignToNewVariable()) node = self.analyze_method_var(node, method_name, bound_method) return node def _call_init_on_binding(self, node, b): if isinstance(b.data, abstract.SimpleValue): for param in b.data.instance_type_parameters.values(): node = self.call_init(node, param) node = self._call_method(node, b, "__init__") cls = b.data.get_class() if isinstance(cls, abstract.InterpreterClass): # Call any additional initalizers the class has registered. for method in cls.additional_init_methods: node = self._call_method(node, b, method) return node def call_init(self, node, instance): # Call __init__ on each binding. for b in instance.bindings: if b.data in self._initialized_instances: continue self._initialized_instances.add(b.data) node = self._call_init_on_binding(node, b) return node def reinitialize_if_initialized(self, node, instance): if instance in self._initialized_instances: self._call_init_on_binding(node, instance.to_binding(node)) def analyze_class(self, node, val): self._analyzed_classes.add(val.data) node, instance = self.init_class(node, val.data) good_instances = [b for b in instance.bindings if val.data == b.data.cls] if not good_instances: # __new__ returned something that's not an instance of our class. instance = val.data.instantiate(node) node = self.call_init(node, instance) elif len(good_instances) != len(instance.bindings): # __new__ returned some extra possibilities we don't need. instance = self.join_bindings(node, good_instances) for instance_value in instance.data: val.data.register_canonical_instance(instance_value) for name, methodvar in sorted(val.data.members.items()): if name in self._CONSTRUCTORS: continue # We already called this method during initialization. b = self.bind_method(node, name, methodvar, instance) node = self.analyze_method_var(node, name, b, val) return node def analyze_function(self, node0, val): if val.data.is_attribute_of_class: # We'll analyze this function as part of a class. log.info("Analyze functions: Skipping class method %s", val.data.name) else: node1 = node0.ConnectNew(val.data.name) node2 = self.maybe_analyze_method(node1, val) node2.ConnectTo(node0) return node0 def _should_analyze_as_interpreter_function(self, data): # We record analyzed functions by opcode rather than function object. The # two ways of recording are equivalent except for closures, which are # re-generated when the variables they close over change, but we don't want # to re-analyze them. return (isinstance(data, abstract.InterpreterFunction) and not data.is_overload and not data.is_class_builder and data.get_first_opcode() not in self._analyzed_functions and not _SKIP_FUNCTION_RE.search(data.name)) def analyze_toplevel(self, node, defs): for name, var in sorted(defs.items()): # sort, for determinicity if not self._is_typing_member(name, var): for value in var.bindings: if isinstance(value.data, abstract.InterpreterClass): new_node = self.analyze_class(node, value) elif (isinstance(value.data, abstract.INTERPRETER_FUNCTION_TYPES) and not value.data.is_overload): new_node = self.analyze_function(node, value) else: continue if new_node is not node: new_node.ConnectTo(node) # Now go through all functions and classes we haven't analyzed yet. # These are typically hidden under a decorator. # Go through classes first so that the `is_attribute_of_class` will # be set for all functions in class. for c in self._interpreter_classes: for value in c.bindings: if (isinstance(value.data, abstract.InterpreterClass) and value.data not in self._analyzed_classes): node = self.analyze_class(node, value) for f in self._interpreter_functions: for value in f.bindings: if self._should_analyze_as_interpreter_function(value.data): node = self.analyze_function(node, value) return node def analyze(self, node, defs, maximum_depth): assert not self.frame self.maximum_depth = maximum_depth self._analyzing = True node = node.ConnectNew(name="Analyze") return self.analyze_toplevel(node, defs) def trace_unknown(self, name, unknown_binding): self._unknowns[name] = unknown_binding def trace_call(self, node, func, sigs, posargs, namedargs, result): """Add an entry into the call trace. Args: node: The CFG node right after this function call. func: A cfg.Binding of a function that was called. sigs: The signatures that the function might have been called with. posargs: The positional arguments, an iterable over cfg.Value. namedargs: The keyword arguments, a dict mapping str to cfg.Value. result: A Variable of the possible result values. """ log.debug("Logging call to %r with %d args, return %r", func, len(posargs), result) args = tuple(posargs) kwargs = tuple((namedargs or {}).items()) record = CallRecord(node, func, sigs, args, kwargs, result) if isinstance(func.data, abstract.BoundPyTDFunction): self._method_calls.add(record) elif isinstance(func.data, abstract.PyTDFunction): self._calls.add(record) def trace_functiondef(self, f): self._interpreter_functions.append(f) def trace_classdef(self, c): self._interpreter_classes.append(c) def trace_namedtuple(self, nt): # All namedtuple instances with the same name are equal, so it's fine to # overwrite previous instances. self._generated_classes[nt.name] = nt def pytd_classes_for_unknowns(self): classes = [] for name, val in self._unknowns.items(): if val in val.variable.Filter(self.exitpoint, strict=False): classes.append(val.data.to_structural_def(self.exitpoint, name)) return classes def pytd_for_types(self, defs): # If a variable is annotated, we'll always output that type. annotated_names = set() data = [] pytd_convert = self.convert.pytd_convert annots = abstract_utils.get_annotations_dict(defs) for name, t in pytd_convert.annotations_to_instance_types( self.exitpoint, annots): annotated_names.add(name) data.append(pytd.Constant(name, t)) for name, var in defs.items(): if (name in output.TOP_LEVEL_IGNORE or name in annotated_names or self._is_typing_member(name, var)): continue options = var.FilteredData(self.exitpoint, strict=False) if (len(options) > 1 and not all(isinstance(o, abstract.FUNCTION_TYPES) for o in options)): # It's ambiguous whether this is a type, a function or something # else, so encode it as a constant. combined_types = pytd_utils.JoinTypes(t.to_type(self.exitpoint) for t in options) data.append(pytd.Constant(name, combined_types)) elif options: for option in options: try: d = option.to_pytd_def(self.exitpoint, name) # Deep definition except NotImplementedError: d = option.to_type(self.exitpoint) # Type only if isinstance(d, pytd.NothingType): if isinstance(option, abstract.Empty): d = pytd.AnythingType() else: assert isinstance(option, typing_overlay.NoReturn) if isinstance(d, pytd.Type) and not isinstance(d, pytd.TypeParameter): data.append(pytd.Constant(name, d)) else: data.append(d) else: log.error("No visible options for %s", name) data.append(pytd.Constant(name, pytd.AnythingType())) return pytd_utils.WrapTypeDeclUnit("inferred", data) @staticmethod def _call_traces_to_function(call_traces, name_transform=lambda x: x): funcs = collections.defaultdict(pytd_utils.OrderedSet) for node, func, sigs, args, kws, retvar in call_traces: # The lengths may be different in the presence of optional and kw args. arg_names = max((sig.get_positional_names() for sig in sigs), key=len) for i in range(len(arg_names)): if not isinstance(func.data, abstract.BoundFunction) or i > 0: arg_names[i] = function.argname(i) arg_types = (a.data.to_type(node) for a in args) ret = pytd_utils.JoinTypes(t.to_type(node) for t in retvar.data) starargs = None starstarargs = None funcs[func.data.name].add(pytd.Signature( tuple(pytd.Parameter(n, t, False, False, None) for n, t in zip(arg_names, arg_types)) + tuple(pytd.Parameter(name, a.data.to_type(node), False, False, None) for name, a in kws), starargs, starstarargs, ret, exceptions=(), template=())) functions = [] for name, signatures in funcs.items(): functions.append(pytd.Function(name_transform(name), tuple(signatures), pytd.MethodTypes.METHOD)) return functions def _is_typing_member(self, name, var): for module_name in ("typing", "typing_extensions"): if module_name not in self.loaded_overlays: continue module = self.loaded_overlays[module_name].get_module(name) if name in module.members and module.members[name].data == var.data: return True return False def pytd_functions_for_call_traces(self): return self._call_traces_to_function(self._calls, escape.pack_partial) def pytd_classes_for_call_traces(self): class_to_records = collections.defaultdict(list) for call_record in self._method_calls: args = call_record.positional_arguments if not any(isinstance(a.data, abstract.Unknown) for a in args): # We don't need to record call signatures that don't involve # unknowns - there's nothing to solve for. continue cls = args[0].data.get_class() if isinstance(cls, abstract.PyTDClass): class_to_records[cls].append(call_record) classes = [] for cls, call_records in class_to_records.items(): full_name = cls.module + "." + cls.name if cls.module else cls.name classes.append(pytd.Class( name=escape.pack_partial(full_name), metaclass=None, parents=(pytd.NamedType("builtins.object"),), # not used in solver methods=tuple(self._call_traces_to_function(call_records)), constants=(), classes=(), decorators=(), slots=None, template=(), )) return classes def pytd_classes_for_namedtuple_instances(self): return tuple(v.generate_ast() for v in self._generated_classes.values()) def compute_types(self, defs): classes = (tuple(self.pytd_classes_for_unknowns()) + tuple(self.pytd_classes_for_call_traces()) + self.pytd_classes_for_namedtuple_instances()) functions = tuple(self.pytd_functions_for_call_traces()) aliases = () # aliases are instead recorded as constants ty = pytd_utils.Concat( self.pytd_for_types(defs), pytd_utils.CreateModule("unknowns", classes=classes, functions=functions, aliases=aliases)) ty = ty.Visit(optimize.CombineReturnsAndExceptions()) ty = ty.Visit(optimize.PullInMethodClasses()) ty = ty.Visit(visitors.DefaceUnresolved( [ty, self.loader.concat_all()], escape.UNKNOWN)) return ty.Visit(visitors.AdjustTypeParameters()) def _check_return(self, node, actual, formal): if not self.options.report_errors: return True views = abstract_utils.get_views([actual], node) # Check for typevars in the return value first, since bad_matches # expects not to get any. bad = [view for view in views if actual in view and view[actual].data.formal] if not bad: bad = self.matcher.bad_matches(actual, formal, node) if bad: self.errorlog.bad_return_type( self.frames, node, formal, actual, bad) return not bad def check_types(src, filename, errorlog, options, loader, deep=True, init_maximum_depth=INIT_MAXIMUM_DEPTH, maximum_depth=None, **kwargs): """Verify the Python code.""" tracer = CallTracer(errorlog=errorlog, options=options, generate_unknowns=False, loader=loader, **kwargs) loc, defs = tracer.run_program(src, filename, init_maximum_depth) snapshotter = metrics.get_metric("memory", metrics.Snapshot) snapshotter.take_snapshot("analyze:check_types:tracer") if deep: if maximum_depth is None: maximum_depth = ( QUICK_CHECK_MAXIMUM_DEPTH if options.quick else MAXIMUM_DEPTH) tracer.analyze(loc, defs, maximum_depth=maximum_depth) snapshotter.take_snapshot("analyze:check_types:post") _maybe_output_debug(options, tracer.program) def infer_types(src, errorlog, options, loader, filename=None, deep=True, init_maximum_depth=INIT_MAXIMUM_DEPTH, show_library_calls=False, maximum_depth=None, tracer_vm=None, **kwargs): """Given Python source return its types. Args: src: A string containing Python source code. errorlog: Where error messages go. Instance of errors.ErrorLog. options: config.Options object loader: A load_pytd.Loader instance to load PYI information. filename: Filename of the program we're parsing. deep: If True, analyze all functions, even the ones not called by the main execution flow. init_maximum_depth: Depth of analysis during module loading. show_library_calls: If True, call traces are kept in the output. maximum_depth: Depth of the analysis. Default: unlimited. tracer_vm: An instance of CallTracer, in case the caller wants to instantiate and retain the vm used for type inference. **kwargs: Additional parameters to pass to vm.VirtualMachine Returns: A tuple of (ast: TypeDeclUnit, builtins: TypeDeclUnit) Raises: AssertionError: In case of a bad parameter combination. """ # If the caller has passed in a vm, use that. if tracer_vm: assert isinstance(tracer_vm, CallTracer) tracer = tracer_vm else: tracer = CallTracer(errorlog=errorlog, options=options, generate_unknowns=options.protocols, store_all_calls=not deep, loader=loader, **kwargs) loc, defs = tracer.run_program(src, filename, init_maximum_depth) log.info("===Done running definitions and module-level code===") snapshotter = metrics.get_metric("memory", metrics.Snapshot) snapshotter.take_snapshot("analyze:infer_types:tracer") if deep: if maximum_depth is None: if not options.quick: maximum_depth = MAXIMUM_DEPTH elif options.analyze_annotated: # Since there's no point in analyzing annotated functions for inference, # the presence of this option means that the user wants checking, too. maximum_depth = QUICK_CHECK_MAXIMUM_DEPTH else: maximum_depth = QUICK_INFER_MAXIMUM_DEPTH tracer.exitpoint = tracer.analyze(loc, defs, maximum_depth) else: tracer.exitpoint = loc snapshotter.take_snapshot("analyze:infer_types:post") ast = tracer.compute_types(defs) ast = tracer.loader.resolve_ast(ast) if tracer.has_unknown_wildcard_imports or any( a in defs for a in abstract_utils.DYNAMIC_ATTRIBUTE_MARKERS): if "__getattr__" not in ast: ast = pytd_utils.Concat( ast, builtins.GetDefaultAst(options.python_version)) # If merged with other if statement, triggers a ValueError: Unresolved class # when attempts to load from the protocols file if options.protocols: protocols_pytd = tracer.loader.import_name("protocols") else: protocols_pytd = None builtins_pytd = tracer.loader.concat_all() # Insert type parameters, where appropriate ast = ast.Visit(visitors.CreateTypeParametersForSignatures()) if options.protocols: log.info("=========== PyTD to solve =============\n%s", pytd_utils.Print(ast)) ast = convert_structural.convert_pytd(ast, builtins_pytd, protocols_pytd) elif not show_library_calls: log.info("Solving is turned off. Discarding call traces.") # Rename remaining "~unknown" to "?" ast = ast.Visit(visitors.RemoveUnknownClasses()) # Remove "~list" etc.: ast = convert_structural.extract_local(ast) _maybe_output_debug(options, tracer.program) return ast, builtins_pytd def _maybe_output_debug(options, program): """Maybe emit debugging output.""" if options.output_cfg or options.output_typegraph: dot = debug.program_to_dot(program, set([]), bool(options.output_cfg)) svg_file = options.output_cfg or options.output_typegraph proc = subprocess.Popen(["/usr/bin/dot", "-T", "svg", "-o", svg_file], stdin=subprocess.PIPE, universal_newlines=True) (_, stderr) = proc.communicate(dot) if stderr: log.info("Failed to create %s: %s", svg_file, stderr) if options.output_debug: text = debug.program_to_text(program) if options.output_debug == "-": log.info("=========== Program Dump =============\n%s", text) else: with options.open_function(options.output_debug, "w") as fi: fi.write(text)

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null

0

1

0

71f490ebabe7d689d377fda1a39b6fe3eaf67bee

3,979

py

Python

src/cupcake/post_isoseq_cluster/demux_by_barcode_groups.py

milescsmith/cDNA_Cupcake

776d841c69fc6d8b3dce95bb9f076546bc0429c0

[ "BSD-3-Clause-Clear" ]

null

src/cupcake/post_isoseq_cluster/demux_by_barcode_groups.py

milescsmith/cDNA_Cupcake

776d841c69fc6d8b3dce95bb9f076546bc0429c0

[ "BSD-3-Clause-Clear" ]

null

src/cupcake/post_isoseq_cluster/demux_by_barcode_groups.py

milescsmith/cDNA_Cupcake

776d841c69fc6d8b3dce95bb9f076546bc0429c0

[ "BSD-3-Clause-Clear" ]

null

#!/usr/bin/env python __author__ = "etseng@pacb.com" """ Given a pooled input GFF + demux CSV file, write out per-{barcode group} GFFs If input fasta/fastq is given, optionally also output per-{barcode group} FASTA/FASTQ """ import re from collections import defaultdict from csv import DictReader from typing import Optional import typer from Bio import SeqIO import cupcake.sequence.GFF as GFF from cupcake import version_callback from cupcake import cupcake_logger as logger rex_pbid = re.compile(r"(PB.\d+.\d+)(|\S+)") app = typer.Typer(name="cupcake.post_isoseq_cluster.demux_by_barcode_groups") def get_type_fafq(in_filename): in_filename = in_filename.upper() if in_filename.endswith(".FA") or in_filename.endswith("FASTA"): return "fasta" elif in_filename.endswith(".FQ") or in_filename.endswith("FASTQ"): return "fastq" else: raise Exception( f"Unrecognized file suffix .{in_filename[in_filename.find('.'):]}! Must end with .fasta or .fastq!" ) def regroup_gff( pooled_gff, demux_count_file, output_prefix, out_group_dict, in_fafq=None ): """ :param pooled_sam: SAM file :param demux_count_file: comma-delimited per-barcode count file :param output_prefix: output prefix for GFF :param out_group_dict: dict of barcode name --> group to be long in (ex: {'EM1':'EM', 'EM2':'EM'}) :param in_fafq: optional fasta/fastq that was input to SAM """ if in_fafq is not None: type_fafq = get_type_fafq(in_fafq) in_tissue = defaultdict( lambda: set() ) # pbid --> list of tissue it is in (EM, END, R) for r in DictReader(open(demux_count_file), delimiter=","): for k, v in r.items(): if k != "id" and int(v) > 0: in_tissue[r["id"]].add(k) # in_tissue = dict(in_tissue) handles = {} handles_fafq = {} for g in out_group_dict.values(): handles[g] = open(f"{output_prefix}_{g}_only.gff", "w") if in_fafq is not None: handles_fafq[g] = open(f"{output_prefix}_{g}_only.{type_fafq}", "w") if in_fafq is not None: fafq_dict = SeqIO.to_dict(SeqIO.parse(open(in_fafq), type_fafq)) fafq_dict_keys = list(fafq_dict.keys()) for k in fafq_dict_keys: m = rex_pbid.match(k) if m is not None: fafq_dict[m.group(1)] = fafq_dict[k] reader = GFF.collapseGFFReader(pooled_gff) for r in reader: groups_to_write_in = set() pbid = r.seqid if pbid not in in_tissue: logger.info( f"WARNING: {pbid} does not belong to any group indicated by outgroup_dict" ) for tissue in in_tissue[pbid]: groups_to_write_in.add(out_group_dict[tissue]) for g in groups_to_write_in: GFF.write_collapseGFF_format(handles[g], r) if in_fafq is not None: SeqIO.write(fafq_dict[pbid], handles_fafq[g], type_fafq) @app.command(name="") def main( pooled_gff: str = typer.Argument(..., help="Pooled GFF file"), demux_count_file: str = typer.Argument(..., help="Demux count file"), output_prefix: str = typer.Argument(..., help="Output prefix for GFF outputs"), outgroup_dict: str = typer.Argument(..., help="Tuples indicating barcode grouping"), pooled_fastx: Optional[str] = typer.Option( None, help="Pooled FASTA/FASTQ (optional, if given, will also output demux fa/fq)", ), version: bool = typer.Option( None, "--version", callback=version_callback, is_eager=True, help="Prints the version of the SQANTI3 package.", ), ) -> None: tmp = eval(outgroup_dict) out_group_dict = dict([tmp]) if len(tmp) == 1 else dict(tmp) regroup_gff( pooled_gff, demux_count_file, output_prefix, out_group_dict, pooled_fastx, ) if __name__ == "__main__": typer.run(main)

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71f49ed361f20a67913d6d3671205fa5c226035f

5,168

py

Python

vll/data/circle_dataset.py

paulhfu/3dcv-students

f8d42c985cf33903170733b0c8f6a2199099553c

[ "MIT" ]

4

2020-04-21T21:40:13.000Z

2022-02-13T18:18:13.000Z

vll/data/circle_dataset.py

paulhfu/3dcv-students

f8d42c985cf33903170733b0c8f6a2199099553c

[ "MIT" ]

1

2022-02-03T11:24:07.000Z

vll/data/circle_dataset.py

paulhfu/3dcv-students

f8d42c985cf33903170733b0c8f6a2199099553c

[ "MIT" ]

8

2020-04-22T10:24:27.000Z

2022-01-13T16:25:52.000Z

import random import numpy as np import math from skimage.draw import line, line_aa, circle, set_color, circle_perimeter_aa from skimage.io import imsave from skimage.util import random_noise maxSlope = 10 # restrict the maximum slope of generated lines for stability minLength = 20 # restrict the minimum length of line segments class ICircleDataset: ''' Generator of circle segment images. Images will have 1 random circle each, filled with noise and distractor lines. Class also offers functionality for drawing line parameters, hypotheses and point predictions. ''' def __init__(self, imgW = 64, imgH = 64, margin = -5, bg_clr = 0.5): ''' Constructor. imgW -- image width (default 64) imgH -- image height (default 64) margin -- lines segments are sampled within this margin, negative value means that a line segment can start or end outside the image (default -5) bg_clr -- background intensity (default 0.5) ''' self.imgW = imgW self.imgH = imgH self.margin = margin self.bg_clr = bg_clr def draw_circle(self, data, cX, cY, r, clr, alpha=1.0): ''' Draw a circle with the given color and opacity. data -- image to draw to cX -- x value of circle center cY -- y value of circle center r -- radius of circle clr -- line color, triple of values alpha -- opacity (default 1.0) ''' cY = int(cY * self.imgH) cX = int(cX * self.imgW) r = int(r * self.imgW) rr, cc, val = circle_perimeter_aa(cY, cX, r) set_color(data, (rr, cc), clr, val) def draw_hyps(self, labels, scores, data=None): ''' Draw a set of line hypothesis for a batch of images. labels -- line parameters, array shape (NxMx2) where N is the number of images in the batch M is the number of hypotheses per image 2 is the number of line parameters (intercept, slope) scores -- hypotheses scores, array shape (NxM), see above, higher score will be drawn with higher opacity data -- batch of images to draw to, if empty a new batch wil be created according to the shape of labels ''' n = labels.shape[0] # number of images m = labels.shape[1] # number of hypotheses if data is None: # create new batch of images data = np.zeros((n, self.imgH, self.imgW, 3), dtype=np.float32) data.fill(self.bg_clr) clr = (0, 0, 1) for i in range (0, n): for j in range (0, m): lY1 = int(labels[i, j, 0] * self.imgH) lY2 = int(labels[i, j, 1] * self.imgW + labels[i, j, 0] * self.imgH) self.draw_line(data[i], 0, lY1, self.imgW, lY2, clr, scores[i, j]) return data def draw_models(self, labels, data=None, correct=None): ''' Draw circles for a batch of images. labels -- circle parameters, array shape (Nx3) where N is the number of images in the batch 3 is the number of circles parameters (center x, center y, radius) data -- batch of images to draw to, if empty a new batch wil be created according to the shape of labels and circles will be green, circles will be blue otherwise correct -- array of shape (N) indicating whether a circle estimate is correct ''' n = labels.shape[0] if data is None: data = np.zeros((n, self.imgH, self.imgW, 3), dtype=np.float32) data.fill(self.bg_clr) clr = (0, 1, 0) else: clr = (0, 0, 1) for i in range (0, n): self.draw_circle(data[i], labels[i, 0], labels[i, 1], labels[i, 2], clr) if correct is not None: # draw border green if estiamte is correct, red otherwise if correct[i]: borderclr = (0, 1, 0) else: borderclr = (1, 0, 0) set_color(data[i], line(0, 0, 0, self.imgW-1), borderclr) set_color(data[i], line(0, 0, self.imgH-1, 0), borderclr) set_color(data[i], line(self.imgH-1, 0, self.imgH-1, self.imgW-1), borderclr) set_color(data[i], line(0, self.imgW-1, self.imgH-1, self.imgW-1), borderclr) return data def draw_points(self, points, data, inliers=None): ''' Draw 2D points for a batch of images. points -- 2D points, array shape (Nx2xM) where N is the number of images in the batch 2 is the number of point dimensions (x, y) M is the number of points data -- batch of images to draw to inliers -- soft inlier score for each point, if given and score < 0.5 point will be drawn green, red otherwise ''' n = points.shape[0] # number of images m = points.shape[2] # number of points for i in range (0, n): for j in range(0, m): clr = (0.2, 0.2, 0.2) # draw predicted points as dark circles if inliers is not None and inliers[i, j] > 0.5: clr = (0.7, 0.7, 0.7) # draw inliers as light circles r = int(points[i, 0, j] * self.imgH) c = int(points[i, 1, j] * self.imgW) rr, cc = circle(r, c, 2) set_color(data[i], (rr, cc), clr) return data def samples(self, n): ''' Create new input images of random line segments and distractors along with ground truth parameters. n -- number of images to create ''' data = np.zeros((n, self.imgH, self.imgW, 3), dtype=np.float32) data.fill(self.bg_clr) labels = np.zeros((n, 3), dtype=np.float32) for i in range (0, n): data[i] = random_noise(data[i], mode='speckle') return data, labels

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0

0.239437

0

null

0

null

0

1

0

71f546859f563e461fa98070b804316bbbaa69c8

1,030

py

Python

anlogger/logger.py

anttin/anlogger

dfa7be7ba2f4651507b188f986c10bab9bd7460e

[ "MIT" ]

null

anlogger/logger.py

anttin/anlogger

dfa7be7ba2f4651507b188f986c10bab9bd7460e

[ "MIT" ]

null

anlogger/logger.py

anttin/anlogger

dfa7be7ba2f4651507b188f986c10bab9bd7460e

[ "MIT" ]

null

import logging import logging.handlers import os class Logger(object): def __init__(self, name, default_loglevel='INFO', fmt=None, syslog=None): self.name = name self.syslog = syslog self.fmt = fmt if fmt is not None else "%(asctime)-15s %(name)s %(levelname)s %(message)s" if 'LOGLEVEL' in os.environ: self.level = os.environ['LOGLEVEL'].upper() else: self.level = default_loglevel.upper() logging.basicConfig(format=self.fmt) self.logger = logging.getLogger(self.name) self.logger.setLevel(self.level) if self.syslog is not None and self.syslog not in (False, 0): if isinstance(self.syslog, (list, tuple)): _addr = tuple(self.syslog) elif isinstance(self.syslog, str): _addr = self.syslog else: _addr = "/dev/log" if os.path.exists("/dev/log") else None if _addr is not None: handler = logging.handlers.SysLogHandler(address=_addr) self.logger.addHandler(handler) def get(self): return self.logger

28.611111

94

0.659223

141

1,030

4.737589

0.375887

0.10479

0.040419

0

0.003722

0.217476

1,030

35

95

29.428571

0.825062

0

0.074074

0

0.082524

0

1

0.074074

false

0

0.111111

0.037037

0.259259

0

null

0

null

0

1

0

71f66963cc795d3d06ec835c6cc0e9a8392f9d65

729

py

Python

lib/env/trade/BaseTradeStrategy.py

devas123/Bitcoin-Trader-RL

097cb0ba7428b2c4f997bdb0425a6153c23f9c83

[ "MIT" ]

null

lib/env/trade/BaseTradeStrategy.py

devas123/Bitcoin-Trader-RL

097cb0ba7428b2c4f997bdb0425a6153c23f9c83

[ "MIT" ]

null

lib/env/trade/BaseTradeStrategy.py

devas123/Bitcoin-Trader-RL

097cb0ba7428b2c4f997bdb0425a6153c23f9c83

[ "MIT" ]

null

from abc import ABCMeta, abstractmethod from typing import Tuple, Callable class BaseTradeStrategy(object, metaclass=ABCMeta): @abstractmethod def __init__(self, commissionPercent: float, maxSlippagePercent: float, base_precision: int, asset_precision: int, min_cost_limit: float, min_amount_limit: float): pass @abstractmethod def trade(self, action: int, n_discrete_actions: int, balance: float, asset_held: float, current_price: Callable[[str], float]) -> Tuple[float, float, float, float]: raise NotImplementedError()

30.375

90

0.577503

65

729

6.261538

0.6

0.07371

0

0.352538

729

23

91

31.695652

0.862288

0

0.1

0

1

0.1

false

0.05

0.1

0

0.25

0

null

0

null

0

1

0

71f9440eb1c326307f7552af69580f96b76f02f9

3,283

py

Python

configs/_base_/datasets/stvqa_dataset.py

linxi1158/iMIX

af87a17275f02c94932bb2e29f132a84db812002

[ "Apache-2.0" ]

23

2021-06-26T08:45:19.000Z

2022-03-02T02:13:33.000Z

configs/_base_/datasets/stvqa_dataset.py

XChuanLee/iMIX

99898de97ef8b45462ca1d6bf2542e423a73d769

[ "Apache-2.0" ]

null

configs/_base_/datasets/stvqa_dataset.py

XChuanLee/iMIX

99898de97ef8b45462ca1d6bf2542e423a73d769

[ "Apache-2.0" ]

9

2021-06-10T02:36:20.000Z

2021-11-09T02:18:16.000Z

dataset_type = 'STVQADATASET' data_root = '/home/datasets/mix_data/iMIX/' feature_path = 'data/datasets/stvqa/defaults/features/' ocr_feature_path = 'data/datasets/stvqa/defaults/ocr_features/' annotation_path = 'data/datasets/stvqa/defaults/annotations/' vocab_path = 'data/datasets/stvqa/defaults/extras/vocabs/' train_datasets = ['train'] test_datasets = ['val'] reader_train_cfg = dict( type='STVQAREADER', card='default', mix_features=dict( train=data_root + feature_path + 'detectron.lmdb', val=data_root + feature_path + 'detectron.lmdb', test=data_root + feature_path + 'detectron.lmdb', ), mix_ocr_features=dict( train=data_root + ocr_feature_path + 'ocr_en_frcn_features.lmdb', val=data_root + ocr_feature_path + 'ocr_en_frcn_features.lmdb', test=data_root + ocr_feature_path + 'ocr_en_frcn_features.lmdb', ), mix_annotations=dict( train=data_root + annotation_path + 'imdb_subtrain.npy', val=data_root + annotation_path + 'imdb_subval.npy', test=data_root + annotation_path + 'imdb_test_task3.npy', ), datasets=train_datasets) reader_test_cfg = dict( type='STVQAREADER', card='default', mix_features=dict( train=data_root + feature_path + 'detectron.lmdb', val=data_root + feature_path + 'detectron.lmdb', test=data_root + feature_path + 'detectron.lmdb', ), mix_ocr_features=dict( train=data_root + ocr_feature_path + 'ocr_en_frcn_features.lmdb', val=data_root + ocr_feature_path + 'ocr_en_frcn_features.lmdb', test=data_root + ocr_feature_path + 'ocr_en_frcn_features.lmdb', ), mix_annotations=dict( train=data_root + annotation_path + 'imdb_subtrain.npy', val=data_root + annotation_path + 'imdb_subval.npy', test=data_root + annotation_path + 'imdb_test_task3.npy', ), datasets=train_datasets) info_cpler_cfg = dict( type='STVQAInfoCpler', glove_weights=dict( glove6b50d=data_root + 'glove/glove.6B.50d.txt.pt', glove6b100d=data_root + 'glove/glove.6B.100d.txt.pt', glove6b200d=data_root + 'glove/glove.6B.200d.txt.pt', glove6b300d=data_root + 'glove/glove.6B.300d.txt.pt', ), fasttext_weights=dict( wiki300d1m=data_root + 'fasttext/wiki-news-300d-1M.vec', wiki300d1msub=data_root + 'fasttext/wiki-news-300d-1M-subword.vec', wiki_bin=data_root + 'fasttext/wiki.en.bin', ), tokenizer='/home/datasets/VQA/bert/' + 'bert-base-uncased-vocab.txt', mix_vocab=dict( answers_st_5k=data_root + vocab_path + 'fixed_answer_vocab_stvqa_5k.txt', vocabulary_100k=data_root + vocab_path + 'vocabulary_100k.txt', ), max_seg_lenth=20, max_ocr_lenth=10, word_mask_ratio=0.0, vocab_name='vocabulary_100k', vocab_answer_name='answers_st_5k', glove_name='glove6b300d', fasttext_name='wiki_bin', if_bert=True, ) train_data = dict( samples_per_gpu=16, workers_per_gpu=1, data=dict(type=dataset_type, reader=reader_train_cfg, info_cpler=info_cpler_cfg, limit_nums=800)) test_data = dict( samples_per_gpu=16, workers_per_gpu=1, data=dict(type=dataset_type, reader=reader_test_cfg, info_cpler=info_cpler_cfg), )

36.88764

101

0.696924

443

3,283

4.810384

0.216704

0.105115

0.045988

0.047865

0.663538

0.59878

0.542468

0.514313

0

0.029346

0.180018

3,283

88

102

37.306818

0.762259

0

0.52439

0

0.285714

0.181541

0.012195

0

1

0

false

0

null

0

null

0

1

0

71fa3b7f37795303ef477432b9138d2cfeb1171c

320

py

Python

code/Line.py

manno-xx/FutureLearnRobotBuggy

d5f0172597ad88d6a8b883b0b16d425a76edfb0b

[ "MIT" ]

null

code/Line.py

manno-xx/FutureLearnRobotBuggy

d5f0172597ad88d6a8b883b0b16d425a76edfb0b

[ "MIT" ]

null

code/Line.py

manno-xx/FutureLearnRobotBuggy

d5f0172597ad88d6a8b883b0b16d425a76edfb0b

[ "MIT" ]

null

#LineSensor test from gpiozero import LineSensor from time import sleep from signal import pause def lineDetected(): print('line detected') def noLineDetected(): print('no line detected') sensor = LineSensor(14) sensor.when_line = lineDetected sensor.when_no_line = noLineDetected pause() sensor.close()

14.545455

36

0.759375

40

320

6

0.5

0.1

0

0.007407

0.15625

320

21

37

15.238095

0.881481

0.046875

0

0.095395

0

1

0.166667

false

0

0.25

0

0.416667

0.166667

0

null

0

null

0

1

0

71fafdbd17b589475cd452d3837ecd482b296f0c

8,468

py

Python

combo/search/discrete/policy.py

zhangkunliang/BayesOptimization

6d78c9e9f96239b0dbb85650a0d878e9410158ec

[ "MIT" ]

139

2016-02-18T02:31:04.000Z

2022-02-18T10:38:06.000Z

combo/search/discrete/policy.py

zhangkunliang/BayesOptimization

6d78c9e9f96239b0dbb85650a0d878e9410158ec

[ "MIT" ]

8

2016-04-18T08:10:44.000Z

2020-12-30T08:49:33.000Z

combo/search/discrete/policy.py

zhangkunliang/BayesOptimization

6d78c9e9f96239b0dbb85650a0d878e9410158ec

[ "MIT" ]

50

2016-05-21T01:17:23.000Z

2022-02-18T01:27:41.000Z

import numpy as np import copy import combo.misc import cPickle as pickle from results import history from .. import utility from ...variable import variable from ..call_simulator import call_simulator from ... import predictor from ...gp import predictor as gp_predictor from ...blm import predictor as blm_predictor import combo.search.score MAX_SEACH = int(20000) class policy: def __init__(self, test_X, config=None): self.predictor = None self.training = variable() self.test = self._set_test(test_X) self.actions = np.arange(0, self.test.X.shape[0]) self.history = history() self.config = self._set_config(config) def set_seed(self, seed): self.seed = seed np.random.seed(self.seed) def delete_actions(self, index, actions=None): actions = self._set_unchosed_actions(actions) return np.delete(actions, index) def write(self, action, t, X=None): if X is None: X = self.test.X[action, :] Z = self.test.Z[action, :] if self.test.Z is not None else None else: Z = self.predictor.get_basis(X) \ if self.predictor is not None else None self.new_data = variable(X, t, Z) self.history.write(t, action) self.training.add(X=X, t=t, Z=Z) def random_search(self, max_num_probes, num_search_each_probe=1, simulator=None, is_disp=True): N = int(num_search_each_probe) if int(max_num_probes) * N > len(self.actions): raise ValueError('max_num_probes * num_search_each_probe must \ be smaller than the length of candidates') if is_disp: utility.show_interactive_mode(simulator, self.history) for n in xrange(0, max_num_probes): if is_disp and N > 1: utility.show_start_message_multi_search(self.history.num_runs) action = self.get_random_action(N) if simulator is None: return action t, X = call_simulator(simulator, action) self.write(action, t, X) if is_disp: utility.show_search_results(self.history, N) return copy.deepcopy(self.history) def bayes_search(self, training=None, max_num_probes=None, num_search_each_probe=1, predictor=None, is_disp=True, simulator=None, score='TS', interval=0, num_rand_basis=0): if max_num_probes is None: max_num_probes = 1 simulator = None is_rand_expans = False if num_rand_basis == 0 else True self.training = self._set_training(training) if predictor is None: self.predictor = self._init_predictor(is_rand_expans) else: self.predictor = predictor N = int(num_search_each_probe) for n in xrange(max_num_probes): if utility.is_learning(n, interval): self.predictor.fit(self.training, num_rand_basis) self.test.Z = self.predictor.get_basis(self.test.X) self.training.Z = self.predictor.get_basis(self.training.X) self.predictor.prepare(self.training) else: try: self.predictor.update(self.training, self.new_data) except: self.predictor.prepare(self.training) if num_search_each_probe != 1: utility.show_start_message_multi_search(self.history.num_runs, score) K = self.config.search.multi_probe_num_sampling alpha = self.config.search.alpha action = self.get_actions(score, N, K, alpha) if simulator is None: return action t, X = call_simulator(simulator, action) self.write(action, t, X) if is_disp: utility.show_search_results(self.history, N) return copy.deepcopy(self.history) def get_score(self, mode, predictor=None, training=None, alpha=1): self._set_training(training) self._set_predictor(predictor) actions = self.actions test = self.test.get_subset(actions) if mode == 'EI': f = combo.search.score.EI(predictor, training, test) elif mode == 'PI': f = combo.search.score.PI(predictor, training, test) elif mode == 'TS': f = combo.search.score.TS(predictor, training, test, alpha) else: raise NotImplementedError('mode must be EI, PI or TS.') return f def get_marginal_score(self, mode, chosed_actions, N, alpha): f = np.zeros((N, len(self.actions))) new_test = self.test.get_subset(chosed_actions) virtual_t \ = self.predictor.get_predict_samples(self.training, new_test, N) for n in xrange(N): predictor = copy.deepcopy(self.predictor) train = copy.deepcopy(self.training) virtual_train = new_test virtual_train.t = virtual_t[n, :] if virtual_train.Z is None: train.add(virtual_train.X, virtual_train.t) else: train.add(virtual_train.X, virtual_train.t, virtual_train.Z) try: predictor.update(train, virtual_train) except: predictor.prepare(train) f[n, :] = self.get_score(mode, predictor, train) return f def get_actions(self, mode, N, K, alpha): f = self.get_score(mode, self.predictor, self.training, alpha) temp = np.argmax(f) action = self.actions[temp] self.actions = self.delete_actions(temp) chosed_actions = np.zeros(N, dtype=int) chosed_actions[0] = action for n in xrange(1, N): f = self.get_marginal_score(mode, chosed_actions[0:n], K, alpha) temp = np.argmax(np.mean(f, 0)) chosed_actions[n] = self.actions[temp] self.actions = self.delete_actions(temp) return chosed_actions def get_random_action(self, N): random_index = np.random.permutation(xrange(self.actions.shape[0])) index = random_index[0:N] action = self.actions[index] self.actions = self.delete_actions(index) return action def load(self, file_history, file_training=None, file_predictor=None): self.history.load(file_history) if file_training is None: N = self.history.total_num_search X = self.test.X[self.history.chosed_actions[0:N], :] t = self.history.fx[0:N] self.training = variable(X=X, t=t) else: self.training = variable() self.training.load(file_training) if file_predictor is not None: with open(file_predictor) as f: self.predictor = pickle.load(f) def export_predictor(self): return self.predictor def export_training(self): return self.training def export_history(self): return self.history def _set_predictor(self, predictor=None): if predictor is None: predictor = self.predictor return predictor def _init_predictor(self, is_rand_expans, predictor=None): self.predictor = self._set_predictor(predictor) if self.predictor is None: if is_rand_expans: self.predictor = blm_predictor(self.config) else: self.predictor = gp_predictor(self.config) return self.predictor def _set_training(self, training=None): if training is None: training = self.training return training def _set_unchosed_actions(self, actions=None): if actions is None: actions = self.actions return actions def _set_test(self, test_X): if isinstance(test_X, np.ndarray): test = variable(X=test_X) elif isinstance(test_X, variable): test = test_X else: raise TypeError('The type of test_X must \ take ndarray or combo.variable') return test def _set_config(self, config=None): if config is None: config = combo.misc.set_config() return config

32.694981

78

0.594473

1,066

8,468

4.542214

0.12758

0.061751

0.019827

0.022305

0.213342

0.150351

0.130525

0.118133

0.104089

0.084676

0

0.004313

0.315541

8,468

258

79

32.821705

0.83109

0

0.22

0

0.004015

0

1

0.1

false

0

0.06

0.015

0.255

0

null

0

null

0

1

0

71fb4a0f65f1788e4523139873b94749e767304c

693

py

Python

source.py

s403o/tw_bot

fd26ebc86d4c7d1be1ae654f26f5ca74c2566a03

[ "MIT" ]

null

source.py

s403o/tw_bot

fd26ebc86d4c7d1be1ae654f26f5ca74c2566a03

[ "MIT" ]

null

source.py

s403o/tw_bot

fd26ebc86d4c7d1be1ae654f26f5ca74c2566a03

[ "MIT" ]

null

import requests from bs4 import BeautifulSoup as bs import os #source url = '' # the source you want the bot take images from #down page page = requests.get(url) html = bs(page.text, 'html.parser') #locate image_loc = html.findAll('img') #create folder for located imgs if not os.path.exists('imgs'): os.makedirs('imgs') #open the new folder os.chdir('imgs') image0 = 0 #img name #get images for image in image_loc: try: url = image['src'] source = requests.get(url) if source.status_code == 200: with open('img-' + str(image0) + '.jpg', 'png') as mkimg: mkimg.write(requests.get(url).content) mkimg.close() image0 += 1 except: pass

19.25

63

0.65368

105

693

4.285714

0.571429

0.073333

0.093333

0

0.016544

0.215007

693

35

64

19.8

0.810662

0.193362

0

0.072595

0

1

0

false

0.045455

0.136364

0

0.136364

0

null

0

null

0

1

0

71fc1181a50c5c3f0fee92d2187d798fa7535036

2,403

py

Python

lib/appController.py

QIAOANGeo/BZB_ydzw

8c11e9797cca31d1fab26be7eb0a71666cfac15f

[ "MIT" ]

2

2019-12-06T14:49:34.000Z

2021-06-10T15:57:59.000Z

lib/appController.py

QIAOANGeo/BZB_ydzw

8c11e9797cca31d1fab26be7eb0a71666cfac15f

[ "MIT" ]

null

lib/appController.py

QIAOANGeo/BZB_ydzw

8c11e9797cca31d1fab26be7eb0a71666cfac15f

[ "MIT" ]

null

''' 1、启动appium服务 subproccess 配置文件 1.1、校验服务是否启动 1.2、杀掉上一次的服务 2、启动driver ''' from lib.tools import Tool import subprocess from lib.path import SYSTEMPATH, ERRORPATH import time from appium import webdriver import queue # 声明一个python队列 driver_queue = queue.Queue() class Controller(object): def __init__(self): # 获取配置信息 self.config = Tool().get_config self.tester = self.config.get('tester') self.device_type = self.config.get('device_type') # 获取到所有的手机信息 self.devices = self.config.get('devices') self.device = self.devices.get(self.device_type)[0] # port 用于校验服务是否启动 self.port = self.device.get('port') self.name = self.device.get('name') def kill_server(self): mac = '''ps -ef|grep appium|grep -v grep|grep %s|awk '{print "kill -9 " $2}'|sh''' % self.port win = 'taskkill /F /IM node.exe /t' subprocess.getoutput(win) def start_server(self): self.kill_server() command = 'appium -a {ip} -p {port} -U {deviceName}'.format(ip=self.device.get('ip'), port=self.device.get('port'), deviceName=self.device.get('deviceName')) print('command : %s' % command) subprocess.Popen(command, stdout=open(SYSTEMPATH, 'a+'), stderr=open(ERRORPATH, 'a+'), shell=True) def test_server(self): # mac = 'ps -ef|grep appium|grep -v grep|grep %s' % self.port win = 'netstat -ano | findstr %s' % self.port time.sleep(3) while True: data = subprocess.getoutput(win) if data: time.sleep(10) print('%s 端口启动成功。' % self.port) break else: print('%s 端口启动失败。5秒后重试。' % self.port) time.sleep(5) return True def start_driver(self): url = 'http://{ip}:{port}/wd/hub'.format(ip=self.device.get('ip'), port=self.port) # 合并手机信息和包名入口 self.device.update(self.tester) driver = webdriver.Remote(url, self.device) driver_queue.put(driver) if __name__ == '__main__': controller = Controller() controller.start_server() if controller.test_server(): controller.start_driver()

30.417722

109

0.553891

279

2,403

4.677419

0.362007

0.084291

0.05977

0.026054

0.136398

0.110345

0.062835

0

0.008526

0.316687

2,403

79

110

30.417722

0.786236

0.080732

0

0.019608

0.130692

0

1

0.098039

false

0

0.117647

0

0.254902

0.078431

0

null

0

null

0

1

0

71fcdf4c5cb6b34edec79a08f7d295031300d28a

2,226

py

Python

pondSizes.py

passionzhan/LeetCode

c4d33b64b9da15ca7a9b0d41e645d86a697694fe

[ "MIT" ]

1

2019-08-29T01:12:47.000Z

pondSizes.py

passionzhan/LeetCode

c4d33b64b9da15ca7a9b0d41e645d86a697694fe

[ "MIT" ]

null

pondSizes.py

passionzhan/LeetCode

c4d33b64b9da15ca7a9b0d41e645d86a697694fe

[ "MIT" ]

null

# -*- encoding: utf-8 -*- ''' @project : LeetCode @File : pondSizes.py @Contact : 9824373@qq.com @Desc : 你有一个用于表示一片土地的整数矩阵land，该矩阵中每个点的值代表对应地点的海拔高度。若值为0则表示水域。由垂直、水平或对角连接的水域为池塘。池塘的大小是指相连接的水域的个数。编写一个方法来计算矩阵中所有池塘的大小，返回值需要从小到大排序。示例：输入： [ [0,2,1,0], [0,1,0,1], [1,1,0,1], [0,1,0,1] ] 输出： [1,2,4] 提示： 0 < len(land) <= 1000 0 < len(land[i]) <= 1000 来源：力扣（LeetCode）链接：https://leetcode-cn.com/problems/pond-sizes-lcci @Modify Time @Author @Version @Desciption ------------ ------- -------- ----------- 2020-03-07 zhan 1.0 None ''' from typing import List from collections import deque class Solution: def pondSizes(self, land: List[List[int]]) -> List[int]: def neighbors(iR,iC,flag): ans = set() if (iR-1,iC-1) in flag: ans.add((iR-1,iC-1)) if (iR-1,iC) in flag: ans.add((iR-1,iC)) if (iR-1,iC+1) in flag: ans.add((iR-1,iC+1)) if (iR,iC-1) in flag: ans.add((iR,iC-1)) if (iR, iC + 1) in flag: ans.add((iR, iC + 1)) if (iR + 1, iC-1) in flag: ans.add((iR + 1, iC-1)) if (iR + 1, iC) in flag: ans.add((iR + 1, iC)) if (iR+1, iC + 1) in flag: ans.add((iR+1, iC + 1)) return ans flag = {(i,j) for j in range(len(land[0])) for i in range(len(land)) if land[i][j] == 0} ans = [] while flag: tmpArea = 0 mydueque = deque() mydueque.append(flag.pop()) while mydueque: curEle = mydueque.popleft() tmpArea +=1 for neighbor in neighbors(curEle[0], curEle[1], flag): mydueque.append(neighbor) flag.remove(neighbor) ans.append(tmpArea) ans.sort() return ans if __name__ == '__main__': a = [ [0,2,1,0], [0,1,0,1], [1,1,0,1], [0,1,0,1] ] ans = Solution().pondSizes(a) print(ans)

25.011236

124

0.444295

288

2,226

3.40625

0.3125

0.036697

0.061162

0.04893

0.236493

0

0.069373

0.391285

2,226

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125

25.295455

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0.297844

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false

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0.021277

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null

0

null

0

1

0

71fdcd33231ded5dc2f9d6d67f26d46eb50eca3d

5,990

py

Python

geolucidate/functions.py

kurtraschke/geolucidate

827195a90d972fa5efce5a03bdbe53d8395d94ba

[ "MIT" ]

3

2015-09-17T01:01:53.000Z

2019-09-10T14:30:43.000Z

geolucidate/functions.py

kurtraschke/geolucidate

827195a90d972fa5efce5a03bdbe53d8395d94ba

[ "MIT" ]

null

geolucidate/functions.py

kurtraschke/geolucidate

827195a90d972fa5efce5a03bdbe53d8395d94ba

[ "MIT" ]

5

2018-09-11T21:54:36.000Z

2020-06-25T19:05:45.000Z

# -*- coding: utf-8 -*- from decimal import Decimal, setcontext, ExtendedContext from geolucidate.links.google import google_maps_link from geolucidate.links.tools import MapLink from geolucidate.parser import parser_re setcontext(ExtendedContext) def _cleanup(parts): """ Normalize up the parts matched by :obj:`parser.parser_re` to degrees, minutes, and seconds. >>> _cleanup({'latdir': 'south', 'longdir': 'west', ... 'latdeg':'60','latmin':'30', ... 'longdeg':'50','longmin':'40'}) ['S', '60', '30', '00', 'W', '50', '40', '00'] >>> _cleanup({'latdir': 'south', 'longdir': 'west', ... 'latdeg':'60','latmin':'30', 'latdecsec':'.50', ... 'longdeg':'50','longmin':'40','longdecsec':'.90'}) ['S', '60', '30.50', '00', 'W', '50', '40.90', '00'] """ latdir = (parts['latdir'] or parts['latdir2']).upper()[0] longdir = (parts['longdir'] or parts['longdir2']).upper()[0] latdeg = parts.get('latdeg') longdeg = parts.get('longdeg') latmin = parts.get('latmin', '00') or '00' longmin = parts.get('longmin', '00') or '00' latdecsec = parts.get('latdecsec', '') longdecsec = parts.get('longdecsec', '') if (latdecsec and longdecsec): latmin += latdecsec longmin += longdecsec latsec = '00' longsec = '00' else: latsec = parts.get('latsec', '') or '00' longsec = parts.get('longsec', '') or '00' return [latdir, latdeg, latmin, latsec, longdir, longdeg, longmin, longsec] def _convert(latdir, latdeg, latmin, latsec, longdir, longdeg, longmin, longsec): """ Convert normalized degrees, minutes, and seconds to decimal degrees. Quantize the converted value based on the input precision and return a 2-tuple of strings. >>> _convert('S','50','30','30','W','50','30','30') ('-50.508333', '-50.508333') >>> _convert('N','50','27','55','W','127','27','65') ('50.459167', '-127.460833') """ if (latsec != '00' or longsec != '00'): precision = Decimal('0.000001') elif (latmin != '00' or longmin != '00'): precision = Decimal('0.001') else: precision = Decimal('1') latitude = Decimal(latdeg) latmin = Decimal(latmin) latsec = Decimal(latsec) longitude = Decimal(longdeg) longmin = Decimal(longmin) longsec = Decimal(longsec) if latsec > 59 or longsec > 59: # Assume that 'seconds' greater than 59 are actually a decimal # fraction of minutes latitude += (latmin + (latsec / Decimal('100'))) / Decimal('60') longitude += (longmin + (longsec / Decimal('100'))) / Decimal('60') else: latitude += (latmin + (latsec / Decimal('60'))) / Decimal('60') longitude += (longmin + (longsec / Decimal('60'))) / Decimal('60') if latdir == 'S': latitude *= Decimal('-1') if longdir == 'W': longitude *= Decimal('-1') lat_str = str(latitude.quantize(precision)) long_str = str(longitude.quantize(precision)) return (lat_str, long_str) def replace(string, sub_function=google_maps_link()): """ Replace detected coordinates with a map link, using the given substitution function. The substitution function will be passed a :class:`~.MapLink` instance, and should return a string which will be substituted by :func:`re.sub` in place of the detected coordinates. >>> replace("58147N/07720W") '<a href="http://maps.google.com/maps?q=58.235278%2C-77.333333+%2858147N%2F07720W%29&ll=58.235278%2C-77.333333&t=h" title="58147N/07720W (58.235278, -77.333333)">58147N/07720W</a>' >>> replace("5814N/07720W", google_maps_link('satellite')) '<a href="http://maps.google.com/maps?q=58.233%2C-77.333+%285814N%2F07720W%29&ll=58.233%2C-77.333&t=k" title="5814N/07720W (58.233, -77.333)">5814N/07720W</a>' >>> from geolucidate.links.bing import bing_maps_link >>> replace("58N/077W", bing_maps_link('map')) '<a href="http://bing.com/maps/default.aspx?style=r&cp=58~-77&sp=Point.58_-77_58N%2F077W&v=2" title="58N/077W (58, -77)">58N/077W</a>' """ def do_replace(match): original_string = match.group() (latitude, longitude) = _convert(*_cleanup(match.groupdict())) return sub_function(MapLink(original_string, latitude, longitude)) return parser_re.sub(do_replace, string) def get_replacements(string, sub_function=google_maps_link()): """ Return a dict whose keys are instances of :class:`re.Match` and whose values are the corresponding replacements. Use :func:`get_replacements` when the replacement cannot be performed through ordinary string substitution by :func:`re.sub`, as in :func:`replace`. >>> get_replacements("4630 NORTH 5705 WEST 58147N/07720W") ... #doctest: +ELLIPSIS {<re.Match object...>: '<a href="..." title="...">4630 NORTH 5705 WEST</a>', <re.Match object...>: '<a href="..." title="...">58147N/07720W</a>'} >>> test_string = "4630 NORTH 5705 WEST 58147N/07720W" >>> replacements = get_replacements(test_string) >>> offset = 0 >>> out = bytearray(test_string, encoding="ascii", errors="replace") >>> for (match, link) in replacements.items(): ... start = match.start() + offset ... end = match.end() + offset ... out[start:end] = bytearray(link, encoding="ascii", errors="replace") ... offset += (len(link) - len(match.group())) >>> out.decode(encoding="ascii") == replace(test_string) True """ substitutions = {} matches = parser_re.finditer(string) for match in matches: (latitude, longitude) = _convert(*_cleanup(match.groupdict())) substitutions[match] = sub_function(MapLink(match.group(), latitude, longitude)) return substitutions

35.235294

184

0.602337

723

5,990

4.923928

0.278008

0.017978

0.01573

0.014326

0.180337

0.164607

0.070787

0.041573

0

0.092331

0.220701

5,990

169

185

35.443787

0.670308

0.478631

0

0.132353

0

0.051371

0

1

0.073529

false

0

0.058824

0

0.205882

0

null

0

null

0

1

0

71feb582dac7753ba6da1c6d33e4df9c56ad4249

17,900

py

Python

lingvo/tasks/asr/encoder.py

j-luo93/lingvo

7398974078391362f0c1b027164a8f33f88cf86b

[ "Apache-2.0" ]

4

2019-01-08T02:59:38.000Z

2022-02-18T11:31:37.000Z

lingvo/tasks/asr/encoder.py

j-luo93/lingvo

7398974078391362f0c1b027164a8f33f88cf86b

[ "Apache-2.0" ]

null

lingvo/tasks/asr/encoder.py

j-luo93/lingvo

7398974078391362f0c1b027164a8f33f88cf86b

[ "Apache-2.0" ]

1

2019-07-02T14:09:42.000Z

# Copyright 2018 The TensorFlow Authors. All Rights Reserved. # # 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. """Encoders for the speech model.""" from __future__ import absolute_import from __future__ import division from __future__ import print_function import collections from six.moves import range from six.moves import zip import tensorflow as tf from tensorflow.python.ops import inplace_ops from lingvo.core import base_encoder from lingvo.core import base_layer from lingvo.core import layers from lingvo.core import plot from lingvo.core import py_utils from lingvo.core import rnn_cell from lingvo.core import rnn_layers from lingvo.core import summary_utils from lingvo.core import model_helper ConvLSTMBlock = collections.namedtuple('ConvLSTMBlock', ('rnn', 'cnn')) class AsrEncoder(base_encoder.BaseEncoder): """Speech encoder version 1.""" @classmethod def Params(cls): """Configs for AsrEncoder.""" p = super(AsrEncoder, cls).Params() p.Define('lstm_tpl', rnn_cell.LSTMCellSimple.Params(), 'Configs template for the RNN layer.') p.Define('cnn_tpl', layers.ConvLayer.Params(), 'Configs template for the conv layer.') p.Define('proj_tpl', layers.ProjectionLayer.Params(), 'Configs template for the projection layer.') p.Define( 'highway_skip', False, 'If set, residual connections from different layers are gated. ' 'Will only be used if residual_start is enabled.') p.Define('highway_skip_tpl', layers.HighwaySkipLayer.Params(), 'Configs template for the highway skip layer.') p.Define('conv_lstm_tpl', rnn_cell.ConvLSTMCell.Params(), 'Configs template for ConvLSTMCell.') p.Define( 'after_conv_lstm_cnn_tpl', layers.ConvLayer.Params(), 'Configs template for the cnn layer immediately follow the' ' convlstm layer.') p.Define('conv_filter_shapes', None, 'Filter shapes for each conv layer.') p.Define('conv_filter_strides', None, 'Filter strides for each conv layer.') p.Define('input_shape', [None, None, None, None], 'Shape of the input. This should a TensorShape with rank 4.') p.Define('lstm_cell_size', 256, 'LSTM cell size for the RNN layer.') p.Define('num_cnn_layers', 2, 'Number of conv layers to create.') p.Define('num_conv_lstm_layers', 1, 'Number of conv lstm layers to create.') p.Define('num_lstm_layers', 3, 'Number of rnn layers to create') p.Define('project_lstm_output', True, 'Include projection layer after each encoder LSTM layer.') p.Define('pad_steps', 6, 'Extra zero-padded timesteps to add to the input sequence. ') p.Define( 'residual_start', 0, 'Start residual connections from this lstm layer. ' 'Disabled if 0 or greater than num_lstm_layers.') p.Define('residual_stride', 1, 'Number of lstm layers to skip per residual connection.') p.Define( 'bidi_rnn_type', 'func', 'Options: func, native_cudnn. ' 'func: BidirectionalFRNN, ' 'native_cudnn: BidirectionalNativeCuDNNLSTM.') # TODO(yonghui): Maybe move those configs to a separate file. # Set some reasonable default values. # # NOTE(yonghui): The default config below assumes the following encoder # architecture: # # cnn/batch-norm/relu -> # cnn/batch-norm/relu -> # bidirectional conv-lstm -> # cnn/batch-norm/relu # bidirectional lstm -> # projection/batch-norm/relu -> # bidirectional lstm -> # projection/batch-norm/relu -> # bidirectional lstm # # Default config for the rnn layer. p.lstm_tpl.params_init = py_utils.WeightInit.Uniform(0.1) # Default config for the convolution layer. p.input_shape = [None, None, 80, 3] p.conv_filter_shapes = [(3, 3, 3, 32), (3, 3, 32, 32)] p.conv_filter_strides = [(2, 2), (2, 2)] p.cnn_tpl.params_init = py_utils.WeightInit.TruncatedGaussian(0.1) # TODO(yonghui): Disable variational noise logic. # NOTE(yonghui): Fortunately, variational noise logic is currently not # implemented for ConvLayer yet (as of sep 22, 2016). # Default config for the projection layer. p.proj_tpl.params_init = py_utils.WeightInit.TruncatedGaussian(0.1) # TODO(yonghui): Disable variational noise logic. # NOTE(yonghui): Fortunately, variational noise logic is currently not # implemented for ProjectionLayer yet (as of sep 22, 2016). p.conv_lstm_tpl.filter_shape = [1, 3] # height (time), width (frequency) p.conv_lstm_tpl.inputs_shape = [None, None, None, None] p.conv_lstm_tpl.cell_shape = [None, None, None, None] p.conv_lstm_tpl.params_init = py_utils.WeightInit.TruncatedGaussian(0.1) p.after_conv_lstm_cnn_tpl.filter_shape = [3, 3, None, None] p.after_conv_lstm_cnn_tpl.params_init = ( py_utils.WeightInit.TruncatedGaussian(0.1)) p.after_conv_lstm_cnn_tpl.filter_stride = [1, 1] return p @base_layer.initializer def __init__(self, params): super(AsrEncoder, self).__init__(params) p = self.params assert p.packed_input is False, ('Packed inputs are not yet supported for ' 'AsrEncoder.') name = p.name with tf.variable_scope(name): # First create the conv layers. assert p.num_cnn_layers == len(p.conv_filter_shapes) assert p.num_cnn_layers == len(p.conv_filter_strides) params_conv_layers = [] for i in range(p.num_cnn_layers): conv_p = p.cnn_tpl.Copy() conv_p.name = 'conv_L%d' % (i) conv_p.filter_shape = p.conv_filter_shapes[i] conv_p.filter_stride = p.conv_filter_strides[i] conv_p.is_eval = p.is_eval params_conv_layers.append(conv_p) self.CreateChildren('conv', params_conv_layers) conv_output_shape = tf.TensorShape(p.input_shape) for i in range(p.num_cnn_layers): conv_output_shape = self.conv[i].OutShape(conv_output_shape) conv_output_shape = conv_output_shape.as_list() assert len(conv_output_shape) == 4 # batch, height, width, channel. params_conv_lstm_rnn = [] params_conv_lstm_cnn = [] for i in range(p.num_conv_lstm_layers): # NOTE(yonghui): We assume that output from ConvLSTMBlock has the same # shape as its input. _, _, width, in_channel = conv_output_shape f_conv_lstm_p = p.conv_lstm_tpl.Copy() f_conv_lstm_p.name = 'f_conv_lstm_%d' % (i) f_conv_lstm_p.inputs_shape = [None, 1, width, in_channel] f_conv_lstm_p.cell_shape = [None, 1, width, in_channel] b_conv_lstm_p = f_conv_lstm_p.Copy() b_conv_lstm_p.name = 'b_conv_lstm_%d' % (i) conv_lstm_rnn_p = self.CreateConvLstmLayerParams() conv_lstm_rnn_p.name = 'conv_lstm_rnn' conv_lstm_rnn_p.fwd = f_conv_lstm_p conv_lstm_rnn_p.bak = b_conv_lstm_p params_conv_lstm_rnn.append(conv_lstm_rnn_p) cnn_p = p.after_conv_lstm_cnn_tpl.Copy() cnn_p.name = 'conv_lstm_cnn_%d' % (i) cnn_p.filter_shape[2] = 2 * in_channel cnn_p.filter_shape[3] = in_channel params_conv_lstm_cnn.append(cnn_p) # TODO(yonghui): Refactor ConvLSTMBlock into a layer. self.CreateChildren('conv_lstm_rnn', params_conv_lstm_rnn) self.CreateChildren('conv_lstm_cnn', params_conv_lstm_cnn) (self._first_lstm_input_dim, self._first_lstm_input_dim_pad) = self.FirstLstmLayerInputDimAndPadding( conv_output_shape, pad_to_multiple=16) # Now create all the rnn layers and projection layers. # TODO(yonghui): take care of device placement. params_rnn_layers = [] params_proj_layers = [] params_highway_skip_layers = [] for i in range(p.num_lstm_layers): if i == 0: input_dim = self._first_lstm_input_dim else: input_dim = 2 * p.lstm_cell_size forward_p = p.lstm_tpl.Copy() forward_p.name = 'fwd_rnn_L%d' % (i) forward_p.num_input_nodes = input_dim forward_p.num_output_nodes = p.lstm_cell_size backward_p = forward_p.Copy() backward_p.name = 'bak_rnn_L%d' % (i) rnn_p = self.CreateBidirectionalRNNParams(forward_p, backward_p) rnn_p.name = 'brnn_L%d' % (i) params_rnn_layers.append(rnn_p) if p.project_lstm_output and (i < p.num_lstm_layers - 1): proj_p = p.proj_tpl.Copy() proj_p.input_dim = 2 * p.lstm_cell_size proj_p.output_dim = 2 * p.lstm_cell_size proj_p.name = 'proj_L%d' % (i) proj_p.is_eval = p.is_eval params_proj_layers.append(proj_p) # add the skip layers residual_index = i - p.residual_start + 1 if p.residual_start > 0 and residual_index >= 0 and p.highway_skip: highway_skip = p.highway_skip_tpl.Copy() highway_skip.name = 'enc_hwskip_%d' % len(params_highway_skip_layers) highway_skip.input_dim = 2 * p.lstm_cell_size params_highway_skip_layers.append(highway_skip) self.CreateChildren('rnn', params_rnn_layers) self.CreateChildren('proj', params_proj_layers) self.CreateChildren('highway_skip', params_highway_skip_layers) @property def _use_functional(self): return True def CreateBidirectionalRNNParams(self, forward_p, backward_p): return model_helper.CreateBidirectionalRNNParams(self.params, forward_p, backward_p) def CreateConvLstmLayerParams(self): return rnn_layers.BidirectionalFRNN.Params() def FirstLstmLayerInputDimAndPadding(self, conv_output_shape, pad_to_multiple=16): lstm_input_shape = conv_output_shape # Makes sure the lstm input dims is multiple of 16 (alignment # requirement from FRNN). first_lstm_input_dim_unpadded = lstm_input_shape[2] * lstm_input_shape[3] if self._use_functional and (first_lstm_input_dim_unpadded % pad_to_multiple != 0): first_lstm_input_dim = int( (first_lstm_input_dim_unpadded + pad_to_multiple - 1) / pad_to_multiple) * pad_to_multiple else: first_lstm_input_dim = first_lstm_input_dim_unpadded first_lstm_input_dim_padding = ( first_lstm_input_dim - first_lstm_input_dim_unpadded) return first_lstm_input_dim, first_lstm_input_dim_padding @property def supports_streaming(self): return False def zero_state(self, batch_size): return py_utils.NestedMap() def FProp(self, theta, batch, state0=None): """Encodes source as represented by 'inputs' and 'paddings'. Args: theta: A NestedMap object containing weights' values of this layer and its children layers. batch: A NestedMap with fields: src_inputs - The inputs tensor. It is expected to be of shape [batch, time, feature_dim, channels]. paddings - The paddings tensor. It is expected to be of shape [batch, time]. state0: Recurrent input state. Not supported/ignored by this encoder. Returns: (outputs, out_paddings, state1) tuple. Outputs is of the shape [time, batch, depth], and out_paddings is of the shape [time, batch] """ p = self.params inputs, paddings = batch.src_inputs, batch.paddings with tf.name_scope(p.name): # Add a few extra padded timesteps at the end. This is for ensuring the # correctness of the conv-layers at the edges. if p.pad_steps > 0: # inplace_update() is not supported by TPU for now. Since we have done # padding on the input_generator, we may avoid this additional padding. assert not py_utils.use_tpu() inputs_pad = tf.zeros( inplace_ops.inplace_update(tf.shape(inputs), 1, p.pad_steps), inputs.dtype) paddings_pad = tf.ones( inplace_ops.inplace_update(tf.shape(paddings), 1, p.pad_steps), paddings.dtype) inputs = tf.concat([inputs, inputs_pad], 1, name='inputs') paddings = tf.concat([paddings, paddings_pad], 1) def ReshapeForPlot(tensor, padding, name): """Transposes and flattens channels to [batch, dim, seq_len] shape.""" # Flatten any dimensions beyond the third into the third. batch_size = tf.shape(tensor)[0] max_len = tf.shape(tensor)[1] plot_tensor = tf.reshape(tensor, [batch_size, max_len, -1]) plot_tensor = tf.transpose(plot_tensor, [0, 2, 1], name=name) return (plot_tensor, summary_utils.SequenceLength(padding)) plots = [ ReshapeForPlot( tf.transpose(inputs, [0, 1, 3, 2]), paddings, 'inputs') ] conv_out = inputs out_padding = paddings for i, conv_layer in enumerate(self.conv): conv_out, out_padding = conv_layer.FProp(theta.conv[i], conv_out, out_padding) plots.append( ReshapeForPlot( tf.transpose(conv_out, [0, 1, 3, 2]), out_padding, 'conv_%d_out' % i)) def TransposeFirstTwoDims(t): first_dim = tf.shape(t)[0] second_dim = tf.shape(t)[1] t_new = tf.transpose( tf.reshape(t, [first_dim, second_dim, -1]), [1, 0, 2]) t_shape_new = tf.concat([[second_dim], [first_dim], tf.shape(t)[2:]], 0) return tf.reshape(t_new, t_shape_new) # Now the conv-lstm part. conv_lstm_out = conv_out conv_lstm_out_padding = out_padding for i, (rnn, cnn) in enumerate( zip(self.conv_lstm_rnn, self.conv_lstm_cnn)): conv_lstm_in = conv_lstm_out # Move time dimension to be the first. conv_lstm_in = TransposeFirstTwoDims(conv_lstm_in) conv_lstm_in = tf.expand_dims(conv_lstm_in, 2) conv_lstm_in_padding = tf.expand_dims( tf.transpose(conv_lstm_out_padding), 2) lstm_out = rnn.FProp(theta.conv_lstm_rnn[i], conv_lstm_in, conv_lstm_in_padding) # Move time dimension to be the second. cnn_in = TransposeFirstTwoDims(lstm_out) cnn_in = tf.squeeze(cnn_in, 2) cnn_in_padding = conv_lstm_out_padding cnn_out, cnn_out_padding = cnn.FProp(theta.conv_lstm_cnn[i], cnn_in, cnn_in_padding) conv_lstm_out, conv_lstm_out_padding = cnn_out, cnn_out_padding plots.append( ReshapeForPlot(conv_lstm_out, conv_lstm_out_padding, 'conv_lstm_%d_out' % i)) # Need to do a reshape before starting the rnn layers. conv_lstm_out = py_utils.HasRank(conv_lstm_out, 4) conv_lstm_out_shape = tf.shape(conv_lstm_out) new_shape = tf.concat([conv_lstm_out_shape[:2], [-1]], 0) conv_lstm_out = tf.reshape(conv_lstm_out, new_shape) if self._first_lstm_input_dim_pad: conv_lstm_out = tf.pad( conv_lstm_out, [[0, 0], [0, 0], [0, self._first_lstm_input_dim_pad]]) conv_lstm_out = py_utils.HasShape(conv_lstm_out, [-1, -1, self._first_lstm_input_dim]) # Transpose to move the time dimension to be the first. rnn_in = tf.transpose(conv_lstm_out, [1, 0, 2]) rnn_padding = tf.expand_dims(tf.transpose(conv_lstm_out_padding), 2) # rnn_in is of shape [time, batch, depth] # rnn_padding is of shape [time, batch, 1] # Now the rnn layers. num_skips = 0 for i in range(p.num_lstm_layers): rnn_out = self.rnn[i].FProp(theta.rnn[i], rnn_in, rnn_padding) residual_index = i - p.residual_start + 1 if p.residual_start > 0 and residual_index >= 0: if residual_index % p.residual_stride == 0: residual_in = rnn_in if residual_index % p.residual_stride == p.residual_stride - 1: # Highway skip connection. if p.highway_skip: rnn_out = self.highway_skip[num_skips].FProp( theta.highway_skip[num_skips], residual_in, rnn_out) num_skips += 1 else: # Residual skip connection. rnn_out += py_utils.HasShape(residual_in, tf.shape(rnn_out)) if p.project_lstm_output and (i < p.num_lstm_layers - 1): # Projection layers. rnn_out = self.proj[i].FProp(theta.proj[i], rnn_out, rnn_padding) if i == p.num_lstm_layers - 1: rnn_out *= (1.0 - rnn_padding) plots.append( ReshapeForPlot( tf.transpose(rnn_out, [1, 0, 2]), tf.transpose(rnn_padding, [1, 0, 2]), 'rnn_%d_out' % i)) rnn_in = rnn_out final_out = rnn_in if self.cluster.add_summary: fig = plot.MatplotlibFigureSummary( 'encoder_example', figsize=(8, len(plots) * 3.5)) # Order layers from bottom to top. plots.reverse() for tensor, seq_len in plots: fig.AddSubplot( [tensor, seq_len], summary_utils.TrimPaddingAndPlotSequence, title=tensor.name, xlabel='Time') fig.Finalize() rnn_padding = tf.squeeze(rnn_padding, [2]) return final_out, rnn_padding, py_utils.NestedMap()

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0

null

0

null

0

1

0

71feffbb5e24e7f37afedbf05e8ccd4bc8d2a4ea

1,898

py

Python

pos_neg_graph/graph_ratio.py

Yudabin/Review_Project

b924199d6845defeb4cd243a99426070c014d8d8

[ "MIT" ]

null

pos_neg_graph/graph_ratio.py

Yudabin/Review_Project

b924199d6845defeb4cd243a99426070c014d8d8

[ "MIT" ]

null

pos_neg_graph/graph_ratio.py

Yudabin/Review_Project

b924199d6845defeb4cd243a99426070c014d8d8

[ "MIT" ]

1

2020-11-10T00:54:45.000Z

import matplotlib.font_manager as fm import matplotlib.pyplot as plt import numpy as np font_location = './wordcloud_file/malgun.ttf' # For Windows font_name = fm.FontProperties(fname=font_location).get_name() plt.rc('font', family=font_name) def percent_graph2(movie_review) : b = movie_review labelss = sorted(b['score'].unique())## 라벨설정함. 한글이 적용이 안됨!!! c = b['score'].value_counts().sort_index() ## 빈도 print(c) print(labelss) fig = plt.figure(figsize=(8,8)) ## 캔버스 생성 fig.set_facecolor('white') ## 캔버스 배경색을 하얀색으로 설정 ax = fig.add_subplot() ## 프레임 생성 pie = ax.pie(c, ## 파이차트 출력 startangle=90, ## 시작점을 90도(degree)로 지정 counterclock=False, ## 시계 방향으로 그린다. # autopct=lambda p : '{:.2f}%'.format(p), ## 퍼센티지 출력 wedgeprops=dict(width=0.5), colors = ['yellowgreen', 'orange'], labels = labelss, textprops={'fontsize': 22} ) total = np.sum(c) ## 빈도수 총합 sum_pct = 0 ## 백분율 초기값 for i, l in enumerate(labelss): ang1, ang2 = pie[0][i].theta1, pie[0][i].theta2 ## 각1, 각2 r = pie[0][i].r ## 원의 반지름 x = ((r + 0.5) / 2) * np.cos(np.pi / 180 * ((ang1 + ang2) / 2)) ## 정중앙 x좌표 y = ((r + 0.5) / 2) * np.sin(np.pi / 180 * ((ang1 + ang2) / 2)) ## 정중앙 y좌표 if i < len(labelss) - 1: sum_pct += float(f'{c[i] / total * 100:.2f}') ## 백분율을 누적한다. ax.text(x, y, f'{c[i] / total * 100:.2f}%', ha='center', va='center', size=22, color='white', weight='bold') ## 백분율 텍스트 표시 else: ## 총합을 100으로 맞추기위해 마지막 백분율은 100에서 백분율 누적값을 빼준다. ax.text(x, y, f'{100 - sum_pct:.2f}%', ha='center', va='center',size=22,color='white', weight='bold') # pie.rc('font', family=font_name) # plt.legend(pie[0], labelss) ## 범례 표시 plt.savefig('./static/images/pos_neg_ratio.png') # 경로

42.177778

105

0.553741

284

1,898

3.630282

0.56338

0.015519

0.014549

0.031038

0.212415

0.14549

0.122211

0.085354

0

0.045812

0.263962

1,898

45

106

42.177778

0.692198

0.18019

0

0.052632

0

0.142102

0.039656

0

1

0.026316

false

0

0.078947

0

0.105263

0.052632

0

null

0

null

0

1

0

71ffb4e7bdba22327963714071779d2e8b20d391

3,727

py

Python

my_area/views.py

Vincent-Juma/area_master

3ea1dd1039053fb4de6326deb967383d09d7145b

[ "MIT" ]

1

2021-05-28T14:16:54.000Z

my_area/views.py

Vincent-Juma/area_master

3ea1dd1039053fb4de6326deb967383d09d7145b

[ "MIT" ]

null

my_area/views.py

Vincent-Juma/area_master

3ea1dd1039053fb4de6326deb967383d09d7145b

[ "MIT" ]

1

2021-04-13T09:14:07.000Z

from django.shortcuts import render from .forms import * from django.shortcuts import redirect,get_object_or_404 from django.contrib.auth.decorators import login_required from . models import * from django.views import generic @login_required(login_url='/accounts/login/') def home(request): mylocs = Myloc.objects.all() return render(request, 'home.html',{"mylocs":mylocs,}) @login_required(login_url='accounts/login/') def add_profile(request): current_user = request.user profile = Profile.objects.filter(id = current_user.id) if request.method == 'POST': form = NewProfileForm(request.POST, request.FILES) if form.is_valid(): caption = form.save(commit=False) caption.user = current_user caption.save() return redirect('myprofile') else: form = NewProfileForm() return render(request, 'edit.html', {"form":form}) @login_required(login_url='accounts/login/') def my_profile(request): current_user = request.user my_my_area = Myloc.objects.filter(user = current_user) my_profile = Profile.objects.filter(user = current_user).first return render(request, 'profile.html', {"my_my_areas":my_my_areas, "my_profile":my_profile}) @login_required(login_url='/accounts/login/') def addmy_area(request): current_user = request.user if request.method == 'POST': form = MylocForm(request.POST, request.FILES) if form.is_valid(): image = form.save(commit=False) image.user = current_user image.save() return redirect('home') else: form = MylocForm() return render(request, 'addmy_area.html', {"form": form}) def myloc_details(request,myloc_id): activities=Activity.objects.filter(myloc=myloc_id) posts=Post.objects.filter(myloc=myloc_id) myloc=Myloc.objects.get(pk=myloc_id) return render(request,'details.html',{'myloc':myloc,'activities':activities,'posts':posts}) @login_required(login_url="/accounts/login/") def new_activity(request,pk): current_user = request.user myloc = get_object_or_404(Myloc,pk=pk) if request.method == 'POST': activity_form = NewActivityForm(request.POST, request.FILES) if activity_form.is_valid(): activity = activity_form.save(commit=False) activity.user = current_user activity.myloc=myloc activity.save() return redirect('detail', myloc_id=myloc.id) else: activity_form = NewActivityForm() return render(request, 'new_activity.html', {"form": activity_form,'myloc':myloc}) @login_required(login_url="/accounts/login/") def new_post(request,pk): current_user = request.user myloc = get_object_or_404(Myloc,pk=pk) if request.method == 'POST': post_form = NewPostForm(request.POST, request.FILES) if post_form.is_valid(): post = post_form.save(commit=False) post.user = current_user post.myloc=myloc post.save() return redirect('detail', myloc_id=myloc.id) else: post_form = NewPostForm() return render(request, 'new_post.html', {"form": post_form,'myloc':myloc}) @login_required(login_url='/accounts/login/') def search_project(request): if 'project_name' in request.GET and request.GET["project_name"]: search_term = request.GET.get("project_name") searched_project = Myloc.search_by_location(search_term) message = f"{search_term}" return render(request, "search.html",{"message":message,"project": searched_project}) else: message = "No search history" return render(request, 'search.html',{"message":message})

37.646465

96

0.676952

465

3,727

5.243011

0.172043

0.054143

0.070139

0.060295

0.407711

0.312961

0.283429

0.187449

0.140279

0.105824

0

0.003007

0.196941

3,727

98

97

38.030612

0.81156

0

0.306818

0

0.112721

0

1

0.090909

false

0

0.068182

0

0.306818

0

null

0

null

0

1

0

9c01e95549f9ef77973f439bfde72aea99322f8e

20,840

py

Python

scripts/data/topple_dataset.py

davrempe/predicting-physical-dynamics

b0abb385a7ac491e25d1df0b9a9a943621fc2d37

[ "MIT" ]

16

2020-02-29T06:44:16.000Z

2022-02-20T13:05:12.000Z

scripts/data/topple_dataset.py

davrempe/predicting-physical-dynamics

b0abb385a7ac491e25d1df0b9a9a943621fc2d37

[ "MIT" ]

6

2020-02-13T08:09:28.000Z

2022-02-09T23:35:55.000Z

scripts/data/topple_dataset.py

davrempe/predicting-physical-dynamics

b0abb385a7ac491e25d1df0b9a9a943621fc2d37

[ "MIT" ]

4

2020-04-22T09:46:55.000Z

2021-04-15T06:17:48.000Z

import numpy as np import pickle from os.path import exists, realpath import sys import math from topple_data_loader import ToppleData, ToppleDataLoader import transforms3d class ToppleNormalizationInfo(): ''' Structure to hold all the normalization information for a dataset. ''' def __init__(self): # max element of any linear vel vector self.max_lin_vel = None # max element of any angular vel vector self.max_ang_vel = None # max distance between positions in two contiguous timesteps self.max_pos = None # max change in rotation around any axis between two contiguous timesteps (for euler rot) self.max_rot = None # max angle of rotation between two steps for axis-angle representation self.max_delta_rot = None # max 2-norm of applied impulse vector self.force_vec_max = None # max 2-norm of a point in an object point cloud (used for point cloud and force pos) self.pc_max = None # normalization values for shape-related stuff self.density_offset = None self.density_max = None self.mass_offset = None self.mass_max = None self.inertia_offset = None self.inertia_max = None self.friction_offset = None self.friction_max = None def print_out(self): print({'max_lin_vel' : self.max_lin_vel, 'max_ang_vel' : self.max_ang_vel, 'max_pos' : self.max_pos, \ 'max_rot' : self.max_rot, 'max_delta_rot' : self.max_delta_rot, 'force_vec_max' : self.force_vec_max, 'pc_max' : self.pc_max, \ 'density_off' : self.density_offset, 'density_max' : self.density_max, 'mass_off' : self.mass_offset, \ 'mass_max' : self.mass_max, 'inertia_off' : self.inertia_offset, 'inertia_max' : self.inertia_max, \ 'friction_off' : self.friction_offset, 'friction_max' : self.friction_max }) def save(self, pkl_file): ''' Saves normalization info object to a specified .pkl file. ''' with open(pkl_file, 'wb') as f: pickle.dump(self, f) def load_from(self, pkl_file): ''' Load normalization info into this object from a specified .pkl file. ''' with open(pkl_file, 'rb') as f: norm_info = pickle.load(f) self.copy_from(norm_info) def copy_from(self, norm_info): ''' Takes values from the given normalization info object and copies them to this one ''' self.max_lin_vel = norm_info.max_lin_vel self.max_ang_vel = norm_info.max_ang_vel self.max_pos = norm_info.max_pos self.max_rot = norm_info.max_rot try: self.max_delta_rot = norm_info.max_delta_rot except: # old versions of data doesn't have max delta rot pass self.force_vec_max = norm_info.force_vec_max self.pc_max = norm_info.pc_max self.density_offset = norm_info.density_offset self.density_max = norm_info.density_max self.mass_offset = norm_info.mass_offset self.mass_max = norm_info.mass_max self.inertia_offset = norm_info.inertia_offset self.inertia_max = norm_info.inertia_max try: self.friction_offset = norm_info.friction_offset self.friction_max = norm_info.friction_max except: # old version doesn't have this pass class ToppleBatch(object): ''' Structure to hold a single batch of data. ''' def __init__(self, size, seq_len, num_pts): self.size = size self.num_steps = seq_len self.num_pts = num_pts self.point_cloud = np.zeros((self.size, self.num_pts, 3)) self.lin_vel = np.zeros((self.size, self.num_steps, 3)) self.ang_vel = np.zeros((self.size, self.num_steps, 3)) self.pos = np.zeros((self.size, self.num_steps, 3)) # cummulative euler angles self.rot = np.zeros((self.size, self.num_steps, 3)) # change in rotation in quaternion rep (w, x, y, z) self.delta_quat = np.zeros((self.size, self.num_steps, 4)) # change in rotation between steps in axis-angle rep (scaled 3 vec) self.delta_rot = np.zeros((self.size, self.num_steps, 3)) # change in rotation between steps in split axis-angle rep (4-vec) self.delta_rot_split = np.zeros((self.size, self.num_steps, 4)) # 0 if before topple idx, 1 if after self.topple_label = np.zeros((self.size, self.num_steps), dtype=int) # other meta-data not directly used in network self.toppled = [] self.shape_name = [] self.body_friction = np.zeros((self.size)) self.mass = np.zeros((self.size)) self.scale = np.zeros((self.size, 3)) self.rot_euler = np.zeros((self.size, self.num_steps, 3)) class ToppleDataset(object): ''' Loads toppling data and provides batches for training and model evaluation. ''' def __init__(self, roots, norm_info_file, batch_size=32, num_steps=15, shuffle=False, num_pts=None, perturb_pts=0.0): ''' - roots : list of directories containing data to load for this dataset - norm_info_file : .pkl file containing normalization information - batch_size : number of sequences to return in each batch - num_steps : number of timesteps to return in each sequence - shuffle : randomly shuffles the returned sequence ordering - num_pts : the number of points to use in the returned point cloud. If None uses all points in the data. - perturb_pts : the stdev to randomly perturb point clouds with. If None no perturbation is performed. - ''' # settings self.batch_size = batch_size self.steps_per_seq = num_steps self.shuffle = shuffle self.perturb_std = perturb_pts self.num_pts = num_pts # load in data for root in roots: if not exists(root): print('Could not find dataset at ' + root) return data_loader = ToppleDataLoader() self.data = data_loader.load_data(roots) if num_pts is None: # use all the points in the point cloud self.num_pts = self.data.point_cloud.shape[1] # load in normalization info if not exists(norm_info_file): print('Could not find normalization info at ' + norm_info_file) return self.norm_info = ToppleNormalizationInfo() self.norm_info.load_from(norm_info_file) print('Loaded normalization info!') # see if we have axis-angle info (for backwards compat) self.use_aa = False self.use_aa_split = False self.use_topple_idx = False self.use_delta_quat = False if len(self.data.delta_rot) > 0: self.use_aa = True if len(self.data.delta_rot_split) > 0: self.use_aa_split = True if len(self.data.topple_idx) > 0: self.use_topple_idx = True if len(self.data.body_friction) > 0: self.use_body_friction = True if len(self.data.delta_quat) > 0: self.use_delta_quat = True # normalize the data print('Normalizing data...') self.normalize_data(self.data, self.norm_info) print('Finished normalizing!') # order to iterate through data when returning batches (in order by default) self.iter_inds = range(0, self.data.size) # prepare to iterate through self.reset() def normalize_data(self, data, norm_info): ''' Normalizes (in place) the given ToppleData using the ToppleNormalizationInfo. ''' # point clouds -> [-1, 1] data.point_cloud /= norm_info.pc_max # force pos -> [-1, 1] data.force_pos /= norm_info.pc_max # force vec -> [-1, 1] data.force_vec /= norm_info.force_vec_max # density -> [0, 1] data.density = (data.density - norm_info.density_offset) / norm_info.density_max # mass -> [0, 1] data.mass = (data.mass - norm_info.mass_offset) / norm_info.mass_max # inertia -> [0, 1] data.inertia = (data.inertia - norm_info.inertia_offset) / norm_info.inertia_max # friction -> [0, 1] if norm_info.friction_offset is not None: data.body_friction = (data.body_friction - norm_info.friction_offset) / norm_info.friction_max # now time sequence data # velocities -> [-1, 1] for i, lin_vel_steps in enumerate(data.lin_vel): data.lin_vel[i] = [(x / norm_info.max_lin_vel) for x in lin_vel_steps] for i, ang_vel_steps in enumerate(data.ang_vel): data.ang_vel[i] = [(x / norm_info.max_ang_vel) for x in ang_vel_steps] # delta position -> [-1, 1] for i, pos_steps in enumerate(data.pos): data.pos[i] = [(x / norm_info.max_pos) for x in pos_steps] # delta rotation -> [-1, 1] for i, rot_steps in enumerate(data.total_rot): data.total_rot[i] = [(x / norm_info.max_rot) for x in rot_steps] # delta rot axis-angle -> [-1, 1] norm if self.use_aa: for i, delta_rot_steps in enumerate(data.delta_rot): data.delta_rot[i] = [(x / norm_info.max_delta_rot) for x in delta_rot_steps] # make axes unit and and normalize angle -> [-1, 1] if self.use_aa_split: for i, delta_rot_split_steps in enumerate(data.delta_rot_split): data.delta_rot_split[i] = [np.append(x[:3] / np.linalg.norm(x[:3]), x[3] / norm_info.max_delta_rot) for x in delta_rot_split_steps] def reset(self): ''' Prepares to iterate through dataset. ''' if self.shuffle: np.random.shuffle(self.iter_inds) # we consider an epoch as returning one sequence from every single simulation # ( though if the sequence length is shorter than sim length the unique sequences contained # in the dataset will be much more than an epoch length ) self.num_batches = (self.data.size + self.batch_size - 1) // self.batch_size self.batch_idx = 0 def has_next_batch(self): ''' Returns false if done with the current "epoch" (seen each sim once). ''' return self.batch_idx < self.num_batches def next_batch(self, random_window=True, focus_toppling=False): ''' Returns the next batch of data. if random_window=True will get a random sequence of correct length (otherwise starts at 0). If focus_toppling=True, will make sure this sequence includes the part of the sequence where toppling occurs. ''' # size is either batch_size, or shorter if we're at the end of the data start_idx = self.batch_idx * self.batch_size end_idx = min((self.batch_idx + 1) * self.batch_size, self.data.size) batch_size = end_idx - start_idx # get batch data batch = ToppleBatch(self.batch_size, self.steps_per_seq, self.num_pts) for i in range(batch_size): pc, lin_vel, ang_vel, pos, rot, delta_quat, delta_rot, delta_rot_split, topple_label, meta_info = \ self.get_seq(self.iter_inds[start_idx + i], self.steps_per_seq, random_window, focus_toppling) batch.point_cloud[i] = pc batch.lin_vel[i] = lin_vel batch.ang_vel[i] = ang_vel batch.pos[i] = pos batch.rot[i] = rot if self.use_delta_quat: batch.delta_quat[i] = delta_quat if self.use_aa: batch.delta_rot[i] = delta_rot if self.use_aa_split: batch.delta_rot_split[i] = delta_rot_split if self.use_topple_idx: batch.topple_label[i] = topple_label batch.toppled.append(meta_info[0]) batch.shape_name.append(meta_info[1]) batch.scale[i] = meta_info[2] batch.rot_euler[i] = meta_info[3] if self.use_body_friction: batch.body_friction[i] = meta_info[4] batch.mass[i] = meta_info[5] if batch_size != self.batch_size: # need to pad the end with repeat of data for i in range(self.batch_size - batch_size): batch.point_cloud[batch_size + i] = batch.point_cloud[i] batch.lin_vel[batch_size + i] = batch.lin_vel[i] batch.ang_vel[batch_size + i] = batch.ang_vel[i] batch.pos[batch_size + i] = batch.pos[i] batch.rot[batch_size + i] = batch.rot[i] if self.use_delta_quat: batch.delta_quat[batch_size + i] = batch.delta_quat[i] batch.toppled.append(batch.toppled[i]) batch.shape_name.append(batch.shape_name[i]) batch.scale[batch_size + i] = batch.scale[i] batch.rot_euler[batch_size + i] = batch.rot_euler[i] batch.mass[batch_size + i] = batch.mass[i] if self.use_aa: batch.delta_rot[batch_size + i] = batch.delta_rot[i] if self.use_aa_split: batch.delta_rot_split[batch_size + i] = batch.delta_rot_split[i] if self.use_topple_idx: batch.topple_label[batch_size + i] = batch.topple_label[i] if self.use_body_friction: batch.body_friction[batch_size + i] = batch.body_friction[i] self.batch_idx += 1 return batch def get_seq(self, idx, num_steps, random_window=True, focus_toppling=False): ''' Returns a random contiguous sequence from the simulation at the given idx and length num_steps. If num_steps > sim_length the final (sim_length-num_steps) steps are padded with the value at sim[sim_length]. ''' # get the normalized canonical point cloud for this simulation pc = np.copy(self.data.point_cloud[self.data.shape_idx[idx]]) scale = self.data.scale[idx] # scale accordingly pc *= np.reshape(scale, (1, -1)) # randomly perturb point cloud pc += np.random.normal(0.0, self.perturb_std, pc.shape) # randomly draw a subset of points if desired if self.num_pts < pc.shape[0]: pc_inds = np.random.choice(pc.shape[0], self.num_pts, replace=False) pc = pc[pc_inds, :] # randomly choose a size num_steps sequence from the simulation to return time-series data total_steps = len(self.data.lin_vel[idx]) max_start_step = total_steps - num_steps start_step = 0 if max_start_step < 0: # simulation is shorter than desired sequence length pad_len = abs(max_start_step) lin_vel_list = self.data.lin_vel[idx] lin_vel_out = np.array(lin_vel_list + [lin_vel_list[-1]]*pad_len) ang_vel_list = self.data.ang_vel[idx] ang_vel_out = np.array(ang_vel_list + [ang_vel_list[-1]]*pad_len) pos_list = self.data.pos[idx] pos_out = np.array(pos_list + [pos_list[-1]]*pad_len) rot_list = self.data.total_rot[idx] rot_out = np.array(rot_list + [rot_list[-1]]*pad_len) if self.use_delta_quat: delta_quat_list = self.data.delta_quat[idx] delta_quat_out = np.array(delta_quat_list + [delta_quat_list[-1]]*pad_len) euler_rot_list = self.data.rot_euler[idx] euler_rot_out = np.array(euler_rot_list + [euler_rot_list[-1]]*pad_len) if self.use_aa: delta_rot_list = self.data.delta_rot[idx] delta_rot_out = np.array(delta_rot_list + [delta_rot_list[-1]]*pad_len) if self.use_aa_split: delta_rot_split_list = self.data.delta_rot_split[idx] delta_rot_split_out = np.array(delta_rot_split_list + [delta_rot_split_list[-1]]*pad_len) if self.use_topple_idx: topple_label_out = np.zeros((total_steps + pad_len), dtype=int) seq_topple_idx = self.data.topple_idx[idx] if seq_topple_idx > 0: topple_label_out[seq_topple_idx:] = 1 else: start_step = 0 if random_window: if focus_toppling and self.data.toppled[idx]: # choose window around the index where it topples topple_idx = self.data.topple_idx[idx] min_idx = max([topple_idx - num_steps + 1, 0]) if min_idx >= max_start_step: # just pick the max index start_step = max_start_step else: # our window is guaranteed to see some part of toppling start_step = np.random.randint(min_idx, max_start_step+1) else: start_step = np.random.randint(0, max_start_step+1) end_step = start_step + num_steps # print('Range: %d, %d' % (start_step, end_step)) lin_vel_out = np.array(self.data.lin_vel[idx][start_step:end_step]) ang_vel_out = np.array(self.data.ang_vel[idx][start_step:end_step]) pos_out = np.array(self.data.pos[idx][start_step:end_step]) rot_out = np.array(self.data.total_rot[idx][start_step:end_step]) if self.use_delta_quat: delta_quat_out = np.array(self.data.delta_quat[idx][start_step:end_step]) euler_rot_out = np.array(self.data.rot_euler[idx][start_step:end_step]) if self.use_aa: delta_rot_out = np.array(self.data.delta_rot[idx][start_step:end_step]) if self.use_aa_split: delta_rot_split_out = np.array(self.data.delta_rot_split[idx][start_step:end_step]) if self.use_topple_idx: topple_label_out = np.zeros((num_steps), dtype=int) seq_topple_idx = self.data.topple_idx[idx] if seq_topple_idx > 0: if seq_topple_idx <= start_step: topple_label_out[:] = 1 elif seq_topple_idx < end_step: topple_label_out[seq_topple_idx-start_step:] = 1 # rotate point cloud to align with first frame of sequence init_rot = self.data.rot_euler[idx][start_step] xrot, yrot, zrot = np.radians(init_rot) R = transforms3d.euler.euler2mat(zrot, xrot, yrot, axes='szxy') # unity applies euler angles in z, x, y ordering pc = np.dot(pc, R.T) toppled = self.data.toppled[idx] shape_name = self.data.shape_name[idx] mass = self.data.mass[idx] body_fric = -1.0 if self.use_body_friction: body_fric = self.data.body_friction[idx] meta_info = (toppled, shape_name, scale, euler_rot_out, body_fric, mass) if not self.use_aa: delta_rot_out = None if not self.use_aa_split: delta_rot_split_out = None if not self.use_topple_idx: topple_label_out = None if not self.use_delta_quat: delta_quat_out = None return pc, lin_vel_out, ang_vel_out, pos_out, rot_out, delta_quat_out, delta_rot_out, delta_rot_split_out, topple_label_out, meta_info def get_norm_info(self): return self.norm_info if __name__=='__main__': # norm_info = ToppleNormalizationInfo() # norm_info.load_from('../../data/sim/normalization_info/cube_train.pkl') # norm_info.print_out() topple_data = ToppleDataset(roots=['./data/sim/Cube/Cube30k_ObjSplit/Cube30kVal'], norm_info_file='./data/sim/normalization_info/cube_30k.pkl', \ batch_size=5, num_steps=10, shuffle=True, num_pts=None, perturb_pts=0.01) count = 0 while topple_data.has_next_batch(): batch = topple_data.next_batch(random_window=True, focus_toppling=False) count += 1 # print(batch.lin_vel[0]) # print(batch.toppled[0]) # print(batch.delta_rot_split[0]) # print(batch.delta_rot[0]) # print(batch.topple_label[0]) # print(batch.pos) # print(batch.body_friction) # print(batch.delta_quat[0]) # print(np.degrees(2*np.arccos(batch.delta_quat[0, :, 0]))) print('Total num batches: ' + str(count)) topple_data.reset() count = 0 while topple_data.has_next_batch(): batch = topple_data.next_batch() count += 1 print(batch.size) print('Total num batches: ' + str(count))

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py

Python

scripts/sct_apply_transfo.py

YangHee-Min/spinalcordtoolbox

38ca15aa99b03ca99b7885ddc98adf2755adc43d

[ "MIT" ]

null

scripts/sct_apply_transfo.py

YangHee-Min/spinalcordtoolbox

38ca15aa99b03ca99b7885ddc98adf2755adc43d

[ "MIT" ]

null

scripts/sct_apply_transfo.py

YangHee-Min/spinalcordtoolbox

38ca15aa99b03ca99b7885ddc98adf2755adc43d

[ "MIT" ]

null

#!/usr/bin/env python ######################################################################################### # # Apply transformations. This function is a wrapper for sct_WarpImageMultiTransform # # --------------------------------------------------------------------------------------- # Copyright (c) 2014 Polytechnique Montreal <www.neuro.polymtl.ca> # Authors: Julien Cohen-Adad, Olivier Comtois # Modified: 2014-07-20 # # About the license: see the file LICENSE.TXT ######################################################################################### # TODO: display message at the end # TODO: interpolation methods from __future__ import division, absolute_import import sys, io, os, time, functools from msct_parser import Parser import sct_utils as sct import sct_convert import sct_image import spinalcordtoolbox.image as msct_image from sct_crop_image import ImageCropper class Param: def __init__(self): self.verbose = '1' self.remove_temp_files = '1' # PARSER # ========================================================================================== def get_parser(): # parser initialisation parser = Parser(__file__) parser.usage.set_description('Apply transformations. This function is a wrapper for antsApplyTransforms (ANTs).') parser.add_option(name="-i", type_value="file", description="input image", mandatory=True, example="t2.nii.gz") parser.add_option(name="-d", type_value="file", description="destination image", mandatory=True, example="out.nii.gz") parser.add_option(name="-w", type_value=[[','], "file"], description="Transformation, which can be a warping field (nifti image) or an affine transformation matrix (text file).", mandatory=True, example="warp1.nii.gz,warp2.nii.gz") parser.add_option(name="-crop", type_value="multiple_choice", description="Crop Reference. 0 : no reference. 1 : sets background to 0. 2 : use normal background", mandatory=False, default_value='0', example=['0', '1', '2']) parser.add_option(name="-c", type_value=None, description="Crop Reference. 0 : no reference. 1 : sets background to 0. 2 : use normal background", mandatory=False, deprecated_by='-crop') parser.add_option(name="-o", type_value="file_output", description="registered source.", mandatory=False, default_value='', example="dest.nii.gz") parser.add_option(name="-x", type_value="multiple_choice", description="interpolation method", mandatory=False, default_value='spline', example=['nn', 'linear', 'spline']) parser.add_option(name="-r", type_value="multiple_choice", description="""Remove temporary files.""", mandatory=False, default_value='1', example=['0', '1']) parser.add_option(name="-v", type_value="multiple_choice", description="""Verbose.""", mandatory=False, default_value='1', example=['0', '1', '2']) return parser class Transform: def __init__(self, input_filename, warp, fname_dest, output_filename='', verbose=0, crop=0, interp='spline', remove_temp_files=1, debug=0): self.input_filename = input_filename if isinstance(warp, str): self.warp_input = list([warp]) else: self.warp_input = warp self.fname_dest = fname_dest self.output_filename = output_filename self.interp = interp self.crop = crop self.verbose = verbose self.remove_temp_files = remove_temp_files self.debug = debug def apply(self): # Initialization fname_src = self.input_filename # source image (moving) fname_warp_list = self.warp_input # list of warping fields fname_out = self.output_filename # output fname_dest = self.fname_dest # destination image (fix) verbose = self.verbose remove_temp_files = self.remove_temp_files crop_reference = self.crop # if = 1, put 0 everywhere around warping field, if = 2, real crop interp = sct.get_interpolation('isct_antsApplyTransforms', self.interp) # Parse list of warping fields sct.printv('\nParse list of warping fields...', verbose) use_inverse = [] fname_warp_list_invert = [] # fname_warp_list = fname_warp_list.replace(' ', '') # remove spaces # fname_warp_list = fname_warp_list.split(",") # parse with comma for idx_warp, path_warp in enumerate(fname_warp_list): # Check if inverse matrix is specified with '-' at the beginning of file name if path_warp.startswith("-"): use_inverse.append('-i') fname_warp_list[idx_warp] = path_warp[1:] # remove '-' fname_warp_list_invert += [[use_inverse[idx_warp], fname_warp_list[idx_warp]]] else: use_inverse.append('') fname_warp_list_invert += [[path_warp]] path_warp = fname_warp_list[idx_warp] if path_warp.endswith((".nii", ".nii.gz")) \ and msct_image.Image(fname_warp_list[idx_warp]).header.get_intent()[0] != 'vector': raise ValueError("Displacement field in {} is invalid: should be encoded" \ " in a 5D file with vector intent code" \ " (see https://nifti.nimh.nih.gov/pub/dist/src/niftilib/nifti1.h" \ .format(path_warp)) # need to check if last warping field is an affine transfo isLastAffine = False path_fname, file_fname, ext_fname = sct.extract_fname(fname_warp_list_invert[-1][-1]) if ext_fname in ['.txt', '.mat']: isLastAffine = True # check if destination file is 3d if not sct.check_if_3d(fname_dest): sct.printv('ERROR: Destination data must be 3d') # N.B. Here we take the inverse of the warp list, because sct_WarpImageMultiTransform concatenates in the reverse order fname_warp_list_invert.reverse() fname_warp_list_invert = functools.reduce(lambda x,y: x+y, fname_warp_list_invert) # Extract path, file and extension path_src, file_src, ext_src = sct.extract_fname(fname_src) path_dest, file_dest, ext_dest = sct.extract_fname(fname_dest) # Get output folder and file name if fname_out == '': path_out = '' # output in user's current directory file_out = file_src + '_reg' ext_out = ext_src fname_out = os.path.join(path_out, file_out + ext_out) # Get dimensions of data sct.printv('\nGet dimensions of data...', verbose) img_src = msct_image.Image(fname_src) nx, ny, nz, nt, px, py, pz, pt = img_src.dim # nx, ny, nz, nt, px, py, pz, pt = sct.get_dimension(fname_src) sct.printv(' ' + str(nx) + ' x ' + str(ny) + ' x ' + str(nz) + ' x ' + str(nt), verbose) # if 3d if nt == 1: # Apply transformation sct.printv('\nApply transformation...', verbose) if nz in [0, 1]: dim = '2' else: dim = '3' sct.run(['isct_antsApplyTransforms', '-d', dim, '-i', fname_src, '-o', fname_out, '-t', ] + fname_warp_list_invert + [ '-r', fname_dest, ] + interp, verbose=verbose, is_sct_binary=True) # if 4d, loop across the T dimension else: path_tmp = sct.tmp_create(basename="apply_transfo", verbose=verbose) # convert to nifti into temp folder sct.printv('\nCopying input data to tmp folder and convert to nii...', verbose) img_src.save(os.path.join(path_tmp, "data.nii")) sct.copy(fname_dest, os.path.join(path_tmp, file_dest + ext_dest)) fname_warp_list_tmp = [] for fname_warp in fname_warp_list: path_warp, file_warp, ext_warp = sct.extract_fname(fname_warp) sct.copy(fname_warp, os.path.join(path_tmp, file_warp + ext_warp)) fname_warp_list_tmp.append(file_warp + ext_warp) fname_warp_list_invert_tmp = fname_warp_list_tmp[::-1] curdir = os.getcwd() os.chdir(path_tmp) # split along T dimension sct.printv('\nSplit along T dimension...', verbose) im_dat = msct_image.Image('data.nii') im_header = im_dat.hdr data_split_list = sct_image.split_data(im_dat, 3) for im in data_split_list: im.save() # apply transfo sct.printv('\nApply transformation to each 3D volume...', verbose) for it in range(nt): file_data_split = 'data_T' + str(it).zfill(4) + '.nii' file_data_split_reg = 'data_reg_T' + str(it).zfill(4) + '.nii' status, output = sct.run(['isct_antsApplyTransforms', '-d', '3', '-i', file_data_split, '-o', file_data_split_reg, '-t', ] + fname_warp_list_invert_tmp + [ '-r', file_dest + ext_dest, ] + interp, verbose, is_sct_binary=True) # Merge files back sct.printv('\nMerge file back...', verbose) import glob path_out, name_out, ext_out = sct.extract_fname(fname_out) # im_list = [Image(file_name) for file_name in glob.glob('data_reg_T*.nii')] # concat_data use to take a list of image in input, now takes a list of file names to open the files one by one (see issue #715) fname_list = glob.glob('data_reg_T*.nii') fname_list.sort() im_out = sct_image.concat_data(fname_list, 3, im_header['pixdim']) im_out.save(name_out + ext_out) os.chdir(curdir) sct.generate_output_file(os.path.join(path_tmp, name_out + ext_out), fname_out) # Delete temporary folder if specified if int(remove_temp_files): sct.printv('\nRemove temporary files...', verbose) sct.rmtree(path_tmp, verbose=verbose) # 2. crop the resulting image using dimensions from the warping field warping_field = fname_warp_list_invert[-1] # if last warping field is an affine transfo, we need to compute the space of the concatenate warping field: if isLastAffine: sct.printv('WARNING: the resulting image could have wrong apparent results. You should use an affine transformation as last transformation...', verbose, 'warning') elif crop_reference == 1: ImageCropper(input_file=fname_out, output_file=fname_out, ref=warping_field, background=0).crop() # sct.run('sct_crop_image -i '+fname_out+' -o '+fname_out+' -ref '+warping_field+' -b 0') elif crop_reference == 2: ImageCropper(input_file=fname_out, output_file=fname_out, ref=warping_field).crop() # sct.run('sct_crop_image -i '+fname_out+' -o '+fname_out+' -ref '+warping_field) sct.display_viewer_syntax([fname_dest, fname_out], verbose=verbose) # MAIN # ========================================================================================== def main(args=None): # check user arguments if not args: args = sys.argv[1:] # Get parser info parser = get_parser() arguments = parser.parse(args) input_filename = arguments["-i"] fname_dest = arguments["-d"] warp_filename = arguments["-w"] transform = Transform(input_filename=input_filename, fname_dest=fname_dest, warp=warp_filename) if "-crop" in arguments: transform.crop = arguments["-crop"] if "-o" in arguments: transform.output_filename = arguments["-o"] if "-x" in arguments: transform.interp = arguments["-x"] if "-r" in arguments: transform.remove_temp_files = int(arguments["-r"]) transform.verbose = int(arguments.get('-v')) sct.init_sct(log_level=transform.verbose, update=True) # Update log level transform.apply() # START PROGRAM # ========================================================================================== if __name__ == "__main__": sct.init_sct() # # initialize parameters param = Param() # call main function main()

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Python

tests/plugins/test_plugin_base.py

vurankar/mongo-connector

202aa28743855643fddd77d3e66bf1a640df3ed6

[ "Apache-2.0" ]

1

2019-08-24T21:06:00.000Z

tests/plugins/test_plugin_base.py

vurankar/mongo-connector

202aa28743855643fddd77d3e66bf1a640df3ed6

[ "Apache-2.0" ]

13

2017-08-07T04:36:25.000Z

2021-02-08T17:37:27.000Z

tests/plugins/test_plugin_base.py

vurankar/mongo-connector

202aa28743855643fddd77d3e66bf1a640df3ed6

[ "Apache-2.0" ]

4

2018-10-22T17:30:46.000Z

2020-07-07T21:24:48.000Z

# Copyright 2013-2014 MongoDB, 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. """Tests methods in plugin_base.py """ import copy import sys sys.path[0:0] = [""] from mongo_connector.plugins.plugin_base import PluginBase from tests import unittest from tests.plugins.helpers import (BAD_PLUGIN_CONFIGS, get_test_namespace) class TestPluginBase(unittest.TestCase): """ Tests the utils """ def setUp(self): """Initialize test instance. """ self.namespace = get_test_namespace() def test_name(self): """Test name. """ configs = self.namespace.plugins[0] for cfg in configs: obj = PluginBase(cfg) self.assertEqual(cfg['pluginName'], obj.name()) for cfg in BAD_PLUGIN_CONFIGS: obj = PluginBase(cfg) self.assertEqual(obj.name().index('generated'), 0) def test_info(self): """Test info. """ configs = self.namespace.plugins[0] for cfg in configs: obj = PluginBase(cfg) self.assertEqual(cfg['config'], obj.info()) for cfg in BAD_PLUGIN_CONFIGS: obj = PluginBase(cfg) self.assertEqual(obj.info(), {}) def _test_not_implemented_method_by_name(self, name): """Test not implemented method by name. """ configs = copy.deepcopy(self.namespace.plugins) configs.extend(BAD_PLUGIN_CONFIGS) for cfg in configs: obj = PluginBase(cfg) try: method = getattr(obj, name) if not method or not callable(method): raise KeyError method() except NotImplementedError as exc: pass return True def test_invoke(self): """Test invoke. """ flag = self._test_not_implemented_method_by_name('invoke') self.assertEqual(flag, True) def test_bulk_invoke(self): """Test bulk_invoke. """ # Bulk invoke is really implemented but it calls invoke in loop # which returns an not implemented exception. flag = self._test_not_implemented_method_by_name('bulk_invoke') self.assertEqual(flag, True) def test_commit(self): """Test commit. """ flag = self._test_not_implemented_method_by_name('commit') self.assertEqual(flag, True) def test_stop(self): """Test stop. """ flag = self._test_not_implemented_method_by_name('stop') self.assertEqual(flag, True) if __name__ == '__main__': unittest.main()

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