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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2e56a21ee0064aad8337abb9489cfc89eeb27322 | 4,955 | py | Python | docs/conf.py | spewil/RTGraph | 0e3f4502988a36866ac2aaa27e232ade2128d7ea | [
"MIT"
] | 43 | 2015-06-10T23:26:03.000Z | 2021-12-16T11:40:40.000Z | docs/conf.py | spewil/RTGraph | 0e3f4502988a36866ac2aaa27e232ade2128d7ea | [
"MIT"
] | 3 | 2017-06-16T13:29:02.000Z | 2019-03-12T22:33:26.000Z | docs/conf.py | spewil/RTGraph | 0e3f4502988a36866ac2aaa27e232ade2128d7ea | [
"MIT"
] | 31 | 2015-03-19T11:59:53.000Z | 2021-10-10T13:15:55.000Z | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# RTGraph documentation build configuration file, created by
# sphinx-quickstart on Tue Dec 20 22:19:34 2016.
#
# This file is execfile()d with the current directory set to its
# containing dir.
#
# Note that not all possible configuration values are present in this
# autogenerated file.
#
# All configuration values have a default; values that are commented out
# serve to show the default.
# If extensions (or modules to document with autodoc) are in another directory,
# add these directories to sys.path here. If the directory is relative to the
# documentation root, use os.path.abspath to make it absolute, like shown here.
#
import os
import sys
sys.path.insert(0, os.path.abspath('..'))
from rtgraph.core.constants import Constants
# -- General configuration ------------------------------------------------
# If your documentation needs a minimal Sphinx version, state it here.
#
# needs_sphinx = '1.0'
# Add any Sphinx extension module names here, as strings. They can be
# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
# ones.
extensions = ['sphinx.ext.autodoc',
'sphinx.ext.doctest']
# Add any paths that contain templates here, relative to this directory.
templates_path = ['_templates']
# The suffix(es) of source filenames.
# You can specify multiple suffix as a list of string:
#
# source_suffix = ['.rst', '.md']
source_suffix = '.rst'
# The master toctree document.
master_doc = 'index'
# General information about the project.
project = 'RTGraph'
copyright = '2016, Sebastian Sepulveda'
author = 'Sebastian Sepulveda'
# The version info for the project you're documenting, acts as replacement for
# |version| and |release|, also used in various other places throughout the
# built documents.
#
# The short X.Y version.
[major, minor, release] = Constants.app_version.split(".")
version = "{}.{}".format(major, minor)
# The full version, including alpha/beta/rc tags.
release = "{}".format(release)
# The language for content autogenerated by Sphinx. Refer to documentation
# for a list of supported languages.
#
# This is also used if you do content translation via gettext catalogs.
# Usually you set "language" from the command line for these cases.
language = None
# List of patterns, relative to source directory, that match files and
# directories to ignore when looking for source files.
# This patterns also effect to html_static_path and html_extra_path
exclude_patterns = ['_build', 'Thumbs.db', '.DS_Store']
# The name of the Pygments (syntax highlighting) style to use.
pygments_style = 'sphinx'
# If true, `todo` and `todoList` produce output, else they produce nothing.
todo_include_todos = False
# -- Options for HTML output ----------------------------------------------
# The theme to use for HTML and HTML Help pages. See the documentation for
# a list of builtin themes.
#
# html_theme = 'sphinx_rtd_theme'
html_theme = 'alabaster'
# Theme options are theme-specific and customize the look and feel of a theme
# further. For a list of options available for each theme, see the
# documentation.
#
# html_theme_options = {}
# Add any paths that contain custom static files (such as style sheets) here,
# relative to this directory. They are copied after the builtin static files,
# so a file named "default.css" will overwrite the builtin "default.css".
html_static_path = ['_static']
# -- Options for HTMLHelp output ------------------------------------------
# Output file base name for HTML help builder.
htmlhelp_basename = 'RTGraphdoc'
# -- Options for LaTeX output ---------------------------------------------
latex_elements = {
# The paper size ('letterpaper' or 'a4paper').
#
# 'papersize': 'letterpaper',
# The font size ('10pt', '11pt' or '12pt').
#
# 'pointsize': '10pt',
# Additional stuff for the LaTeX preamble.
#
# 'preamble': '',
# Latex figure (float) alignment
#
# 'figure_align': 'htbp',
}
# Grouping the document tree into LaTeX files. List of tuples
# (source start file, target name, title,
# author, documentclass [howto, manual, or own class]).
latex_documents = [
(master_doc, 'RTGraph.tex', 'RTGraph Documentation',
'Sebastian Sepulveda', 'manual'),
]
# -- Options for manual page output ---------------------------------------
# One entry per manual page. List of tuples
# (source start file, name, description, authors, manual section).
man_pages = [
(master_doc, 'rtgraph', 'RTGraph Documentation',
[author], 1)
]
# -- Options for Texinfo output -------------------------------------------
# Grouping the document tree into Texinfo files. List of tuples
# (source start file, target name, title, author,
# dir menu entry, description, category)
texinfo_documents = [
(master_doc, 'RTGraph', 'RTGraph Documentation',
author, 'RTGraph', 'One line description of project.',
'Miscellaneous'),
]
| 30.58642 | 79 | 0.683552 |
4e18ca2164579871a64ba9bda93e7d956f7fa595 | 395 | py | Python | beautifultable/compat.py | digitronik/beautifultable | 23ce72f1d2491f3015e6419e828e2ea499404ecd | [
"MIT"
] | null | null | null | beautifultable/compat.py | digitronik/beautifultable | 23ce72f1d2491f3015e6419e828e2ea499404ecd | [
"MIT"
] | null | null | null | beautifultable/compat.py | digitronik/beautifultable | 23ce72f1d2491f3015e6419e828e2ea499404ecd | [
"MIT"
] | null | null | null | import sys
PY3 = sys.version_info[0] == 3
if PY3:
to_unicode = str
basestring = (str, bytes)
from itertools import zip_longest
from collections.abc import Iterable
else: # pragma: no cover
basestring = basestring
to_unicode = unicode # noqa: F821
from itertools import izip_longest as zip_longest # noqa: F401
from collections import Iterable # noqa: F401
| 24.6875 | 67 | 0.703797 |
da3c93f3300d62ee4bf391d38d9382f29dd0e9db | 2,955 | py | Python | fridrich/server/WStationFuncs.py | Nilusink/Fridrich | 73fb361207af9984ea5d9413c28c90d8fc56d33c | [
"MIT"
] | null | null | null | fridrich/server/WStationFuncs.py | Nilusink/Fridrich | 73fb361207af9984ea5d9413c28c90d8fc56d33c | [
"MIT"
] | null | null | null | fridrich/server/WStationFuncs.py | Nilusink/Fridrich | 73fb361207af9984ea5d9413c28c90d8fc56d33c | [
"MIT"
] | null | null | null | """
for weather-stations to commit data to the pool
Author: Nilusink
"""
from fridrich.server.server_funcs import send_success
from fridrich.classes import User
from fridrich.server import Const
import json
def register(message: dict, user: User, *_args) -> None:
"""
register a new weather-station
"""
tmp: list
try:
tmp = json.load(open(Const.WeatherDir+"all.json", "r"))
except json.JSONDecodeError:
tmp = []
for element in tmp:
if message["station_name"] == element["station_name"]:
mes = {
'Error': 'RegistryError',
"info": "weather-station is already registered"
}
user.send(mes, message_type="Error")
return
tmp.append({
"station_name": message["station_name"],
"location": message["location"]
})
with open(Const.WeatherDir+"all.json", "w") as out_file:
json.dump(tmp, out_file, indent=4)
with open(Const.WeatherDir+message["station_name"], "w") as out_file:
out_file.write("[]")
send_success(user)
def commit_data(message: dict, user: User, *_args) -> None:
"""
commit data for already registered stations
"""
now_data: dict
station_data: dict
if not check_if_registered(message, user, *_args):
mes = {
'Error': 'RegistryError',
"info": "weather-station is not registered yet"
}
user.send(mes, message_type="Error")
return
try:
now_data = json.load(open(Const.WeatherDir+"now.json", "r"))
except json.JSONDecodeError:
now_data = {}
now_data[message["station_name"]] = {
"time": message["time"],
"temp": message["temp"],
"hum": message["hum"],
"press": message["press"]
}
with open(Const.WeatherDir+"now.json", "w") as out_file:
json.dump(now_data, out_file, indent=4)
try:
station_data = json.load(open(Const.WeatherDir+message["station_name"], "r"))
except json.JSONEncoder:
station_data = {}
station_data[message["time"]] = {
"temp": message["temp"],
"hum": message["hum"],
"press": message["press"]
}
with open(Const.WeatherDir + message["station_name"], "w") as out_file:
json.dump(station_data, out_file, indent=4)
send_success(user)
def check_if_registered(message: dict, _user: User, *_args) -> bool:
"""
check if a weather-station is already registered
"""
return message["station_name"] in json.load(open(Const.WeatherDir+"all.json", "r"))
def get_all(_message: dict, user: User, *_args) -> None:
"""
send a dict of all weather-stations with their current measurement
"""
now_data: dict
try:
now_data = json.load(open(Const.WeatherDir+"now.json", "r"))
except json.JSONDecodeError:
now_data = {}
user.send(now_data)
| 26.150442 | 87 | 0.598646 |
8cf3285fc2c30bca6f21b1ac3717714afd942dff | 11,561 | py | Python | widget_team_block/views.py | chr0nu5/core | aa80ccb3ae30dd12a5c848079d1184a830fcb83b | [
"MIT"
] | null | null | null | widget_team_block/views.py | chr0nu5/core | aa80ccb3ae30dd12a5c848079d1184a830fcb83b | [
"MIT"
] | null | null | null | widget_team_block/views.py | chr0nu5/core | aa80ccb3ae30dd12a5c848079d1184a830fcb83b | [
"MIT"
] | null | null | null | from django.shortcuts import render
from django.http import HttpResponse
from django.views.decorators.csrf import csrf_exempt
@csrf_exempt
def get_widget(request):
return HttpResponse('<div class="container webrock-object ui-sortable" data-atts="{"margin":"","padding":"","classes":"","id":""}" data-shortcode="container" data-filter="*" data-filter-exclude="*"><div class="webrock-content"><div class="row margin-top-2x margin-bottom-2x webrock-object ui-sortable" data-atts="{"margin":"","padding":"","classes":"margin-top-2x margin-bottom-2x"}" data-shortcode="row" data-filter="*" data-filter-exclude="*" style="position: relative;"><div class="webrock-content"><div class="col col-md-12 webrock-object ui-sortable" data-atts="{"xs":"","sm":"","md":"col-md-12","lg":"","classes":""}" data-shortcode="column"><div class="webrock-content"><div class="text-center webrock-object" data-atts="{"text":"OUR TEAM","type":"h1","responsive":"","font":"text-heading-bold","style":"","classes":"text-center","animation":""}" data-shortcode="heading" data-filter="*" data-filter-exclude="*"><h1 class="heading text-heading-bold">OUR TEAM</h1></div><div class="textbox text-gray-dark webrock-object" data-atts="{"text":"&lt;p style=&quot;text-align: center;&quot;&gt;Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam&lt;/p&gt;","classes":"","color":"#000000","animation":""}" data-shortcode="textbox" data-filter="*" data-filter-exclude="*"><p style="text-align: center;">Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam</p></div></div></div></div></div><div class="row margin-top-2x margin-bottom-2x webrock-object ui-sortable" data-atts="{"margin":"","padding":"","classes":"margin-top-2x margin-bottom-2x"}" data-shortcode="row" data-filter="*" data-filter-exclude="*" style="position: relative;"><div class="webrock-content"><div class="col col-sm-6 col-md-3 webrock-object ui-sortable" data-atts="{"xs":"","sm":"col-sm-6","md":"col-md-3","lg":"","classes":""}" data-shortcode="column" data-filter="*" data-filter-exclude="*"><div class="webrock-content"><div class="team-member team-member-1 team-member-inverse text-center webrock-object" data-atts="{"style":"team-member-1","image":"img/default/teammember.jpg","name":"John Doe","profession":"Manager","description":"&lt;p&gt;Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.&lt;/p&gt;","theme":"team-member-inverse","social":"{&quot;fa fa-twitter&quot;:&quot;http://twitter.com/grozavcom&quot;,&quot;fa fa-facebook&quot;:&quot;http://facebook.com/grozavcom&quot;,&quot;fa fa-google-plus&quot;:&quot;http;//plus.google.com/#&quot;,&quot;fa fa-linkedin&quot;:&quot;http://linkedin.com/pub/alex-grozav/48/4b3/127&quot;}","animation":"","classes":""}" data-shortcode="teammember" data-filter="*" data-filter-exclude="*"><div class="team-member-img-wrapper"><img src="img/default/teammember.jpg" class="img-fullwidth team-member-image"></div><div class="team-member-details"><h2 class="team-member-name">John Doe</h2><h4 class="team-member-profession">Manager</h4><div class="team-member-description text-sm"><p>Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.</p></div><ul class="team-member-social list-inline"><li><a href="http://twitter.com/grozavcom"><i class="fa fa-twitter"></i></a></li><li><a href="http://facebook.com/grozavcom"><i class="fa fa-facebook"></i></a></li><li><a href="http;//plus.google.com/#"><i class="fa fa-google-plus"></i></a></li><li><a href="http://linkedin.com/pub/alex-grozav/48/4b3/127"><i class="fa fa-linkedin"></i></a></li></ul></div></div></div></div><div class="col col-sm-6 col-md-3 webrock-object ui-sortable" data-atts="{"xs":"","sm":"col-sm-6","md":"col-md-3","lg":"","classes":""}" data-shortcode="column" data-filter="*" data-filter-exclude="*"><div class="webrock-content"><div class="team-member team-member-1 team-member-inverse text-center webrock-object" data-atts="{"style":"team-member-1","image":"img/default/teammember-2.jpg","name":"Lisa Kramer","profession":"Web Developer","description":"&lt;p&gt;Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.&lt;/p&gt;","theme":"team-member-inverse","social":"{&quot;fa fa-twitter&quot;:&quot;http://twitter.com/grozavcom&quot;,&quot;fa fa-facebook&quot;:&quot;http://facebook.com/grozavcom&quot;,&quot;fa fa-google-plus&quot;:&quot;http;//plus.google.com/#&quot;,&quot;fa fa-linkedin&quot;:&quot;http://linkedin.com/pub/alex-grozav/48/4b3/127&quot;}","animation":"","classes":""}" data-shortcode="teammember" data-filter="*" data-filter-exclude="*"><div class="team-member-img-wrapper"><img src="img/default/teammember-2.jpg" class="img-fullwidth team-member-image"></div><div class="team-member-details"><h2 class="team-member-name">Lisa Kramer</h2><h4 class="team-member-profession">Web Developer</h4><div class="team-member-description text-sm"><p>Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.</p></div><ul class="team-member-social list-inline"><li><a href="http://twitter.com/grozavcom"><i class="fa fa-twitter"></i></a></li><li><a href="http://facebook.com/grozavcom"><i class="fa fa-facebook"></i></a></li><li><a href="http;//plus.google.com/#"><i class="fa fa-google-plus"></i></a></li><li><a href="http://linkedin.com/pub/alex-grozav/48/4b3/127"><i class="fa fa-linkedin"></i></a></li></ul></div></div></div></div><div class="col col-sm-6 col-md-3 webrock-object ui-sortable" data-atts="{"xs":"","sm":"col-sm-6","md":"col-md-3","lg":"","classes":""}" data-shortcode="column" data-filter="*" data-filter-exclude="*"><div class="webrock-content"><div class="team-member team-member-1 team-member-inverse text-center webrock-object" data-atts="{"style":"team-member-1","image":"img/default/teammember-3.jpg","name":"Daniel Ray","profession":"Web Developer","description":"&lt;p&gt;Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.&lt;/p&gt;","theme":"team-member-inverse","social":"{&quot;fa fa-twitter&quot;:&quot;http://twitter.com/grozavcom&quot;,&quot;fa fa-facebook&quot;:&quot;http://facebook.com/grozavcom&quot;,&quot;fa fa-google-plus&quot;:&quot;http;//plus.google.com/#&quot;,&quot;fa fa-linkedin&quot;:&quot;http://linkedin.com/pub/alex-grozav/48/4b3/127&quot;}","animation":"","classes":""}" data-shortcode="teammember" data-filter="*" data-filter-exclude="*"><div class="team-member-img-wrapper"><img src="img/default/teammember-3.jpg" class="img-fullwidth team-member-image"></div><div class="team-member-details"><h2 class="team-member-name">Daniel Ray</h2><h4 class="team-member-profession">Web Developer</h4><div class="team-member-description text-sm"><p>Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.</p></div><ul class="team-member-social list-inline"><li><a href="http://twitter.com/grozavcom"><i class="fa fa-twitter"></i></a></li><li><a href="http://facebook.com/grozavcom"><i class="fa fa-facebook"></i></a></li><li><a href="http;//plus.google.com/#"><i class="fa fa-google-plus"></i></a></li><li><a href="http://linkedin.com/pub/alex-grozav/48/4b3/127"><i class="fa fa-linkedin"></i></a></li></ul></div></div></div></div><div class="col col-sm-6 col-md-3 webrock-object ui-sortable" data-atts="{"xs":"","sm":"col-sm-6","md":"col-md-3","lg":"","classes":""}" data-shortcode="column" data-filter="*" data-filter-exclude="*"><div class="webrock-content"><div class="team-member team-member-1 team-member-inverse text-center webrock-object" data-atts="{"style":"team-member-1","image":"img/default/teammember-4.jpg","name":"Alice Lane","profession":"Web Designer","description":"&lt;p&gt;Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.&lt;/p&gt;","theme":"team-member-inverse","social":"{&quot;fa fa-twitter&quot;:&quot;http://twitter.com/grozavcom&quot;,&quot;fa fa-facebook&quot;:&quot;http://facebook.com/grozavcom&quot;,&quot;fa fa-google-plus&quot;:&quot;http;//plus.google.com/#&quot;,&quot;fa fa-linkedin&quot;:&quot;http://linkedin.com/pub/alex-grozav/48/4b3/127&quot;}","animation":"","classes":""}" data-shortcode="teammember" data-filter="*" data-filter-exclude="*"><div class="team-member-img-wrapper"><img src="img/default/teammember-4.jpg" class="img-fullwidth team-member-image"></div><div class="team-member-details"><h2 class="team-member-name">Alice Lane</h2><h4 class="team-member-profession">Web Designer</h4><div class="team-member-description text-sm"><p>Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.</p></div><ul class="team-member-social list-inline"><li><a href="http://twitter.com/grozavcom"><i class="fa fa-twitter"></i></a></li><li><a href="http://facebook.com/grozavcom"><i class="fa fa-facebook"></i></a></li><li><a href="http;//plus.google.com/#"><i class="fa fa-google-plus"></i></a></li><li><a href="http://linkedin.com/pub/alex-grozav/48/4b3/127"><i class="fa fa-linkedin"></i></a></li></ul></div></div></div></div></div></div></div></div>') | 1,445.125 | 11,395 | 0.723121 |
04ca7da1043045a1b5703433113c9a65a4a85c9e | 146,983 | py | Python | python/paddle/tensor/math.py | xiaoyangyang2/Paddle | b1a4668c5ff39e44efcfea46d567a5c398fdf3dc | [
"Apache-2.0"
] | null | null | null | python/paddle/tensor/math.py | xiaoyangyang2/Paddle | b1a4668c5ff39e44efcfea46d567a5c398fdf3dc | [
"Apache-2.0"
] | null | null | null | python/paddle/tensor/math.py | xiaoyangyang2/Paddle | b1a4668c5ff39e44efcfea46d567a5c398fdf3dc | [
"Apache-2.0"
] | null | null | null | # Copyright (c) 2020 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.
"""
math functions
"""
from __future__ import print_function
import numpy as np
from paddle.common_ops_import import VarDesc
from paddle.common_ops_import import dygraph_only
from paddle.common_ops_import import OpProtoHolder
from paddle.common_ops_import import templatedoc
from paddle.common_ops_import import dygraph_utils
from paddle.tensor import cast
from paddle.tensor.attribute import _complex_to_real_dtype
import paddle
from paddle.static import Variable
from ..framework import core, _in_eager_mode
from ..framework import _varbase_creator, convert_np_dtype_to_dtype_
from ..fluid.layer_helper import LayerHelper
from ..fluid.data_feeder import check_variable_and_dtype, check_type, check_dtype, convert_dtype
from ..fluid.layers.layer_function_generator import _generate_doc_string_, generate_activation_fn, generate_layer_fn
from ..fluid.dygraph.inplace_utils import inplace_apis_in_dygraph_only
# TODO: define math functions
# yapf: disable
from ..fluid.layers import abs # noqa: F401
from ..fluid.layers import acos # noqa: F401
from ..fluid.layers import asin # noqa: F401
from ..fluid.layers import ceil # noqa: F401
from ..fluid.layers import ceil_ # noqa: F401
from ..fluid.layers import cos # noqa: F401
from ..fluid.layers import tan # noqa: F401
from ..fluid.layers import sinh # noqa: F401
from ..fluid.layers import cosh # noqa: F401
from ..fluid.layers import exp # noqa: F401
from ..fluid.layers import exp_ # noqa: F401
from ..fluid.layers import expm1 # noqa: F401
from ..fluid.layers import floor # noqa: F401
from ..fluid.layers import floor_ # noqa: F401
from ..fluid.layers import log # noqa: F401
from ..fluid.layers import reciprocal # noqa: F401
from ..fluid.layers import reciprocal_ # noqa: F401
from ..fluid.layers import round # noqa: F401
from ..fluid.layers import round_ # noqa: F401
from ..fluid.layers import rsqrt # noqa: F401
from ..fluid.layers import rsqrt_ # noqa: F401
from ..fluid.layers import scale # noqa: F401
from ..fluid.layers import square # noqa: F401
from ..fluid.layers import stanh # noqa: F401
from ..fluid.layers import atan # noqa: F401
from ..fluid.layers import erf # noqa: F401
from ..fluid.layers import sqrt # noqa: F401
from ..fluid.layers import sqrt_ # noqa: F401
from ..fluid.layers import sin # noqa: F401
from ..fluid.layers import lgamma # noqa: F401
from ..fluid.layers import asinh # noqa: F401
from ..fluid.layers import acosh # noqa: F401
from ..fluid.layers import atanh # noqa: F401
from ..fluid.layers import multiplex # noqa: F401
from ..fluid.layers import reduce_prod
from ..fluid.layers import elementwise_sub
from paddle import _C_ops
__all__ = []
_supported_int_dtype_ = [
VarDesc.VarType.UINT8,
VarDesc.VarType.INT8,
VarDesc.VarType.INT16,
VarDesc.VarType.INT32,
VarDesc.VarType.INT64,
]
_supported_float_dtype_ = [
VarDesc.VarType.FP32,
VarDesc.VarType.FP64,
]
@inplace_apis_in_dygraph_only
def scale_(x, scale=1.0, bias=0.0, bias_after_scale=True, act=None, name=None):
"""
Inplace version of ``scale`` API, the output Tensor will be inplaced with input ``x``.
Please refer to :ref:`api_tensor_scale`.
"""
_scale = scale.numpy().item(0) if isinstance(scale, Variable) else scale
return _C_ops.scale_(x, 'scale',
float(_scale), 'bias',
float(bias), 'bias_after_scale', bias_after_scale)
def pow(x, y, name=None):
"""
Compute the power of tensor elements. The equation is:
.. math::
out = x^{y}
**Note**:
``paddle.pow`` supports broadcasting. If you want know more about broadcasting, please refer to :ref:`user_guide_broadcasting` .
Args:
x (Tensor): An N-D Tensor, the data type is float32, float64, int32 or int64.
y (float|int|Tensor): If it is an N-D Tensor, its data type should be the same as `x`.
name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
Returns:
N-D Tensor. A location into which the result is stored. Its dimension and data type are the same as `x`.
Examples:
.. code-block:: python
import paddle
x = paddle.to_tensor([1, 2, 3], dtype='float32')
# example 1: y is a float or int
res = paddle.pow(x, 2)
print(res)
# Tensor(shape=[3], dtype=float32, place=CUDAPlace(0), stop_gradient=True,
# [1., 4., 9.])
res = paddle.pow(x, 2.5)
print(res)
# Tensor(shape=[3], dtype=float32, place=CUDAPlace(0), stop_gradient=True,
# [1. , 5.65685415 , 15.58845711])
# example 2: y is a Tensor
y = paddle.to_tensor([2], dtype='float32')
res = paddle.pow(x, y)
print(res)
# Tensor(shape=[3], dtype=float32, place=CUDAPlace(0), stop_gradient=True,
# [1., 4., 9.])
"""
# in dynamic graph mode
if paddle.in_dynamic_mode():
if isinstance(y, (int, float)):
return _C_ops.pow(x, 'factor', y)
elif isinstance(y, (paddle.Tensor, Variable)):
return _elementwise_op_in_dygraph(
x, y, axis=-1, act=None, op_name='elementwise_pow')
else:
raise TypeError('y must be scalar or tensor type, but received: %s '% (y.dtype))
# in static graph mode
else:
if isinstance(y, (int, float)):
helper = LayerHelper('pow', **locals())
inputs = {'X': x}
attrs = {'factor': y}
out = helper.create_variable_for_type_inference(dtype=x.dtype)
helper.append_op(
type='pow', inputs=inputs, outputs={'Out': out}, attrs=attrs)
return out
elif isinstance(y, (paddle.Tensor, Variable)):
# TODO A potential speed improvement is supporting different types in C++ and removing the cast ops here
helper = LayerHelper('elementwise_pow', **locals())
out = helper.create_variable_for_type_inference(dtype=x.dtype)
return _elementwise_op(LayerHelper('elementwise_pow', **locals()))
else:
raise TypeError('y must be scalar or tensor type, but received: %s '% (type(y)))
@dygraph_only
def _elementwise_op_in_dygraph(x,
y,
axis=-1,
act=None,
use_mkldnn=False,
op_name=None):
op = getattr(_C_ops, op_name)
out = op(x, y, 'axis', axis, 'use_mkldnn', use_mkldnn)
return dygraph_utils._append_activation_in_dygraph(
out, act, use_mkldnn=use_mkldnn)
def _elementwise_op(helper):
op_type = helper.layer_type
original_op_type = helper.kwargs.get('original_op_type', op_type)
x = helper.kwargs.get('x', None)
y = helper.kwargs.get('y', None)
out = helper.kwargs.get('out', None)
assert x is not None, 'x cannot be None in {}'.format(original_op_type)
assert y is not None, 'y cannot be None in {}'.format(original_op_type)
check_variable_and_dtype(
x, 'x', ['float16', 'float32', 'float64', 'int32', 'int64', 'bool'],
original_op_type)
check_variable_and_dtype(
y, 'y', ['float16', 'float32', 'float64', 'int32', 'int64', 'bool'],
original_op_type)
axis = helper.kwargs.get('axis', -1)
use_mkldnn = helper.kwargs.get('use_mkldnn', False)
name = helper.kwargs.get('name', None)
if out is None:
if name is None:
out = helper.create_variable_for_type_inference(dtype=x.dtype)
else:
out = helper.create_variable(name=name, dtype=x.dtype, persistable=False)
helper.append_op(
type=op_type,
inputs={'X': x,
'Y': y},
outputs={'Out': out},
attrs={'axis': axis,
'use_mkldnn': use_mkldnn})
return helper.append_activation(out)
def add(x, y, name=None):
"""
Examples:
.. code-block:: python
import paddle
x = paddle.to_tensor([2, 3, 4], 'float64')
y = paddle.to_tensor([1, 5, 2], 'float64')
z = paddle.add(x, y)
print(z) # [3., 8., 6. ]
"""
if paddle.in_dynamic_mode():
if _in_eager_mode():
return _C_ops.final_state_add( x, y)
return _C_ops.elementwise_add(x, y)
return _elementwise_op(LayerHelper('elementwise_add', **locals()))
@inplace_apis_in_dygraph_only
def add_(x, y, name=None):
"""
Inplace version of ``add`` API, the output Tensor will be inplaced with input ``x``.
Please refer to :ref:`api_tensor_add`.
"""
op_type = 'elementwise_add_'
axis = -1
out_shape = broadcast_shape(x.shape, y.shape)
if out_shape != x.shape:
raise ValueError("The shape of broadcast output {} is different from that of inplace tensor {} in the Inplace operation.".format(out_shape, x.shape))
out = _elementwise_op_in_dygraph(
x, y, axis=axis, op_name=op_type)
return out
def subtract(x, y, name=None):
"""
Substract two tensors element-wise. The equation is:
.. math::
out = x - y
**Note**:
``paddle.subtract`` supports broadcasting. If you want know more about broadcasting, please refer to :ref:`user_guide_broadcasting` .
Args:
x (Tensor): the input tensor, it's data type should be float32, float64, int32, int64.
y (Tensor): the input tensor, it's data type should be float32, float64, int32, int64.
name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
Returns:
N-D Tensor. A location into which the result is stored. If x, y have different shapes and are "broadcastable", the resulting tensor shape is the shape of x and y after broadcasting. If x, y have the same shape, its shape is the same as x and y.
Examples:
.. code-block:: python
import numpy as np
import paddle
x = paddle.to_tensor([[1, 2], [7, 8]])
y = paddle.to_tensor([[5, 6], [3, 4]])
res = paddle.subtract(x, y)
print(res)
# [[-4, -4],
# [4, 4]]
x = paddle.to_tensor([[[1, 2, 3], [1, 2, 3]]])
y = paddle.to_tensor([1, 0, 4])
res = paddle.subtract(x, y)
print(res)
# [[[ 0, 2, -1],
# [ 0, 2, -1]]]
x = paddle.to_tensor([2, np.nan, 5], dtype='float32')
y = paddle.to_tensor([1, 4, np.nan], dtype='float32')
res = paddle.subtract(x, y)
print(res)
# [ 1., nan, nan]
x = paddle.to_tensor([5, np.inf, -np.inf], dtype='float64')
y = paddle.to_tensor([1, 4, 5], dtype='float64')
res = paddle.subtract(x, y)
print(res)
# [ 4., inf., -inf.]
"""
op_type = 'elementwise_sub'
axis = -1
act = None
if paddle.in_dynamic_mode():
if _in_eager_mode():
return _C_ops.final_state_subtract(x, y)
return _elementwise_op_in_dygraph(
x, y, axis=axis, act=act, op_name=op_type)
return _elementwise_op(LayerHelper(op_type, **locals()))
@inplace_apis_in_dygraph_only
def subtract_(x, y, name=None):
"""
Inplace version of ``subtract`` API, the output Tensor will be inplaced with input ``x``.
Please refer to :ref:`api_tensor_subtract`.
"""
axis = -1
act = None
out_shape = broadcast_shape(x.shape, y.shape)
if out_shape != x.shape:
raise ValueError("The shape of broadcast output {} is different from that of inplace tensor {} in the Inplace operation.".format(out_shape, x.shape))
out = _elementwise_op_in_dygraph(
x, y, axis=axis, act=act, op_name='elementwise_sub_')
return out
def divide(x, y, name=None):
"""
Divide two tensors element-wise. The equation is:
.. math::
out = x / y
**Note**:
``paddle.divide`` supports broadcasting. If you want know more about broadcasting, please refer to :ref:`user_guide_broadcasting` .
Args:
x (Tensor): the input tensor, it's data type should be float32, float64, int32, int64.
y (Tensor): the input tensor, it's data type should be float32, float64, int32, int64.
name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
Returns:
N-D Tensor. A location into which the result is stored. If x, y have different shapes and are "broadcastable", the resulting tensor shape is the shape of x and y after broadcasting. If x, y have the same shape, its shape is the same as x and y.
Examples:
.. code-block:: python
import paddle
x = paddle.to_tensor([2, 3, 4], dtype='float64')
y = paddle.to_tensor([1, 5, 2], dtype='float64')
z = paddle.divide(x, y)
print(z) # [2., 0.6, 2.]
"""
op_type = 'elementwise_div'
axis = -1
act = None
if paddle.in_dynamic_mode():
if _in_eager_mode():
return _C_ops.final_state_divide( x, y)
return _elementwise_op_in_dygraph(
x, y, axis=axis, act=act, op_name=op_type)
return _elementwise_op(LayerHelper(op_type, **locals()))
def floor_divide(x, y, name=None):
"""
Floor divide two tensors element-wise. The equation is:
.. math::
out = x // y
**Note**:
``paddle.floor_divide`` supports broadcasting. If you want know more about broadcasting, please refer to :ref:`user_guide_broadcasting` .
Args:
x (Tensor): the input tensor, it's data type should be int32, int64.
y (Tensor): the input tensor, it's data type should be int32, int64.
name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
Returns:
N-D Tensor. A location into which the result is stored. It's dimension equals with $x$.
Examples:
.. code-block:: python
import paddle
x = paddle.to_tensor([2, 3, 8, 7])
y = paddle.to_tensor([1, 5, 3, 3])
z = paddle.floor_divide(x, y)
print(z) # [2, 0, 2, 2]
"""
op_type = 'elementwise_floordiv'
axis = -1
if paddle.in_dynamic_mode():
return _elementwise_op_in_dygraph(
x, y, axis=axis, op_name=op_type)
return _elementwise_op(LayerHelper(op_type, **locals()))
def remainder(x, y, name=None):
r"""
Mod two tensors element-wise. The equation is:
.. math::
out = x \% y
**Note**:
``paddle.remainder`` supports broadcasting. If you want know more about broadcasting, please refer to :ref:`user_guide_broadcasting` .
Args:
x (Tensor): the input tensor, it's data type should be float32, float64, int32, int64.
y (Tensor): the input tensor, it's data type should be float32, float64, int32, int64.
name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
Returns:
N-D Tensor. A location into which the result is stored. If x, y have different shapes and are "broadcastable", the resulting tensor shape is the shape of x and y after broadcasting. If x, y have the same shape, its shape is the same as x and y.
Examples:
.. code-block:: python
import paddle
x = paddle.to_tensor([2, 3, 8, 7])
y = paddle.to_tensor([1, 5, 3, 3])
z = paddle.remainder(x, y)
print(z) # [0, 3, 2, 1]
"""
op_type = 'elementwise_mod'
axis = -1
if paddle.in_dynamic_mode():
return _elementwise_op_in_dygraph(
x, y, axis=axis, op_name=op_type)
return _elementwise_op(LayerHelper(op_type, **locals()))
mod = remainder # noqa: F841
floor_mod = remainder # noqa: F841
def multiply(x, y, name=None):
"""
multiply two tensors element-wise. The equation is:
.. math::
out = x * y
**Note**:
``paddle.multiply`` supports broadcasting. If you would like to know more about broadcasting, please refer to :ref:`user_guide_broadcasting` .
Args:
x (Tensor): the input tensor, its data type should be one of float32, float64, int32, int64, bool.
y (Tensor): the input tensor, its data type should be one of float32, float64, int32, int64, bool.
name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
Returns:
N-D Tensor. A location into which the result is stored. If x, y have different shapes and are "broadcastable", the resulting tensor shape is the shape of x and y after broadcasting. If x, y have the same shape, its shape is the same as x and y.
Examples:
.. code-block:: python
import paddle
x = paddle.to_tensor([[1, 2], [3, 4]])
y = paddle.to_tensor([[5, 6], [7, 8]])
res = paddle.multiply(x, y)
print(res) # [[5, 12], [21, 32]]
x = paddle.to_tensor([[[1, 2, 3], [1, 2, 3]]])
y = paddle.to_tensor([2])
res = paddle.multiply(x, y)
print(res) # [[[2, 4, 6], [2, 4, 6]]]
"""
op_type = 'elementwise_mul'
act = None
axis = -1
if paddle.in_dynamic_mode():
if _in_eager_mode():
return _C_ops.final_state_multiply(x, y)
return _elementwise_op_in_dygraph(
x, y, axis=axis, act=act, op_name=op_type)
if x.dtype != y.dtype:
raise TypeError(
'Input tensors must be same type, but received type of x: %s, type of y: %s '
% (x.dtype, y.dtype))
return _elementwise_op(LayerHelper(op_type, **locals()))
def maximum(x, y, name=None):
"""
Compare two tensors and returns a new tensor containing the element-wise maxima. The equation is:
.. math::
out = max(x, y)
**Note**:
``paddle.maximum`` supports broadcasting. If you want know more about broadcasting, please refer to :ref:`user_guide_broadcasting` .
Args:
x (Tensor): the input tensor, it's data type should be float32, float64, int32, int64.
y (Tensor): the input tensor, it's data type should be float32, float64, int32, int64.
name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
Returns:
N-D Tensor. A location into which the result is stored. If x, y have different shapes and are "broadcastable", the resulting tensor shape is the shape of x and y after broadcasting. If x, y have the same shape, its shape is the same as x and y.
Examples:
.. code-block:: python
import numpy as np
import paddle
x = paddle.to_tensor([[1, 2], [7, 8]])
y = paddle.to_tensor([[3, 4], [5, 6]])
res = paddle.maximum(x, y)
print(res)
# [[3, 4],
# [7, 8]]
x = paddle.to_tensor([[1, 2, 3], [1, 2, 3]])
y = paddle.to_tensor([3, 0, 4])
res = paddle.maximum(x, y)
print(res)
# [[3, 2, 4],
# [3, 2, 4]]
x = paddle.to_tensor([2, 3, 5], dtype='float32')
y = paddle.to_tensor([1, np.nan, np.nan], dtype='float32')
res = paddle.maximum(x, y)
print(res)
# [ 2., nan, nan]
x = paddle.to_tensor([5, 3, np.inf], dtype='float32')
y = paddle.to_tensor([1, -np.inf, 5], dtype='float32')
res = paddle.maximum(x, y)
print(res)
# [ 5., 3., inf.]
"""
op_type = 'elementwise_max'
axis = -1
act = None
if paddle.in_dynamic_mode():
return _elementwise_op_in_dygraph(
x, y, axis=axis, act=act, op_name=op_type)
return _elementwise_op(LayerHelper(op_type, **locals()))
def minimum(x, y, name=None):
"""
Compare two tensors and returns a new tensor containing the element-wise minima. The equation is:
.. math::
out = min(x, y)
**Note**:
``paddle.minimum`` supports broadcasting. If you want know more about broadcasting, please refer to :ref:`user_guide_broadcasting` .
Args:
x (Tensor): the input tensor, it's data type should be float32, float64, int32, int64.
y (Tensor): the input tensor, it's data type should be float32, float64, int32, int64.
name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
Returns:
N-D Tensor. A location into which the result is stored. If x, y have different shapes and are "broadcastable", the resulting tensor shape is the shape of x and y after broadcasting. If x, y have the same shape, its shape is the same as x and y.
Examples:
.. code-block:: python
import numpy as np
import paddle
x = paddle.to_tensor([[1, 2], [7, 8]])
y = paddle.to_tensor([[3, 4], [5, 6]])
res = paddle.minimum(x, y)
print(res)
# [[1, 2],
# [5, 6]]
x = paddle.to_tensor([[[1, 2, 3], [1, 2, 3]]])
y = paddle.to_tensor([3, 0, 4])
res = paddle.minimum(x, y)
print(res)
# [[[1, 0, 3],
# [1, 0, 3]]]
x = paddle.to_tensor([2, 3, 5], dtype='float32')
y = paddle.to_tensor([1, np.nan, np.nan], dtype='float32')
res = paddle.minimum(x, y)
print(res)
# [ 1., nan, nan]
x = paddle.to_tensor([5, 3, np.inf], dtype='float64')
y = paddle.to_tensor([1, -np.inf, 5], dtype='float64')
res = paddle.minimum(x, y)
print(res)
# [ 1., -inf., 5.]
"""
op_type = 'elementwise_min'
axis = -1
act = None
if paddle.in_dynamic_mode():
return _elementwise_op_in_dygraph(
x, y, axis=axis, act=act, op_name=op_type)
return _elementwise_op(LayerHelper(op_type, **locals()))
def fmax(x, y, name=None):
"""
Compares the elements at the corresponding positions of the two tensors and returns a new tensor containing the maximum value of the element.
If one of them is a nan value, the other value is directly returned, if both are nan values, then the first nan value is returned.
The equation is:
.. math::
out = fmax(x, y)
**Note**:
``paddle.fmax`` supports broadcasting. If you want know more about broadcasting, please refer to :ref:`user_guide_broadcasting` .
Args:
x (Tensor): the input tensor, it's data type should be float32, float64, int32, int64.
y (Tensor): the input tensor, it's data type should be float32, float64, int32, int64.
name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
Returns:
N-D Tensor. A location into which the result is stored. If x, y have different shapes and are "broadcastable", the resulting tensor shape is the shape of x and y after broadcasting. If x, y have the same shape, its shape is the same as x and y.
Examples:
.. code-block:: python
import numpy as np
import paddle
x = paddle.to_tensor([[1, 2], [7, 8]])
y = paddle.to_tensor([[3, 4], [5, 6]])
res = paddle.fmax(x, y)
print(res)
# [[3, 4],
# [7, 8]]
x = paddle.to_tensor([[1, 2, 3], [1, 2, 3]])
y = paddle.to_tensor([3, 0, 4])
res = paddle.fmax(x, y)
print(res)
# [[3, 2, 4],
# [3, 2, 4]]
x = paddle.to_tensor([2, 3, 5], dtype='float32')
y = paddle.to_tensor([1, np.nan, np.nan], dtype='float32')
res = paddle.fmax(x, y)
print(res)
# [ 2., 3., 5.]
x = paddle.to_tensor([5, 3, np.inf], dtype='float32')
y = paddle.to_tensor([1, -np.inf, 5], dtype='float32')
res = paddle.fmax(x, y)
print(res)
# [ 5., 3., inf.]
"""
op_type = 'elementwise_fmax'
axis = -1
act = None
if paddle.in_dynamic_mode():
return _elementwise_op_in_dygraph(
x, y, axis=axis, act=act, op_name=op_type)
return _elementwise_op(LayerHelper(op_type, **locals()))
def fmin(x, y, name=None):
"""
Compares the elements at the corresponding positions of the two tensors and returns a new tensor containing the minimum value of the element.
If one of them is a nan value, the other value is directly returned, if both are nan values, then the first nan value is returned.
The equation is:
.. math::
out = fmin(x, y)
**Note**:
``paddle.fmin`` supports broadcasting. If you want know more about broadcasting, please refer to :ref:`user_guide_broadcasting` .
Args:
x (Tensor): the input tensor, it's data type should be float32, float64, int32, int64.
y (Tensor): the input tensor, it's data type should be float32, float64, int32, int64.
name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
Returns:
N-D Tensor. A location into which the result is stored. If x, y have different shapes and are "broadcastable", the resulting tensor shape is the shape of x and y after broadcasting. If x, y have the same shape, its shape is the same as x and y.
Examples:
.. code-block:: python
import numpy as np
import paddle
x = paddle.to_tensor([[1, 2], [7, 8]])
y = paddle.to_tensor([[3, 4], [5, 6]])
res = paddle.fmin(x, y)
print(res)
# [[1, 2],
# [5, 6]]
x = paddle.to_tensor([[[1, 2, 3], [1, 2, 3]]])
y = paddle.to_tensor([3, 0, 4])
res = paddle.fmin(x, y)
print(res)
# [[[1, 0, 3],
# [1, 0, 3]]]
x = paddle.to_tensor([2, 3, 5], dtype='float32')
y = paddle.to_tensor([1, np.nan, np.nan], dtype='float32')
res = paddle.fmin(x, y)
print(res)
# [ 1., 3., 5.]
x = paddle.to_tensor([5, 3, np.inf], dtype='float64')
y = paddle.to_tensor([1, -np.inf, 5], dtype='float64')
res = paddle.fmin(x, y)
print(res)
# [ 1., -inf., 5.]
"""
op_type = 'elementwise_fmin'
axis = -1
act = None
if paddle.in_dynamic_mode():
return _elementwise_op_in_dygraph(
x, y, axis=axis, act=act, op_name=op_type)
return _elementwise_op(LayerHelper(op_type, **locals()))
for func in [
add,
multiply
]:
proto_dict = {'add': 'elementwise_add', 'multiply': 'elementwise_mul'}
op_proto = OpProtoHolder.instance().get_op_proto(proto_dict[func.__name__])
additional_args_lines = [
"name (string, optional): Name of the output. \
Default is None. It's used to print debug info for developers. Details: \
:ref:`api_guide_Name` "
]
func.__doc__ = _generate_doc_string_(
op_proto,
additional_args_lines=additional_args_lines,
skip_attrs_set={"x_data_format", "y_data_format", "axis",
"use_quantizer", "mkldnn_data_type", "Scale_x", "Scale_y", "Scale_out"
}) + """\n""" + str(func.__doc__)
def sum(x, axis=None, dtype=None, keepdim=False, name=None):
"""
Computes the sum of tensor elements over the given dimension.
Args:
x (Tensor): An N-D Tensor, the data type is bool, float16, float32, float64, int32 or int64.
axis (int|list|tuple, optional): The dimensions along which the sum is performed. If
:attr:`None`, sum all elements of :attr:`x` and return a
Tensor with a single element, otherwise must be in the
range :math:`[-rank(x), rank(x))`. If :math:`axis[i] < 0`,
the dimension to reduce is :math:`rank + axis[i]`.
dtype (str, optional): The dtype of output Tensor. The default value is None, the dtype
of output is the same as input Tensor `x`.
keepdim (bool, optional): Whether to reserve the reduced dimension in the
output Tensor. The result Tensor will have one fewer dimension
than the :attr:`x` unless :attr:`keepdim` is true, default
value is False.
name (str, optional): The default value is None. Normally there is no need for
user to set this property. For more information, please refer to :ref:`api_guide_Name`
Returns:
Tensor: Results of summation operation on the specified axis of input Tensor `x`,
if `x.dtype='bool'`, `x.dtype='int32'`, it's data type is `'int64'`,
otherwise it's data type is the same as `x`.
Raises:
TypeError: The type of :attr:`axis` must be int, list or tuple.
Examples:
.. code-block:: python
import paddle
# x is a Tensor with following elements:
# [[0.2, 0.3, 0.5, 0.9]
# [0.1, 0.2, 0.6, 0.7]]
# Each example is followed by the corresponding output tensor.
x = paddle.to_tensor([[0.2, 0.3, 0.5, 0.9],
[0.1, 0.2, 0.6, 0.7]])
out1 = paddle.sum(x) # [3.5]
out2 = paddle.sum(x, axis=0) # [0.3, 0.5, 1.1, 1.6]
out3 = paddle.sum(x, axis=-1) # [1.9, 1.6]
out4 = paddle.sum(x, axis=1, keepdim=True) # [[1.9], [1.6]]
# y is a Tensor with shape [2, 2, 2] and elements as below:
# [[[1, 2], [3, 4]],
# [[5, 6], [7, 8]]]
# Each example is followed by the corresponding output tensor.
y = paddle.to_tensor([[[1, 2], [3, 4]],
[[5, 6], [7, 8]]])
out5 = paddle.sum(y, axis=[1, 2]) # [10, 26]
out6 = paddle.sum(y, axis=[0, 1]) # [16, 20]
# x is a Tensor with following elements:
# [[True, True, True, True]
# [False, False, False, False]]
# Each example is followed by the corresponding output tensor.
x = paddle.to_tensor([[True, True, True, True],
[False, False, False, False]])
out7 = paddle.sum(x) # [4]
out8 = paddle.sum(x, axis=0) # [1, 1, 1, 1]
out9 = paddle.sum(x, axis=1) # [4, 0]
"""
if axis is not None and not isinstance(axis, (list, tuple)):
axis = [axis]
if not axis:
reduce_all_flag = True
else:
if len(axis) == len(x.shape):
reduce_all_flag = True
else:
reduce_all_flag = False
def get_dtype(x, dtype):
if dtype is not None:
return (True, dtype)
src_type = convert_dtype(x.dtype)
if src_type in ['bool','int32', 'int64']:
return (True, 'int64')
return (False, src_type)
dtype_flag, dtype = get_dtype(x, dtype)
if paddle.in_dynamic_mode():
axis = axis if axis != None and axis != [] else [0]
if dtype_flag:
return _C_ops.reduce_sum(x, 'dim', axis, 'keep_dim', keepdim,
'reduce_all', reduce_all_flag, 'in_dtype',
x.dtype, 'out_dtype',
convert_np_dtype_to_dtype_(dtype))
else:
return _C_ops.reduce_sum(x, 'dim', axis, 'keep_dim', keepdim,
'reduce_all', reduce_all_flag)
attrs = {
'dim': axis if axis != None and axis != [] and axis != () else [0],
'keep_dim': keepdim,
'reduce_all': reduce_all_flag
}
if dtype_flag:
attrs.update({
'in_dtype': x.dtype,
'out_dtype': convert_np_dtype_to_dtype_(dtype)
})
check_variable_and_dtype(
x, 'x', ['bool', 'float16', 'float32', 'float64',
'int16', 'int32', 'int64', 'complex64', 'complex128',
u'bool', u'float16', u'float32', u'float64',
u'int32', u'int64', u'complex64', u'complex128'], 'sum')
check_type(axis, 'axis', (int, list, tuple, type(None)), 'sum')
helper = LayerHelper('sum', **locals())
if dtype_flag:
out = helper.create_variable_for_type_inference(
dtype=convert_np_dtype_to_dtype_(dtype))
else:
out = helper.create_variable_for_type_inference(dtype=x.dtype)
helper.append_op(
type='reduce_sum',
inputs={'X': x},
outputs={'Out': out},
attrs=attrs)
return out
def nansum(x, axis=None, dtype=None, keepdim=False, name=None):
"""
Computes the sum of tensor elements over the given axis, treating Not a Numbers (NaNs) as zero.
Args:
x (Tensor): An N-D Tensor, the data type is float32, float64, int32 or int64.
axis (int|list|tuple, optional): The dimensions along which the nansum is performed. If
:attr:`None`, nansum all elements of :attr:`x` and return a
Tensor with a single element, otherwise must be in the
range :math:`[-rank(x), rank(x))`. If :math:`axis[i] < 0`,
the dimension to reduce is :math:`rank + axis[i]`.
dtype (str, optional): The dtype of output Tensor. The default value is None, the dtype
of output is the same as input Tensor `x`.
keepdim (bool, optional): Whether to reserve the reduced dimension in the
output Tensor. The result Tensor will have one fewer dimension
than the :attr:`x` unless :attr:`keepdim` is true, default
value is False.
name (str, optional): The default value is None. Normally there is no need for
user to set this property. For more information, please refer to :ref:`api_guide_Name`
Returns:
Tensor: Results of summation operation on the specified axis of input Tensor `x`,
Examples:
.. code-block:: python
import paddle
import numpy as np
# x is a Tensor with following elements:
# [[nan, 0.3, 0.5, 0.9]
# [0.1, 0.2, -nan, 0.7]]
# Each example is followed by the corresponding output tensor.
x = np.array([[float('nan'), 0.3, 0.5, 0.9],
[0.1, 0.2, float('-nan'), 0.7]]).astype(np.float32)
x = paddle.to_tensor(x)
out1 = paddle.nansum(x) # [2.7]
out2 = paddle.nansum(x, axis=0) # [0.1, 0.5, 0.5, 1.6]
out3 = paddle.nansum(x, axis=-1) # [1.7, 1.0]
out4 = paddle.nansum(x, axis=1, keepdim=True) # [[1.7], [1.0]]
# y is a Tensor with shape [2, 2, 2] and elements as below:
# [[[1, nan], [3, 4]],
# [[5, 6], [-nan, 8]]]
# Each example is followed by the corresponding output tensor.
y = np.array([[[1, float('nan')], [3, 4]],
[[5, 6], [float('-nan'), 8]]])
y = paddle.to_tensor(y)
out5 = paddle.nansum(y, axis=[1, 2]) # [8, 19]
out6 = paddle.nansum(y, axis=[0, 1]) # [9, 18]
"""
check_variable_and_dtype(
x, 'x', ['float32', 'float64', 'int32', 'int64'], 'nansum')
check_type(axis, 'axis', (int, list, tuple, type(None)), 'nansum')
zero_tensor = paddle.zeros_like(x)
tmp_tensor = paddle.where(isnan(x), zero_tensor, x)
return sum(tmp_tensor, axis, dtype, keepdim, name)
@templatedoc(op_type="sum")
def add_n(inputs, name=None):
"""
This OP is used to sum one or more Tensor of the input.
For example:
.. code-block:: text
Case 1:
Input:
input.shape = [2, 3]
input = [[1, 2, 3],
[4, 5, 6]]
Output:
output.shape = [2, 3]
output = [[1, 2, 3],
[4, 5, 6]]
Case 2:
Input:
First input:
input1.shape = [2, 3]
Input1 = [[1, 2, 3],
[4, 5, 6]]
The second input:
input2.shape = [2, 3]
input2 = [[7, 8, 9],
[10, 11, 12]]
Output:
output.shape = [2, 3]
output = [[8, 10, 12],
[14, 16, 18]]
Args:
inputs (Tensor|list[Tensor]|tuple[Tensor]): A Tensor or a list/tuple of Tensors. The shape and data type of the list/tuple elements should be consistent.
Input can be multi-dimensional Tensor, and data types can be: float32, float64, int32, int64.
name(str, optional): The default value is None. Normally there is no need for
user to set this property. For more information, please refer to :ref:`api_guide_Name`
Returns:
Tensor, the sum of input :math:`inputs` , its shape and data types are consistent with :math:`inputs`.
Examples:
.. code-block:: python
import paddle
input0 = paddle.to_tensor([[1, 2, 3], [4, 5, 6]], dtype='float32')
input1 = paddle.to_tensor([[7, 8, 9], [10, 11, 12]], dtype='float32')
output = paddle.add_n([input0, input1])
# [[8., 10., 12.],
# [14., 16., 18.]]
"""
if paddle.in_dynamic_mode():
if isinstance(inputs, Variable):
inputs = [inputs]
return _C_ops.sum(inputs, 'use_mkldnn', False)
helper = LayerHelper('add_n', **locals())
check_type(inputs, 'inputs', (Variable, tuple, list), 'add_n')
if isinstance(inputs, list) or isinstance(inputs, tuple):
if len(inputs) > 0:
for input in inputs:
check_variable_and_dtype(input, "inputs", \
['float32', 'float64', 'int32', 'int64'], 'add_n')
else:
check_variable_and_dtype(inputs, "inputs", \
['float32', 'float64', 'int32', 'int64'], 'add_n')
out = helper.create_variable_for_type_inference(
dtype=helper.input_dtype('inputs'))
helper.append_op(
type='sum',
inputs={'X': inputs},
outputs={'Out': out},
attrs={'use_mkldnn': False})
return out
def trunc(input, name=None):
'''
This API is used to returns a new tensor with the truncated integer values of input.
Args:
input (Tensor): The input tensor, it's data type should be int32, int64, float32, float64.
name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
Returns:
Tensor: The output Tensor of trunc.
Examples:
.. code-block:: python
import paddle
input = paddle.rand([2,2],'float32')
print(input)
# Tensor(shape=[2, 2], dtype=float32, place=CUDAPlace(0), stop_gradient=True,
# [[0.02331470, 0.42374918],
# [0.79647720, 0.74970269]])
output = paddle.trunc(input)
print(output)
# Tensor(shape=[2, 2], dtype=float32, place=CUDAPlace(0), stop_gradient=True,
# [[0., 0.],
# [0., 0.]]))
'''
if paddle.in_dynamic_mode():
if _in_eager_mode():
return _C_ops.final_state_trunc(input)
return _C_ops.trunc(input)
else:
inputs = {"X": input}
attrs = {}
helper = LayerHelper("trunc", **locals())
check_variable_and_dtype(input, 'X', ['int32', 'int64', 'float32', 'float64'], 'trunc')
out = helper.create_variable_for_type_inference(dtype=input.dtype)
helper.append_op(
type="trunc", inputs=inputs, attrs=attrs, outputs={"Out": out})
return out
def mm(input, mat2, name=None):
"""
Applies matrix multiplication to two tensors.
Currently, the input tensors' rank can be any, but when the rank of any
inputs is bigger than 3, this two inputs' rank should be equal.
Also note that if the raw tensor :math:`x` or :math:`mat2` is rank-1 and
nontransposed, the prepended or appended dimension :math:`1` will be
removed after matrix multiplication.
Args:
input (Tensor): The input tensor which is a Tensor.
mat2 (Tensor): The input tensor which is a Tensor.
name(str, optional): The default value is None. Normally there is no need for
user to set this property. For more information, please refer to :ref:`api_guide_Name`
Returns:
Tensor: The product Tensor.
::
* example 1:
input: [B, ..., M, K], mat2: [B, ..., K, N]
out: [B, ..., M, N]
* example 2:
input: [B, M, K], mat2: [B, K, N]
out: [B, M, N]
* example 3:
input: [B, M, K], mat2: [K, N]
out: [B, M, N]
* example 4:
input: [M, K], mat2: [K, N]
out: [M, N]
* example 5:
input: [B, M, K], mat2: [K]
out: [B, M]
* example 6:
input: [K], mat2: [K]
out: [1]
Examples:
.. code-block:: python
import paddle
input = paddle.arange(1, 7).reshape((3, 2)).astype('float32')
mat2 = paddle.arange(1, 9).reshape((2, 4)).astype('float32')
out = paddle.mm(input, mat2)
print(out)
# [[11., 14., 17., 20.],
# [23., 30., 37., 44.],
# [35., 46., 57., 68.]])
"""
if paddle.in_dynamic_mode():
return _C_ops.matmul_v2(input, mat2)
def __check_input(x, y):
var_names = {'x': x, 'y': y}
for name, val in var_names.items():
check_variable_and_dtype(val, name,
['float16', 'float32', 'float64'], 'mm')
x_shape = list(x.shape)
y_shape = list(y.shape)
if len(x_shape) == 1:
x_shape = [1] + x_shape
if len(y_shape) == 1:
y_shape = y_shape + [1]
# check the inner 2 dimensions
if x_shape[-1] != y_shape[-2]:
if not ((x_shape[-1] == -1) or (y_shape[-2] == -1)):
raise ValueError(
"After performing an optional transpose, Input X's width should be "
"equal to Y's width for multiplication "
"prerequisites. But received X's shape: %s, Y's shape: %s\n"
% (x_shape, y_shape))
if len(y_shape) > 2 and len(x_shape) > 2:
for i, dim_x in enumerate(x_shape[:-2]):
# don't check neg shape
if dim_x < 0 or y_shape[i] < 0:
continue
if dim_x != y_shape[i]:
raise ValueError(
"When the matrix is larger than 2 dimensions, the higher "
"dimensional values of the two matrices need to be equal. "
"But received x_shape[%d] != y_shape[%d]. X's shape: %s, "
"Y's shape: %s.\n" % (i, i, x_shape, y_shape))
__check_input(input, mat2)
helper = LayerHelper('mm', **locals())
out = helper.create_variable_for_type_inference(dtype=input.dtype)
helper.append_op(
type='matmul_v2', inputs={'X': input,
'Y': mat2}, outputs={'Out': out})
return out
def addmm(input, x, y, beta=1.0, alpha=1.0, name=None):
"""
**addmm**
This operator is used to perform matrix multiplication for input $x$ and $y$.
$input$ is added to the final result.
The equation is:
.. math::
Out = alpha * x * y + beta * input
$Input$, $x$ and $y$ can carry the LoD (Level of Details) information, or not. But the output only shares the LoD information with input $input$.
Args:
input (Tensor): The input Tensor to be added to the final result.
x (Tensor): The first input Tensor for matrix multiplication.
y (Tensor): The second input Tensor for matrix multiplication.
beta (float): Coefficient of $input$.
alpha (float): Coefficient of $x*y$.
name (str, optional): Name of the output. Normally there is no need for user to set this property. For more information, please refer to :ref:`api_guide_Name`. Default is None.
Returns:
Tensor: The output Tensor of addmm op.
Examples:
.. code-block:: python
import paddle
x = paddle.ones([2,2])
y = paddle.ones([2,2])
input = paddle.ones([2,2])
out = paddle.addmm( input=input, x=x, y=y, beta=0.5, alpha=5.0 )
print(out)
# [[10.5 10.5]
# [10.5 10.5]]
"""
input_shape = input.shape
x_shape = x.shape
y_shape = y.shape
if not len(input_shape) == len(x_shape) == len(y_shape) == 2:
raise ValueError("The dimention of input, x, y should be 2 but receive input's shape: {}, x's shape: {}, y's shape: {}".format(input_shape, x_shape, y_shape))
if input_shape[0] != x_shape[0]:
if input_shape[0] != 1:
raise ValueError( "When x's dimension[0] is not equal with input's dimension[0], input's dimension[0] must be 1 but got {}".format(input_shape[0]))
if input_shape[1] != y_shape[1] and input_shape[1] != 1:
raise ValueError( "When y's dimension[1] is not equal with input's dimension[1], input's dimension[1] must be 1 but got {}".format(input_shape[1]))
if input_shape[1] != y_shape[1]:
if input_shape[1] != 1:
raise ValueError( "When y's dimension[1] is not equal with input's dimension[1], input's dimension[1] must be 1 but got {}".format(input_shape[1]))
if input_shape[0] != x_shape[0] and input_shape[0] != 1:
raise ValueError( "When x's dimension[0] is not equal with input's dimension[0], input's dimension[0] must be 1 but got {}".format(input_shape[0]))
if x_shape[1] != y_shape[0]:
raise ValueError("The input Variable x's width must be equal with Variable y' height. But received x's shape = {}, y's shape = {}.".format(x_shape, y_shape))
if paddle.in_dynamic_mode():
if _in_eager_mode():
return _C_ops.final_state_addmm( input, x, y, alpha, beta)
out = _C_ops.addmm(input, x, y, "Alpha", alpha, "Beta", beta)
return out
inputs = {'Input': input, "X": x, "Y": y}
attrs = {'Alpha': alpha, 'Beta': beta}
helper = LayerHelper("addmm", **locals())
check_variable_and_dtype(input, 'Input', ['float32', 'float64'], 'addmm')
check_variable_and_dtype(x, 'X', ['float32', 'float64'], 'addmm')
check_variable_and_dtype(y, 'Y', ['float32', 'float64'], 'addmm')
out = helper.create_variable_for_type_inference(dtype=x.dtype)
helper.append_op(
type="addmm", inputs=inputs, attrs=attrs, outputs={"Out": out})
return out
def renorm(x, p, axis, max_norm):
"""
**renorm**
This operator is used to calculate the p-norm along the axis,
suppose the input-shape on axis dimension has the value of T, then
the tensor is split into T parts, the p-norm should be calculated for each
part, if the p-norm for part i is larger than max-norm, then each element
in part i should be re-normalized at the same scale so that part-i' p-norm equals
max-norm exactly, otherwise part-i stays unchanged.
Args:
x (Tensor): The input Tensor
p (float): The power of the norm operation.
axis (int): the dimension to slice the tensor.
max-norm (float): the maximal norm limit.
Returns:
Tensor: the renorm Tensor.
Examples:
.. code-block:: python
import paddle
input = [[[2.0,2,-2],[3,0.3,3]],[[2,-8,2],[3.1,3.7,3]]]
x = paddle.to_tensor(input,dtype='float32')
y = paddle.renorm(x, 1.0, 2, 2.05)
print(y)
# [[[ 0.40594056, 0.29285714, -0.41000000],
# [ 0.60891086, 0.04392857, 0.61500001]],
# [[ 0.40594056, -1.17142856, 0.41000000],
# [ 0.62920785, 0.54178572, 0.61500001]]])
"""
input_shape = x.shape
check_variable_and_dtype(x, 'x', ['float32', 'float64'], 'renorm')
if not axis < len(input_shape):
raise ValueError("the axis:{} should be less then the shape's size {}:{}".format(axis,len(input_shape),input_shape))
if not axis >=0:
if not axis >= -1 * len(input_shape):
raise ValueError("the axis:{} should not be less than -1 * length of input_shape:{}".format(axis,-1 * len(input_shape)))
axis = axis + len(input_shape)
if paddle.in_dynamic_mode():
out = _C_ops.renorm(x, 'p',p, 'axis',axis, 'max_norm', max_norm)
return out
inputs = {'X': x}
attrs = {'p': p, 'axis': axis, 'max_norm':max_norm}
helper = LayerHelper("renorm", **locals())
out = helper.create_variable_for_type_inference(dtype=x.dtype)
helper.append_op(
type="renorm", inputs=inputs, attrs=attrs, outputs={"Out": out})
return out
def inner(x, y, name=None):
"""
Inner product of two input Tensor.
Ordinary inner product for 1-D Tensors, in higher dimensions a sum product over the last axes.
Args:
x (Tensor): An N-D Tensor or a Scalar Tensor. If its not a scalar Tensor, its last dimensions must match y's.
y (Tensor): An N-D Tensor or a Scalar Tensor. If its not a scalar Tensor, its last dimensions must match x's.
name(str, optional): The default value is None. Normally there is no need for
user to set this property. For more information, please refer to :ref:`api_guide_Name`
Returns:
Tensor: The inner-product Tensor, the output shape is x.shape[:-1] + y.shape[:-1].
Examples:
.. code-block:: python
import paddle
x = paddle.arange(1, 7).reshape((2, 3)).astype('float32')
y = paddle.arange(1, 10).reshape((3, 3)).astype('float32')
out = paddle.inner(x, y)
print(out)
# ([[14, 32, 50],
# [32, 77, 122]])
"""
if x.size == 1 or y.size == 1:
return multiply(x, y)
else:
xshape = x.shape
yshape = y.shape
dstshape = list(xshape[:-1])+list(yshape[:-1])
if len(dstshape)==0:
dstshape = [1]
nx = x.reshape((-1, xshape[-1]))
ny = y.reshape((-1, yshape[-1]))
if paddle.in_dynamic_mode():
return _C_ops.matmul_v2(nx, ny.T).reshape(dstshape)
def __check_input(x, y):
var_names = {'x': x, 'y': y}
for name, val in var_names.items():
check_variable_and_dtype(val, name,
['float16', 'float32', 'float64'], 'inner')
x_shape = list(xshape)
y_shape = list(yshape)
# check the inner 2 dimensions
if x_shape[-1] != y_shape[-1]:
if not ((x_shape[-1] == -1) or (y_shape[-1] == -1)):
raise ValueError(
"After performing an optional transpose, Input X's last dim should be "
"equal to Y's last dim for multiplication "
"prerequisites. But received X's shape: %s, Y's shape: %s\n"
% (x_shape, y_shape))
__check_input(nx, ny)
helper = LayerHelper('inner', **locals())
out = helper.create_variable_for_type_inference(dtype=nx.dtype)
helper.append_op(
type='matmul_v2', inputs={'X': nx,
'Y': ny.T}, outputs={'Out': out})
return out.reshape(dstshape)
def outer(x, y, name=None):
"""
Outer product of two Tensors.
Input is flattened if not already 1-dimensional.
Args:
x (Tensor): An N-D Tensor or a Scalar Tensor.
y (Tensor): An N-D Tensor or a Scalar Tensor.
name(str, optional): The default value is None. Normally there is no need for
user to set this property. For more information, please refer to :ref:`api_guide_Name`
Returns:
Tensor: The outer-product Tensor.
Examples:
.. code-block:: python
import paddle
x = paddle.arange(1, 4).astype('float32')
y = paddle.arange(1, 6).astype('float32')
out = paddle.outer(x, y)
print(out)
# ([[1, 2, 3, 4, 5],
# [2, 4, 6, 8, 10],
# [3, 6, 9, 12, 15]])
"""
nx = x.reshape((-1, 1))
ny = y.reshape((1, -1))
if paddle.in_dynamic_mode():
return _C_ops.matmul_v2(nx, ny)
def __check_input(x, y):
var_names = {'x': x, 'y': y}
for name, val in var_names.items():
check_variable_and_dtype(val, name,
['float16', 'float32', 'float64'], 'inner')
__check_input(nx, ny)
helper = LayerHelper('outer', **locals())
out = helper.create_variable_for_type_inference(dtype=nx.dtype)
helper.append_op(
type='matmul_v2', inputs={'X': nx,
'Y': ny}, outputs={'Out': out})
return out
def logsumexp(x, axis=None, keepdim=False, name=None):
r"""
This OP calculates the log of the sum of exponentials of ``x`` along ``axis`` .
.. math::
logsumexp(x) = \\log\\sum exp(x)
Args:
x (Tensor): The input Tensor with data type float32 or float64, which
have no more than 4 dimensions.
axis (int|list|tuple, optional): The axis along which to perform
logsumexp calculations. ``axis`` should be int, list(int) or
tuple(int). If ``axis`` is a list/tuple of dimension(s), logsumexp
is calculated along all element(s) of ``axis`` . ``axis`` or
element(s) of ``axis`` should be in range [-D, D), where D is the
dimensions of ``x`` . If ``axis`` or element(s) of ``axis`` is
less than 0, it works the same way as :math:`axis + D` . If
``axis`` is None, logsumexp is calculated along all elements of
``x``. Default is None.
keepdim (bool, optional): Whether to reserve the reduced dimension(s)
in the output Tensor. If ``keep_dim`` is True, the dimensions of
the output Tensor is the same as ``x`` except in the reduced
dimensions(it is of size 1 in this case). Otherwise, the shape of
the output Tensor is squeezed in ``axis`` . Default is False.
name (str, optional): Name for the operation (optional, default is None).
For more information, please refer to :ref:`api_guide_Name`.
Returns:
Tensor, results of logsumexp along ``axis`` of ``x``, with the same data
type as ``x``.
Examples:
.. code-block:: python
import paddle
x = paddle.to_tensor([[-1.5, 0., 2.], [3., 1.2, -2.4]])
out1 = paddle.logsumexp(x) # [3.4691226]
out2 = paddle.logsumexp(x, 1) # [2.15317821, 3.15684602]
"""
if isinstance(axis, int):
axis = [axis]
reduce_all = True if axis is None \
or len(axis)==0 \
or len(axis) == len(x.shape) else False
if axis is None or len(axis) == 0:
axis = [0]
if paddle.in_dynamic_mode():
return _C_ops.logsumexp(x, 'axis', axis, 'keepdim', keepdim, 'reduce_all', reduce_all)
check_variable_and_dtype(x, 'x',
['float32', 'float64'],
'logsumexp')
helper = LayerHelper('logsumexp', **locals())
attrs = {'axis': axis, 'keepdim': keepdim, 'reduce_all':reduce_all}
out = helper.create_variable_for_type_inference(x.dtype)
helper.append_op(
type='logsumexp', inputs={'X': x}, outputs={'Out': out}, attrs=attrs)
return out
def inverse(x, name=None):
"""
Takes the inverse of the square matrix. A square matrix is a matrix with
the same number of rows and columns. The input can be a square matrix
(2-D Tensor) or batches of square matrices.
Args:
x (Tensor): The input tensor. The last two
dimensions should be equal. When the number of dimensions is
greater than 2, it is treated as batches of square matrix. The data
type can be float32 and float64.
name (str, optional): The default value is None. Normally there is no need for
user to set this property. For more information,
please refer to :ref:`api_guide_Name`
Returns:
Tensor: A Tensor holds the inverse of x. The shape and data type
is the same as x.
Examples:
.. code-block:: python
import paddle
mat = paddle.to_tensor([[2, 0], [0, 2]], dtype='float32')
inv = paddle.inverse(mat)
print(inv) # [[0.5, 0], [0, 0.5]]
"""
if paddle.in_dynamic_mode():
return _C_ops.inverse(x)
def _check_input(x):
check_variable_and_dtype(x, 'x',
['float32', 'float64'], 'inverse')
if len(x.shape) < 2:
raise ValueError(
"The input of inverse is expected to be a Tensor whose number "
"of dimensions is no less than 2. But reviced: %d, "
"x's shape: %s." % (len(x.shape), x.shape))
_check_input(x)
helper = LayerHelper('inverse', **locals())
out = helper.create_variable_for_type_inference(dtype=x.dtype)
helper.append_op(
type='inverse', inputs={'Input': [x] }, outputs={'Output': [out]})
return out
def _get_reduce_all_value(axis):
"""
Internal function for max, min, amax and amin.
It computes the attribute reduce_all value based on axis.
"""
if axis is not None and not isinstance(axis, list):
if isinstance(axis, tuple):
axis = list(axis)
elif isinstance(axis, int):
axis= [axis]
else:
raise TypeError(
"The type of axis must be int, list or tuple, but received {}".format(type(axis)))
reduce_all = True if axis == None or axis == [] else False
axis = axis if axis != None and axis != [] else [0]
return reduce_all, axis
def max(x, axis=None, keepdim=False, name=None):
"""
Computes the maximum of tensor elements over the given axis.
Note:
The difference between max and amax is: If there are multiple maximum elements,
amax evenly distributes gradient between these equal values,
while max propagates gradient to all of them.
Args:
x(Tensor): A tensor, the data type is float32, float64, int32, int64.
axis(int|list|tuple, optional): The axis along which the maximum is computed.
If :attr:`None`, compute the maximum over all elements of
`x` and return a Tensor with a single element,
otherwise must be in the range :math:`[-x.ndim(x), x.ndim(x))`.
If :math:`axis[i] < 0`, the axis to reduce is :math:`x.ndim + axis[i]`.
keepdim(bool, optional): Whether to reserve the reduced dimension in the
output Tensor. The result tensor will have one fewer dimension
than the `x` unless :attr:`keepdim` is true, default
value is False.
name(str, optional): The default value is None. Normally there is no need for
user to set this property. For more information, please refer to :ref:`api_guide_Name`
Returns:
Tensor, results of maximum on the specified axis of input tensor,
it's data type is the same as `x`.
Examples:
.. code-block:: python
import paddle
# data_x is a Tensor with shape [2, 4]
# the axis is a int element
x = paddle.to_tensor([[0.2, 0.3, 0.5, 0.9],
[0.1, 0.2, 0.6, 0.7]],
dtype='float64', stop_gradient=False)
result1 = paddle.max(x)
result1.backward()
print(result1, x.grad)
#[0.9], [[0., 0., 0., 1.], [0., 0., 0., 0.]]
x.clear_grad()
result2 = paddle.max(x, axis=0)
result2.backward()
print(result2, x.grad)
#[0.2, 0.3, 0.6, 0.9], [[1., 1., 0., 1.], [0., 0., 1., 0.]]
x.clear_grad()
result3 = paddle.max(x, axis=-1)
result3.backward()
print(result3, x.grad)
#[0.9, 0.7], [[0., 0., 0., 1.], [0., 0., 0., 1.]]
x.clear_grad()
result4 = paddle.max(x, axis=1, keepdim=True)
result4.backward()
print(result4, x.grad)
#[[0.9], [0.7]], [[0., 0., 0., 1.], [0., 0., 0., 1.]]
# data_y is a Tensor with shape [2, 2, 2]
# the axis is list
y = paddle.to_tensor([[[1.0, 2.0], [3.0, 4.0]],
[[5.0, 6.0], [7.0, 8.0]]],
dtype='float64', stop_gradient=False)
result5 = paddle.max(y, axis=[1, 2])
result5.backward()
print(result5, y.grad)
#[4., 8.], [[[0., 0.], [0., 1.]], [[0., 0.], [0., 1.]]]
y.clear_grad()
result6 = paddle.max(y, axis=[0, 1])
result6.backward()
print(result6, y.grad)
#[7., 8.], [[[0., 0.], [0., 0.]], [[0., 0.], [1., 1.]]]
"""
reduce_all, axis = _get_reduce_all_value(axis)
if paddle.in_dynamic_mode():
return _C_ops.reduce_max(x, 'dim', axis, 'keep_dim', keepdim,
'reduce_all', reduce_all)
helper = LayerHelper('max', **locals())
check_variable_and_dtype(
x, 'x', ['float32', 'float64', 'int32', 'int64'], 'max')
out = helper.create_variable_for_type_inference(
dtype=x.dtype)
helper.append_op(
type='reduce_max',
inputs={'X': x},
outputs={'Out': out},
attrs={
'dim': axis,
'keep_dim': keepdim,
'reduce_all': reduce_all
})
return out
def min(x, axis=None, keepdim=False, name=None):
"""
Computes the minimum of tensor elements over the given axis
Note:
The difference between min and amin is: If there are multiple minimum elements,
amin evenly distributes gradient between these equal values,
while min propagates gradient to all of them.
Args:
x(Tensor): A tensor, the data type is float32, float64, int32, int64.
axis(int|list|tuple, optional): The axis along which the minimum is computed.
If :attr:`None`, compute the minimum over all elements of
`x` and return a Tensor with a single element,
otherwise must be in the range :math:`[-x.ndim, x.ndim)`.
If :math:`axis[i] < 0`, the axis to reduce is :math:`x.ndim + axis[i]`.
keepdim(bool, optional): Whether to reserve the reduced dimension in the
output Tensor. The result tensor will have one fewer dimension
than the `x` unless :attr:`keepdim` is true, default
value is False.
name(str, optional): The default value is None. Normally there is no need for
user to set this property. For more information, please refer to :ref:`api_guide_Name`
Returns:
Tensor, results of minimum on the specified axis of input tensor,
it's data type is the same as input's Tensor.
Examples:
.. code-block:: python
import paddle
# data_x is a Tensor with shape [2, 4]
# the axis is a int element
x = paddle.to_tensor([[0.2, 0.3, 0.5, 0.9],
[0.1, 0.2, 0.6, 0.7]],
dtype='float64', stop_gradient=False)
result1 = paddle.min(x)
result1.backward()
print(result1, x.grad)
#[0.1], [[0., 0., 0., 0.], [1., 0., 0., 0.]]
x.clear_grad()
result2 = paddle.min(x, axis=0)
result2.backward()
print(result2, x.grad)
#[0.1, 0.2, 0.5, 0.7], [[0., 0., 1., 0.], [1., 1., 0., 1.]]
x.clear_grad()
result3 = paddle.min(x, axis=-1)
result3.backward()
print(result3, x.grad)
#[0.2, 0.1], [[1., 0., 0., 0.], [1., 0., 0., 0.]]
x.clear_grad()
result4 = paddle.min(x, axis=1, keepdim=True)
result4.backward()
print(result4, x.grad)
#[[0.2], [0.1]], [[1., 0., 0., 0.], [1., 0., 0., 0.]]
# data_y is a Tensor with shape [2, 2, 2]
# the axis is list
y = paddle.to_tensor([[[1.0, 2.0], [3.0, 4.0]],
[[5.0, 6.0], [7.0, 8.0]]],
dtype='float64', stop_gradient=False)
result5 = paddle.min(y, axis=[1, 2])
result5.backward()
print(result5, y.grad)
#[1., 5.], [[[1., 0.], [0., 0.]], [[1., 0.], [0., 0.]]]
y.clear_grad()
result6 = paddle.min(y, axis=[0, 1])
result6.backward()
print(result6, y.grad)
#[1., 2.], [[[1., 1.], [0., 0.]], [[0., 0.], [0., 0.]]]
"""
reduce_all, axis = _get_reduce_all_value(axis)
if paddle.in_dynamic_mode():
return _C_ops.reduce_min(x, 'dim', axis, 'keep_dim', keepdim,
'reduce_all', reduce_all)
helper = LayerHelper('min', **locals())
check_variable_and_dtype(
x, 'x', ['float32', 'float64', 'int32', 'int64'], 'min')
out = helper.create_variable_for_type_inference(
dtype=x.dtype)
helper.append_op(
type='reduce_min',
inputs={'X': x},
outputs={'Out': out},
attrs={
'dim': axis,
'keep_dim': keepdim,
'reduce_all': reduce_all
})
return out
def amax(x, axis=None, keepdim=False, name=None):
"""
Computes the maximum of tensor elements over the given axis.
Note:
The difference between max and amax is: If there are multiple maximum elements,
amax evenly distributes gradient between these equal values,
while max propagates gradient to all of them.
Args:
x(Tensor): A tensor, the data type is float32, float64, int32, int64,
the dimension is no more than 4.
axis(int|list|tuple, optional): The axis along which the maximum is computed.
If :attr:`None`, compute the maximum over all elements of
`x` and return a Tensor with a single element,
otherwise must be in the range :math:`[-x.ndim(x), x.ndim(x))`.
If :math:`axis[i] < 0`, the axis to reduce is :math:`x.ndim + axis[i]`.
keepdim(bool, optional): Whether to reserve the reduced dimension in the
output Tensor. The result tensor will have one fewer dimension
than the `x` unless :attr:`keepdim` is true, default
value is False.
name(str, optional): The default value is None. Normally there is no need for
user to set this property. For more information, please refer to :ref:`api_guide_Name`
Returns:
Tensor, results of maximum on the specified axis of input tensor,
it's data type is the same as `x`.
Examples:
.. code-block:: python
import paddle
# data_x is a Tensor with shape [2, 4] with multiple maximum elements
# the axis is a int element
x = paddle.to_tensor([[0.1, 0.9, 0.9, 0.9],
[0.9, 0.9, 0.6, 0.7]],
dtype='float64', stop_gradient=False)
# There are 5 maximum elements:
# 1) amax evenly distributes gradient between these equal values,
# thus the corresponding gradients are 1/5=0.2;
# 2) while max propagates gradient to all of them,
# thus the corresponding gradient are 1.
result1 = paddle.amax(x)
result1.backward()
print(result1, x.grad)
#[0.9], [[0., 0.2, 0.2, 0.2], [0.2, 0.2, 0., 0.]]
x.clear_grad()
result1_max = paddle.max(x)
result1_max.backward()
print(result1_max, x.grad)
#[0.9], [[0., 1.0, 1.0, 1.0], [1.0, 1.0, 0., 0.]]
###############################
x.clear_grad()
result2 = paddle.amax(x, axis=0)
result2.backward()
print(result2, x.grad)
#[0.9, 0.9, 0.9, 0.9], [[0., 0.5, 1., 1.], [1., 0.5, 0., 0.]]
x.clear_grad()
result3 = paddle.amax(x, axis=-1)
result3.backward()
print(result3, x.grad)
#[0.9, 0.9], [[0., 0.3333, 0.3333, 0.3333], [0.5, 0.5, 0., 0.]]
x.clear_grad()
result4 = paddle.amax(x, axis=1, keepdim=True)
result4.backward()
print(result4, x.grad)
#[[0.9], [0.9]], [[0., 0.3333, 0.3333, 0.3333.], [0.5, 0.5, 0., 0.]]
# data_y is a Tensor with shape [2, 2, 2]
# the axis is list
y = paddle.to_tensor([[[0.1, 0.9], [0.9, 0.9]],
[[0.9, 0.9], [0.6, 0.7]]],
dtype='float64', stop_gradient=False)
result5 = paddle.amax(y, axis=[1, 2])
result5.backward()
print(result5, y.grad)
#[0.9., 0.9], [[[0., 0.3333], [0.3333, 0.3333]], [[0.5, 0.5], [0., 1.]]]
y.clear_grad()
result6 = paddle.amax(y, axis=[0, 1])
result6.backward()
print(result6, y.grad)
#[0.9., 0.9], [[[0., 0.3333], [0.5, 0.3333]], [[0.5, 0.3333], [1., 1.]]]
"""
reduce_all, axis = _get_reduce_all_value(axis)
if paddle.in_dynamic_mode():
return _C_ops.reduce_amax(x, 'dim', axis, 'keep_dim', keepdim, 'reduce_all', reduce_all)
helper = LayerHelper('amax', **locals())
check_variable_and_dtype(
x, 'x', ['float32', 'float64', 'int32', 'int64'], 'amax')
out = helper.create_variable_for_type_inference(
dtype=x.dtype)
helper.append_op(
type='reduce_amax',
inputs={'X': x},
outputs={'Out': out},
attrs={
'dim': axis,
'keep_dim': keepdim,
'reduce_all': reduce_all
})
return out
def amin(x, axis=None, keepdim=False, name=None):
"""
Computes the minimum of tensor elements over the given axis
Note:
The difference between min and amin is: If there are multiple minimum elements,
amin evenly distributes gradient between these equal values,
while min propagates gradient to all of them.
Args:
x(Tensor): A tensor, the data type is float32, float64, int32, int64,
the dimension is no more than 4.
axis(int|list|tuple, optional): The axis along which the minimum is computed.
If :attr:`None`, compute the minimum over all elements of
`x` and return a Tensor with a single element,
otherwise must be in the range :math:`[-x.ndim, x.ndim)`.
If :math:`axis[i] < 0`, the axis to reduce is :math:`x.ndim + axis[i]`.
keepdim(bool, optional): Whether to reserve the reduced dimension in the
output Tensor. The result tensor will have one fewer dimension
than the `x` unless :attr:`keepdim` is true, default
value is False.
name(str, optional): The default value is None. Normally there is no need for
user to set this property. For more information, please refer to :ref:`api_guide_Name`
Returns:
Tensor, results of minimum on the specified axis of input tensor,
it's data type is the same as input's Tensor.
Examples:
.. code-block:: python
import paddle
# data_x is a Tensor with shape [2, 4] with multiple minimum elements
# the axis is a int element
x = paddle.to_tensor([[0.2, 0.1, 0.1, 0.1],
[0.1, 0.1, 0.6, 0.7]],
dtype='float64', stop_gradient=False)
# There are 5 minimum elements:
# 1) amin evenly distributes gradient between these equal values,
# thus the corresponding gradients are 1/5=0.2;
# 2) while min propagates gradient to all of them,
# thus the corresponding gradient are 1.
result1 = paddle.amin(x)
result1.backward()
print(result1, x.grad)
#[0.1], [[0., 0.2, 0.2, 0.2], [0.2, 0.2, 0., 0.]]
x.clear_grad()
result1_min = paddle.min(x)
result1_min.backward()
print(result1_min, x.grad)
#[0.1], [[0., 1.0, 1.0, 1.0], [1.0, 1.0, 0., 0.]]
###############################
x.clear_grad()
result2 = paddle.amin(x, axis=0)
result2.backward()
print(result2, x.grad)
#[0.1, 0.1, 0.1, 0.1], [[0., 0.5, 1., 1.], [1., 0.5, 0., 0.]]
x.clear_grad()
result3 = paddle.amin(x, axis=-1)
result3.backward()
print(result3, x.grad)
#[0.1, 0.1], [[0., 0.3333, 0.3333, 0.3333], [0.5, 0.5, 0., 0.]]
x.clear_grad()
result4 = paddle.amin(x, axis=1, keepdim=True)
result4.backward()
print(result4, x.grad)
#[[0.1], [0.1]], [[0., 0.3333, 0.3333, 0.3333.], [0.5, 0.5, 0., 0.]]
# data_y is a Tensor with shape [2, 2, 2]
# the axis is list
y = paddle.to_tensor([[[0.2, 0.1], [0.1, 0.1]],
[[0.1, 0.1], [0.6, 0.7]]],
dtype='float64', stop_gradient=False)
result5 = paddle.amin(y, axis=[1, 2])
result5.backward()
print(result5, y.grad)
#[0.1., 0.1], [[[0., 0.3333], [0.3333, 0.3333]], [[0.5, 0.5], [0., 1.]]]
y.clear_grad()
result6 = paddle.amin(y, axis=[0, 1])
result6.backward()
print(result6, y.grad)
#[0.1., 0.1], [[[0., 0.3333], [0.5, 0.3333]], [[0.5, 0.3333], [1., 1.]]]
"""
reduce_all, axis = _get_reduce_all_value(axis)
if paddle.in_dynamic_mode():
return _C_ops.reduce_amin(x, 'dim', axis, 'keep_dim', keepdim, 'reduce_all', reduce_all)
helper = LayerHelper('amin', **locals())
check_variable_and_dtype(
x, 'x', ['float32', 'float64', 'int32', 'int64'], 'amin')
out = helper.create_variable_for_type_inference(
dtype=x.dtype)
helper.append_op(
type='reduce_amin',
inputs={'X': x},
outputs={'Out': out},
attrs={
'dim': axis,
'keep_dim': keepdim,
'reduce_all': reduce_all
})
return out
def log1p(x, name=None):
r"""
Calculates the natural log of the given input tensor, element-wise.
.. math::
Out = \\ln(x+1)
Args:
x (Tensor): Input Tensor. Must be one of the following types: float32, float64.
name(str, optional): The default value is None. Normally there is no need for
user to set this property. For more information, please refer to :ref:`api_guide_Name`
Returns:
Tensor, the natural log of the input Tensor computed element-wise.
Examples:
.. code-block:: python
import paddle
data = paddle.to_tensor([[0], [1]], dtype='float32')
res = paddle.log1p(data)
# [[0.], [0.6931472]]
"""
if paddle.in_dynamic_mode():
return _C_ops.log1p(x)
check_variable_and_dtype(x, 'x', ['float32', 'float64'], "log1p")
inputs = {'X': [x]}
helper = LayerHelper('log1p', **locals())
dtype = helper.input_dtype(input_param_name='x')
out = helper.create_variable_for_type_inference(dtype)
helper.append_op(type="log1p", inputs={"X": x}, outputs={"Out": out})
return out
def log2(x, name=None):
r"""
Calculates the log to the base 2 of the given input tensor, element-wise.
.. math::
Out = \\log_2x
Args:
x (Tensor): Input tensor must be one of the following types: float32, float64.
name (str|None): The default value is None. Normally there is no need for user to set this property. For more information, please refer to :ref:`api_guide_Name`
Returns:
Tensor: The log to the base 2 of the input Tensor computed element-wise.
Examples:
.. code-block:: python
import paddle
# example 1: x is a float
x_i = paddle.to_tensor([[1.0], [2.0]])
res = paddle.log2(x_i) # [[0.], [1.0]]
# example 2: x is float32
x_i = paddle.full(shape=[1], fill_value=2, dtype='float32')
paddle.to_tensor(x_i)
res = paddle.log2(x_i)
print(res) # [1.0]
# example 3: x is float64
x_i = paddle.full(shape=[1], fill_value=2, dtype='float64')
paddle.to_tensor(x_i)
res = paddle.log2(x_i)
print(res) # [1.0]
"""
if paddle.in_dynamic_mode():
return _C_ops.log2(x)
check_variable_and_dtype(x, 'x', ['float16', 'float32', 'float64'], "log2")
inputs = {'X': [x]}
helper = LayerHelper('log2', **locals())
dtype = helper.input_dtype(input_param_name='x')
out = helper.create_variable_for_type_inference(dtype)
helper.append_op(type="log2", inputs={"X": x}, outputs={"Out": out})
return out
def log10(x, name=None):
r"""
Calculates the log to the base 10 of the given input tensor, element-wise.
.. math::
Out = \\log_10_x
Args:
x (Tensor): Input tensor must be one of the following types: float32, float64.
name (str|None): The default value is None. Normally there is no need for user to set this property. For more information, please refer to :ref:`api_guide_Name`
Returns:
Tensor: The log to the base 10 of the input Tensor computed element-wise.
Examples:
.. code-block:: python
import paddle
# example 1: x is a float
x_i = paddle.to_tensor([[1.0], [10.0]])
res = paddle.log10(x_i) # [[0.], [1.0]]
# example 2: x is float32
x_i = paddle.full(shape=[1], fill_value=10, dtype='float32')
paddle.to_tensor(x_i)
res = paddle.log10(x_i)
print(res) # [1.0]
# example 3: x is float64
x_i = paddle.full(shape=[1], fill_value=10, dtype='float64')
paddle.to_tensor(x_i)
res = paddle.log10(x_i)
print(res) # [1.0]
"""
if paddle.in_dynamic_mode():
return _C_ops.log10(x)
check_variable_and_dtype(x, 'x', ['float16', 'float32', 'float64'], "log10")
inputs = {'X': [x]}
helper = LayerHelper('log10', **locals())
dtype = helper.input_dtype(input_param_name='x')
out = helper.create_variable_for_type_inference(dtype)
helper.append_op(type="log10", inputs={"X": x}, outputs={"Out": out})
return out
def clip(x, min=None, max=None, name=None):
"""
This operator clip all elements in input into the range [ min, max ] and return
a resulting tensor as the following equation:
.. math::
Out = MIN(MAX(x, min), max)
Args:
x (Tensor): An N-D Tensor with data type float32, float64, int32 or int64.
min (float|int|Tensor): The lower bound with type ``float`` , ``int`` or a ``Tensor``
with shape [1] and type ``int32``, ``float32``, ``float64``.
max (float|int|Tensor): The upper bound with type ``float``, ``int`` or a ``Tensor``
with shape [1] and type ``int32``, ``float32``, ``float64``.
name (str, optional): The default value is None. Normally there is no
need for user to set this property. For more information, please
refer to :ref:`api_guide_Name`.
Returns:
Tensor: A Tensor with the same data type and data shape as input.
Examples:
.. code-block:: python
import paddle
x1 = paddle.to_tensor([[1.2, 3.5], [4.5, 6.4]], 'float32')
out1 = paddle.clip(x1, min=3.5, max=5.0)
out2 = paddle.clip(x1, min=2.5)
print(out1)
# [[3.5, 3.5]
# [4.5, 5.0]]
print(out2)
# [[2.5, 3.5]
# [[4.5, 6.4]
"""
x_dtype = str(x.dtype)
if x_dtype == 'paddle.int32':
min_ = np.iinfo(np.int32).min
max_ = np.iinfo(np.int32).max - 2**7
elif x_dtype == 'paddle.int64':
min_ = np.iinfo(np.int64).min
max_ = np.iinfo(np.int64).max - 2**39
else:
min_ = float(np.finfo(np.float32).min)
max_ = float(np.finfo(np.float32).max)
if paddle.in_dynamic_mode():
if isinstance(min, Variable):
min = min.numpy().item(0)
if isinstance(max, Variable):
max = max.numpy().item(0)
min = min_ if min is None else min
max = max_ if max is None else max
return _C_ops.clip(x, "min", min, "max", max)
if min is not None:
check_type(min, 'min', (float, int, Variable), 'clip')
if isinstance(min, Variable):
check_dtype(min.dtype, 'min', ['float32', 'float64', 'int32'],
'clip', '(When the type of min in clip is Variable.)')
if max is not None:
check_type(max, 'max', (float, int, Variable), 'clip')
if isinstance(max, Variable):
check_dtype(max.dtype, 'max', ['float32', 'float64', 'int32'],
'clip', '(When the type of max in clip is Variable.)')
check_variable_and_dtype(x, 'x', ['float32', 'float64', 'int32', 'int64'], 'clip')
inputs = {'X': x}
attrs = {'min': min_, 'max': max_}
if isinstance(min, Variable):
min.stop_gradient = True
inputs['Min'] = min
elif min is not None:
attrs['min'] = min
if isinstance(max, Variable):
max.stop_gradient = True
inputs['Max'] = max
elif max is not None:
attrs['max'] = max
helper = LayerHelper('clip', **locals())
output = helper.create_variable_for_type_inference(
dtype=helper.input_dtype('x'))
helper.append_op(
type='clip', inputs=inputs, outputs={'Out': [output]}, attrs=attrs)
return output
@inplace_apis_in_dygraph_only
def clip_(x, min=None, max=None, name=None):
"""
Inplace version of ``clip`` API, the output Tensor will be inplaced with input ``x``.
Please refer to :ref:`api_tensor_clip`.
"""
fmin = float(np.finfo(np.float32).min)
fmax = float(np.finfo(np.float32).max)
if isinstance(min, Variable):
min = min.numpy().item(0)
if isinstance(max, Variable):
max = max.numpy().item(0)
min = fmin if min is None else min
max = fmax if max is None else max
return _C_ops.clip_(x, "min", min, "max", max)
def trace(x, offset=0, axis1=0, axis2=1, name=None):
"""
**trace**
This OP computes the sum along diagonals of the input tensor x.
If ``x`` is 2D, returns the sum of diagonal.
If ``x`` has larger dimensions, then returns an tensor of diagonals sum, diagonals be taken from
the 2D planes specified by axis1 and axis2. By default, the 2D planes formed by the first and second axes
of the input tensor x.
The argument ``offset`` determines where diagonals are taken from input tensor x:
- If offset = 0, it is the main diagonal.
- If offset > 0, it is above the main diagonal.
- If offset < 0, it is below the main diagonal.
- Note that if offset is out of input's shape indicated by axis1 and axis2, 0 will be returned.
Args:
x(Tensor): The input tensor x. Must be at least 2-dimensional. The input data type should be float32, float64, int32, int64.
offset(int, optional): Which diagonals in input tensor x will be taken. Default: 0 (main diagonals).
axis1(int, optional): The first axis with respect to take diagonal. Default: 0.
axis2(int, optional): The second axis with respect to take diagonal. Default: 1.
name (str, optional): Normally there is no need for user to set this property. For more information, please refer to :ref:`api_guide_Name`. Default: None.
Returns:
Tensor: the output data type is the same as input data type.
Examples:
.. code-block:: python
import paddle
case1 = paddle.randn([2, 3])
case2 = paddle.randn([3, 10, 10])
case3 = paddle.randn([3, 10, 5, 10])
data1 = paddle.trace(case1) # data1.shape = [1]
data2 = paddle.trace(case2, offset=1, axis1=1, axis2=2) # data2.shape = [3]
data3 = paddle.trace(case3, offset=-3, axis1=1, axis2=-1) # data2.shape = [3, 5]
"""
def __check_input(input, offset, dim1, dim2):
check_dtype(x.dtype, 'Input',
['int32', 'int64', 'float16', 'float32', 'float64'],
'trace')
input_shape = list(x.shape)
assert len(input_shape) >= 2, \
"The x must be at least 2-dimensional, " \
"But received Input x's dimensional: %s.\n" % \
len(input_shape)
axis1_ = axis1 if axis1 >= 0 else len(input_shape) + axis1
axis2_ = axis2 if axis2 >= 0 else len(input_shape) + axis2
assert ((0 <= axis1_) and (axis1_ < len(input_shape))), \
"The argument axis1 is out of range (expected to be in range of [%d, %d], but got %d).\n" \
% (-(len(input_shape)), len(input_shape) - 1, axis1)
assert ((0 <= axis2_) and (axis2_ < len(input_shape))), \
"The argument axis2 is out of range (expected to be in range of [%d, %d], but got %d).\n" \
% (-(len(input_shape)), len(input_shape) - 1, axis2)
assert axis1_ != axis2_, \
"axis1 and axis2 cannot be the same axis." \
"But received axis1 = %d, axis2 = %d\n"%(axis1, axis2)
__check_input(input, offset, axis1, axis2)
if paddle.in_dynamic_mode():
return _C_ops.trace(x, 'offset', offset, 'axis1', axis1, 'axis2', axis2)
inputs = {'Input': [x]}
attrs = {'offset': offset, 'axis1': axis1, 'axis2': axis2}
helper = LayerHelper('trace', **locals())
out = helper.create_variable_for_type_inference(dtype=x.dtype)
helper.append_op(
type='trace',
inputs={'Input': [x]},
attrs={'offset': offset,
'axis1': axis1,
'axis2': axis2},
outputs={'Out': [out]})
return out
def diagonal(x, offset=0, axis1=0, axis2=1, name=None):
"""
This OP computes the diagonals of the input tensor x.
If ``x`` is 2D, returns the diagonal.
If ``x`` has larger dimensions, diagonals be taken from the 2D planes specified by axis1 and axis2.
By default, the 2D planes formed by the first and second axis of the input tensor x.
The argument ``offset`` determines where diagonals are taken from input tensor x:
- If offset = 0, it is the main diagonal.
- If offset > 0, it is above the main diagonal.
- If offset < 0, it is below the main diagonal.
Args:
x(Tensor): The input tensor x. Must be at least 2-dimensional. The input data type should be bool, int32, int64, float16, float32, float64.
offset(int, optional): Which diagonals in input tensor x will be taken. Default: 0 (main diagonals).
axis1(int, optional): The first axis with respect to take diagonal. Default: 0.
axis2(int, optional): The second axis with respect to take diagonal. Default: 1.
name (str, optional): Normally there is no need for user to set this property. For more information, please refer to :ref:`api_guide_Name`. Default: None.
Returns:
Tensor: a partial view of input tensor in specify two dimensions, the output data type is the same as input data type.
Examples:
.. code-block:: python
import paddle
x = paddle.rand([2,2,3],'float32')
print(x)
# Tensor(shape=[2, 2, 3], dtype=float32, place=CUDAPlace(0), stop_gradient=True,
# [[[0.45661032, 0.03751532, 0.90191704],
# [0.43760979, 0.86177313, 0.65221709]],
# [[0.17020577, 0.00259554, 0.28954273],
# [0.51795638, 0.27325270, 0.18117726]]])
out1 = paddle.diagonal(x)
print(out1)
#Tensor(shape=[3, 2], dtype=float32, place=CUDAPlace(0), stop_gradient=True,
# [[0.45661032, 0.51795638],
# [0.03751532, 0.27325270],
# [0.90191704, 0.18117726]])
out2 = paddle.diagonal(x, offset=0, axis1=2, axis2=1)
print(out2)
#Tensor(shape=[2, 2], dtype=float32, place=CUDAPlace(0), stop_gradient=True,
# [[0.45661032, 0.86177313],
# [0.17020577, 0.27325270]])
out3 = paddle.diagonal(x, offset=1, axis1=0, axis2=1)
print(out3)
#Tensor(shape=[3, 1], dtype=float32, place=CUDAPlace(0), stop_gradient=True,
# [[0.43760979],
# [0.86177313],
# [0.65221709]])
out4 = paddle.diagonal(x, offset=0, axis1=1, axis2=2)
print(out4)
#Tensor(shape=[2, 2], dtype=float32, place=CUDAPlace(0), stop_gradient=True,
# [[0.45661032, 0.86177313],
# [0.17020577, 0.27325270]])
"""
if paddle.in_dynamic_mode():
if _in_eager_mode():
return _C_ops.final_state_diagonal(x, offset, axis1, axis2)
return _C_ops.diagonal(x, 'offset', offset, 'axis1', axis1, 'axis2', axis2)
def __check_input(input, offset, dim1, dim2):
check_dtype(x.dtype, 'Input',
['bool', 'int32', 'int64', 'float16', 'float32', 'float64'],
'diagonal')
input_shape = list(x.shape)
assert len(input_shape) >= 2, \
"The x must be at least 2-dimensional, " \
"But received Input x's dimensional: %s.\n" % \
len(input_shape)
axis1_ = axis1 if axis1 >= 0 else len(input_shape) + axis1
axis2_ = axis2 if axis2 >= 0 else len(input_shape) + axis2
assert axis1_ < len(input_shape), \
"The argument axis1 is out of range (expected to be in range of [%d, %d], but got %d).\n" \
% (-(len(input_shape)), len(input_shape) - 1, axis1)
assert axis2_ < len(input_shape), \
"The argument axis2 is out of range (expected to be in range of [%d, %d], but got %d).\n" \
% (-(len(input_shape)), len(input_shape) - 1, axis2)
assert axis1_ != axis2_, \
"axis1 and axis2 cannot be the same axis." \
"But received axis1 = %d, axis2 = %d\n"%(axis1, axis2)
__check_input(input, offset, axis1, axis2)
helper = LayerHelper('diagonal', **locals())
out = helper.create_variable_for_type_inference(dtype=x.dtype)
helper.append_op(
type='diagonal',
inputs={'Input': [x]},
attrs={'offset': offset,
'axis1': axis1,
'axis2': axis2},
outputs={'Out': [out]})
return out
@templatedoc(op_type="kron")
def kron(x, y, name=None):
"""
${comment}
Args:
x (Tensor): the fist operand of kron op, data type: float16, float32,
float64, int32 or int64.
y (Tensor): the second operand of kron op, data type: float16,
float32, float64, int32 or int64. Its data type should be the same
with x.
name(str, optional): The default value is None. Normally there is no
need for user to set this property. For more information, please
refer to :ref:`api_guide_Name`.
Returns:
Tensor: The output of kron op, data type: float16, float32, float64, int32 or int64. Its data is the same with x.
Examples:
.. code-block:: python
import paddle
x = paddle.to_tensor([[1, 2], [3, 4]], dtype='int64')
y = paddle.to_tensor([[1, 2, 3], [4, 5, 6], [7, 8, 9]], dtype='int64')
out = paddle.kron(x, y)
print(out)
# [[1, 2, 3, 2, 4, 6],
# [ 4, 5, 6, 8, 10, 12],
# [ 7, 8, 9, 14, 16, 18],
# [ 3, 6, 9, 4, 8, 12],
# [12, 15, 18, 16, 20, 24],
# [21, 24, 27, 28, 32, 36]])
"""
if paddle.in_dynamic_mode():
return _C_ops.kron(x, y)
helper = LayerHelper('kron', **locals())
check_variable_and_dtype(x, 'x', ['float16', 'float32', 'float64', 'int32', 'int64'], 'kron')
check_variable_and_dtype(y, 'y', ['float16', 'float32', 'float64', 'int32', 'int64'], 'kron')
out = helper.create_variable_for_type_inference(dtype=x.dtype)
helper.append_op(type="kron", inputs={"X": x, "Y": y}, outputs={"Out": out})
return out
def cumsum(x, axis=None, dtype=None, name=None):
"""
The cumulative sum of the elements along a given axis.
**Note**:
The first element of the result is the same of the first element of the input.
Args:
x (Tensor): The input tensor needed to be cumsumed.
axis (int, optional): The dimension to accumulate along. -1 means the last dimension. The default (None) is to compute the cumsum over the flattened array.
dtype (str, optional): The data type of the output tensor, can be float32, float64, int32, int64. If specified, the input tensor is casted to dtype before the operation is performed. This is useful for preventing data type overflows. The default value is None.
name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
Returns:
Tensor, the result of cumsum operator.
Examples:
.. code-block:: python
import paddle
data = paddle.arange(12)
data = paddle.reshape(data, (3, 4))
y = paddle.cumsum(data)
# [ 0 1 3 6 10 15 21 28 36 45 55 66]
y = paddle.cumsum(data, axis=0)
# [[ 0 1 2 3]
# [ 4 6 8 10]
# [12 15 18 21]]
y = paddle.cumsum(data, axis=-1)
# [[ 0 1 3 6]
# [ 4 9 15 22]
# [ 8 17 27 38]]
y = paddle.cumsum(data, dtype='float64')
print(y.dtype)
# VarType.FP64
"""
if axis is None:
flatten = True
else:
flatten = False
if dtype is not None and x.dtype != convert_np_dtype_to_dtype_(dtype):
x = cast(x, dtype)
if paddle.in_dynamic_mode():
if axis is None:
return _C_ops.cumsum(x, 'flatten', flatten)
else:
return _C_ops.cumsum(x, 'axis', axis, 'flatten', flatten)
check_type(x, 'x', (Variable), 'cumsum')
locals_var = locals().copy()
kwargs = dict()
for name, val in locals_var.items():
if val is not None:
kwargs[name] = val
_cum_sum_ = generate_layer_fn('cumsum')
return _cum_sum_(**kwargs)
def cumprod(x, dim=None, dtype=None, name=None):
"""
Compute the cumulative product of the input tensor x along a given dimension dim.
**Note**:
The first element of the result is the same as the first element of the input.
Args:
x (Tensor): the input tensor need to be cumproded.
dim (int): the dimension along which the input tensor will be accumulated. It need to be in the range of [-x.rank, x.rank), where x.rank means the dimensions of the input tensor x and -1 means the last dimension.
dtype (str, optional): The data type of the output tensor, can be float32, float64, int32, int64, complex64, complex128. If specified, the input tensor is casted to dtype before the operation is performed. This is useful for preventing data type overflows. The default value is None.
name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
Returns:
Tensor, the result of cumprod operator.
Examples:
.. code-block:: python
import paddle
data = paddle.arange(12)
data = paddle.reshape(data, (3, 4))
# [[ 0 1 2 3 ]
# [ 4 5 6 7 ]
# [ 8 9 10 11]]
y = paddle.cumprod(data, dim=0)
# [[ 0 1 2 3]
# [ 0 5 12 21]
# [ 0 45 120 231]]
y = paddle.cumprod(data, dim=-1)
# [[ 0 0 0 0]
# [ 4 20 120 840]
# [ 8 72 720 7920]]
y = paddle.cumprod(data, dim=1, dtype='float64')
# [[ 0. 0. 0. 0.]
# [ 4. 20. 120. 840.]
# [ 8. 72. 720. 7920.]]
print(y.dtype)
# paddle.float64
"""
if dtype is not None and x.dtype != convert_np_dtype_to_dtype_(dtype):
x = cast(x, dtype)
if paddle.in_dynamic_mode():
return _C_ops.cumprod(x, 'dim', dim)
check_variable_and_dtype(x, "x", ['complex64', 'complex128', 'float32', 'float64', 'int32', 'int64'], 'cumprod')
check_type(dim, 'dim', int, 'cumprod')
helper = LayerHelper('cumprod', **locals())
out = helper.create_variable_for_type_inference(x.dtype)
helper.append_op(type='cumprod', inputs={'X': x}, outputs={'Out': out}, attrs={'dim': dim})
return out
def isfinite(x, name=None):
"""
Return whether every element of input tensor is finite number or not.
Args:
x (Tensor): The input tensor, it's data type should be float16, float32, float64, int32, int64.
name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
Returns:
`Tensor`, the bool result which shows every element of `x` whether it is finite number or not.
Examples:
.. code-block:: python
import paddle
x = paddle.to_tensor([float('-inf'), -2, 3.6, float('inf'), 0, float('-nan'), float('nan')])
out = paddle.tensor.isfinite(x)
print(out) # [False True True False True False False]
"""
if paddle.in_dynamic_mode():
return _C_ops.isfinite_v2(x)
helper = LayerHelper("isfinite_v2", **locals())
check_variable_and_dtype(x, 'x', ['float16', 'float32', 'float64', 'int32', 'int64'], 'isfinite')
out = helper.create_variable_for_type_inference('bool')
helper.append_op(type="isfinite_v2", inputs={"X": x}, outputs={"Out": out})
return out
def isinf(x, name=None):
"""
Return whether every element of input tensor is `+/-INF` or not.
Args:
x (Tensor): The input tensor, it's data type should be float16, float32, float64, int32, int64.
name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
Returns:
`Tensor`, the bool result which shows every element of `x` whether it is `+/-INF` or not.
Examples:
.. code-block:: python
import paddle
x = paddle.to_tensor([float('-inf'), -2, 3.6, float('inf'), 0, float('-nan'), float('nan')])
out = paddle.tensor.isinf(x)
print(out) # [ True False False True False False False]
"""
if paddle.in_dynamic_mode():
return _C_ops.isinf_v2(x)
helper = LayerHelper("isinf_v2", **locals())
check_variable_and_dtype(x, 'x', ['float16', 'float32', 'float64', 'int32', 'int64'], 'isinf')
out = helper.create_variable_for_type_inference(dtype='bool')
helper.append_op(type="isinf_v2", inputs={"X": x}, outputs={"Out": out})
return out
def isnan(x, name=None):
"""
Return whether every element of input tensor is `NaN` or not.
Args:
x (Tensor): The input tensor, it's data type should be float16, float32, float64, int32, int64.
name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
Returns:
`Tensor`, the bool result which shows every element of `x` whether it is `NaN` or not.
Examples:
.. code-block:: python
import paddle
x = paddle.to_tensor([float('-inf'), -2, 3.6, float('inf'), 0, float('-nan'), float('nan')])
out = paddle.tensor.isnan(x)
print(out) # [False False False False False True True]
"""
if paddle.in_dynamic_mode():
return _C_ops.isnan_v2(x)
helper = LayerHelper("isnan_v2", **locals())
check_variable_and_dtype(x, 'x', ['float16', 'float32', 'float64', 'int32', 'int64'], 'isnan')
out = helper.create_variable_for_type_inference(dtype='bool')
helper.append_op(type="isnan_v2", inputs={"X": x}, outputs={"Out": out})
return out
def prod(x, axis=None, keepdim=False, dtype=None, name=None):
"""
Compute the product of tensor elements over the given axis.
Args:
x(Tensor): The input tensor, its data type should be float32, float64, int32, int64.
axis(int|list|tuple, optional): The axis along which the product is computed. If :attr:`None`,
multiply all elements of `x` and return a Tensor with a single element,
otherwise must be in the range :math:`[-x.ndim, x.ndim)`. If :math:`axis[i]<0`,
the axis to reduce is :math:`x.ndim + axis[i]`. Default is None.
dtype(str|np.dtype, optional): The desired date type of returned tensor, can be float32, float64,
int32, int64. If specified, the input tensor is casted to dtype before operator performed.
This is very useful for avoiding data type overflows. The default value is None, the dtype
of output is the same as input Tensor `x`.
keepdim(bool, optional): Whether to reserve the reduced dimension in the output Tensor. The result
tensor will have one fewer dimension than the input unless `keepdim` is true. Default is False.
name(string, optional): The default value is None. Normally there is no need for user to set this property.
For more information, please refer to :ref:`api_guide_Name` .
Returns:
Tensor, result of product on the specified dim of input tensor.
Raises:
ValueError: The :attr:`dtype` must be float32, float64, int32 or int64.
TypeError: The type of :attr:`axis` must be int, list or tuple.
Examples:
.. code-block:: python
import paddle
# the axis is a int element
x = paddle.to_tensor([[0.2, 0.3, 0.5, 0.9],
[0.1, 0.2, 0.6, 0.7]])
out1 = paddle.prod(x)
# [0.0002268]
out2 = paddle.prod(x, -1)
# [0.027 0.0084]
out3 = paddle.prod(x, 0)
# [0.02 0.06 0.3 0.63]
out4 = paddle.prod(x, 0, keepdim=True)
# [[0.02 0.06 0.3 0.63]]
out5 = paddle.prod(x, 0, dtype='int64')
# [0 0 0 0]
# the axis is list
y = paddle.to_tensor([[[1.0, 2.0], [3.0, 4.0]],
[[5.0, 6.0], [7.0, 8.0]]])
out6 = paddle.prod(y, [0, 1])
# [105. 384.]
out7 = paddle.prod(y, (1, 2))
# [ 24. 1680.]
"""
if dtype is not None:
check_dtype(dtype, 'dtype', ['float32', 'float64', 'int32', 'int64'], 'prod')
if x.dtype != convert_np_dtype_to_dtype_(dtype):
x = cast(x, dtype)
return reduce_prod(input=x, dim=axis, keep_dim=keepdim, name=name)
def sign(x, name=None):
"""
This OP returns sign of every element in `x`: 1 for positive, -1 for negative and 0 for zero.
Args:
x(Tensor): The input tensor. The data type can be float16, float32 or float64.
name (str, optional): The default value is None. Normally there is no need for user to
set this property. For more information, please refer to :ref:`api_guide_Name`
Returns:
Tensor: The output sign tensor with identical shape and data type to the input :attr:`x`.
Examples:
.. code-block:: python
import paddle
x = paddle.to_tensor([3.0, 0.0, -2.0, 1.7], dtype='float32')
out = paddle.sign(x=x)
print(out) # [1.0, 0.0, -1.0, 1.0]
"""
if paddle.in_dynamic_mode():
return _C_ops.sign(x)
check_variable_and_dtype(x, 'x', ['float16', 'float32', 'float64'], 'sign')
helper = LayerHelper("sign", **locals())
out = helper.create_variable_for_type_inference(dtype=x.dtype)
helper.append_op(type='sign', inputs={'X': [x]}, outputs={'Out': [out]})
return out
def tanh(x, name=None):
r"""
Tanh Activation Operator.
.. math::
out = \\frac{e^{x} - e^{-x}}{e^{x} + e^{-x}}
Args:
x (Tensor): Input of Tanh operator, an N-D Tensor, with data type float32, float64 or float16.
name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
Returns:
Output of Tanh operator, a Tensor with same data type and shape as input.
Examples:
.. code-block:: python
import paddle
x = paddle.to_tensor([-0.4, -0.2, 0.1, 0.3])
out = paddle.tanh(x)
print(out)
# [-0.37994896 -0.19737532 0.09966799 0.29131261]
"""
if paddle.in_dynamic_mode():
return _C_ops.tanh(x)
check_variable_and_dtype(x, 'x', ['float16', 'float32', 'float64'], 'tanh')
check_type(x, 'x', (Variable), 'tanh')
helper = LayerHelper('tanh', **locals())
out = helper.create_variable_for_type_inference(x.dtype)
helper.append_op(type='tanh', inputs={'X': x}, outputs={'Out': out})
return out
@inplace_apis_in_dygraph_only
def tanh_(x, name=None):
r"""
Inplace version of ``tanh`` API, the output Tensor will be inplaced with input ``x``.
Please refer to :ref:`api_tensor_tanh`.
"""
return _C_ops.tanh_(x)
def increment(x, value=1.0, name=None):
"""
The OP is usually used for control flow to increment the data of :attr:`x` by an amount :attr:`value`.
Notice that the number of elements in :attr:`x` must be equal to 1.
Args:
x (Tensor): A tensor that must always contain only one element, its data type supports float32, float64, int32 and int64.
value(float, optional): The amount to increment the data of :attr:`x`. Default: 1.0.
name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
Returns:
Tensor, the elementwise-incremented tensor with the same shape and data type as :attr:`x`.
Examples:
.. code-block:: python
import paddle
data = paddle.zeros(shape=[1], dtype='float32')
counter = paddle.increment(data)
# [1.]
"""
if paddle.in_dynamic_mode():
return _C_ops.increment(x, 'step', value)
check_variable_and_dtype(x, 'x', ['float32', 'float64', 'int32', 'int64'],
'increment')
helper = LayerHelper("increment", **locals())
helper.append_op(
type='increment',
inputs={'X': [x]},
outputs={'Out': [x]},
attrs={'step': float(value)})
return x
def all(x, axis=None, keepdim=False, name=None):
"""
Computes the the ``logical and`` of tensor elements over the given dimension.
Args:
x (Tensor): An N-D Tensor, the input data type should be `bool`.
axis (int|list|tuple, optional): The dimensions along which the ``logical and`` is compute. If
:attr:`None`, and all elements of :attr:`x` and return a
Tensor with a single element, otherwise must be in the
range :math:`[-rank(x), rank(x))`. If :math:`axis[i] < 0`,
the dimension to reduce is :math:`rank + axis[i]`.
keepdim (bool, optional): Whether to reserve the reduced dimension in the
output Tensor. The result Tensor will have one fewer dimension
than the :attr:`x` unless :attr:`keepdim` is true, default
value is False.
name (str, optional): The default value is None. Normally there is no need for
user to set this property. For more information, please refer to :ref:`api_guide_Name`
Returns:
Tensor: Results the ``logical and`` on the specified axis of input Tensor `x`, it's data type is bool.
Raises:
ValueError: If the data type of `x` is not bool.
TypeError: The type of :attr:`axis` must be int, list or tuple.
Examples:
.. code-block:: python
import paddle
import numpy as np
# x is a bool Tensor with following elements:
# [[True, False]
# [True, True]]
x = paddle.assign(np.array([[1, 0], [1, 1]], dtype='int32'))
print(x)
x = paddle.cast(x, 'bool')
# out1 should be [False]
out1 = paddle.all(x) # [False]
print(out1)
# out2 should be [True, False]
out2 = paddle.all(x, axis=0) # [True, False]
print(out2)
# keep_dim=False, out3 should be [False, True], out.shape should be (2,)
out3 = paddle.all(x, axis=-1) # [False, True]
print(out3)
# keep_dim=True, out4 should be [[False], [True]], out.shape should be (2,1)
out4 = paddle.all(x, axis=1, keepdim=True)
out4 = paddle.cast(out4, 'int32') # [[False], [True]]
print(out4)
"""
if axis is not None and not isinstance(axis, (list, tuple)):
axis = [axis]
if not axis:
reduce_all_flag = True
else:
if len(axis) == len(x.shape):
reduce_all_flag = True
else:
reduce_all_flag = False
if paddle.in_dynamic_mode():
axis = axis if axis != None and axis != [] else [0]
return _C_ops.reduce_all(x, 'dim', axis, 'keep_dim', keepdim,
'reduce_all', reduce_all_flag)
attrs = {
'dim': axis if axis != None and axis != [] and axis != () else [0],
'keep_dim': keepdim,
'reduce_all': reduce_all_flag
}
check_variable_and_dtype(x, 'x', ['bool'], 'all')
check_type(axis, 'axis', (int, list, tuple, type(None)), 'all')
helper = LayerHelper('all', **locals())
out = helper.create_variable_for_type_inference(dtype=x.dtype)
helper.append_op(
type='reduce_all',
inputs={'X': x},
outputs={'Out': out},
attrs=attrs)
return out
def any(x, axis=None, keepdim=False, name=None):
"""
Computes the the ``logical or`` of tensor elements over the given dimension.
Args:
x (Tensor): An N-D Tensor, the input data type should be `bool`.
axis (int|list|tuple, optional): The dimensions along which the ``logical or`` is compute. If
:attr:`None`, and all elements of :attr:`x` and return a
Tensor with a single element, otherwise must be in the
range :math:`[-rank(x), rank(x))`. If :math:`axis[i] < 0`,
the dimension to reduce is :math:`rank + axis[i]`.
keepdim (bool, optional): Whether to reserve the reduced dimension in the
output Tensor. The result Tensor will have one fewer dimension
than the :attr:`x` unless :attr:`keepdim` is true, default
value is False.
name (str, optional): The default value is None. Normally there is no need for
user to set this property. For more information, please refer to :ref:`api_guide_Name`
Returns:
Tensor: Results the ``logical or`` on the specified axis of input Tensor `x`, it's data type is bool.
Raises:
ValueError: If the data type of `x` is not bool.
TypeError: The type of :attr:`axis` must be int, list or tuple.
Examples:
.. code-block:: python
import paddle
import numpy as np
# x is a bool Tensor with following elements:
# [[True, False]
# [False, False]]
x = paddle.assign(np.array([[1, 0], [1, 1]], dtype='int32'))
print(x)
x = paddle.cast(x, 'bool')
# out1 should be [True]
out1 = paddle.any(x) # [True]
print(out1)
# out2 should be [True, True]
out2 = paddle.any(x, axis=0) # [True, True]
print(out2)
# keep_dim=False, out3 should be [True, True], out.shape should be (2,)
out3 = paddle.any(x, axis=-1) # [True, True]
print(out3)
# keep_dim=True, result should be [[True], [True]], out.shape should be (2,1)
out4 = paddle.any(x, axis=1, keepdim=True)
out4 = paddle.cast(out4, 'int32') # [[True], [True]]
print(out4)
"""
if axis is not None and not isinstance(axis, (list, tuple)):
axis = [axis]
if not axis:
reduce_all_flag = True
else:
if len(axis) == len(x.shape):
reduce_all_flag = True
else:
reduce_all_flag = False
if paddle.in_dynamic_mode():
axis = axis if axis != None and axis != [] else [0]
return _C_ops.reduce_any(x, 'dim', axis, 'keep_dim', keepdim,
'reduce_all', reduce_all_flag)
attrs = {
'dim': axis if axis != None and axis != [] and axis != () else [0],
'keep_dim': keepdim,
'reduce_all': reduce_all_flag
}
check_variable_and_dtype(x, 'x', ['bool'], 'any')
check_type(axis, 'axis', (int, list, tuple, type(None)), 'any')
helper = LayerHelper('any', **locals())
out = helper.create_variable_for_type_inference(dtype=x.dtype)
helper.append_op(
type='reduce_any',
inputs={'X': x},
outputs={'Out': out},
attrs=attrs)
return out
def broadcast_shape(x_shape, y_shape):
"""
The function returns the shape of doing operation with broadcasting on tensors of x_shape and y_shape, please refer to :ref:`user_guide_broadcasting` for more details.
Args:
x_shape (list[int]|tuple[int]): A shape of tensor.
y_shape (list[int]|tuple[int]): A shape of tensor.
Returns:
list[int], the result shape.
Examples:
.. code-block:: python
import paddle
shape = paddle.broadcast_shape([2, 1, 3], [1, 3, 1])
# [2, 3, 3]
# shape = paddle.broadcast_shape([2, 1, 3], [3, 3, 1])
# ValueError (terminated with error message).
"""
return core.broadcast_shape(x_shape, y_shape)
def conj(x, name=None):
r"""
This function computes the conjugate of the Tensor elementwisely.
Args:
x (Tensor): The input tensor which hold the complex numbers.
Optional data types are: complex64, complex128, float32, float64, int32 or int64.
name (str, optional): The default value is None. Normally there is no need for
user to set this property. For more information, please refer to :ref:`api_guide_Name`
Returns:
out (Tensor): The conjugate of input. The shape and data type is the same with input.
If the elements of tensor is real type such as float32, float64, int32 or int64, the out is the same with input.
Examples:
.. code-block:: python
import paddle
data=paddle.to_tensor([[1+1j, 2+2j, 3+3j], [4+4j, 5+5j, 6+6j]])
#Tensor(shape=[2, 3], dtype=complex64, place=CUDAPlace(0), stop_gradient=True,
# [[(1+1j), (2+2j), (3+3j)],
# [(4+4j), (5+5j), (6+6j)]])
conj_data=paddle.conj(data)
#Tensor(shape=[2, 3], dtype=complex64, place=CUDAPlace(0), stop_gradient=True,
# [[(1-1j), (2-2j), (3-3j)],
# [(4-4j), (5-5j), (6-6j)]])
"""
if paddle.in_dynamic_mode():
return _C_ops.conj(x)
check_variable_and_dtype(x, "x", ['complex64', 'complex128', 'float32', 'float64', 'int32', 'int64'], 'conj')
helper = LayerHelper('conj', **locals())
out = helper.create_variable_for_type_inference(
dtype=helper.input_dtype())
helper.append_op(type='conj', inputs={'X': x}, outputs={'Out': [out]})
return out
def digamma(x, name=None):
r"""
Calculates the digamma of the given input tensor, element-wise.
.. math::
Out = \Psi(x) = \frac{ \Gamma^{'}(x) }{ \Gamma(x) }
Args:
x (Tensor): Input Tensor. Must be one of the following types: float32, float64.
name(str, optional): The default value is None. Normally there is no need for
user to set this property. For more information, please refer to :ref:`api_guide_Name`
Returns:
Tensor, the digamma of the input Tensor, the shape and data type is the same with input.
Examples:
.. code-block:: python
import paddle
data = paddle.to_tensor([[1, 1.5], [0, -2.2]], dtype='float32')
res = paddle.digamma(data)
print(res)
# Tensor(shape=[2, 2], dtype=float32, place=CUDAPlace(0), stop_gradient=True,
# [[-0.57721591, 0.03648996],
# [ nan , 5.32286835]])
"""
if paddle.in_dynamic_mode():
if _in_eager_mode():
return _C_ops.final_state_digamma(x)
return _C_ops.digamma(x)
check_variable_and_dtype(x, 'x', ['float32', 'float64'], 'digamma')
helper = LayerHelper('digamma', **locals())
out = helper.create_variable_for_type_inference(x.dtype)
helper.append_op(type='digamma', inputs={'X': x}, outputs={'Out': out})
return out
def neg(x, name=None):
"""
This function computes the negative of the Tensor elementwisely.
Args:
x (Tensor): Input of neg operator, an N-D Tensor, with data type float32, float64, int8, int16, int32, or int64.
name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
Returns:
out (Tensor): The negative of input Tensor. The shape and data type are the same with input Tensor.
Examples:
.. code-block:: python
import paddle
x = paddle.to_tensor([-0.4, -0.2, 0.1, 0.3])
out = paddle.neg(x)
print(out)
# [0.4 0.2 -0.1 -0.3]
"""
return scale(x, scale=-1.0, bias=0.0, bias_after_scale=True, act=None, name=name)
def atan2(x, y, name=None):
r"""
Element-wise arctangent of x/y with consideration of the quadrant.
Equation:
.. math::
atan2(x,y)=\left\{\begin{matrix}
& tan^{-1}(\frac{x}{y}) & y > 0 \\
& tan^{-1}(\frac{x}{y}) + \pi & x>=0, y < 0 \\
& tan^{-1}(\frac{x}{y}) - \pi & x<0, y < 0 \\
& +\frac{\pi}{2} & x>0, y = 0 \\
& -\frac{\pi}{2} & x<0, y = 0 \\
&\text{undefined} & x=0, y = 0
\end{matrix}\right.
Args:
x (Tensor): An N-D Tensor, the data type is int32, int64, float16, float32, float64.
y (Tensor): An N-D Tensor, must have the same type as `x`.
name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
Returns:
out (Tensor): An N-D Tensor, the shape and data type is the same with input (The output data type is float64 when the input data type is int).
Examples:
.. code-block:: python
import paddle
x = paddle.to_tensor([-1, +1, +1, -1]).astype('float32')
#Tensor(shape=[4], dtype=float32, place=CUDAPlace(0), stop_gradient=True,
# [-1, 1, 1, -1])
y = paddle.to_tensor([-1, -1, +1, +1]).astype('float32')
#Tensor(shape=[4], dtype=float32, place=CUDAPlace(0), stop_gradient=True,
# [-1, -1, 1, 1])
out = paddle.atan2(x, y)
#Tensor(shape=[4], dtype=float32, place=CUDAPlace(0), stop_gradient=True,
# [-2.35619450, 2.35619450, 0.78539819, -0.78539819])
"""
if paddle.in_dynamic_mode():
if _in_eager_mode():
return _C_ops.final_state_atan2( x, y)
return _C_ops.atan2(x, y)
else:
check_variable_and_dtype(x, 'x', ['int32', 'int64', 'float16', 'float32', 'float64'], 'atan2')
check_variable_and_dtype(y, 'y', ['int32', 'int64', 'float16', 'float32', 'float64'], 'atan2')
helper = LayerHelper('atan2', **locals())
inputs = {'X1' : x, 'X2' : y}
out = helper.create_variable_for_type_inference(dtype=x.dtype)
helper.append_op(
type='atan2', inputs=inputs, outputs={'Out': out})
return out
def logit(x, eps=None, name=None):
r"""
This function generates a new tensor with the logit of the elements of input x. x is clamped to [eps, 1-eps] when eps is not zero. When eps is zero and x < 0 or x > 1, the function will yields NaN.
.. math::
logit(x) = ln(\frac{x}{1 - x})
where
.. math::
x_i=
\left\{\begin{array}{rcl}
x_i & &\text{if } eps == Default \\
eps & &\text{if } x_i < eps \\
x_i & &\text{if } eps <= x_i <= 1-eps \\
1-eps & &\text{if } x_i > 1-eps
\end{array}\right.
Args:
x (Tensor): The input Tensor with data type float32, float64.
eps (float, optional): the epsilon for input clamp bound. Default is None.
name (str, optional): Name for the operation (optional, default is None).
For more information, please refer to :ref:`api_guide_Name`.
Returns:
out(Tensor): A Tensor with the same data type and shape as ``x`` .
Examples:
.. code-block:: python
import paddle
x = paddle.to_tensor([0.2635, 0.0106, 0.2780, 0.2097, 0.8095])
out1 = paddle.logit(x)
print(out1)
# [-1.0277, -4.5365, -0.9544, -1.3269, 1.4468]
"""
if eps == None:
eps = 0.0
if paddle.in_dynamic_mode():
return _C_ops.logit(x, 'eps', eps)
check_variable_and_dtype(x, 'x', ['float16', 'float32', 'float64'], 'logit')
helper = LayerHelper("logit", **locals())
out = helper.create_variable_for_type_inference(x.dtype)
helper.append_op(
type='logit',
inputs={'X': x},
outputs={'Out': out},
attrs={'eps': eps})
return out
def lerp(x, y, weight, name=None):
r"""
Does a linear interpolation between x and y based on weight.
Equation:
.. math::
lerp(x, y, weight) = x + weight * (y - x).
Args:
x (Tensor): An N-D Tensor with starting points, the data type is float32, float64.
y (Tensor): An N-D Tensor with ending points, the data type is float32, float64.
weight (float|Tensor): The weight for the interpolation formula. When weight is Tensor, the data type is float32, float64.
name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
Returns:
out (Tensor): An N-D Tensor, the shape and data type is the same with input.
Example:
.. code-block:: python
import paddle
x = paddle.arange(1., 5., dtype='float32')
y = paddle.empty([4], dtype='float32')
y.fill_(10.)
out = paddle.lerp(start, end, 0.5)
# out: [5.5., 6., 6.5, 7.]
"""
if paddle.in_dynamic_mode():
check_type(weight, 'weight', (float, paddle.Tensor, Variable), 'lerp')
if isinstance(weight, float):
weight = paddle.to_tensor(weight, dtype=x.dtype)
return _C_ops.lerp(x, y, weight)
if isinstance(weight, float):
weight = paddle.full(shape=[1], fill_value=weight, dtype=x.dtype)
check_variable_and_dtype(x, 'x', ['float32', 'float64'], 'lerp')
check_variable_and_dtype(y, 'y', ['float32', 'float64'], 'lerp')
check_variable_and_dtype(weight, 'weight', ['float32', 'float64'], 'lerp')
helper = LayerHelper('lerp', **locals())
inputs = {'X': x, 'Y': y, 'Weight': weight}
out = helper.create_variable_for_type_inference(dtype=x.dtype)
helper.append_op(type='lerp', inputs=inputs, outputs={'Out': out})
return out
@inplace_apis_in_dygraph_only
def lerp_(x, y, weight, name=None):
r"""
Inplace version of ``lerp`` API, the output Tensor will be inplaced with input ``x``.
Please refer to :ref:`api_tensor_lerp`.
"""
out_shape = broadcast_shape(x.shape, y.shape)
check_type(weight, 'weight', (float, paddle.Tensor, Variable), 'lerp')
if isinstance(weight, float):
weight = paddle.to_tensor([weight], dtype=x.dtype)
elif isinstance(weight, (paddle.Tensor, Variable)):
out_shape = broadcast_shape(out_shape, weight.shape)
if out_shape != x.shape:
raise ValueError("The shape of broadcast output {} is different from that of inplace tensor {} in the Inplace operation.".format(out_shape, x.shape))
return _C_ops.lerp_(x, y, weight)
def erfinv(x, name=None):
r"""
The inverse error function of x, .
Equation:
.. math::
erfinv(erf(x)) = x.
Args:
x (Tensor): An N-D Tensor, the data type is float32, float64.
name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
Returns:
out (Tensor): An N-D Tensor, the shape and data type is the same with input.
Example:
.. code-block:: python
import paddle
x = paddle.to_tensor([0, 0.5, -1.], dtype="float32")
out = paddle.erfinv(x)
# out: [0, 0.4769, -inf]
"""
check_variable_and_dtype(x, 'x', ['float32', 'float64'], 'erfinv')
if paddle.in_dynamic_mode():
return _C_ops.erfinv(x)
helper = LayerHelper('erfinv', **locals())
out = helper.create_variable_for_type_inference(dtype=x.dtype)
helper.append_op(type='erfinv', inputs={'X': x}, outputs={'Out': out})
return out
@inplace_apis_in_dygraph_only
def erfinv_(x, name=None):
r"""
Inplace version of ``erfinv`` API, the output Tensor will be inplaced with input ``x``.
Please refer to :ref:`api_tensor_erfinv`.
"""
check_type(x, 'x', (paddle.Tensor, Variable), 'erfinv')
return _C_ops.erfinv_(x)
def rad2deg(x, name=None):
r"""
Convert each of the elements of input x from angles in radians to degrees.
Equation:
.. math::
rad2deg(x)=180/ \pi * x
Args:
x (Tensor): An N-D Tensor, the data type is float32, float64, int32, int64.
name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
Returns:
out (Tensor): An N-D Tensor, the shape and data type is the same with input (The output data type is float32 when the input data type is int).
Examples:
.. code-block:: python
import paddle
import numpy as np
x1 = paddle.to_tensor([3.142, -3.142, 6.283, -6.283, 1.570, -1.570])
result1 = paddle.rad2deg(x1)
print(result1)
# Tensor(shape=[6], dtype=float32, place=CUDAPlace(0), stop_gradient=True,
# [180.02334595, -180.02334595, 359.98937988, -359.98937988,
# 9.95437622 , -89.95437622])
x2 = paddle.to_tensor(np.pi/2)
result2 = paddle.rad2deg(x2)
print(result2)
# Tensor(shape=[1], dtype=float32, place=CUDAPlace(0), stop_gradient=True,
# [90.])
x3 = paddle.to_tensor(1)
result3 = paddle.rad2deg(x3)
print(result3)
# Tensor(shape=[1], dtype=float32, place=CUDAPlace(0), stop_gradient=True,
# [57.29578018])
"""
rad2deg_scale = 180 / np.pi
if paddle.in_dynamic_mode():
if convert_dtype(x.dtype) in ['int32', 'int64']:
x = cast(x, dtype="float32")
return _C_ops.scale(x, 'scale', rad2deg_scale)
else:
check_variable_and_dtype(x, 'x', ['int32', 'int64', 'float32', 'float64'], 'rad2deg')
helper = LayerHelper('rad2deg', **locals())
out_cast = x
if convert_dtype(x.dtype) in ['int32', 'int64']:
out_cast = helper.create_variable_for_type_inference(dtype=paddle.float32)
helper.append_op(
type='cast', inputs={'X':x}, outputs={'Out': out_cast}, attrs={'in_dtype': x.dtype,'out_dtype': paddle.float32})
out = helper.create_variable_for_type_inference(dtype=out_cast.dtype)
helper.append_op(
type='scale', inputs={'X':out_cast}, outputs={'Out': out}, attrs={'scale': rad2deg_scale})
return out
def deg2rad(x, name=None):
r"""
Convert each of the elements of input x from degrees to angles in radians.
Equation:
.. math::
deg2rad(x)=\pi * x / 180
Args:
x (Tensor): An N-D Tensor, the data type is float32, float64, int32, int64.
name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
Returns:
out (Tensor): An N-D Tensor, the shape and data type is the same with input (The output data type is float32 when the input data type is int).
Examples:
.. code-block:: python
import paddle
import numpy as np
x1 = paddle.to_tensor([180.0, -180.0, 360.0, -360.0, 90.0, -90.0])
result1 = paddle.deg2rad(x1)
print(result1)
# Tensor(shape=[6], dtype=float32, place=CUDAPlace(0), stop_gradient=True,
# [3.14159274, -3.14159274, 6.28318548, -6.28318548, 1.57079637,
# -1.57079637])
x2 = paddle.to_tensor(180)
result2 = paddle.deg2rad(x2)
print(result2)
# Tensor(shape=[1], dtype=float32, place=CUDAPlace(0), stop_gradient=True,
# [3.14159274])
"""
deg2rad_scale = np.pi / 180.0
if paddle.in_dynamic_mode():
if convert_dtype(x.dtype) in ['int32', 'int64']:
x = cast(x, dtype="float32")
return _C_ops.scale(x, 'scale', deg2rad_scale)
else:
check_variable_and_dtype(x, 'x', ['int32', 'int64', 'float32', 'float64'], 'deg2rad')
helper = LayerHelper('deg2rad', **locals())
out_cast = x
if convert_dtype(x.dtype) in ['int32', 'int64']:
out_cast = helper.create_variable_for_type_inference(dtype=paddle.float32)
helper.append_op(
type='cast', inputs={'X':x}, outputs={'Out': out_cast}, attrs={'in_dtype': x.dtype,'out_dtype': paddle.float32})
out = helper.create_variable_for_type_inference(dtype=out_cast.dtype)
helper.append_op(
type='scale', inputs={'X':out_cast}, outputs={'Out': out}, attrs={'scale': deg2rad_scale})
return out
def gcd(x, y, name=None):
"""
Computes the element-wise greatest common divisor (GCD) of input |x| and |y|.
Both x and y must have integer types.
Note:
gcd(0,0)=0, gcd(0, y)=|y|
If x.shape != y.shape, they must be broadcastable to a common shape (which becomes the shape of the output).
Args:
x (Tensor): An N-D Tensor, the data type is int32，int64.
y (Tensor): An N-D Tensor, the data type is int32，int64.
name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
Returns:
out (Tensor): An N-D Tensor, the data type is the same with input.
Examples:
.. code-block:: python
import paddle
x1 = paddle.to_tensor(12)
x2 = paddle.to_tensor(20)
paddle.gcd(x1, x2)
# Tensor(shape=[1], dtype=int64, place=CUDAPlace(0), stop_gradient=True,
# [4])
x3 = paddle.arange(6)
paddle.gcd(x3, x2)
# Tensor(shape=[6], dtype=int64, place=CUDAPlace(0), stop_gradient=True,
# [20, 1 , 2 , 1 , 4 , 5])
x4 = paddle.to_tensor(0)
paddle.gcd(x4, x2)
# Tensor(shape=[1], dtype=int64, place=CUDAPlace(0), stop_gradient=True,
# [20])
paddle.gcd(x4, x4)
# Tensor(shape=[1], dtype=int64, place=CUDAPlace(0), stop_gradient=True,
# [0])
x5 = paddle.to_tensor(-20)
paddle.gcd(x1, x5)
# Tensor(shape=[1], dtype=int64, place=CUDAPlace(0), stop_gradient=True,
# [4])
"""
shape = paddle.broadcast_shape(x.shape, y.shape)
x = paddle.broadcast_to(x, shape)
y = paddle.broadcast_to(y, shape)
x = paddle.abs(x)
y = paddle.abs(y)
def _gcd_cond_fn(x, y):
return paddle.any(y != 0)
def _gcd_body_fn(x, y):
# paddle.mod will raise an error when any element of y is 0. To avoid
# that, we change those zeros to ones. Their values don't matter because
# they won't be used.
y_not_equal_0 = (y != 0)
y_safe = paddle.where(y_not_equal_0, y, paddle.ones(y.shape, y.dtype))
x, y = (paddle.where(y_not_equal_0, y, x),
paddle.where(y_not_equal_0, paddle.mod(x, y_safe),paddle.zeros(y.shape, y.dtype)))
return (paddle.where(x < y, y, x), paddle.where(x < y, x, y))
if paddle.in_dynamic_mode():
while _gcd_cond_fn(x, y):
x, y = _gcd_body_fn(x, y)
return x
else:
check_variable_and_dtype(x, 'x', ['int32', 'int64'], 'gcd')
check_variable_and_dtype(y, 'y', ['int32', 'int64'], 'gcd')
out, _ = paddle.static.nn.while_loop(_gcd_cond_fn, _gcd_body_fn, [x, y])
return out
def lcm(x, y, name=None):
"""
Computes the element-wise least common multiple (LCM) of input |x| and |y|.
Both x and y must have integer types.
Note:
lcm(0,0)=0, lcm(0, y)=0
If x.shape != y.shape, they must be broadcastable to a common shape (which becomes the shape of the output).
Args:
x (Tensor): An N-D Tensor, the data type is int32，int64.
y (Tensor): An N-D Tensor, the data type is int32，int64.
name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
Returns:
out (Tensor): An N-D Tensor, the data type is the same with input.
Examples:
.. code-block:: python
import paddle
x1 = paddle.to_tensor(12)
x2 = paddle.to_tensor(20)
paddle.lcm(x1, x2)
# Tensor(shape=[1], dtype=int64, place=CUDAPlace(0), stop_gradient=True,
# [60])
x3 = paddle.arange(6)
paddle.lcm(x3, x2)
# Tensor(shape=[6], dtype=int64, place=CUDAPlace(0), stop_gradient=True,
# [0, 20, 20, 60, 20, 20])
x4 = paddle.to_tensor(0)
paddle.lcm(x4, x2)
# Tensor(shape=[1], dtype=int64, place=CUDAPlace(0), stop_gradient=True,
# [0])
paddle.lcm(x4, x4)
# Tensor(shape=[1], dtype=int64, place=CUDAPlace(0), stop_gradient=True,
# [0])
x5 = paddle.to_tensor(-20)
paddle.lcm(x1, x5)
# Tensor(shape=[1], dtype=int64, place=CUDAPlace(0), stop_gradient=True,
# [60])
"""
d = paddle.gcd(x, y)
# paddle.mod will raise an error when any element of y is 0. To avoid
# that, we change those zeros to ones. Their values don't matter because
# they won't be used.
d_equal_0 = paddle.equal(d, 0)
d_safe = paddle.where(d_equal_0, paddle.ones(d.shape, d.dtype), d)
out = paddle.where(d_equal_0, paddle.zeros(d.shape, d.dtype), paddle.abs(x * y) // d_safe)
return out
def diff(x, n=1, axis=-1, prepend=None, append=None, name=None):
r"""
Computes the n-th forward difference along the given axis.
The first-order differences is computed by using the following formula:
.. math::
out[i] = x[i+1] - x[i]
Higher-order differences are computed by using paddle.diff() recursively.
Only n=1 is currently supported.
Args:
x(Tensor): The input tensor to compute the forward difference on
n(int, optional): The number of times to recursively compute the difference.
Only support n=1. Default:1
axis(int, optional): The axis to compute the difference along. Default:-1
prepend(Tensor, optional): The tensor to prepend to input along axis before computing the difference.
It's dimensions must be equivalent to that of x,
and its shapes must match x's shape except on axis.
append(Tensor, optional): The tensor to append to input along axis before computing the difference,
It's dimensions must be equivalent to that of x,
and its shapes must match x's shape except on axis.
name(str|None): A name for this layer(optional). If set None,
the layer will be named automatically.
Returns:
Tensor: The output tensor with same dtype with x.
Examples:
.. code-block:: python
import paddle
x = paddle.to_tensor([1, 4, 5, 2])
out = paddle.diff(x)
print(out)
# out:
# [3, 1, -3]
y = paddle.to_tensor([7, 9])
out = paddle.diff(x, append=y)
print(out)
# out:
# [3, 1, -3, 5, 2]
z = paddle.to_tensor([[1, 2, 3], [4, 5, 6]])
out = paddle.diff(z, axis=0)
print(out)
# out:
# [[3, 3, 3]]
out = paddle.diff(z, axis=1)
print(out)
# out:
# [[1, 1], [1, 1]]
"""
if axis < 0:
axis = axis + len(x.shape)
if axis > len(x.shape):
axis = len(x.shape)
if axis < 0:
axis = 0
dtype = x.dtype
axes = [axis]
infer_flags = list(1 for i in range(len(axes)))
if paddle.in_dynamic_mode():
has_pend = False
input_list = []
if prepend is not None and append is not None:
input_list = [prepend, x, append]
has_pend = True
elif prepend is not None:
input_list = [prepend, x]
has_pend = True
elif append is not None:
input_list = [x, append]
has_pend = True
if has_pend:
new_input = _C_ops.concat(input_list, 'axis', axis)
else:
new_input = x
attrs_1 = ()
attrs_2 = ()
dim_len = new_input.shape[axis]
starts_1 = [0]
attrs_1 += ('starts', starts_1)
ends_1 = [dim_len - 1]
attrs_1 += ('ends', ends_1)
input_front = _C_ops.slice(new_input, None, None, None, None, 'axes', axes, \
'infer_flags', infer_flags, *attrs_1)
starts_2 = [1]
attrs_2 += ('starts', starts_2)
ends_2 = [dim_len]
attrs_2 += ('ends', ends_2)
input_back = _C_ops.slice(new_input, None, None, None, None, 'axes', axes, \
'infer_flags', infer_flags, *attrs_2)
if x.dtype == paddle.bool:
op = getattr(_C_ops, "logical_xor")
out = op(input_back, input_front)
else:
out = elementwise_sub(input_back, input_front, axis=axis)
return out
else:
check_variable_and_dtype(x, 'x', ['float32', 'float64', 'bool', 'int32', 'int64'], 'diff')
check_type(axis, 'axis', (int), 'diff')
helper = LayerHelper('diff', **locals())
has_pend = False
input_list = []
if prepend is not None and append is not None:
input_list = [prepend, x, append]
has_pend = True
elif prepend is not None:
input_list = [prepend, x]
has_pend = True
elif append is not None:
input_list = [x, append]
has_pend = True
if has_pend:
new_input = helper.create_variable_for_type_inference(dtype)
helper.append_op(
type='concat', inputs={'X': input_list}, outputs={'Out': [new_input]}, attrs={'axis': axis}
)
else:
new_input = x
dim_len = new_input.shape[axis]
attrs_1 = {'axes': axes}
starts_1 = [0]
ends_1 = [dim_len - 1]
attrs_1['starts'] = starts_1
attrs_1['ends'] = ends_1
input_front = helper.create_variable_for_type_inference(dtype)
helper.append_op(
type='slice', inputs={'Input': new_input}, attrs=attrs_1, outputs={'Out': input_front}
)
attrs_2 = {'axes': axes}
starts_2 = [1]
ends_2 = [dim_len]
attrs_2['starts'] = starts_2
attrs_2['ends'] = ends_2
input_back = helper.create_variable_for_type_inference(dtype)
helper.append_op(
type='slice', inputs={'Input': new_input}, attrs=attrs_2, outputs={'Out': input_back}
)
if dtype == paddle.bool:
out = helper.create_variable_for_type_inference(dtype)
helper.append_op(
type='logical_xor', inputs={"X": input_back, "Y": input_front}, outputs={"Out": out}
)
else:
out = elementwise_sub(input_back, input_front, axis=axis)
return out
def angle(x, name=None):
r"""
Element-wise angle of complex numbers. For non-negative real numbers, the angle is 0 while
for negative real numbers, the angle is :math:`\pi`.
Equation:
.. math::
angle(x)=arctan2(x.imag, x.real)
Args:
x (Tensor): An N-D Tensor, the data type is complex64, complex128, or float32, float64 .
name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
Returns:
Tensor: An N-D Tensor of real data type with the same precision as that of x's data type.
Examples:
.. code-block:: python
import paddle
x = paddle.to_tensor([-2, -1, 0, 1]).unsqueeze(-1).astype('float32')
y = paddle.to_tensor([-2, -1, 0, 1]).astype('float32')
z = x + 1j * y
print(z.numpy())
# [[-2.-2.j -2.-1.j -2.+0.j -2.+1.j]
# [-1.-2.j -1.-1.j -1.+0.j -1.+1.j]
# [ 0.-2.j 0.-1.j 0.+0.j 0.+1.j]
# [ 1.-2.j 1.-1.j 1.+0.j 1.+1.j]]
theta = paddle.angle(z)
print(theta.numpy())
# [[-2.3561945 -2.6779451 3.1415927 2.6779451]
# [-2.0344439 -2.3561945 3.1415927 2.3561945]
# [-1.5707964 -1.5707964 0. 1.5707964]
# [-1.1071488 -0.7853982 0. 0.7853982]]
"""
if paddle.in_dynamic_mode():
return _C_ops.angle(x)
check_variable_and_dtype(x, 'x',
['float32', 'float64', 'complex64', 'complex128'], 'angle')
op_type = "angle"
helper = LayerHelper(op_type, **locals())
inputs = {"X": x}
out = helper.create_variable_for_type_inference(
dtype=_complex_to_real_dtype(x.dtype))
outputs = {"Out": out}
helper.append_op(type=op_type, inputs=inputs, outputs=outputs)
return out
| 37.505231 | 291 | 0.564467 |
54c87d3bb5eafbdda0c7721da76bda878f1f6103 | 17,893 | py | Python | src/saltuser/saltuser.py | saltastro/saltuser | a5c97b15b5c2cbf732fb957c9dd91ac04ac23373 | [
"MIT"
] | null | null | null | src/saltuser/saltuser.py | saltastro/saltuser | a5c97b15b5c2cbf732fb957c9dd91ac04ac23373 | [
"MIT"
] | null | null | null | src/saltuser/saltuser.py | saltastro/saltuser | a5c97b15b5c2cbf732fb957c9dd91ac04ac23373 | [
"MIT"
] | null | null | null | import pandas as pd
class SALTUser:
"""
A user of the Southern African Large Telescope with roles and permissions.
The user is identified by their username, as used for the Principal Investigator
Proposal Tool (PIPT) or the Web Manager.
The aim of this class is to allow checking roles and permissions. It includes no
authentication.
A new user should be created using either the constructor or the
:meth:`find_by_username` method.
You need to specify a database connection when creating the user. Any format allowed
by the `con` parameter of pandas' `read_sql` function can be used.
Parameters
----------
user_id : int
The user id.
db_connectable : SQLAlchemy connectable(engine/connection) or database string URI
A connection to the database to use, or its URI.
Raises
------
ValueError
If the user does not exist.
"""
def __init__(self, user_id, db_connectable):
# sanity check: does the user exist?
sql = """
SELECT pu.PiptUser_Id, FirstName, Surname, Email
FROM PiptUser AS pu
JOIN Investigator AS i USING (Investigator_Id)
WHERE pu.PiptUser_Id=%(user_id)s
"""
df = pd.read_sql(sql, con=db_connectable, params=dict(user_id=user_id))
if len(df) == 0:
raise ValueError(
"There is no user with id {user_id}.".format(user_id=user_id)
)
self._db_connectable = db_connectable
self._user_id = user_id
self._given_name = df["FirstName"][0]
self._family_name = df["Surname"][0]
self._email = df["Email"][0]
self._is_board_member = None
self._tac_member_partners = self._find_tac_member_partners()
self._tac_chair_partners = self._find_tac_chair_partners()
self._viewable_proposals_cache = None
@staticmethod
def verify(username, password, db_connectable):
"""
Verify that a username-password combination is valid.
Parameters
----------
username : str
The username.
password : str
The password.
db_connectable : SQLAlchemy connectable(engine/connection) or database string
URI
A connection to the database to use, or its URI.
Raises
------
ValueError
If the username or password are wrong.
"""
sql = """
SELECT PiptUser_Id AS UserCount
FROM PiptUser
WHERE Username=%(username)s AND Password=MD5(%(password)s)
"""
df = pd.read_sql(
sql, con=db_connectable, params=dict(username=username, password=password)
)
if len(df) == 0:
raise ValueError("invlid username or password")
@staticmethod
def find_by_username(username, db_connectable):
"""
Get the user with a given username.
Parameters
----------
username : str
The username.
db_connectable : SQLAlchemy connectable(engine/connection) or database string
URI
A connection to the database to use, or its URI.
Returns
-------
SALTUser
The SALT user.
Raises
------
ValueError
If the user does not exist.
"""
user_id = SALTUser._find_user_id(username, db_connectable)
return SALTUser(user_id, db_connectable)
@property
def given_name(self):
"""
Get the user's given name(s).
Returns
-------
str
The given name(s).
"""
return self._given_name
@property
def family_name(self):
"""
Get the user's family name.
Returns
-------
str
The family name.
"""
return self._family_name
@property
def email(self):
"""
Get the user's email address.
Returns
-------
str
The email address.
"""
return self._email
def is_admin(self):
"""
Check whether the user is an administrator.
Returns
-------
bool
Whether the user is an administrator.
"""
sql = """
SELECT Value
FROM PiptUserSetting as pus
JOIN PiptSetting ps on pus.PiptSetting_Id = ps.PiptSetting_Id
JOIN PiptUser AS pu ON pus.PiptUser_Id = pu.PiptUser_Id
WHERE pu.PiptUser_Id=%(user_id)s AND PiptSetting_Name='RightAdmin'
"""
df = self._query(sql, params=dict(user_id=self._user_id))
return len(df) > 0 and int(df["Value"][0], 10) > 0
def is_investigator(self, proposal_code):
"""
Check whether the user is an investigator for a given proposal.
Parameters
----------
proposal_code : str
The proposal code.
Returns
-------
bool
Whether the user is an investigator for the proposal.
"""
sql = """
SELECT COUNT(*) AS User_Count
FROM ProposalCode AS pc
JOIN ProposalInvestigator pi on pc.ProposalCode_Id = pi.ProposalCode_Id
JOIN Investigator AS i ON pi.Investigator_Id = i.Investigator_Id
WHERE Proposal_Code=%(proposal_code)s AND PiptUser_Id=%(user_id)s
"""
df = self._query(
sql, params=dict(proposal_code=proposal_code, user_id=self._user_id)
)
return df["User_Count"][0] > 0
def is_principal_investigator(self, proposal_code):
"""
Check whether user is the Principal Investigator of a given proposal.
Parameters
----------
proposal_code : str
The proposal code.
Returns
-------
bool
Whether the user is the Principal Investigator of the proposal.
"""
sql = """
SELECT COUNT(*) AS User_Count
FROM ProposalContact AS pco
JOIN Investigator AS i ON pco.Leader_Id=i.Investigator_Id
JOIN ProposalCode AS pc ON pco.ProposalCode_Id = pc.ProposalCode_Id
WHERE Proposal_Code=%(proposal_code)s AND PiptUser_Id=%(user_id)s
"""
df = self._query(
sql, params=dict(proposal_code=proposal_code, user_id=self._user_id)
)
return df["User_Count"][0] > 0
def is_principal_contact(self, proposal_code):
"""
Check whether user is the Principal Contact of a given proposal.
Parameters
----------
proposal_code : str
The proposal code.
Returns
-------
bool
Whether the user is the Principal Contact of the proposal.
"""
sql = """
SELECT COUNT(*) AS User_Count
FROM ProposalContact AS pco
JOIN Investigator AS i ON pco.Contact_Id=i.Investigator_Id
JOIN ProposalCode AS pc ON pco.ProposalCode_Id = pc.ProposalCode_Id
WHERE Proposal_Code=%(proposal_code)s AND PiptUser_Id=%(user_id)s
"""
df = self._query(
sql, params=dict(proposal_code=proposal_code, user_id=self._user_id)
)
return df["User_Count"][0] > 0
def is_board_member(self):
"""
Check whether the user is a Board member.
Returns
-------
bool
Whether the user is a Board member.
"""
if self._is_board_member is None:
sql = """
SELECT *
FROM PiptUserSetting
WHERE PiptUser_Id=%(user_id)s
AND PiptSetting_Id=
(SELECT PiptSetting_Id
FROM PiptSetting
WHERE PiptSetting_Name='RightBoard')
AND Value>0
"""
df = self._query(sql, dict(user_id=self._user_id))
self._is_board_member = len(df) > 0
return self._is_board_member
def is_tac_member(self, partner_code=None):
"""
Check whether the user is member of a partner's TAC.
If no partner code is given, this method checks whether the user is member of
any TAC.
Parameters
----------
partner_code : str
The partner code of the partner.
Returns
-------
bool
Whether the user is member of the partner's TAC.
"""
if not partner_code:
return len(self._tac_member_partners)
return partner_code in self._tac_member_partners
def is_proposal_tac_member(self, proposal_code):
"""
Check whether the user is member of a TAC represented on a given proposal.
Parameters
----------
proposal_code : str
The proposal code.
Returns
-------
bool
Whether the user is member of a TAC represented on the proposal.
"""
return (
len(
set(self._tac_member_partners).intersection(
self._proposal_partners(proposal_code)
)
)
> 0
)
@property
def tacs(self):
"""
The TACs (as a list of partner codes) on which the user serves.
Returns
-------
list of str
The partner codes of the TACs.
"""
return self._tac_member_partners
def is_tac_chair(self, partner_code=None):
"""
Check whether the user is chair of a partner's TAC.
If no partner code is given, this method check whether the user is chair of any
TAC.
Parameters
----------
partner_code : str
The partner code of the partner.
Returns
-------
bool
Whether the user is TAC chair.
"""
if not partner_code:
return len(self._tac_chair_partners)
return partner_code in self._tac_chair_partners
def may_view_proposal(self, proposal_code):
"""
Check whether the user may view a given proposal.
Parameters
----------
proposal_code : str
The proposal code.
Returns
-------
Whether the user may view the proposal.
"""
return proposal_code in self._viewable_proposals
@property
def _viewable_proposals(self):
"""
The proposals (as a list of proposal codes) the user may view.
Returns
-------
list of str
The list of proposal codes.
"""
if self._viewable_proposals_cache is not None:
return self._viewable_proposals_cache
sql = """
SELECT DISTINCT Proposal_Code
FROM ProposalCode AS pc
JOIN ProposalInvestigator AS pi ON pc.ProposalCode_Id = pi.ProposalCode_Id
JOIN Investigator AS i ON pi.Investigator_Id = i.Investigator_Id
JOIN PiptUser AS pu ON i.PiptUser_Id=pu.PiptUser_Id
JOIN Proposal AS p ON pc.ProposalCode_Id = p.ProposalCode_Id
JOIN MultiPartner AS mp ON pc.ProposalCode_Id = mp.ProposalCode_Id
AND p.Semester_Id = mp.Semester_Id
JOIN Partner AS partner ON mp.Partner_Id = partner.Partner_Id
WHERE pu.PiptUser_Id=%(user_id)s
OR (partner.Partner_Code IN %(tacs)s AND mp.ReqTimeAmount>0)
OR (1=%(is_admin)s)
OR (1=%(is_board_member)s)
"""
df = self._query(
sql,
params=dict(
user_id=self._user_id,
tacs=self.tacs if self.tacs else ["IMPOSSIBLE_VALUE"],
is_admin=1 if self.is_admin() else 0,
is_board_member=1 if self.is_board_member() else 0,
),
)
self._viewable_proposals_cache = set(df["Proposal_Code"].tolist())
return self._viewable_proposals_cache
def may_edit_proposal(self, proposal_code):
"""
Check whether the user may edit a given proposal.
Parameters
----------
proposal_code : str
The proposal code.
Returns
-------
bool
Whether the user may edit the proposal.
"""
return (
self.is_principal_investigator(proposal_code)
or self.is_principal_contact(proposal_code)
or self.is_admin()
)
def may_view_block(self, block_id):
"""
Check whether the user may view a given block.
Parameters
----------
block_id : int
The block id.
Returns
-------
bool
Whether the user may view the block.
Raises
------
ValueError
If there exists no block with the given block id.
"""
proposal_code = self._proposal_code_of_block(block_id=block_id)
return self.may_view_proposal(proposal_code=proposal_code)
def may_edit_block(self, block_id):
"""
Check whether the user may edit a given block.
Parameters
----------
block_id : int
The block id.
Returns
-------
bool
Whether the user may edit the block.
Raises
------
ValueError
If there exists no block with the given block id.
"""
proposal_code = self._proposal_code_of_block(block_id=block_id)
return self.may_edit_proposal(proposal_code=proposal_code)
def _proposal_code_of_block(self, block_id):
"""
Get the proposal code of the proposal containing a given block.
Parameters
----------
block_id : int
The block id.
Returns
-------
str
The proposal code.
Raises
------
ValueError
If there exists no block with the given block id.
"""
sql = """
SELECT Proposal_Code
FROM ProposalCode AS pc
JOIN Block AS b ON pc.ProposalCode_Id = b.ProposalCode_Id
WHERE Block_Id=%(block_id)s
"""
df = self._query(sql, params=dict(block_id=block_id))
# sanity check: does the block exist?
if len(df) == 0:
raise ValueError(
"There exists no block with id {block_id}".format(block_id=block_id)
)
return df["Proposal_Code"][0]
def _query(self, sql, params):
"""
Query the database.
Depending on how they are referenced in the SQL query, the query parameters must
be passed as an iterable or as a dict.
Parameters
----------
sql : str
The SQL query.
params : iterable or dict
The query parameters.
Returns
-------
DataFrame
A pandas data frame with the query results.
"""
return pd.read_sql(sql, con=self._db_connectable, params=params)
@staticmethod
def _find_user_id(username, db_connectable):
"""
Find the user id corresponding to a username.
Parameters
----------
username : str
The username.
db_connectable : SQLAlchemy connectable(engine/connection) or database string
URI
A connection to the database to use, or its URI.
Returns
-------
int
The user id.
Raises
------
ValueError
If the username does not exist.
"""
sql = """
SELECT PiptUser_Id FROM PiptUser WHERE Username=%(username)s
"""
df = pd.read_sql(sql, con=db_connectable, params=dict(username=username))
# sanity check: does the user exist?
if len(df) == 0:
raise ValueError(
"The username does not exist: {username}".format(username=username)
)
return df["PiptUser_Id"][0].item()
def _proposal_partners(self, proposal_code):
"""
Find the partners who are represented among a proposal's investigators.
Parameters
----------
proposal_code : str
The proposal code.
Returns
-------
list of str
The list of partner codes.
"""
sql = """
SELECT DISTINCT Partner_Code
FROM Partner AS p
JOIN Institute AS ins ON p.Partner_Id = ins.Partner_Id
JOIN Investigator AS i ON ins.Institute_Id = i.Institute_Id
JOIN ProposalInvestigator pi on i.Investigator_Id = pi.Investigator_Id
JOIN ProposalCode AS pc ON pi.ProposalCode_Id = pc.ProposalCode_Id
WHERE Proposal_Code=%(proposal_code)s
"""
df = self._query(sql, params=dict(proposal_code=proposal_code))
return df["Partner_Code"].tolist()
def _find_tac_member_partners(self):
"""
Find the partners of whose TACs the user is a member.
Returns
-------
list of str
The partner codes.
"""
sql = """
SELECT Partner_Code
FROM PiptUserTAC AS putac
JOIN Partner AS p ON putac.Partner_Id = p.Partner_Id
WHERE PiptUser_Id=%(user_id)s
"""
df = self._query(sql, params=dict(user_id=self._user_id))
return [pc for pc in df["Partner_Code"].tolist()]
def _find_tac_chair_partners(self):
"""
Find the partners of whose TACs the user is chair.
Returns
-------
list of str
The partner codes.
"""
sql = """
SELECT Partner_Code
FROM PiptUserTAC AS putac
JOIN Partner AS p ON putac.Partner_Id = p.Partner_Id
WHERE PiptUser_Id=%(user_id)s AND Chair=1
"""
df = self._query(sql, params=dict(user_id=self._user_id))
return [pc for pc in df["Partner_Code"].tolist()]
| 26.23607 | 88 | 0.565137 |
34b4b03703e9316af4fe90aded64acd1dff18b1d | 40,714 | py | Python | mmtbx/validation/molprobity/__init__.py | rimmartin/cctbx_project | 644090f9432d9afc22cfb542fc3ab78ca8e15e5d | [
"BSD-3-Clause-LBNL"
] | null | null | null | mmtbx/validation/molprobity/__init__.py | rimmartin/cctbx_project | 644090f9432d9afc22cfb542fc3ab78ca8e15e5d | [
"BSD-3-Clause-LBNL"
] | null | null | null | mmtbx/validation/molprobity/__init__.py | rimmartin/cctbx_project | 644090f9432d9afc22cfb542fc3ab78ca8e15e5d | [
"BSD-3-Clause-LBNL"
] | null | null | null |
"""
Classes for MolProbity validation, combining all other analyses in
mmtbx.validation, which use the same APIs for storing and displaying results.
"""
# TODO combine with some parts of mmtbx.kinemage.validation
from __future__ import division, print_function
from iotbx.cli_parser import CCTBXParser
from libtbx.program_template import ProgramTemplate
from mmtbx.rotamer import rotamer_eval
from mmtbx.validation import validation, residue
from mmtbx.validation import model_properties
from mmtbx.validation import experimental
from mmtbx.validation import rna_validate
from mmtbx.validation import clashscore
from mmtbx.validation import restraints
from mmtbx.validation import ramalyze
from mmtbx.validation import omegalyze
from mmtbx.validation import rotalyze
from mmtbx.validation import cbetadev
from mmtbx.validation import waters
from mmtbx.validation import sequence
from libtbx.str_utils import make_header, make_sub_header, format_value
from libtbx import slots_getstate_setstate, \
slots_getstate_setstate_default_initializer
from libtbx.utils import multi_out, null_out, show_times, to_str, Sorry
import iotbx.pdb
import libtbx.load_env
import libtbx.phil
import mmtbx.model
import os.path
import sys
master_phil_str = """
clashscore = True
.type = bool
ramalyze = True
.type = bool
omegalyze = True
.type = bool
rotalyze = True
.type = bool
cbetadev = True
.type = bool
nqh = True
.type = bool
rna = True
.type = bool
model_stats = True
.type = bool
restraints = True
.type = bool
rfactors = True
.type = bool
real_space = True
.type = bool
waters = True
.type = bool
seq = True
.type = bool
xtriage = False
.type = bool
"""
def molprobity_flags():
"""
Default flags for analyses to perform (all True).
"""
return libtbx.phil.parse(master_phil_str).extract()
class molprobity(slots_getstate_setstate):
"""
Comprehensive validation. At a minimum this performs the standard MolProbity
analyses (ramalyze, rotalyze, cbetadev, clashscore). If a geometry
restraints manager is available, the deviations from standard covalent
geometry will also be displayed. Passing an fmodel object enables the
re-calculation of R-factors and real-space correlation.
:param model: model object (required)
:param fmodel: mmtbx.f_model.manager object, after bulk solvent/scaling
:param fmodel_neutron: separate Fmodel manager for neutron data (used in
phenix.refine for join X/N refinement)
:param sequences: parsed sequence objects (from iotbx.bioinformatics)
:param flags: object containing boolean flags for analyses to perform
:param header_info: extracted statistics from PDB file header
:param raw_data: input data before French-Wilson treatment, etc.
:param unmerged_data: separate unmerged intensities for merging statistics
:param all_chain_proxies: object containing restraints information and \
advanced selections from mmtbx.monomer_library.pdb_interpretation
:param keep_hydrogens: don't discard and replace existing hydrogens for \
clashscore calculation
:param nuclear: use nuclear hydrogen distances (for neutron experiments)
:param save_probe_unformatted_file: file name for Probe output suitable for \
display in Coot
:param show_hydrogen_outliers: show geometry outliers for hydrogen atoms
:param min_cc_two_fofc: Fo-Fc map cutoff for real-space outliers
:param n_bins_data: Number of resolution bins for data statistics
:param count_anomalous_pairs_separately: count F+ and F- as separate \
reflections (default=False)
:param outliers_only: only display validation outliers
:param use_pdb_header_resolution_cutoffs: use resolution cutoff(s) \
specified in PDB header for data statistics
"""
# XXX this is used to distinguish objects of this type from an older (and
# now obsolete) class in the phenix tree.
molprobity_version_number = (4,1)
__slots__ = [
"ramalyze",
"omegalyze",
"rotalyze",
"cbetadev",
"clashes",
"nqh_flips",
"rna",
"restraints",
"missing_atoms",
"data_stats",
"neutron_stats",
"real_space",
"pdb_hierarchy",
"crystal_symmetry",
"model_stats",
"waters",
"header_info",
"merging",
"sequence",
"xtriage",
"_multi_criterion",
"file_name",
"kinemage_file",
"model_statistics_geometry",
"model_statistics_geometry_result",
"polygon_stats",
"wilson_b",
"hydrogens",
"model"
]
# backwards compatibility with saved results
def __setstate__(self, state):
for name,value in state.items(): setattr(self, name, value)
for name in self.__slots__ :
if not hasattr(self, name) : setattr(self, name, None)
def __init__(self,
model,
pdb_hierarchy=None, # keep for mmtbx.validation_summary (multiple models)
fmodel=None,
fmodel_neutron=None,
sequences=None,
flags=None,
header_info=None,
raw_data=None,
unmerged_data=None,
keep_hydrogens=True,
nuclear=False,
save_probe_unformatted_file=None,
show_hydrogen_outliers=False,
min_cc_two_fofc=0.8,
n_bins_data=10,
count_anomalous_pairs_separately=False,
use_internal_variance=True,
outliers_only=True,
use_pdb_header_resolution_cutoffs=False,
file_name=None,
ligand_selection=None,
rotamer_library="8000",
map_params=None):
assert rotamer_library == "8000", "data_version given to RotamerEval not recognized."
for name in self.__slots__ :
setattr(self, name, None)
# use objects from model
self.model = model
if (self.model is not None):
pdb_hierarchy = self.model.get_hierarchy()
xray_structure = self.model.get_xray_structure()
geometry_restraints_manager = self.model.get_restraints_manager().geometry
crystal_symmetry = self.model.crystal_symmetry()
all_chain_proxies = self.model.all_chain_proxies
else:
assert (pdb_hierarchy is not None)
xray_structure = None
geometry_restraints_manager = None
crystal_symmetry = None
all_chain_proxies = None
# very important - the i_seq attributes may be extracted later
pdb_hierarchy.atoms().reset_i_seq()
self.pdb_hierarchy = pdb_hierarchy
if (xray_structure is None):
if (fmodel is not None):
xray_structure = fmodel.xray_structure
elif (crystal_symmetry is not None):
xray_structure = pdb_hierarchy.extract_xray_structure(
crystal_symmetry=crystal_symmetry)
self.crystal_symmetry = crystal_symmetry
if (crystal_symmetry is None) and (fmodel is not None):
self.crystal_symmetry = fmodel.f_obs().crystal_symmetry()
# use maps (fmodel is not used)
# run earlier since pdb_hierarchy gets modified
use_maps = False
if (map_params is not None):
use_maps = ( (map_params.input.maps.map_file_name) or
( (map_params.input.maps.map_coefficients_file_name) and
(map_params.input.maps.map_coefficients_label) ) )
if (use_maps):
if (flags.real_space):
self.real_space = experimental.real_space(
fmodel=None,
model=self.model,
cc_min=min_cc_two_fofc,
molprobity_map_params=map_params.input.maps)
if (flags.waters):
self.waters = waters.waters(
pdb_hierarchy=pdb_hierarchy,
xray_structure=xray_structure,
fmodel=None,
collect_all=True,
molprobity_map_params=map_params.input.maps)
self.header_info = header_info
if (flags is None):
flags = molprobity_flags()
import mmtbx.model.statistics
self.model_statistics_geometry = mmtbx.model.statistics.geometry(
pdb_hierarchy = pdb_hierarchy,
geometry_restraints_manager = geometry_restraints_manager,
use_hydrogens = keep_hydrogens,
use_nuclear = nuclear)
self.model_statistics_geometry_result = \
self.model_statistics_geometry.result()
self.ramalyze = self.model_statistics_geometry_result.ramachandran.ramalyze
self.omegalyze = self.model_statistics_geometry_result.omega.omegalyze
self.rotalyze = self.model_statistics_geometry_result.rotamer.rotalyze
self.cbetadev = self.model_statistics_geometry_result.c_beta.cbetadev
self.clashes = self.model_statistics_geometry_result.clash.clashes
if pdb_hierarchy.contains_protein():
self.find_missing_atoms(out=null_out())
if (flags.nqh):
self.nqh_flips = clashscore.nqh_flips(
pdb_hierarchy=pdb_hierarchy)
if (pdb_hierarchy.contains_rna() and flags.rna and
libtbx.env.has_module(name="suitename")):
if (geometry_restraints_manager is not None):
self.rna = rna_validate.rna_validation(
pdb_hierarchy=pdb_hierarchy,
geometry_restraints_manager=geometry_restraints_manager,
outliers_only=outliers_only,
params=None)
if (flags.model_stats) and (xray_structure is not None):
self.model_stats = model_properties.model_statistics(
pdb_hierarchy=pdb_hierarchy,
xray_structure=xray_structure,
all_chain_proxies=all_chain_proxies,
ignore_hd=(not nuclear),
ligand_selection=ligand_selection)
if (geometry_restraints_manager is not None) and (flags.restraints):
assert (xray_structure is not None)
self.restraints = restraints.combined(
pdb_hierarchy=pdb_hierarchy,
xray_structure=xray_structure,
geometry_restraints_manager=geometry_restraints_manager,
ignore_hd=(not nuclear),
cdl=getattr(all_chain_proxies, "use_cdl", None))
if (sequences is not None) and (flags.seq):
self.sequence = sequence.validation(
pdb_hierarchy=pdb_hierarchy,
sequences=sequences,
log=null_out(),
include_secondary_structure=True,
extract_coordinates=True)
if (fmodel is not None):
if (use_pdb_header_resolution_cutoffs) and (header_info is not None):
fmodel = fmodel.resolution_filter(
d_min=header_info.d_min,
d_max=header_info.d_max)
if (flags.rfactors):
self.data_stats = experimental.data_statistics(fmodel,
raw_data=raw_data,
n_bins=n_bins_data,
count_anomalous_pairs_separately=count_anomalous_pairs_separately)
if (not use_maps): # if maps are used, keep previous results
if (flags.real_space):
self.real_space = experimental.real_space(
model=model,
fmodel=fmodel,
cc_min=min_cc_two_fofc)
if (flags.waters):
self.waters = waters.waters(
pdb_hierarchy=pdb_hierarchy,
xray_structure=xray_structure,
fmodel=fmodel,
collect_all=True)
if (unmerged_data is not None):
self.merging = experimental.merging_and_model_statistics(
f_obs=fmodel.f_obs(),
f_model=fmodel.f_model(),
r_free_flags=fmodel.r_free_flags(),
unmerged_i_obs=unmerged_data,
anomalous=count_anomalous_pairs_separately,
use_internal_variance=use_internal_variance,
n_bins=n_bins_data)
if (flags.xtriage):
import mmtbx.scaling.xtriage
f_model = abs(fmodel.f_model()).set_observation_type_xray_amplitude()
if (raw_data is not None):
f_model, obs = f_model.common_sets(other=raw_data)
else :
obs = fmodel.f_obs()
self.xtriage = mmtbx.scaling.xtriage.xtriage_analyses(
miller_obs=obs,
miller_calc=f_model,
unmerged_obs=unmerged_data, # XXX some redundancy here...
text_out=null_out())
if (fmodel_neutron is not None) and (flags.rfactors):
self.neutron_stats = experimental.data_statistics(fmodel_neutron,
n_bins=n_bins_data,
count_anomalous_pairs_separately=False)
if (pdb_hierarchy.models_size() == 1):
self._multi_criterion = multi_criterion_view(pdb_hierarchy)
# wilson B
self.wilson_b = None
if (fmodel is not None):
self.wilson_b = fmodel.wilson_b()
elif (fmodel_neutron is not None):
self.wilson_b = fmodel_neutron.wilson_b()
# validate hydrogens
self.hydrogens = None
if self.model is not None and self.model.has_hd():
# import here to avoid circular import issues
from mmtbx.hydrogens.validate_H import validate_H, validate_H_results
hydrogens = validate_H(model, nuclear)
hydrogens.validate_inputs()
hydrogens.run()
self.hydrogens = validate_H_results(hydrogens.get_results())
# write probe file if needed (CLI and GUI)
if (save_probe_unformatted_file is not None):
pcm = self.clashes.probe_clashscore_manager
try:
with open(save_probe_unformatted_file, 'w') as f:
f.write(pcm.probe_unformatted)
self.clashes.probe_file = save_probe_unformatted_file
except IOError as err:
raise Sorry('%s could not be written correctly.\n%s' %
(save_probe_unformatted_file, err))
def show(self, out=sys.stdout, outliers_only=True, suppress_summary=False,
show_percentiles=False):
"""
Comprehensive output with individual outlier lists, plus summary.
"""
if (self.xtriage is not None):
self.xtriage.summarize_issues().show(out=out)
if (self.data_stats is not None):
make_header("Experimental data", out=out)
self.data_stats.show(out=out, prefix=" ")
if (self.real_space is not None):
make_sub_header("Residues with poor real-space CC", out=out)
self.real_space.show(out=out, prefix=" ")
if (self.waters is not None):
make_sub_header("Suspicious water molecules", out=out)
self.waters.show(out=out, prefix=" ")
if (self.model_stats is not None):
make_header("Model properties", out=out)
self.model_stats.show(prefix=" ", out=out)
if (self.sequence is not None):
make_header("Sequence validation", out=out)
self.sequence.show(out=out)
if (self.restraints is not None):
make_header("Geometry restraints", out=out)
self.restraints.show(out=out, prefix=" ")
if (self.hydrogens is not None):
make_header("Hydrogen validation", out=out)
self.hydrogens.print_results(prefix=' ', log=out)
make_header("Molprobity validation", out=out)
self.model_statistics_geometry.show(log=out, prefix=" ", uppercase=False)
if (self.nqh_flips is not None):
make_sub_header("Asn/Gln/His flips", out=out)
self.nqh_flips.show(out=out, prefix=" ")
if (self.rna is not None):
make_header("RNA validation", out=out)
self.rna.show(out=out, prefix=" ", outliers_only=outliers_only)
if (not suppress_summary):
make_header("Summary", out=out)
self.show_summary(out=out, prefix=" ",
show_percentiles=show_percentiles)
return self
def summarize(self):
"""
Condense results into a compact object - for compatibility with
(now obsolete) mmtbx.validation_summary, and use in high-throughput
analyses
"""
r_work, r_free, d_min = [None,]*3
if(self.data_stats is not None):
r_work, r_free = self.data_stats.r_work, self.data_stats.r_free
d_min = self.data_stats.d_min
elif (self.header_info is not None):
r_work, r_free = self.header_info.r_work, self.header_info.r_free
d_min = self.header_info.d_min
if(self.restraints is None):
rms_bonds = self.header_info.rms_bonds
rms_angles = self.header_info.rms_angles
return summary(
rama_outliers = self.rama_outliers(),
rama_favored = self.rama_favored(),
rotamer_outliers = self.rota_outliers(),
c_beta_deviations = self.cbeta_outliers(),
clashscore = self.clashscore(),
bond_rmsd = self.rms_bonds(),
angle_rmsd = self.rms_angles(),
mpscore = self.molprobity_score(),
d_min = d_min,
r_work = r_work,
r_free = r_free,
program = getattr(self.header_info, "refinement_program", None))
def show_summary(self, *args, **kwds):
"""
Print summary of outliers or scores for each analysis.
"""
return self.summarize().show(*args, **kwds)
def find_missing_atoms(self, out=None):
'''
Function for finding missing protein atoms
Derived from run_find_missing function in phenix/validation/__init__.py
'''
if out is None :
out = sys.stdout
self.missing_atoms = []
# make_header("Finding missing atoms", out=out)
try :
missing_list = rotamer_eval.eval_sidechain_completeness(
pdb_hierarchy=self.pdb_hierarchy,
ignore_hydrogens=True,
report_whole_res=True,
return_ca_pos=True)
except Exception as e :
print(to_str(e), file=out)
else :
for (res_info, missing_atoms, xyz) in missing_list :
if len(missing_atoms) == 0 :
continue
chain_id = res_info[0:2].strip()
try :
resseq = int(res_info[2:6])
except ValueError : # FIXME use hybrid36?
print(" warning: indecipherable residue number '%s'" % \
res_info[2:6], file=out)
print(res_info)
continue
alt = res_info[-4]
resname = res_info[-3:]
# self.get_residue_info((chain_id, resseq, resname, alt), "missing")
self.missing_atoms.append((chain_id, "%s %s" % (resname, str(resseq)),
alt, ", ".join(missing_atoms),
"chain '%s' and resseq %s" % (chain_id, str(resseq)), xyz))
def r_work(self, outer_shell=False):
if (outer_shell):
return getattr(self.data_stats, "r_work_outer", None)
else :
return getattr(self.data_stats, "r_work",
getattr(self.header_info, "r_work", None))
def r_free(self, outer_shell=False):
if (outer_shell):
return getattr(self.data_stats, "r_free_outer", None)
else :
return getattr(self.data_stats, "r_free",
getattr(self.header_info, "r_free", None))
def d_min(self):
if (self.data_stats is not None):
return self.data_stats.d_min
elif (self.header_info is not None):
return self.header_info.d_min
def d_max_min(self, outer_shell=False):
if (self.data_stats is not None):
if (outer_shell):
return self.data_stats.d_max_outer, self.data_stats.d_min_outer
else :
return self.data_stats.d_max, self.data_stats.d_min
def rms_bonds(self):
return self.model_statistics_geometry_result.bond.mean
def rms_angles(self):
return self.model_statistics_geometry_result.angle.mean
def rama_favored(self):
return self.model_statistics_geometry_result.ramachandran.favored
def rama_outliers(self):
return self.model_statistics_geometry_result.ramachandran.outliers
def rama_allowed(self):
return self.model_statistics_geometry_result.ramachandran.allowed
def rota_outliers(self):
return self.model_statistics_geometry_result.rotamer.outliers
def cbeta_outliers(self):
return self.model_statistics_geometry_result.c_beta.cbetadev.get_outlier_count()
def clashscore(self):
return self.model_statistics_geometry_result.clash.score
def molprobity_score(self):
return self.model_statistics_geometry_result.molprobity_score
def b_iso_mean(self):
overall_stats = getattr(self.model_stats, "all", None)
return getattr(overall_stats, "b_mean", None)
def space_group(self):
return getattr(self.crystal_symmetry, "space_group", lambda: None)()
def space_group_info(self):
return getattr(self.crystal_symmetry, "space_group_info", lambda: None)()
def unit_cell(self):
return getattr(self.crystal_symmetry, "unit_cell", lambda: None)()
def twin_law(self):
return getattr(self.data_stats, "twin_law", None)
def fmodel_statistics_by_resolution(self):
"""
Returns the resolution bins containing F(model) statistics; see
mmtbx.f_model.f_model_info for details.
"""
fmodel_info = getattr(self.data_stats, "info", None)
return getattr(fmodel_info, "bins", None)
def fmodel_statistics_graph_data(self):
"""
Wrapper for fmodel_statistics_by_resolution(), returns object suitable for
routines in wxtbx.plots.
"""
bins = self.fmodel_statistics_by_resolution()
if (bins is not None):
from mmtbx.f_model.f_model_info import export_bins_table_data
return export_bins_table_data(bins)
return None
def atoms_to_observations_ratio(self, assume_riding_hydrogens=True):
n_atoms = self.model_stats.n_atoms
if (assume_riding_hydrogens):
n_atoms -= self.model_stats.n_hydrogens
n_refl = self.data_stats.n_refl
assert (n_refl > 0)
return n_atoms / n_refl
def as_mmcif_records(self) : # TODO
raise NotImplementedError()
def as_multi_criterion_view(self):
if (self._multi_criterion is None):
return None
if (not self._multi_criterion.is_populated):
if (self.real_space is not None):
self._multi_criterion.process_outliers(self.real_space.results)
if (self.waters is not None):
self._multi_criterion.process_outliers(self.waters.results)
msr = self.model_statistics_geometry_result
self._multi_criterion.process_outliers(msr.ramachandran.ramalyze.results)
self._multi_criterion.process_outliers(msr.rotamer.rotalyze.results)
self._multi_criterion.process_outliers(msr.c_beta.cbetadev.results)
self._multi_criterion.process_outliers(msr.clash.clashes.results)
return self._multi_criterion
def display_wx_plots(self):
if (self.ramalyze is not None):
self.ramalyze.display_wx_plots()
if (self.rotalyze is not None):
self.rotalyze.display_wx_plots()
mc = self.as_multi_criterion_view()
mc.display_wx_plots()
def write_coot_script(self, file_name):
"""
Write a Python script for displaying outlier lists with click-to-recenter
enabled.
"""
coot_script = libtbx.env.find_in_repositories(
relative_path="cctbx_project/cootbx/validation_lists.py",
test=os.path.isfile)
if (coot_script is None):
raise Sorry("Can't find template Python script for Coot.")
f = open(file_name, "w")
f.write("# script auto-generated by phenix.molprobity\n")
f.write("\n")
f.write(open(coot_script).read())
f.write("\n")
f.write("data = {}\n")
msr = self.model_statistics_geometry_result
f.write("data['rama'] = %s\n" % msr.ramachandran.ramalyze.as_coot_data())
f.write("data['omega'] = %s\n" % msr.omega.omegalyze.as_coot_data())
f.write("data['rota'] = %s\n" % msr.rotamer.rotalyze.as_coot_data())
f.write("data['cbeta'] = %s\n" % msr.c_beta.cbetadev.as_coot_data())
f.write("data['probe'] = %s\n" % msr.clash.clashes.as_coot_data())
if(msr.clash.clashes.probe_file is not None):
f.write("handle_read_draw_probe_dots_unformatted(\"%s\", 0, 0)\n" %
msr.clash.clashes.probe_file)
f.write("show_probe_dots(True, True)\n")
f.write("gui = coot_molprobity_todo_list_gui(data=data)\n")
f.close()
def get_polygon_statistics(self, stat_names):
# missing keys from polygon.keys_to_show:
# r_work_cutoffs, r_free_cutoffs
# completeness_in_range, completeness_d_min_inf, completeness_6A_inf
# solvent_content_via_mask
stats = {}
for name in stat_names :
val = 0.0
if (name == "r_work") : val = self.r_work()
elif (name == "r_free") : val = self.r_free()
elif (name == "adp_mean_all") : val = self.b_iso_mean()
elif (name == "adp_min_all"): val = self.model_stats.all.b_min
elif (name == "adp_max_all"): val = self.model_stats.all.b_max
elif (name == "wilson_b") : val = self.wilson_b
elif (name == "bond_rmsd") : val = self.rms_bonds()
elif (name == "bond_max_deviation"):
val = self.model_statistics_geometry_result.bond.max
elif (name == "angle_rmsd") : val = self.rms_angles()
elif (name == "angle_max_deviation"):
val = self.model_statistics_geometry_result.angle.max
elif (name == "dihedral_rmsd"):
val = self.model_statistics_geometry_result.dihedral.mean
elif (name == "dihedral_max_deviation"):
val = self.model_statistics_geometry_result.dihedral.max
elif (name == "planarity_rmsd"):
val = self.model_statistics_geometry_result.planarity.mean
elif (name == "planarity_max_deviation"):
val = self.model_statistics_geometry_result.planarity.max
elif (name == "chirality_rmsd"):
val = self.model_statistics_geometry_result.chirality.mean
elif (name == "chirality_max_deviation"):
val = self.model_statistics_geometry_result.chirality.max
elif (name == "rama_favored") : val = self.rama_favored()
elif (name == "rama_allowed") : val = self.rama_allowed()
elif (name == "rama_outliers") : val = self.rama_outliers()
elif (name == "rotamer_outliers") : val = self.rota_outliers()
elif (name == "clashscore") : val = self.clashscore()
stats[name] = val
return stats
def get_statistics_for_phenix_gui(self):
mp = self
stats = [
("R-work", format_value("%.4f", mp.r_work())),
("R-free", format_value("%.4f", mp.r_free())),
("RMS(bonds)", format_value("%.3f", mp.rms_bonds())),
("RMS(angles)", format_value("%.4f", mp.rms_angles())),
("Clashscore", format_value("%.2f", mp.clashscore())),
("MolProbity score", format_value("%.3f", mp.molprobity_score())),
]
if (self.neutron_stats is not None):
stats.extend([
("R-work (neutron)", format_value("%.4f", self.neutron_stats.r_work)),
("R-free (neutron)", format_value("%.4f", self.neutron_stats.r_free)),
])
return stats
class summary(slots_getstate_setstate_default_initializer):
"""
Simplified container for overall statistics; replaces class of the same
name in mmtbx.command_line.validation_summary. The more complete molprobity
class is prefered when analyzing a single structure, but it is considerably
larger.
"""
__slots__ = [
"rama_outliers",
"rama_favored",
"rotamer_outliers",
"c_beta_deviations",
"clashscore",
"bond_rmsd",
"angle_rmsd",
"mpscore",
"d_min",
"r_work",
"r_free",
"program",
]
labels = [
"Ramachandran outliers",
" favored",
"Rotamer outliers",
"C-beta deviations",
"Clashscore",
"RMS(bonds)",
"RMS(angles)",
"MolProbity score",
"Resolution",
"R-work",
"R-free",
"Refinement program",
]
formats = [
"%6.2f", "%6.2f", "%6.2f", "%5d", "%6.2f", "%8.4f", "%6.2f", "%6.2f",
"%6.2f", "%8.4f", "%8.4f", "%s",
]
def show(self, out=sys.stdout, prefix=" ", show_percentiles=False):
def fs(format, value):
return format_value(format, value, replace_none_with=("(none)"))
maxlen = max([ len(label) for label in self.labels ])
percentiles = {}
if (show_percentiles):
perc_attr = ["clashscore", "mpscore", "r_work", "r_free"]
stats = dict([ (name, getattr(self, name)) for name in perc_attr ])
from mmtbx.polygon import get_statistics_percentiles
percentiles = get_statistics_percentiles(self.d_min, stats)
for k, name in enumerate(self.__slots__):
format = "%%s%%-%ds = %%s" % maxlen
if (k < 3):
format += " %%"
percentile_info = ""
if (show_percentiles):
percentile = percentiles.get(name, None)
if (percentile is not None):
format += " (percentile: %s)"
percentile_info = "%.1f" % percentile
else :
format += "%s"
else :
format += "%s"
value = getattr(self, name)
if (value is not None):
print(format % (prefix, self.labels[k], fs(self.formats[k],
value), percentile_info), file=out)
return self
def iter_molprobity_gui_fields(self):
stats = [
("Ramachandran outliers","%6.2f%%",self.rama_outliers,0.5,0.2,"< 0.2%"),
("Ramachandran favored", "%6.2f%%",self.rama_favored,95,98,"> 98%"),
("Rotamer outliers", "%6.2f%%", self.rotamer_outliers, 2, 1, "1%"),
("C-beta outliers", "%3d ", self.c_beta_deviations, 2, 0, "0"),
("Clashscore", "%6.2f", self.clashscore, 40, 20, None),
("Overall score", "%6.2f", self.mpscore, None, None, None),
]
for stat_info in stats :
yield stat_info
########################################################################
class pdb_header_info(slots_getstate_setstate):
"""
Container for information extracted from the PDB header (if available).
"""
__slots__ = ["d_min", "d_max", "r_work", "r_free", "rms_bonds", "rms_angles",
"refinement_program", "n_tls_groups"]
def __init__(self, pdb_file, pdb_hierarchy=None):
for name in self.__slots__ :
setattr(self, name, None)
if (pdb_file is not None):
import iotbx.pdb.hierarchy
from iotbx.pdb import extract_rfactors_resolutions_sigma
pdb_in = iotbx.pdb.hierarchy.input(file_name=pdb_file)
published_results = extract_rfactors_resolutions_sigma.extract(
file_lines=pdb_in.input.remark_section(), file_name=None)
if (published_results is not None):
self.r_work = published_results.r_work
self.r_free = published_results.r_free
self.d_min = published_results.high
self.d_max = published_results.low
self.refinement_program = pdb_in.input.get_program_name()
# XXX phenix.refine hack, won't work for other programs
lines = open(pdb_file).readlines()
for line in lines :
if (line.startswith("REMARK Final:")):
fields = line.strip().split()
self.rms_bonds = float(fields[-4])
self.rms_angles = float(fields[-1])
break
if (pdb_hierarchy is not None):
tls_groups = pdb_in.input.extract_tls_params(pdb_hierarchy).tls_params
if (tls_groups is not None):
self.n_tls_groups = len(tls_groups)
def is_phenix_refinement(self):
return (self.refinement_program is not None and
"phenix" in self.refinement_program.lower())
def show(self, out=sys.stdout, prefix="", include_r_factors=True,
include_rms_geom=True):
if (self.refinement_program is not None):
print("%sRefinement program = %s" % (prefix,
self.refinement_program), file=out)
if (include_r_factors):
if (self.d_min is not None):
print("%sHigh resolution = %6.2f" % (prefix, self.d_min), file=out)
if (self.r_work is not None):
print("%sR-work = %8.4f" % (prefix, self.r_work), file=out)
if (self.r_free is not None):
print("%sR-free = %8.4f" % (prefix, self.r_free), file=out)
if (include_rms_geom):
if (self.rms_bonds is not None):
print("%sRMS(bonds) = %8.4f" % (prefix,
self.rms_bonds), file=out)
if (self.rms_angles is not None):
print("%sRMS(angles) = %6.2f" % (prefix,
self.rms_angles), file=out)
class residue_multi_criterion(residue):
"""
Container for multiple outliers associated with a single residue. If data
are used, this may include real-space statistics regardless of whether the
residue is technically an outlier or not.
"""
__slots__ = residue.__slots__ + ["outliers", "n_confs", "i_seq"]
def __init__(self, **kwds):
residue.__init__(self, **kwds)
self.outliers = []
def add_outlier(self, outlier):
if isinstance(outlier, residue):
assert self.is_same_residue_group(outlier)
self.outliers.append(outlier)
def _find_outlier_type(self, outlier_type=None, outlier_types=(),
retrieve_all=False):
assert (outlier_type is not None) or (len(outlier_types) > 0)
for outlier in self.outliers :
if (not outlier.is_outlier()) and (not retrieve_all):
continue
otype = type(outlier).__name__
if (otype == outlier_type) or (otype in outlier_types):
return True
return False
def is_ramachandran_outlier(self):
return self._find_outlier_type("ramachandran")
def is_rotamer_outlier(self):
return self._find_outlier_type("rotamer")
def is_cbeta_outlier(self):
return self._find_outlier_type("cbeta")
def is_clash_outlier(self):
return self._find_outlier_type("clash")
def is_geometry_outlier(self):
return self._find_outlier_type(
outlier_types=["bond","angle","dihedral","chirality","planarity"])
def __str__(self):
outliers = []
if self.is_ramachandran_outlier() : outliers.append("rama")
if self.is_rotamer_outlier() : outliers.append("rota")
if self.is_cbeta_outlier() : outliers.append("cb")
if self.is_clash_outlier() : outliers.append("clash")
if self.is_geometry_outlier() : outliers.append("geo")
if (len(outliers) == 0) : outliers = ["---"]
return "%s %s" % (self.id_str(), ",".join(outliers))
def __hash__(self):
return self.residue_group_id_str().__hash__()
def __cmp__(self, other):
return cmp(self.i_seq, other.i_seq)
def get_real_space_plot_values(self, use_numpy_NaN=True):
for outlier in self.outliers :
if (type(outlier).__name__ == 'residue_real_space'):
values = [ outlier.b_iso, outlier.cc, outlier.two_fofc, outlier.fmodel ]
return values
if (use_numpy_NaN):
import numpy
return [ numpy.NaN ] * 4
else :
return [ None ] * 4
def is_map_outlier(self, cc_min=0.8):
b_iso, cc, two_fofc, fmodel = self.get_real_space_plot_values(False)
if (cc is None):
return None
elif (cc < cc_min):
return True
return False
def get_outlier_plot_values(self, use_numpy_NaN=True):
y = []
if self.is_ramachandran_outlier() : y.append(1)
else : y.append(None)
if self.is_rotamer_outlier() : y.append(1)
else : y.append(None)
if self.is_cbeta_outlier() : y.append(1)
else : y.append(None)
if self.is_clash_outlier() : y.append(1)
else : y.append(None)
if (use_numpy_NaN):
import numpy
y_ = []
for yval in y :
if (yval is None) : y_.append(numpy.NaN)
else : y_.append(yval)
return y_
return y
class multi_criterion_view(slots_getstate_setstate):
"""
Container for generating multi-criterion plots and tables from separate lists
of outliers.
"""
__slots__ = ["residues", "is_populated"]
def __init__(self, pdb_hierarchy, include_all=False):
self.is_populated = False
self.residues = {}
i_seq = 0
for chain in pdb_hierarchy.only_model().chains():
if (not include_all):
if (not chain.is_protein()) and (not chain.is_na()):
continue
for residue_group in chain.residue_groups():
atom_group = residue_group.atom_groups()[0]
resname = atom_group.resname
if (resname == "HOH") : continue
combined = residue_multi_criterion(
chain_id=chain.id,
resseq=residue_group.resseq,
icode=residue_group.icode,
resname=residue_group.atom_groups()[0].resname,
altloc="",
i_seq=i_seq,
n_confs=len(residue_group.atom_groups()))
# set_coordinates_from_hierarchy does not seem to work?
combined.xyz = atom_group.atoms().extract_xyz().mean()
id_str = combined.residue_group_id_str()
self.residues[id_str] = combined
i_seq += 1
def process_outliers(self, outliers, log=sys.stderr):
self.is_populated = True
for outlier in outliers :
if outlier.is_single_residue_object():
if (outlier.resname == "HOH") : continue
id_str = outlier.residue_group_id_str()
if (id_str in self.residues):
self.residues[id_str].add_outlier(outlier)
else :
print("missing residue group '%s'" % id_str, file=log)
else :
have_ids = set([])
for atom in outlier.atoms_info :
id_str = atom.residue_group_id_str()
if (atom.resname == "HOH") or (id_str in have_ids) : continue
if (id_str in self.residues):
self.residues[id_str].add_outlier(outlier)
have_ids.add(id_str)
else :
print("missing residue group '%s'" % id_str, file=log)
def get_residue_group_data(self, residue_group):
residue_validation = self.residues.get(residue_group.id_str(), None)
if (residue_validation is None):
raise RuntimeError("Can't find residue '%s'" % residue_group.id_str())
return residue_validation
def data(self):
return sorted(self.residues.values())
def binned_data(self):
from mmtbx.validation import graphics
return graphics.residue_binner(self.data())
def get_y_limits(self):
import numpy
values = []
for outlier in self.data():
values.append(outlier.get_real_space_plot_values(False))
values = numpy.array(values).transpose()
if (len(values) > 0):
rho_min = min(min(values[2]), min(values[3]))
rho_max = max(max(values[2]), max(values[3]))
return {
"rho" : (rho_min, rho_max),
"b" : (min(values[0]), max(values[0])),
"cc" : (min(values[1]), max(values[1])),
}
else:
raise Sorry('No residues (usually protein or nucleic acid) are available for generating plots.')
def display_wx_plots(self, parent=None):
import wxtbx.plots.molprobity
frame = wxtbx.plots.molprobity.multi_criterion_frame(
parent=parent,
title="MolProbity multi-criterion plot",
validation=self)
frame.Show()
# =============================================================================
# MolProbity ProgramTemplate
class MolProbityTemplate(ProgramTemplate):
def get_results_as_PDB_JSON(self):
return None
# MolProbity CLI Parser
class MolProbityParser(CCTBXParser):
def add_default_options(self):
super(MolProbityParser, self).add_default_options()
# add extra CLI option for PDB JSON
self.add_argument(
'--write-pdb-json', '--write_pdb_json', action='store_true',
help='write output in JSON file for PDB'
)
# MolProbity run_program function
# Since the JSON output comes at the end, there is no easy way to modify the
# default run_program function
# But, this can be the basis for running other MolProbity validation tools
# that can output a JSON file specific for the PDB.
def run_molprobity_program(program_class=None, custom_process_arguments=None,
args=None, logger=None):
'''
Function for running programs using CCTBXParser and the program template
:param program_class: ProgramTemplate type (required)
:param custom_process_arguments:
Custom function to parse unknown arguments (optional)
:param args: list of command-line arguments (optional)
:param logger: logger (e.g. multi_out) for output (optional)
:rtype: whatever is returned from program_class.get_results()
'''
assert (program_class is not None)
if (args is None):
args = sys.argv[1:]
# create logger
if (logger is None):
logger = multi_out()
logger.register('stdout', sys.stdout)
# start timer
t = show_times(out=logger)
# create parser
parser = MolProbityParser(program_class=program_class,
custom_process_arguments=custom_process_arguments,
logger=logger)
namespace = parser.parse_args(args)
# start program
print('Starting job', file=logger)
print('='*79, file=logger)
task = program_class(parser.data_manager, parser.working_phil.extract(),
master_phil=parser.master_phil,
logger=logger)
# custom constructor (optional)
task.custom_init()
# validate inputs
task.validate()
# run program
task.run()
# clean up (optional)
task.clean_up()
# output JSON file for PDB
if (namespace.write_pdb_json):
filename, ext = os.path.splitext(
os.path.basename(parser.data_manager.get_default_model_name()))
filename += '_pdb.json'
json_text = task.get_results_as_PDB_JSON()
print('\nJSON output')
print('-'*79, file=logger)
print(' Writing results in JSON format to %s.' % filename, file=logger)
parser.data_manager._write_text(None, filename, json_text,
overwrite=namespace.overwrite)
# stop timer
print('', file=logger)
print('='*79, file=logger)
print('Job complete', file=logger)
t()
return task.get_results()
| 36.778681 | 102 | 0.672349 |
1000b0fcac70c571fd2bc6661dc6ca29755365af | 1,119 | py | Python | tune_parameters.py | wuga214/NCE_Projected_LRec | 5628c33e66fec2709a7b4741aabeec90f948ae5c | [
"MIT"
] | 30 | 2018-11-06T22:17:05.000Z | 2022-01-31T23:32:10.000Z | tune_parameters.py | wuga214/NCE_Projected_LRec | 5628c33e66fec2709a7b4741aabeec90f948ae5c | [
"MIT"
] | 2 | 2018-12-17T06:07:31.000Z | 2021-01-09T00:17:14.000Z | tune_parameters.py | wuga214/NCE_Projected_LRec | 5628c33e66fec2709a7b4741aabeec90f948ae5c | [
"MIT"
] | 7 | 2018-12-07T05:48:26.000Z | 2021-07-28T13:49:42.000Z | import numpy as np
import argparse
from experiment.tuning import hyper_parameter_tuning
from utils.io import load_numpy, save_dataframe_csv, load_yaml
from utils.modelnames import models
def main(args):
params = load_yaml(args.grid)
params['models'] = {params['models']: models[params['models']]}
R_train = load_numpy(path=args.path, name=args.train)
R_valid = load_numpy(path=args.path, name=args.valid)
hyper_parameter_tuning(R_train, R_valid, params, save_path=args.name, measure=params['similarity'], gpu_on=args.gpu)
if __name__ == "__main__":
# Commandline arguments
parser = argparse.ArgumentParser(description="ParameterTuning")
parser.add_argument('-n', dest='name', default="autorecs_tuning.csv")
parser.add_argument('-d', dest='path', default="datax/")
parser.add_argument('-t', dest='train', default='Rtrain.npz')
parser.add_argument('-v', dest='valid', default='Rvalid.npz')
parser.add_argument('-y', dest='grid', default='config/default.yml')
parser.add_argument('-gpu', dest='gpu', action='store_true')
args = parser.parse_args()
main(args) | 43.038462 | 120 | 0.723861 |
f74ed9c32ce2f3b2bef22c7458ed2566fe9abcdf | 5,048 | py | Python | dashboard/pagination.py | encode/dashboard | a184d749a3a806f8d65574b5712ddce24169c677 | [
"BSD-3-Clause"
] | 92 | 2020-04-09T17:26:33.000Z | 2022-03-21T02:23:59.000Z | dashboard/pagination.py | encode/staradmin | a184d749a3a806f8d65574b5712ddce24169c677 | [
"BSD-3-Clause"
] | 6 | 2020-04-21T14:01:56.000Z | 2021-11-23T14:29:50.000Z | dashboard/pagination.py | encode/staradmin | a184d749a3a806f8d65574b5712ddce24169c677 | [
"BSD-3-Clause"
] | 7 | 2020-04-13T13:59:07.000Z | 2022-03-13T02:18:41.000Z | import typing
from dataclasses import dataclass
from starlette.datastructures import URL, QueryParams
@dataclass
class PageControl:
text: str
url: URL = None
is_active: bool = False
is_disabled: bool = False
def inclusive_range(st: int, en: int, cutoff: int) -> typing.List[int]:
"""
Return an inclusive range from 'st' to 'en',
bounded within a minimum of 1 and a maximum of 'cutoff'.
"""
st = max(st, 1)
en = min(en, cutoff)
return list(range(st, en + 1))
def get_page_number(url: URL) -> int:
"""
Return a page number specified in the URL query parameters.
"""
query_params = QueryParams(url.query)
try:
return int(query_params.get("page", default="1"))
except (TypeError, ValueError):
return 1
def get_page_controls(
url: URL, current_page: int, total_pages: int
) -> typing.List[PageControl]:
"""
Returns a list of pagination controls, using GitHub's style for rendering
which controls should be displayed. See eg. issue pages in GitHub.
Previous [1] 2 3 4 5 ... 14 15 Next
"""
assert total_pages >= 1
assert current_page >= 1
assert current_page <= total_pages
# If we've only got a single page, then don't include pagination controls.
if total_pages == 1:
return []
# We always have 5 contextual page numbers around the current page.
if current_page <= 2:
# If we're on the first or second-to-first page, then our 5 contextual
# pages should start from the first page onwards.
main_block = inclusive_range(1, 5, cutoff=total_pages)
elif current_page >= total_pages - 1:
# If we're on the last or second-to-last page, then our 5 contextual
# pages should end with the final page backwards.
main_block = inclusive_range(total_pages - 4, total_pages, cutoff=total_pages)
else:
# All other cases, our 5 contextual pages should be 2 pages on either
# side of our current page.
main_block = inclusive_range(
current_page - 2, current_page + 2, cutoff=total_pages
)
# We always have 2 contextual page numbers at the start.
start_block = inclusive_range(1, 2, cutoff=total_pages)
if main_block[0] == 4:
# If we've only got a gap of one between the start and main blocks
# then fill in the gap with a page marker.
# | 1 2 3 4 5 [6] 7 8
start_block += [3]
elif main_block[0] > 4:
# If we've got a gap of more that one between the start and main
# blocks then fill in the gap with an ellipsis marker.
# | 1 2 … 5 6 [7] 8 9
start_block += [None]
# We always have 2 contextual page numbers at the end.
end_block = inclusive_range(total_pages - 1, total_pages, cutoff=total_pages)
if main_block[-1] == total_pages - 3:
# If we've got a gap of one between the end and main blocks then
# fill in the gap with an page marker.
# 92 93 [94] 95 96 97 98 99 |
end_block = [total_pages - 2] + end_block
elif main_block[-1] < total_pages - 3:
# If we've got a gap of more that one between the end and main
# blocks then fill in the gap with an ellipsis marker.
# 91 92 [93] 94 95 … 98 99 |
end_block = [None] + end_block
# We've got a list of integer/None values representing which pages to
# display in the controls. Now we use those to generate the actual
# PageControl instances.
seen_numbers = set()
controls = []
# Add a 'Previous' page control.
if current_page == 1:
previous_url = None
previous_disabled = True
elif current_page == 2:
previous_url = url.remove_query_params("page")
previous_disabled = False
else:
previous_url = url.include_query_params(page=current_page - 1)
previous_disabled = False
previous = PageControl(
text="Previous", url=previous_url, is_disabled=previous_disabled
)
controls.append(previous)
for page_number in start_block + main_block + end_block:
if page_number is None:
gap = PageControl(text="…", is_disabled=True)
controls.append(gap)
elif page_number not in seen_numbers:
seen_numbers.add(page_number)
if page_number == 1:
page_url = url.remove_query_params("page")
else:
page_url = url.include_query_params(page=page_number)
page = PageControl(
text=str(page_number),
url=page_url,
is_active=page_number == current_page,
)
controls.append(page)
# Add a 'Next' page control.
if current_page == total_pages:
next_url = None
next_disabled = True
else:
next_url = url.include_query_params(page=current_page + 1)
next_disabled = False
next = PageControl(text="Next", url=next_url, is_disabled=next_disabled)
controls.append(next)
return controls
| 34.813793 | 86 | 0.636094 |
ea148b95f654a211233610ea11c4d24114cec630 | 958 | py | Python | test/test_list_integrations_response.py | Logicworks/opsgenie-python-sdk | 244c4c40ddcc25e70df5ba4425ab8d7c8da59c18 | [
"Apache-2.0"
] | null | null | null | test/test_list_integrations_response.py | Logicworks/opsgenie-python-sdk | 244c4c40ddcc25e70df5ba4425ab8d7c8da59c18 | [
"Apache-2.0"
] | null | null | null | test/test_list_integrations_response.py | Logicworks/opsgenie-python-sdk | 244c4c40ddcc25e70df5ba4425ab8d7c8da59c18 | [
"Apache-2.0"
] | 1 | 2020-11-07T11:27:13.000Z | 2020-11-07T11:27:13.000Z | # coding: utf-8
"""
OpsGenie REST API
OpsGenie OpenAPI Specification # noqa: E501
OpenAPI spec version: 2.0.0
Generated by: https://github.com/swagger-api/swagger-codegen.git
"""
from __future__ import absolute_import
import unittest
import opsgenie_swagger
from opsgenie_swagger.models.list_integrations_response import ListIntegrationsResponse # noqa: E501
from opsgenie_swagger.rest import ApiException
class TestListIntegrationsResponse(unittest.TestCase):
"""ListIntegrationsResponse unit test stubs"""
def setUp(self):
pass
def tearDown(self):
pass
def testListIntegrationsResponse(self):
"""Test ListIntegrationsResponse"""
# FIXME: construct object with mandatory attributes with example values
# model = opsgenie_swagger.models.list_integrations_response.ListIntegrationsResponse() # noqa: E501
pass
if __name__ == '__main__':
unittest.main()
| 23.365854 | 109 | 0.730689 |
be088c2a6648da2fb69c990b45fea7e3bc696d38 | 282 | py | Python | Python/DefangIP.py | lywc20/daily-programming | 78529e535aea5bda409e5a2a009274dca7011e29 | [
"MIT"
] | null | null | null | Python/DefangIP.py | lywc20/daily-programming | 78529e535aea5bda409e5a2a009274dca7011e29 | [
"MIT"
] | null | null | null | Python/DefangIP.py | lywc20/daily-programming | 78529e535aea5bda409e5a2a009274dca7011e29 | [
"MIT"
] | null | null | null | def defangIPaddr(address):
#convert to mutable list
lAddress = list(address)
delim = ''
for i in range(len(lAddress)):
if lAddress[i] == ".":
lAddress[i] = "[.]"
return delim.join(lAddress)
ip = "1.1.1.1.1"
print(defangIPaddr(ip))
| 16.588235 | 34 | 0.556738 |
424a84acc68ad320302adc3d409aa491347d787c | 1,693 | py | Python | hata/ext/slash/client_wrapper_extension.py | Multiface24111/hata | cd28f9ef158e347363669cc8d1d49db0ff41aba0 | [
"0BSD"
] | 173 | 2019-06-14T20:25:00.000Z | 2022-03-21T19:36:10.000Z | hata/ext/slash/client_wrapper_extension.py | Multiface24111/hata | cd28f9ef158e347363669cc8d1d49db0ff41aba0 | [
"0BSD"
] | 52 | 2020-01-03T17:05:14.000Z | 2022-03-31T11:39:50.000Z | hata/ext/slash/client_wrapper_extension.py | Multiface24111/hata | cd28f9ef158e347363669cc8d1d49db0ff41aba0 | [
"0BSD"
] | 47 | 2019-11-09T08:46:45.000Z | 2022-03-31T14:33:34.000Z | __all__ = ()
from ...backend.utils import KeepType
from ...discord.client.utils import ClientWrapper
from ...discord.events.handling_helpers import _EventHandlerManagerRouter
from .application_command import SlasherApplicationCommand
from .slasher import Slasher
def interactions_getter(manager_router):
"""
Gets the slash command processer using `Client.slasher` of an ``_EventHandlerManagerRouter``.
Parameters
----------
manager_router : ``_EventHandlerManagerRouter``
The caller manager router.
Returns
-------
handlers : `list` of ``Slasher`` instances
"""
handlers = []
for client in manager_router.parent.clients:
manager = getattr(client, 'interactions', None)
if manager is None:
continue
handler = manager.parent
if isinstance(handler, Slasher):
handlers.append(handler)
return handlers
def from_class_constructor(klass):
"""
Creates a slash command from the given class.
Raises
------
BaseException
Any exception raised by the respective ``SlasherApplicationCommand`` constructor.
"""
return SlasherApplicationCommand.from_class(klass)
@KeepType(ClientWrapper)
class ClientWrapper:
@property
def interactions(self):
"""
Returns a ``_EventHandlerManagerRouter`` instance, with what slash commands can be added to more clients at the
same time.
Returns
-------
event_handler_manager_router : ``_EventHandlerManagerRouter``
"""
return _EventHandlerManagerRouter(self, interactions_getter, from_class_constructor)
| 26.453125 | 119 | 0.668636 |
be34d11c1611ac231e35cfbdbe5b460d2a618197 | 1,633 | py | Python | grr/client/grr_response_client/client_actions/operating_system.py | dekoder/grr | 27ba38dc0f5ad4f3e0cdbfb146a0a789e3b0d27b | [
"Apache-2.0"
] | 3 | 2018-09-30T01:31:29.000Z | 2019-04-22T11:44:54.000Z | grr/client/grr_response_client/client_actions/operating_system.py | tomchop/grr | 27ba38dc0f5ad4f3e0cdbfb146a0a789e3b0d27b | [
"Apache-2.0"
] | 1 | 2022-03-02T09:58:05.000Z | 2022-03-02T09:58:05.000Z | grr/client/grr_response_client/client_actions/operating_system.py | tomchop/grr | 27ba38dc0f5ad4f3e0cdbfb146a0a789e3b0d27b | [
"Apache-2.0"
] | null | null | null | #!/usr/bin/env python
"""A facade to operating system dependent client actions."""
from __future__ import unicode_literals
import platform
# pylint: disable=g-import-not-at-top
# pylint: disable=g-wrong-blank-lines
# These imports populate the Action registry
if platform.system() == "Linux":
from grr_response_client.client_actions.linux import linux
submodule = linux
elif platform.system() == "Windows":
from grr_response_client.client_actions.windows import windows
submodule = windows
elif platform.system() == "Darwin":
from grr_response_client.client_actions.osx import osx
import grr_response_client.client_actions.osx.local # pylint: disable=unused-import
submodule = osx
# pylint: enable=g-import-not-at-top
# pylint: enable=g-wrong-blank-lines
# pylint: disable=invalid-name
EnumerateInterfaces = submodule.EnumerateInterfaces
EnumerateInterfacesFromClient = submodule.EnumerateInterfacesFromClient
EnumerateFilesystems = submodule.EnumerateFilesystems
EnumerateFilesystemsFromClient = submodule.EnumerateFilesystemsFromClient
if platform.system() == "Linux":
EnumerateUsers = submodule.EnumerateUsers
EnumerateUsersFromClient = submodule.EnumerateUsersFromClient
else:
EnumerateUsers = None
EnumerateUsersFromClient = None
GetInstallDate = submodule.GetInstallDate
if platform.system() == "Darwin":
OSXEnumerateRunningServices = submodule.OSXEnumerateRunningServices
EnumerateRunningServices = submodule.OSXEnumerateRunningServicesFromClient
else:
OSXEnumerateRunningServices = None
EnumerateRunningServices = None
Uninstall = submodule.Uninstall
UpdateAgent = submodule.UpdateAgent
| 34.744681 | 86 | 0.818739 |
1dea2b1ae7abaae13eb07f27e2fd379b8fee2af0 | 784 | py | Python | object_detection/YOLO_V3/models/layers/blocks_module.py | Gaurav14cs17/Computer-Vision | 49054f6984bf3833bf0529da58c4d216bcc6b5bf | [
"MIT"
] | null | null | null | object_detection/YOLO_V3/models/layers/blocks_module.py | Gaurav14cs17/Computer-Vision | 49054f6984bf3833bf0529da58c4d216bcc6b5bf | [
"MIT"
] | null | null | null | object_detection/YOLO_V3/models/layers/blocks_module.py | Gaurav14cs17/Computer-Vision | 49054f6984bf3833bf0529da58c4d216bcc6b5bf | [
"MIT"
] | null | null | null | import torch.nn as nn
from ..layers.conv_module import Convolutional
class Residual_block(nn.Module):
def __init__(self, filters_in=None, filters_out=None, filters_medium=None):
super(Residual_block, self).__init__()
self.__conv1 = Convolutional(filters_in=filters_in, filters_out=filters_medium, kernel_size=1, stride=1,
padding=0, batch_norm="bn", activate="leaky")
self.__conv2 = Convolutional(filters_in=filters_medium, filters_out=filters_out, kernel_size=3, stride=1,
padding=1, batch_norm="bn", activate="leaky")
def forward(self, x):
'''
x - > ( -1 , c , n , m )
'''
r = self.__conv1(x)
r = self.__conv2(r)
return x + r
| 41.263158 | 113 | 0.604592 |
85871e733fe05835e1e9719ccdbdf17cbe1888cd | 10,476 | py | Python | tests/html_quotations_test.py | a-listware/talon | e9f65b3a8097193323829bccaf5233e02463265e | [
"Apache-2.0"
] | null | null | null | tests/html_quotations_test.py | a-listware/talon | e9f65b3a8097193323829bccaf5233e02463265e | [
"Apache-2.0"
] | null | null | null | tests/html_quotations_test.py | a-listware/talon | e9f65b3a8097193323829bccaf5233e02463265e | [
"Apache-2.0"
] | null | null | null | # -*- coding: utf-8 -*-
from __future__ import absolute_import
# noinspection PyUnresolvedReferences
import re
from unittest.mock import Mock, patch
from nose.tools import assert_false, assert_true, eq_, ok_
from tests.fixtures import (OLK_SRC_BODY_SECTION,
REPLY_QUOTATIONS_SHARE_BLOCK,
REPLY_SEPARATED_BY_HR)
from talon import quotations, utils as u
RE_WHITESPACE = re.compile(r"\s")
RE_DOUBLE_WHITESPACE = re.compile(r"\s")
def test_quotation_splitter_inside_blockquote():
msg_body = """Reply
<blockquote>
<div>
On 11-Apr-2011, at 6:54 PM, Bob <bob@example.com> wrote:
</div>
<div>
Test
</div>
</blockquote>"""
eq_("<html><head></head><body>Reply</body></html>",
RE_WHITESPACE.sub('', quotations.extract_from_html(msg_body)))
def test_quotation_splitter_outside_blockquote():
msg_body = """Reply
<div>
On 11-Apr-2011, at 6:54 PM, Bob <bob@example.com> wrote:
</div>
<blockquote>
<div>
Test
</div>
</blockquote>
"""
eq_("<html><head></head><body>Reply</body></html>",
RE_WHITESPACE.sub('', quotations.extract_from_html(msg_body)))
def test_regular_blockquote():
msg_body = """Reply
<blockquote>Regular</blockquote>
<div>
On 11-Apr-2011, at 6:54 PM, Bob <bob@example.com> wrote:
</div>
<blockquote>
<div>
<blockquote>Nested</blockquote>
</div>
</blockquote>
"""
eq_("<html><head></head><body>Reply<blockquote>Regular</blockquote></body></html>",
RE_WHITESPACE.sub('', quotations.extract_from_html(msg_body)))
def test_no_blockquote():
msg_body = """
<html>
<body>
Reply
<div>
On 11-Apr-2011, at 6:54 PM, Bob <bob@example.com> wrote:
</div>
<div>
Test
</div>
</body>
</html>
"""
reply = """
<html>
<head></head>
<body>
Reply
</body></html>"""
eq_(RE_WHITESPACE.sub('', reply),
RE_WHITESPACE.sub('', quotations.extract_from_html(msg_body)))
def test_empty_body():
eq_('', quotations.extract_from_html(''))
def test_validate_output_html():
msg_body = """Reply
<div>
On 11-Apr-2011, at 6:54 PM, Bob <bob@example.com> wrote:
<blockquote>
<div>
Test
</div>
</blockquote>
</div>
<div/>
"""
out = quotations.extract_from_html(msg_body)
ok_('<html>' in out and '</html>' in out,
'Invalid HTML - <html>/</html> tag not present')
ok_('<div/>' not in out,
'Invalid HTML output - <div/> element is not valid')
def test_gmail_quote():
msg_body = """Reply
<div class="gmail_quote">
<div class="gmail_quote">
On 11-Apr-2011, at 6:54 PM, Bob <bob@example.com> wrote:
<div>
Test
</div>
</div>
</div>"""
eq_("<html><head></head><body>Reply</body></html>",
RE_WHITESPACE.sub('', quotations.extract_from_html(msg_body)))
def test_gmail_quote_compact():
msg_body = 'Reply' \
'<div class="gmail_quote">' \
'<div class="gmail_quote">On 11-Apr-2011, at 6:54 PM, Bob <bob@example.com> wrote:' \
'<div>Test</div>' \
'</div>' \
'</div>'
eq_("<html><head></head><body>Reply</body></html>",
RE_WHITESPACE.sub('', quotations.extract_from_html(msg_body)))
def test_gmail_quote_blockquote():
msg_body = """Message
<blockquote class="gmail_quote">
<div class="gmail_default">
My name is William Shakespeare.
<br/>
</div>
</blockquote>"""
eq_(RE_WHITESPACE.sub('', msg_body),
RE_WHITESPACE.sub('', quotations.extract_from_html(msg_body)))
def test_unicode_in_reply():
msg_body = u"""Reply \xa0 \xa0 Text<br>
<div>
<br>
</div>
<blockquote>
Quote
</blockquote>"""
eq_("<html><head></head><body>Reply  Text<br><div><br></div>"
"</body></html>",
RE_WHITESPACE.sub('', quotations.extract_from_html(msg_body)))
def test_blockquote_disclaimer():
msg_body = """
<html>
<body>
<div>
<div>
message
</div>
<blockquote>
Quote
</blockquote>
</div>
<div>
disclaimer
</div>
</body>
</html>
"""
stripped_html = """
<html>
<head></head>
<body>
<div>
<div>
message
</div>
</div>
<div>
disclaimer
</div>
</body>
</html>
"""
eq_(RE_WHITESPACE.sub('', stripped_html),
RE_WHITESPACE.sub('', quotations.extract_from_html(msg_body)))
def test_date_block():
msg_body = """
<div>
message<br>
<div>
<hr>
Date: Fri, 23 Mar 2012 12:35:31 -0600<br>
To: <a href="mailto:bob@example.com">bob@example.com</a><br>
From: <a href="mailto:rob@example.com">rob@example.com</a><br>
Subject: You Have New Mail From Mary!<br><br>
text
</div>
</div>
"""
eq_('<html><head></head><body><div>message<br></div></body></html>',
RE_WHITESPACE.sub('', quotations.extract_from_html(msg_body)))
def test_from_block():
msg_body = """<div>
message<br>
<div>
<hr>
From: <a href="mailto:bob@example.com">bob@example.com</a><br>
Date: Fri, 23 Mar 2012 12:35:31 -0600<br>
To: <a href="mailto:rob@example.com">rob@example.com</a><br>
Subject: You Have New Mail From Mary!<br><br>
text
</div></div>
"""
eq_('<html><head></head><body><div>message<br></div></body></html>',
RE_WHITESPACE.sub('', quotations.extract_from_html(msg_body)))
def test_reply_shares_div_with_from_block():
msg_body = '''
<body>
<div>
Blah<br><br>
<hr>Date: Tue, 22 May 2012 18:29:16 -0600<br>
To: xx@hotmail.ca<br>
From: quickemail@ashleymadison.com<br>
Subject: You Have New Mail From x!<br><br>
</div>
</body>'''
eq_('<html><head></head><body><div>Blah<br><br></div></body></html>',
RE_WHITESPACE.sub('', quotations.extract_from_html(msg_body)))
def test_reply_quotations_share_block():
stripped_html = quotations.extract_from_plain(REPLY_QUOTATIONS_SHARE_BLOCK)
ok_(stripped_html)
ok_('From' not in stripped_html)
def test_OLK_SRC_BODY_SECTION_stripped():
eq_('<html><head></head><body><div>Reply</div></body></html>',
RE_WHITESPACE.sub(
'', quotations.extract_from_html(OLK_SRC_BODY_SECTION)))
def test_reply_separated_by_hr():
eq_('<html><head></head><body><div>Hi<div>there</div></div></body></html>',
RE_WHITESPACE.sub(
'', quotations.extract_from_html(REPLY_SEPARATED_BY_HR)))
def test_from_block_and_quotations_in_separate_divs():
msg_body = '''
Reply
<div>
<hr/>
<div>
<font>
<b>From: bob@example.com</b>
<b>Date: Thu, 24 Mar 2016 08:07:12 -0700</b>
</font>
</div>
<div>
Quoted message
</div>
</div>
'''
eq_('<html><head></head><body>Reply<div><hr></div></body></html>',
RE_WHITESPACE.sub('', quotations.extract_from_html(msg_body)))
def extract_reply_and_check(filename):
import sys
kwargs = {}
if sys.version_info > (3, 0):
kwargs["encoding"] = "utf8"
f = open(filename, **kwargs)
msg_body = f.read()
reply = quotations.extract_from_html(msg_body)
plain_reply = u.html_to_text(reply)
eq_(RE_WHITESPACE.sub('', "Hi. I am fine.\n\nThanks,\nAlex"),
RE_WHITESPACE.sub('', plain_reply))
def test_gmail_reply():
extract_reply_and_check("tests/fixtures/html_replies/gmail.html")
def test_mail_ru_reply():
extract_reply_and_check("tests/fixtures/html_replies/mail_ru.html")
def test_hotmail_reply():
extract_reply_and_check("tests/fixtures/html_replies/hotmail.html")
def test_ms_outlook_2003_reply():
extract_reply_and_check("tests/fixtures/html_replies/ms_outlook_2003.html")
def test_ms_outlook_2007_reply():
extract_reply_and_check("tests/fixtures/html_replies/ms_outlook_2007.html")
def test_ms_outlook_2010_reply():
extract_reply_and_check("tests/fixtures/html_replies/ms_outlook_2010.html")
def test_thunderbird_reply():
extract_reply_and_check("tests/fixtures/html_replies/thunderbird.html")
def test_windows_mail_reply():
extract_reply_and_check("tests/fixtures/html_replies/windows_mail.html")
def test_yandex_ru_reply():
extract_reply_and_check("tests/fixtures/html_replies/yandex_ru.html")
def test_CRLF():
"""CR is not converted to ' '
"""
symbol = ' '
extracted = quotations.extract_from_html('<html>\r\n</html>')
assert_false(symbol in extracted)
eq_('<html></html>', RE_WHITESPACE.sub('', extracted))
msg_body = """My
reply
<blockquote>
<div>
On 11-Apr-2011, at 6:54 PM, Bob <bob@example.com> wrote:
</div>
<div>
Test
</div>
</blockquote>"""
msg_body = msg_body.replace('\n', '\r\n')
extracted = quotations.extract_from_html(msg_body)
assert_false(symbol in extracted)
# Keep new lines otherwise "My reply" becomes one word - "Myreply"
eq_("<html><head></head><body>My\nreply\n</body></html>", extracted)
def test_gmail_forwarded_msg():
msg_body = """<div dir="ltr"><br><div class="gmail_quote">---------- Forwarded message ----------<br>From: <b class="gmail_sendername">Bob</b> <span dir="ltr"><<a href="mailto:bob@example.com">bob@example.com</a>></span><br>Date: Fri, Feb 11, 2010 at 5:59 PM<br>Subject: Bob WFH today<br>To: Mary <<a href="mailto:mary@example.com">mary@example.com</a>><br><br><br><div dir="ltr">eom</div>
</div><br></div>"""
extracted = quotations.extract_from_html(msg_body)
eq_(RE_WHITESPACE.sub('', msg_body), RE_WHITESPACE.sub('', extracted))
def test_readable_html_empty():
msg_body = """
<blockquote>
Reply
<div>
On 11-Apr-2011, at 6:54 PM, Bob <bob@example.com> wrote:
</div>
<div>
Test
</div>
</blockquote>"""
eq_(RE_WHITESPACE.sub('', msg_body),
RE_WHITESPACE.sub('', quotations.extract_from_html(msg_body)))
@patch.object(quotations, 'html_document_fromstring', Mock(return_value=None))
def test_bad_html():
bad_html = "<html></html>"
eq_(bad_html, quotations.extract_from_html(bad_html))
def test_remove_namespaces():
msg_body = """
<html xmlns:o="urn:schemas-microsoft-com:office:office" xmlns="http://www.w3.org/TR/REC-html40">
<body>
<o:p>Dear Sir,</o:p>
<o:p>Thank you for the email.</o:p>
<blockquote>thing</blockquote>
</body>
</html>
"""
rendered = quotations.extract_from_html(msg_body)
assert_true("<p>" in rendered)
assert_true("xmlns" in rendered)
assert_true("<o:p>" not in rendered)
assert_true("<xmlns:o>" not in rendered)
| 23.917808 | 405 | 0.643948 |
66f701627e391a8dd856cd06cb1658959055c464 | 2,952 | py | Python | ros/src/twist_controller/twist_controller.py | Abosobaie/CarND-Capstone-Project | ed26f4586120588b325916f2086420ef583be164 | [
"MIT"
] | null | null | null | ros/src/twist_controller/twist_controller.py | Abosobaie/CarND-Capstone-Project | ed26f4586120588b325916f2086420ef583be164 | [
"MIT"
] | 9 | 2020-01-28T22:18:21.000Z | 2022-03-12T00:05:03.000Z | ros/src/twist_controller/twist_controller.py | Jianshu-Wang/CarND-Capstone-Project | ed26f4586120588b325916f2086420ef583be164 | [
"MIT"
] | null | null | null | import rospy
from yaw_controller import YawController
from pid import PID
from lowpass import LowPassFilter
GAS_DENSITY = 2.858
ONE_MPH = 0.44704
class Controller(object):
def __init__(self,
vehicle_mass,
fuel_capacity,
brake_deadband,
decel_limit,
accel_limit,
wheel_radius,
wheel_base,
steer_ratio,
max_lat_accel,
max_steer_angle):
#Yaw Controller
self.yaw_controller = YawController(wheel_base, steer_ratio, 0.1, max_lat_accel, max_steer_angle)
#PID
kp = 2
ki = 0.0004
kd = 0.1
mn = 0. # Minimum throttle value
mx = 0.2 # Maximum throttle value
self.throttle_controller = PID(kp, ki, kd, mn, max)
#LowPassFilter because velocity coming on messages are noise, so, we need to filter high frequency noise
tau = 0.5
ts = 0.02 #sample time
self.vel_lpf = LowPassFilter(tau,ts)
self.vehicle_mass = vehicle_mass
self.fuel_capacity = fuel_capacity
self.brake_deadband = brake_deadband
self.decel_limit = decel_limit
self.accel_limit = accel_limit
self.wheel_radius = wheel_radius
self.wheel_base = wheel_base
self.steer_ratio = steer_ratio
self.max_lat_accel = max_lat_accel
self.max_steer_angle = max_steer_angle
self.last_vel = 0
self.brake = 0
self.last_time = rospy.get_time()
def control(self, current_vel, dbw_enabled, linear_vel, angular_vel):
# Return throttle, brake, steer
if not dbw_enabled:
self.throttle_controller.reset()
return 0., 0., 0.
current_vel = self.vel_lpf.filt(current_vel)
steering = self.yaw_controller.get_steering(linear_vel, angular_vel , current_vel)
vel_error = linear_vel - current_vel
self.last_vel = current_vel
current_time = rospy.get_time()
sample_time = current_time - self.last_time
self.last_time = current_time
throttle = self.throttle_controller.step(vel_error, sample_time)
brake = 0
if linear_vel == 0. and current_vel < 0.1:
throttle = 0
self.brake = 700 # 700 Nm to hold the car in place if we are stopped at traffic light.
print("Condition1", current_vel, linear_vel)
elif throttle < 0.1 and vel_error < 0:
throttle = 0
decelerator = max(vel_error,self.decel_limit)
self.brake = abs(decelerator) * (self.vehicle_mass + (self.fuel_capacity * GAS_DENSITY))* self.wheel_radius # Torque is in Nm units
print("Condition2", current_vel, linear_vel)
else:
self.brake = 0
print("Condition3", current_vel, linear_vel)
return throttle, self.brake, steering
| 31.741935 | 144 | 0.614499 |
ec6bfc8bc2e6c1a6a670afb35530468e97fd07ef | 10,192 | py | Python | climetlab/readers/netcdf.py | emadehsan/climetlab | 82d3911565179f66ae19d17d96e94fc7456e7725 | [
"Apache-2.0"
] | 182 | 2020-07-24T14:44:32.000Z | 2022-03-31T12:25:28.000Z | climetlab/readers/netcdf.py | emadehsan/climetlab | 82d3911565179f66ae19d17d96e94fc7456e7725 | [
"Apache-2.0"
] | 30 | 2020-07-22T10:29:12.000Z | 2022-03-31T13:55:04.000Z | climetlab/readers/netcdf.py | emadehsan/climetlab | 82d3911565179f66ae19d17d96e94fc7456e7725 | [
"Apache-2.0"
] | 32 | 2020-09-12T14:02:11.000Z | 2022-02-17T08:18:37.000Z | # (C) Copyright 2020 ECMWF.
#
# This software is licensed under the terms of the Apache Licence Version 2.0
# which can be obtained at http://www.apache.org/licenses/LICENSE-2.0.
# In applying this licence, ECMWF does not waive the privileges and immunities
# granted to it by virtue of its status as an intergovernmental organisation
# nor does it submit to any jurisdiction.
#
# The code is copied from skinnywms, and we should combile later
import datetime
from contextlib import closing
from itertools import product
import numpy as np
import xarray as xr
from climetlab.core import Base
from climetlab.utils.bbox import BoundingBox
from climetlab.utils.dates import to_datetime
from . import Reader
def as_datetime(self, time):
return datetime.datetime.strptime(str(time)[:19], "%Y-%m-%dT%H:%M:%S")
def as_level(self, level):
n = float(level)
if int(n) == n:
return int(n)
return n
class Slice:
def __init__(self, name, value, index, is_dimension, is_info):
self.name = name
self.index = index
self.value = value
self.is_dimension = (not is_info,)
self.is_info = is_info
def __repr__(self):
return "[%s:%s=%s]" % (self.name, self.index, self.value)
class TimeSlice(Slice):
pass
class Coordinate:
def __init__(self, variable, info):
self.variable = variable
# We only support 1D coordinate for now
# assert len(variable.dims) == 1
self.is_info = info
self.is_dimension = not info
if variable.values.ndim == 0:
self.values = [self.convert(variable.values)]
else:
self.values = [self.convert(t) for t in variable.values.flatten()]
def make_slice(self, value):
return self.slice_class(
self.variable.name,
value,
self.values.index(value),
self.is_dimension,
self.is_info,
)
def __repr__(self):
return "%s[name=%s,values=%s]" % (
self.__class__.__name__,
self.variable.name,
len(self.values),
)
class TimeCoordinate(Coordinate):
slice_class = TimeSlice
is_dimension = True
convert = as_datetime
class LevelCoordinate(Coordinate):
# This class is just in case we want to specialise
# 'level', othewise, it is the same as OtherCoordinate
slice_class = Slice
is_dimension = False
convert = as_level
class OtherCoordinate(Coordinate):
slice_class = Slice
is_dimension = False
convert = as_level
class DataSet:
def __init__(self, ds):
self._ds = ds
self._bbox = {}
self._cache = {}
@property
def data_vars(self):
return self._ds.data_vars
def __getitem__(self, key):
if key not in self._cache:
self._cache[key] = self._ds[key]
return self._cache[key]
def bbox(self, variable):
data_array = self[variable]
dims = data_array.dims
lat = dims[-2]
lon = dims[-1]
if (lat, lon) not in self._bbox:
dims = data_array.dims
latitude = data_array[lat]
longitude = data_array[lon]
self._bbox[(lat, lon)] = (
np.amax(latitude.data),
np.amin(longitude.data),
np.amin(latitude.data),
np.amax(longitude.data),
)
return self._bbox[(lat, lon)]
class NetCDFField(Base):
def __init__(self, path, ds, variable, slices, non_dim_coords):
data_array = ds[variable]
self.north, self.west, self.south, self.east = ds.bbox(variable)
self.path = path
self.variable = variable
self.slices = slices
self.non_dim_coords = non_dim_coords
self.name = self.variable
self.title = getattr(
data_array,
"long_name",
getattr(data_array, "standard_name", self.variable),
)
self.time = non_dim_coords.get("valid_time", non_dim_coords.get("time"))
# print('====', non_dim_coords)
for s in self.slices:
if isinstance(s, TimeSlice):
self.time = s.value
if s.is_info:
self.title += " (" + s.name + "=" + str(s.value) + ")"
def plot_map(self, backend):
dimensions = dict((s.name, s.index) for s in self.slices)
backend.bounding_box(
north=self.north, south=self.south, west=self.west, east=self.east
)
backend.plot_netcdf(self.path, self.variable, dimensions)
def __repr__(self):
return "NetCDFField[%r,%r]" % (self.variable, self.slices)
def to_bounding_box(self):
return BoundingBox(
north=self.north, south=self.south, east=self.east, west=self.west
)
# class MultiNetcdfReaders(GriddedMultiReaders):
# engine = "netcdf4"
class NetCDFReader(Reader):
open_mfdataset_backend_kwargs = {}
open_mfdataset_engine = None
def __init__(self, source, path):
super().__init__(source, path)
self.fields = None
def _scan(self):
if self.fields is None:
self.fields = self.get_fields()
def __repr__(self):
return "NetCDFReader(%s)" % (self.path,)
def __iter__(self):
self._scan()
return iter(self.fields)
def __len__(self):
self._scan()
return len(self.fields)
def __getitem__(self, n):
self._scan()
return self.fields[n]
def get_fields(self):
with closing(
xr.open_mfdataset(self.path, combine="by_coords", engine="netcdf4")
) as ds: # or nested
return self._get_fields(DataSet(ds))
def _get_fields(self, ds): # noqa C901
# Select only geographical variables
has_lat = False
has_lon = False
fields = []
skip = set()
for name in ds.data_vars:
v = ds[name]
skip.update(getattr(v, "coordinates", "").split(" "))
skip.update(getattr(v, "bounds", "").split(" "))
skip.update(getattr(v, "grid_mapping", "").split(" "))
for name in ds.data_vars:
if name in skip:
continue
v = ds[name]
coordinates = []
# self.log.info('Scanning file: %s var=%s coords=%s', self.path, name, v.coords)
info = [value for value in v.coords if value not in v.dims]
non_dim_coords = {}
for coord in v.coords:
if coord not in v.dims:
non_dim_coords[coord] = ds[coord].values
continue
c = ds[coord]
# self.log.info("COORD %s %s %s %s", coord, type(coord), hasattr(c, 'calendar'), c)
standard_name = getattr(c, "standard_name", None)
axis = getattr(c, "axis", None)
long_name = getattr(c, "long_name", None)
use = False
if (
standard_name in ("longitude", "projection_x_coordinate")
or (long_name == "longitude")
or (axis == "X")
):
has_lon = True
use = True
if (
standard_name in ("latitude", "projection_y_coordinate")
or (long_name == "latitude")
or (axis == "Y")
):
has_lat = True
use = True
# Of course, not every one sets the standard_name
if standard_name in ("time", "forecast_reference_time") or axis == "T":
coordinates.append(TimeCoordinate(c, coord in info))
use = True
# TODO: Support other level types
if standard_name in (
"air_pressure",
"model_level_number",
"altitude",
): # or axis == 'Z':
coordinates.append(LevelCoordinate(c, coord in info))
use = True
if axis in ("X", "Y"):
use = True
if not use:
coordinates.append(OtherCoordinate(c, coord in info))
if not (has_lat and has_lon):
# self.log.info("NetCDFReader: skip %s (Not a 2 field)", name)
continue
for values in product(*[c.values for c in coordinates]):
slices = []
for value, coordinate in zip(values, coordinates):
slices.append(coordinate.make_slice(value))
fields.append(NetCDFField(self.path, ds, name, slices, non_dim_coords))
if not fields:
raise Exception("NetCDFReader no 2D fields found in %s" % (self.path,))
return fields
def to_xarray(self, **kwargs):
return type(self).to_xarray_multi([self.path], **kwargs)
@classmethod
def to_xarray_multi(cls, paths, **kwargs):
import xarray as xr
options = dict()
options.update(kwargs.get("xarray_open_mfdataset_kwargs", {}))
return xr.open_mfdataset(
paths,
**options,
)
def to_metview(self):
from climetlab.metview import mv_read
return mv_read(self.path)
def plot_map(self, *args, **kwargs):
return self.get_fields()[0].plot_map(*args, **kwargs)
# Used by normalisers
def to_datetime(self):
times = self.to_datetime_list()
assert len(times) == 1
return times[0]
def to_datetime_list(self):
# TODO: check if that can be done faster
result = set()
for s in self.get_fields():
result.add(to_datetime(s.time))
return sorted(result)
def to_bounding_box(self):
return BoundingBox.multi_merge([s.to_bounding_box() for s in self.get_fields()])
def reader(source, path, magic=None, deeper_check=False):
if magic is None or magic[:4] in (b"\x89HDF", b"CDF\x01", b"CDF\x02"):
return NetCDFReader(source, path)
| 27.397849 | 99 | 0.562206 |
c5dd915da1718c573bd1489fb012a2465fb7c2c6 | 2,293 | py | Python | tests/test_dwi_run.py | alex-reardon/ANTsPyMM | ecedca733bac15f0200649070fc0412b16f82ed6 | [
"Apache-2.0"
] | null | null | null | tests/test_dwi_run.py | alex-reardon/ANTsPyMM | ecedca733bac15f0200649070fc0412b16f82ed6 | [
"Apache-2.0"
] | null | null | null | tests/test_dwi_run.py | alex-reardon/ANTsPyMM | ecedca733bac15f0200649070fc0412b16f82ed6 | [
"Apache-2.0"
] | 1 | 2021-11-05T18:02:53.000Z | 2021-11-05T18:02:53.000Z | import sys, os
import unittest
os.environ["TF_NUM_INTEROP_THREADS"] = "8"
os.environ["TF_NUM_INTRAOP_THREADS"] = "8"
os.environ["ITK_GLOBAL_DEFAULT_NUMBER_OF_THREADS"] = "8"
import tempfile
import shutil
import tensorflow as tf
import antspymm
import antspyt1w
import antspynet
import ants
testingClass = unittest.TestCase( )
islocal = False
id1 = "I1499279_Anon_20210819142214_5"
id2 = "I1499337_Anon_20210819142214_6"
img1 = ants.image_read( antspymm.get_data( id1, target_extension=".nii.gz") )
img2 = ants.image_read( antspymm.get_data( id2, target_extension=".nii.gz") )
# img1 = ants.image_read( "processed/dwp0sr.nii.gz" )
# img2 = ants.image_read( "processed/dwp1sr.nii.gz" )
b0indices = antspymm.segment_timeseries_by_meanvalue( img1 )['highermeans']
b0indices2 = antspymm.segment_timeseries_by_meanvalue( img1 )['highermeans']
# FIXME: - test that these are the same values
# NOTE: could run SR at this point - will take a long time - example here:
# mdlfn = antspymm.get_data( "brainSR", target_extension=".h5")
# mdl = tf.keras.models.load_model( mdlfn )
# srimg = antspymm.super_res_mcimage( img, mdl, verbose=False )
dwp = antspymm.dewarp_imageset( [img1,img2], iterations=2, padding=6,
target_idx = b0indices,
syn_sampling = 20, syn_metric='mattes',
type_of_transform = 'SyN',
total_sigma = 0.0, random_seed=1,
reg_iterations = [200,50,20] )
if islocal:
print('dewarp done')
ants.image_write( dwp['dewarped'][0], './dewarped0.nii.gz' )
ants.image_write( dwp['dewarped'][1], './dewarped1.nii.gz' )
# FIXME: - add test
# testingClass.assertAlmostEqual(
# float( dwp['dewarpedmean'].mean() ),
# float( 108.2 ), 0, "template mean not close enough")
# now reconstruct DTI
bvec = antspymm.get_data( id1, target_extension=".bvec")
bval = antspymm.get_data( id1, target_extension=".bval")
dd = antspymm.dipy_dti_recon( dwp['dewarped'][0], bval, bvec, vol_idx=b0indices )
# ants.image_write( dd['RGB'], '/tmp/tempsr_rgb.nii.gz' )
bvec = antspymm.get_data( id2, target_extension=".bvec")
bval = antspymm.get_data( id2, target_extension=".bval")
ee = antspymm.dipy_dti_recon( dwp['dewarped'][1], bval, bvec, vol_idx=b0indices )
# ants.image_write( ee['RGB'], '/tmp/temp_rgb2.nii.gz' )
# FIXME: - add test
# sys.exit(os.EX_OK) # code 0, all ok
| 37.590164 | 81 | 0.726995 |
3fd1b0b09d0d48a7daeea19606b2c068b80c1e31 | 3,968 | py | Python | experiments/sarsa_2way-single-intersection.py | huyz-git/sumo-rl | fb5c57b0664b8bf5d5673d84acb4dcc9c7a947e7 | [
"MIT"
] | 1 | 2021-01-13T00:55:03.000Z | 2021-01-13T00:55:03.000Z | experiments/sarsa_2way-single-intersection.py | huyz-git/sumo-rl | fb5c57b0664b8bf5d5673d84acb4dcc9c7a947e7 | [
"MIT"
] | null | null | null | experiments/sarsa_2way-single-intersection.py | huyz-git/sumo-rl | fb5c57b0664b8bf5d5673d84acb4dcc9c7a947e7 | [
"MIT"
] | 1 | 2021-04-14T05:53:07.000Z | 2021-04-14T05:53:07.000Z | import argparse
import os
import sys
import pandas as pd
from datetime import datetime
if 'SUMO_HOME' in os.environ:
tools = os.path.join(os.environ['SUMO_HOME'], 'tools')
sys.path.append(tools)
else:
sys.exit("Please declare the environment variable 'SUMO_HOME'")
import traci
from sumo_rl.util.gen_route import write_route_file
from sumo_rl.environment.env import SumoEnvironment
from sumo_rl.agents.sarsa_lambda import TrueOnlineSarsaLambda
if __name__ == '__main__':
prs = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter,
description="""SarsaLambda Single-Intersection""")
prs.add_argument("-route", dest="route", type=str, default='nets/2way-single-intersection/single-intersection-gen.rou.xml', help="Route definition xml file.\n")
prs.add_argument("-a", dest="alpha", type=float, default=0.0001, required=False, help="Alpha learning rate.\n")
prs.add_argument("-g", dest="gamma", type=float, default=0.99, required=False, help="Gamma discount rate.\n")
prs.add_argument("-e", dest="epsilon", type=float, default=0.05, required=False, help="Epsilon.\n")
prs.add_argument("-mingreen", dest="min_green", type=int, default=5, required=False, help="Minimum green time.\n")
prs.add_argument("-maxgreen", dest="max_green", type=int, default=50, required=False, help="Maximum green time.\n")
prs.add_argument("-gui", action="store_true", default=False, help="Run with visualization on SUMO.\n")
prs.add_argument("-fixed", action="store_true", default=False, help="Run with fixed timing traffic signals.\n")
prs.add_argument("-s", dest="seconds", type=int, default=400000, required=False, help="Number of simulation seconds.\n")
prs.add_argument("-runs", dest="runs", type=int, default=1, help="Number of runs.\n")
args = prs.parse_args()
experiment_time = str(datetime.now()).split('.')[0]
out_csv = 'outputs/2way-single-intersection/sarsa_lambda'
write_route_file('nets/2way-single-intersection/single-intersection-gen.rou.xml', 400000, 100000)
env = SumoEnvironment(net_file='nets/2way-single-intersection/single-intersection.net.xml',
single_agent=True,
route_file=args.route,
out_csv_name=out_csv,
use_gui=args.gui,
num_seconds=args.seconds,
min_green=args.min_green,
max_green=args.max_green,
max_depart_delay=0,
time_to_load_vehicles=120,
phases=[
traci.trafficlight.Phase(32, "GGrrrrGGrrrr"),
traci.trafficlight.Phase(2, "yyrrrryyrrrr"),
traci.trafficlight.Phase(32, "rrGrrrrrGrrr"),
traci.trafficlight.Phase(2, "rryrrrrryrrr"),
traci.trafficlight.Phase(32, "rrrGGrrrrGGr"),
traci.trafficlight.Phase(2, "rrryyrrrryyr"),
traci.trafficlight.Phase(32, "rrrrrGrrrrrG"),
traci.trafficlight.Phase(2, "rrrrryrrrrry")
])
for run in range(1, args.runs+1):
obs = env.reset()
agent = TrueOnlineSarsaLambda(env.observation_space, env.action_space, alpha=args.alpha, gamma=args.gamma, epsilon=args.epsilon, fourier_order=7)
done = False
if args.fixed:
while not done:
_, _, done, _ = env.step({})
else:
while not done:
action = agent.act(agent.get_features(obs))
next_obs, r, done, _ = env.step(action=action)
agent.learn(state=obs, action=action, reward=r, next_state=next_obs, done=done)
obs = next_obs
env.save_csv(out_csv, run)
| 47.807229 | 164 | 0.614163 |
23f0db27ce933bc2bd64620c112cb731a4699a09 | 521 | py | Python | rest/member/instance-post-example-1/instance-post-example-1.6.x.py | azaddeveloper/api-snippets | f88b153cd7186fa70b33733b205886502db0d1f2 | [
"MIT"
] | 3 | 2020-05-05T10:01:02.000Z | 2021-02-06T14:23:13.000Z | rest/member/instance-post-example-1/instance-post-example-1.6.x.py | azaddeveloper/api-snippets | f88b153cd7186fa70b33733b205886502db0d1f2 | [
"MIT"
] | null | null | null | rest/member/instance-post-example-1/instance-post-example-1.6.x.py | azaddeveloper/api-snippets | f88b153cd7186fa70b33733b205886502db0d1f2 | [
"MIT"
] | 1 | 2019-10-02T14:36:36.000Z | 2019-10-02T14:36:36.000Z | # Download the Python helper library from twilio.com/docs/python/install
from twilio.rest import Client
# Your Account Sid and Auth Token from twilio.com/user/account
account_sid = "ACXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
auth_token = "your_auth_token"
client = Client(account_sid, auth_token)
member = client.queues("QU5ef8732a3c49700934481addd5ce1659") \
.members("Front") \
.update(url="http://demo.twilio.com/docs/voice.xml",
method="POST")
print(member.wait_time)
| 34.733333 | 72 | 0.712092 |
313c4ee2709eb07fbb5875e08cbd27711df3944f | 3,634 | py | Python | tests/st/ops/ascend/test_aicpu_ops/test_reshape.py | GuoSuiming/mindspore | 48afc4cfa53d970c0b20eedfb46e039db2a133d5 | [
"Apache-2.0"
] | 3,200 | 2020-02-17T12:45:41.000Z | 2022-03-31T20:21:16.000Z | tests/st/ops/ascend/test_aicpu_ops/test_reshape.py | forwhat461/mindspore | 59a277756eb4faad9ac9afcc7fd526e8277d4994 | [
"Apache-2.0"
] | 176 | 2020-02-12T02:52:11.000Z | 2022-03-28T22:15:55.000Z | tests/st/ops/ascend/test_aicpu_ops/test_reshape.py | forwhat461/mindspore | 59a277756eb4faad9ac9afcc7fd526e8277d4994 | [
"Apache-2.0"
] | 621 | 2020-03-09T01:31:41.000Z | 2022-03-30T03:43:19.000Z | # Copyright 2019 Huawei Technologies Co., Ltd
#
# 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 numpy as np
import mindspore.context as context
import mindspore.nn as nn
from mindspore import Tensor
from mindspore.ops import operations as P
context.set_context(mode=context.PYNATIVE_MODE, device_target="Ascend")
class Net(nn.Cell):
def __init__(self):
super(Net, self).__init__()
self.reshape = P.Reshape()
def construct(self, tensor):
return self.reshape(tensor, (4, 4))
def test_net_bool():
x = np.random.randn(1, 16, 1, 1).astype(np.bool)
net = Net()
output = net(Tensor(x))
print(output.asnumpy())
assert np.all(output.asnumpy() == np.reshape(x, (4, 4)))
def test_net_int8():
x = np.random.randn(1, 16, 1, 1).astype(np.int8)
net = Net()
output = net(Tensor(x))
print(output.asnumpy())
assert np.all(output.asnumpy() == np.reshape(x, (4, 4)))
def test_net_uint8():
x = np.random.randn(1, 16, 1, 1).astype(np.uint8)
net = Net()
output = net(Tensor(x))
print(output.asnumpy())
assert np.all(output.asnumpy() == np.reshape(x, (4, 4)))
def test_net_int16():
x = np.random.randn(1, 16, 1, 1).astype(np.int16)
net = Net()
output = net(Tensor(x))
print(output.asnumpy())
assert np.all(output.asnumpy() == np.reshape(x, (4, 4)))
def test_net_uint16():
x = np.random.randn(1, 16, 1, 1).astype(np.uint16)
net = Net()
output = net(Tensor(x))
print(output.asnumpy())
assert np.all(output.asnumpy() == np.reshape(x, (4, 4)))
def test_net_int32():
x = np.random.randn(1, 16, 1, 1).astype(np.int32)
net = Net()
output = net(Tensor(x))
print(output.asnumpy())
assert np.all(output.asnumpy() == np.reshape(x, (4, 4)))
def test_net_uint32():
x = np.random.randn(1, 16, 1, 1).astype(np.uint32)
net = Net()
output = net(Tensor(x))
print(output.asnumpy())
assert np.all(output.asnumpy() == np.reshape(x, (4, 4)))
def test_net_int64():
x = np.random.randn(1, 16, 1, 1).astype(np.int64)
net = Net()
output = net(Tensor(x))
print(output.asnumpy())
assert np.all(output.asnumpy() == np.reshape(x, (4, 4)))
def test_net_uint64():
x = np.random.randn(1, 16, 1, 1).astype(np.uint64)
net = Net()
output = net(Tensor(x))
print(output.asnumpy())
assert np.all(output.asnumpy() == np.reshape(x, (4, 4)))
def test_net_float16():
x = np.random.randn(1, 16, 1, 1).astype(np.float16)
net = Net()
output = net(Tensor(x))
print(output.asnumpy())
assert np.all(output.asnumpy() == np.reshape(x, (4, 4)))
def test_net_float32():
x = np.random.randn(1, 16, 1, 1).astype(np.float32)
net = Net()
output = net(Tensor(x))
print(output.asnumpy())
assert np.all(output.asnumpy() == np.reshape(x, (4, 4)))
def test_net_float64():
x = np.random.randn(1, 16, 1, 1).astype(np.float64)
net = Net()
output = net(Tensor(x))
print(output.asnumpy())
assert np.all(output.asnumpy() == np.reshape(x, (4, 4)))
| 28.390625 | 78 | 0.624381 |
9d9e5dcdd286f34161d29d70de25d6fc6a7675ff | 933 | py | Python | setup.py | alicebambi/idcode_recognition | 64dd391d7be64cc8af40d610ad72a22843c73629 | [
"MIT"
] | null | null | null | setup.py | alicebambi/idcode_recognition | 64dd391d7be64cc8af40d610ad72a22843c73629 | [
"MIT"
] | null | null | null | setup.py | alicebambi/idcode_recognition | 64dd391d7be64cc8af40d610ad72a22843c73629 | [
"MIT"
] | null | null | null | #!/usr/bin/env python
#-*- coding:utf-8 -*-
#############################################
# File Name: setup.py
# Author: xingming
# Mail: huoxingming@gmail.com
# Created Time: 2015-12-11 01:25:34 AM
#############################################
from setuptools import setup, find_packages
setup(
name = "ufzh",
version = "1.0.0",
keywords = ("pip", "ufzh"),
description = "深度学习实现知乎验证码识别",
long_description = "深度学习实现知乎验证码识别",
license = "MIT Licence",
author = "bambi",
author_email = "bambi2017@aliyun.com",
packages = find_packages(),
include_package_data = True,
data_files=[('ufzh/checkpoint', ['ufzh/checkpoint/checkpoint', 'ufzh/checkpoint/ocr-model-22001.data-00000-of-00001', 'ufzh/checkpoint/ocr-model-22001.index','ufzh/checkpoint/ocr-model-22001.meta'])],
platforms = "any",
install_requires = ['requests', "bs4", 'tensorflow==1.2.1', 'pillow', 'numpy', 'tqdm']
)
| 30.096774 | 204 | 0.596999 |
a3af649915970b070f8c497cf67a91b240f7d034 | 65,763 | py | Python | O365/drive.py | livejake/python-o365 | 7179e85b95778a52affbf70596388530dedf90c9 | [
"Apache-2.0"
] | null | null | null | O365/drive.py | livejake/python-o365 | 7179e85b95778a52affbf70596388530dedf90c9 | [
"Apache-2.0"
] | null | null | null | O365/drive.py | livejake/python-o365 | 7179e85b95778a52affbf70596388530dedf90c9 | [
"Apache-2.0"
] | null | null | null | import logging
import warnings
from pathlib import Path
from time import sleep
from urllib.parse import urlparse, quote
from dateutil.parser import parse
from .address_book import Contact
from .utils import ApiComponent, Pagination, NEXT_LINK_KEYWORD, \
OneDriveWellKnowFolderNames
log = logging.getLogger(__name__)
SIZE_THERSHOLD = 1024 * 1024 * 2 # 2 MB
UPLOAD_SIZE_LIMIT_SIMPLE = 1024 * 1024 * 4 # 4 MB
UPLOAD_SIZE_LIMIT_SESSION = 1024 * 1024 * 60 # 60 MB
CHUNK_SIZE_BASE = 1024 * 320 # 320 Kb
# 5 MB --> Must be a multiple of CHUNK_SIZE_BASE
DEFAULT_UPLOAD_CHUNK_SIZE = 1024 * 1024 * 5
ALLOWED_PDF_EXTENSIONS = {'.csv', '.doc', '.docx', '.odp', '.ods', '.odt',
'.pot', '.potm', '.potx',
'.pps', '.ppsx', '.ppsxm', '.ppt', '.pptm', '.pptx',
'.rtf', '.xls', '.xlsx'}
class DownloadableMixin:
def download(self, to_path=None, name=None, chunk_size='auto',
convert_to_pdf=False):
""" Downloads this file to the local drive. Can download the
file in chunks with multiple requests to the server.
:param to_path: a path to store the downloaded file
:type to_path: str or Path
:param str name: the name you want the stored file to have.
:param int chunk_size: number of bytes to retrieve from
each api call to the server. if auto, files bigger than
SIZE_THERSHOLD will be chunked (into memory, will be
however only 1 request)
:param bool convert_to_pdf: will try to download the converted pdf
if file extension in ALLOWED_PDF_EXTENSIONS
:return: Success / Failure
:rtype: bool
"""
# TODO: Add download with more than one request (chunk_requests) with
# header 'Range'. For example: 'Range': 'bytes=0-1024'
if to_path is None:
to_path = Path()
else:
if not isinstance(to_path, Path):
to_path = Path(to_path)
if not to_path.exists():
raise FileNotFoundError('{} does not exist'.format(to_path))
if name and not Path(name).suffix and self.name:
name = name + Path(self.name).suffix
name = name or self.name
to_path = to_path / name
url = self.build_url(
self._endpoints.get('download').format(id=self.object_id))
try:
if chunk_size is None:
stream = False
elif chunk_size == 'auto':
if self.size and self.size > SIZE_THERSHOLD:
stream = True
else:
stream = False
chunk_size = None
elif isinstance(chunk_size, int):
stream = True
else:
raise ValueError("Argument chunk_size must be either 'auto' "
"or any integer number representing bytes")
params = {}
if convert_to_pdf and Path(name).suffix in ALLOWED_PDF_EXTENSIONS:
params['format'] = 'pdf'
with self.con.get(url, stream=stream, params=params) as response:
if not response:
log.debug('Downloading driveitem Request failed: {}'.format(
response.reason))
return False
with to_path.open(mode='wb') as output:
if stream:
for chunk in response.iter_content(
chunk_size=chunk_size):
if chunk:
output.write(chunk)
else:
output.write(response.content)
except Exception as e:
log.error(
'Error downloading driveitem {}. Error: {}'.format(self.name,
str(e)))
return False
return True
class CopyOperation(ApiComponent):
""" https://github.com/OneDrive/onedrive-api-docs/issues/762 """
_endpoints = {
# all prefixed with /drives/{drive_id} on main_resource by default
'item': '/items/{id}',
}
def __init__(self, *, parent=None, con=None, **kwargs):
"""
:param parent: parent for this operation
:type parent: Drive
:param Connection con: connection to use if no parent specified
:param Protocol protocol: protocol to use if no parent specified
(kwargs)
:param str main_resource: use this resource instead of parent resource
(kwargs)
:param str monitor_url:
:param str item_id:
"""
if parent and con:
raise ValueError('Need a parent or a connection but not both')
self.con = parent.con if parent else con
self.parent = parent # parent will be always a DriveItem
# Choose the main_resource passed in kwargs over parent main_resource
main_resource = kwargs.pop('main_resource', None) or (
getattr(parent, 'main_resource', None) if parent else None)
super().__init__(
protocol=parent.protocol if parent else kwargs.get('protocol'),
main_resource=main_resource)
self.monitor_url = kwargs.get('monitor_url', None)
self.item_id = kwargs.get('item_id', None)
if self.monitor_url is None and self.item_id is None:
raise ValueError('Must provide a valid monitor_url or item_id')
if self.monitor_url is not None and self.item_id is not None:
raise ValueError(
'Must provide a valid monitor_url or item_id, but not both')
if self.item_id:
self.status = 'completed'
self.completion_percentage = 100.0
else:
self.status = 'inProgress'
self.completion_percentage = 0.0
def _request_status(self):
""" Checks the api endpoint to check if the async job progress """
if self.item_id:
return True
response = self.con.get(self.monitor_url)
if not response:
return False
data = response.json()
self.status = data.get('status', 'inProgress')
self.completion_percentage = data.get(self._cc('percentageComplete'),
0)
self.item_id = data.get(self._cc('resourceId'), None)
return self.item_id is not None
def check_status(self, delay=0):
""" Checks the api endpoint in a loop
:param delay: number of seconds to wait between api calls.
Note Connection 'requests_delay' also apply.
:return: tuple of status and percentage complete
:rtype: tuple(str, float)
"""
if not self.item_id:
while not self._request_status():
# wait until _request_status returns True
yield self.status, self.completion_percentage
if self.item_id is None:
sleep(delay)
else:
yield self.status, self.completion_percentage
def get_item(self):
""" Returns the item copied
:return: Copied Item
:rtype: DriveItem
"""
return self.parent.get_item(
self.item_id) if self.item_id is not None else None
class DriveItemVersion(ApiComponent, DownloadableMixin):
""" A version of a DriveItem """
_endpoints = {
'download': '/versions/{id}/content',
'restore': '/versions/{id}/restoreVersion'
}
def __init__(self, *, parent=None, con=None, **kwargs):
""" Version of DriveItem
:param parent: parent for this operation
:type parent: DriveItem
:param Connection con: connection to use if no parent specified
:param Protocol protocol: protocol to use if no parent specified
(kwargs)
:param str main_resource: use this resource instead of parent resource
(kwargs)
"""
if parent and con:
raise ValueError('Need a parent or a connection but not both')
self.con = parent.con if parent else con
self._parent = parent if isinstance(parent, DriveItem) else None
protocol = parent.protocol if parent else kwargs.get('protocol')
# Choose the main_resource passed in kwargs over parent main_resource
main_resource = kwargs.pop('main_resource', None) or (
getattr(parent, 'main_resource', None) if parent else None)
resource_prefix = '/items/{item_id}'.format(
item_id=self._parent.object_id)
main_resource = '{}{}'.format(
main_resource or (protocol.default_resource if protocol else ''),
resource_prefix)
super().__init__(protocol=protocol, main_resource=main_resource)
cloud_data = kwargs.get(self._cloud_data_key, {})
self.driveitem_id = self._parent.object_id
self.object_id = cloud_data.get('id', '1.0')
self.name = self.object_id
modified = cloud_data.get(self._cc('lastModifiedDateTime'), None)
local_tz = self.protocol.timezone
self.modified = parse(modified).astimezone(
local_tz) if modified else None
self.size = cloud_data.get('size', 0)
modified_by = cloud_data.get(self._cc('lastModifiedBy'), {}).get('user',
None)
self.modified_by = Contact(con=self.con, protocol=self.protocol, **{
self._cloud_data_key: modified_by}) if modified_by else None
def __str__(self):
return self.__repr__()
def __repr__(self):
return ('Version Id: {} | Modified on: {} | by: {}'
''.format(self.name,
self.modified,
self.modified_by.display_name
if self.modified_by else None))
def restore(self):
""" Restores this DriveItem Version.
You can not restore the current version (last one).
:return: Success / Failure
:rtype: bool
"""
url = self.build_url(
self._endpoints.get('restore').format(id=self.object_id))
response = self.con.post(url)
return bool(response)
def download(self, to_path=None, name=None, chunk_size='auto',
convert_to_pdf=False):
""" Downloads this version.
You can not download the current version (last one).
:return: Success / Failure
:rtype: bool
"""
return super().download(to_path=to_path, name=name,
chunk_size=chunk_size,
convert_to_pdf=convert_to_pdf)
class DriveItemPermission(ApiComponent):
""" A Permission representation for a DriveItem """
_endpoints = {
'permission': '/items/{driveitem_id}/permissions/{id}'
}
def __init__(self, *, parent=None, con=None, **kwargs):
""" Permissions for DriveItem
:param parent: parent for this operation
:type parent: DriveItem
:param Connection con: connection to use if no parent specified
:param Protocol protocol: protocol to use if no parent specified
(kwargs)
:param str main_resource: use this resource instead of parent resource
(kwargs)
"""
if parent and con:
raise ValueError('Need a parent or a connection but not both')
self.con = parent.con if parent else con
self._parent = parent if isinstance(parent, DriveItem) else None
# Choose the main_resource passed in kwargs over parent main_resource
main_resource = kwargs.pop('main_resource', None) or (
getattr(parent, 'main_resource', None) if parent else None)
protocol = parent.protocol if parent else kwargs.get('protocol')
super().__init__(protocol=protocol, main_resource=main_resource)
self.driveitem_id = self._parent.object_id
cloud_data = kwargs.get(self._cloud_data_key, {})
self.object_id = cloud_data.get(self._cc('id'))
self.inherited_from = cloud_data.get(self._cc('inheritedFrom'), None)
link = cloud_data.get(self._cc('link'), None)
self.permission_type = 'owner'
if link:
self.permission_type = 'link'
self.share_type = link.get('type', 'view')
self.share_scope = link.get('scope', 'anonymous')
self.share_link = link.get('webUrl', None)
invitation = cloud_data.get(self._cc('invitation'), None)
if invitation:
self.permission_type = 'invitation'
self.share_email = invitation.get('email', '')
invited_by = invitation.get('invitedBy', {})
self.invited_by = invited_by.get('user', {}).get(
self._cc('displayName'), None) or invited_by.get('application',
{}).get(
self._cc('displayName'), None)
self.require_sign_in = invitation.get(self._cc('signInRequired'),
True)
self.roles = cloud_data.get(self._cc('roles'), [])
granted_to = cloud_data.get(self._cc('grantedTo'), {})
self.granted_to = granted_to.get('user', {}).get(
self._cc('displayName')) or granted_to.get('application', {}).get(
self._cc('displayName'))
self.share_id = cloud_data.get(self._cc('shareId'), None)
def __str__(self):
return self.__repr__()
def __repr__(self):
return 'Permission for {} of type: {}'.format(self._parent.name,
self.permission_type)
def update_roles(self, roles='view'):
""" Updates the roles of this permission
:return: Success / Failure
:rtype: bool
"""
if not self.object_id:
return False
url = self.build_url(self._endpoints.get('permission').format(
driveitem_id=self.driveitem_id, id=self.object_id))
if roles in {'view', 'read'}:
data = {'roles': ['read']}
elif roles == {'edit', 'write'}:
data = {'roles': ['write']}
else:
raise ValueError('"{}" is not a valid share_type'.format(roles))
response = self.con.patch(url, data=data)
if not response:
return False
self.roles = data.get('roles', [])
return True
def delete(self):
""" Deletes this permission. Only permissions that are not
inherited can be deleted.
:return: Success / Failure
:rtype: bool
"""
if not self.object_id:
return False
url = self.build_url(self._endpoints.get('permission').format(
driveitem_id=self.driveitem_id, id=self.object_id))
response = self.con.delete(url)
if not response:
return False
self.object_id = None
return True
class DriveItem(ApiComponent):
""" A DriveItem representation. Groups all functionality """
_endpoints = {
# all prefixed with /drives/{drive_id} on main_resource by default
'list_items': '/items/{id}/children',
'thumbnails': '/items/{id}/thumbnails',
'item': '/items/{id}',
'copy': '/items/{id}/copy',
'download': '/items/{id}/content',
'search': "/items/{id}/search(q='{search_text}')",
'versions': '/items/{id}/versions',
'version': '/items/{id}/versions/{version_id}',
'simple_upload': '/items/{id}:/{filename}:/content',
'create_upload_session': '/items/{id}:/{filename}:/createUploadSession',
'share_link': '/items/{id}/createLink',
'share_invite': '/items/{id}/invite',
'permissions': '/items/{id}/permissions',
}
def __init__(self, *, parent=None, con=None, **kwargs):
""" Create a DriveItem
:param parent: parent for this operation
:type parent: Drive or drive.Folder
:param Connection con: connection to use if no parent specified
:param Protocol protocol: protocol to use if no parent specified
(kwargs)
:param str main_resource: use this resource instead of parent resource
(kwargs)
"""
if parent and con:
raise ValueError('Need a parent or a connection but not both')
self.con = parent.con if parent else con
self._parent = parent if isinstance(parent, DriveItem) else None
self.drive = parent if isinstance(parent, Drive) else (
parent.drive if isinstance(parent.drive, Drive) else kwargs.get(
'drive', None))
# Choose the main_resource passed in kwargs over parent main_resource
main_resource = kwargs.pop('main_resource', None) or (
getattr(parent, 'main_resource', None) if parent else None)
protocol = parent.protocol if parent else kwargs.get('protocol')
if parent and not isinstance(parent, DriveItem):
# parent is a Drive so append the drive route to the main_resource
drive_id = (None if parent.object_id == 'root'
else parent.object_id) or None
# prefix with the current known drive or the default one
resource_prefix = '/drives/{drive_id}'.format(
drive_id=drive_id) if drive_id else '/drive'
main_resource = '{}{}'.format(main_resource or (
protocol.default_resource if protocol else ''), resource_prefix)
super().__init__(protocol=protocol, main_resource=main_resource)
cloud_data = kwargs.get(self._cloud_data_key, {})
self.object_id = cloud_data.get(self._cc('id'))
self.name = cloud_data.get(self._cc('name'), '')
self.web_url = cloud_data.get(self._cc('webUrl'))
created_by = cloud_data.get(self._cc('createdBy'), {}).get('user', None)
self.created_by = Contact(con=self.con, protocol=self.protocol, **{
self._cloud_data_key: created_by}) if created_by else None
modified_by = cloud_data.get(self._cc('lastModifiedBy'), {}).get('user',
None)
self.modified_by = Contact(con=self.con, protocol=self.protocol, **{
self._cloud_data_key: modified_by}) if modified_by else None
created = cloud_data.get(self._cc('createdDateTime'), None)
modified = cloud_data.get(self._cc('lastModifiedDateTime'), None)
local_tz = self.protocol.timezone
self.created = parse(created).astimezone(local_tz) if created else None
self.modified = parse(modified).astimezone(
local_tz) if modified else None
self.description = cloud_data.get(self._cc('description'), '')
self.size = cloud_data.get(self._cc('size'), 0)
self.shared = cloud_data.get(self._cc('shared'), {}).get('scope', None)
parent_reference = cloud_data.get(self._cc('parentReference'), {})
self.parent_id = parent_reference.get('id', None)
self.drive_id = parent_reference.get(self._cc('driveId'), None)
remote_item = cloud_data.get(self._cc('remoteItem'), None)
self.remote_item = self._classifier(remote_item)(parent=self, **{
self._cloud_data_key: remote_item}) if remote_item else None
# Thumbnails
self.thumbnails = cloud_data.get(self._cc('thumbnails'), [])
def __str__(self):
return self.__repr__()
def __repr__(self):
return '{}: {}'.format(self.__class__.__name__, self.name)
def __eq__(self, other):
obj_id = getattr(other, 'object_id', None)
if obj_id is not None:
return self.object_id == obj_id
return False
@staticmethod
def _classifier(item):
""" Subclass to change factory classes """
if 'folder' in item:
return Folder
elif 'image' in item:
return Image
elif 'photo' in item:
return Photo
else:
return File
@property
def is_folder(self):
""" Returns if this DriveItem is a Folder """
return isinstance(self, Folder)
@property
def is_file(self):
""" Returns if this DriveItem is a File """
return isinstance(self, File)
@property
def is_image(self):
""" Returns if this DriveItem is a Image """
return isinstance(self, Image)
@property
def is_photo(self):
""" Returns if this DriveItem is a Photo """
return isinstance(self, Photo)
def get_parent(self):
""" the parent of this DriveItem
:return: Parent of this item
:rtype: Drive or drive.Folder
"""
if self._parent and self._parent.object_id == self.parent_id:
return self._parent
else:
if self.parent_id:
return self.drive.get_item(self.parent_id)
else:
# return the drive
return self.drive
def get_thumbnails(self, size=None):
""" Returns this Item Thumbnails. Thumbnails are not supported on
SharePoint Server 2016.
:param size: request only the specified size: ej: "small",
Custom 300x400 px: "c300x400", Crop: "c300x400_Crop"
:return: Thumbnail Data
:rtype: dict
"""
if not self.object_id:
return []
url = self.build_url(
self._endpoints.get('thumbnails').format(id=self.object_id))
params = {}
if size is not None:
params['select'] = size
response = self.con.get(url, params=params)
if not response:
return []
data = response.json()
if not self.thumbnails or size is None:
self.thumbnails = data
return data
def update(self, **kwargs):
""" Updates this item
:param kwargs: all the properties to be updated.
only name and description are allowed at the moment.
:return: Success / Failure
:rtype: bool
"""
if not self.object_id:
return False
url = self.build_url(
self._endpoints.get('item').format(id=self.object_id))
data = {self._cc(key): value for key, value in kwargs.items() if
key in {'name',
'description'}} # convert keys to protocol casing
if not data:
return False
response = self.con.patch(url, data=data)
if not response:
return False
new_data = response.json()
for key in data:
value = new_data.get(key, None)
if value:
setattr(self, self.protocol.to_api_case(key), value)
return True
def delete(self):
""" Moves this item to the Recycle Bin
:return: Success / Failure
:rtype: bool
"""
if not self.object_id:
return False
url = self.build_url(
self._endpoints.get('item').format(id=self.object_id))
response = self.con.delete(url)
if not response:
return False
self.object_id = None
return True
def move(self, target):
""" Moves this DriveItem to another Folder.
Can't move between different Drives.
:param target: a Folder, Drive item or Item Id string.
If it's a drive the item will be moved to the root folder.
:type target: drive.Folder or DriveItem or str
:return: Success / Failure
:rtype: bool
"""
if isinstance(target, Folder):
target_id = target.object_id
elif isinstance(target, Drive):
# we need the root folder id
root_folder = target.get_root_folder()
if not root_folder:
return False
target_id = root_folder.object_id
elif isinstance(target, str):
target_id = target
else:
raise ValueError('Target must be a Folder or Drive')
if not self.object_id or not target_id:
raise ValueError(
'Both self, and target must have a valid object_id.')
if target_id == 'root':
raise ValueError("When moving, target id can't be 'root'")
url = self.build_url(
self._endpoints.get('item').format(id=self.object_id))
data = {'parentReference': {'id': target_id}}
response = self.con.patch(url, data=data)
if not response:
return False
self.parent_id = target_id
return True
def copy(self, target=None, name=None):
""" Asynchronously creates a copy of this DriveItem and all it's
child elements.
:param target: target location to move to.
If it's a drive the item will be moved to the root folder.
:type target: drive.Folder or Drive
:param name: a new name for the copy.
:rtype: CopyOperation
"""
if target is None and name is None:
raise ValueError('Must provide a target or a name (or both)')
if isinstance(target, Folder):
target_id = target.object_id
drive_id = target.drive_id
elif isinstance(target, Drive):
# we need the root folder
root_folder = target.get_root_folder()
if not root_folder:
return None
target_id = root_folder.object_id
drive_id = root_folder.drive_id
elif target is None:
target_id = None
drive_id = None
else:
raise ValueError('Target, if provided, must be a Folder or Drive')
if not self.object_id:
return None
if target_id == 'root':
raise ValueError("When copying, target id can't be 'root'")
url = self.build_url(
self._endpoints.get('copy').format(id=self.object_id))
if target_id and drive_id:
data = {'parentReference': {'id': target_id, 'driveId': drive_id}}
else:
data = {}
if name:
# incorporate the extension if the name provided has none.
if not Path(name).suffix and self.name:
name = name + Path(self.name).suffix
data['name'] = name
response = self.con.post(url, data=data)
if not response:
return None
# Find out if the server has run a Sync or Async operation
location = response.headers.get('Location', None)
if 'monitor' in location:
# Async operation
return CopyOperation(parent=self.drive, monitor_url=location)
else:
# Sync operation. Item is ready to be retrieved
path = urlparse(location).path
item_id = path.split('/')[-1]
return CopyOperation(parent=self.drive, item_id=item_id)
def get_versions(self):
""" Returns a list of available versions for this item
:return: list of versions
:rtype: list[DriveItemVersion]
"""
if not self.object_id:
return []
url = self.build_url(
self._endpoints.get('versions').format(id=self.object_id))
response = self.con.get(url)
if not response:
return []
data = response.json()
# Everything received from cloud must be passed as self._cloud_data_key
return [DriveItemVersion(parent=self, **{self._cloud_data_key: item})
for item in data.get('value', [])]
def get_version(self, version_id):
""" Returns a version for specified id
:return: a version object of specified id
:rtype: DriveItemVersion
"""
if not self.object_id:
return None
url = self.build_url(
self._endpoints.get('version').format(id=self.object_id,
version_id=version_id))
response = self.con.get(url)
if not response:
return None
data = response.json()
# Everything received from cloud must be passed as self._cloud_data_key
return DriveItemVersion(parent=self, **{self._cloud_data_key: data})
def share_with_link(self, share_type='view', share_scope='anonymous'):
""" Creates or returns a link you can share with others
:param str share_type: 'view' to allow only view access,
'edit' to allow editions, and
'embed' to allow the DriveItem to be embedded
:param str share_scope: 'anonymous': anyone with the link can access.
'organization' Only organization members can access
:return: link to share
:rtype: DriveItemPermission
"""
if not self.object_id:
return None
url = self.build_url(
self._endpoints.get('share_link').format(id=self.object_id))
data = {
'type': share_type,
'scope': share_scope
}
response = self.con.post(url, data=data)
if not response:
return None
data = response.json()
# return data.get('link', {}).get('webUrl')
return DriveItemPermission(parent=self, **{self._cloud_data_key: data})
def share_with_invite(self, recipients, require_sign_in=True,
send_email=True, message=None, share_type='view'):
""" Sends an invitation to access or edit this DriveItem
:param recipients: a string or Contact or a list of the former
representing recipients of this invitation
:type recipients: list[str] or list[Contact] or str or Contact
:param bool require_sign_in: if True the recipients
invited will need to log in to view the contents
:param bool send_email: if True an email will be send to the recipients
:param str message: the body text of the message emailed
:param str share_type: 'view': will allow to read the contents.
'edit' will allow to modify the contents
:return: link to share
:rtype: DriveItemPermission
"""
if not self.object_id:
return None
to = []
if recipients is None:
raise ValueError('Provide a valid to parameter')
elif isinstance(recipients, (list, tuple)):
for x in recipients:
if isinstance(x, str):
to.append({'email': x})
elif isinstance(x, Contact):
to.append({'email': x.main_email})
else:
raise ValueError(
'All the recipients must be either strings or Contacts')
elif isinstance(recipients, str):
to.append({'email': recipients})
elif isinstance(recipients, Contact):
to.append({'email': recipients.main_email})
else:
raise ValueError(
'All the recipients must be either strings or Contacts')
url = self.build_url(
self._endpoints.get('share_invite').format(id=self.object_id))
data = {
'recipients': to,
self._cc('requireSignIn'): require_sign_in,
self._cc('sendInvitation'): send_email,
}
if share_type in {'view', 'read'}:
data['roles'] = ['read']
elif share_type in {'edit', 'write'}:
data['roles'] = ['write']
else:
raise ValueError(
'"{}" is not a valid share_type'.format(share_type))
if send_email and message:
data['message'] = message
response = self.con.post(url, data=data)
if not response:
return None
data = response.json()
return DriveItemPermission(parent=self, **{self._cloud_data_key: data})
def get_permissions(self):
""" Returns a list of DriveItemPermissions with the
permissions granted for this DriveItem.
:return: List of Permissions
:rtype: list[DriveItemPermission]
"""
if not self.object_id:
return []
url = self.build_url(
self._endpoints.get('permissions').format(id=self.object_id))
response = self.con.get(url)
if not response:
return None
data = response.json()
# Everything received from cloud must be passed as self._cloud_data_key
return [DriveItemPermission(parent=self, **{self._cloud_data_key: item})
for item in data.get('value', [])]
class File(DriveItem, DownloadableMixin):
""" A File """
def __init__(self, **kwargs):
super().__init__(**kwargs)
cloud_data = kwargs.get(self._cloud_data_key, {})
self.mime_type = cloud_data.get(self._cc('file'), {}).get(
self._cc('mimeType'), None)
@property
def extension(self):
return Path(self.name).suffix
class Image(File):
""" An Image """
def __init__(self, **kwargs):
super().__init__(**kwargs)
cloud_data = kwargs.get(self._cloud_data_key, {})
image = cloud_data.get(self._cc('image'), {})
self.height = image.get(self._cc('height'), 0)
self.width = image.get(self._cc('width'), 0)
@property
def dimensions(self):
""" Dimension of the Image
:return: width x height
:rtype: str
"""
return '{}x{}'.format(self.width, self.height)
class Photo(Image):
""" Photo Object. Inherits from Image but has more attributes """
def __init__(self, **kwargs):
super().__init__(**kwargs)
cloud_data = kwargs.get(self._cloud_data_key, {})
photo = cloud_data.get(self._cc('photo'), {})
taken = photo.get(self._cc('takenDateTime'), None)
local_tz = self.protocol.timezone
self.taken_datetime = parse(taken).astimezone(
local_tz) if taken else None
self.camera_make = photo.get(self._cc('cameraMake'), None)
self.camera_model = photo.get(self._cc('cameraModel'), None)
self.exposure_denominator = photo.get(self._cc('exposureDenominator'),
None)
self.exposure_numerator = photo.get(self._cc('exposureNumerator'), None)
self.fnumber = photo.get(self._cc('fNumber'), None)
self.focal_length = photo.get(self._cc('focalLength'), None)
self.iso = photo.get(self._cc('iso'), None)
class Folder(DriveItem):
""" A Folder inside a Drive """
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
cloud_data = kwargs.get(self._cloud_data_key, {})
self.child_count = cloud_data.get(self._cc('folder'), {}).get(
self._cc('childCount'), 0)
self.special_folder = cloud_data.get(self._cc('specialFolder'), {}).get(
'name', None)
def get_items(self, limit=None, *, query=None, order_by=None, batch=None):
""" Returns all the items inside this folder
:param int limit: max no. of folders to get. Over 999 uses batch.
:param query: applies a OData filter to the request
:type query: Query or str
:param order_by: orders the result set based on this condition
:type order_by: Query or str
:param int batch: batch size, retrieves items in
batches allowing to retrieve more items than the limit.
:return: list of items in this folder
:rtype: list[DriveItem] or Pagination
"""
url = self.build_url(
self._endpoints.get('list_items').format(id=self.object_id))
if limit is None or limit > self.protocol.max_top_value:
batch = self.protocol.max_top_value
params = {'$top': batch if batch else limit}
if order_by:
params['$orderby'] = order_by
if query:
if query.has_filters:
warnings.warn('Filters are not allowed by the '
'Api Provider in this method')
query.clear_filters()
if isinstance(query, str):
params['$filter'] = query
else:
params.update(query.as_params())
response = self.con.get(url, params=params)
if not response:
return iter(())
data = response.json()
# Everything received from cloud must be passed as self._cloud_data_key
items = (
self._classifier(item)(parent=self, **{self._cloud_data_key: item})
for item in data.get('value', []))
next_link = data.get(NEXT_LINK_KEYWORD, None)
if batch and next_link:
return Pagination(parent=self, data=items,
constructor=self._classifier,
next_link=next_link, limit=limit)
else:
return items
def create_child_folder(self, name, description=None):
""" Creates a Child Folder
:param str name: the name of the new child folder
:param str description: the description of the new child folder
:return: newly created folder
:rtype: drive.Folder
"""
if not self.object_id:
return None
url = self.build_url(
self._endpoints.get('list_items').format(id=self.object_id))
data = {'name': name, 'folder': {}}
if description:
data['description'] = description
response = self.con.post(url, data=data)
if not response:
return None
folder = response.json()
return self._classifier(folder)(parent=self,
**{self._cloud_data_key: folder})
def download_contents(self, to_folder=None):
""" This will download each file and folder sequentially.
Caution when downloading big folder structures
:param drive.Folder to_folder: folder where to store the contents
"""
to_folder = to_folder or Path()
if not to_folder.exists():
to_folder.mkdir()
for item in self.get_items(query=self.new_query().select('id', 'size')):
if item.is_folder and item.child_count > 0:
item.download_contents(to_folder=to_folder / item.name)
else:
item.download(to_folder)
def search(self, search_text, limit=None, *, query=None, order_by=None,
batch=None):
""" Search for DriveItems under this folder
The search API uses a search service under the covers,
which requires indexing of content.
As a result, there will be some time between creation of an item
and when it will appear in search results.
:param str search_text: The query text used to search for items.
Values may be matched across several fields including filename,
metadata, and file content.
:param int limit: max no. of folders to get. Over 999 uses batch.
:param query: applies a OData filter to the request
:type query: Query or str
:param order_by: orders the result set based on this condition
:type order_by: Query or str
:param int batch: batch size, retrieves items in
batches allowing to retrieve more items than the limit.
:return: list of items in this folder
:rtype: list[DriveItem] or Pagination
"""
if not isinstance(search_text, str) or not search_text:
raise ValueError('Provide a valid search_text')
url = self.build_url(
self._endpoints.get('search').format(id=self.object_id,
search_text=search_text))
if limit is None or limit > self.protocol.max_top_value:
batch = self.protocol.max_top_value
params = {'$top': batch if batch else limit}
if order_by:
params['$orderby'] = order_by
if query:
if query.has_filters:
warnings.warn(
'Filters are not allowed by the Api '
'Provider in this method')
query.clear_filters()
if isinstance(query, str):
params['$filter'] = query
else:
params.update(query.as_params())
response = self.con.get(url, params=params)
if not response:
return iter(())
data = response.json()
# Everything received from cloud must be passed as self._cloud_data_key
items = (
self._classifier(item)(parent=self, **{self._cloud_data_key: item})
for item in data.get('value', []))
next_link = data.get(NEXT_LINK_KEYWORD, None)
if batch and next_link:
return Pagination(parent=self, data=items,
constructor=self._classifier,
next_link=next_link, limit=limit)
else:
return items
def upload_file(self, item, chunk_size=DEFAULT_UPLOAD_CHUNK_SIZE):
""" Uploads a file
:param item: path to the item you want to upload
:type item: str or Path
:param chunk_size: Only applies if file is bigger than 4MB.
Chunk size for uploads. Must be a multiple of 327.680 bytes
:return: uploaded file
:rtype: DriveItem
"""
if item is None:
raise ValueError('Item must be a valid path to file')
item = Path(item) if not isinstance(item, Path) else item
if not item.exists():
raise ValueError('Item must exist')
if not item.is_file():
raise ValueError('Item must be a file')
file_size = item.stat().st_size
if file_size <= UPLOAD_SIZE_LIMIT_SIMPLE:
# Simple Upload
url = self.build_url(
self._endpoints.get('simple_upload').format(id=self.object_id,
filename=quote(item.name)))
# headers = {'Content-type': 'text/plain'}
headers = {'Content-type': 'application/octet-stream'}
# headers = None
with item.open(mode='rb') as file:
data = file.read()
response = self.con.put(url, headers=headers, data=data)
if not response:
return None
data = response.json()
return self._classifier(data)(parent=self,
**{self._cloud_data_key: data})
else:
# Resumable Upload
url = self.build_url(
self._endpoints.get('create_upload_session').format(
id=self.object_id, filename=quote(item.name)))
response = self.con.post(url)
if not response:
return None
data = response.json()
upload_url = data.get(self._cc('uploadUrl'), None)
if upload_url is None:
log.error('Create upload session response without '
'upload_url for file {}'.format(item.name))
return None
current_bytes = 0
with item.open(mode='rb') as file:
while True:
data = file.read(chunk_size)
if not data:
break
transfer_bytes = len(data)
headers = {
'Content-type': 'application/octet-stream',
'Content-Length': str(len(data)),
'Content-Range': 'bytes {}-{}/{}'
''.format(current_bytes,
current_bytes +
transfer_bytes - 1,
file_size)
}
current_bytes += transfer_bytes
# this request mut NOT send the authorization header.
# so we use a naive simple request.
response = self.con.naive_request(upload_url, 'PUT',
data=data,
headers=headers)
if not response:
return None
if response.status_code != 202:
# file is completed
data = response.json()
return self._classifier(data)(parent=self, **{
self._cloud_data_key: data})
class Drive(ApiComponent):
""" A Drive representation.
A Drive is a Container of Folders and Files and act as a root item """
_endpoints = {
'default_drive': '/drive',
'get_drive': '/drives/{id}',
'get_root_item_default': '/drive/root',
'get_root_item': '/drives/{id}/root',
'list_items_default': '/drive/root/children',
'list_items': '/drives/{id}/root/children',
'get_item_default': '/drive/items/{item_id}',
'get_item': '/drives/{id}/items/{item_id}',
'get_item_by_path_default': '/drive/root:{item_path}',
'get_item_by_path': '/drives/{id}/root:{item_path}',
'recent_default': '/drive/recent',
'recent': '/drives/{id}/recent',
'shared_with_me_default': '/drive/sharedWithMe',
'shared_with_me': '/drives/{id}/sharedWithMe',
'get_special_default': '/drive/special/{name}',
'get_special': '/drives/{id}/special/{name}',
'search_default': "/drive/search(q='{search_text}')",
'search': "/drives/{id}/search(q='{search_text}')",
}
def __init__(self, *, parent=None, con=None, **kwargs):
""" Create a drive representation
:param parent: parent for this operation
:type parent: Drive or Storage
:param Connection con: connection to use if no parent specified
:param Protocol protocol: protocol to use if no parent specified
(kwargs)
:param str main_resource: use this resource instead of parent resource
(kwargs)
"""
if parent and con:
raise ValueError('Need a parent or a connection but not both')
self.con = parent.con if parent else con
self.parent = parent if isinstance(parent, Drive) else None
# Choose the main_resource passed in kwargs over parent main_resource
main_resource = kwargs.pop('main_resource', None) or (
getattr(parent, 'main_resource', None) if parent else None)
super().__init__(
protocol=parent.protocol if parent else kwargs.get('protocol'),
main_resource=main_resource)
self._update_data(kwargs)
def _update_data(self, data):
cloud_data = data.get(self._cloud_data_key, {})
self.object_id = cloud_data.get(self._cc('id'))
# Fallback to manual drive
self.name = cloud_data.get(self._cc('name'), data.get('name',
''))
self.description = cloud_data.get(self._cc('description'))
self.drive_type = cloud_data.get(self._cc('driveType'))
self.web_url = cloud_data.get(self._cc('webUrl'))
owner = cloud_data.get(self._cc('owner'), {}).get('user', None)
self.owner = Contact(con=self.con, protocol=self.protocol,
**{self._cloud_data_key: owner}) if owner else None
self.quota = cloud_data.get(self._cc('quota')) # dict
created = cloud_data.get(self._cc('createdDateTime'), None)
modified = cloud_data.get(self._cc('lastModifiedDateTime'), None)
local_tz = self.protocol.timezone
self.created = parse(created).astimezone(local_tz) if created else None
self.modified = parse(modified).astimezone(
local_tz) if modified else None
def __str__(self):
return self.__repr__()
def __repr__(self):
return 'Drive: {}'.format(
self.name or self.object_id or 'Default Drive')
def get_root_folder(self):
""" Returns the Root Folder of this drive
:return: Root Folder
:rtype: DriveItem
"""
if self.object_id:
# reference the current drive_id
url = self.build_url(
self._endpoints.get('get_root_item').format(id=self.object_id))
else:
# we don't know the drive_id so go to the default drive
url = self.build_url(self._endpoints.get('get_root_item_default'))
response = self.con.get(url)
if not response:
return None
data = response.json()
# Everything received from cloud must be passed as self._cloud_data_key
return self._classifier(data)(parent=self,
**{self._cloud_data_key: data})
def _base_get_list(self, url, limit=None, *, query=None, order_by=None,
batch=None):
""" Returns a collection of drive items """
if limit is None or limit > self.protocol.max_top_value:
batch = self.protocol.max_top_value
params = {'$top': batch if batch else limit}
if order_by:
params['$orderby'] = order_by
if query:
if query.has_filters:
warnings.warn(
'Filters are not allowed by the Api Provider '
'in this method')
query.clear_filters()
if isinstance(query, str):
params['$filter'] = query
else:
params.update(query.as_params())
response = self.con.get(url, params=params)
if not response:
return iter(())
data = response.json()
# Everything received from cloud must be passed as self._cloud_data_key
items = (
self._classifier(item)(parent=self, **{self._cloud_data_key: item})
for item in data.get('value', []))
next_link = data.get(NEXT_LINK_KEYWORD, None)
if batch and next_link:
return Pagination(parent=self, data=items,
constructor=self._classifier,
next_link=next_link, limit=limit)
else:
return items
def get_items(self, limit=None, *, query=None, order_by=None, batch=None):
""" Returns a collection of drive items from the root folder
:param int limit: max no. of items to get. Over 999 uses batch.
:param query: applies a OData filter to the request
:type query: Query or str
:param order_by: orders the result set based on this condition
:type order_by: Query or str
:param int batch: batch size, retrieves items in
batches allowing to retrieve more items than the limit.
:return: list of items in this folder
:rtype: list[DriveItem] or Pagination
"""
if self.object_id:
# reference the current drive_id
url = self.build_url(
self._endpoints.get('list_items').format(id=self.object_id))
else:
# we don't know the drive_id so go to the default
url = self.build_url(self._endpoints.get('list_items_default'))
return self._base_get_list(url, limit=limit, query=query,
order_by=order_by, batch=batch)
def get_recent(self, limit=None, *, query=None, order_by=None, batch=None):
""" Returns a collection of recently used DriveItems
:param int limit: max no. of items to get. Over 999 uses batch.
:param query: applies a OData filter to the request
:type query: Query or str
:param order_by: orders the result set based on this condition
:type order_by: Query or str
:param int batch: batch size, retrieves items in
batches allowing to retrieve more items than the limit.
:return: list of items in this folder
:rtype: list[DriveItem] or Pagination
"""
if self.object_id:
# reference the current drive_id
url = self.build_url(
self._endpoints.get('recent').format(id=self.object_id))
else:
# we don't know the drive_id so go to the default
url = self.build_url(self._endpoints.get('recent_default'))
return self._base_get_list(url, limit=limit, query=query,
order_by=order_by, batch=batch)
def get_shared_with_me(self, limit=None, *, query=None, order_by=None,
batch=None):
""" Returns a collection of DriveItems shared with me
:param int limit: max no. of items to get. Over 999 uses batch.
:param query: applies a OData filter to the request
:type query: Query or str
:param order_by: orders the result set based on this condition
:type order_by: Query or str
:param int batch: batch size, retrieves items in
batches allowing to retrieve more items than the limit.
:return: list of items in this folder
:rtype: list[DriveItem] or Pagination
"""
if self.object_id:
# reference the current drive_id
url = self.build_url(
self._endpoints.get('shared_with_me').format(id=self.object_id))
else:
# we don't know the drive_id so go to the default
url = self.build_url(self._endpoints.get('shared_with_me_default'))
return self._base_get_list(url, limit=limit, query=query,
order_by=order_by, batch=batch)
def get_item(self, item_id):
""" Returns a DriveItem by it's Id
:return: one item
:rtype: DriveItem
"""
if self.object_id:
# reference the current drive_id
url = self.build_url(
self._endpoints.get('get_item').format(id=self.object_id,
item_id=item_id))
else:
# we don't know the drive_id so go to the default drive
url = self.build_url(
self._endpoints.get('get_item_default').format(item_id=item_id))
response = self.con.get(url)
if not response:
return None
data = response.json()
# Everything received from cloud must be passed as self._cloud_data_key
return self._classifier(data)(parent=self,
**{self._cloud_data_key: data})
def get_item_by_path(self, item_path):
""" Returns a DriveItem by it's path: /path/to/file
:return: one item
:rtype: DriveItem
"""
if self.object_id:
# reference the current drive_id
url = self.build_url(
self._endpoints.get('get_item_by_path').format(id=self.object_id,
item_path=item_path))
else:
# we don't know the drive_id so go to the default drive
url = self.build_url(
self._endpoints.get('get_item_by_path_default').format(item_path=item_path))
response = self.con.get(url)
if not response:
return None
data = response.json()
# Everything received from cloud must be passed as self._cloud_data_key
return self._classifier(data)(parent=self,
**{self._cloud_data_key: data})
def get_special_folder(self, name):
""" Returns the specified Special Folder
:return: a special Folder
:rtype: drive.Folder
"""
name = name if \
isinstance(name, OneDriveWellKnowFolderNames) \
else OneDriveWellKnowFolderNames(name.lower())
name = name.value
if self.object_id:
# reference the current drive_id
url = self.build_url(
self._endpoints.get('get_special').format(id=self.object_id,
name=name))
else:
# we don't know the drive_id so go to the default
url = self.build_url(
self._endpoints.get('get_special_default').format(name=name))
response = self.con.get(url)
if not response:
return None
data = response.json()
# Everything received from cloud must be passed as self._cloud_data_key
return self._classifier(data)(parent=self,
**{self._cloud_data_key: data})
@staticmethod
def _classifier(item):
""" Subclass to change factory classes """
if 'folder' in item:
return Folder
elif 'image' in item:
return Image
elif 'photo' in item:
return Photo
else:
return File
def refresh(self):
""" Updates this drive with data from the server
:return: Success / Failure
:rtype: bool
"""
if self.object_id is None:
url = self.build_url(self._endpoints.get('default_drive'))
else:
url = self.build_url(
self._endpoints.get('get_drive').format(id=self.object_id))
response = self.con.get(url)
if not response:
return False
drive = response.json()
self._update_data({self._cloud_data_key: drive})
return True
def search(self, search_text, limit=None, *, query=None, order_by=None,
batch=None):
""" Search for DriveItems under this drive.
Your app can search more broadly to include items shared with the
current user.
To broaden the search scope, use this search instead the Folder Search.
The search API uses a search service under the covers, which requires
indexing of content.
As a result, there will be some time between creation of an
item and when it will appear in search results.
:param str search_text: The query text used to search for items.
Values may be matched across several fields including filename,
metadata, and file content.
:param int limit: max no. of items to get. Over 999 uses batch.
:param query: applies a OData filter to the request
:type query: Query or str
:param order_by: orders the result set based on this condition
:type order_by: Query or str
:param int batch: batch size, retrieves items in
batches allowing to retrieve more items than the limit.
:return: list of items in this folder
:rtype: list[DriveItem] or Pagination
"""
if not isinstance(search_text, str) or not search_text:
raise ValueError('Provide a valid search_text')
if self.object_id is None:
url = self.build_url(self._endpoints.get('search_default').format(
search_text=search_text))
else:
url = self.build_url(
self._endpoints.get('search').format(id=self.object_id,
search_text=search_text))
if limit is None or limit > self.protocol.max_top_value:
batch = self.protocol.max_top_value
params = {'$top': batch if batch else limit}
if order_by:
params['$orderby'] = order_by
if query:
if query.has_filters:
warnings.warn(
'Filters are not allowed by the Api Provider '
'in this method')
query.clear_filters()
if isinstance(query, str):
params['$filter'] = query
else:
params.update(query.as_params())
response = self.con.get(url, params=params)
if not response:
return iter(())
data = response.json()
# Everything received from cloud must be passed as self._cloud_data_key
items = (
self._classifier(item)(parent=self, **{self._cloud_data_key: item})
for item in data.get('value', []))
next_link = data.get(NEXT_LINK_KEYWORD, None)
if batch and next_link:
return Pagination(parent=self, data=items,
constructor=self._classifier,
next_link=next_link, limit=limit)
else:
return items
class Storage(ApiComponent):
""" Parent Class that holds drives """
_endpoints = {
'default_drive': '/drive',
'get_drive': '/drives/{id}',
'list_drives': '/drives',
}
drive_constructor = Drive
def __init__(self, *, parent=None, con=None, **kwargs):
""" Create a storage representation
:param parent: parent for this operation
:type parent: Account
:param Connection con: connection to use if no parent specified
:param Protocol protocol: protocol to use if no parent specified
(kwargs)
:param str main_resource: use this resource instead of parent resource
(kwargs)
"""
if parent and con:
raise ValueError('Need a parent or a connection but not both')
self.con = parent.con if parent else con
# Choose the main_resource passed in kwargs over parent main_resource
main_resource = kwargs.pop('main_resource', None) or (
getattr(parent, 'main_resource', None) if parent else None)
super().__init__(
protocol=parent.protocol if parent else kwargs.get('protocol'),
main_resource=main_resource)
def __str__(self):
return self.__repr__()
def __repr__(self):
return 'Storage for resource: {}'.format(self.main_resource)
def get_default_drive(self, request_drive=False):
""" Returns a Drive instance
:param request_drive: True will make an api call to retrieve the drive
data
:return: default One Drive
:rtype: Drive
"""
if request_drive is False:
return Drive(con=self.con, protocol=self.protocol,
main_resource=self.main_resource, name='Default Drive')
url = self.build_url(self._endpoints.get('default_drive'))
response = self.con.get(url)
if not response:
return None
drive = response.json()
# Everything received from cloud must be passed as self._cloud_data_key
return self.drive_constructor(con=self.con, protocol=self.protocol,
main_resource=self.main_resource,
**{self._cloud_data_key: drive})
def get_drive(self, drive_id):
""" Returns a Drive instance
:param drive_id: the drive_id to be retrieved
:return: Drive for the id
:rtype: Drive
"""
if not drive_id:
return None
url = self.build_url(
self._endpoints.get('get_drive').format(id=drive_id))
response = self.con.get(url)
if not response:
return None
drive = response.json()
# Everything received from cloud must be passed as self._cloud_data_key
return self.drive_constructor(con=self.con, protocol=self.protocol,
main_resource=self.main_resource,
**{self._cloud_data_key: drive})
def get_drives(self, limit=None, *, query=None, order_by=None,
batch=None):
""" Returns a collection of drives
:param int limit: max no. of items to get. Over 999 uses batch.
:param query: applies a OData filter to the request
:type query: Query or str
:param order_by: orders the result set based on this condition
:type order_by: Query or str
:param int batch: batch size, retrieves items in
batches allowing to retrieve more items than the limit.
:return: list of drives in this Storage
:rtype: list[Drive] or Pagination
"""
url = self.build_url(self._endpoints.get('list_drives'))
if limit is None or limit > self.protocol.max_top_value:
batch = self.protocol.max_top_value
params = {'$top': batch if batch else limit}
if order_by:
params['$orderby'] = order_by
if query:
if isinstance(query, str):
params['$filter'] = query
else:
params.update(query.as_params())
response = self.con.get(url, params=params)
if not response:
return []
data = response.json()
# Everything received from cloud must be passed as self._cloud_data_key
drives = [self.drive_constructor(parent=self, **{self._cloud_data_key: drive}) for
drive in data.get('value', [])]
next_link = data.get(NEXT_LINK_KEYWORD, None)
if batch and next_link:
return Pagination(parent=self, data=drives, constructor=self.drive_constructor,
next_link=next_link, limit=limit)
else:
return drives
| 36.821389 | 92 | 0.577239 |
204a9dae555e8b94b1ad26ba3a89d291fb2723b6 | 1,608 | py | Python | tests/test_merge.py | Be5yond/testtp | abefbb7e9d9e086f372c247df5df00713294f841 | [
"Apache-2.0"
] | 2 | 2020-12-15T03:01:39.000Z | 2021-01-04T05:51:39.000Z | tests/test_merge.py | Be5yond/testtp | abefbb7e9d9e086f372c247df5df00713294f841 | [
"Apache-2.0"
] | null | null | null | tests/test_merge.py | Be5yond/testtp | abefbb7e9d9e086f372c247df5df00713294f841 | [
"Apache-2.0"
] | null | null | null | import json
from copy import deepcopy
import testtp
merge = testtp.utils.merge
DATA = {
'a': 1,
'b': 'strgs',
'c': [{'type': 'a'}, {'type': 'b'}],
'd': {
'd1': [1,2,3],
'd2': 123,
'd3': {'k': 'v'}
},
'e': True
}
def test_schema_equal():
schema = {
'a': 1,
'b': 'strgs',
'c': [{'type': 'a'}, {'type': 'b'}],
'd': {
'd1': [1,2,3],
'd2': 123,
'd3': {'k': 'v'}
},
'e': True
}
ret = merge(deepcopy(DATA), schema)
print(json.dumps(ret, indent=4))
def test_schema_check_datatype():
schema = {
'a': int,
'b': str,
'c': list,
'd': dict
}
ret = merge(deepcopy(DATA), schema)
print(json.dumps(ret, indent=4))
def test_schema_check_part():
schema = {
'c': [dict],
'd': {'d2': int}
}
ret = merge(deepcopy(DATA), schema)
print(json.dumps(ret, indent=4))
def test_schema_custom_function():
def le_100(i):
return i < 100
schema = {
'a': le_100
}
ret = merge(deepcopy(DATA), schema)
print(json.dumps(ret, indent=4))
def test_schema_custom_method():
class Checker:
@staticmethod
def le_100(i):
return i < 100
schema = {
'a': Checker.le_100
}
ret = merge(deepcopy(DATA), schema)
print(json.dumps(ret, indent=4))
def test_schema_addtion_checkpoint():
schema = {
'a': ''
}
ret = merge(deepcopy(DATA), schema)
print(json.dumps(ret, indent=4))
# test_schema_custom_method()
| 20.1 | 44 | 0.49005 |
cb2bdc6b83d00092da195f03fe0e9f1c711a9a8c | 519 | py | Python | main_page/urls.py | slusarczyk41/my_django_website | 1ae95297a1a5901a57f858cca1cf90fbd8c2dfb1 | [
"MIT"
] | null | null | null | main_page/urls.py | slusarczyk41/my_django_website | 1ae95297a1a5901a57f858cca1cf90fbd8c2dfb1 | [
"MIT"
] | null | null | null | main_page/urls.py | slusarczyk41/my_django_website | 1ae95297a1a5901a57f858cca1cf90fbd8c2dfb1 | [
"MIT"
] | null | null | null | from django.urls import path
from . import views
app_name = 'main_page'
urlpatterns = [
path('', views.index, name='index'),
path('services/', views.services, name='services'),
path('about/', views.about, name='about'),
path('contact/', views.contact, name='contact'),
path('valuation/', views.valuation, name='valuation'),
path('contact_endpoint/', views.contact_endpoint, name='contact_endpoint'),
path('download_cv_endpoint/', views.download_cv_endpoint, name='download_cv_endpoint'),
] | 37.071429 | 91 | 0.699422 |
fedd9bdeb6f2c4998b627d11f67593f879664eca | 5,031 | py | Python | test/functional/feature_versionbits_warning.py | BitcoinReload/BitcoinReload | c927ca366ba769e33903b8e4f90d364c74e5e590 | [
"MIT"
] | 1 | 2022-03-23T00:32:26.000Z | 2022-03-23T00:32:26.000Z | test/functional/feature_versionbits_warning.py | BitcoinReload/BitcoinReload | c927ca366ba769e33903b8e4f90d364c74e5e590 | [
"MIT"
] | null | null | null | test/functional/feature_versionbits_warning.py | BitcoinReload/BitcoinReload | c927ca366ba769e33903b8e4f90d364c74e5e590 | [
"MIT"
] | null | null | null | #!/usr/bin/env python3
# Copyright (c) 2016-2019 The Bitcoin Core developers
# Distributed under the MIT software license, see the accompanying
# file COPYING or http://www.opensource.org/licenses/mit-license.php.
"""Test version bits warning system.
Generate chains with block versions that appear to be signalling unknown
soft-forks, and test that warning alerts are generated.
"""
import os
import re
from test_framework.blocktools import create_block, create_coinbase
from test_framework.messages import msg_block
from test_framework.p2p import P2PInterface
from test_framework.test_framework import BitcoinReloadTestFramework
VB_PERIOD = 144 # versionbits period length for regtest
VB_THRESHOLD = 108 # versionbits activation threshold for regtest
VB_TOP_BITS = 0x20000000
VB_UNKNOWN_BIT = 27 # Choose a bit unassigned to any deployment
VB_UNKNOWN_VERSION = VB_TOP_BITS | (1 << VB_UNKNOWN_BIT)
WARN_UNKNOWN_RULES_ACTIVE = "unknown new rules activated (versionbit {})".format(VB_UNKNOWN_BIT)
VB_PATTERN = re.compile("Warning: unknown new rules activated.*versionbit")
class VersionBitsWarningTest(BitcoinReloadTestFramework):
def set_test_params(self):
self.setup_clean_chain = True
self.num_nodes = 1
def setup_network(self):
self.alert_filename = os.path.join(self.options.tmpdir, "alert.txt")
# Open and close to create zero-length file
with open(self.alert_filename, 'w', encoding='utf8'):
pass
self.extra_args = [["-alertnotify=echo %s >> \"" + self.alert_filename + "\""]]
self.setup_nodes()
def send_blocks_with_version(self, peer, numblocks, version):
"""Send numblocks blocks to peer with version set"""
tip = self.nodes[0].getbestblockhash()
height = self.nodes[0].getblockcount()
block_time = self.nodes[0].getblockheader(tip)["time"] + 1
tip = int(tip, 16)
for _ in range(numblocks):
block = create_block(tip, create_coinbase(height + 1), block_time)
block.nVersion = version
block.solve()
peer.send_message(msg_block(block))
block_time += 1
height += 1
tip = block.sha256
peer.sync_with_ping()
def versionbits_in_alert_file(self):
"""Test that the versionbits warning has been written to the alert file."""
alert_text = open(self.alert_filename, 'r', encoding='utf8').read()
return VB_PATTERN.search(alert_text) is not None
def run_test(self):
node = self.nodes[0]
peer = node.add_p2p_connection(P2PInterface())
node_deterministic_address = node.get_deterministic_priv_key().address
# Mine one period worth of blocks
node.generatetoaddress(VB_PERIOD, node_deterministic_address)
self.log.info("Check that there is no warning if previous VB_BLOCKS have <VB_THRESHOLD blocks with unknown versionbits version.")
# Build one period of blocks with < VB_THRESHOLD blocks signaling some unknown bit
self.send_blocks_with_version(peer, VB_THRESHOLD - 1, VB_UNKNOWN_VERSION)
node.generatetoaddress(VB_PERIOD - VB_THRESHOLD + 1, node_deterministic_address)
# Check that we're not getting any versionbit-related errors in get*info()
assert not VB_PATTERN.match(node.getmininginfo()["warnings"])
assert not VB_PATTERN.match(node.getnetworkinfo()["warnings"])
# Build one period of blocks with VB_THRESHOLD blocks signaling some unknown bit
self.send_blocks_with_version(peer, VB_THRESHOLD, VB_UNKNOWN_VERSION)
node.generatetoaddress(VB_PERIOD - VB_THRESHOLD, node_deterministic_address)
self.log.info("Check that there is a warning if previous VB_BLOCKS have >=VB_THRESHOLD blocks with unknown versionbits version.")
# Mine a period worth of expected blocks so the generic block-version warning
# is cleared. This will move the versionbit state to ACTIVE.
node.generatetoaddress(VB_PERIOD, node_deterministic_address)
# Stop-start the node. This is required because bitcoinreloadd will only warn once about unknown versions or unknown rules activating.
self.restart_node(0)
# Generating one block guarantees that we'll get out of IBD
node.generatetoaddress(1, node_deterministic_address)
self.wait_until(lambda: not node.getblockchaininfo()['initialblockdownload'])
# Generating one more block will be enough to generate an error.
node.generatetoaddress(1, node_deterministic_address)
# Check that get*info() shows the versionbits unknown rules warning
assert WARN_UNKNOWN_RULES_ACTIVE in node.getmininginfo()["warnings"]
assert WARN_UNKNOWN_RULES_ACTIVE in node.getnetworkinfo()["warnings"]
# Check that the alert file shows the versionbits unknown rules warning
self.wait_until(lambda: self.versionbits_in_alert_file())
if __name__ == '__main__':
VersionBitsWarningTest().main()
| 48.375 | 142 | 0.719141 |
fbf0e14576e50aaa801de5dc50f88606553add6d | 5,637 | py | Python | tweet_engine.py | alybel/vrbase | c01a8b641e3e6c011fe32e343fa01eca01f4c7c6 | [
"MIT"
] | null | null | null | tweet_engine.py | alybel/vrbase | c01a8b641e3e6c011fe32e343fa01eca01f4c7c6 | [
"MIT"
] | null | null | null | tweet_engine.py | alybel/vrbase | c01a8b641e3e6c011fe32e343fa01eca01f4c7c6 | [
"MIT"
] | null | null | null | #! /usr/bin/python -u
import sys
import os.path
import time
valureach_ops_path = "/home/vr/valureach_ops"
sys.path.append("%s/bluebird" % valureach_ops_path)
import load_config
import bblib as bbl
import random
import vr_main
import subprocess
def rtime():
return int(random.random() * 10 * 60)
def tweet_account(account_name=""):
print "starting", account_name
account_path = "%s/accounts/%s/" % (valureach_ops_path, account_name)
if not os.path.isfile("%s/tweet.py" % account_path):
return False
sys.path.append(account_path)
cfg = load_config.load_config(account_name)
import tweet
bbl.set_cfg(cfg)
auth, api = bbl.connect_app_to_twitter()
#Check for correct frequency
freq = tweet.freq * 60
logfile = "%stweet_engine.log" % account_path
if os.path.isfile(logfile):
with open(logfile, 'r') as f:
for line in f:
if "tweetid" in line:
tweet_id =line.strip("\n").split(":")[1]
try:
api.destroy_status(tweet_id)
print account_name,"tweet destroyed in ramping up", tweet_id
except:
pass
#reset the logfile
f = open(logfile, "w")
f.close()
while True:
#Tweet own tweets
sel_tweet = random.choice(tweet.tweets)
print "selected tweet:", sel_tweet
res = api.update_status(sel_tweet)
with open(logfile, 'a') as f:
f.write("tweetid:%d\n" % res.id)
print account_name, "tweeted:", sel_tweet
time.sleep(rtime())
#retweet tweets from friended accounts
for account in tweet.watch_account:
print "seeking for tweets to retweet in", account
apath = "%s/accounts/%s/" % (valureach_ops_path, account)
lf = "%stweet_engine.log"%apath
if not os.path.isfile(lf):
continue
with open(lf,'r') as f2:
for line in f2:
print line
if "tweetid" in line:
tweet_id = line.strip("\n").split(":")[1]
print "tweet_id", tweet_id
try:
api.retweet(tweet_id)
print "retweeted", tweet_id
except Exception,e:
print e
print "retweet not carried out", tweet_id
print "reached sleep point"
time.sleep(freq)
#remove own tweets
try:
api.destroy_status(res.id)
except:
pass
print account_name, "status deleted"
with open(logfile, 'a') as f:
f.write("deleted-tweetiid:%d\n"%res.id)
f = open(logfile, "w")
f.close()
time.sleep(rtime())
def clean_account(account, api = None):
"""
not used yet
"""
if not api:
api = get_account_api(account)
account_path = "%s/accounts/%s/" % (valureach_ops_path, account_name)
logfile = "%stweet_engine.log"%account_path
if os.path.isfile(logfile):
with open(logfile, 'r') as f:
for line in f:
if "tweetid" in line:
tweet_id = line.strip("\n").split(":")[1]
try:
api.destroy_status(tweet_id)
print account_name,"tweet destroyed in ramping up", tweet_id
except:
pass
def get_account_api(account):
account_path = "%s/accounts/%s/" % (valureach_ops_path, account_name)
sys.path.append(account_path)
import config as cfg
bbl.set_cfg(cfg)
auth, api = bbl.connect_app_to_twitter()
return api
def start_account(account):
if os.path.isfile("accounts/%s/.tweet_engine_lock" % account):
print "tweet engine Account", account, "is locked. is already running?"
return False
print "starting account", account
with open("stdout/tweet_engine_%s.out" % account, "w") as f:
subprocess.Popen(["python", "tweet_engine.py", "%s" % account], stdout=f)
subprocess.call(["touch","accounts/%s/.tweet_engine_lock" % account])
return True
def stop_account(account):
procname = "tweet_engine.py"
subprocess.call(["rm","accounts/%s/.tweet_engine_lock" % account])
print "lockfile removed"
for proc in psutil.process_iter():
if proc.name() == procname and account in proc.cmdline()[-1]:
print "killing", proc.cmdline()
psutil.Process(proc.pid).kill()
return True
if not auto_call:
print "no running tweet engine proccess for account", account, "could be found"
return False
def remove_all_lockfiles():
accounts = vr_main.get_accounts()
for account in accounts:
subprocess.call(["rm","accounts/%s/.tweet_engine_lock" % account])
print "all tweet_engine lockfiles removed"
def start_all():
accounts = vr_main.get_accounts()
for account in accounts:
start_account(account)
if __name__ == "__main__":
args = sys.argv
if not len(args) == 2:
print "usage: tweet_engine.py <account_name>"
print "other options: all, stopall"
sys.exit()
print "starting for account", args[1]
if args[1] == "all":
start_all()
elif args[1] == "stopall":
subprocess.call(["killall", "tweet_engine.py"])
subprocess.call(["killall", "tweet_engine.py"])
remove_all_lockfiles()
else:
tweet_account(args[1])
| 34.796296 | 87 | 0.573532 |
6e3169d0e8d671dc0eb5c30e1fe8db3a520d546f | 118 | py | Python | mujoco_parallel/__init__.py | thanhbok26b/mujoco-rewards-landscape-visualization | c1a95b38a0ea03468bbbb7ce013eff37ccd67101 | [
"MIT"
] | null | null | null | mujoco_parallel/__init__.py | thanhbok26b/mujoco-rewards-landscape-visualization | c1a95b38a0ea03468bbbb7ce013eff37ccd67101 | [
"MIT"
] | null | null | null | mujoco_parallel/__init__.py | thanhbok26b/mujoco-rewards-landscape-visualization | c1a95b38a0ea03468bbbb7ce013eff37ccd67101 | [
"MIT"
] | null | null | null | from .mujoco_parallel import MujocoParallel
from .worker_manager import WorkerManager
from .config import benchmarks
| 23.6 | 43 | 0.864407 |
827735cfbb792b3d588edfd9636ab425182577de | 1,539 | py | Python | backend/tests/test_api_admin.py | kevinmonisit/shrunk | 55106356735c3491f8c8c0774f5ae500ba1c970a | [
"MIT"
] | 13 | 2015-05-08T00:26:23.000Z | 2021-07-28T15:42:10.000Z | backend/tests/test_api_admin.py | kevinmonisit/shrunk | 55106356735c3491f8c8c0774f5ae500ba1c970a | [
"MIT"
] | 68 | 2015-01-12T20:27:44.000Z | 2021-05-17T19:08:05.000Z | backend/tests/test_api_admin.py | kevinmonisit/shrunk | 55106356735c3491f8c8c0774f5ae500ba1c970a | [
"MIT"
] | 7 | 2015-08-05T20:31:20.000Z | 2022-01-28T21:14:06.000Z | # admin.get_endpoint_stats GET /api/v1/admin/stats/endpoint
# admin.get_overview_stats POST /api/v1/admin/stats/overview
from datetime import datetime, timezone, timedelta
from werkzeug.test import Client
from util import dev_login
def test_endpoint_stats(client: Client) -> None:
with dev_login(client, 'admin'):
resp = client.get('/api/v1/admin/stats/endpoint')
assert resp.status_code == 200
assert 'stats' in resp.json
assert isinstance(resp.json['stats'], list)
def test_endpoint_stats_unauthorized(client: Client) -> None:
with dev_login(client, 'user'):
resp = client.get('/api/v1/admin/stats/endpoint')
assert resp.status_code == 403
def test_overview_stats(client: Client) -> None:
with dev_login(client, 'admin'):
resp = client.post('/api/v1/admin/stats/overview', json={})
assert resp.status_code == 200
def test_overview_stats_range(client: Client) -> None:
with dev_login(client, 'admin'):
end = datetime.now(timezone.utc)
begin = end - timedelta(days=2)
resp = client.post('/api/v1/admin/stats/overview', json={
'range': {
'begin': begin.isoformat(),
'end': end.isoformat(),
},
})
assert resp.status_code == 200
def test_overview_stats_unauthorized(client: Client) -> None:
with dev_login(client, 'user'):
resp = client.post('/api/v1/admin/stats/overview', json={})
assert resp.status_code == 403
| 32.0625 | 69 | 0.641975 |
ef072dc2734042c31d6d854b96644cc8d09645de | 30,675 | py | Python | tools/metrics/actions/extract_actions.py | zealoussnow/chromium | fd8a8914ca0183f0add65ae55f04e287543c7d4a | [
"BSD-3-Clause-No-Nuclear-License-2014",
"BSD-3-Clause"
] | 76 | 2020-09-02T03:05:41.000Z | 2022-03-30T04:40:55.000Z | tools/metrics/actions/extract_actions.py | zealoussnow/chromium | fd8a8914ca0183f0add65ae55f04e287543c7d4a | [
"BSD-3-Clause-No-Nuclear-License-2014",
"BSD-3-Clause"
] | 45 | 2020-09-02T03:21:37.000Z | 2022-03-31T22:19:45.000Z | tools/metrics/actions/extract_actions.py | zealoussnow/chromium | fd8a8914ca0183f0add65ae55f04e287543c7d4a | [
"BSD-3-Clause-No-Nuclear-License-2014",
"BSD-3-Clause"
] | 8 | 2020-07-22T18:49:18.000Z | 2022-02-08T10:27:16.000Z | #!/usr/bin/env python
#
# 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.
"""Extract UserMetrics "actions" strings from the Chrome source.
This program generates the list of known actions we expect to see in the
user behavior logs. It walks the Chrome source, looking for calls to
UserMetrics functions, extracting actions and warning on improper calls,
as well as generating the lists of possible actions in situations where
there are many possible actions.
See also:
base/metrics/user_metrics.h
After extracting all actions, the content will go through a pretty print
function to make sure it's well formatted. If the file content needs to be
changed, a window will be prompted asking for user's consent. The old version
will also be saved in a backup file.
"""
from __future__ import print_function
__author__ = 'evanm (Evan Martin)'
import logging
import os
import re
import shutil
import sys
from xml.dom import minidom
if sys.version_info.major == 2:
from HTMLParser import HTMLParser
else:
from html.parser import HTMLParser
import action_utils
import actions_model
# Import the metrics/common module for pretty print xml.
sys.path.append(os.path.join(os.path.dirname(__file__), '..', 'common'))
import presubmit_util
import diff_util
import pretty_print_xml
USER_METRICS_ACTION_RE = re.compile(r"""
[^a-zA-Z] # Preceded by a non-alphabetical character.
(?: # Begin non-capturing group.
UserMetricsAction # C++ / Objective C function name.
| # or...
RecordUserAction\.record # Java function name.
) # End non-capturing group.
\( # Opening parenthesis.
\s* # Any amount of whitespace, including new lines.
(.+?) # A sequence of characters for the param.
\) # Closing parenthesis.
""",
re.VERBOSE | re.DOTALL # Verbose syntax and makes . also match new lines.
)
USER_METRICS_ACTION_RE_JS = re.compile(r"""
chrome\.send # Start of function call.
\( # Opening parenthesis.
\s* # Any amount of whitespace, including new lines.
# WebUI message handled by CoreOptionsHandler.
'coreOptionsUserMetricsAction'
, # Separator after first parameter.
\s* # Any amount of whitespace, including new lines.
\[ # Opening bracket for arguments for C++ function.
\s* # Any amount of whitespace, including new lines.
(.+?) # A sequence of characters for the param.
\s* # Any amount of whitespace, including new lines.
\] # Closing bracket.
\s* # Any amount of whitespace, including new lines.
\) # Closing parenthesis.
""",
re.VERBOSE | re.DOTALL # Verbose syntax and makes . also match new lines.
)
USER_METRICS_ACTION_RE_DEVTOOLS = re.compile(r"""
InspectorFrontendHost\.recordUserMetricsAction # Start of function call.
\( # Opening parenthesis.
\s* # Any amount of whitespace, including new lines.
(.+?) # A sequence of characters for the param.
\s* # Any amount of whitespace, including new lines.
\) # Closing parenthesis.
""",
re.VERBOSE | re.DOTALL # Verbose syntax and makes . also match new lines.
)
COMPUTED_ACTION_RE = re.compile(r'RecordComputedAction')
QUOTED_STRING_RE = re.compile(r"""('[^']+'|"[^"]+")$""")
# Files that are known to use content::RecordComputedAction(), which means
# they require special handling code in this script.
# To add a new file, add it to this list and add the appropriate logic to
# generate the known actions to AddComputedActions() below.
KNOWN_COMPUTED_USERS = (
'back_forward_menu_model.cc',
'options_page_view.cc',
'render_view_host.cc', # called using webkit identifiers
'user_metrics.cc', # method definition
'new_tab_ui.cc', # most visited clicks 1-9
'extension_metrics_module.cc', # extensions hook for user metrics
'language_options_handler_common.cc', # languages and input methods in CrOS
'cros_language_options_handler.cc', # languages and input methods in CrOS
'external_metrics.cc', # see AddChromeOSActions()
'core_options_handler.cc', # see AddWebUIActions()
'browser_render_process_host.cc', # see AddRendererActions()
'render_thread_impl.cc', # impl of RenderThread::RecordComputedAction()
'render_process_host_impl.cc', # browser side impl for
# RenderThread::RecordComputedAction()
'mock_render_thread.cc', # mock of RenderThread::RecordComputedAction()
'ppb_pdf_impl.cc', # see AddClosedSourceActions()
'pepper_pdf_host.cc', # see AddClosedSourceActions()
'record_user_action.cc', # see RecordUserAction.java
'blink_platform_impl.cc', # see WebKit/public/platform/Platform.h
'devtools_ui_bindings.cc', # see AddDevToolsActions()
'sharing_hub_bubble_controller.cc', # share targets
'sharing_hub_sub_menu_model.cc', # share targets
)
# Language codes used in Chrome. The list should be updated when a new
# language is added to app/l10n_util.cc, as follows:
#
# % (cat app/l10n_util.cc | \
# perl -n0e 'print $1 if /kAcceptLanguageList.*?\{(.*?)\}/s' | \
# perl -nle 'print $1, if /"(.*)"/'; echo 'es-419') | \
# sort | perl -pe "s/(.*)\n/'\$1', /" | \
# fold -w75 -s | perl -pe 's/^/ /;s/ $//'; echo
#
# The script extracts language codes from kAcceptLanguageList, but es-419
# (Spanish in Latin America) is an exception.
LANGUAGE_CODES = (
'af', 'am', 'ar', 'az', 'be', 'bg', 'bh', 'bn', 'br', 'bs', 'ca', 'co',
'cs', 'cy', 'da', 'de', 'de-AT', 'de-CH', 'de-DE', 'el', 'en', 'en-AU',
'en-CA', 'en-GB', 'en-NZ', 'en-US', 'en-ZA', 'eo', 'es', 'es-419', 'et',
'eu', 'fa', 'fi', 'fil', 'fo', 'fr', 'fr-CA', 'fr-CH', 'fr-FR', 'fy',
'ga', 'gd', 'gl', 'gn', 'gu', 'ha', 'haw', 'he', 'hi', 'hr', 'hu', 'hy',
'ia', 'id', 'is', 'it', 'it-CH', 'it-IT', 'ja', 'jw', 'ka', 'kk', 'km',
'kn', 'ko', 'ku', 'ky', 'la', 'ln', 'lo', 'lt', 'lv', 'mk', 'ml', 'mn',
'mo', 'mr', 'ms', 'mt', 'nb', 'ne', 'nl', 'nn', 'no', 'oc', 'om', 'or',
'pa', 'pl', 'ps', 'pt', 'pt-BR', 'pt-PT', 'qu', 'rm', 'ro', 'ru', 'sd',
'sh', 'si', 'sk', 'sl', 'sn', 'so', 'sq', 'sr', 'st', 'su', 'sv', 'sw',
'ta', 'te', 'tg', 'th', 'ti', 'tk', 'to', 'tr', 'tt', 'tw', 'ug', 'uk',
'ur', 'uz', 'vi', 'xh', 'yi', 'yo', 'zh', 'zh-CN', 'zh-TW', 'zu',
)
# Input method IDs used in Chrome OS. The list should be updated when a
# new input method is added to
# chromeos/ime/input_methods.txt in the Chrome tree, as
# follows:
#
# % sort chromeos/ime/input_methods.txt | \
# perl -ne "print \"'\$1', \" if /^([^#]+?)\s/" | \
# fold -w75 -s | perl -pe 's/^/ /;s/ $//'; echo
#
# The script extracts input method IDs from input_methods.txt.
INPUT_METHOD_IDS = (
'xkb:am:phonetic:arm', 'xkb:be::fra', 'xkb:be::ger', 'xkb:be::nld',
'xkb:bg::bul', 'xkb:bg:phonetic:bul', 'xkb:br::por', 'xkb:by::bel',
'xkb:ca::fra', 'xkb:ca:eng:eng', 'xkb:ca:multix:fra', 'xkb:ch::ger',
'xkb:ch:fr:fra', 'xkb:cz::cze', 'xkb:cz:qwerty:cze', 'xkb:de::ger',
'xkb:de:neo:ger', 'xkb:dk::dan', 'xkb:ee::est', 'xkb:es::spa',
'xkb:es:cat:cat', 'xkb:fi::fin', 'xkb:fr::fra', 'xkb:gb:dvorak:eng',
'xkb:gb:extd:eng', 'xkb:ge::geo', 'xkb:gr::gre', 'xkb:hr::scr',
'xkb:hu::hun', 'xkb:il::heb', 'xkb:is::ice', 'xkb:it::ita', 'xkb:jp::jpn',
'xkb:latam::spa', 'xkb:lt::lit', 'xkb:lv:apostrophe:lav', 'xkb:mn::mon',
'xkb:no::nob', 'xkb:pl::pol', 'xkb:pt::por', 'xkb:ro::rum', 'xkb:rs::srp',
'xkb:ru::rus', 'xkb:ru:phonetic:rus', 'xkb:se::swe', 'xkb:si::slv',
'xkb:sk::slo', 'xkb:tr::tur', 'xkb:ua::ukr', 'xkb:us::eng',
'xkb:us:altgr-intl:eng', 'xkb:us:colemak:eng', 'xkb:us:dvorak:eng',
'xkb:us:intl:eng',
)
# The path to the root of the repository.
REPOSITORY_ROOT = os.path.join(os.path.dirname(__file__), '..', '..', '..')
number_of_files_total = 0
# Tags that need to be inserted to each 'action' tag and their default content.
TAGS = {'description': 'Please enter the description of the metric.',
'owner': ('Please list the metric\'s owners. Add more owner tags as '
'needed.')}
SHARE_TARGETS = {
'CopyURLSelected', 'QRCodeSelected', 'ScreenshotSelected',
'SendTabToSelfSelected', 'CastSelected', 'SavePageSelected',
'ThirdPartyAppSelected'
}
def AddComputedActions(actions):
"""Add computed actions to the actions list.
Arguments:
actions: set of actions to add to.
"""
# Actions for back_forward_menu_model.cc.
for dir in ('BackMenu_', 'ForwardMenu_'):
actions.add(dir + 'ShowFullHistory')
actions.add(dir + 'Popup')
for i in range(1, 20):
actions.add(dir + 'HistoryClick' + str(i))
actions.add(dir + 'ChapterClick' + str(i))
# Actions for new_tab_ui.cc.
for i in range(1, 10):
actions.add('MostVisited%d' % i)
# Actions for language_options_handler.cc (Chrome OS specific).
for input_method_id in INPUT_METHOD_IDS:
actions.add('LanguageOptions_DisableInputMethod_%s' % input_method_id)
actions.add('LanguageOptions_EnableInputMethod_%s' % input_method_id)
for language_code in LANGUAGE_CODES:
actions.add('LanguageOptions_UiLanguageChange_%s' % language_code)
actions.add('LanguageOptions_SpellCheckLanguageChange_%s' % language_code)
# Actions for sharing_hub_bubble_controller.cc and
# sharing_hub_sub_menu_model.cc.
for share_target in SHARE_TARGETS:
actions.add('SharingHubDesktop.%s' % share_target)
def AddPDFPluginActions(actions):
"""Add actions that are sent by the PDF plugin.
Arguments
actions: set of actions to add to.
"""
actions.add('PDF.LoadFailure')
actions.add('PDF.LoadSuccess')
actions.add('PDF.PreviewDocumentLoadFailure')
actions.add('PDF.PrintPage')
actions.add('PDF.ZoomFromBrowser')
actions.add('PDF_Unsupported_3D')
actions.add('PDF_Unsupported_Attachment')
actions.add('PDF_Unsupported_Bookmarks')
actions.add('PDF_Unsupported_Digital_Signature')
actions.add('PDF_Unsupported_Movie')
actions.add('PDF_Unsupported_Portfolios_Packages')
actions.add('PDF_Unsupported_Rights_Management')
actions.add('PDF_Unsupported_Screen')
actions.add('PDF_Unsupported_Shared_Form')
actions.add('PDF_Unsupported_Shared_Review')
actions.add('PDF_Unsupported_Sound')
actions.add('PDF_Unsupported_XFA')
def AddBookmarkManagerActions(actions):
"""Add actions that are used by BookmarkManager.
Arguments
actions: set of actions to add to.
"""
actions.add('BookmarkManager_Command_AddPage')
actions.add('BookmarkManager_Command_Copy')
actions.add('BookmarkManager_Command_Cut')
actions.add('BookmarkManager_Command_Delete')
actions.add('BookmarkManager_Command_Edit')
actions.add('BookmarkManager_Command_Export')
actions.add('BookmarkManager_Command_Import')
actions.add('BookmarkManager_Command_NewFolder')
actions.add('BookmarkManager_Command_OpenIncognito')
actions.add('BookmarkManager_Command_OpenInNewTab')
actions.add('BookmarkManager_Command_OpenInNewWindow')
actions.add('BookmarkManager_Command_OpenInSame')
actions.add('BookmarkManager_Command_Paste')
actions.add('BookmarkManager_Command_ShowInFolder')
actions.add('BookmarkManager_Command_Sort')
actions.add('BookmarkManager_Command_UndoDelete')
actions.add('BookmarkManager_Command_UndoGlobal')
actions.add('BookmarkManager_Command_UndoNone')
actions.add('BookmarkManager_NavigateTo_BookmarkBar')
actions.add('BookmarkManager_NavigateTo_Mobile')
actions.add('BookmarkManager_NavigateTo_Other')
actions.add('BookmarkManager_NavigateTo_Recent')
actions.add('BookmarkManager_NavigateTo_Search')
actions.add('BookmarkManager_NavigateTo_SubFolder')
def AddChromeOSActions(actions):
"""Add actions reported by non-Chrome processes in Chrome OS.
Arguments:
actions: set of actions to add to.
"""
# Actions sent by Chrome OS update engine.
actions.add('Updater.ServerCertificateChanged')
actions.add('Updater.ServerCertificateFailed')
def AddExtensionActions(actions):
"""Add actions reported by extensions via chrome.metricsPrivate API.
Arguments:
actions: set of actions to add to.
"""
# Actions sent by Chrome OS File Browser.
actions.add('FileBrowser.CreateNewFolder')
actions.add('FileBrowser.PhotoEditor.Edit')
actions.add('FileBrowser.PhotoEditor.View')
actions.add('FileBrowser.SuggestApps.ShowDialog')
# Actions sent by Google Now client.
actions.add('GoogleNow.MessageClicked')
actions.add('GoogleNow.ButtonClicked0')
actions.add('GoogleNow.ButtonClicked1')
actions.add('GoogleNow.Dismissed')
# Actions sent by Chrome Connectivity Diagnostics.
actions.add('ConnectivityDiagnostics.LaunchSource.OfflineChromeOS')
actions.add('ConnectivityDiagnostics.LaunchSource.WebStore')
actions.add('ConnectivityDiagnostics.UA.LogsShown')
actions.add('ConnectivityDiagnostics.UA.PassingTestsShown')
actions.add('ConnectivityDiagnostics.UA.SettingsShown')
actions.add('ConnectivityDiagnostics.UA.TestResultExpanded')
actions.add('ConnectivityDiagnostics.UA.TestSuiteRun')
class InvalidStatementException(Exception):
"""Indicates an invalid statement was found."""
class ActionNameFinder:
"""Helper class to find action names in source code file."""
def __init__(self, path, contents, action_re):
self.__path = path
self.__pos = 0
self.__contents = contents
self.__action_re = action_re
def FindNextAction(self):
"""Finds the next action name in the file.
Returns:
The name of the action found or None if there are no more actions.
Raises:
InvalidStatementException if the next action statement is invalid
and could not be parsed. There may still be more actions in the file,
so FindNextAction() can continue to be called to find following ones.
"""
match = self.__action_re.search(self.__contents, pos=self.__pos)
if not match:
return None
match_start = match.start()
self.__pos = match.end()
match = QUOTED_STRING_RE.match(match.group(1))
if not match:
if self.__action_re == USER_METRICS_ACTION_RE_JS:
return None
self._RaiseException(match_start, self.__pos)
# Remove surrounding quotation marks.
return match.group(1)[1:-1]
def _RaiseException(self, match_start, match_end):
"""Raises an InvalidStatementException for the specified code range."""
line_number = self.__contents.count('\n', 0, match_start) + 1
# Add 1 to |match_start| since the RE checks the preceding character.
statement = self.__contents[match_start + 1:match_end]
raise InvalidStatementException(
'%s uses UserMetricsAction incorrectly on line %d:\n%s' %
(self.__path, line_number, statement))
def GrepForActions(path, actions):
"""Grep a source file for calls to UserMetrics functions.
Arguments:
path: path to the file
actions: set of actions to add to
"""
global number_of_files_total
number_of_files_total = number_of_files_total + 1
# Check the extension, using the regular expression for C++ syntax by default.
ext = os.path.splitext(path)[1].lower()
if ext == '.js':
action_re = USER_METRICS_ACTION_RE_JS
else:
action_re = USER_METRICS_ACTION_RE
finder = ActionNameFinder(path, open(path).read(), action_re)
while True:
try:
action_name = finder.FindNextAction()
if not action_name:
break
actions.add(action_name)
except InvalidStatementException as e:
logging.warning(str(e))
if action_re != USER_METRICS_ACTION_RE:
return
line_number = 0
for line in open(path):
line_number = line_number + 1
if COMPUTED_ACTION_RE.search(line):
# Warn if this file shouldn't be calling RecordComputedAction.
if os.path.basename(path) not in KNOWN_COMPUTED_USERS:
logging.warning('%s has RecordComputedAction statement on line %d' %
(path, line_number))
class WebUIActionsParser(HTMLParser):
"""Parses an HTML file, looking for all tags with a 'metric' attribute.
Adds user actions corresponding to any metrics found.
Arguments:
actions: set of actions to add to
"""
def __init__(self, actions):
HTMLParser.__init__(self)
self.actions = actions
def handle_starttag(self, tag, attrs):
# We only care to examine tags that have a 'metric' attribute.
attrs = dict(attrs)
if not 'metric' in attrs:
return
# Boolean metrics have two corresponding actions. All other metrics have
# just one corresponding action. By default, we check the 'dataType'
# attribute.
is_boolean = ('dataType' in attrs and attrs['dataType'] == 'boolean')
if 'type' in attrs and attrs['type'] in ('checkbox', 'radio'):
if attrs['type'] == 'checkbox':
is_boolean = True
else:
# Radio buttons are boolean if and only if their values are 'true' or
# 'false'.
assert(attrs['type'] == 'radio')
if 'value' in attrs and attrs['value'] in ['true', 'false']:
is_boolean = True
if is_boolean:
self.actions.add(attrs['metric'] + '_Enable')
self.actions.add(attrs['metric'] + '_Disable')
else:
self.actions.add(attrs['metric'])
def GrepForWebUIActions(path, actions):
"""Grep a WebUI source file for elements with associated metrics.
Arguments:
path: path to the file
actions: set of actions to add to
"""
close_called = False
try:
parser = WebUIActionsParser(actions)
parser.feed(open(path).read())
# An exception can be thrown by parser.close(), so do it in the try to
# ensure the path of the file being parsed gets printed if that happens.
close_called = True
parser.close()
except Exception as e:
print("Error encountered for path %s" % path)
raise e
finally:
if not close_called:
parser.close()
def GrepForDevToolsActions(path, actions):
"""Grep a DevTools source file for calls to UserMetrics functions.
Arguments:
path: path to the file
actions: set of actions to add to
"""
global number_of_files_total
number_of_files_total = number_of_files_total + 1
ext = os.path.splitext(path)[1].lower()
if ext != '.js':
return
finder = ActionNameFinder(path, open(path).read(),
USER_METRICS_ACTION_RE_DEVTOOLS)
while True:
try:
action_name = finder.FindNextAction()
if not action_name:
break
actions.add(action_name)
except InvalidStatementException as e:
logging.warning(str(e))
def WalkDirectory(root_path, actions, extensions, callback):
for path, dirs, files in os.walk(root_path):
if '.svn' in dirs:
dirs.remove('.svn')
if '.git' in dirs:
dirs.remove('.git')
for file in files:
filename, ext = os.path.splitext(file)
if ext in extensions and not filename.endswith('test'):
callback(os.path.join(path, file), actions)
def AddLiteralActions(actions):
"""Add literal actions specified via calls to UserMetrics functions.
Arguments:
actions: set of actions to add to.
"""
EXTENSIONS = ('.cc', '.cpp', '.mm', '.c', '.m', '.java')
# Walk the source tree to process all files.
ash_root = os.path.normpath(os.path.join(REPOSITORY_ROOT, 'ash'))
WalkDirectory(ash_root, actions, EXTENSIONS, GrepForActions)
chrome_root = os.path.normpath(os.path.join(REPOSITORY_ROOT, 'chrome'))
WalkDirectory(chrome_root, actions, EXTENSIONS, GrepForActions)
content_root = os.path.normpath(os.path.join(REPOSITORY_ROOT, 'content'))
WalkDirectory(content_root, actions, EXTENSIONS, GrepForActions)
components_root = os.path.normpath(os.path.join(REPOSITORY_ROOT,
'components'))
WalkDirectory(components_root, actions, EXTENSIONS, GrepForActions)
net_root = os.path.normpath(os.path.join(REPOSITORY_ROOT, 'net'))
WalkDirectory(net_root, actions, EXTENSIONS, GrepForActions)
webkit_root = os.path.normpath(os.path.join(REPOSITORY_ROOT, 'webkit'))
WalkDirectory(os.path.join(webkit_root, 'glue'), actions, EXTENSIONS,
GrepForActions)
WalkDirectory(os.path.join(webkit_root, 'port'), actions, EXTENSIONS,
GrepForActions)
webkit_core_root = os.path.normpath(
os.path.join(REPOSITORY_ROOT,
'third_party/blink/renderer/core'))
WalkDirectory(webkit_core_root, actions, EXTENSIONS, GrepForActions)
def AddWebUIActions(actions):
"""Add user actions defined in WebUI files.
Arguments:
actions: set of actions to add to.
"""
resources_root = os.path.join(REPOSITORY_ROOT, 'chrome', 'browser',
'resources')
WalkDirectory(resources_root, actions, ('.html'), GrepForWebUIActions)
WalkDirectory(resources_root, actions, ('.js'), GrepForActions)
def AddDevToolsActions(actions):
"""Add user actions defined in DevTools frontend files.
Arguments:
actions: set of actions to add to.
"""
resources_root = os.path.join(REPOSITORY_ROOT, 'third_party', 'blink',
'renderer', 'devtools', 'front_end')
WalkDirectory(resources_root, actions, ('.js'), GrepForDevToolsActions)
def AddHistoryPageActions(actions):
"""Add actions that are used in History page.
Arguments
actions: set of actions to add to.
"""
actions.add('HistoryPage_BookmarkStarClicked')
actions.add('HistoryPage_EntryMenuRemoveFromHistory')
actions.add('HistoryPage_EntryLinkClick')
actions.add('HistoryPage_EntryLinkRightClick')
actions.add('HistoryPage_SearchResultClick')
actions.add('HistoryPage_EntryMenuShowMoreFromSite')
actions.add('HistoryPage_NewestHistoryClick')
actions.add('HistoryPage_NewerHistoryClick')
actions.add('HistoryPage_OlderHistoryClick')
actions.add('HistoryPage_Search')
actions.add('HistoryPage_InitClearBrowsingData')
actions.add('HistoryPage_RemoveSelected')
actions.add('HistoryPage_SearchResultRemove')
actions.add('HistoryPage_ConfirmRemoveSelected')
actions.add('HistoryPage_CancelRemoveSelected')
def AddAutomaticResetBannerActions(actions):
"""Add actions that are used for the automatic profile settings reset banners
in chrome://settings.
Arguments
actions: set of actions to add to.
"""
# These actions relate to the the automatic settings reset banner shown as
# a result of the reset prompt.
actions.add('AutomaticReset_WebUIBanner_BannerShown')
actions.add('AutomaticReset_WebUIBanner_ManuallyClosed')
actions.add('AutomaticReset_WebUIBanner_ResetClicked')
# These actions relate to the the automatic settings reset banner shown as
# a result of settings hardening.
actions.add('AutomaticSettingsReset_WebUIBanner_BannerShown')
actions.add('AutomaticSettingsReset_WebUIBanner_ManuallyClosed')
actions.add('AutomaticSettingsReset_WebUIBanner_LearnMoreClicked')
actions.add('AutomaticSettingsReset_WebUIBanner_ResetClicked')
class Error(Exception):
pass
def _ExtractText(parent_dom, tag_name):
"""Extract the text enclosed by |tag_name| under |parent_dom|
Args:
parent_dom: The parent Element under which text node is searched for.
tag_name: The name of the tag which contains a text node.
Returns:
A (list of) string enclosed by |tag_name| under |parent_dom|.
"""
texts = []
for child_dom in parent_dom.getElementsByTagName(tag_name):
text_dom = child_dom.childNodes
if text_dom.length != 1:
raise Error('More than 1 child node exists under %s' % tag_name)
if text_dom[0].nodeType != minidom.Node.TEXT_NODE:
raise Error('%s\'s child node is not a text node.' % tag_name)
texts.append(text_dom[0].data)
return texts
def ParseActionFile(file_content):
"""Parse the XML data currently stored in the file.
Args:
file_content: a string containing the action XML file content.
Returns:
(actions_dict, comment_nodes, suffixes):
- actions_dict is a dict from user action name to Action object.
- comment_nodes is a list of top-level comment nodes.
- suffixes is a list of <action-suffix> DOM elements.
"""
dom = minidom.parseString(file_content)
comment_nodes = []
# Get top-level comments. It is assumed that all comments are placed before
# <actions> tag. Therefore the loop will stop if it encounters a non-comment
# node.
for node in dom.childNodes:
if node.nodeType == minidom.Node.COMMENT_NODE:
comment_nodes.append(node)
else:
break
actions_dict = {}
# Get each user action data.
for action_dom in dom.getElementsByTagName('action'):
action_name = action_dom.getAttribute('name')
not_user_triggered = bool(action_dom.getAttribute('not_user_triggered'))
owners = _ExtractText(action_dom, 'owner')
# There is only one description for each user action. Get the first element
# of the returned list.
description_list = _ExtractText(action_dom, 'description')
if len(description_list) > 1:
logging.error('User action "%s" has more than one description. Exactly '
'one description is needed for each user action. Please '
'fix.', action_name)
sys.exit(1)
description = description_list[0] if description_list else None
# There is at most one obsolete tag for each user action.
obsolete_list = _ExtractText(action_dom, 'obsolete')
if len(obsolete_list) > 1:
logging.error('User action "%s" has more than one obsolete tag. At most '
'one obsolete tag can be added for each user action. Please'
' fix.', action_name)
sys.exit(1)
obsolete = obsolete_list[0] if obsolete_list else None
actions_dict[action_name] = action_utils.Action(action_name, description,
owners, not_user_triggered, obsolete)
suffixes = dom.getElementsByTagName('action-suffix')
action_utils.CreateActionsFromSuffixes(actions_dict, suffixes)
return actions_dict, comment_nodes, suffixes
def _CreateActionTag(doc, action):
"""Create a new action tag.
Format of an action tag:
<action name="name" not_user_triggered="true">
<obsolete>Deprecated.</obsolete>
<owner>Owner</owner>
<description>Description.</description>
</action>
not_user_triggered is an optional attribute. If set, it implies that the
belonging action is not a user action. A user action is an action that
is logged exactly once right after a user has made an action.
<obsolete> is an optional tag. It's added to actions that are no longer used
any more.
If action_name is in actions_dict, the values to be inserted are based on the
corresponding Action object. If action_name is not in actions_dict, the
default value from TAGS is used.
Args:
doc: The document under which the new action tag is created.
action: An Action object representing the data to be inserted.
Returns:
An action tag Element with proper children elements, or None if a tag should
not be created for this action (e.g. if it comes from a suffix).
"""
if action.from_suffix:
return None
action_dom = doc.createElement('action')
action_dom.setAttribute('name', action.name)
# Add not_user_triggered attribute.
if action.not_user_triggered:
action_dom.setAttribute('not_user_triggered', 'true')
# Create obsolete tag.
if action.obsolete:
obsolete_dom = doc.createElement('obsolete')
action_dom.appendChild(obsolete_dom)
obsolete_dom.appendChild(doc.createTextNode(action.obsolete))
# Create owner tag.
if action.owners:
# If owners for this action is not None, use the stored value. Otherwise,
# use the default value.
for owner in action.owners:
owner_dom = doc.createElement('owner')
owner_dom.appendChild(doc.createTextNode(owner))
action_dom.appendChild(owner_dom)
else:
# Use default value.
owner_dom = doc.createElement('owner')
owner_dom.appendChild(doc.createTextNode(TAGS.get('owner', '')))
action_dom.appendChild(owner_dom)
# Create description tag.
description_dom = doc.createElement('description')
action_dom.appendChild(description_dom)
if action.description:
# If description for this action is not None, use the store value.
# Otherwise, use the default value.
description_dom.appendChild(doc.createTextNode(action.description))
else:
description_dom.appendChild(doc.createTextNode(
TAGS.get('description', '')))
return action_dom
def PrettyPrint(actions_dict, comment_nodes, suffixes):
"""Given a list of actions, create a well-printed minidom document.
Args:
actions_dict: A mappting from action name to Action object.
comment_nodes: A list of top-level comment nodes.
suffixes: A list of <action-suffix> tags to be appended as-is.
Returns:
A well-printed minidom document that represents the input action data.
"""
doc = minidom.Document()
# Attach top-level comments.
for node in comment_nodes:
doc.appendChild(node)
actions_element = doc.createElement('actions')
doc.appendChild(actions_element)
# Attach action node based on updated |actions_dict|.
for _, action in sorted(actions_dict.items()):
action_tag = _CreateActionTag(doc, action)
if action_tag:
actions_element.appendChild(action_tag)
for suffix_tag in suffixes:
actions_element.appendChild(suffix_tag)
return actions_model.PrettifyTree(doc)
def UpdateXml(original_xml):
actions_dict, comment_nodes, suffixes = ParseActionFile(original_xml)
actions = set()
AddComputedActions(actions)
AddWebUIActions(actions)
AddDevToolsActions(actions)
AddLiteralActions(actions)
AddAutomaticResetBannerActions(actions)
AddBookmarkManagerActions(actions)
AddChromeOSActions(actions)
AddExtensionActions(actions)
AddHistoryPageActions(actions)
AddPDFPluginActions(actions)
for action_name in actions:
if action_name not in actions_dict:
actions_dict[action_name] = action_utils.Action(action_name, None, [])
return PrettyPrint(actions_dict, comment_nodes, suffixes)
def main(argv):
presubmit_util.DoPresubmitMain(
argv,
'actions.xml',
'actions.old.xml',
UpdateXml,
script_name='extract_actions.py')
if '__main__' == __name__:
sys.exit(main(sys.argv))
| 37.591912 | 80 | 0.695485 |
302eeff0c32a51ff3b5056053c74952623c31ef1 | 4,216 | py | Python | bin/newmap.py | sympolite/very-small-roguelike | cd3635cfe0db65a1df69fa5c1b72a4f794444449 | [
"MIT"
] | 1 | 2021-04-06T04:32:49.000Z | 2021-04-06T04:32:49.000Z | bin/newmap.py | sympolite/very-small-roguelike | cd3635cfe0db65a1df69fa5c1b72a4f794444449 | [
"MIT"
] | null | null | null | bin/newmap.py | sympolite/very-small-roguelike | cd3635cfe0db65a1df69fa5c1b72a4f794444449 | [
"MIT"
] | 1 | 2021-04-06T04:32:52.000Z | 2021-04-06T04:32:52.000Z | import tdl
import sys
palettes = {'grey': ((45, 45, 45), (0, 0, 0), (180, 180, 180), (90, 90, 90))}
MAXWIDTH = 9
MAXHEIGHT = 9
MINWIDTH = 3
MINHEIGHT = 3
FOV_ALGO = 'BASIC'
FOV_LIGHT_WALLS = True
class Tile:
# a tile of the map and its properties
def __init__(self, blocked, block_sight=None):
self.blocked = blocked
self.explored = False
# by default, if a tile is blocked, it also blocks sight
if block_sight is None:
block_sight = blocked
self.block_sight = block_sight
class GameMap:
def __init__(self, map_id, con):
self.map_id = str(map_id)
self.con = con
self.palette = palettes['grey']
self.width, self.height = 0
self.tilemap = []
self.tilemap = [[]]
self.load_tilemap()
self.create_tilemap()
def in_map_bounds(self, x, y):
if 0 < x < self.width-1 and 0 < y < self.height-1:
return True
return False
def load_tilemap(self):
width = 0
height = 0
map_data = []
try:
with open('maps/'+self.map_id+'.map') as map_file:
for counter, line in enumerate(map_file):
if 0 < len(line) <= MAXWIDTH and height <= MAXHEIGHT:
map_data.append(line)
self.height += 1
if counter == 0:
self.width = len(line)
elif len(line) != self.width:
raise ValueError
else:
pass
else:
raise ValueError
for datum in map_data:
for char in datum:
if char != "-" or char != "#":
raise ValueError
self.create_tilemap(map_data)
except IOError:
print("ERROR - .map file not found")
sys.exit(1)
except ValueError:
print("ERROR - Invalid map data")
sys.exit(1)
def create_tilemap(self, mapdata):
for i, row in enumerate(mapdata):
for j, column in enumerate(mapdata[i]):
if column == '-':
self.tilemap[j][i] = Tile(False)
elif column == '#':
self.tilemap[j][i] = Tile(True)
else:
pass
def is_visible_tile(self, x, y):
if self.in_map_bounds(x, y):
if self.tilemap[x][y].blocked:
return False
elif self.tilemap[x][y].block_sight:
return False
else:
return True
else:
return False
def draw(self, player):
visible_tiles = tdl.map.quick_fov(player.x, player.y,
self.is_visible_tile,
fov=FOV_ALGO,
radius=player.sight,
lightWalls=False)
for y in range(self.height):
for x in range(self.width):
#self.compute_fov(player)
visible = (x, y) in visible_tiles
wall = self.tilemap[x][y].block_sight
if not visible:
if self.tilemap[x][y].explored:
if wall:
self.con.draw_char(x, y, None, fg=None, bg=self.palette[1])
else:
self.con.draw_char(x, y, None, fg=None, bg=self.palette[0])
else:
if wall:
self.con.draw_char(x, y, None, fg=None, bg=self.palette[3])
else:
self.con.draw_char(x, y, None, fg=None, bg=self.palette[2])
self.tilemap[x][y].explored = True
def clear(self):
for y in range(self.height):
for x in range(self.width):
self.con.draw_char(x, y, ' ', fg=(0, 0, 0), bg=(0, 0, 0))
| 35.133333 | 88 | 0.446869 |
0fcf489f14e3b09b56d79865aa01194f384a99c3 | 160 | py | Python | tests/python/test_browser.py | mdp/rpaframework | d427a3a4b9ea360780e449ece2674e275060310e | [
"Apache-2.0"
] | 2 | 2021-04-17T17:24:20.000Z | 2021-04-18T18:09:54.000Z | packages/main/tests/python/test_browser.py | aikarjal/rpaframework | cd0599b33b7fcca3d43ea45116a43fc7507b73c9 | [
"Apache-2.0"
] | null | null | null | packages/main/tests/python/test_browser.py | aikarjal/rpaframework | cd0599b33b7fcca3d43ea45116a43fc7507b73c9 | [
"Apache-2.0"
] | 1 | 2021-02-11T21:00:11.000Z | 2021-02-11T21:00:11.000Z | from unittest import TestCase
class TestBrowserFunctionality(TestCase):
def test_import(self):
from RPA.Browser import Browser
Browser()
| 17.777778 | 41 | 0.71875 |
47ae17fb1c7800cad28eaf9509185c35ad8ebeb8 | 6,842 | py | Python | tests/test_dynamicbatching.py | terrorizer1980/ParlAI | f8fda24bd11804104b0a91aa84e170d3efbd8983 | [
"MIT"
] | 2 | 2020-08-27T05:21:14.000Z | 2020-09-29T14:34:09.000Z | tests/test_dynamicbatching.py | terrorizer1980/ParlAI | f8fda24bd11804104b0a91aa84e170d3efbd8983 | [
"MIT"
] | 316 | 2021-03-19T14:53:31.000Z | 2022-03-27T03:36:51.000Z | tests/test_dynamicbatching.py | terrorizer1980/ParlAI | f8fda24bd11804104b0a91aa84e170d3efbd8983 | [
"MIT"
] | 2 | 2020-10-29T18:14:33.000Z | 2020-11-07T09:46:23.000Z | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from parlai.core.opt import Opt
from parlai.tasks.integration_tests.agents import NUM_TEST, EXAMPLE_SIZE
from parlai.utils.conversations import Conversations
import parlai.utils.testing as testing_utils
import os
from typing import Dict, Any
import unittest
_TASK = 'integration_tests:variable_length'
# we don't need a real agent, since we're only checking the number examples
# is correct
_DEFAULT_OPTIONS = {
'dict_file': 'zoo:unittest/transformer_generator2/model.dict',
'dict_tokenizer': 'space',
'batchsize': 16,
'dynamic_batching': 'full',
'num_epochs': 1,
'truncate': 8,
'model': 'parlai.agents.test_agents.test_agents:SilentTorchAgent',
'task': _TASK,
}
_RANKER_OPTIONS = {
'dict_file': 'zoo:unittest/transformer_generator2/model.dict',
'dict_tokenizer': 'space',
'batchsize': 32,
'num_epochs': 0.1,
'n_layers': 1,
'n_heads': 1,
'candidates': 'batch',
'ffn_size': 4,
'embedding_size': 4,
'task': _TASK,
'truncate': 8,
'model': 'transformer/ranker',
}
# TODO tests to write:
# - multiple validation runs, streaming/not streaming
# - ranking model
class TestDynamicBatching(unittest.TestCase):
def _test_correct_processed(self, num_goal: int, **kwargs: Dict[str, Any]):
opt = Opt({**_DEFAULT_OPTIONS, **kwargs})
valid_report, test_report = testing_utils.train_model(opt)
self.assertEqual(valid_report['exs'], num_goal)
self.assertEqual(test_report['exs'], num_goal)
def test_no_truncate(self):
with self.assertRaises(ValueError):
testing_utils.train_model(Opt({**_DEFAULT_OPTIONS, **{'truncate': -1}}))
def test_no_batch_act(self):
"""
Fail when the agent doesn't support dynamic batching.
"""
with self.assertRaises(TypeError):
testing_utils.train_model(model='repeat_label', task=_TASK)
with self.assertRaises(TypeError):
testing_utils.eval_model(model='repeat_label', task=_TASK)
def test_ranking(self):
testing_utils.train_model(
Opt(datatype='train', dynamic_batching='full', **_RANKER_OPTIONS)
)
def test_ranking_streaming(self):
testing_utils.train_model(
Opt(datatype='train:stream', dynamic_batching='full', **_RANKER_OPTIONS)
)
def test_training(self):
self._test_correct_processed(NUM_TEST, datatype='train')
def test_streaming(self):
self._test_correct_processed(NUM_TEST, datatype='train:stream')
def test_multiworld(self):
self._test_correct_processed(
NUM_TEST + NUM_TEST * EXAMPLE_SIZE,
task='integration_tests:variable_length,integration_tests:multiturn',
)
def test_multiworld_stream(self):
self._test_correct_processed(
NUM_TEST + NUM_TEST * EXAMPLE_SIZE,
task='integration_tests:variable_length,integration_tests:multiturn',
datatype='train:stream',
)
def test_world_logging(self):
with testing_utils.tempdir() as tmpdir:
save_report = os.path.join(tmpdir, 'report')
testing_utils.eval_model(
dict(
model_file='zoo:unittest/transformer_generator2/model',
task='integration_tests:multiturn_candidate',
save_world_logs=True,
report_filename=save_report,
truncate=1024,
dynamic_batching='full',
batchsize=4,
)
)
convo_fle = (
str(save_report)
+ '_integration_tests:multiturn_candidate_replies.jsonl'
)
convos = Conversations(convo_fle)
for convo in convos:
self.assertEquals(len(convo), 2 * 4) # each episode is 4 turns
# now assert that they are all from the same dynamic batch index
dyn_batch_idx = convo[0]['dyn_batch_idx']
for i, turn in enumerate(convo):
if i % 2 == 0 and i > 0:
# we log the batch index in the teacher acts only
self.assertEquals(dyn_batch_idx, turn['dyn_batch_idx'])
def test_weird_batchsize(self):
# intentionally a difficult number
self._test_correct_processed(NUM_TEST, batchsize=7)
def test_batchsize4(self):
# intentionally an edgecase in the world
self._test_correct_processed(NUM_TEST, batchsize=4)
class TestBatchSort(unittest.TestCase):
def _test_correct_processed(self, num_goal: int, **kwargs: Dict[str, Any]):
opt = Opt({**_DEFAULT_OPTIONS, **kwargs})
opt['dynamic_batching'] = 'batchsort'
valid_report, test_report = testing_utils.train_model(opt)
self.assertEqual(valid_report['exs'], num_goal)
self.assertEqual(test_report['exs'], num_goal)
def test_no_batch_act(self):
"""
Fail when the agent doesn't support dynamic batching.
"""
with self.assertRaises(TypeError):
testing_utils.train_model(model='repeat_label', task=_TASK)
with self.assertRaises(TypeError):
testing_utils.eval_model(model='repeat_label', task=_TASK)
def test_ranking(self):
testing_utils.train_model(
Opt(datatype='train', dynamic_batching='batchsort', **_RANKER_OPTIONS)
)
def test_ranking_streaming(self):
testing_utils.train_model(
Opt(
datatype='train:stream', dynamic_batching='batchsort', **_RANKER_OPTIONS
)
)
def test_training(self):
self._test_correct_processed(NUM_TEST, datatype='train')
def test_streaming(self):
self._test_correct_processed(NUM_TEST, datatype='train:stream')
def test_multiworld(self):
self._test_correct_processed(
NUM_TEST + NUM_TEST * EXAMPLE_SIZE,
task='integration_tests:variable_length,integration_tests:multiturn',
)
def test_multiworld_stream(self):
self._test_correct_processed(
NUM_TEST + NUM_TEST * EXAMPLE_SIZE,
task='integration_tests:variable_length,integration_tests:multiturn',
datatype='train:stream',
)
def test_weird_batchsize(self):
# intentionally a difficult number
self._test_correct_processed(NUM_TEST, batchsize=7)
def test_batchsize4(self):
# intentionally an edgecase in the world
self._test_correct_processed(NUM_TEST, batchsize=4)
if __name__ == '__main__':
unittest.main()
| 34.38191 | 88 | 0.647033 |
1333ec44fb48dc1afc96258d5fd14bb02e79d81d | 566 | py | Python | checkout/migrations/0005_order_user_profile.py | vladoprea/dream-woollies | 7113400a03e4047312b88a3afff7e5969ff96f6b | [
"W3C",
"PostgreSQL"
] | null | null | null | checkout/migrations/0005_order_user_profile.py | vladoprea/dream-woollies | 7113400a03e4047312b88a3afff7e5969ff96f6b | [
"W3C",
"PostgreSQL"
] | 5 | 2021-06-04T23:31:01.000Z | 2021-09-22T19:18:34.000Z | checkout/migrations/0005_order_user_profile.py | vladoprea/dream-woollies | 7113400a03e4047312b88a3afff7e5969ff96f6b | [
"W3C",
"PostgreSQL"
] | 1 | 2020-08-17T14:27:29.000Z | 2020-08-17T14:27:29.000Z | # Generated by Django 3.0.7 on 2020-07-23 12:04
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('profiles', '0001_initial'),
('checkout', '0004_auto_20200723_1235'),
]
operations = [
migrations.AddField(
model_name='order',
name='user_profile',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='orders', to='profiles.UserProfile'),
),
]
| 26.952381 | 155 | 0.64841 |
596a942c40345e424ffbf90e7ddd80001482fddd | 7,337 | py | Python | pysnmp/EQLTAG-MIB.py | agustinhenze/mibs.snmplabs.com | 1fc5c07860542b89212f4c8ab807057d9a9206c7 | [
"Apache-2.0"
] | 11 | 2021-02-02T16:27:16.000Z | 2021-08-31T06:22:49.000Z | pysnmp/EQLTAG-MIB.py | agustinhenze/mibs.snmplabs.com | 1fc5c07860542b89212f4c8ab807057d9a9206c7 | [
"Apache-2.0"
] | 75 | 2021-02-24T17:30:31.000Z | 2021-12-08T00:01:18.000Z | pysnmp/EQLTAG-MIB.py | agustinhenze/mibs.snmplabs.com | 1fc5c07860542b89212f4c8ab807057d9a9206c7 | [
"Apache-2.0"
] | 10 | 2019-04-30T05:51:36.000Z | 2022-02-16T03:33:41.000Z | #
# PySNMP MIB module EQLTAG-MIB (http://snmplabs.com/pysmi)
# ASN.1 source file:///Users/davwang4/Dev/mibs.snmplabs.com/asn1/EQLTAG-MIB
# Produced by pysmi-0.3.4 at Mon Apr 29 18:51:22 2019
# On host DAVWANG4-M-1475 platform Darwin version 18.5.0 by user davwang4
# Using Python version 3.7.3 (default, Mar 27 2019, 09:23:15)
#
OctetString, ObjectIdentifier, Integer = mibBuilder.importSymbols("ASN1", "OctetString", "ObjectIdentifier", "Integer")
NamedValues, = mibBuilder.importSymbols("ASN1-ENUMERATION", "NamedValues")
ValueSizeConstraint, SingleValueConstraint, ValueRangeConstraint, ConstraintsIntersection, ConstraintsUnion = mibBuilder.importSymbols("ASN1-REFINEMENT", "ValueSizeConstraint", "SingleValueConstraint", "ValueRangeConstraint", "ConstraintsIntersection", "ConstraintsUnion")
eqlGroupId, eqlStorageGroupAdminAccountIndex, UTFString = mibBuilder.importSymbols("EQLGROUP-MIB", "eqlGroupId", "eqlStorageGroupAdminAccountIndex", "UTFString")
eqliscsiLocalMemberId, eqliscsiVolumeIndex = mibBuilder.importSymbols("EQLVOLUME-MIB", "eqliscsiLocalMemberId", "eqliscsiVolumeIndex")
equalLogic, = mibBuilder.importSymbols("EQUALLOGIC-SMI", "equalLogic")
NotificationGroup, ModuleCompliance = mibBuilder.importSymbols("SNMPv2-CONF", "NotificationGroup", "ModuleCompliance")
enterprises, NotificationType, Bits, MibIdentifier, Counter64, Gauge32, MibScalar, MibTable, MibTableRow, MibTableColumn, iso, ModuleIdentity, Counter32, TimeTicks, ObjectIdentity, IpAddress, Integer32, Unsigned32 = mibBuilder.importSymbols("SNMPv2-SMI", "enterprises", "NotificationType", "Bits", "MibIdentifier", "Counter64", "Gauge32", "MibScalar", "MibTable", "MibTableRow", "MibTableColumn", "iso", "ModuleIdentity", "Counter32", "TimeTicks", "ObjectIdentity", "IpAddress", "Integer32", "Unsigned32")
TextualConvention, DisplayString, TruthValue, RowPointer, RowStatus = mibBuilder.importSymbols("SNMPv2-TC", "TextualConvention", "DisplayString", "TruthValue", "RowPointer", "RowStatus")
eqltagModule = ModuleIdentity((1, 3, 6, 1, 4, 1, 12740, 23))
eqltagModule.setRevisions(('2011-10-02 00:00',))
if mibBuilder.loadTexts: eqltagModule.setLastUpdated('201403121459Z')
if mibBuilder.loadTexts: eqltagModule.setOrganization('EqualLogic Inc.')
eqltagObjects = MibIdentifier((1, 3, 6, 1, 4, 1, 12740, 23, 1))
eqltagNotifications = MibIdentifier((1, 3, 6, 1, 4, 1, 12740, 23, 2))
eqltagConformance = MibIdentifier((1, 3, 6, 1, 4, 1, 12740, 23, 3))
eqlTagTable = MibTable((1, 3, 6, 1, 4, 1, 12740, 23, 1, 1), )
if mibBuilder.loadTexts: eqlTagTable.setStatus('current')
eqlTagEntry = MibTableRow((1, 3, 6, 1, 4, 1, 12740, 23, 1, 1, 1), ).setIndexNames((0, "EQLTAG-MIB", "eqlTagType"), (0, "EQLTAG-MIB", "eqlTagIndex"))
if mibBuilder.loadTexts: eqlTagEntry.setStatus('current')
eqlTagType = MibTableColumn((1, 3, 6, 1, 4, 1, 12740, 23, 1, 1, 1, 1), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1))).clone(namedValues=NamedValues(("folder", 1))).clone(1))
if mibBuilder.loadTexts: eqlTagType.setStatus('current')
eqlTagIndex = MibTableColumn((1, 3, 6, 1, 4, 1, 12740, 23, 1, 1, 1, 2), Unsigned32())
if mibBuilder.loadTexts: eqlTagIndex.setStatus('current')
eqlTagRowStatus = MibTableColumn((1, 3, 6, 1, 4, 1, 12740, 23, 1, 1, 1, 3), RowStatus()).setMaxAccess("readcreate")
if mibBuilder.loadTexts: eqlTagRowStatus.setStatus('current')
eqlTagValue = MibTableColumn((1, 3, 6, 1, 4, 1, 12740, 23, 1, 1, 1, 4), UTFString().subtype(subtypeSpec=ValueSizeConstraint(0, 64))).setMaxAccess("readwrite")
if mibBuilder.loadTexts: eqlTagValue.setStatus('current')
eqlTagAdminAccountKey = MibTableColumn((1, 3, 6, 1, 4, 1, 12740, 23, 1, 1, 1, 5), Unsigned32()).setMaxAccess("readwrite")
if mibBuilder.loadTexts: eqlTagAdminAccountKey.setStatus('current')
eqlTagValueDescription = MibTableColumn((1, 3, 6, 1, 4, 1, 12740, 23, 1, 1, 1, 6), UTFString().subtype(subtypeSpec=ValueSizeConstraint(0, 128))).setMaxAccess("readwrite")
if mibBuilder.loadTexts: eqlTagValueDescription.setStatus('current')
eqlTagObjectTable = MibTable((1, 3, 6, 1, 4, 1, 12740, 23, 1, 2), )
if mibBuilder.loadTexts: eqlTagObjectTable.setStatus('current')
eqlTagObjectEntry = MibTableRow((1, 3, 6, 1, 4, 1, 12740, 23, 1, 2, 1), ).setIndexNames((0, "EQLTAG-MIB", "eqlTagType"), (0, "EQLTAG-MIB", "eqlTagIndex"), (0, "EQLTAG-MIB", "eqlTagObjectIndex"))
if mibBuilder.loadTexts: eqlTagObjectEntry.setStatus('current')
eqlTagObjectIndex = MibTableColumn((1, 3, 6, 1, 4, 1, 12740, 23, 1, 2, 1, 1), Unsigned32())
if mibBuilder.loadTexts: eqlTagObjectIndex.setStatus('current')
eqlTagObjectTaggedObjectPointer = MibTableColumn((1, 3, 6, 1, 4, 1, 12740, 23, 1, 2, 1, 2), RowPointer()).setMaxAccess("readwrite")
if mibBuilder.loadTexts: eqlTagObjectTaggedObjectPointer.setStatus('current')
eqlTagObjectRowStatus = MibTableColumn((1, 3, 6, 1, 4, 1, 12740, 23, 1, 2, 1, 3), RowStatus()).setMaxAccess("readcreate")
if mibBuilder.loadTexts: eqlTagObjectRowStatus.setStatus('current')
eqlAdminAccountTagTable = MibTable((1, 3, 6, 1, 4, 1, 12740, 23, 1, 3), )
if mibBuilder.loadTexts: eqlAdminAccountTagTable.setStatus('current')
eqlAdminAccountTagEntry = MibTableRow((1, 3, 6, 1, 4, 1, 12740, 23, 1, 3, 1), ).setIndexNames((0, "EQLGROUP-MIB", "eqlGroupId"), (0, "EQLGROUP-MIB", "eqlStorageGroupAdminAccountIndex"), (0, "EQLTAG-MIB", "eqlTagType"), (0, "EQLTAG-MIB", "eqlTagIndex"))
if mibBuilder.loadTexts: eqlAdminAccountTagEntry.setStatus('current')
eqlAdminAccountTagAccess = MibTableColumn((1, 3, 6, 1, 4, 1, 12740, 23, 1, 3, 1, 1), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2))).clone(namedValues=NamedValues(("read-only", 1), ("read-write", 2)))).setMaxAccess("readonly")
if mibBuilder.loadTexts: eqlAdminAccountTagAccess.setStatus('current')
eqlVolumeTagTable = MibTable((1, 3, 6, 1, 4, 1, 12740, 23, 1, 4), )
if mibBuilder.loadTexts: eqlVolumeTagTable.setStatus('current')
eqlVolumeTagEntry = MibTableRow((1, 3, 6, 1, 4, 1, 12740, 23, 1, 4, 1), ).setIndexNames((0, "EQLVOLUME-MIB", "eqliscsiLocalMemberId"), (0, "EQLVOLUME-MIB", "eqliscsiVolumeIndex"), (0, "EQLTAG-MIB", "eqlTagType"), (0, "EQLTAG-MIB", "eqlTagIndex"))
if mibBuilder.loadTexts: eqlVolumeTagEntry.setStatus('current')
eqlVolumeTagValue = MibTableColumn((1, 3, 6, 1, 4, 1, 12740, 23, 1, 4, 1, 1), UTFString().subtype(subtypeSpec=ValueSizeConstraint(0, 64))).setMaxAccess("readwrite")
if mibBuilder.loadTexts: eqlVolumeTagValue.setStatus('current')
mibBuilder.exportSymbols("EQLTAG-MIB", eqlAdminAccountTagEntry=eqlAdminAccountTagEntry, eqlTagObjectIndex=eqlTagObjectIndex, eqlVolumeTagTable=eqlVolumeTagTable, eqlTagValueDescription=eqlTagValueDescription, eqlTagTable=eqlTagTable, eqltagModule=eqltagModule, eqlTagIndex=eqlTagIndex, eqltagConformance=eqltagConformance, eqlVolumeTagValue=eqlVolumeTagValue, eqlAdminAccountTagTable=eqlAdminAccountTagTable, eqlTagValue=eqlTagValue, eqlVolumeTagEntry=eqlVolumeTagEntry, eqlTagType=eqlTagType, eqlAdminAccountTagAccess=eqlAdminAccountTagAccess, eqlTagObjectEntry=eqlTagObjectEntry, eqlTagObjectTaggedObjectPointer=eqlTagObjectTaggedObjectPointer, eqlTagObjectRowStatus=eqlTagObjectRowStatus, eqltagObjects=eqltagObjects, PYSNMP_MODULE_ID=eqltagModule, eqltagNotifications=eqltagNotifications, eqlTagAdminAccountKey=eqlTagAdminAccountKey, eqlTagObjectTable=eqlTagObjectTable, eqlTagEntry=eqlTagEntry, eqlTagRowStatus=eqlTagRowStatus)
| 116.460317 | 932 | 0.76857 |
e942c0deab528bd045371e99c9201111017a2648 | 1,857 | py | Python | Django/api-basic2/photo/views.py | sug5806/TIL | 2309d8a270e4a7b8961268a40b6492c5db317e37 | [
"MIT"
] | null | null | null | Django/api-basic2/photo/views.py | sug5806/TIL | 2309d8a270e4a7b8961268a40b6492c5db317e37 | [
"MIT"
] | 102 | 2020-02-12T00:10:33.000Z | 2022-03-11T23:58:41.000Z | Django/api-basic2/photo/views.py | sug5806/TIL | 2309d8a270e4a7b8961268a40b6492c5db317e37 | [
"MIT"
] | null | null | null | from django.views.generic import ListView, CreateView, DetailView, UpdateView, DeleteView
from rest_framework import generics
from django.http import HttpResponse
from .models import Photo
from .serializers import *
# Create your views here.
def index(request):
return HttpResponse('index')
class PhotoList(ListView):
model = Photo
template_name = 'photo/photo_list.html'
class PhotoCreate(CreateView):
model = Photo
template_name = 'photo/photo_create.html'
fields = ['image', 'text']
def form_valid(self, form):
if self.request.user.id:
form.instance.author_id = self.request.user.id
return super().form_valid(form)
else:
return False
# get_absolute_url 이 있으므로 생략 가능
# success_url = '/'
class PhotoDetail(DetailView):
model = Photo
template_name = 'photo/photo_detail.html'
class PhotoUpdate(UpdateView):
model = Photo
fields = ['image', 'text']
template_name = 'photo/photo_update.html'
class PhotoDelete(DeleteView):
model = Photo
template_name = 'photo/photo_delete.html'
######################################################
class PhotoListAPI(generics.ListAPIView):
queryset = Photo.objects.all()
serializer_class = PhotoListSerializer
class PhotoCreateAPI(generics.CreateAPIView):
serializer_class = PhotoCreateSerializer
class PhotoDetailAPI(generics.RetrieveAPIView):
queryset = Photo.objects.all()
serializer_class = PhotoDetailSerializer
class PhotoUpdateAPI(generics.UpdateAPIView):
queryset = Photo.objects.all()
serializer_class = PhotoUpdateSerializer
class photoDeleteAPI(generics.DestroyAPIView):
queryset = Photo.objects.all()
# 토큰 인증 기능 추가, 기본 인증, 권한 클래스
# 1) 인증된 사용자만 API를 사용할 수 있도록 설정 : token 인증
# 2) 특정 동작에 대해 특정 권한을 득한 사용자만 사용할 수 있도록 설정 : permission클래스 추가
| 23.506329 | 89 | 0.695746 |
77ce043ae32f18025f1a4130286956c126ed8131 | 3,026 | py | Python | util/DFA.py | MartrixG/comlier | a29a9201478d59da6786bbe1cd6760cd3bb481a9 | [
"MIT"
] | null | null | null | util/DFA.py | MartrixG/comlier | a29a9201478d59da6786bbe1cd6760cd3bb481a9 | [
"MIT"
] | null | null | null | util/DFA.py | MartrixG/comlier | a29a9201478d59da6786bbe1cd6760cd3bb481a9 | [
"MIT"
] | null | null | null | import string
class DFA(object):
def __init__(self, data):
self.name = data['name'][0]
self.Q = data['Q'][0].split(' ')
self.sigma = data['sigma'][0].split(' ')
self.q0 = data['q0'][0]
species = data['F'][0].split(' ')
self.F = {}
self.error = {}
for spec in species:
tmp = spec.split(",")
if tmp[0] == 'comma':
tmp[0] = tmp[1] = ','
self.F[tmp[0]] = tmp[1]
tmp = ""
for item in data['t']:
tmp += item
t = {}
for item in tmp.split(' '):
key, value = item.split(',')
key = [key]
if key[0] == 'digit':
key = ['0', '1', '2', '3', '4', '5', '6', '7', '8', '9']
if key[0] == 'letter':
key = [i for i in string.ascii_letters]
if key[0] == 'comma':
key = [',']
value = value[0] + ','
for each_key in key:
t[value[0] + each_key] = value[1]
for error in data['error'][0].split(';'):
state, statement = error.split(':')
self.error[state] = statement
self.t = t
def scan(self, src_code):
re = ''
now_state = self.q0
now_ch = src_code.get_now()
while True:
if self.t.get(now_state + now_ch, None) is not None:
now_state = self.t.get(now_state + now_ch)
elif self.t.get(now_state + 'exc*', None) is not None and now_ch != '*':
now_state = self.t.get(now_state + 'exc*')
elif now_state in self.F.keys():
return re, self.F.get(now_state), src_code.line
else:
while src_code.has_next():
if src_code.get_now() not in (string.ascii_letters, '_', string.digits):
break
re += src_code.get_next()
return -1, self.error[now_state] + "at " + src_code.get_pos(len(re)) + ".", src_code.line
re += now_ch
now_ch = src_code.get_next()
def get_list(self):
re = []
line = ["s\\Q"]
for s in self.Q:
line.append(s)
re.append(line)
for s in self.sigma:
line = [s]
for to in self.Q:
tmp = to + s
if self.t.get(tmp, None) is None:
line.append('err')
else:
line.append(self.t.get(tmp))
re.append(line)
return re
def __repr__(self):
re = self.name + ":\n" + "s\\Q\t"
for s in self.Q:
re += s + '\t'
re += '\n'
for s in self.sigma:
re += s + '\t'
for to in self.Q:
tmp = to + s
if self.t.get(tmp, None) is None:
re += 'err\t'
else:
re += self.t.get(tmp) + '\t'
re += '\n'
return re
| 33.252747 | 105 | 0.41573 |
61fb23047037ee307ef4070a9eed543209d7b75d | 947 | py | Python | src/utils/snapshot.py | TUM-LMF/MTLCC-pytorch | 894a470be2fb4b9e2e0b9e20e8684131ffdb5577 | [
"MIT"
] | 39 | 2018-08-27T11:33:28.000Z | 2021-12-13T11:17:31.000Z | src/utils/snapshot.py | TUM-LMF/MTLCC-pytorch | 894a470be2fb4b9e2e0b9e20e8684131ffdb5577 | [
"MIT"
] | 2 | 2019-02-16T11:40:54.000Z | 2020-04-23T08:01:53.000Z | src/utils/snapshot.py | TUM-LMF/MTLCC-pytorch | 894a470be2fb4b9e2e0b9e20e8684131ffdb5577 | [
"MIT"
] | 16 | 2018-08-29T02:03:31.000Z | 2022-03-12T09:41:06.000Z | import torch
def save(path, model, optimizer, **kwargs):
model_state = None
optimizer_state = None
if model is not None:
model_state = model.state_dict()
if optimizer is not None:
optimizer_state = optimizer.state_dict()
torch.save(
dict(model_state=model_state,
optimizer_state=optimizer_state,
**kwargs),
path
)
def resume(path, model, optimizer):
if torch.cuda.is_available():
snapshot = torch.load(path)
else:
snapshot = torch.load(path, map_location="cpu")
model_state = snapshot.pop('model_state', snapshot)
optimizer_state = snapshot.pop('optimizer_state', None)
if model is not None and model_state is not None:
print("load model")
model.load_state_dict(model_state)
if optimizer is not None and optimizer_state is not None:
optimizer.load_state_dict(optimizer_state)
return snapshot | 28.69697 | 61 | 0.663147 |
7f590493906211f152f3834baf12c64bd1f02b6d | 1,986 | py | Python | python/caffe2_benchmarks/models/deep_mnist.py | joehandzik/dlcookbook-dlbs | 7c5ca5a6dfa4e2f7b8b4d81c60bd8be343dabd30 | [
"Apache-2.0"
] | 123 | 2017-11-28T20:21:24.000Z | 2022-03-22T11:21:04.000Z | python/caffe2_benchmarks/models/deep_mnist.py | joehandzik/dlcookbook-dlbs | 7c5ca5a6dfa4e2f7b8b4d81c60bd8be343dabd30 | [
"Apache-2.0"
] | 17 | 2018-01-05T00:05:13.000Z | 2020-09-18T05:12:45.000Z | python/caffe2_benchmarks/models/deep_mnist.py | joehandzik/dlcookbook-dlbs | 7c5ca5a6dfa4e2f7b8b4d81c60bd8be343dabd30 | [
"Apache-2.0"
] | 48 | 2018-01-04T20:52:51.000Z | 2022-03-06T00:47:17.000Z | # (c) Copyright [2017] Hewlett Packard Enterprise Development LP
#
# 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.
"""
https://caffe2.ai/docs/SynchronousSGD.html
"""
from __future__ import absolute_import
from caffe2.python import brew
from caffe2_benchmarks.models.model import Model
class DeepMNIST(Model):
"""A somewhat deep FCNN."""
implements = 'deep_mnist'
def __init__(self, params):
Model.check_parameters(
params,
{'name': 'DeepMNIST', 'input_shape':(784),
'num_classes': 10, 'arg_scope': {'order': 'NCHW'}}
)
Model.__init__(self, params)
def forward_pass_builder(self, model, loss_scale=1.0):
"""
This function adds the operators, layers to the network. It should return
a list of loss-blobs that are used for computing the loss gradient. This
function is also passed an internally calculated loss_scale parameter that
is used to scale your loss to normalize for the number of GPUs.
Signature: function(model, loss_scale)
"""
v = 'data'
dim_in = self.input_shape[0]
for idx, dim_out in enumerate([2500, 2000, 1500, 1000, 500]):
v = brew.fc(model, v, 'fc%d' % (idx+1), dim_in=dim_in, dim_out=dim_out)
v = brew.relu(model, v, 'relu%d' % (idx+1))
dim_in = dim_out
return self.add_head_nodes(model, v, dim_in, 'fc%d' % (idx+2), loss_scale=loss_scale)
| 39.72 | 93 | 0.662638 |
2427b69bec93ef3bc82d3ad46daa19f43e0c4d1a | 2,674 | py | Python | cptm/utils/inputgeneration.py | egpbos/cptm | c5f310858c341040b4afd166cf628aeee6845159 | [
"Apache-2.0"
] | 13 | 2016-03-14T14:58:04.000Z | 2020-11-03T22:48:59.000Z | cptm/utils/inputgeneration.py | egpbos/cptm | c5f310858c341040b4afd166cf628aeee6845159 | [
"Apache-2.0"
] | 5 | 2015-10-30T12:34:16.000Z | 2017-10-27T04:55:07.000Z | cptm/utils/inputgeneration.py | egpbos/cptm | c5f310858c341040b4afd166cf628aeee6845159 | [
"Apache-2.0"
] | 3 | 2016-03-03T10:49:05.000Z | 2018-02-03T14:36:59.000Z | """Helpers to generate input data for cross-perspective topic modeling."""
import os
import logging
import codecs
import re
logger = logging.getLogger('inputgeneration')
class Perspective():
def __init__(self, name, posTopic, posOpinion):
"""Initialize inputgeneration Perspective.
Parameters:
name : str
The perspective name. Used as directory name to store the data.
posTopic : list of strings
List of strings specifying the pos-tags for topic words.
posOpinion : list of strings
List of strings specifying the pos-tags for opinion words.
"""
self.name = name
self.wordTypes = posTopic + posOpinion
self.posTopic = posTopic
self.posOpinion = posOpinion
self.words = {}
for w in self.wordTypes:
self.words[w] = []
def __str__(self):
len_topic_words, len_opinion_words = self.word_lengths()
return 'Perspective: {} - {} topic words; {} opinion words'.format(
self.name, len_topic_words, len_opinion_words)
def add(self, tag, word):
self.words[tag].append(word)
def write2file(self, out_dir, file_name):
# create dir (if not exists)
directory = os.path.join(out_dir, self.name)
if not os.path.exists(directory):
os.makedirs(directory)
# write words to file
out_file = os.path.join(directory, file_name)
logger.debug('Writing file {} for perspective {}'.format(out_file,
self.name))
with codecs.open(out_file, 'wb', 'utf8') as f:
for w in self.wordTypes:
f.write(u'{}\n'.format(' '.join(self.words[w])))
def word_lengths(self):
len_topic_words = sum([len(self.words[w])
for w in self.posTopic])
len_opinion_words = sum([len(self.words[w])
for w in self.posOpinion])
return len_topic_words, len_opinion_words
def remove_trailing_digits(word):
"""Convert words like d66 to d.
In the folia files from politicalmashup, words such as d66 have been
extracted as two words (d and 66) and only d ended up in the data input
files. The folia files were probably created with an old version of frog,
because currenly, words like these are parsed correctly.
This function can be used when parsing and lemmatizing new text to match
the vocabulary used in the old folia files.
"""
regex = re.compile('^(.+?)(\d+)$', flags=re.UNICODE)
m = regex.match(word)
if m:
return m.group(1)
return word
| 34.727273 | 79 | 0.618175 |
feaad7b597b6126d98a8c190505671c0aa793dba | 78,865 | py | Python | tests/core/consensus/test_blockchain.py | kd637xx/chia-blockchain | b82f3ba8a2953de12bddf5c5d6a33e443b51bc8b | [
"Apache-2.0"
] | null | null | null | tests/core/consensus/test_blockchain.py | kd637xx/chia-blockchain | b82f3ba8a2953de12bddf5c5d6a33e443b51bc8b | [
"Apache-2.0"
] | null | null | null | tests/core/consensus/test_blockchain.py | kd637xx/chia-blockchain | b82f3ba8a2953de12bddf5c5d6a33e443b51bc8b | [
"Apache-2.0"
] | null | null | null | # flake8: noqa: F811, F401
import asyncio
import multiprocessing
import time
from dataclasses import replace
import logging
import pytest
from blspy import AugSchemeMPL, G2Element
from src.consensus.blockchain import ReceiveBlockResult
from src.types.classgroup import ClassgroupElement
from src.types.end_of_slot_bundle import EndOfSubSlotBundle
from src.types.full_block import FullBlock
from src.types.slots import InfusedChallengeChainSubSlot
from src.types.unfinished_block import UnfinishedBlock
from src.types.vdf import VDFInfo, VDFProof
from src.util.block_tools import get_vdf_info_and_proof
from src.util.errors import Err
from src.util.hash import std_hash
from src.util.ints import uint64, uint8, int512
from src.util.wallet_tools import WalletTool
from tests.recursive_replace import recursive_replace
from tests.setup_nodes import test_constants, bt
from tests.core.fixtures import empty_blockchain # noqa: F401
from tests.core.fixtures import default_1000_blocks # noqa: F401
from tests.core.fixtures import default_400_blocks # noqa: F401
from tests.core.fixtures import default_10000_blocks # noqa: F401
log = logging.getLogger(__name__)
@pytest.fixture(scope="module")
def event_loop():
loop = asyncio.get_event_loop()
yield loop
class TestGenesisBlock:
@pytest.mark.asyncio
async def test_block_tools_proofs_400(self, default_400_blocks):
vdf, proof = get_vdf_info_and_proof(
test_constants, ClassgroupElement.get_default_element(), test_constants.FIRST_CC_CHALLENGE, uint64(231)
)
if proof.is_valid(test_constants, ClassgroupElement.get_default_element(), vdf) is False:
raise Exception("invalid proof")
@pytest.mark.asyncio
async def test_block_tools_proofs_1000(self, default_1000_blocks):
vdf, proof = get_vdf_info_and_proof(
test_constants, ClassgroupElement.get_default_element(), test_constants.FIRST_CC_CHALLENGE, uint64(231)
)
if proof.is_valid(test_constants, ClassgroupElement.get_default_element(), vdf) is False:
raise Exception("invalid proof")
@pytest.mark.asyncio
async def test_block_tools_proofs_10000(self, default_10000_blocks):
vdf, proof = get_vdf_info_and_proof(
test_constants, ClassgroupElement.get_default_element(), test_constants.FIRST_CC_CHALLENGE, uint64(231)
)
if proof.is_valid(test_constants, ClassgroupElement.get_default_element(), vdf) is False:
raise Exception("invalid proof")
@pytest.mark.asyncio
async def test_non_overflow_genesis(self, empty_blockchain):
assert empty_blockchain.get_peak() is None
genesis = bt.get_consecutive_blocks(1, force_overflow=False)[0]
result, err, _ = await empty_blockchain.receive_block(genesis)
assert err is None
assert result == ReceiveBlockResult.NEW_PEAK
assert empty_blockchain.get_peak().sub_block_height == 0
@pytest.mark.asyncio
async def test_overflow_genesis(self, empty_blockchain):
genesis = bt.get_consecutive_blocks(1, force_overflow=True)[0]
result, err, _ = await empty_blockchain.receive_block(genesis)
assert err is None
assert result == ReceiveBlockResult.NEW_PEAK
@pytest.mark.asyncio
async def test_genesis_empty_slots(self, empty_blockchain):
genesis = bt.get_consecutive_blocks(1, force_overflow=False, skip_slots=3)[0]
result, err, _ = await empty_blockchain.receive_block(genesis)
assert err is None
assert result == ReceiveBlockResult.NEW_PEAK
@pytest.mark.asyncio
async def test_overflow_genesis_empty_slots(self, empty_blockchain):
genesis = bt.get_consecutive_blocks(1, force_overflow=True, skip_slots=3)[0]
result, err, _ = await empty_blockchain.receive_block(genesis)
assert err is None
assert result == ReceiveBlockResult.NEW_PEAK
@pytest.mark.asyncio
async def test_genesis_validate_1(self, empty_blockchain):
genesis = bt.get_consecutive_blocks(1, force_overflow=False)[0]
bad_prev = bytes([1] * 32)
genesis = recursive_replace(genesis, "foliage_sub_block.prev_sub_block_hash", bad_prev)
result, err, _ = await empty_blockchain.receive_block(genesis)
assert err == Err.INVALID_PREV_BLOCK_HASH
class TestBlockHeaderValidation:
@pytest.mark.asyncio
async def test_long_chain(self, empty_blockchain, default_1000_blocks):
blocks = default_1000_blocks
for block in blocks:
if (
len(block.finished_sub_slots) > 0
and block.finished_sub_slots[0].challenge_chain.subepoch_summary_hash is not None
):
# Sub/Epoch. Try using a bad ssi and difficulty to test 2m and 2n
new_finished_ss = recursive_replace(
block.finished_sub_slots[0],
"challenge_chain.new_sub_slot_iters",
uint64(10000000),
)
block_bad = recursive_replace(
block, "finished_sub_slots", [new_finished_ss] + block.finished_sub_slots[1:]
)
result, err, _ = await empty_blockchain.receive_block(block_bad)
assert err == Err.INVALID_NEW_SUB_SLOT_ITERS
new_finished_ss_2 = recursive_replace(
block.finished_sub_slots[0],
"challenge_chain.new_difficulty",
uint64(10000000),
)
block_bad_2 = recursive_replace(
block, "finished_sub_slots", [new_finished_ss_2] + block.finished_sub_slots[1:]
)
result, err, _ = await empty_blockchain.receive_block(block_bad_2)
assert err == Err.INVALID_NEW_DIFFICULTY
# 3c
new_finished_ss_3: EndOfSubSlotBundle = recursive_replace(
block.finished_sub_slots[0],
"challenge_chain.subepoch_summary_hash",
bytes([0] * 32),
)
new_finished_ss_3 = recursive_replace(
new_finished_ss_3,
"reward_chain.challenge_chain_sub_slot_hash",
new_finished_ss_3.challenge_chain.get_hash(),
)
block_bad_3 = recursive_replace(
block, "finished_sub_slots", [new_finished_ss_3] + block.finished_sub_slots[1:]
)
result, err, _ = await empty_blockchain.receive_block(block_bad_3)
assert err == Err.INVALID_SUB_EPOCH_SUMMARY
# 3d
new_finished_ss_4 = recursive_replace(
block.finished_sub_slots[0],
"challenge_chain.subepoch_summary_hash",
None,
)
new_finished_ss_4 = recursive_replace(
new_finished_ss_4,
"reward_chain.challenge_chain_sub_slot_hash",
new_finished_ss_4.challenge_chain.get_hash(),
)
block_bad_4 = recursive_replace(
block, "finished_sub_slots", [new_finished_ss_4] + block.finished_sub_slots[1:]
)
result, err, _ = await empty_blockchain.receive_block(block_bad_4)
assert err == Err.INVALID_SUB_EPOCH_SUMMARY or err == Err.INVALID_NEW_SUB_SLOT_ITERS
result, err, _ = await empty_blockchain.receive_block(block)
assert err is None
assert result == ReceiveBlockResult.NEW_PEAK
log.info(
f"Added block {block.sub_block_height} total iters {block.total_iters} "
f"new slot? {len(block.finished_sub_slots)}"
)
assert empty_blockchain.get_peak().sub_block_height == len(blocks) - 1
@pytest.mark.asyncio
async def test_unfinished_blocks(self, empty_blockchain):
blockchain = empty_blockchain
blocks = bt.get_consecutive_blocks(2)
for block in blocks[:-1]:
result, err, _ = await blockchain.receive_block(block)
assert result == ReceiveBlockResult.NEW_PEAK
block = blocks[-1]
unf = UnfinishedBlock(
block.finished_sub_slots,
block.reward_chain_sub_block.get_unfinished(),
block.challenge_chain_sp_proof,
block.reward_chain_sp_proof,
block.foliage_sub_block,
block.foliage_block,
block.transactions_info,
block.transactions_generator,
)
_, err = await blockchain.validate_unfinished_block(unf, False)
assert err is None
result, err, _ = await blockchain.receive_block(block)
blocks = bt.get_consecutive_blocks(1, block_list_input=blocks, force_overflow=True)
block = blocks[-1]
unf = UnfinishedBlock(
block.finished_sub_slots,
block.reward_chain_sub_block.get_unfinished(),
block.challenge_chain_sp_proof,
block.reward_chain_sp_proof,
block.foliage_sub_block,
block.foliage_block,
block.transactions_info,
block.transactions_generator,
)
_, err = await blockchain.validate_unfinished_block(unf, False)
assert err is None
@pytest.mark.asyncio
async def test_empty_genesis(self, empty_blockchain):
blockchain = empty_blockchain
for block in bt.get_consecutive_blocks(2, skip_slots=3):
result, err, _ = await blockchain.receive_block(block)
assert err is None
assert result == ReceiveBlockResult.NEW_PEAK
@pytest.mark.asyncio
async def test_empty_slots_non_genesis(self, empty_blockchain):
blockchain = empty_blockchain
blocks = bt.get_consecutive_blocks(10)
for block in blocks:
result, err, _ = await blockchain.receive_block(block)
assert err is None
assert result == ReceiveBlockResult.NEW_PEAK
blocks = bt.get_consecutive_blocks(10, skip_slots=2, block_list_input=blocks)
for block in blocks[10:]:
result, err, _ = await blockchain.receive_block(block)
assert err is None
assert blockchain.get_peak().sub_block_height == 19
@pytest.mark.asyncio
async def test_one_sb_per_slot(self, empty_blockchain):
blockchain = empty_blockchain
num_blocks = 20
blocks = []
for i in range(num_blocks):
blocks = bt.get_consecutive_blocks(1, block_list_input=blocks, skip_slots=1)
result, err, _ = await blockchain.receive_block(blocks[-1])
assert result == ReceiveBlockResult.NEW_PEAK
assert blockchain.get_peak().sub_block_height == num_blocks - 1
@pytest.mark.asyncio
async def test_one_sb_per_two_slots(self, empty_blockchain):
blockchain = empty_blockchain
num_blocks = 20
blocks = []
for i in range(num_blocks): # Same thing, but 2 sub-slots per sub-block
blocks = bt.get_consecutive_blocks(1, block_list_input=blocks, skip_slots=2)
result, err, _ = await blockchain.receive_block(blocks[-1])
assert result == ReceiveBlockResult.NEW_PEAK
assert blockchain.get_peak().sub_block_height == num_blocks - 1
@pytest.mark.asyncio
async def test_one_sb_per_five_slots(self, empty_blockchain):
blockchain = empty_blockchain
num_blocks = 10
blocks = []
for i in range(num_blocks): # Same thing, but 5 sub-slots per sub-block
blocks = bt.get_consecutive_blocks(1, block_list_input=blocks, skip_slots=5)
result, err, _ = await blockchain.receive_block(blocks[-1])
assert result == ReceiveBlockResult.NEW_PEAK
assert blockchain.get_peak().sub_block_height == num_blocks - 1
@pytest.mark.asyncio
async def test_basic_chain_overflow(self, empty_blockchain):
blocks = bt.get_consecutive_blocks(5, force_overflow=True)
for block in blocks:
result, err, _ = await empty_blockchain.receive_block(block)
assert err is None
assert result == ReceiveBlockResult.NEW_PEAK
assert empty_blockchain.get_peak().sub_block_height == len(blocks) - 1
@pytest.mark.asyncio
async def test_one_sb_per_two_slots_force_overflow(self, empty_blockchain):
blockchain = empty_blockchain
num_blocks = 10
blocks = []
for i in range(num_blocks):
blocks = bt.get_consecutive_blocks(1, block_list_input=blocks, skip_slots=2, force_overflow=True)
result, err, _ = await blockchain.receive_block(blocks[-1])
assert err is None
assert result == ReceiveBlockResult.NEW_PEAK
assert blockchain.get_peak().sub_block_height == num_blocks - 1
@pytest.mark.asyncio
async def test_invalid_prev(self, empty_blockchain):
# 1
blocks = bt.get_consecutive_blocks(2, force_overflow=False)
assert (await empty_blockchain.receive_block(blocks[0]))[0] == ReceiveBlockResult.NEW_PEAK
block_1_bad = recursive_replace(blocks[-1], "foliage_sub_block.prev_sub_block_hash", bytes([0] * 32))
result, err, _ = await empty_blockchain.receive_block(block_1_bad)
assert result == ReceiveBlockResult.DISCONNECTED_BLOCK
@pytest.mark.asyncio
async def test_invalid_pospace(self, empty_blockchain):
# 2
blocks = bt.get_consecutive_blocks(2, force_overflow=False)
assert (await empty_blockchain.receive_block(blocks[0]))[0] == ReceiveBlockResult.NEW_PEAK
block_1_bad = recursive_replace(blocks[-1], "reward_chain_sub_block.proof_of_space.proof", bytes([0] * 32))
result, err, _ = await empty_blockchain.receive_block(block_1_bad)
assert result == ReceiveBlockResult.INVALID_BLOCK
assert err == Err.INVALID_POSPACE
@pytest.mark.asyncio
async def test_invalid_sub_slot_challenge_hash_genesis(self, empty_blockchain):
# 2a
blocks = bt.get_consecutive_blocks(1, force_overflow=False, skip_slots=1)
new_finished_ss = recursive_replace(
blocks[0].finished_sub_slots[0],
"challenge_chain.challenge_chain_end_of_slot_vdf.challenge",
bytes([2] * 32),
)
block_0_bad = recursive_replace(
blocks[0], "finished_sub_slots", [new_finished_ss] + blocks[0].finished_sub_slots[1:]
)
result, err, _ = await empty_blockchain.receive_block(block_0_bad)
assert result == ReceiveBlockResult.INVALID_BLOCK
assert err == Err.INVALID_PREV_CHALLENGE_SLOT_HASH
@pytest.mark.asyncio
async def test_invalid_sub_slot_challenge_hash_non_genesis(self, empty_blockchain):
# 2b
blocks = bt.get_consecutive_blocks(1, force_overflow=False, skip_slots=0)
blocks = bt.get_consecutive_blocks(1, force_overflow=False, skip_slots=1, block_list_input=blocks)
new_finished_ss = recursive_replace(
blocks[1].finished_sub_slots[0],
"challenge_chain.challenge_chain_end_of_slot_vdf.challenge",
bytes([2] * 32),
)
block_1_bad = recursive_replace(
blocks[1], "finished_sub_slots", [new_finished_ss] + blocks[1].finished_sub_slots[1:]
)
_, _, _ = await empty_blockchain.receive_block(blocks[0])
result, err, _ = await empty_blockchain.receive_block(block_1_bad)
assert result == ReceiveBlockResult.INVALID_BLOCK
assert err == Err.INVALID_PREV_CHALLENGE_SLOT_HASH
@pytest.mark.asyncio
async def test_invalid_sub_slot_challenge_hash_empty_ss(self, empty_blockchain):
# 2c
blocks = bt.get_consecutive_blocks(1, force_overflow=False, skip_slots=0)
blocks = bt.get_consecutive_blocks(1, force_overflow=False, skip_slots=2, block_list_input=blocks)
new_finished_ss = recursive_replace(
blocks[1].finished_sub_slots[-1],
"challenge_chain.challenge_chain_end_of_slot_vdf.challenge",
bytes([2] * 32),
)
block_1_bad = recursive_replace(
blocks[1], "finished_sub_slots", blocks[1].finished_sub_slots[:-1] + [new_finished_ss]
)
_, _, _ = await empty_blockchain.receive_block(blocks[0])
result, err, _ = await empty_blockchain.receive_block(block_1_bad)
assert result == ReceiveBlockResult.INVALID_BLOCK
assert err == Err.INVALID_PREV_CHALLENGE_SLOT_HASH
@pytest.mark.asyncio
async def test_genesis_no_icc(self, empty_blockchain):
# 2d
blocks = bt.get_consecutive_blocks(1, force_overflow=False, skip_slots=1)
new_finished_ss = recursive_replace(
blocks[0].finished_sub_slots[0],
"infused_challenge_chain",
InfusedChallengeChainSubSlot(
VDFInfo(
bytes([0] * 32),
uint64(1200),
ClassgroupElement.get_default_element(),
)
),
)
block_0_bad = recursive_replace(
blocks[0], "finished_sub_slots", [new_finished_ss] + blocks[0].finished_sub_slots[1:]
)
result, err, _ = await empty_blockchain.receive_block(block_0_bad)
assert result == ReceiveBlockResult.INVALID_BLOCK
assert err == Err.SHOULD_NOT_HAVE_ICC
@pytest.mark.asyncio
async def test_invalid_icc_sub_slot_vdf(self, empty_blockchain):
blocks = bt.get_consecutive_blocks(10)
for block in blocks:
if len(block.finished_sub_slots) > 0 and block.finished_sub_slots[-1].infused_challenge_chain is not None:
# Bad iters
new_finished_ss = recursive_replace(
block.finished_sub_slots[-1],
"infused_challenge_chain",
InfusedChallengeChainSubSlot(
replace(
block.finished_sub_slots[
-1
].infused_challenge_chain.infused_challenge_chain_end_of_slot_vdf,
number_of_iterations=10000000,
)
),
)
block_bad = recursive_replace(
block, "finished_sub_slots", block.finished_sub_slots[:-1] + [new_finished_ss]
)
result, err, _ = await empty_blockchain.receive_block(block_bad)
assert err == Err.INVALID_ICC_EOS_VDF
# Bad output
new_finished_ss_2 = recursive_replace(
block.finished_sub_slots[-1],
"infused_challenge_chain",
InfusedChallengeChainSubSlot(
replace(
block.finished_sub_slots[
-1
].infused_challenge_chain.infused_challenge_chain_end_of_slot_vdf,
output=ClassgroupElement.get_default_element(),
)
),
)
block_bad_2 = recursive_replace(
block, "finished_sub_slots", block.finished_sub_slots[:-1] + [new_finished_ss_2]
)
result, err, _ = await empty_blockchain.receive_block(block_bad_2)
assert err == Err.INVALID_ICC_EOS_VDF
# Bad challenge hash
new_finished_ss_3 = recursive_replace(
block.finished_sub_slots[-1],
"infused_challenge_chain",
InfusedChallengeChainSubSlot(
replace(
block.finished_sub_slots[
-1
].infused_challenge_chain.infused_challenge_chain_end_of_slot_vdf,
challenge=bytes([0] * 32),
)
),
)
block_bad_3 = recursive_replace(
block, "finished_sub_slots", block.finished_sub_slots[:-1] + [new_finished_ss_3]
)
result, err, _ = await empty_blockchain.receive_block(block_bad_3)
assert err == Err.INVALID_ICC_EOS_VDF
# Bad proof
new_finished_ss_5 = recursive_replace(
block.finished_sub_slots[-1],
"proofs.infused_challenge_chain_slot_proof",
VDFProof(uint8(0), b"1239819023890"),
)
block_bad_5 = recursive_replace(
block, "finished_sub_slots", block.finished_sub_slots[:-1] + [new_finished_ss_5]
)
result, err, _ = await empty_blockchain.receive_block(block_bad_5)
assert err == Err.INVALID_ICC_EOS_VDF
result, err, _ = await empty_blockchain.receive_block(block)
assert err is None
assert result == ReceiveBlockResult.NEW_PEAK
@pytest.mark.asyncio
async def test_invalid_icc_into_cc(self, empty_blockchain):
blockchain = empty_blockchain
blocks = bt.get_consecutive_blocks(1)
assert (await blockchain.receive_block(blocks[0]))[0] == ReceiveBlockResult.NEW_PEAK
case_1, case_2 = False, False
while not case_1 or not case_2:
blocks = bt.get_consecutive_blocks(1, block_list_input=blocks, skip_slots=1)
block = blocks[-1]
if len(block.finished_sub_slots) > 0 and block.finished_sub_slots[-1].infused_challenge_chain is not None:
if (
block.finished_sub_slots[-1].reward_chain.deficit
== test_constants.MIN_SUB_BLOCKS_PER_CHALLENGE_BLOCK
):
# 2g
case_1 = True
new_finished_ss = recursive_replace(
block.finished_sub_slots[-1],
"challenge_chain",
replace(
block.finished_sub_slots[-1].challenge_chain,
infused_challenge_chain_sub_slot_hash=bytes([1] * 32),
),
)
else:
# 2h
case_2 = True
new_finished_ss = recursive_replace(
block.finished_sub_slots[-1],
"challenge_chain",
replace(
block.finished_sub_slots[-1].challenge_chain,
infused_challenge_chain_sub_slot_hash=block.finished_sub_slots[
-1
].infused_challenge_chain.get_hash(),
),
)
block_bad = recursive_replace(
block, "finished_sub_slots", block.finished_sub_slots[:-1] + [new_finished_ss]
)
result, err, _ = await blockchain.receive_block(block_bad)
assert err == Err.INVALID_ICC_HASH_CC
# 2i
new_finished_ss_bad_rc = recursive_replace(
block.finished_sub_slots[-1],
"reward_chain",
replace(block.finished_sub_slots[-1].reward_chain, infused_challenge_chain_sub_slot_hash=None),
)
block_bad = recursive_replace(
block, "finished_sub_slots", block.finished_sub_slots[:-1] + [new_finished_ss_bad_rc]
)
result, err, _ = await blockchain.receive_block(block_bad)
assert err == Err.INVALID_ICC_HASH_RC
elif len(block.finished_sub_slots) > 0 and block.finished_sub_slots[-1].infused_challenge_chain is None:
# 2j
new_finished_ss_bad_cc = recursive_replace(
block.finished_sub_slots[-1],
"challenge_chain",
replace(
block.finished_sub_slots[-1].challenge_chain,
infused_challenge_chain_sub_slot_hash=bytes([1] * 32),
),
)
block_bad = recursive_replace(
block, "finished_sub_slots", block.finished_sub_slots[:-1] + [new_finished_ss_bad_cc]
)
result, err, _ = await blockchain.receive_block(block_bad)
assert err == Err.INVALID_ICC_HASH_CC
# 2k
new_finished_ss_bad_rc = recursive_replace(
block.finished_sub_slots[-1],
"reward_chain",
replace(
block.finished_sub_slots[-1].reward_chain, infused_challenge_chain_sub_slot_hash=bytes([1] * 32)
),
)
block_bad = recursive_replace(
block, "finished_sub_slots", block.finished_sub_slots[:-1] + [new_finished_ss_bad_rc]
)
result, err, _ = await blockchain.receive_block(block_bad)
assert err == Err.INVALID_ICC_HASH_RC
# Finally, add the block properly
result, err, _ = await blockchain.receive_block(block)
assert err is None
assert result == ReceiveBlockResult.NEW_PEAK
@pytest.mark.asyncio
async def test_empty_slot_no_ses(self, empty_blockchain):
# 2l
blockchain = empty_blockchain
blocks = bt.get_consecutive_blocks(1)
assert (await blockchain.receive_block(blocks[0]))[0] == ReceiveBlockResult.NEW_PEAK
blocks = bt.get_consecutive_blocks(1, block_list_input=blocks, skip_slots=4)
new_finished_ss = recursive_replace(
blocks[-1].finished_sub_slots[-1],
"challenge_chain",
replace(blocks[-1].finished_sub_slots[-1].challenge_chain, subepoch_summary_hash=std_hash(b"0")),
)
block_bad = recursive_replace(
blocks[-1], "finished_sub_slots", blocks[-1].finished_sub_slots[:-1] + [new_finished_ss]
)
result, err, _ = await blockchain.receive_block(block_bad)
assert err == Err.INVALID_SUB_EPOCH_SUMMARY_HASH
@pytest.mark.asyncio
async def test_empty_sub_slots_epoch(self, empty_blockchain):
# 2m
# Tests adding an empty sub slot after the sub-epoch / epoch.
# Also tests overflow block in epoch
blocks_base = bt.get_consecutive_blocks(test_constants.EPOCH_SUB_BLOCKS)
blocks_1 = bt.get_consecutive_blocks(1, block_list_input=blocks_base, force_overflow=True)
blocks_2 = bt.get_consecutive_blocks(1, skip_slots=1, block_list_input=blocks_base, force_overflow=True)
blocks_3 = bt.get_consecutive_blocks(1, skip_slots=2, block_list_input=blocks_base, force_overflow=True)
blocks_4 = bt.get_consecutive_blocks(1, block_list_input=blocks_base)
for block in blocks_base:
result, err, _ = await empty_blockchain.receive_block(block)
assert err is None
assert result == ReceiveBlockResult.NEW_PEAK
for block in [blocks_1[-1], blocks_2[-1], blocks_3[-1], blocks_4[-1]]:
result, err, _ = await empty_blockchain.receive_block(block)
assert err is None
@pytest.mark.asyncio
async def test_wrong_cc_hash_rc(self, empty_blockchain):
# 2o
blockchain = empty_blockchain
blocks = bt.get_consecutive_blocks(1, skip_slots=1)
blocks = bt.get_consecutive_blocks(1, skip_slots=1, block_list_input=blocks)
assert (await blockchain.receive_block(blocks[0]))[0] == ReceiveBlockResult.NEW_PEAK
new_finished_ss = recursive_replace(
blocks[-1].finished_sub_slots[-1],
"reward_chain",
replace(blocks[-1].finished_sub_slots[-1].reward_chain, challenge_chain_sub_slot_hash=bytes([3] * 32)),
)
block_1_bad = recursive_replace(
blocks[-1], "finished_sub_slots", blocks[-1].finished_sub_slots[:-1] + [new_finished_ss]
)
result, err, _ = await blockchain.receive_block(block_1_bad)
assert result == ReceiveBlockResult.INVALID_BLOCK
assert err == Err.INVALID_CHALLENGE_SLOT_HASH_RC
@pytest.mark.asyncio
async def test_invalid_cc_sub_slot_vdf(self, empty_blockchain):
# 2q
blocks = bt.get_consecutive_blocks(10)
for block in blocks:
if len(block.finished_sub_slots):
# Bad iters
new_finished_ss = recursive_replace(
block.finished_sub_slots[-1],
"challenge_chain",
recursive_replace(
block.finished_sub_slots[-1].challenge_chain,
"challenge_chain_end_of_slot_vdf.number_of_iterations",
uint64(10000000),
),
)
new_finished_ss = recursive_replace(
new_finished_ss,
"reward_chain.challenge_chain_sub_slot_hash",
new_finished_ss.challenge_chain.get_hash(),
)
block_bad = recursive_replace(
block, "finished_sub_slots", block.finished_sub_slots[:-1] + [new_finished_ss]
)
result, err, _ = await empty_blockchain.receive_block(block_bad)
assert err == Err.INVALID_CC_EOS_VDF
# Bad output
new_finished_ss_2 = recursive_replace(
block.finished_sub_slots[-1],
"challenge_chain",
recursive_replace(
block.finished_sub_slots[-1].challenge_chain,
"challenge_chain_end_of_slot_vdf.output",
ClassgroupElement.get_default_element(),
),
)
new_finished_ss_2 = recursive_replace(
new_finished_ss_2,
"reward_chain.challenge_chain_sub_slot_hash",
new_finished_ss_2.challenge_chain.get_hash(),
)
block_bad_2 = recursive_replace(
block, "finished_sub_slots", block.finished_sub_slots[:-1] + [new_finished_ss_2]
)
result, err, _ = await empty_blockchain.receive_block(block_bad_2)
assert err == Err.INVALID_CC_EOS_VDF
# Bad challenge hash
new_finished_ss_3 = recursive_replace(
block.finished_sub_slots[-1],
"challenge_chain",
recursive_replace(
block.finished_sub_slots[-1].challenge_chain,
"challenge_chain_end_of_slot_vdf.challenge",
bytes([1] * 32),
),
)
new_finished_ss_3 = recursive_replace(
new_finished_ss_3,
"reward_chain.challenge_chain_sub_slot_hash",
new_finished_ss_3.challenge_chain.get_hash(),
)
block_bad_3 = recursive_replace(
block, "finished_sub_slots", block.finished_sub_slots[:-1] + [new_finished_ss_3]
)
result, err, _ = await empty_blockchain.receive_block(block_bad_3)
assert err == Err.INVALID_CC_EOS_VDF or err == Err.INVALID_PREV_CHALLENGE_SLOT_HASH
# Bad proof
new_finished_ss_5 = recursive_replace(
block.finished_sub_slots[-1],
"proofs.challenge_chain_slot_proof",
VDFProof(uint8(0), b"1239819023890"),
)
block_bad_5 = recursive_replace(
block, "finished_sub_slots", block.finished_sub_slots[:-1] + [new_finished_ss_5]
)
result, err, _ = await empty_blockchain.receive_block(block_bad_5)
assert err == Err.INVALID_CC_EOS_VDF
result, err, _ = await empty_blockchain.receive_block(block)
assert err is None
assert result == ReceiveBlockResult.NEW_PEAK
@pytest.mark.asyncio
async def test_invalid_rc_sub_slot_vdf(self, empty_blockchain):
# 2p
blocks = bt.get_consecutive_blocks(10)
for block in blocks:
if len(block.finished_sub_slots):
# Bad iters
new_finished_ss = recursive_replace(
block.finished_sub_slots[-1],
"reward_chain",
recursive_replace(
block.finished_sub_slots[-1].reward_chain,
"end_of_slot_vdf.number_of_iterations",
uint64(10000000),
),
)
block_bad = recursive_replace(
block, "finished_sub_slots", block.finished_sub_slots[:-1] + [new_finished_ss]
)
result, err, _ = await empty_blockchain.receive_block(block_bad)
assert err == Err.INVALID_RC_EOS_VDF
# Bad output
new_finished_ss_2 = recursive_replace(
block.finished_sub_slots[-1],
"reward_chain",
recursive_replace(
block.finished_sub_slots[-1].reward_chain,
"end_of_slot_vdf.output",
ClassgroupElement.get_default_element(),
),
)
block_bad_2 = recursive_replace(
block, "finished_sub_slots", block.finished_sub_slots[:-1] + [new_finished_ss_2]
)
result, err, _ = await empty_blockchain.receive_block(block_bad_2)
assert err == Err.INVALID_RC_EOS_VDF
# Bad challenge hash
new_finished_ss_3 = recursive_replace(
block.finished_sub_slots[-1],
"reward_chain",
recursive_replace(
block.finished_sub_slots[-1].reward_chain,
"end_of_slot_vdf.challenge",
bytes([1] * 32),
),
)
block_bad_3 = recursive_replace(
block, "finished_sub_slots", block.finished_sub_slots[:-1] + [new_finished_ss_3]
)
result, err, _ = await empty_blockchain.receive_block(block_bad_3)
assert err == Err.INVALID_RC_EOS_VDF
# Bad proof
new_finished_ss_5 = recursive_replace(
block.finished_sub_slots[-1],
"proofs.reward_chain_slot_proof",
VDFProof(uint8(0), b"1239819023890"),
)
block_bad_5 = recursive_replace(
block, "finished_sub_slots", block.finished_sub_slots[:-1] + [new_finished_ss_5]
)
result, err, _ = await empty_blockchain.receive_block(block_bad_5)
assert err == Err.INVALID_RC_EOS_VDF
result, err, _ = await empty_blockchain.receive_block(block)
assert err is None
assert result == ReceiveBlockResult.NEW_PEAK
@pytest.mark.asyncio
async def test_genesis_bad_deficit(self, empty_blockchain):
# 2r
block = bt.get_consecutive_blocks(1, skip_slots=2)[0]
new_finished_ss = recursive_replace(
block.finished_sub_slots[-1],
"reward_chain",
recursive_replace(
block.finished_sub_slots[-1].reward_chain,
"deficit",
test_constants.MIN_SUB_BLOCKS_PER_CHALLENGE_BLOCK - 1,
),
)
block_bad = recursive_replace(block, "finished_sub_slots", block.finished_sub_slots[:-1] + [new_finished_ss])
result, err, _ = await empty_blockchain.receive_block(block_bad)
assert err == Err.INVALID_DEFICIT
@pytest.mark.asyncio
async def test_reset_deficit(self, empty_blockchain):
# 2s, 2t
blockchain = empty_blockchain
blocks = bt.get_consecutive_blocks(2)
await empty_blockchain.receive_block(blocks[0])
await empty_blockchain.receive_block(blocks[1])
case_1, case_2 = False, False
while not case_1 or not case_2:
blocks = bt.get_consecutive_blocks(1, block_list_input=blocks, skip_slots=1)
if len(blocks[-1].finished_sub_slots) > 0:
new_finished_ss = recursive_replace(
blocks[-1].finished_sub_slots[-1],
"reward_chain",
recursive_replace(
blocks[-1].finished_sub_slots[-1].reward_chain,
"deficit",
uint8(0),
),
)
if blockchain.sub_blocks[blocks[-2].header_hash].deficit == 0:
case_1 = True
else:
case_2 = True
block_bad = recursive_replace(
blocks[-1], "finished_sub_slots", blocks[-1].finished_sub_slots[:-1] + [new_finished_ss]
)
result, err, _ = await empty_blockchain.receive_block(block_bad)
assert err == Err.INVALID_DEFICIT or err == Err.INVALID_ICC_HASH_CC
result, err, _ = await empty_blockchain.receive_block(blocks[-1])
assert result == ReceiveBlockResult.NEW_PEAK
@pytest.mark.asyncio
async def test_genesis_has_ses(self, empty_blockchain):
# 3a
block = bt.get_consecutive_blocks(1, skip_slots=1)[0]
new_finished_ss = recursive_replace(
block.finished_sub_slots[0],
"challenge_chain",
recursive_replace(
block.finished_sub_slots[0].challenge_chain,
"subepoch_summary_hash",
bytes([0] * 32),
),
)
new_finished_ss = recursive_replace(
new_finished_ss,
"reward_chain",
replace(
new_finished_ss.reward_chain, challenge_chain_sub_slot_hash=new_finished_ss.challenge_chain.get_hash()
),
)
block_bad = recursive_replace(block, "finished_sub_slots", [new_finished_ss] + block.finished_sub_slots[1:])
result, err, _ = await empty_blockchain.receive_block(block_bad)
assert err == Err.INVALID_SUB_EPOCH_SUMMARY_HASH
@pytest.mark.asyncio
async def test_no_ses_if_no_se(self, empty_blockchain):
# 3b
blocks = bt.get_consecutive_blocks(1)
assert (await empty_blockchain.receive_block(blocks[0]))[0] == ReceiveBlockResult.NEW_PEAK
while True:
blocks = bt.get_consecutive_blocks(1, block_list_input=blocks)
if len(blocks[-1].finished_sub_slots) > 0:
new_finished_ss: EndOfSubSlotBundle = recursive_replace(
blocks[-1].finished_sub_slots[0],
"challenge_chain",
recursive_replace(
blocks[-1].finished_sub_slots[0].challenge_chain,
"subepoch_summary_hash",
bytes([0] * 32),
),
)
new_finished_ss = recursive_replace(
new_finished_ss,
"reward_chain",
replace(
new_finished_ss.reward_chain,
challenge_chain_sub_slot_hash=new_finished_ss.challenge_chain.get_hash(),
),
)
block_bad = recursive_replace(
blocks[-1], "finished_sub_slots", [new_finished_ss] + blocks[-1].finished_sub_slots[1:]
)
result, err, _ = await empty_blockchain.receive_block(block_bad)
assert err == Err.INVALID_SUB_EPOCH_SUMMARY_HASH
return
await empty_blockchain.receive_block(blocks[-1])
@pytest.mark.asyncio
async def test_too_many_sub_blocks(self, empty_blockchain):
# 4: TODO
pass
@pytest.mark.asyncio
async def test_bad_pos(self, empty_blockchain):
# 5
blocks = bt.get_consecutive_blocks(2)
assert (await empty_blockchain.receive_block(blocks[0]))[0] == ReceiveBlockResult.NEW_PEAK
block_bad = recursive_replace(blocks[-1], "reward_chain_sub_block.proof_of_space.challenge", std_hash(b""))
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.INVALID_POSPACE
block_bad = recursive_replace(
blocks[-1], "reward_chain_sub_block.proof_of_space.pool_contract_puzzle_hash", std_hash(b"")
)
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.INVALID_POSPACE
block_bad = recursive_replace(blocks[-1], "reward_chain_sub_block.proof_of_space.pool_public_key", None)
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.INVALID_POSPACE
block_bad = recursive_replace(
blocks[-1],
"reward_chain_sub_block.proof_of_space.plot_public_key",
AugSchemeMPL.key_gen(std_hash(b"1231n")).get_g1(),
)
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.INVALID_POSPACE
block_bad = recursive_replace(
blocks[-1],
"reward_chain_sub_block.proof_of_space.size",
32,
)
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.INVALID_POSPACE
block_bad = recursive_replace(
blocks[-1],
"reward_chain_sub_block.proof_of_space.proof",
bytes([1] * int(blocks[-1].reward_chain_sub_block.proof_of_space.size * 64 / 8)),
)
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.INVALID_POSPACE
# TODO: test not passing the plot filter
@pytest.mark.asyncio
async def test_bad_signage_point_index(self, empty_blockchain):
# 6
blocks = bt.get_consecutive_blocks(2)
assert (await empty_blockchain.receive_block(blocks[0]))[0] == ReceiveBlockResult.NEW_PEAK
with pytest.raises(ValueError):
block_bad = recursive_replace(
blocks[-1], "reward_chain_sub_block.signage_point_index", test_constants.NUM_SPS_SUB_SLOT
)
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.INVALID_SP_INDEX
with pytest.raises(ValueError):
block_bad = recursive_replace(
blocks[-1], "reward_chain_sub_block.signage_point_index", test_constants.NUM_SPS_SUB_SLOT + 1
)
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.INVALID_SP_INDEX
@pytest.mark.asyncio
async def test_sp_0_no_sp(self, empty_blockchain):
# 7
blocks = []
case_1, case_2 = False, False
while not case_1 or not case_2:
blocks = bt.get_consecutive_blocks(1, block_list_input=blocks)
if blocks[-1].reward_chain_sub_block.signage_point_index == 0:
case_1 = True
block_bad = recursive_replace(blocks[-1], "reward_chain_sub_block.signage_point_index", uint8(1))
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.INVALID_SP_INDEX
else:
case_2 = True
block_bad = recursive_replace(blocks[-1], "reward_chain_sub_block.signage_point_index", uint8(0))
error_code = (await empty_blockchain.receive_block(block_bad))[1]
assert error_code == Err.INVALID_SP_INDEX or error_code == Err.INVALID_POSPACE
assert (await empty_blockchain.receive_block(blocks[-1]))[0] == ReceiveBlockResult.NEW_PEAK
@pytest.mark.asyncio
async def test_epoch_overflows(self, empty_blockchain):
# 9. TODO. This is hard to test because it requires modifying the block tools to make these special blocks
pass
@pytest.mark.asyncio
async def test_bad_total_iters(self, empty_blockchain):
# 10
blocks = bt.get_consecutive_blocks(2)
assert (await empty_blockchain.receive_block(blocks[0]))[0] == ReceiveBlockResult.NEW_PEAK
block_bad = recursive_replace(
blocks[-1], "reward_chain_sub_block.total_iters", blocks[-1].reward_chain_sub_block.total_iters + 1
)
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.INVALID_TOTAL_ITERS
@pytest.mark.asyncio
async def test_bad_rc_sp_vdf(self, empty_blockchain):
# 11
blocks = bt.get_consecutive_blocks(1)
assert (await empty_blockchain.receive_block(blocks[0]))[0] == ReceiveBlockResult.NEW_PEAK
while True:
blocks = bt.get_consecutive_blocks(1, block_list_input=blocks)
if blocks[-1].reward_chain_sub_block.signage_point_index != 0:
block_bad = recursive_replace(
blocks[-1], "reward_chain_sub_block.reward_chain_sp_vdf.challenge", std_hash(b"1")
)
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.INVALID_RC_SP_VDF
block_bad = recursive_replace(
blocks[-1],
"reward_chain_sub_block.reward_chain_sp_vdf.output",
ClassgroupElement(int512(10), int512(2)),
)
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.INVALID_RC_SP_VDF
block_bad = recursive_replace(
blocks[-1],
"reward_chain_sub_block.reward_chain_sp_vdf.number_of_iterations",
uint64(1111111111111),
)
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.INVALID_RC_SP_VDF
block_bad = recursive_replace(
blocks[-1],
"reward_chain_sp_proof",
VDFProof(uint8(0), std_hash(b"")),
)
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.INVALID_RC_SP_VDF
return
assert (await empty_blockchain.receive_block(blocks[-1]))[0] == ReceiveBlockResult.NEW_PEAK
@pytest.mark.asyncio
async def test_bad_rc_sp_sig(self, empty_blockchain):
# 12
blocks = bt.get_consecutive_blocks(2)
assert (await empty_blockchain.receive_block(blocks[0]))[0] == ReceiveBlockResult.NEW_PEAK
block_bad = recursive_replace(
blocks[-1], "reward_chain_sub_block.reward_chain_sp_signature", G2Element.generator()
)
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.INVALID_RC_SIGNATURE
@pytest.mark.asyncio
async def test_bad_cc_sp_vdf(self, empty_blockchain):
# 13. Note: does not validate fully due to proof of space being validated first
blocks = bt.get_consecutive_blocks(1)
assert (await empty_blockchain.receive_block(blocks[0]))[0] == ReceiveBlockResult.NEW_PEAK
while True:
blocks = bt.get_consecutive_blocks(1, block_list_input=blocks)
if blocks[-1].reward_chain_sub_block.signage_point_index != 0:
block_bad = recursive_replace(
blocks[-1], "reward_chain_sub_block.challenge_chain_sp_vdf.challenge", std_hash(b"1")
)
assert (await empty_blockchain.receive_block(block_bad))[0] == ReceiveBlockResult.INVALID_BLOCK
block_bad = recursive_replace(
blocks[-1],
"reward_chain_sub_block.challenge_chain_sp_vdf.output",
ClassgroupElement(int512(10), int512(2)),
)
assert (await empty_blockchain.receive_block(block_bad))[0] == ReceiveBlockResult.INVALID_BLOCK
block_bad = recursive_replace(
blocks[-1],
"reward_chain_sub_block.challenge_chain_sp_vdf.number_of_iterations",
uint64(1111111111111),
)
assert (await empty_blockchain.receive_block(block_bad))[0] == ReceiveBlockResult.INVALID_BLOCK
block_bad = recursive_replace(
blocks[-1],
"challenge_chain_sp_proof",
VDFProof(uint8(0), std_hash(b"")),
)
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.INVALID_CC_SP_VDF
return
assert (await empty_blockchain.receive_block(blocks[-1]))[0] == ReceiveBlockResult.NEW_PEAK
@pytest.mark.asyncio
async def test_bad_cc_sp_sig(self, empty_blockchain):
# 14
blocks = bt.get_consecutive_blocks(2)
assert (await empty_blockchain.receive_block(blocks[0]))[0] == ReceiveBlockResult.NEW_PEAK
block_bad = recursive_replace(
blocks[-1], "reward_chain_sub_block.challenge_chain_sp_signature", G2Element.generator()
)
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.INVALID_CC_SIGNATURE
@pytest.mark.asyncio
async def test_is_block(self, empty_blockchain):
# 15: TODO
pass
@pytest.mark.asyncio
async def test_bad_foliage_sb_sig(self, empty_blockchain):
# 16
blocks = bt.get_consecutive_blocks(2)
assert (await empty_blockchain.receive_block(blocks[0]))[0] == ReceiveBlockResult.NEW_PEAK
block_bad = recursive_replace(
blocks[-1], "foliage_sub_block.foliage_sub_block_signature", G2Element.generator()
)
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.INVALID_PLOT_SIGNATURE
@pytest.mark.asyncio
async def test_bad_foliage_block_sig(self, empty_blockchain):
# 17
blocks = bt.get_consecutive_blocks(1)
assert (await empty_blockchain.receive_block(blocks[0]))[0] == ReceiveBlockResult.NEW_PEAK
while True:
blocks = bt.get_consecutive_blocks(1, block_list_input=blocks)
if blocks[-1].foliage_block is not None:
block_bad = recursive_replace(
blocks[-1], "foliage_sub_block.foliage_block_signature", G2Element.generator()
)
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.INVALID_PLOT_SIGNATURE
return
assert (await empty_blockchain.receive_block(blocks[-1]))[0] == ReceiveBlockResult.NEW_PEAK
@pytest.mark.asyncio
async def test_unfinished_reward_chain_sb_hash(self, empty_blockchain):
# 18
blocks = bt.get_consecutive_blocks(2)
assert (await empty_blockchain.receive_block(blocks[0]))[0] == ReceiveBlockResult.NEW_PEAK
block_bad: FullBlock = recursive_replace(
blocks[-1], "foliage_sub_block.foliage_sub_block_data.unfinished_reward_block_hash", std_hash(b"2")
)
new_m = block_bad.foliage_sub_block.foliage_sub_block_data.get_hash()
new_fsb_sig = bt.get_plot_signature(new_m, blocks[-1].reward_chain_sub_block.proof_of_space.plot_public_key)
block_bad = recursive_replace(block_bad, "foliage_sub_block.foliage_sub_block_signature", new_fsb_sig)
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.INVALID_URSB_HASH
@pytest.mark.asyncio
async def test_pool_target_height(self, empty_blockchain):
# 19
blocks = bt.get_consecutive_blocks(3)
assert (await empty_blockchain.receive_block(blocks[0]))[0] == ReceiveBlockResult.NEW_PEAK
assert (await empty_blockchain.receive_block(blocks[1]))[0] == ReceiveBlockResult.NEW_PEAK
block_bad: FullBlock = recursive_replace(
blocks[-1], "foliage_sub_block.foliage_sub_block_data.pool_target.max_height", 1
)
new_m = block_bad.foliage_sub_block.foliage_sub_block_data.get_hash()
new_fsb_sig = bt.get_plot_signature(new_m, blocks[-1].reward_chain_sub_block.proof_of_space.plot_public_key)
block_bad = recursive_replace(block_bad, "foliage_sub_block.foliage_sub_block_signature", new_fsb_sig)
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.OLD_POOL_TARGET
@pytest.mark.asyncio
async def test_pool_target_pre_farm(self, empty_blockchain):
# 20a
blocks = bt.get_consecutive_blocks(1)
block_bad: FullBlock = recursive_replace(
blocks[-1], "foliage_sub_block.foliage_sub_block_data.pool_target.puzzle_hash", std_hash(b"12")
)
new_m = block_bad.foliage_sub_block.foliage_sub_block_data.get_hash()
new_fsb_sig = bt.get_plot_signature(new_m, blocks[-1].reward_chain_sub_block.proof_of_space.plot_public_key)
block_bad = recursive_replace(block_bad, "foliage_sub_block.foliage_sub_block_signature", new_fsb_sig)
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.INVALID_PREFARM
@pytest.mark.asyncio
async def test_pool_target_signature(self, empty_blockchain):
# 20b
blocks = bt.get_consecutive_blocks(3)
assert (await empty_blockchain.receive_block(blocks[0]))[0] == ReceiveBlockResult.NEW_PEAK
assert (await empty_blockchain.receive_block(blocks[1]))[0] == ReceiveBlockResult.NEW_PEAK
block_bad: FullBlock = recursive_replace(
blocks[-1], "foliage_sub_block.foliage_sub_block_data.pool_signature", G2Element.generator()
)
new_m = block_bad.foliage_sub_block.foliage_sub_block_data.get_hash()
new_fsb_sig = bt.get_plot_signature(new_m, blocks[-1].reward_chain_sub_block.proof_of_space.plot_public_key)
block_bad = recursive_replace(block_bad, "foliage_sub_block.foliage_sub_block_signature", new_fsb_sig)
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.INVALID_POOL_SIGNATURE
@pytest.mark.asyncio
async def test_foliage_data_presence(self, empty_blockchain):
# 22
blocks = bt.get_consecutive_blocks(1)
assert (await empty_blockchain.receive_block(blocks[0]))[0] == ReceiveBlockResult.NEW_PEAK
case_1, case_2 = False, False
while not case_1 or not case_2:
blocks = bt.get_consecutive_blocks(1, block_list_input=blocks)
if blocks[-1].foliage_block is not None:
case_1 = True
block_bad: FullBlock = recursive_replace(blocks[-1], "foliage_sub_block.foliage_block_hash", None)
else:
case_2 = True
block_bad: FullBlock = recursive_replace(
blocks[-1], "foliage_sub_block.foliage_block_hash", std_hash(b"")
)
err_code = (await empty_blockchain.receive_block(block_bad))[1]
assert err_code == Err.INVALID_FOLIAGE_BLOCK_PRESENCE or err_code == Err.INVALID_IS_BLOCK
await empty_blockchain.receive_block(blocks[-1])
@pytest.mark.asyncio
async def test_foliage_block_hash(self, empty_blockchain):
# 23
blocks = bt.get_consecutive_blocks(1)
assert (await empty_blockchain.receive_block(blocks[0]))[0] == ReceiveBlockResult.NEW_PEAK
case_1, case_2 = False, False
while not case_1 or not case_2:
blocks = bt.get_consecutive_blocks(1, block_list_input=blocks)
if blocks[-1].foliage_block is not None:
block_bad: FullBlock = recursive_replace(
blocks[-1], "foliage_sub_block.foliage_block_hash", std_hash(b"2")
)
new_m = block_bad.foliage_sub_block.foliage_block_hash
new_fbh_sig = bt.get_plot_signature(
new_m, blocks[-1].reward_chain_sub_block.proof_of_space.plot_public_key
)
block_bad = recursive_replace(block_bad, "foliage_sub_block.foliage_block_signature", new_fbh_sig)
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.INVALID_FOLIAGE_BLOCK_HASH
return
await empty_blockchain.receive_block(blocks[-1])
@pytest.mark.asyncio
async def test_genesis_bad_prev_block(self, empty_blockchain):
# 24a
blocks = bt.get_consecutive_blocks(1)
block_bad: FullBlock = recursive_replace(blocks[-1], "foliage_block.prev_block_hash", std_hash(b"2"))
block_bad: FullBlock = recursive_replace(
block_bad, "foliage_sub_block.foliage_block_hash", block_bad.foliage_block.get_hash()
)
new_m = block_bad.foliage_sub_block.foliage_block_hash
new_fbh_sig = bt.get_plot_signature(new_m, blocks[-1].reward_chain_sub_block.proof_of_space.plot_public_key)
block_bad = recursive_replace(block_bad, "foliage_sub_block.foliage_block_signature", new_fbh_sig)
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.INVALID_PREV_BLOCK_HASH
@pytest.mark.asyncio
async def test_bad_prev_block_non_genesis(self, empty_blockchain):
# 24b
blocks = bt.get_consecutive_blocks(1)
assert (await empty_blockchain.receive_block(blocks[0]))[0] == ReceiveBlockResult.NEW_PEAK
while True:
blocks = bt.get_consecutive_blocks(1, block_list_input=blocks)
if blocks[-1].foliage_block is not None:
block_bad: FullBlock = recursive_replace(blocks[-1], "foliage_block.prev_block_hash", std_hash(b"2"))
block_bad: FullBlock = recursive_replace(
block_bad, "foliage_sub_block.foliage_block_hash", block_bad.foliage_block.get_hash()
)
new_m = block_bad.foliage_sub_block.foliage_block_hash
new_fbh_sig = bt.get_plot_signature(
new_m, blocks[-1].reward_chain_sub_block.proof_of_space.plot_public_key
)
block_bad = recursive_replace(block_bad, "foliage_sub_block.foliage_block_signature", new_fbh_sig)
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.INVALID_PREV_BLOCK_HASH
return
await empty_blockchain.receive_block(blocks[-1])
@pytest.mark.asyncio
async def test_bad_filter_hash(self, empty_blockchain):
# 25
blocks = bt.get_consecutive_blocks(1)
assert (await empty_blockchain.receive_block(blocks[0]))[0] == ReceiveBlockResult.NEW_PEAK
while True:
blocks = bt.get_consecutive_blocks(1, block_list_input=blocks)
if blocks[-1].foliage_block is not None:
block_bad: FullBlock = recursive_replace(blocks[-1], "foliage_block.filter_hash", std_hash(b"2"))
block_bad: FullBlock = recursive_replace(
block_bad, "foliage_sub_block.foliage_block_hash", block_bad.foliage_block.get_hash()
)
new_m = block_bad.foliage_sub_block.foliage_block_hash
new_fbh_sig = bt.get_plot_signature(
new_m, blocks[-1].reward_chain_sub_block.proof_of_space.plot_public_key
)
block_bad = recursive_replace(block_bad, "foliage_sub_block.foliage_block_signature", new_fbh_sig)
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.INVALID_TRANSACTIONS_FILTER_HASH
return
await empty_blockchain.receive_block(blocks[-1])
@pytest.mark.asyncio
async def test_bad_timestamp(self, empty_blockchain):
# 26
blocks = bt.get_consecutive_blocks(1)
assert (await empty_blockchain.receive_block(blocks[0]))[0] == ReceiveBlockResult.NEW_PEAK
while True:
blocks = bt.get_consecutive_blocks(1, block_list_input=blocks)
if blocks[-1].foliage_block is not None:
block_bad: FullBlock = recursive_replace(
blocks[-1], "foliage_block.timestamp", blocks[0].foliage_block.timestamp - 10
)
block_bad: FullBlock = recursive_replace(
block_bad, "foliage_sub_block.foliage_block_hash", block_bad.foliage_block.get_hash()
)
new_m = block_bad.foliage_sub_block.foliage_block_hash
new_fbh_sig = bt.get_plot_signature(
new_m, blocks[-1].reward_chain_sub_block.proof_of_space.plot_public_key
)
block_bad = recursive_replace(block_bad, "foliage_sub_block.foliage_block_signature", new_fbh_sig)
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.TIMESTAMP_TOO_FAR_IN_PAST
block_bad: FullBlock = recursive_replace(
blocks[-1], "foliage_block.timestamp", blocks[0].foliage_block.timestamp + 10000000
)
block_bad: FullBlock = recursive_replace(
block_bad, "foliage_sub_block.foliage_block_hash", block_bad.foliage_block.get_hash()
)
new_m = block_bad.foliage_sub_block.foliage_block_hash
new_fbh_sig = bt.get_plot_signature(
new_m, blocks[-1].reward_chain_sub_block.proof_of_space.plot_public_key
)
block_bad = recursive_replace(block_bad, "foliage_sub_block.foliage_block_signature", new_fbh_sig)
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.TIMESTAMP_TOO_FAR_IN_FUTURE
return
await empty_blockchain.receive_block(blocks[-1])
@pytest.mark.asyncio
async def test_sub_block_height(self, empty_blockchain):
# 27
blocks = bt.get_consecutive_blocks(2)
assert (await empty_blockchain.receive_block(blocks[0]))[0] == ReceiveBlockResult.NEW_PEAK
block_bad: FullBlock = recursive_replace(blocks[-1], "reward_chain_sub_block.sub_block_height", 2)
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.INVALID_HEIGHT
@pytest.mark.asyncio
async def test_sub_block_height_genesis(self, empty_blockchain):
# 27
blocks = bt.get_consecutive_blocks(1)
block_bad: FullBlock = recursive_replace(blocks[-1], "reward_chain_sub_block.sub_block_height", 1)
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.INVALID_PREV_BLOCK_HASH
@pytest.mark.asyncio
async def test_weight(self, empty_blockchain):
# 28
blocks = bt.get_consecutive_blocks(2)
assert (await empty_blockchain.receive_block(blocks[0]))[0] == ReceiveBlockResult.NEW_PEAK
block_bad: FullBlock = recursive_replace(blocks[-1], "reward_chain_sub_block.weight", 22131)
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.INVALID_WEIGHT
@pytest.mark.asyncio
async def test_weight_genesis(self, empty_blockchain):
# 28
blocks = bt.get_consecutive_blocks(1)
block_bad: FullBlock = recursive_replace(blocks[-1], "reward_chain_sub_block.weight", 0)
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.INVALID_WEIGHT
@pytest.mark.asyncio
async def test_bad_cc_ip_vdf(self, empty_blockchain):
# 29
blocks = bt.get_consecutive_blocks(1)
assert (await empty_blockchain.receive_block(blocks[0]))[0] == ReceiveBlockResult.NEW_PEAK
blocks = bt.get_consecutive_blocks(1, block_list_input=blocks)
block_bad = recursive_replace(
blocks[-1], "reward_chain_sub_block.challenge_chain_ip_vdf.challenge", std_hash(b"1")
)
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.INVALID_CC_IP_VDF
block_bad = recursive_replace(
blocks[-1],
"reward_chain_sub_block.challenge_chain_ip_vdf.output",
ClassgroupElement(int512(10), int512(2)),
)
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.INVALID_CC_IP_VDF
block_bad = recursive_replace(
blocks[-1],
"reward_chain_sub_block.challenge_chain_ip_vdf.number_of_iterations",
uint64(1111111111111),
)
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.INVALID_CC_IP_VDF
block_bad = recursive_replace(
blocks[-1],
"challenge_chain_ip_proof",
VDFProof(uint8(0), std_hash(b"")),
)
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.INVALID_CC_IP_VDF
@pytest.mark.asyncio
async def test_bad_rc_ip_vdf(self, empty_blockchain):
# 30
blocks = bt.get_consecutive_blocks(1)
assert (await empty_blockchain.receive_block(blocks[0]))[0] == ReceiveBlockResult.NEW_PEAK
blocks = bt.get_consecutive_blocks(1, block_list_input=blocks)
block_bad = recursive_replace(
blocks[-1], "reward_chain_sub_block.reward_chain_ip_vdf.challenge", std_hash(b"1")
)
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.INVALID_RC_IP_VDF
block_bad = recursive_replace(
blocks[-1],
"reward_chain_sub_block.reward_chain_ip_vdf.output",
ClassgroupElement(int512(10), int512(2)),
)
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.INVALID_RC_IP_VDF
block_bad = recursive_replace(
blocks[-1],
"reward_chain_sub_block.reward_chain_ip_vdf.number_of_iterations",
uint64(1111111111111),
)
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.INVALID_RC_IP_VDF
block_bad = recursive_replace(
blocks[-1],
"reward_chain_ip_proof",
VDFProof(uint8(0), std_hash(b"")),
)
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.INVALID_RC_IP_VDF
@pytest.mark.asyncio
async def test_bad_icc_ip_vdf(self, empty_blockchain):
# 31
blocks = bt.get_consecutive_blocks(1)
assert (await empty_blockchain.receive_block(blocks[0]))[0] == ReceiveBlockResult.NEW_PEAK
blocks = bt.get_consecutive_blocks(1, block_list_input=blocks)
block_bad = recursive_replace(
blocks[-1], "reward_chain_sub_block.infused_challenge_chain_ip_vdf.challenge", std_hash(b"1")
)
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.INVALID_ICC_VDF
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.INVALID_ICC_VDF
block_bad = recursive_replace(
blocks[-1],
"reward_chain_sub_block.infused_challenge_chain_ip_vdf.output",
ClassgroupElement(int512(10), int512(2)),
)
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.INVALID_ICC_VDF
block_bad = recursive_replace(
blocks[-1],
"reward_chain_sub_block.infused_challenge_chain_ip_vdf.number_of_iterations",
uint64(1111111111111),
)
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.INVALID_ICC_VDF
block_bad = recursive_replace(
blocks[-1],
"infused_challenge_chain_ip_proof",
VDFProof(uint8(0), std_hash(b"")),
)
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.INVALID_ICC_VDF
@pytest.mark.asyncio
async def test_reward_block_hash(self, empty_blockchain):
# 32
blocks = bt.get_consecutive_blocks(2)
assert (await empty_blockchain.receive_block(blocks[0]))[0] == ReceiveBlockResult.NEW_PEAK
block_bad: FullBlock = recursive_replace(blocks[-1], "foliage_sub_block.reward_block_hash", std_hash(b""))
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.INVALID_REWARD_BLOCK_HASH
@pytest.mark.asyncio
async def test_reward_block_hash_2(self, empty_blockchain):
# 33
blocks = bt.get_consecutive_blocks(1)
block_bad: FullBlock = recursive_replace(blocks[0], "reward_chain_sub_block.is_block", False)
block_bad: FullBlock = recursive_replace(
block_bad, "foliage_sub_block.reward_block_hash", block_bad.reward_chain_sub_block.get_hash()
)
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.INVALID_FOLIAGE_BLOCK_PRESENCE
assert (await empty_blockchain.receive_block(blocks[0]))[0] == ReceiveBlockResult.NEW_PEAK
# Test one which should not be a block
while True:
blocks = bt.get_consecutive_blocks(1, block_list_input=blocks)
if not blocks[-1].is_block():
block_bad: FullBlock = recursive_replace(blocks[-1], "reward_chain_sub_block.is_block", True)
block_bad: FullBlock = recursive_replace(
block_bad, "foliage_sub_block.reward_block_hash", block_bad.reward_chain_sub_block.get_hash()
)
assert (await empty_blockchain.receive_block(block_bad))[1] == Err.INVALID_FOLIAGE_BLOCK_PRESENCE
return
assert (await empty_blockchain.receive_block(blocks[-1]))[0] == ReceiveBlockResult.NEW_PEAK
class TestBodyValidation:
@pytest.mark.asyncio
async def test_not_block_but_has_data(self, empty_blockchain):
# TODO
pass
class TestReorgs:
@pytest.mark.asyncio
async def test_basic_reorg(self, empty_blockchain):
b = empty_blockchain
blocks = bt.get_consecutive_blocks(15)
for block in blocks:
assert (await b.receive_block(block))[0] == ReceiveBlockResult.NEW_PEAK
assert b.get_peak().sub_block_height == 14
blocks_reorg_chain = bt.get_consecutive_blocks(7, blocks[:10], seed=b"2")
for reorg_block in blocks_reorg_chain:
result, error_code, fork_height = await b.receive_block(reorg_block)
if reorg_block.sub_block_height < 10:
assert result == ReceiveBlockResult.ALREADY_HAVE_BLOCK
elif reorg_block.sub_block_height < 14:
assert result == ReceiveBlockResult.ADDED_AS_ORPHAN
elif reorg_block.sub_block_height >= 15:
assert result == ReceiveBlockResult.NEW_PEAK
assert error_code is None
assert b.get_peak().sub_block_height == 16
@pytest.mark.asyncio
async def test_long_reorg(self, empty_blockchain, default_10000_blocks):
# Reorg longer than a difficulty adjustment
# Also tests higher weight chain but lower height
b = empty_blockchain
num_blocks_chain_1 = 3 * test_constants.EPOCH_SUB_BLOCKS + test_constants.MAX_SUB_SLOT_SUB_BLOCKS + 10
num_blocks_chain_2_start = test_constants.EPOCH_SUB_BLOCKS - 20
num_blocks_chain_2 = 3 * test_constants.EPOCH_SUB_BLOCKS + test_constants.MAX_SUB_SLOT_SUB_BLOCKS + 8
assert num_blocks_chain_1 < 10000
blocks = default_10000_blocks[:num_blocks_chain_1]
for block in blocks:
assert (await b.receive_block(block))[0] == ReceiveBlockResult.NEW_PEAK
chain_1_height = b.get_peak().sub_block_height
chain_1_weight = b.get_peak().weight
assert chain_1_height == (num_blocks_chain_1 - 1)
# These blocks will have less time between them (timestamp) and therefore will make difficulty go up
# This means that the weight will grow faster, and we can get a heavier chain with lower height
blocks_reorg_chain = bt.get_consecutive_blocks(
num_blocks_chain_2 - num_blocks_chain_2_start,
blocks[:num_blocks_chain_2_start],
seed=b"2",
time_per_sub_block=8,
)
found_orphan = False
for reorg_block in blocks_reorg_chain:
result, error_code, fork_height = await b.receive_block(reorg_block)
if reorg_block.sub_block_height < num_blocks_chain_2_start:
assert result == ReceiveBlockResult.ALREADY_HAVE_BLOCK
if reorg_block.weight <= chain_1_weight:
if result == ReceiveBlockResult.ADDED_AS_ORPHAN:
found_orphan = True
assert error_code is None
assert result == ReceiveBlockResult.ADDED_AS_ORPHAN or result == ReceiveBlockResult.ALREADY_HAVE_BLOCK
elif reorg_block.weight > chain_1_weight:
assert reorg_block.sub_block_height < chain_1_height
assert result == ReceiveBlockResult.NEW_PEAK
assert error_code is None
assert found_orphan
assert b.get_peak().weight > chain_1_weight
assert b.get_peak().sub_block_height < chain_1_height
@pytest.mark.asyncio
async def test_reorg_from_genesis(self, empty_blockchain):
b = empty_blockchain
WALLET_A = WalletTool()
WALLET_A_PUZZLE_HASHES = [WALLET_A.get_new_puzzlehash() for _ in range(5)]
blocks = bt.get_consecutive_blocks(15)
for block in blocks:
assert (await b.receive_block(block))[0] == ReceiveBlockResult.NEW_PEAK
assert b.get_peak().sub_block_height == 14
# Reorg to alternate chain that is 1 height longer
found_orphan = False
blocks_reorg_chain = bt.get_consecutive_blocks(16, [], seed=b"2")
for reorg_block in blocks_reorg_chain:
result, error_code, fork_height = await b.receive_block(reorg_block)
if reorg_block.sub_block_height < 14:
if result == ReceiveBlockResult.ADDED_AS_ORPHAN:
found_orphan = True
assert result == ReceiveBlockResult.ADDED_AS_ORPHAN or result == ReceiveBlockResult.ALREADY_HAVE_BLOCK
elif reorg_block.sub_block_height >= 15:
assert result == ReceiveBlockResult.NEW_PEAK
assert error_code is None
# Back to original chain
blocks_reorg_chain_2 = bt.get_consecutive_blocks(3, blocks, seed=b"3")
result, error_code, fork_height = await b.receive_block(blocks_reorg_chain_2[-3])
assert result == ReceiveBlockResult.ADDED_AS_ORPHAN
result, error_code, fork_height = await b.receive_block(blocks_reorg_chain_2[-2])
assert result == ReceiveBlockResult.NEW_PEAK
result, error_code, fork_height = await b.receive_block(blocks_reorg_chain_2[-1])
assert result == ReceiveBlockResult.NEW_PEAK
assert found_orphan
assert b.get_peak().sub_block_height == 17
@pytest.mark.asyncio
async def test_reorg_transaction(self, empty_blockchain):
b = empty_blockchain
wallet_a = WalletTool()
WALLET_A_PUZZLE_HASHES = [wallet_a.get_new_puzzlehash() for _ in range(5)]
coinbase_puzzlehash = WALLET_A_PUZZLE_HASHES[0]
receiver_puzzlehash = WALLET_A_PUZZLE_HASHES[1]
blocks = bt.get_consecutive_blocks(10, farmer_reward_puzzle_hash=coinbase_puzzlehash)
blocks = bt.get_consecutive_blocks(
2, blocks, farmer_reward_puzzle_hash=coinbase_puzzlehash, guarantee_block=True
)
spend_block = blocks[10]
spend_coin = None
for coin in list(spend_block.get_included_reward_coins()):
if coin.puzzle_hash == coinbase_puzzlehash:
spend_coin = coin
spend_bundle = wallet_a.generate_signed_transaction(1000, receiver_puzzlehash, spend_coin)
blocks = bt.get_consecutive_blocks(
2,
blocks,
farmer_reward_puzzle_hash=coinbase_puzzlehash,
transaction_data=spend_bundle,
guarantee_block=True,
)
blocks_fork = bt.get_consecutive_blocks(
1, blocks[:12], farmer_reward_puzzle_hash=coinbase_puzzlehash, seed=b"123", guarantee_block=True
)
blocks_fork = bt.get_consecutive_blocks(
2,
blocks_fork,
farmer_reward_puzzle_hash=coinbase_puzzlehash,
transaction_data=spend_bundle,
guarantee_block=True,
seed=b"1245",
)
for block in blocks:
result, error_code, _ = await b.receive_block(block)
assert error_code is None and result == ReceiveBlockResult.NEW_PEAK
for block in blocks_fork:
result, error_code, _ = await b.receive_block(block)
assert error_code is None
class TestPreValidation:
@pytest.mark.asyncio
async def test_pre_validation_fails_bad_blocks(self, empty_blockchain):
blocks = bt.get_consecutive_blocks(2)
assert (await empty_blockchain.receive_block(blocks[0]))[0] == ReceiveBlockResult.NEW_PEAK
block_bad = recursive_replace(
blocks[-1], "reward_chain_sub_block.total_iters", blocks[-1].reward_chain_sub_block.total_iters + 1
)
res = await empty_blockchain.pre_validate_blocks_multiprocessing([blocks[0], block_bad])
assert res[0].error is None
assert res[1].error is not None
@pytest.mark.asyncio
async def test_pre_validation(self, empty_blockchain, default_1000_blocks):
blocks = default_1000_blocks[:100]
start = time.time()
n_at_a_time = min(multiprocessing.cpu_count(), 32)
times_pv = []
times_rb = []
for i in range(0, len(blocks), n_at_a_time):
end_i = min(i + n_at_a_time, len(blocks))
blocks_to_validate = blocks[i:end_i]
start_pv = time.time()
res = await empty_blockchain.pre_validate_blocks_multiprocessing(blocks_to_validate)
end_pv = time.time()
times_pv.append(end_pv - start_pv)
assert res is not None
for n in range(end_i - i):
assert res[n] is not None
assert res[n].error is None
block = blocks_to_validate[n]
start_rb = time.time()
result, err, _ = await empty_blockchain.receive_block(block, res[n])
end_rb = time.time()
times_rb.append(end_rb - start_rb)
assert err is None
assert result == ReceiveBlockResult.NEW_PEAK
log.info(
f"Added block {block.sub_block_height} total iters {block.total_iters} "
f"new slot? {len(block.finished_sub_slots)}, time {end_rb - start_rb}"
)
end = time.time()
log.info(f"Total time: {end - start} seconds")
log.info(f"Average pv: {sum(times_pv)/(len(blocks)/n_at_a_time)}")
log.info(f"Average rb: {sum(times_rb)/(len(blocks))}")
| 48.088415 | 120 | 0.63416 |
592d342df6c9858c4c94c87ee163aac0c7eacb74 | 11,556 | py | Python | hsequeces_bench.py | bankbiz/Key.Net | 5ba46614821e94be1b36d97721bd6c2e5fff9e20 | [
"BSD-3-Clause-Clear"
] | 162 | 2019-09-26T09:03:31.000Z | 2022-03-29T08:51:44.000Z | keypoint/hsequeces_bench.py | semnan-university-ai/Key.Net | 887f595cb7b87e0551d52e34441f61546a9aee97 | [
"MIT"
] | 14 | 2019-10-30T07:36:12.000Z | 2022-03-23T03:22:19.000Z | keypoint/hsequeces_bench.py | semnan-university-ai/Key.Net | 887f595cb7b87e0551d52e34441f61546a9aee97 | [
"MIT"
] | 36 | 2019-10-15T10:14:51.000Z | 2021-12-08T13:02:28.000Z | import os
import argparse
import numpy as np
import pickle
from tqdm import tqdm
import HSequences_bench.tools.aux_tools as aux
import HSequences_bench.tools.geometry_tools as geo_tools
import HSequences_bench.tools.repeatability_tools as rep_tools
import HSequences_bench.tools.matching_tools as match_tools
from HSequences_bench.tools.HSequences_reader import HSequences_dataset
from HSequences_bench.tools.opencv_matcher import OpencvBruteForceMatcher
def hsequences_metrics():
parser = argparse.ArgumentParser(description='HSequences Compute Repeatability')
parser.add_argument('--data-dir', type=str, default='hpatches-sequences-release/',
help='The root path to HSequences dataset.')
parser.add_argument('--results-bench-dir', type=str, default='HSequences_bench/results/',
help='The output path to save the results.')
parser.add_argument('--detector-name', type=str, default='KeyNet_default',
help='The name of the detector to compute metrics.')
parser.add_argument('--results-dir', type=str, default='extracted_features/',
help='The path to the extracted points.')
parser.add_argument('--split', type=str, default='view',
help='The name of the HPatches (HSequences) split. Use full, debug_view, debug_illum, view or illum.')
parser.add_argument('--split-path', type=str, default='HSequences_bench/splits.json',
help='The path to the split json file.')
parser.add_argument('--top-k-points', type=int, default=1000,
help='The number of top points to use for evaluation. Set to None to use all points')
parser.add_argument('--overlap', type=float, default=0.6,
help='The overlap threshold for a correspondence to be considered correct.')
parser.add_argument('--pixel-threshold', type=int, default=5,
help='The distance of pixels for a matching correspondence to be considered correct.')
parser.add_argument('--dst-to-src-evaluation', type=bool, default=True,
help='Order to apply homography to points. Use True for dst to src, False otherwise.')
parser.add_argument('--order-coord', type=str, default='xysr',
help='The coordinate order that follows the extracted points. Use either xysr or yxsr.')
args = parser.parse_args()
print(args.detector_name + ': ' + args.split)
aux.check_directory(args.results_bench_dir)
# create the dataloader
data_loader = HSequences_dataset(args.data_dir, args.split, args.split_path)
results = aux.create_overlapping_results(args.detector_name, args.overlap)
# matching method
matcher = OpencvBruteForceMatcher('l2')
count_seq = 0
# load data and compute the keypoints
for sample_id, sample_data in enumerate(data_loader.extract_hsequences()):
sequence = sample_data['sequence_name']
count_seq += 1
image_src = sample_data['im_src']
images_dst = sample_data['images_dst']
h_src_2_dst = sample_data['h_src_2_dst']
h_dst_2_src = sample_data['h_dst_2_src']
print('\nComputing ' + sequence + ' sequence {0} / {1} \n'.format(count_seq, len(data_loader.sequences)))
for idx_im in tqdm(range(len(images_dst))):
# create the mask to filter out the points outside of the common areas
mask_src, mask_dst = geo_tools.create_common_region_masks(h_dst_2_src[idx_im], image_src.shape, images_dst[idx_im].shape)
# compute the files paths
src_pts_filename = os.path.join(args.results_dir, args.detector_name,
'hpatches-sequences-release', '{}/1.ppm.kpt.npy'.format(sample_data['sequence_name']))
src_dsc_filename = os.path.join(args.results_dir, args.detector_name,
'hpatches-sequences-release', '{}/1.ppm.dsc.npy'.format(sample_data['sequence_name']))
dst_pts_filename = os.path.join(args.results_dir, args.detector_name,
'hpatches-sequences-release', '{}/{}.ppm.kpt.npy'.format(sample_data['sequence_name'], idx_im+2))
dst_dsc_filename = os.path.join(args.results_dir, args.detector_name,
'hpatches-sequences-release', '{}/{}.ppm.dsc.npy'.format(sample_data['sequence_name'], idx_im+2))
if not os.path.isfile(src_pts_filename):
print("Could not find the file: " + src_pts_filename)
return False
if not os.path.isfile(src_dsc_filename):
print("Could not find the file: " + src_dsc_filename)
return False
if not os.path.isfile(dst_pts_filename):
print("Could not find the file: " + dst_pts_filename)
return False
if not os.path.isfile(dst_dsc_filename):
print("Could not find the file: " + dst_dsc_filename)
return False
# load the points
src_pts = np.load(src_pts_filename)
src_dsc = np.load(src_dsc_filename)
dst_pts = np.load(dst_pts_filename)
dst_dsc = np.load(dst_dsc_filename)
if args.order_coord == 'xysr':
src_pts = np.asarray(list(map(lambda x: [x[1], x[0], x[2], x[3]], src_pts)))
dst_pts = np.asarray(list(map(lambda x: [x[1], x[0], x[2], x[3]], dst_pts)))
# Check Common Points
src_idx = rep_tools.check_common_points(src_pts, mask_src)
src_pts = src_pts[src_idx]
src_dsc = src_dsc[src_idx]
dst_idx = rep_tools.check_common_points(dst_pts, mask_dst)
dst_pts = dst_pts[dst_idx]
dst_dsc = dst_dsc[dst_idx]
# Select top K points
if args.top_k_points:
src_idx = rep_tools.select_top_k(src_pts, args.top_k_points)
src_pts = src_pts[src_idx]
src_dsc = src_dsc[src_idx]
dst_idx = rep_tools.select_top_k(dst_pts, args.top_k_points)
dst_pts = dst_pts[dst_idx]
dst_dsc = dst_dsc[dst_idx]
src_pts = np.asarray(list(map(lambda x: [x[1], x[0], x[2], x[3]], src_pts)))
dst_pts = np.asarray(list(map(lambda x: [x[1], x[0], x[2], x[3]], dst_pts)))
src_to_dst_pts = geo_tools.apply_homography_to_points(
src_pts, h_src_2_dst[idx_im])
dst_to_src_pts = geo_tools.apply_homography_to_points(
dst_pts, h_dst_2_src[idx_im])
if args.dst_to_src_evaluation:
points_src = src_pts
points_dst = dst_to_src_pts
else:
points_src = src_to_dst_pts
points_dst = dst_pts
# compute repeatability
repeatability_results = rep_tools.compute_repeatability(points_src, points_dst, overlap_err=1-args.overlap,
dist_match_thresh=args.pixel_threshold)
# match descriptors
matches = matcher.match(src_dsc, dst_dsc)
matches_np = aux.convert_opencv_matches_to_numpy(matches)
matches_inv = matcher.match(dst_dsc, src_dsc)
matches_inv_np = aux.convert_opencv_matches_to_numpy(matches_inv)
mask = matches_np[:, 0] == matches_inv_np[matches_np[:, 1], 1]
matches_np = matches_np[mask]
match_score, match_score_corr, num_matches = {}, {}, {}
# compute matching based on pixel distance
for th_i in range(1, 11):
match_score_i, match_score_corr_i, num_matches_i = match_tools.compute_matching_based_distance(points_src, points_dst, matches_np,
repeatability_results['total_num_points'],
pixel_threshold=th_i,
possible_matches=repeatability_results['possible_matches'])
match_score[str(th_i)] = match_score_i
match_score_corr[str(th_i)] = match_score_corr_i
num_matches[str(th_i)] = num_matches_i
mma = np.mean([match_score[str(idx)] for idx in match_score])
results['rep_single_scale'].append(
repeatability_results['rep_single_scale'])
results['rep_multi_scale'].append(
repeatability_results['rep_multi_scale'])
results['num_points_single_scale'].append(
repeatability_results['num_points_single_scale'])
results['num_points_multi_scale'].append(
repeatability_results['num_points_multi_scale'])
results['error_overlap_single_scale'].append(
repeatability_results['error_overlap_single_scale'])
results['error_overlap_multi_scale'].append(
repeatability_results['error_overlap_multi_scale'])
results['mma'].append(match_score[str(args.pixel_threshold)])
results['mma_corr'].append(match_score_corr[str(args.pixel_threshold)])
results['num_matches'].append(num_matches[str(args.pixel_threshold)])
results['num_mutual_corresp'].append(len(matches_np))
results['avg_mma'].append(mma)
results['num_features'].append(repeatability_results['total_num_points'])
# average the results
rep_single = np.array(results['rep_single_scale']).mean()
rep_multi = np.array(results['rep_multi_scale']).mean()
error_overlap_s = np.array(results['error_overlap_single_scale']).mean()
error_overlap_m = np.array(results['error_overlap_multi_scale']).mean()
mma = np.array(results['mma']).mean()
mma_corr = np.array(results['mma_corr']).mean()
num_matches = np.array(results['num_matches']).mean()
num_mutual_corresp = np.array(results['num_mutual_corresp']).mean()
avg_mma = np.array(results['avg_mma']).mean()
num_features = np.array(results['num_features']).mean()
# Matching Score: Matching Score taking into account all features that have been
# detected in any of the two images.
# Matching Score (possible matches): Matching Score only taking into account those features that have been
# detected in both images.
# MMA Score is computed based on the Matching Score (all detected features)
print('\n## Overlap @{0}:\n \
#### Rep. Multi: {1:.4f}\n \
#### Rep. Single: {2:.4f}\n \
#### Overlap Multi: {3:.4f}\n \
#### Overlap Single: {4:.4f}\n \
#### MMA: {5:.4f}\n \
#### MMA (possible matches): {6:.4f}\n \
#### Num matches: {7:.4f}\n \
#### Num Mutual Correspondences: {8:.4f}\n \
#### Avg. over Threshold MMA: {9:.4f}\n \
#### Num Feats: {10:.4f}'.format(
args.overlap, rep_multi, rep_single, error_overlap_s, error_overlap_m, mma,
mma_corr, num_matches, num_mutual_corresp, avg_mma, num_features))
# Store data (serialize)
output_file_path = os.path.join(args.results_bench_dir, '{0}_{1}.pickle'
.format(args.detector_name, args.split))
with open(output_file_path, 'wb') as handle:
pickle.dump(results, handle, protocol=pickle.HIGHEST_PROTOCOL)
if __name__ == '__main__':
hsequences_metrics() | 47.360656 | 146 | 0.624351 |
5bae3e62b32ead986ab1ddb7763be7ffd4563d98 | 1,246 | py | Python | setup.py | ahmadiesa-abu/cloudify-kubernetes-plugin | 3f5363e82f12bb97dafee178c972491898f54680 | [
"Apache-2.0"
] | null | null | null | setup.py | ahmadiesa-abu/cloudify-kubernetes-plugin | 3f5363e82f12bb97dafee178c972491898f54680 | [
"Apache-2.0"
] | null | null | null | setup.py | ahmadiesa-abu/cloudify-kubernetes-plugin | 3f5363e82f12bb97dafee178c972491898f54680 | [
"Apache-2.0"
] | null | null | null | # Copyright (c) 2017-2019 Cloudify Platform Ltd. 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 setuptools import setup
setup(
name='cloudify-kubernetes-plugin',
version='2.6.5',
author='Cloudify Platform Ltd.',
author_email='hello@cloudify.co',
description='Plugin provides Kubernetes management possibility',
packages=['cloudify_kubernetes', 'cloudify_kubernetes.k8s'],
license='LICENSE',
install_requires=[
'cloudify-python-importer==0.1',
'cloudify-common==4.5.5',
'kubernetes==10.0.1',
'pyyaml>=3.12',
'pyasn1>=0.1.7',
'pyasn1-modules>=0.0.5,<0.2.1',
'oauth2client', # used only in GCPServiceAccountAuthentication
]
)
| 34.611111 | 74 | 0.698234 |
65841c48a969f11c93a2932f27057380f030a1f0 | 1,830 | py | Python | venv/Lib/site-packages/nipype/interfaces/mipav/tests/test_auto_JistLaminarProfileSampling.py | richung99/digitizePlots | 6b408c820660a415a289726e3223e8f558d3e18b | [
"MIT"
] | 585 | 2015-01-12T16:06:47.000Z | 2022-03-26T14:51:08.000Z | nipype/interfaces/mipav/tests/test_auto_JistLaminarProfileSampling.py | tamires-consulting/nipype | b7879d75a63b6500b2e7d2c3eba5aa7670339274 | [
"Apache-2.0"
] | 2,329 | 2015-01-01T09:56:41.000Z | 2022-03-30T14:24:49.000Z | nipype/interfaces/mipav/tests/test_auto_JistLaminarProfileSampling.py | tamires-consulting/nipype | b7879d75a63b6500b2e7d2c3eba5aa7670339274 | [
"Apache-2.0"
] | 487 | 2015-01-20T01:04:52.000Z | 2022-03-21T21:22:47.000Z | # AUTO-GENERATED by tools/checkspecs.py - DO NOT EDIT
from ..developer import JistLaminarProfileSampling
def test_JistLaminarProfileSampling_inputs():
input_map = dict(
args=dict(
argstr="%s",
),
environ=dict(
nohash=True,
usedefault=True,
),
inCortex=dict(
argstr="--inCortex %s",
extensions=None,
),
inIntensity=dict(
argstr="--inIntensity %s",
extensions=None,
),
inProfile=dict(
argstr="--inProfile %s",
extensions=None,
),
null=dict(
argstr="--null %s",
),
outProfile2=dict(
argstr="--outProfile2 %s",
hash_files=False,
),
outProfilemapped=dict(
argstr="--outProfilemapped %s",
hash_files=False,
),
xDefaultMem=dict(
argstr="-xDefaultMem %d",
),
xMaxProcess=dict(
argstr="-xMaxProcess %d",
usedefault=True,
),
xPrefExt=dict(
argstr="--xPrefExt %s",
),
)
inputs = JistLaminarProfileSampling.input_spec()
for key, metadata in list(input_map.items()):
for metakey, value in list(metadata.items()):
assert getattr(inputs.traits()[key], metakey) == value
def test_JistLaminarProfileSampling_outputs():
output_map = dict(
outProfile2=dict(
extensions=None,
),
outProfilemapped=dict(
extensions=None,
),
)
outputs = JistLaminarProfileSampling.output_spec()
for key, metadata in list(output_map.items()):
for metakey, value in list(metadata.items()):
assert getattr(outputs.traits()[key], metakey) == value
| 26.521739 | 67 | 0.533333 |
9677eae2ae1c192f3bb5a8e3f2446930f7a144b3 | 7,790 | py | Python | pysnmp/ARISTA-CONFIG-COPY-MIB.py | agustinhenze/mibs.snmplabs.com | 1fc5c07860542b89212f4c8ab807057d9a9206c7 | [
"Apache-2.0"
] | 11 | 2021-02-02T16:27:16.000Z | 2021-08-31T06:22:49.000Z | pysnmp/ARISTA-CONFIG-COPY-MIB.py | agustinhenze/mibs.snmplabs.com | 1fc5c07860542b89212f4c8ab807057d9a9206c7 | [
"Apache-2.0"
] | 75 | 2021-02-24T17:30:31.000Z | 2021-12-08T00:01:18.000Z | pysnmp/ARISTA-CONFIG-COPY-MIB.py | agustinhenze/mibs.snmplabs.com | 1fc5c07860542b89212f4c8ab807057d9a9206c7 | [
"Apache-2.0"
] | 10 | 2019-04-30T05:51:36.000Z | 2022-02-16T03:33:41.000Z | #
# PySNMP MIB module ARISTA-CONFIG-COPY-MIB (http://snmplabs.com/pysmi)
# ASN.1 source file:///Users/davwang4/Dev/mibs.snmplabs.com/asn1/ARISTA-CONFIG-COPY-MIB
# Produced by pysmi-0.3.4 at Mon Apr 29 17:09:07 2019
# On host DAVWANG4-M-1475 platform Darwin version 18.5.0 by user davwang4
# Using Python version 3.7.3 (default, Mar 27 2019, 09:23:15)
#
aristaProducts, aristaModules, aristaMibs = mibBuilder.importSymbols("ARISTA-SMI-MIB", "aristaProducts", "aristaModules", "aristaMibs")
ObjectIdentifier, OctetString, Integer = mibBuilder.importSymbols("ASN1", "ObjectIdentifier", "OctetString", "Integer")
NamedValues, = mibBuilder.importSymbols("ASN1-ENUMERATION", "NamedValues")
ConstraintsUnion, ValueSizeConstraint, ConstraintsIntersection, SingleValueConstraint, ValueRangeConstraint = mibBuilder.importSymbols("ASN1-REFINEMENT", "ConstraintsUnion", "ValueSizeConstraint", "ConstraintsIntersection", "SingleValueConstraint", "ValueRangeConstraint")
ObjectGroup, NotificationGroup, ModuleCompliance = mibBuilder.importSymbols("SNMPv2-CONF", "ObjectGroup", "NotificationGroup", "ModuleCompliance")
Counter32, ModuleIdentity, Integer32, MibScalar, MibTable, MibTableRow, MibTableColumn, Gauge32, Counter64, NotificationType, Unsigned32, IpAddress, MibIdentifier, Bits, TimeTicks, iso, ObjectIdentity = mibBuilder.importSymbols("SNMPv2-SMI", "Counter32", "ModuleIdentity", "Integer32", "MibScalar", "MibTable", "MibTableRow", "MibTableColumn", "Gauge32", "Counter64", "NotificationType", "Unsigned32", "IpAddress", "MibIdentifier", "Bits", "TimeTicks", "iso", "ObjectIdentity")
TextualConvention, RowStatus, DisplayString, DateAndTime = mibBuilder.importSymbols("SNMPv2-TC", "TextualConvention", "RowStatus", "DisplayString", "DateAndTime")
aristaConfigCopyMIB = ModuleIdentity((1, 3, 6, 1, 4, 1, 30065, 3, 7))
aristaConfigCopyMIB.setRevisions(('2014-08-15 00:00', '2013-02-14 00:00',))
if mibBuilder.loadTexts: aristaConfigCopyMIB.setLastUpdated('201408150000Z')
if mibBuilder.loadTexts: aristaConfigCopyMIB.setOrganization('Arista Networks, Inc.')
class ConfigCopyState(TextualConvention, Integer32):
status = 'current'
subtypeSpec = Integer32.subtypeSpec + ConstraintsUnion(SingleValueConstraint(0, 1, 2, 3, 4))
namedValues = NamedValues(("inactive", 0), ("scheduled", 1), ("running", 2), ("completed", 3), ("failed", 4))
class ConfigCopyFailureCause(TextualConvention, Integer32):
status = 'current'
subtypeSpec = Integer32.subtypeSpec + ConstraintsUnion(SingleValueConstraint(0, 1, 2))
namedValues = NamedValues(("none", 0), ("unknown", 1), ("timeout", 2))
aristaConfigCopyCommandTable = MibTable((1, 3, 6, 1, 4, 1, 30065, 3, 7, 1), )
if mibBuilder.loadTexts: aristaConfigCopyCommandTable.setStatus('current')
aristaConfigCopyCommandEntry = MibTableRow((1, 3, 6, 1, 4, 1, 30065, 3, 7, 1, 1), ).setIndexNames((0, "ARISTA-CONFIG-COPY-MIB", "aristaConfigCopyName"), (0, "ARISTA-CONFIG-COPY-MIB", "aristaConfigCopyId"))
if mibBuilder.loadTexts: aristaConfigCopyCommandEntry.setStatus('current')
aristaConfigCopyName = MibTableColumn((1, 3, 6, 1, 4, 1, 30065, 3, 7, 1, 1, 1), DisplayString().subtype(subtypeSpec=ValueSizeConstraint(0, 255)))
if mibBuilder.loadTexts: aristaConfigCopyName.setStatus('current')
aristaConfigCopyId = MibTableColumn((1, 3, 6, 1, 4, 1, 30065, 3, 7, 1, 1, 2), Unsigned32())
if mibBuilder.loadTexts: aristaConfigCopyId.setStatus('current')
aristaConfigCopySourceUri = MibTableColumn((1, 3, 6, 1, 4, 1, 30065, 3, 7, 1, 1, 3), DisplayString().subtype(subtypeSpec=ValueSizeConstraint(0, 512))).setMaxAccess("readcreate")
if mibBuilder.loadTexts: aristaConfigCopySourceUri.setStatus('current')
aristaConfigCopyDestUri = MibTableColumn((1, 3, 6, 1, 4, 1, 30065, 3, 7, 1, 1, 4), DisplayString().subtype(subtypeSpec=ValueSizeConstraint(0, 512))).setMaxAccess("readcreate")
if mibBuilder.loadTexts: aristaConfigCopyDestUri.setStatus('current')
aristaConfigCopyState = MibTableColumn((1, 3, 6, 1, 4, 1, 30065, 3, 7, 1, 1, 5), ConfigCopyState()).setMaxAccess("readonly")
if mibBuilder.loadTexts: aristaConfigCopyState.setStatus('current')
aristaConfigCopyTimeout = MibTableColumn((1, 3, 6, 1, 4, 1, 30065, 3, 7, 1, 1, 6), Unsigned32().clone(60)).setMaxAccess("readcreate")
if mibBuilder.loadTexts: aristaConfigCopyTimeout.setStatus('current')
aristaConfigCopyTimeStarted = MibTableColumn((1, 3, 6, 1, 4, 1, 30065, 3, 7, 1, 1, 7), DateAndTime()).setMaxAccess("readonly")
if mibBuilder.loadTexts: aristaConfigCopyTimeStarted.setStatus('current')
aristaConfigCopyTimeCompleted = MibTableColumn((1, 3, 6, 1, 4, 1, 30065, 3, 7, 1, 1, 8), DateAndTime()).setMaxAccess("readonly")
if mibBuilder.loadTexts: aristaConfigCopyTimeCompleted.setStatus('current')
aristaConfigCopyFailureCause = MibTableColumn((1, 3, 6, 1, 4, 1, 30065, 3, 7, 1, 1, 9), ConfigCopyFailureCause()).setMaxAccess("readonly")
if mibBuilder.loadTexts: aristaConfigCopyFailureCause.setStatus('current')
aristaConfigCopyFailureMessage = MibTableColumn((1, 3, 6, 1, 4, 1, 30065, 3, 7, 1, 1, 10), DisplayString()).setMaxAccess("readonly")
if mibBuilder.loadTexts: aristaConfigCopyFailureMessage.setStatus('current')
aristaConfigCopyRowStatus = MibTableColumn((1, 3, 6, 1, 4, 1, 30065, 3, 7, 1, 1, 11), RowStatus()).setMaxAccess("readcreate")
if mibBuilder.loadTexts: aristaConfigCopyRowStatus.setStatus('current')
aristaConfigCopyConformance = MibIdentifier((1, 3, 6, 1, 4, 1, 30065, 3, 7, 2))
aristaConfigCopyCompliances = MibIdentifier((1, 3, 6, 1, 4, 1, 30065, 3, 7, 2, 1))
aristaConfigCopyGroups = MibIdentifier((1, 3, 6, 1, 4, 1, 30065, 3, 7, 2, 2))
aristaConfigCopyCompliance = ModuleCompliance((1, 3, 6, 1, 4, 1, 30065, 3, 7, 2, 1, 1)).setObjects(("ARISTA-CONFIG-COPY-MIB", "aristaConfigCopyObjectsGroup"))
if getattr(mibBuilder, 'version', (0, 0, 0)) > (4, 4, 0):
aristaConfigCopyCompliance = aristaConfigCopyCompliance.setStatus('current')
aristaConfigCopyObjectsGroup = ObjectGroup((1, 3, 6, 1, 4, 1, 30065, 3, 7, 2, 2, 1)).setObjects(("ARISTA-CONFIG-COPY-MIB", "aristaConfigCopySourceUri"), ("ARISTA-CONFIG-COPY-MIB", "aristaConfigCopyDestUri"), ("ARISTA-CONFIG-COPY-MIB", "aristaConfigCopyState"), ("ARISTA-CONFIG-COPY-MIB", "aristaConfigCopyTimeout"), ("ARISTA-CONFIG-COPY-MIB", "aristaConfigCopyTimeStarted"), ("ARISTA-CONFIG-COPY-MIB", "aristaConfigCopyTimeCompleted"), ("ARISTA-CONFIG-COPY-MIB", "aristaConfigCopyFailureCause"), ("ARISTA-CONFIG-COPY-MIB", "aristaConfigCopyFailureMessage"), ("ARISTA-CONFIG-COPY-MIB", "aristaConfigCopyRowStatus"))
if getattr(mibBuilder, 'version', (0, 0, 0)) > (4, 4, 0):
aristaConfigCopyObjectsGroup = aristaConfigCopyObjectsGroup.setStatus('current')
mibBuilder.exportSymbols("ARISTA-CONFIG-COPY-MIB", aristaConfigCopySourceUri=aristaConfigCopySourceUri, aristaConfigCopyObjectsGroup=aristaConfigCopyObjectsGroup, aristaConfigCopyFailureMessage=aristaConfigCopyFailureMessage, ConfigCopyState=ConfigCopyState, aristaConfigCopyDestUri=aristaConfigCopyDestUri, aristaConfigCopyTimeStarted=aristaConfigCopyTimeStarted, aristaConfigCopyTimeCompleted=aristaConfigCopyTimeCompleted, aristaConfigCopyTimeout=aristaConfigCopyTimeout, aristaConfigCopyName=aristaConfigCopyName, aristaConfigCopyConformance=aristaConfigCopyConformance, PYSNMP_MODULE_ID=aristaConfigCopyMIB, aristaConfigCopyCommandTable=aristaConfigCopyCommandTable, aristaConfigCopyRowStatus=aristaConfigCopyRowStatus, aristaConfigCopyCompliance=aristaConfigCopyCompliance, aristaConfigCopyGroups=aristaConfigCopyGroups, aristaConfigCopyCompliances=aristaConfigCopyCompliances, aristaConfigCopyMIB=aristaConfigCopyMIB, aristaConfigCopyCommandEntry=aristaConfigCopyCommandEntry, aristaConfigCopyId=aristaConfigCopyId, ConfigCopyFailureCause=ConfigCopyFailureCause, aristaConfigCopyState=aristaConfigCopyState, aristaConfigCopyFailureCause=aristaConfigCopyFailureCause)
| 118.030303 | 1,173 | 0.783312 |
19391e510f1d4c983df94b15ea0b6a7366930d67 | 1,036 | py | Python | problem_4.py | YoussefAli99/Problems-vs-Algorithms | 081022d196ec0185374868a4654ec8795cd1cbe3 | [
"MIT"
] | null | null | null | problem_4.py | YoussefAli99/Problems-vs-Algorithms | 081022d196ec0185374868a4654ec8795cd1cbe3 | [
"MIT"
] | null | null | null | problem_4.py | YoussefAli99/Problems-vs-Algorithms | 081022d196ec0185374868a4654ec8795cd1cbe3 | [
"MIT"
] | null | null | null | def sort_012(input_list):
"""
Given an input array consisting on only 0, 1, and 2, sort the array in a single traversal.
Args:
input_list(list): List to be sorted
"""
z,o = 0,0
t = len(input_list) - 1
while o <= t:
if input_list[o] == 0:
input_list[o], input_list[z] = input_list[z], input_list[o]
z += 1
o += 1
elif input_list[o] == 1:
o += 1
elif input_list[o] == 2:
input_list[o], input_list[t] = input_list[t], input_list[o]
t -= 1
return input_list
def test_function(test_case):
sorted_array = sort_012(test_case)
print(sorted_array)
if sorted_array == sorted(test_case):
print("Pass")
else:
print("Fail")
test_function([0, 0, 2, 2, 2, 1, 1, 1, 2, 0, 2])
test_function([2, 1, 2, 0, 0, 2, 1, 0, 1, 0, 0, 2, 2, 2, 1, 2, 0, 0, 0, 2, 1, 0, 2, 0, 0, 1])
test_function([0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2])
test_function([0])
test_function([]) | 28 | 94 | 0.530888 |
e600abd8b90788d1401b155cee468ad6e556ea1b | 2,335 | py | Python | Projects_in_Python/Message- I Love You/love.py | vivekagarwal2349/Mini_Python_Projects | 96fa28d851cddefa5d9a63823b1a9b04ad6c3e04 | [
"MIT"
] | null | null | null | Projects_in_Python/Message- I Love You/love.py | vivekagarwal2349/Mini_Python_Projects | 96fa28d851cddefa5d9a63823b1a9b04ad6c3e04 | [
"MIT"
] | null | null | null | Projects_in_Python/Message- I Love You/love.py | vivekagarwal2349/Mini_Python_Projects | 96fa28d851cddefa5d9a63823b1a9b04ad6c3e04 | [
"MIT"
] | null | null | null | #here we are importing the required stuffs -
from turtle import color, back, left, forward, right, exitonclick
import turtle
color("black")
back(450)
color("orange")
# let us start creating the words
left(90)
forward(100)
back(100)
right(90)
color("black")
forward(100)
left(90)
color("orange")
forward(100)
back(100)
right(90)
#we are adjusting the cursor in such a way where in the cursor will write i love you in the given code.
color("orange")
forward(50)
color("black")
forward(50)
color("orange")
forward(50)
back(50)
left(90)
forward(100)
right(90)
forward(50)
right(90)
forward(100)
left(90)
color("black")
forward(100)
color("orange")
left(120)
forward(110)
back(110)
right(60)
forward(110)
back(110)
right(60)
color("black")
forward(100)
# if we observe carefully, there are only two colors, one is black other one is orange.
color("orange")
forward(50)
back(50)
left(90)
forward(100)
right(90)
forward(50)
back(50)
right(90)
forward(50)
left(90)
forward(50)
back(50)
right(90)
forward(50)
left(90)
forward(50)
color("black")
forward(150)
color("orange")
left(90)
forward(50)
left(45)
forward(75)
back(75)
right(90)
forward(75)
back(75)
left(45)
# we are at the middle of the word
back(50)
right(90)
color("black")
forward(100)
color("orange")
forward(50)
back(50)
left(90)
forward(100)
right(90)
forward(50)
right(90)
forward(100)
left(90)
color("black")
forward(100)
color("orange")
back(50)
left(90)
forward(100)
back(100)
right(90)
forward(50)
left(90)
forward(107)
color("black")
pen = turtle.Turtle()
# we are done with the cursor part.
def curve():
for i in range(200):
pen.right(1)
pen.forward(1)
# what if there is a heart in between the 3 words ??
def heart():
#interesting right? now, let us give the points where we need the heart symbol to be visible
pen.fillcolor('red')
pen.begin_fill()
pen.left(140)
pen.forward(250)
curve()
pen.left(120)
curve()
pen.forward(112)
pen.end_fill()
heart()
def txt(x="" ):
pen.up()
pen.setpos(-70, 60)
pen.down()
pen.color('lightgreen')
pen.write(x, font=("Verdana", 10, ""))
# that's it we are done.
txt()
pen.ht()
exitonclick()
| 15.671141 | 104 | 0.6394 |
239ddaf4723f9d579e4b033891462be6213efdc4 | 698 | py | Python | venv/Scripts/rst2html.py | muatahunt/django_cityloc_pkg_muatahunt | 68074cc3d96ef183b350c1b6492a7c0f7c2524b8 | [
"MIT"
] | null | null | null | venv/Scripts/rst2html.py | muatahunt/django_cityloc_pkg_muatahunt | 68074cc3d96ef183b350c1b6492a7c0f7c2524b8 | [
"MIT"
] | null | null | null | venv/Scripts/rst2html.py | muatahunt/django_cityloc_pkg_muatahunt | 68074cc3d96ef183b350c1b6492a7c0f7c2524b8 | [
"MIT"
] | null | null | null | #!C:\Users\Name\Desktop\Nucamp\Python\3-DevOps\week4\github_packaging\django_cityloc_pkg_muatahunt\venv\Scripts\python.exe
# $Id: rst2html.py 4564 2006-05-21 20:44:42Z wiemann $
# Author: David Goodger <goodger@python.org>
# Copyright: This module has been placed in the public domain.
"""
A minimal front end to the Docutils Publisher, producing HTML.
"""
try:
import locale
locale.setlocale(locale.LC_ALL, '')
except:
pass
from docutils.core import publish_cmdline, default_description
description = ('Generates (X)HTML documents from standalone reStructuredText '
'sources. ' + default_description)
publish_cmdline(writer_name='html', description=description)
| 29.083333 | 122 | 0.755014 |
1485ecc01b16979a783502985855a829802807bd | 17,691 | py | Python | scipy/linalg/basic.py | jasonmccampbell/scipy-refactor | 52708e04bca51e7043248d56383780b1e51e0d8f | [
"BSD-3-Clause"
] | 8 | 2015-10-07T00:37:32.000Z | 2022-01-21T17:02:33.000Z | scipy/linalg/basic.py | enthought/scipy-refactor | 52708e04bca51e7043248d56383780b1e51e0d8f | [
"BSD-3-Clause"
] | null | null | null | scipy/linalg/basic.py | enthought/scipy-refactor | 52708e04bca51e7043248d56383780b1e51e0d8f | [
"BSD-3-Clause"
] | 8 | 2015-05-09T14:23:57.000Z | 2018-11-15T05:56:00.000Z | #
# Author: Pearu Peterson, March 2002
#
# w/ additions by Travis Oliphant, March 2002
__all__ = ['solve', 'solve_triangular', 'solveh_banded', 'solve_banded',
'inv', 'det', 'lstsq', 'pinv', 'pinv2']
from numpy import asarray, zeros, sum, conjugate, dot, transpose, \
asarray_chkfinite, single
import numpy
from flinalg import get_flinalg_funcs
from lapack import get_lapack_funcs
from misc import LinAlgError, _datacopied
from scipy.linalg import calc_lwork
from funcinfo import get_func_info
import decomp_svd
# Linear equations
def solve(a, b, sym_pos=False, lower=False, overwrite_a=False, overwrite_b=False,
debug=False):
"""Solve the equation a x = b for x
Parameters
----------
a : array, shape (M, M)
b : array, shape (M,) or (M, N)
sym_pos : boolean
Assume a is symmetric and positive definite
lower : boolean
Use only data contained in the lower triangle of a, if sym_pos is true.
Default is to use upper triangle.
overwrite_a : boolean
Allow overwriting data in a (may enhance performance)
overwrite_b : boolean
Allow overwriting data in b (may enhance performance)
Returns
-------
x : array, shape (M,) or (M, N) depending on b
Solution to the system a x = b
Raises LinAlgError if a is singular
"""
a1, b1 = map(asarray_chkfinite,(a,b))
if len(a1.shape) != 2 or a1.shape[0] != a1.shape[1]:
raise ValueError('expected square matrix')
if a1.shape[0] != b1.shape[0]:
raise ValueError('incompatible dimensions')
overwrite_a = overwrite_a or _datacopied(a1, a)
overwrite_b = overwrite_b or _datacopied(b1, b)
if debug:
print 'solve:overwrite_a=',overwrite_a
print 'solve:overwrite_b=',overwrite_b
if sym_pos:
posv, = get_lapack_funcs(('posv',), (a1,b1))
c, x, info = posv(a1, b1, lower=lower,
overwrite_a=overwrite_a,
overwrite_b=overwrite_b)
else:
gesv, = get_lapack_funcs(('gesv',), (a1,b1))
lu, piv, x, info = gesv(a1, b1, overwrite_a=overwrite_a,
overwrite_b=overwrite_b)
if info == 0:
return x
if info > 0:
raise LinAlgError("singular matrix")
raise ValueError('illegal value in %d-th argument of internal gesv|posv'
% -info)
def solve_triangular(a, b, trans=0, lower=False, unit_diagonal=False,
overwrite_b=False, debug=False):
"""Solve the equation `a x = b` for `x`, assuming a is a triangular matrix.
Parameters
----------
a : array, shape (M, M)
b : array, shape (M,) or (M, N)
lower : boolean
Use only data contained in the lower triangle of a.
Default is to use upper triangle.
trans : {0, 1, 2, 'N', 'T', 'C'}
Type of system to solve:
======== =========
trans system
======== =========
0 or 'N' a x = b
1 or 'T' a^T x = b
2 or 'C' a^H x = b
======== =========
unit_diagonal : boolean
If True, diagonal elements of A are assumed to be 1 and
will not be referenced.
overwrite_b : boolean
Allow overwriting data in b (may enhance performance)
Returns
-------
x : array, shape (M,) or (M, N) depending on b
Solution to the system a x = b
Raises
------
LinAlgError
If a is singular
"""
a1, b1 = map(asarray_chkfinite,(a,b))
if len(a1.shape) != 2 or a1.shape[0] != a1.shape[1]:
raise ValueError('expected square matrix')
if a1.shape[0] != b1.shape[0]:
raise ValueError('incompatible dimensions')
overwrite_b = overwrite_b or _datacopied(b1, b)
if debug:
print 'solve:overwrite_b=',overwrite_b
trans = {'N': 0, 'T': 1, 'C': 2}.get(trans, trans)
trtrs, = get_lapack_funcs(('trtrs',), (a1,b1))
x, info = trtrs(a1, b1, overwrite_b=overwrite_b, lower=lower,
trans=trans, unitdiag=unit_diagonal)
if info == 0:
return x
if info > 0:
raise LinAlgError("singular matrix: resolution failed at diagonal %s" % (info-1))
raise ValueError('illegal value in %d-th argument of internal trtrs')
def solve_banded((l, u), ab, b, overwrite_ab=False, overwrite_b=False,
debug=False):
"""Solve the equation a x = b for x, assuming a is banded matrix.
The matrix a is stored in ab using the matrix diagonal orded form::
ab[u + i - j, j] == a[i,j]
Example of ab (shape of a is (6,6), u=1, l=2)::
* a01 a12 a23 a34 a45
a00 a11 a22 a33 a44 a55
a10 a21 a32 a43 a54 *
a20 a31 a42 a53 * *
Parameters
----------
(l, u) : (integer, integer)
Number of non-zero lower and upper diagonals
ab : array, shape (l+u+1, M)
Banded matrix
b : array, shape (M,) or (M, K)
Right-hand side
overwrite_ab : boolean
Discard data in ab (may enhance performance)
overwrite_b : boolean
Discard data in b (may enhance performance)
Returns
-------
x : array, shape (M,) or (M, K)
The solution to the system a x = b
"""
a1, b1 = map(asarray_chkfinite, (ab, b))
# Validate shapes.
if a1.shape[-1] != b1.shape[0]:
raise ValueError("shapes of ab and b are not compatible.")
if l + u + 1 != a1.shape[0]:
raise ValueError("invalid values for the number of lower and upper diagonals:"
" l+u+1 (%d) does not equal ab.shape[0] (%d)" % (l+u+1, ab.shape[0]))
overwrite_b = overwrite_b or _datacopied(b1, b)
gbsv, = get_lapack_funcs(('gbsv',), (a1, b1))
a2 = zeros((2*l+u+1, a1.shape[1]), dtype=get_func_info(gbsv).dtype)
a2[l:,:] = a1
lu, piv, x, info = gbsv(l, u, a2, b1, overwrite_ab=True,
overwrite_b=overwrite_b)
if info == 0:
return x
if info > 0:
raise LinAlgError("singular matrix")
raise ValueError('illegal value in %d-th argument of internal gbsv' % -info)
def solveh_banded(ab, b, overwrite_ab=False, overwrite_b=False, lower=False):
"""Solve equation a x = b. a is Hermitian positive-definite banded matrix.
The matrix a is stored in ab either in lower diagonal or upper
diagonal ordered form:
ab[u + i - j, j] == a[i,j] (if upper form; i <= j)
ab[ i - j, j] == a[i,j] (if lower form; i >= j)
Example of ab (shape of a is (6,6), u=2)::
upper form:
* * a02 a13 a24 a35
* a01 a12 a23 a34 a45
a00 a11 a22 a33 a44 a55
lower form:
a00 a11 a22 a33 a44 a55
a10 a21 a32 a43 a54 *
a20 a31 a42 a53 * *
Cells marked with * are not used.
Parameters
----------
ab : array, shape (u + 1, M)
Banded matrix
b : array, shape (M,) or (M, K)
Right-hand side
overwrite_ab : boolean
Discard data in ab (may enhance performance)
overwrite_b : boolean
Discard data in b (may enhance performance)
lower : boolean
Is the matrix in the lower form. (Default is upper form)
Returns
-------
x : array, shape (M,) or (M, K)
The solution to the system a x = b
"""
ab, b = map(asarray_chkfinite, (ab, b))
# Validate shapes.
if ab.shape[-1] != b.shape[0]:
raise ValueError("shapes of ab and b are not compatible.")
pbsv, = get_lapack_funcs(('pbsv',), (ab, b))
c, x, info = pbsv(ab, b, lower=lower, overwrite_ab=overwrite_ab,
overwrite_b=overwrite_b)
if info > 0:
raise LinAlgError("%d-th leading minor not positive definite" % info)
if info < 0:
raise ValueError('illegal value in %d-th argument of internal pbsv'
% -info)
return x
# matrix inversion
def inv(a, overwrite_a=False):
"""
Compute the inverse of a matrix.
Parameters
----------
a : array_like
Square matrix to be inverted.
overwrite_a : bool, optional
Discard data in `a` (may improve performance). Default is False.
Returns
-------
ainv : ndarray
Inverse of the matrix `a`.
Raises
------
LinAlgError :
If `a` is singular.
ValueError :
If `a` is not square, or not 2-dimensional.
Examples
--------
>>> a = np.array([[1., 2.], [3., 4.]])
>>> sp.linalg.inv(a)
array([[-2. , 1. ],
[ 1.5, -0.5]])
>>> np.dot(a, sp.linalg.inv(a))
array([[ 1., 0.],
[ 0., 1.]])
"""
a1 = asarray_chkfinite(a)
if len(a1.shape) != 2 or a1.shape[0] != a1.shape[1]:
raise ValueError('expected square matrix')
overwrite_a = overwrite_a or _datacopied(a1, a)
#XXX: I found no advantage or disadvantage of using finv.
## finv, = get_flinalg_funcs(('inv',),(a1,))
## if finv is not None:
## a_inv,info = finv(a1,overwrite_a=overwrite_a)
## if info==0:
## return a_inv
## if info>0: raise LinAlgError, "singular matrix"
## if info<0: raise ValueError,\
## 'illegal value in %d-th argument of internal inv.getrf|getri'%(-info)
getrf, getri = get_lapack_funcs(('getrf','getri'), (a1,))
getrf_info = get_func_info(getrf)
getri_info = get_func_info(getri)
#XXX: C ATLAS versions of getrf/i have rowmajor=1, this could be
# exploited for further optimization. But it will be probably
# a mess. So, a good testing site is required before trying
# to do that.
if (getrf_info.module_name[:7] == 'clapack' !=
getri_info.module_name[:7]):
# ATLAS 3.2.1 has getrf but not getri.
lu, piv, info = getrf(transpose(a1), rowmajor=0,
overwrite_a=overwrite_a)
lu = transpose(lu)
else:
lu, piv, info = getrf(a1, overwrite_a=overwrite_a)
if info == 0:
if getri_info.module_name[:7] == 'flapack':
lwork = calc_lwork.getri(getri_info.prefix, a1.shape[0])
lwork = lwork[1]
# XXX: the following line fixes curious SEGFAULT when
# benchmarking 500x500 matrix inverse. This seems to
# be a bug in LAPACK ?getri routine because if lwork is
# minimal (when using lwork[0] instead of lwork[1]) then
# all tests pass. Further investigation is required if
# more such SEGFAULTs occur.
lwork = int(1.01 * lwork)
inv_a, info = getri(lu, piv, lwork=lwork, overwrite_lu=1)
else: # clapack
inv_a, info = getri(lu, piv, overwrite_lu=1)
if info > 0:
raise LinAlgError("singular matrix")
if info < 0:
raise ValueError('illegal value in %d-th argument of internal '
'getrf|getri' % -info)
return inv_a
### Determinant
def det(a, overwrite_a=False):
"""Compute the determinant of a matrix
Parameters
----------
a : array, shape (M, M)
Returns
-------
det : float or complex
Determinant of a
Notes
-----
The determinant is computed via LU factorization, LAPACK routine z/dgetrf.
"""
a1 = asarray_chkfinite(a)
if len(a1.shape) != 2 or a1.shape[0] != a1.shape[1]:
raise ValueError('expected square matrix')
overwrite_a = overwrite_a or _datacopied(a1, a)
fdet, = get_flinalg_funcs(('det',), (a1,))
a_det, info = fdet(a1, overwrite_a=overwrite_a)
if info < 0:
raise ValueError('illegal value in %d-th argument of internal '
'det.getrf' % -info)
return a_det
### Linear Least Squares
def lstsq(a, b, cond=None, overwrite_a=False, overwrite_b=False):
"""
Compute least-squares solution to equation Ax = b.
Compute a vector x such that the 2-norm ``|b - A x|`` is minimized.
Parameters
----------
a : array, shape (M, N)
Left hand side matrix (2-D array).
b : array, shape (M,) or (M, K)
Right hand side matrix or vector (1-D or 2-D array).
cond : float, optional
Cutoff for 'small' singular values; used to determine effective
rank of a. Singular values smaller than
``rcond * largest_singular_value`` are considered zero.
overwrite_a : bool, optional
Discard data in `a` (may enhance performance). Default is False.
overwrite_b : bool, optional
Discard data in `b` (may enhance performance). Default is False.
Returns
-------
x : array, shape (N,) or (N, K) depending on shape of b
Least-squares solution.
residues : ndarray, shape () or (1,) or (K,)
Sums of residues, squared 2-norm for each column in ``b - a x``.
If rank of matrix a is < N or > M this is an empty array.
If b was 1-D, this is an (1,) shape array, otherwise the shape is (K,).
rank : int
Effective rank of matrix `a`.
s : array, shape (min(M,N),)
Singular values of `a`. The condition number of a is
``abs(s[0]/s[-1])``.
Raises
------
LinAlgError :
If computation does not converge.
See Also
--------
optimize.nnls : linear least squares with non-negativity constraint
"""
a1, b1 = map(asarray_chkfinite, (a, b))
if len(a1.shape) != 2:
raise ValueError('expected matrix')
m, n = a1.shape
if len(b1.shape) == 2:
nrhs = b1.shape[1]
else:
nrhs = 1
if m != b1.shape[0]:
raise ValueError('incompatible dimensions')
gelss, = get_lapack_funcs(('gelss',), (a1, b1))
gelss_info = get_func_info(gelss)
if n > m:
# need to extend b matrix as it will be filled with
# a larger solution matrix
b2 = zeros((n, nrhs), dtype=gelss_info.dtype)
if len(b1.shape) == 2:
b2[:m,:] = b1
else:
b2[:m,0] = b1
b1 = b2
overwrite_a = overwrite_a or _datacopied(a1, a)
overwrite_b = overwrite_b or _datacopied(b1, b)
if gelss_info.module_name[:7] == 'flapack':
lwork = calc_lwork.gelss(gelss_info.prefix, m, n, nrhs)[1]
v, x, s, rank, info = gelss(a1, b1, cond=cond, lwork=lwork,
overwrite_a=overwrite_a,
overwrite_b=overwrite_b)
else:
raise NotImplementedError('calling gelss from %s' % get_func_info(gelss).module_name)
if info > 0:
raise LinAlgError("SVD did not converge in Linear Least Squares")
if info < 0:
raise ValueError('illegal value in %d-th argument of internal gelss'
% -info)
resids = asarray([], dtype=x.dtype)
if n < m:
x1 = x[:n]
if rank == n:
resids = sum(abs(x[n:])**2, axis=0)
x = x1
return x, resids, rank, s
def pinv(a, cond=None, rcond=None):
"""Compute the (Moore-Penrose) pseudo-inverse of a matrix.
Calculate a generalized inverse of a matrix using a least-squares
solver.
Parameters
----------
a : array, shape (M, N)
Matrix to be pseudo-inverted
cond, rcond : float
Cutoff for 'small' singular values in the least-squares solver.
Singular values smaller than rcond*largest_singular_value are
considered zero.
Returns
-------
B : array, shape (N, M)
Raises LinAlgError if computation does not converge
Examples
--------
>>> from numpy import *
>>> a = random.randn(9, 6)
>>> B = linalg.pinv(a)
>>> allclose(a, dot(a, dot(B, a)))
True
>>> allclose(B, dot(B, dot(a, B)))
True
"""
a = asarray_chkfinite(a)
b = numpy.identity(a.shape[0], dtype=a.dtype)
if rcond is not None:
cond = rcond
return lstsq(a, b, cond=cond)[0]
def pinv2(a, cond=None, rcond=None):
"""Compute the (Moore-Penrose) pseudo-inverse of a matrix.
Calculate a generalized inverse of a matrix using its
singular-value decomposition and including all 'large' singular
values.
Parameters
----------
a : array, shape (M, N)
Matrix to be pseudo-inverted
cond, rcond : float or None
Cutoff for 'small' singular values.
Singular values smaller than rcond*largest_singular_value are
considered zero.
If None or -1, suitable machine precision is used.
Returns
-------
B : array, shape (N, M)
Raises LinAlgError if SVD computation does not converge
Examples
--------
>>> from numpy import *
>>> a = random.randn(9, 6)
>>> B = linalg.pinv2(a)
>>> allclose(a, dot(a, dot(B, a)))
True
>>> allclose(B, dot(B, dot(a, B)))
True
"""
a = asarray_chkfinite(a)
u, s, vh = decomp_svd.svd(a)
t = u.dtype.char
if rcond is not None:
cond = rcond
if cond in [None,-1]:
eps = numpy.finfo(float).eps
feps = numpy.finfo(single).eps
_array_precision = {'f': 0, 'd': 1, 'F': 0, 'D': 1}
cond = {0: feps*1e3, 1: eps*1e6}[_array_precision[t]]
m, n = a.shape
cutoff = cond*numpy.maximum.reduce(s)
psigma = zeros((m, n), t)
for i in range(len(s)):
if s[i] > cutoff:
psigma[i,i] = 1.0/conjugate(s[i])
#XXX: use lapack/blas routines for dot
return transpose(conjugate(dot(dot(u,psigma),vh)))
| 32.224044 | 93 | 0.567916 |
08f48f78e32c8607808e34b785c090af34ff0e63 | 5,172 | py | Python | flexget/plugins/sites/cpasbien.py | davidcollom/Flexget | cd763e04afdf6da8f1673dd567a42d55d4cb3b6c | [
"MIT"
] | 1 | 2021-03-24T11:54:01.000Z | 2021-03-24T11:54:01.000Z | flexget/plugins/sites/cpasbien.py | davidcollom/Flexget | cd763e04afdf6da8f1673dd567a42d55d4cb3b6c | [
"MIT"
] | null | null | null | flexget/plugins/sites/cpasbien.py | davidcollom/Flexget | cd763e04afdf6da8f1673dd567a42d55d4cb3b6c | [
"MIT"
] | null | null | null | from __future__ import unicode_literals, division, absolute_import
from builtins import * # noqa pylint: disable=unused-import, redefined-builtin
from future.moves.urllib.parse import quote_plus
import logging
import re
from flexget import plugin
from flexget.entry import Entry
from flexget.event import event
from flexget.utils import requests
from flexget.utils.soup import get_soup
from flexget.utils.search import normalize_unicode
from flexget.utils.tools import parse_filesize
log = logging.getLogger('search_cpasbien')
session = requests.Session()
class SearchCPASBIEN(object):
schema = {
'type': 'object',
'properties':
{
'category': {
'type': 'string',
'enum': ['films', 'series', 'musique', 'films-french',
'720p', 'series-francaise', 'films-dvdrip', 'all',
'films-vostfr', '1080p', 'series-vostfr', 'ebook']
},
},
'required': ['category'],
'additionalProperties': False
}
@plugin.internet(log)
def search(self, task, entry, config):
"""CPASBIEN search plugin
Config example:
tv_search_cpasbien:
discover:
what:
- trakt_list:
username: xxxxxxx
api_key: xxxxxxx
series: watchlist
from:
- cpasbien:
category: "series-vostfr"
interval: 1 day
ignore_estimations: yes
Category is ONE of:
all
films
series
musique
films-french
1080p
720p
series-francaise
films-dvdrip
films-vostfr
series-vostfr
ebook
"""
base_url = 'http://www.cpasbien.io'
entries = set()
for search_string in entry.get('search_strings', [entry['title']]):
search_string = search_string.replace(' ', '-').lower()
search_string = search_string.replace('(', '')
search_string = search_string.replace(')', '')
query = normalize_unicode(search_string)
query_url_fragment = quote_plus(query.encode('utf-8'))
# http://www.cpasbien.pe/recherche/ncis.html
if config['category'] == 'all':
str_url = (base_url, 'recherche', query_url_fragment)
url = '/'.join(str_url)
else:
category_url_fragment = '%s' % config['category']
str_url = (base_url, 'recherche', category_url_fragment, query_url_fragment)
url = '/'.join(str_url)
log.debug('search url: %s' % url + '.html')
# GET URL
f = task.requests.get(url + '.html').content
soup = get_soup(f)
if soup.findAll(text=re.compile(' 0 torrents')):
log.debug('search returned no results')
else:
nextpage = 0
while (nextpage >= 0):
if (nextpage > 0):
newurl = url + '/page-' + str(nextpage)
log.debug('-----> NEXT PAGE : %s' % newurl)
f1 = task.requests.get(newurl).content
soup = get_soup(f1)
for result in soup.findAll('div', attrs={'class': re.compile('ligne')}):
entry = Entry()
link = result.find('a', attrs={'href': re.compile('dl-torrent')})
entry['title'] = link.contents[0]
# REWRITE URL
page_link = link.get('href')
link_rewrite = page_link.split('/')
# get last value in array remove .html and replace by .torrent
endlink = link_rewrite[-1]
str_url = (base_url, '/telechargement/', endlink[:-5], '.torrent')
entry['url'] = ''.join(str_url)
log.debug('Title: %s | DL LINK: %s' % (entry['title'], entry['url']))
entry['torrent_seeds'] = (int(result.find('span', attrs={'class': re.compile('seed')}).text))
entry['torrent_leeches'] = (int(result.find('div', attrs={'class': re.compile('down')}).text))
size = result.find('div', attrs={'class': re.compile('poid')}).text
entry['content_size'] = parse_filesize(size, si=False)
if (entry['torrent_seeds'] > 0):
entries.add(entry)
else:
log.debug('0 SEED, not adding entry')
if soup.find(text=re.compile('Suiv')):
nextpage += 1
else:
nextpage = -1
return entries
@event('plugin.register')
def register_plugin():
plugin.register(SearchCPASBIEN, 'cpasbien', groups=['search'], api_ver=2)
| 38.311111 | 118 | 0.49478 |
a7332523db26dfe9c695ddb1723177bb76c57101 | 111 | py | Python | Bases/Practice/Solution/TicTacToe/Player.py | PierreAnken/TrainingPython | a788090d335d8d940838d17e68f263ba4aa013d4 | [
"MIT"
] | null | null | null | Bases/Practice/Solution/TicTacToe/Player.py | PierreAnken/TrainingPython | a788090d335d8d940838d17e68f263ba4aa013d4 | [
"MIT"
] | null | null | null | Bases/Practice/Solution/TicTacToe/Player.py | PierreAnken/TrainingPython | a788090d335d8d940838d17e68f263ba4aa013d4 | [
"MIT"
] | 1 | 2021-12-07T10:53:43.000Z | 2021-12-07T10:53:43.000Z | class Player:
def __init__(self, name: str, sign: str):
self.name = name
self.sign = sign
| 18.5 | 45 | 0.576577 |
2e184de571210a4e4dcfab2bd59b86a9f19df7b3 | 167 | py | Python | reformat_gherkin/ast_node/doc_string.py | rayjolt/reformat-gherkin | 4869bd5b3a904283171f8a49849d53e8e9e81c18 | [
"MIT"
] | null | null | null | reformat_gherkin/ast_node/doc_string.py | rayjolt/reformat-gherkin | 4869bd5b3a904283171f8a49849d53e8e9e81c18 | [
"MIT"
] | null | null | null | reformat_gherkin/ast_node/doc_string.py | rayjolt/reformat-gherkin | 4869bd5b3a904283171f8a49849d53e8e9e81c18 | [
"MIT"
] | null | null | null | from ._base import prepare
from .location import LocationMixin
@prepare
class DocString(LocationMixin):
content: str
def __iter__(self):
yield self
| 15.181818 | 35 | 0.724551 |
e89cafdde490cb1a0cb94bd31e995a45ddf87570 | 174 | py | Python | 104-maximum-depth-of-binary-tree/104-maximum-depth-of-binary-tree.py | Atri10/Leet-code---Atri_Patel | 49fc59b9147a44ab04a66128fbb2ef259b5f7b7c | [
"MIT"
] | 1 | 2021-10-10T20:21:18.000Z | 2021-10-10T20:21:18.000Z | 104-maximum-depth-of-binary-tree/104-maximum-depth-of-binary-tree.py | Atri10/Leet-code---Atri_Patel | 49fc59b9147a44ab04a66128fbb2ef259b5f7b7c | [
"MIT"
] | null | null | null | 104-maximum-depth-of-binary-tree/104-maximum-depth-of-binary-tree.py | Atri10/Leet-code---Atri_Patel | 49fc59b9147a44ab04a66128fbb2ef259b5f7b7c | [
"MIT"
] | null | null | null | class Solution:
def maxDepth(self, root: Optional[TreeNode]) -> int:
if not root:return 0
return max(self.maxDepth(root.left),self.maxDepth(root.right))+1 | 43.5 | 72 | 0.678161 |
29c541cfb13bfb1add79b7909c4b1aab18641aab | 12,721 | py | Python | python/paddle/distributed/fleet/utils/recompute.py | ucsk/Paddle | 1d4566592287d84b39f7f3cab2f00e9d3f993d92 | [
"Apache-2.0"
] | 2 | 2022-01-04T10:51:58.000Z | 2022-01-10T12:29:08.000Z | python/paddle/distributed/fleet/utils/recompute.py | ucsk/Paddle | 1d4566592287d84b39f7f3cab2f00e9d3f993d92 | [
"Apache-2.0"
] | 1 | 2020-09-08T01:45:28.000Z | 2020-09-08T01:45:28.000Z | python/paddle/distributed/fleet/utils/recompute.py | ucsk/Paddle | 1d4566592287d84b39f7f3cab2f00e9d3f993d92 | [
"Apache-2.0"
] | 5 | 2021-12-10T11:20:06.000Z | 2022-02-18T05:18:12.000Z | # Copyright (c) 2021 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.
import paddle
from paddle.fluid import core
from paddle.autograd import PyLayer
from paddle.fluid import framework
import contextlib
import logging
logger = logging.getLogger(__name__)
formatter = logging.Formatter(
fmt='%(asctime)s %(levelname)-8s %(message)s', datefmt='%Y-%m-%d %H:%M:%S')
ch = logging.StreamHandler()
ch.setFormatter(formatter)
logger.addHandler(ch)
__all__ = []
def detach_variable(inputs):
out = []
for inp in inputs:
if not isinstance(inp, core.VarBase):
out.append(inp)
continue
x = inp.detach()
x.stop_gradient = inp.stop_gradient
out.append(x)
return tuple(out)
def check_recompute_necessary(inputs):
if not any(input_.stop_gradient == False for input_ in inputs
if isinstance(input_, paddle.Tensor)):
logger.warn(
"[Recompute]: None of the inputs to current recompute block need grad, "
"therefore there is NO need to recompute this block in backward !")
@contextlib.contextmanager
def swith_rng_state(rng_state):
orig_cuda_rng_state = paddle.get_cuda_rng_state()
paddle.set_cuda_rng_state(rng_state)
try:
yield
finally:
paddle.set_cuda_rng_state(orig_cuda_rng_state)
class RecomputeFunction(PyLayer):
@staticmethod
def forward(ctx, run_function, preserve_rng_state, *args):
check_recompute_necessary(args)
# store for recomputing
ctx.run_function = run_function
ctx.preserve_rng_state = preserve_rng_state
# NOTE the number of outputs of backward() should be equal to the number of tensors in forward()'s input
# the order of tensors in backward()'s output should be the same as tensors in forward()'s input
# None tensor inputs will be filtered in backward inputs.
# save input for backward
ctx.inputs = []
ctx.tensor_indices = []
tensor_inputs = []
for i, arg in enumerate(args):
if paddle.is_tensor(arg):
tensor_inputs.append(arg)
ctx.tensor_indices.append(i)
ctx.inputs.append(None)
else:
ctx.inputs.append(arg)
ctx.save_for_backward(*tensor_inputs)
# NOTE recompute with restore RNG only support one senario where one process for one cuda gpu.
# one process with multiple gpu and mix-gpu-cpu senarios are not support
if ctx.preserve_rng_state:
cur_device = paddle.get_device()
if 'gpu:' not in cur_device:
raise RuntimeError(
"Recompute with RNG perserve is not support current device: {}.".
format(cur_device))
ctx.fw_cuda_rng_state = paddle.get_cuda_rng_state()
# TODO support AMP
tracer = framework._dygraph_tracer()
ctx.is_fw_autocast = False if tracer._amp_level == core.AmpLevel.O0 else True
if tracer._amp_level == core.AmpLevel.O2:
ctx.amp_level = 'O2'
elif tracer._amp_level in (core.AmpLevel.O1, core.AmpLevel.O0):
ctx.amp_level = 'O1'
else:
raise ValueError("unsupported amp level: {}".format(
tracer._amp_level))
ctx.amp_white_list, ctx.amp_black_list = tracer._get_amp_op_list()
with paddle.no_grad():
outputs = run_function(*args)
return outputs
@staticmethod
def backward(ctx, *args):
with paddle.fluid.dygraph.guard():
# TODO need to check the recompute calling is vaild or not
# Restore inputs
inputs = list(ctx.inputs)
tensor_indices = ctx.tensor_indices
tensors = ctx.saved_tensor()
for i, idx in enumerate(tensor_indices):
inputs[idx] = tensors[i]
# paddle.enable_grad()
tracer = framework._dygraph_tracer()
tracer._has_grad = True
# NOTE support AMP
# need restore auto_cast state as well as w/b list
if ctx.preserve_rng_state:
with swith_rng_state(ctx.fw_cuda_rng_state):
with paddle.amp.auto_cast(
enable=ctx.is_fw_autocast,
custom_white_list=ctx.amp_white_list,
custom_black_list=ctx.amp_black_list,
level=ctx.amp_level):
detached_inputs = detach_variable(tuple(inputs))
outputs = ctx.run_function(*detached_inputs)
else:
with paddle.amp.auto_cast(
enable=ctx.is_fw_autocast,
custom_white_list=ctx.amp_white_list,
custom_black_list=ctx.amp_black_list,
level=ctx.amp_level):
detached_inputs = detach_variable(tuple(inputs))
outputs = ctx.run_function(*detached_inputs)
if isinstance(outputs, core.VarBase):
outputs = (outputs, )
assert len(outputs) == len(args)
# run backward() with only tensor that requires grad
forward_outputs_with_grad = []
# NOTE In Transformer-like network, if user put the attention mask into the recompute segment output,
# pylayer will force the stop_gradient of attention mask to be False, which will make the number of
# tensor that need grad does not match.
# the following backward_inputs_with_grad is used to avoid this case.
backward_inputs_with_grad = []
for i in range(len(outputs)):
if isinstance(outputs[i],
core.VarBase) and not outputs[i].stop_gradient:
forward_outputs_with_grad.append(outputs[i])
backward_inputs_with_grad.append(args[i])
if len(forward_outputs_with_grad) == 0:
raise RuntimeError(
"none of output has requires_grad=True, this recompute() is not necessary"
)
# actually backward
paddle.autograd.backward(forward_outputs_with_grad,
backward_inputs_with_grad)
grads = list(inp._grad_ivar() for inp in detached_inputs
if isinstance(inp, core.VarBase))
return grads
def recompute(function, *args, **kwargs):
"""
recompute intermediate activations to save then memory.
Parameters:
function(paddle.nn.Sequential): layer of sequence of layers that describes part of forward pass of the model
whose intermediate activations will be released to save memory in forward stage and will be recomputed
in backward stage for gradient calculation.
*args(Tensor): inputs to the function.
**kwargs(Dict): Kwargs should only contain the key-value pair of preserve_rng_state, which is used to
indicate whether to save the forward rng. If it is True, then the last forward rng value will be
restored when the forward recalculation of backpropagation is performed. The default
preserve_rng_state is True.
Returns:
Output of function on args.
Examples:
.. code-block:: python
import numpy as np
import paddle
from paddle.distributed.fleet.utils import recompute
import random
# required: gpu
def get_fc_block(block_idx, input_size, is_last=False):
block_name = "block_" + str(block_idx)
block = paddle.nn.Sequential(
(block_name + "_fc_0", paddle.nn.Linear(input_size, input_size, bias_attr=False)),
(block_name + "_dropout", paddle.nn.Dropout(p=0.5)),
(block_name + "_relu_1", paddle.nn.ReLU()),
(block_name + "_fc_1", paddle.nn.Linear(input_size, input_size, bias_attr=False)),
(block_name + "_relu_2", paddle.nn.ReLU()),
)
if is_last:
block.add_sublayer(
block_name + "_fc_2",
paddle.nn.Linear(
input_size, 1, bias_attr=False
)
)
else:
block.add_sublayer(
block_name + "_fc_2",
paddle.nn.Linear(input_size, input_size, bias_attr=False)
)
return block
class Naive_fc_net(paddle.nn.Layer):
def __init__(self, input_size=10,
recompute_blocks=[1, 3],
recompute_kwargs={}):
super(Naive_fc_net, self).__init__()
self.recompute_blocks = recompute_blocks
self.recompute_kwargs = recompute_kwargs
self.runfunc0 = get_fc_block(0, input_size, is_last=False)
self.runfunc1 = get_fc_block(1, input_size, is_last=False)
self.runfunc2 = get_fc_block(2, input_size, is_last=False)
self.runfunc3 = get_fc_block(3, input_size, is_last=False)
self.runfunc4 = get_fc_block(4, input_size, is_last=True)
self.total_func = [self.runfunc0, self.runfunc1, self.runfunc2, self.runfunc3, self.runfunc4]
def forward(self, inputs):
nums = len(self.total_func)
for i in range(nums):
if i in self.recompute_blocks:
inputs = recompute(self.total_func[i], inputs, **{"preserve_rng_state": True})
else:
inputs = self.total_func[i](inputs)
return inputs
def run_model(cuda_state, recompute_block=[], recompute_kwargs={}):
gen = paddle.seed(10)
gen.manual_seed(10)
np.random.seed(10)
random.seed(10)
if cuda_state:
paddle.set_cuda_rng_state(cuda_state)
batch_size, input_size = 1, 10
model = Naive_fc_net(
input_size,
recompute_blocks=recompute_block,
recompute_kwargs=recompute_kwargs)
optimizer = paddle.optimizer.SGD(learning_rate=0.01, parameters=model.parameters())
loss_ = []
param_ = []
grad_ = []
for _ in range(5):
x_data = np.random.randn(batch_size, input_size).astype(np.float32)
x = paddle.to_tensor(x_data)
y_pred = model(x)
loss = y_pred.mean()
loss_.append(np.asarray(loss).tolist())
loss.backward()
optimizer.step()
param_.append(np.asarray(model.parameters()[9]).tolist())
grad_.append(np.asarray(model.parameters()[3]._grad_ivar()).tolist())
optimizer.clear_grad()
return loss_, param_, grad_
cuda_state = paddle.get_cuda_rng_state()
# without recompute
loss_ref, param_ref, grad_ref = run_model(
cuda_state, recompute_block=[]
)
loss, param, grad = run_model(cuda_state, recompute_block=[1, 2])
print("normal_loss: {}, recompute_loss: {}".format(loss_ref, loss))
# The result of the recompute_loss should be the same as the normal_loss.
"""
# Hack to mix *args with **kwargs in a python 2.7-compliant way
preserve = kwargs.pop('preserve_rng_state', True)
if kwargs:
raise ValueError("Unexpected keyword arguments: " + ",".join(
arg for arg in kwargs))
return RecomputeFunction.apply(function, preserve, *args)
| 41.571895 | 118 | 0.57975 |
ebb45d136800e7f29e236c0c0336318158b9c6f1 | 327 | py | Python | lagom/agents/__init__.py | lkylych/lagom | 64777be7f09136072a671c444b5b3fbbcb1b2f18 | [
"MIT"
] | null | null | null | lagom/agents/__init__.py | lkylych/lagom | 64777be7f09136072a671c444b5b3fbbcb1b2f18 | [
"MIT"
] | null | null | null | lagom/agents/__init__.py | lkylych/lagom | 64777be7f09136072a671c444b5b3fbbcb1b2f18 | [
"MIT"
] | null | null | null | from .base_agent import BaseAgent
from .random_agent import RandomAgent
from .reinforce_agent import REINFORCEAgent
from .actor_critic_agent import ActorCriticAgent
#from lagom.agents.a2c_agent import A2CAgent
#from lagom.agents.reinforce_agent import REINFORCEAgent
#rom lagom.agents.actor_critic_agent import ActorCriticAgent | 46.714286 | 60 | 0.877676 |
11fa402140c4eca3a6b55eaf1ef14756db1a68de | 1,554 | py | Python | A_source_code/generalcode/trunk/hydraulic_load.py | vanHoek-dgnm/CARBON-DISC | 3ecd5f4efba5e032d43679ee977064d6b25154a9 | [
"Naumen",
"Condor-1.1",
"MS-PL"
] | null | null | null | A_source_code/generalcode/trunk/hydraulic_load.py | vanHoek-dgnm/CARBON-DISC | 3ecd5f4efba5e032d43679ee977064d6b25154a9 | [
"Naumen",
"Condor-1.1",
"MS-PL"
] | null | null | null | A_source_code/generalcode/trunk/hydraulic_load.py | vanHoek-dgnm/CARBON-DISC | 3ecd5f4efba5e032d43679ee977064d6b25154a9 | [
"Naumen",
"Condor-1.1",
"MS-PL"
] | null | null | null | # ******************************************************
## Revision "$LastChangedDate: 2018-06-01 15:05:44 +0200 (Fri, 01 Jun 2018) $"
## Date "$LastChangedRevision: 1 $"
## Author "$LastChangedBy: arthurbeusen $"
## URL "$HeadURL: https://pbl.sliksvn.com/generalcode/trunk/hydraulic_load.py $"
## Copyright 2017, PBL Netherlands Environmental Assessment Agency and Utrecht University.
## Reuse permitted under Gnu Public License, GPL v3.
# ******************************************************
import os
import ascraster
def calculate(params,mask,residence_time_grid,lake_icell_dict):
'''
This function calculates the hydraulic load in the water bodies.
'''
# Depth water of waterbody in metres (result of residence time function)
depth_grid = ascraster.Asciigrid(ascii_file=os.path.join(params.outputdir,"depth_waterbody_grid.asc"),\
mask=mask,numtype=float)
hydraulic_load_grid = ascraster.duplicategrid(residence_time_grid)
hydraulic_load_grid.add_values(hydraulic_load_grid.length *[0.0])
for icell in range(hydraulic_load_grid.length):
depth = depth_grid.get_data(icell,0.0)
resi_time = residence_time_grid.get_data(icell,0.0)
try:
Hl = depth/resi_time
except ZeroDivisionError:
Hl = 0.0
hydraulic_load_grid.set_data(icell,Hl)
# Write hydraulic load to output file:
hydraulic_load_grid.write_ascii_file(os.path.join(params.outputdir,"hydraulic_load.asc"))
return hydraulic_load_grid
| 42 | 107 | 0.657658 |
f3647a856685abe6be6d6c0d90eed286e115d19e | 610 | py | Python | pymatgen/phasediagram/__init__.py | ltalirz/pymatgen | 894cdb2ec7b9bd74f0ac3cdad40d144203ccdcf6 | [
"MIT"
] | null | null | null | pymatgen/phasediagram/__init__.py | ltalirz/pymatgen | 894cdb2ec7b9bd74f0ac3cdad40d144203ccdcf6 | [
"MIT"
] | null | null | null | pymatgen/phasediagram/__init__.py | ltalirz/pymatgen | 894cdb2ec7b9bd74f0ac3cdad40d144203ccdcf6 | [
"MIT"
] | null | null | null | # coding: utf-8
# Copyright (c) Pymatgen Development Team.
# Distributed under the terms of the MIT License.
"""
The phasediagram package implements the analysis tools to perform phase
stability analyses, including the constructing of phase diagrams, determination
of decomposition products, etc. The package is designed to be fairly modular
and standalone.
"""
__author__ = "Shyue"
__date__ = "Mar 28 2013"
import warnings
warnings.warn("pymatgen.phasediagram and submodules has been moved to "
"pymatgen.analysis.phase_diagram This stub will be "
"removed in pmg 2018.01.01.") | 32.105263 | 79 | 0.74918 |
657eb74a7a5970e9183a0dcc4462c6385ec32fb3 | 352 | py | Python | pysoup/display/__init__.py | illBeRoy/pysoup | 742fd6630e1be27c275cb8dc6ee94412472cb20b | [
"MIT"
] | 4 | 2016-02-21T12:40:44.000Z | 2019-06-13T13:23:19.000Z | pysoup/display/__init__.py | illBeRoy/pysoup | 742fd6630e1be27c275cb8dc6ee94412472cb20b | [
"MIT"
] | null | null | null | pysoup/display/__init__.py | illBeRoy/pysoup | 742fd6630e1be27c275cb8dc6ee94412472cb20b | [
"MIT"
] | 1 | 2020-07-16T12:22:12.000Z | 2020-07-16T12:22:12.000Z | import pysoup.display.interactive_display
import pysoup.display.silent_display
class DisplayAdapter(object):
@staticmethod
def create_interactive_display():
return pysoup.display.interactive_display.InteractiveDisplay()
@staticmethod
def create_silent_display():
return pysoup.display.silent_display.SilentDisplay()
| 25.142857 | 70 | 0.78125 |
bd7c783ddd41806d08f2eeeb5802c9822ec903b4 | 2,915 | py | Python | src/models/FeatExtractNet.py | sunshuofeng/Bi3D | aa4a4bf739017d0a9bf0149a6df891f3b97752cb | [
"BSD-Source-Code"
] | null | null | null | src/models/FeatExtractNet.py | sunshuofeng/Bi3D | aa4a4bf739017d0a9bf0149a6df891f3b97752cb | [
"BSD-Source-Code"
] | null | null | null | src/models/FeatExtractNet.py | sunshuofeng/Bi3D | aa4a4bf739017d0a9bf0149a6df891f3b97752cb | [
"BSD-Source-Code"
] | null | null | null | # Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
#
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and related documentation without an express
# license agreement from NVIDIA CORPORATION is strictly prohibited.
from __future__ import print_function
import torch
import torch.nn as nn
import math
from bi_models.PSMNet import conv2d
from bi_models.PSMNet import conv2d_relu
from bi_models.PSMNet import FeatExtractNetSPP
__all__ = ["featextractnetspp", "featextractnethr"]
"""
Feature extraction network.
Generates 16D features at the image resolution.
Used for final refinement.
"""
class FeatExtractNetHR(nn.Module):
def __init__(self, out_planes=16):
super(FeatExtractNetHR, self).__init__()
self.conv1 = nn.Sequential(
conv2d_relu(3, out_planes, kernel_size=3, stride=1, pad=1, dilation=1),
conv2d_relu(out_planes, out_planes, kernel_size=3, stride=1, pad=1, dilation=1),
nn.Conv2d(out_planes, out_planes, kernel_size=1, padding=0, stride=1, bias=False),
)
for m in self.modules():
if isinstance(m, nn.Conv2d):
n = m.kernel_size[0] * m.kernel_size[1] * m.out_channels
m.weight.data.normal_(0, math.sqrt(2.0 / n))
elif isinstance(m, nn.Conv3d):
n = m.kernel_size[0] * m.kernel_size[1] * m.kernel_size[2] * m.out_channels
m.weight.data.normal_(0, math.sqrt(2.0 / n))
elif isinstance(m, nn.BatchNorm2d):
m.weight.data.fill_(1)
m.bias.data.zero_()
elif isinstance(m, nn.BatchNorm3d):
m.weight.data.fill_(1)
m.bias.data.zero_()
elif isinstance(m, nn.Linear):
m.bias.data.zero_()
return
def forward(self, input):
output = self.conv1(input)
return output
def featextractnethr(options, data=None):
print("==> USING FeatExtractNetHR")
for key in options:
if "featextractnethr" in key:
print("{} : {}".format(key, options[key]))
model = FeatExtractNetHR(out_planes=options["featextractnethr_out_planes"])
if data is not None:
model.load_state_dict(data["state_dict"])
return model
"""
Feature extraction network.
Generates 32D features at 3x less resolution.
Uses Spatial Pyramid Pooling inspired by PSMNet.
"""
def featextractnetspp(options, data=None):
print("==> USING FeatExtractNetSPP")
for key in options:
if "feat" in key:
print("{} : {}".format(key, options[key]))
model = FeatExtractNetSPP()
if data is not None:
model.load_state_dict(data["state_dict"])
return model
| 29.744898 | 94 | 0.656604 |
7bb9a43b4a986f022cefd5da35c7deec19972bc8 | 1,017 | py | Python | 2021/day3/main.py | g-ford/advent-of-code | b706680df004cc1072551626816ce871300760f1 | [
"MIT"
] | null | null | null | 2021/day3/main.py | g-ford/advent-of-code | b706680df004cc1072551626816ce871300760f1 | [
"MIT"
] | null | null | null | 2021/day3/main.py | g-ford/advent-of-code | b706680df004cc1072551626816ce871300760f1 | [
"MIT"
] | null | null | null | from operator import ge, lt
from utils import log_time, to_dec, transpose
def parse_line(l):
return list(map(int, l.strip()))
@log_time
def part_a(input):
transposed = transpose(input)
mid = len(input) // 2
gamma = [int(sum(c) > mid) for c in transposed]
epsilon = [abs(x - 1) for x in gamma]
return to_dec(gamma) * to_dec(epsilon)
def filter_rating(ratings, op, index=0):
if len(ratings) == 1:
return ratings[0]
mid = len(ratings) / 2
transpose = list(zip(*ratings))[index]
bit = int(op(sum(transpose), mid))
filtered = [x for x in ratings if x[index] == bit]
return filter_rating(filtered, op, index + 1)
@log_time
def part_b(input):
o2_filtered = filter_rating(input, ge)
co2_filtered = filter_rating(input, lt)
return to_dec(o2_filtered) * to_dec(co2_filtered)
input = list(map(parse_line, open('day3/input.txt').readlines()))
result_a = part_a(input)
result_b = part_b(input)
print("Part A:", result_a)
print("Part B:", result_b)
| 23.113636 | 65 | 0.6647 |
7581139e3890799b2af7c684fd5c2e63c33f385f | 385,398 | py | Python | ns3/ns-3.26/src/visualizer/bindings/modulegen__gcc_LP64.py | Aedemon/clusim | 7f09cdb79b5f02cf0fed1bd44842981941f29f32 | [
"Apache-2.0"
] | 7 | 2017-08-11T06:06:47.000Z | 2022-02-27T07:34:33.000Z | ns3/ns-3.26/src/visualizer/bindings/modulegen__gcc_LP64.py | Aedemon/clusim | 7f09cdb79b5f02cf0fed1bd44842981941f29f32 | [
"Apache-2.0"
] | 3 | 2017-08-11T03:04:59.000Z | 2017-09-11T14:01:14.000Z | ns3/ns-3.26/src/visualizer/bindings/modulegen__gcc_LP64.py | Aedemon/clusim | 7f09cdb79b5f02cf0fed1bd44842981941f29f32 | [
"Apache-2.0"
] | 3 | 2017-08-08T13:36:30.000Z | 2018-07-04T09:49:41.000Z | from pybindgen import Module, FileCodeSink, param, retval, cppclass, typehandlers
import pybindgen.settings
import warnings
class ErrorHandler(pybindgen.settings.ErrorHandler):
def handle_error(self, wrapper, exception, traceback_):
warnings.warn("exception %r in wrapper %s" % (exception, wrapper))
return True
pybindgen.settings.error_handler = ErrorHandler()
import sys
def module_init():
root_module = Module('ns.visualizer', cpp_namespace='::ns3')
return root_module
def register_types(module):
root_module = module.get_root()
## address.h (module 'network'): ns3::Address [class]
module.add_class('Address', import_from_module='ns.network')
## address.h (module 'network'): ns3::Address::MaxSize_e [enumeration]
module.add_enum('MaxSize_e', ['MAX_SIZE'], outer_class=root_module['ns3::Address'], import_from_module='ns.network')
## attribute-construction-list.h (module 'core'): ns3::AttributeConstructionList [class]
module.add_class('AttributeConstructionList', import_from_module='ns.core')
## attribute-construction-list.h (module 'core'): ns3::AttributeConstructionList::Item [struct]
module.add_class('Item', import_from_module='ns.core', outer_class=root_module['ns3::AttributeConstructionList'])
## buffer.h (module 'network'): ns3::Buffer [class]
module.add_class('Buffer', import_from_module='ns.network')
## buffer.h (module 'network'): ns3::Buffer::Iterator [class]
module.add_class('Iterator', import_from_module='ns.network', outer_class=root_module['ns3::Buffer'])
## packet.h (module 'network'): ns3::ByteTagIterator [class]
module.add_class('ByteTagIterator', import_from_module='ns.network')
## packet.h (module 'network'): ns3::ByteTagIterator::Item [class]
module.add_class('Item', import_from_module='ns.network', outer_class=root_module['ns3::ByteTagIterator'])
## byte-tag-list.h (module 'network'): ns3::ByteTagList [class]
module.add_class('ByteTagList', import_from_module='ns.network')
## byte-tag-list.h (module 'network'): ns3::ByteTagList::Iterator [class]
module.add_class('Iterator', import_from_module='ns.network', outer_class=root_module['ns3::ByteTagList'])
## byte-tag-list.h (module 'network'): ns3::ByteTagList::Iterator::Item [struct]
module.add_class('Item', import_from_module='ns.network', outer_class=root_module['ns3::ByteTagList::Iterator'])
## callback.h (module 'core'): ns3::CallbackBase [class]
module.add_class('CallbackBase', import_from_module='ns.core')
## event-id.h (module 'core'): ns3::EventId [class]
module.add_class('EventId', import_from_module='ns.core')
## hash.h (module 'core'): ns3::Hasher [class]
module.add_class('Hasher', import_from_module='ns.core')
## inet6-socket-address.h (module 'network'): ns3::Inet6SocketAddress [class]
module.add_class('Inet6SocketAddress', import_from_module='ns.network')
## inet6-socket-address.h (module 'network'): ns3::Inet6SocketAddress [class]
root_module['ns3::Inet6SocketAddress'].implicitly_converts_to(root_module['ns3::Address'])
## inet-socket-address.h (module 'network'): ns3::InetSocketAddress [class]
module.add_class('InetSocketAddress', import_from_module='ns.network')
## inet-socket-address.h (module 'network'): ns3::InetSocketAddress [class]
root_module['ns3::InetSocketAddress'].implicitly_converts_to(root_module['ns3::Address'])
## ipv4-address.h (module 'network'): ns3::Ipv4Address [class]
module.add_class('Ipv4Address', import_from_module='ns.network')
## ipv4-address.h (module 'network'): ns3::Ipv4Address [class]
root_module['ns3::Ipv4Address'].implicitly_converts_to(root_module['ns3::Address'])
## ipv4-interface-address.h (module 'internet'): ns3::Ipv4InterfaceAddress [class]
module.add_class('Ipv4InterfaceAddress', import_from_module='ns.internet')
## ipv4-interface-address.h (module 'internet'): ns3::Ipv4InterfaceAddress::InterfaceAddressScope_e [enumeration]
module.add_enum('InterfaceAddressScope_e', ['HOST', 'LINK', 'GLOBAL'], outer_class=root_module['ns3::Ipv4InterfaceAddress'], import_from_module='ns.internet')
## ipv4-address.h (module 'network'): ns3::Ipv4Mask [class]
module.add_class('Ipv4Mask', import_from_module='ns.network')
## ipv6-address.h (module 'network'): ns3::Ipv6Address [class]
module.add_class('Ipv6Address', import_from_module='ns.network')
## ipv6-address.h (module 'network'): ns3::Ipv6Address [class]
root_module['ns3::Ipv6Address'].implicitly_converts_to(root_module['ns3::Address'])
## ipv6-address.h (module 'network'): ns3::Ipv6Prefix [class]
module.add_class('Ipv6Prefix', import_from_module='ns.network')
## mac48-address.h (module 'network'): ns3::Mac48Address [class]
module.add_class('Mac48Address', import_from_module='ns.network')
## mac48-address.h (module 'network'): ns3::Mac48Address [class]
root_module['ns3::Mac48Address'].implicitly_converts_to(root_module['ns3::Address'])
## object-base.h (module 'core'): ns3::ObjectBase [class]
module.add_class('ObjectBase', allow_subclassing=True, import_from_module='ns.core')
## object.h (module 'core'): ns3::ObjectDeleter [struct]
module.add_class('ObjectDeleter', import_from_module='ns.core')
## object-factory.h (module 'core'): ns3::ObjectFactory [class]
module.add_class('ObjectFactory', import_from_module='ns.core')
## packet-metadata.h (module 'network'): ns3::PacketMetadata [class]
module.add_class('PacketMetadata', import_from_module='ns.network')
## packet-metadata.h (module 'network'): ns3::PacketMetadata::Item [struct]
module.add_class('Item', import_from_module='ns.network', outer_class=root_module['ns3::PacketMetadata'])
## packet-metadata.h (module 'network'): ns3::PacketMetadata::Item [enumeration]
module.add_enum('', ['PAYLOAD', 'HEADER', 'TRAILER'], outer_class=root_module['ns3::PacketMetadata::Item'], import_from_module='ns.network')
## packet-metadata.h (module 'network'): ns3::PacketMetadata::ItemIterator [class]
module.add_class('ItemIterator', import_from_module='ns.network', outer_class=root_module['ns3::PacketMetadata'])
## packet.h (module 'network'): ns3::PacketTagIterator [class]
module.add_class('PacketTagIterator', import_from_module='ns.network')
## packet.h (module 'network'): ns3::PacketTagIterator::Item [class]
module.add_class('Item', import_from_module='ns.network', outer_class=root_module['ns3::PacketTagIterator'])
## packet-tag-list.h (module 'network'): ns3::PacketTagList [class]
module.add_class('PacketTagList', import_from_module='ns.network')
## packet-tag-list.h (module 'network'): ns3::PacketTagList::TagData [struct]
module.add_class('TagData', import_from_module='ns.network', outer_class=root_module['ns3::PacketTagList'])
## packet-tag-list.h (module 'network'): ns3::PacketTagList::TagData::TagData_e [enumeration]
module.add_enum('TagData_e', ['MAX_SIZE'], outer_class=root_module['ns3::PacketTagList::TagData'], import_from_module='ns.network')
## pyviz.h (module 'visualizer'): ns3::PyViz [class]
module.add_class('PyViz')
## pyviz.h (module 'visualizer'): ns3::PyViz::PacketCaptureMode [enumeration]
module.add_enum('PacketCaptureMode', ['PACKET_CAPTURE_DISABLED', 'PACKET_CAPTURE_FILTER_HEADERS_OR', 'PACKET_CAPTURE_FILTER_HEADERS_AND'], outer_class=root_module['ns3::PyViz'])
## pyviz.h (module 'visualizer'): ns3::PyViz::LastPacketsSample [struct]
module.add_class('LastPacketsSample', outer_class=root_module['ns3::PyViz'])
## pyviz.h (module 'visualizer'): ns3::PyViz::NetDeviceStatistics [struct]
module.add_class('NetDeviceStatistics', outer_class=root_module['ns3::PyViz'])
## pyviz.h (module 'visualizer'): ns3::PyViz::NodeStatistics [struct]
module.add_class('NodeStatistics', outer_class=root_module['ns3::PyViz'])
## pyviz.h (module 'visualizer'): ns3::PyViz::PacketCaptureOptions [struct]
module.add_class('PacketCaptureOptions', outer_class=root_module['ns3::PyViz'])
## pyviz.h (module 'visualizer'): ns3::PyViz::PacketDropSample [struct]
module.add_class('PacketDropSample', outer_class=root_module['ns3::PyViz'])
## pyviz.h (module 'visualizer'): ns3::PyViz::PacketSample [struct]
module.add_class('PacketSample', outer_class=root_module['ns3::PyViz'])
## pyviz.h (module 'visualizer'): ns3::PyViz::RxPacketSample [struct]
module.add_class('RxPacketSample', parent=root_module['ns3::PyViz::PacketSample'], outer_class=root_module['ns3::PyViz'])
## pyviz.h (module 'visualizer'): ns3::PyViz::TransmissionSample [struct]
module.add_class('TransmissionSample', outer_class=root_module['ns3::PyViz'])
## pyviz.h (module 'visualizer'): ns3::PyViz::TxPacketSample [struct]
module.add_class('TxPacketSample', parent=root_module['ns3::PyViz::PacketSample'], outer_class=root_module['ns3::PyViz'])
## simple-ref-count.h (module 'core'): ns3::SimpleRefCount<ns3::Object, ns3::ObjectBase, ns3::ObjectDeleter> [class]
module.add_class('SimpleRefCount', automatic_type_narrowing=True, import_from_module='ns.core', template_parameters=['ns3::Object', 'ns3::ObjectBase', 'ns3::ObjectDeleter'], parent=root_module['ns3::ObjectBase'], memory_policy=cppclass.ReferenceCountingMethodsPolicy(incref_method='Ref', decref_method='Unref', peekref_method='GetReferenceCount'))
## simulator.h (module 'core'): ns3::Simulator [class]
module.add_class('Simulator', destructor_visibility='private', import_from_module='ns.core')
## simulator.h (module 'core'): ns3::Simulator [enumeration]
module.add_enum('', ['NO_CONTEXT'], outer_class=root_module['ns3::Simulator'], import_from_module='ns.core')
## tag.h (module 'network'): ns3::Tag [class]
module.add_class('Tag', import_from_module='ns.network', parent=root_module['ns3::ObjectBase'])
## tag-buffer.h (module 'network'): ns3::TagBuffer [class]
module.add_class('TagBuffer', import_from_module='ns.network')
## nstime.h (module 'core'): ns3::TimeWithUnit [class]
module.add_class('TimeWithUnit', import_from_module='ns.core')
## type-id.h (module 'core'): ns3::TypeId [class]
module.add_class('TypeId', import_from_module='ns.core')
## type-id.h (module 'core'): ns3::TypeId::AttributeFlag [enumeration]
module.add_enum('AttributeFlag', ['ATTR_GET', 'ATTR_SET', 'ATTR_CONSTRUCT', 'ATTR_SGC'], outer_class=root_module['ns3::TypeId'], import_from_module='ns.core')
## type-id.h (module 'core'): ns3::TypeId::SupportLevel [enumeration]
module.add_enum('SupportLevel', ['SUPPORTED', 'DEPRECATED', 'OBSOLETE'], outer_class=root_module['ns3::TypeId'], import_from_module='ns.core')
## type-id.h (module 'core'): ns3::TypeId::AttributeInformation [struct]
module.add_class('AttributeInformation', import_from_module='ns.core', outer_class=root_module['ns3::TypeId'])
## type-id.h (module 'core'): ns3::TypeId::TraceSourceInformation [struct]
module.add_class('TraceSourceInformation', import_from_module='ns.core', outer_class=root_module['ns3::TypeId'])
## empty.h (module 'core'): ns3::empty [class]
module.add_class('empty', import_from_module='ns.core')
## int64x64-double.h (module 'core'): ns3::int64x64_t [class]
module.add_class('int64x64_t', import_from_module='ns.core')
## int64x64-double.h (module 'core'): ns3::int64x64_t::impl_type [enumeration]
module.add_enum('impl_type', ['int128_impl', 'cairo_impl', 'ld_impl'], outer_class=root_module['ns3::int64x64_t'], import_from_module='ns.core')
## chunk.h (module 'network'): ns3::Chunk [class]
module.add_class('Chunk', import_from_module='ns.network', parent=root_module['ns3::ObjectBase'])
## header.h (module 'network'): ns3::Header [class]
module.add_class('Header', import_from_module='ns.network', parent=root_module['ns3::Chunk'])
## ipv4-header.h (module 'internet'): ns3::Ipv4Header [class]
module.add_class('Ipv4Header', import_from_module='ns.internet', parent=root_module['ns3::Header'])
## ipv4-header.h (module 'internet'): ns3::Ipv4Header::DscpType [enumeration]
module.add_enum('DscpType', ['DscpDefault', 'DSCP_CS1', 'DSCP_AF11', 'DSCP_AF12', 'DSCP_AF13', 'DSCP_CS2', 'DSCP_AF21', 'DSCP_AF22', 'DSCP_AF23', 'DSCP_CS3', 'DSCP_AF31', 'DSCP_AF32', 'DSCP_AF33', 'DSCP_CS4', 'DSCP_AF41', 'DSCP_AF42', 'DSCP_AF43', 'DSCP_CS5', 'DSCP_EF', 'DSCP_CS6', 'DSCP_CS7'], outer_class=root_module['ns3::Ipv4Header'], import_from_module='ns.internet')
## ipv4-header.h (module 'internet'): ns3::Ipv4Header::EcnType [enumeration]
module.add_enum('EcnType', ['ECN_NotECT', 'ECN_ECT1', 'ECN_ECT0', 'ECN_CE'], outer_class=root_module['ns3::Ipv4Header'], import_from_module='ns.internet')
## object.h (module 'core'): ns3::Object [class]
module.add_class('Object', import_from_module='ns.core', parent=root_module['ns3::SimpleRefCount< ns3::Object, ns3::ObjectBase, ns3::ObjectDeleter >'])
## object.h (module 'core'): ns3::Object::AggregateIterator [class]
module.add_class('AggregateIterator', import_from_module='ns.core', outer_class=root_module['ns3::Object'])
## simple-ref-count.h (module 'core'): ns3::SimpleRefCount<ns3::AttributeAccessor, ns3::empty, ns3::DefaultDeleter<ns3::AttributeAccessor> > [class]
module.add_class('SimpleRefCount', automatic_type_narrowing=True, import_from_module='ns.core', template_parameters=['ns3::AttributeAccessor', 'ns3::empty', 'ns3::DefaultDeleter<ns3::AttributeAccessor>'], parent=root_module['ns3::empty'], memory_policy=cppclass.ReferenceCountingMethodsPolicy(incref_method='Ref', decref_method='Unref', peekref_method='GetReferenceCount'))
## simple-ref-count.h (module 'core'): ns3::SimpleRefCount<ns3::AttributeChecker, ns3::empty, ns3::DefaultDeleter<ns3::AttributeChecker> > [class]
module.add_class('SimpleRefCount', automatic_type_narrowing=True, import_from_module='ns.core', template_parameters=['ns3::AttributeChecker', 'ns3::empty', 'ns3::DefaultDeleter<ns3::AttributeChecker>'], parent=root_module['ns3::empty'], memory_policy=cppclass.ReferenceCountingMethodsPolicy(incref_method='Ref', decref_method='Unref', peekref_method='GetReferenceCount'))
## simple-ref-count.h (module 'core'): ns3::SimpleRefCount<ns3::AttributeValue, ns3::empty, ns3::DefaultDeleter<ns3::AttributeValue> > [class]
module.add_class('SimpleRefCount', automatic_type_narrowing=True, import_from_module='ns.core', template_parameters=['ns3::AttributeValue', 'ns3::empty', 'ns3::DefaultDeleter<ns3::AttributeValue>'], parent=root_module['ns3::empty'], memory_policy=cppclass.ReferenceCountingMethodsPolicy(incref_method='Ref', decref_method='Unref', peekref_method='GetReferenceCount'))
## simple-ref-count.h (module 'core'): ns3::SimpleRefCount<ns3::CallbackImplBase, ns3::empty, ns3::DefaultDeleter<ns3::CallbackImplBase> > [class]
module.add_class('SimpleRefCount', automatic_type_narrowing=True, import_from_module='ns.core', template_parameters=['ns3::CallbackImplBase', 'ns3::empty', 'ns3::DefaultDeleter<ns3::CallbackImplBase>'], parent=root_module['ns3::empty'], memory_policy=cppclass.ReferenceCountingMethodsPolicy(incref_method='Ref', decref_method='Unref', peekref_method='GetReferenceCount'))
## simple-ref-count.h (module 'core'): ns3::SimpleRefCount<ns3::EventImpl, ns3::empty, ns3::DefaultDeleter<ns3::EventImpl> > [class]
module.add_class('SimpleRefCount', automatic_type_narrowing=True, import_from_module='ns.core', template_parameters=['ns3::EventImpl', 'ns3::empty', 'ns3::DefaultDeleter<ns3::EventImpl>'], parent=root_module['ns3::empty'], memory_policy=cppclass.ReferenceCountingMethodsPolicy(incref_method='Ref', decref_method='Unref', peekref_method='GetReferenceCount'))
## simple-ref-count.h (module 'core'): ns3::SimpleRefCount<ns3::Hash::Implementation, ns3::empty, ns3::DefaultDeleter<ns3::Hash::Implementation> > [class]
module.add_class('SimpleRefCount', automatic_type_narrowing=True, import_from_module='ns.core', template_parameters=['ns3::Hash::Implementation', 'ns3::empty', 'ns3::DefaultDeleter<ns3::Hash::Implementation>'], parent=root_module['ns3::empty'], memory_policy=cppclass.ReferenceCountingMethodsPolicy(incref_method='Ref', decref_method='Unref', peekref_method='GetReferenceCount'))
## simple-ref-count.h (module 'core'): ns3::SimpleRefCount<ns3::Ipv4MulticastRoute, ns3::empty, ns3::DefaultDeleter<ns3::Ipv4MulticastRoute> > [class]
module.add_class('SimpleRefCount', automatic_type_narrowing=True, import_from_module='ns.core', template_parameters=['ns3::Ipv4MulticastRoute', 'ns3::empty', 'ns3::DefaultDeleter<ns3::Ipv4MulticastRoute>'], parent=root_module['ns3::empty'], memory_policy=cppclass.ReferenceCountingMethodsPolicy(incref_method='Ref', decref_method='Unref', peekref_method='GetReferenceCount'))
## simple-ref-count.h (module 'core'): ns3::SimpleRefCount<ns3::Ipv4Route, ns3::empty, ns3::DefaultDeleter<ns3::Ipv4Route> > [class]
module.add_class('SimpleRefCount', automatic_type_narrowing=True, import_from_module='ns.core', template_parameters=['ns3::Ipv4Route', 'ns3::empty', 'ns3::DefaultDeleter<ns3::Ipv4Route>'], parent=root_module['ns3::empty'], memory_policy=cppclass.ReferenceCountingMethodsPolicy(incref_method='Ref', decref_method='Unref', peekref_method='GetReferenceCount'))
## simple-ref-count.h (module 'core'): ns3::SimpleRefCount<ns3::NetDeviceQueue, ns3::empty, ns3::DefaultDeleter<ns3::NetDeviceQueue> > [class]
module.add_class('SimpleRefCount', automatic_type_narrowing=True, import_from_module='ns.core', template_parameters=['ns3::NetDeviceQueue', 'ns3::empty', 'ns3::DefaultDeleter<ns3::NetDeviceQueue>'], parent=root_module['ns3::empty'], memory_policy=cppclass.ReferenceCountingMethodsPolicy(incref_method='Ref', decref_method='Unref', peekref_method='GetReferenceCount'))
## simple-ref-count.h (module 'core'): ns3::SimpleRefCount<ns3::NixVector, ns3::empty, ns3::DefaultDeleter<ns3::NixVector> > [class]
module.add_class('SimpleRefCount', automatic_type_narrowing=True, import_from_module='ns.core', template_parameters=['ns3::NixVector', 'ns3::empty', 'ns3::DefaultDeleter<ns3::NixVector>'], parent=root_module['ns3::empty'], memory_policy=cppclass.ReferenceCountingMethodsPolicy(incref_method='Ref', decref_method='Unref', peekref_method='GetReferenceCount'))
## simple-ref-count.h (module 'core'): ns3::SimpleRefCount<ns3::OutputStreamWrapper, ns3::empty, ns3::DefaultDeleter<ns3::OutputStreamWrapper> > [class]
module.add_class('SimpleRefCount', automatic_type_narrowing=True, import_from_module='ns.core', template_parameters=['ns3::OutputStreamWrapper', 'ns3::empty', 'ns3::DefaultDeleter<ns3::OutputStreamWrapper>'], parent=root_module['ns3::empty'], memory_policy=cppclass.ReferenceCountingMethodsPolicy(incref_method='Ref', decref_method='Unref', peekref_method='GetReferenceCount'))
## simple-ref-count.h (module 'core'): ns3::SimpleRefCount<ns3::Packet, ns3::empty, ns3::DefaultDeleter<ns3::Packet> > [class]
module.add_class('SimpleRefCount', automatic_type_narrowing=True, import_from_module='ns.core', template_parameters=['ns3::Packet', 'ns3::empty', 'ns3::DefaultDeleter<ns3::Packet>'], parent=root_module['ns3::empty'], memory_policy=cppclass.ReferenceCountingMethodsPolicy(incref_method='Ref', decref_method='Unref', peekref_method='GetReferenceCount'))
## simple-ref-count.h (module 'core'): ns3::SimpleRefCount<ns3::QueueItem, ns3::empty, ns3::DefaultDeleter<ns3::QueueItem> > [class]
module.add_class('SimpleRefCount', automatic_type_narrowing=True, import_from_module='ns.core', template_parameters=['ns3::QueueItem', 'ns3::empty', 'ns3::DefaultDeleter<ns3::QueueItem>'], parent=root_module['ns3::empty'], memory_policy=cppclass.ReferenceCountingMethodsPolicy(incref_method='Ref', decref_method='Unref', peekref_method='GetReferenceCount'))
## simple-ref-count.h (module 'core'): ns3::SimpleRefCount<ns3::TraceSourceAccessor, ns3::empty, ns3::DefaultDeleter<ns3::TraceSourceAccessor> > [class]
module.add_class('SimpleRefCount', automatic_type_narrowing=True, import_from_module='ns.core', template_parameters=['ns3::TraceSourceAccessor', 'ns3::empty', 'ns3::DefaultDeleter<ns3::TraceSourceAccessor>'], parent=root_module['ns3::empty'], memory_policy=cppclass.ReferenceCountingMethodsPolicy(incref_method='Ref', decref_method='Unref', peekref_method='GetReferenceCount'))
## socket.h (module 'network'): ns3::Socket [class]
module.add_class('Socket', import_from_module='ns.network', parent=root_module['ns3::Object'])
## socket.h (module 'network'): ns3::Socket::SocketErrno [enumeration]
module.add_enum('SocketErrno', ['ERROR_NOTERROR', 'ERROR_ISCONN', 'ERROR_NOTCONN', 'ERROR_MSGSIZE', 'ERROR_AGAIN', 'ERROR_SHUTDOWN', 'ERROR_OPNOTSUPP', 'ERROR_AFNOSUPPORT', 'ERROR_INVAL', 'ERROR_BADF', 'ERROR_NOROUTETOHOST', 'ERROR_NODEV', 'ERROR_ADDRNOTAVAIL', 'ERROR_ADDRINUSE', 'SOCKET_ERRNO_LAST'], outer_class=root_module['ns3::Socket'], import_from_module='ns.network')
## socket.h (module 'network'): ns3::Socket::SocketType [enumeration]
module.add_enum('SocketType', ['NS3_SOCK_STREAM', 'NS3_SOCK_SEQPACKET', 'NS3_SOCK_DGRAM', 'NS3_SOCK_RAW'], outer_class=root_module['ns3::Socket'], import_from_module='ns.network')
## socket.h (module 'network'): ns3::Socket::SocketPriority [enumeration]
module.add_enum('SocketPriority', ['NS3_PRIO_BESTEFFORT', 'NS3_PRIO_FILLER', 'NS3_PRIO_BULK', 'NS3_PRIO_INTERACTIVE_BULK', 'NS3_PRIO_INTERACTIVE', 'NS3_PRIO_CONTROL'], outer_class=root_module['ns3::Socket'], import_from_module='ns.network')
## socket.h (module 'network'): ns3::Socket::Ipv6MulticastFilterMode [enumeration]
module.add_enum('Ipv6MulticastFilterMode', ['INCLUDE', 'EXCLUDE'], outer_class=root_module['ns3::Socket'], import_from_module='ns.network')
## socket.h (module 'network'): ns3::SocketIpTosTag [class]
module.add_class('SocketIpTosTag', import_from_module='ns.network', parent=root_module['ns3::Tag'])
## socket.h (module 'network'): ns3::SocketIpTtlTag [class]
module.add_class('SocketIpTtlTag', import_from_module='ns.network', parent=root_module['ns3::Tag'])
## socket.h (module 'network'): ns3::SocketIpv6HopLimitTag [class]
module.add_class('SocketIpv6HopLimitTag', import_from_module='ns.network', parent=root_module['ns3::Tag'])
## socket.h (module 'network'): ns3::SocketIpv6TclassTag [class]
module.add_class('SocketIpv6TclassTag', import_from_module='ns.network', parent=root_module['ns3::Tag'])
## socket.h (module 'network'): ns3::SocketPriorityTag [class]
module.add_class('SocketPriorityTag', import_from_module='ns.network', parent=root_module['ns3::Tag'])
## socket.h (module 'network'): ns3::SocketSetDontFragmentTag [class]
module.add_class('SocketSetDontFragmentTag', import_from_module='ns.network', parent=root_module['ns3::Tag'])
## nstime.h (module 'core'): ns3::Time [class]
module.add_class('Time', import_from_module='ns.core')
## nstime.h (module 'core'): ns3::Time::Unit [enumeration]
module.add_enum('Unit', ['Y', 'D', 'H', 'MIN', 'S', 'MS', 'US', 'NS', 'PS', 'FS', 'LAST'], outer_class=root_module['ns3::Time'], import_from_module='ns.core')
## nstime.h (module 'core'): ns3::Time [class]
root_module['ns3::Time'].implicitly_converts_to(root_module['ns3::int64x64_t'])
## trace-source-accessor.h (module 'core'): ns3::TraceSourceAccessor [class]
module.add_class('TraceSourceAccessor', import_from_module='ns.core', parent=root_module['ns3::SimpleRefCount< ns3::TraceSourceAccessor, ns3::empty, ns3::DefaultDeleter<ns3::TraceSourceAccessor> >'])
## trailer.h (module 'network'): ns3::Trailer [class]
module.add_class('Trailer', import_from_module='ns.network', parent=root_module['ns3::Chunk'])
## attribute.h (module 'core'): ns3::AttributeAccessor [class]
module.add_class('AttributeAccessor', import_from_module='ns.core', parent=root_module['ns3::SimpleRefCount< ns3::AttributeAccessor, ns3::empty, ns3::DefaultDeleter<ns3::AttributeAccessor> >'])
## attribute.h (module 'core'): ns3::AttributeChecker [class]
module.add_class('AttributeChecker', allow_subclassing=False, automatic_type_narrowing=True, import_from_module='ns.core', parent=root_module['ns3::SimpleRefCount< ns3::AttributeChecker, ns3::empty, ns3::DefaultDeleter<ns3::AttributeChecker> >'])
## attribute.h (module 'core'): ns3::AttributeValue [class]
module.add_class('AttributeValue', allow_subclassing=False, automatic_type_narrowing=True, import_from_module='ns.core', parent=root_module['ns3::SimpleRefCount< ns3::AttributeValue, ns3::empty, ns3::DefaultDeleter<ns3::AttributeValue> >'])
## callback.h (module 'core'): ns3::CallbackChecker [class]
module.add_class('CallbackChecker', import_from_module='ns.core', parent=root_module['ns3::AttributeChecker'])
## callback.h (module 'core'): ns3::CallbackImplBase [class]
module.add_class('CallbackImplBase', import_from_module='ns.core', parent=root_module['ns3::SimpleRefCount< ns3::CallbackImplBase, ns3::empty, ns3::DefaultDeleter<ns3::CallbackImplBase> >'])
## callback.h (module 'core'): ns3::CallbackValue [class]
module.add_class('CallbackValue', import_from_module='ns.core', parent=root_module['ns3::AttributeValue'])
## channel.h (module 'network'): ns3::Channel [class]
module.add_class('Channel', import_from_module='ns.network', parent=root_module['ns3::Object'])
## attribute.h (module 'core'): ns3::EmptyAttributeAccessor [class]
module.add_class('EmptyAttributeAccessor', import_from_module='ns.core', parent=root_module['ns3::AttributeAccessor'])
## attribute.h (module 'core'): ns3::EmptyAttributeChecker [class]
module.add_class('EmptyAttributeChecker', import_from_module='ns.core', parent=root_module['ns3::AttributeChecker'])
## attribute.h (module 'core'): ns3::EmptyAttributeValue [class]
module.add_class('EmptyAttributeValue', import_from_module='ns.core', parent=root_module['ns3::AttributeValue'])
## event-impl.h (module 'core'): ns3::EventImpl [class]
module.add_class('EventImpl', import_from_module='ns.core', parent=root_module['ns3::SimpleRefCount< ns3::EventImpl, ns3::empty, ns3::DefaultDeleter<ns3::EventImpl> >'])
## ipv4.h (module 'internet'): ns3::Ipv4 [class]
module.add_class('Ipv4', import_from_module='ns.internet', parent=root_module['ns3::Object'])
## ipv4-address.h (module 'network'): ns3::Ipv4AddressChecker [class]
module.add_class('Ipv4AddressChecker', import_from_module='ns.network', parent=root_module['ns3::AttributeChecker'])
## ipv4-address.h (module 'network'): ns3::Ipv4AddressValue [class]
module.add_class('Ipv4AddressValue', import_from_module='ns.network', parent=root_module['ns3::AttributeValue'])
## ipv4-l3-protocol.h (module 'internet'): ns3::Ipv4L3Protocol [class]
module.add_class('Ipv4L3Protocol', import_from_module='ns.internet', parent=root_module['ns3::Ipv4'])
## ipv4-l3-protocol.h (module 'internet'): ns3::Ipv4L3Protocol::DropReason [enumeration]
module.add_enum('DropReason', ['DROP_TTL_EXPIRED', 'DROP_NO_ROUTE', 'DROP_BAD_CHECKSUM', 'DROP_INTERFACE_DOWN', 'DROP_ROUTE_ERROR', 'DROP_FRAGMENT_TIMEOUT'], outer_class=root_module['ns3::Ipv4L3Protocol'], import_from_module='ns.internet')
## ipv4-address.h (module 'network'): ns3::Ipv4MaskChecker [class]
module.add_class('Ipv4MaskChecker', import_from_module='ns.network', parent=root_module['ns3::AttributeChecker'])
## ipv4-address.h (module 'network'): ns3::Ipv4MaskValue [class]
module.add_class('Ipv4MaskValue', import_from_module='ns.network', parent=root_module['ns3::AttributeValue'])
## ipv4-route.h (module 'internet'): ns3::Ipv4MulticastRoute [class]
module.add_class('Ipv4MulticastRoute', import_from_module='ns.internet', parent=root_module['ns3::SimpleRefCount< ns3::Ipv4MulticastRoute, ns3::empty, ns3::DefaultDeleter<ns3::Ipv4MulticastRoute> >'])
## ipv4-route.h (module 'internet'): ns3::Ipv4Route [class]
module.add_class('Ipv4Route', import_from_module='ns.internet', parent=root_module['ns3::SimpleRefCount< ns3::Ipv4Route, ns3::empty, ns3::DefaultDeleter<ns3::Ipv4Route> >'])
## ipv4-routing-protocol.h (module 'internet'): ns3::Ipv4RoutingProtocol [class]
module.add_class('Ipv4RoutingProtocol', import_from_module='ns.internet', parent=root_module['ns3::Object'])
## ipv6-address.h (module 'network'): ns3::Ipv6AddressChecker [class]
module.add_class('Ipv6AddressChecker', import_from_module='ns.network', parent=root_module['ns3::AttributeChecker'])
## ipv6-address.h (module 'network'): ns3::Ipv6AddressValue [class]
module.add_class('Ipv6AddressValue', import_from_module='ns.network', parent=root_module['ns3::AttributeValue'])
## ipv6-address.h (module 'network'): ns3::Ipv6PrefixChecker [class]
module.add_class('Ipv6PrefixChecker', import_from_module='ns.network', parent=root_module['ns3::AttributeChecker'])
## ipv6-address.h (module 'network'): ns3::Ipv6PrefixValue [class]
module.add_class('Ipv6PrefixValue', import_from_module='ns.network', parent=root_module['ns3::AttributeValue'])
## mac48-address.h (module 'network'): ns3::Mac48AddressChecker [class]
module.add_class('Mac48AddressChecker', import_from_module='ns.network', parent=root_module['ns3::AttributeChecker'])
## mac48-address.h (module 'network'): ns3::Mac48AddressValue [class]
module.add_class('Mac48AddressValue', import_from_module='ns.network', parent=root_module['ns3::AttributeValue'])
## net-device.h (module 'network'): ns3::NetDevice [class]
module.add_class('NetDevice', import_from_module='ns.network', parent=root_module['ns3::Object'])
## net-device.h (module 'network'): ns3::NetDevice::PacketType [enumeration]
module.add_enum('PacketType', ['PACKET_HOST', 'NS3_PACKET_HOST', 'PACKET_BROADCAST', 'NS3_PACKET_BROADCAST', 'PACKET_MULTICAST', 'NS3_PACKET_MULTICAST', 'PACKET_OTHERHOST', 'NS3_PACKET_OTHERHOST'], outer_class=root_module['ns3::NetDevice'], import_from_module='ns.network')
## net-device.h (module 'network'): ns3::NetDeviceQueue [class]
module.add_class('NetDeviceQueue', import_from_module='ns.network', parent=root_module['ns3::SimpleRefCount< ns3::NetDeviceQueue, ns3::empty, ns3::DefaultDeleter<ns3::NetDeviceQueue> >'])
## net-device.h (module 'network'): ns3::NetDeviceQueueInterface [class]
module.add_class('NetDeviceQueueInterface', import_from_module='ns.network', parent=root_module['ns3::Object'])
## nix-vector.h (module 'network'): ns3::NixVector [class]
module.add_class('NixVector', import_from_module='ns.network', parent=root_module['ns3::SimpleRefCount< ns3::NixVector, ns3::empty, ns3::DefaultDeleter<ns3::NixVector> >'])
## node.h (module 'network'): ns3::Node [class]
module.add_class('Node', import_from_module='ns.network', parent=root_module['ns3::Object'])
## object-factory.h (module 'core'): ns3::ObjectFactoryChecker [class]
module.add_class('ObjectFactoryChecker', import_from_module='ns.core', parent=root_module['ns3::AttributeChecker'])
## object-factory.h (module 'core'): ns3::ObjectFactoryValue [class]
module.add_class('ObjectFactoryValue', import_from_module='ns.core', parent=root_module['ns3::AttributeValue'])
## output-stream-wrapper.h (module 'network'): ns3::OutputStreamWrapper [class]
module.add_class('OutputStreamWrapper', import_from_module='ns.network', parent=root_module['ns3::SimpleRefCount< ns3::OutputStreamWrapper, ns3::empty, ns3::DefaultDeleter<ns3::OutputStreamWrapper> >'])
## packet.h (module 'network'): ns3::Packet [class]
module.add_class('Packet', import_from_module='ns.network', parent=root_module['ns3::SimpleRefCount< ns3::Packet, ns3::empty, ns3::DefaultDeleter<ns3::Packet> >'])
## net-device.h (module 'network'): ns3::QueueItem [class]
module.add_class('QueueItem', import_from_module='ns.network', parent=root_module['ns3::SimpleRefCount< ns3::QueueItem, ns3::empty, ns3::DefaultDeleter<ns3::QueueItem> >'])
## net-device.h (module 'network'): ns3::QueueItem::Uint8Values [enumeration]
module.add_enum('Uint8Values', ['IP_DSFIELD'], outer_class=root_module['ns3::QueueItem'], import_from_module='ns.network')
## nstime.h (module 'core'): ns3::TimeValue [class]
module.add_class('TimeValue', import_from_module='ns.core', parent=root_module['ns3::AttributeValue'])
## type-id.h (module 'core'): ns3::TypeIdChecker [class]
module.add_class('TypeIdChecker', import_from_module='ns.core', parent=root_module['ns3::AttributeChecker'])
## type-id.h (module 'core'): ns3::TypeIdValue [class]
module.add_class('TypeIdValue', import_from_module='ns.core', parent=root_module['ns3::AttributeValue'])
## address.h (module 'network'): ns3::AddressChecker [class]
module.add_class('AddressChecker', import_from_module='ns.network', parent=root_module['ns3::AttributeChecker'])
## address.h (module 'network'): ns3::AddressValue [class]
module.add_class('AddressValue', import_from_module='ns.network', parent=root_module['ns3::AttributeValue'])
module.add_container('std::vector< ns3::PyViz::RxPacketSample >', 'ns3::PyViz::RxPacketSample', container_type=u'vector')
module.add_container('std::vector< ns3::PyViz::TxPacketSample >', 'ns3::PyViz::TxPacketSample', container_type=u'vector')
module.add_container('std::vector< ns3::PyViz::PacketSample >', 'ns3::PyViz::PacketSample', container_type=u'vector')
module.add_container('std::set< ns3::TypeId >', 'ns3::TypeId', container_type=u'set')
module.add_container('std::vector< ns3::PyViz::TransmissionSample >', 'ns3::PyViz::TransmissionSample', container_type=u'vector')
module.add_container('std::vector< ns3::PyViz::PacketDropSample >', 'ns3::PyViz::PacketDropSample', container_type=u'vector')
module.add_container('std::vector< ns3::PyViz::NetDeviceStatistics >', 'ns3::PyViz::NetDeviceStatistics', container_type=u'vector')
module.add_container('std::vector< std::string >', 'std::string', container_type=u'vector')
module.add_container('std::set< unsigned int >', 'unsigned int', container_type=u'set')
module.add_container('std::vector< ns3::PyViz::NodeStatistics >', 'ns3::PyViz::NodeStatistics', container_type=u'vector')
module.add_container('std::vector< ns3::Ipv6Address >', 'ns3::Ipv6Address', container_type=u'vector')
module.add_container('std::map< unsigned int, unsigned int >', ('unsigned int', 'unsigned int'), container_type=u'map')
## Register a nested module for the namespace FatalImpl
nested_module = module.add_cpp_namespace('FatalImpl')
register_types_ns3_FatalImpl(nested_module)
## Register a nested module for the namespace Hash
nested_module = module.add_cpp_namespace('Hash')
register_types_ns3_Hash(nested_module)
## Register a nested module for the namespace TracedValueCallback
nested_module = module.add_cpp_namespace('TracedValueCallback')
register_types_ns3_TracedValueCallback(nested_module)
def register_types_ns3_FatalImpl(module):
root_module = module.get_root()
def register_types_ns3_Hash(module):
root_module = module.get_root()
## hash-function.h (module 'core'): ns3::Hash::Implementation [class]
module.add_class('Implementation', import_from_module='ns.core', parent=root_module['ns3::SimpleRefCount< ns3::Hash::Implementation, ns3::empty, ns3::DefaultDeleter<ns3::Hash::Implementation> >'])
typehandlers.add_type_alias(u'uint32_t ( * ) ( char const *, size_t ) *', u'ns3::Hash::Hash32Function_ptr')
typehandlers.add_type_alias(u'uint32_t ( * ) ( char const *, size_t ) **', u'ns3::Hash::Hash32Function_ptr*')
typehandlers.add_type_alias(u'uint32_t ( * ) ( char const *, size_t ) *&', u'ns3::Hash::Hash32Function_ptr&')
typehandlers.add_type_alias(u'uint64_t ( * ) ( char const *, size_t ) *', u'ns3::Hash::Hash64Function_ptr')
typehandlers.add_type_alias(u'uint64_t ( * ) ( char const *, size_t ) **', u'ns3::Hash::Hash64Function_ptr*')
typehandlers.add_type_alias(u'uint64_t ( * ) ( char const *, size_t ) *&', u'ns3::Hash::Hash64Function_ptr&')
## Register a nested module for the namespace Function
nested_module = module.add_cpp_namespace('Function')
register_types_ns3_Hash_Function(nested_module)
def register_types_ns3_Hash_Function(module):
root_module = module.get_root()
## hash-fnv.h (module 'core'): ns3::Hash::Function::Fnv1a [class]
module.add_class('Fnv1a', import_from_module='ns.core', parent=root_module['ns3::Hash::Implementation'])
## hash-function.h (module 'core'): ns3::Hash::Function::Hash32 [class]
module.add_class('Hash32', import_from_module='ns.core', parent=root_module['ns3::Hash::Implementation'])
## hash-function.h (module 'core'): ns3::Hash::Function::Hash64 [class]
module.add_class('Hash64', import_from_module='ns.core', parent=root_module['ns3::Hash::Implementation'])
## hash-murmur3.h (module 'core'): ns3::Hash::Function::Murmur3 [class]
module.add_class('Murmur3', import_from_module='ns.core', parent=root_module['ns3::Hash::Implementation'])
def register_types_ns3_TracedValueCallback(module):
root_module = module.get_root()
typehandlers.add_type_alias(u'void ( * ) ( ns3::Time, ns3::Time ) *', u'ns3::TracedValueCallback::Time')
typehandlers.add_type_alias(u'void ( * ) ( ns3::Time, ns3::Time ) **', u'ns3::TracedValueCallback::Time*')
typehandlers.add_type_alias(u'void ( * ) ( ns3::Time, ns3::Time ) *&', u'ns3::TracedValueCallback::Time&')
def register_methods(root_module):
register_Ns3Address_methods(root_module, root_module['ns3::Address'])
register_Ns3AttributeConstructionList_methods(root_module, root_module['ns3::AttributeConstructionList'])
register_Ns3AttributeConstructionListItem_methods(root_module, root_module['ns3::AttributeConstructionList::Item'])
register_Ns3Buffer_methods(root_module, root_module['ns3::Buffer'])
register_Ns3BufferIterator_methods(root_module, root_module['ns3::Buffer::Iterator'])
register_Ns3ByteTagIterator_methods(root_module, root_module['ns3::ByteTagIterator'])
register_Ns3ByteTagIteratorItem_methods(root_module, root_module['ns3::ByteTagIterator::Item'])
register_Ns3ByteTagList_methods(root_module, root_module['ns3::ByteTagList'])
register_Ns3ByteTagListIterator_methods(root_module, root_module['ns3::ByteTagList::Iterator'])
register_Ns3ByteTagListIteratorItem_methods(root_module, root_module['ns3::ByteTagList::Iterator::Item'])
register_Ns3CallbackBase_methods(root_module, root_module['ns3::CallbackBase'])
register_Ns3EventId_methods(root_module, root_module['ns3::EventId'])
register_Ns3Hasher_methods(root_module, root_module['ns3::Hasher'])
register_Ns3Inet6SocketAddress_methods(root_module, root_module['ns3::Inet6SocketAddress'])
register_Ns3InetSocketAddress_methods(root_module, root_module['ns3::InetSocketAddress'])
register_Ns3Ipv4Address_methods(root_module, root_module['ns3::Ipv4Address'])
register_Ns3Ipv4InterfaceAddress_methods(root_module, root_module['ns3::Ipv4InterfaceAddress'])
register_Ns3Ipv4Mask_methods(root_module, root_module['ns3::Ipv4Mask'])
register_Ns3Ipv6Address_methods(root_module, root_module['ns3::Ipv6Address'])
register_Ns3Ipv6Prefix_methods(root_module, root_module['ns3::Ipv6Prefix'])
register_Ns3Mac48Address_methods(root_module, root_module['ns3::Mac48Address'])
register_Ns3ObjectBase_methods(root_module, root_module['ns3::ObjectBase'])
register_Ns3ObjectDeleter_methods(root_module, root_module['ns3::ObjectDeleter'])
register_Ns3ObjectFactory_methods(root_module, root_module['ns3::ObjectFactory'])
register_Ns3PacketMetadata_methods(root_module, root_module['ns3::PacketMetadata'])
register_Ns3PacketMetadataItem_methods(root_module, root_module['ns3::PacketMetadata::Item'])
register_Ns3PacketMetadataItemIterator_methods(root_module, root_module['ns3::PacketMetadata::ItemIterator'])
register_Ns3PacketTagIterator_methods(root_module, root_module['ns3::PacketTagIterator'])
register_Ns3PacketTagIteratorItem_methods(root_module, root_module['ns3::PacketTagIterator::Item'])
register_Ns3PacketTagList_methods(root_module, root_module['ns3::PacketTagList'])
register_Ns3PacketTagListTagData_methods(root_module, root_module['ns3::PacketTagList::TagData'])
register_Ns3PyViz_methods(root_module, root_module['ns3::PyViz'])
register_Ns3PyVizLastPacketsSample_methods(root_module, root_module['ns3::PyViz::LastPacketsSample'])
register_Ns3PyVizNetDeviceStatistics_methods(root_module, root_module['ns3::PyViz::NetDeviceStatistics'])
register_Ns3PyVizNodeStatistics_methods(root_module, root_module['ns3::PyViz::NodeStatistics'])
register_Ns3PyVizPacketCaptureOptions_methods(root_module, root_module['ns3::PyViz::PacketCaptureOptions'])
register_Ns3PyVizPacketDropSample_methods(root_module, root_module['ns3::PyViz::PacketDropSample'])
register_Ns3PyVizPacketSample_methods(root_module, root_module['ns3::PyViz::PacketSample'])
register_Ns3PyVizRxPacketSample_methods(root_module, root_module['ns3::PyViz::RxPacketSample'])
register_Ns3PyVizTransmissionSample_methods(root_module, root_module['ns3::PyViz::TransmissionSample'])
register_Ns3PyVizTxPacketSample_methods(root_module, root_module['ns3::PyViz::TxPacketSample'])
register_Ns3SimpleRefCount__Ns3Object_Ns3ObjectBase_Ns3ObjectDeleter_methods(root_module, root_module['ns3::SimpleRefCount< ns3::Object, ns3::ObjectBase, ns3::ObjectDeleter >'])
register_Ns3Simulator_methods(root_module, root_module['ns3::Simulator'])
register_Ns3Tag_methods(root_module, root_module['ns3::Tag'])
register_Ns3TagBuffer_methods(root_module, root_module['ns3::TagBuffer'])
register_Ns3TimeWithUnit_methods(root_module, root_module['ns3::TimeWithUnit'])
register_Ns3TypeId_methods(root_module, root_module['ns3::TypeId'])
register_Ns3TypeIdAttributeInformation_methods(root_module, root_module['ns3::TypeId::AttributeInformation'])
register_Ns3TypeIdTraceSourceInformation_methods(root_module, root_module['ns3::TypeId::TraceSourceInformation'])
register_Ns3Empty_methods(root_module, root_module['ns3::empty'])
register_Ns3Int64x64_t_methods(root_module, root_module['ns3::int64x64_t'])
register_Ns3Chunk_methods(root_module, root_module['ns3::Chunk'])
register_Ns3Header_methods(root_module, root_module['ns3::Header'])
register_Ns3Ipv4Header_methods(root_module, root_module['ns3::Ipv4Header'])
register_Ns3Object_methods(root_module, root_module['ns3::Object'])
register_Ns3ObjectAggregateIterator_methods(root_module, root_module['ns3::Object::AggregateIterator'])
register_Ns3SimpleRefCount__Ns3AttributeAccessor_Ns3Empty_Ns3DefaultDeleter__lt__ns3AttributeAccessor__gt___methods(root_module, root_module['ns3::SimpleRefCount< ns3::AttributeAccessor, ns3::empty, ns3::DefaultDeleter<ns3::AttributeAccessor> >'])
register_Ns3SimpleRefCount__Ns3AttributeChecker_Ns3Empty_Ns3DefaultDeleter__lt__ns3AttributeChecker__gt___methods(root_module, root_module['ns3::SimpleRefCount< ns3::AttributeChecker, ns3::empty, ns3::DefaultDeleter<ns3::AttributeChecker> >'])
register_Ns3SimpleRefCount__Ns3AttributeValue_Ns3Empty_Ns3DefaultDeleter__lt__ns3AttributeValue__gt___methods(root_module, root_module['ns3::SimpleRefCount< ns3::AttributeValue, ns3::empty, ns3::DefaultDeleter<ns3::AttributeValue> >'])
register_Ns3SimpleRefCount__Ns3CallbackImplBase_Ns3Empty_Ns3DefaultDeleter__lt__ns3CallbackImplBase__gt___methods(root_module, root_module['ns3::SimpleRefCount< ns3::CallbackImplBase, ns3::empty, ns3::DefaultDeleter<ns3::CallbackImplBase> >'])
register_Ns3SimpleRefCount__Ns3EventImpl_Ns3Empty_Ns3DefaultDeleter__lt__ns3EventImpl__gt___methods(root_module, root_module['ns3::SimpleRefCount< ns3::EventImpl, ns3::empty, ns3::DefaultDeleter<ns3::EventImpl> >'])
register_Ns3SimpleRefCount__Ns3HashImplementation_Ns3Empty_Ns3DefaultDeleter__lt__ns3HashImplementation__gt___methods(root_module, root_module['ns3::SimpleRefCount< ns3::Hash::Implementation, ns3::empty, ns3::DefaultDeleter<ns3::Hash::Implementation> >'])
register_Ns3SimpleRefCount__Ns3Ipv4MulticastRoute_Ns3Empty_Ns3DefaultDeleter__lt__ns3Ipv4MulticastRoute__gt___methods(root_module, root_module['ns3::SimpleRefCount< ns3::Ipv4MulticastRoute, ns3::empty, ns3::DefaultDeleter<ns3::Ipv4MulticastRoute> >'])
register_Ns3SimpleRefCount__Ns3Ipv4Route_Ns3Empty_Ns3DefaultDeleter__lt__ns3Ipv4Route__gt___methods(root_module, root_module['ns3::SimpleRefCount< ns3::Ipv4Route, ns3::empty, ns3::DefaultDeleter<ns3::Ipv4Route> >'])
register_Ns3SimpleRefCount__Ns3NetDeviceQueue_Ns3Empty_Ns3DefaultDeleter__lt__ns3NetDeviceQueue__gt___methods(root_module, root_module['ns3::SimpleRefCount< ns3::NetDeviceQueue, ns3::empty, ns3::DefaultDeleter<ns3::NetDeviceQueue> >'])
register_Ns3SimpleRefCount__Ns3NixVector_Ns3Empty_Ns3DefaultDeleter__lt__ns3NixVector__gt___methods(root_module, root_module['ns3::SimpleRefCount< ns3::NixVector, ns3::empty, ns3::DefaultDeleter<ns3::NixVector> >'])
register_Ns3SimpleRefCount__Ns3OutputStreamWrapper_Ns3Empty_Ns3DefaultDeleter__lt__ns3OutputStreamWrapper__gt___methods(root_module, root_module['ns3::SimpleRefCount< ns3::OutputStreamWrapper, ns3::empty, ns3::DefaultDeleter<ns3::OutputStreamWrapper> >'])
register_Ns3SimpleRefCount__Ns3Packet_Ns3Empty_Ns3DefaultDeleter__lt__ns3Packet__gt___methods(root_module, root_module['ns3::SimpleRefCount< ns3::Packet, ns3::empty, ns3::DefaultDeleter<ns3::Packet> >'])
register_Ns3SimpleRefCount__Ns3QueueItem_Ns3Empty_Ns3DefaultDeleter__lt__ns3QueueItem__gt___methods(root_module, root_module['ns3::SimpleRefCount< ns3::QueueItem, ns3::empty, ns3::DefaultDeleter<ns3::QueueItem> >'])
register_Ns3SimpleRefCount__Ns3TraceSourceAccessor_Ns3Empty_Ns3DefaultDeleter__lt__ns3TraceSourceAccessor__gt___methods(root_module, root_module['ns3::SimpleRefCount< ns3::TraceSourceAccessor, ns3::empty, ns3::DefaultDeleter<ns3::TraceSourceAccessor> >'])
register_Ns3Socket_methods(root_module, root_module['ns3::Socket'])
register_Ns3SocketIpTosTag_methods(root_module, root_module['ns3::SocketIpTosTag'])
register_Ns3SocketIpTtlTag_methods(root_module, root_module['ns3::SocketIpTtlTag'])
register_Ns3SocketIpv6HopLimitTag_methods(root_module, root_module['ns3::SocketIpv6HopLimitTag'])
register_Ns3SocketIpv6TclassTag_methods(root_module, root_module['ns3::SocketIpv6TclassTag'])
register_Ns3SocketPriorityTag_methods(root_module, root_module['ns3::SocketPriorityTag'])
register_Ns3SocketSetDontFragmentTag_methods(root_module, root_module['ns3::SocketSetDontFragmentTag'])
register_Ns3Time_methods(root_module, root_module['ns3::Time'])
register_Ns3TraceSourceAccessor_methods(root_module, root_module['ns3::TraceSourceAccessor'])
register_Ns3Trailer_methods(root_module, root_module['ns3::Trailer'])
register_Ns3AttributeAccessor_methods(root_module, root_module['ns3::AttributeAccessor'])
register_Ns3AttributeChecker_methods(root_module, root_module['ns3::AttributeChecker'])
register_Ns3AttributeValue_methods(root_module, root_module['ns3::AttributeValue'])
register_Ns3CallbackChecker_methods(root_module, root_module['ns3::CallbackChecker'])
register_Ns3CallbackImplBase_methods(root_module, root_module['ns3::CallbackImplBase'])
register_Ns3CallbackValue_methods(root_module, root_module['ns3::CallbackValue'])
register_Ns3Channel_methods(root_module, root_module['ns3::Channel'])
register_Ns3EmptyAttributeAccessor_methods(root_module, root_module['ns3::EmptyAttributeAccessor'])
register_Ns3EmptyAttributeChecker_methods(root_module, root_module['ns3::EmptyAttributeChecker'])
register_Ns3EmptyAttributeValue_methods(root_module, root_module['ns3::EmptyAttributeValue'])
register_Ns3EventImpl_methods(root_module, root_module['ns3::EventImpl'])
register_Ns3Ipv4_methods(root_module, root_module['ns3::Ipv4'])
register_Ns3Ipv4AddressChecker_methods(root_module, root_module['ns3::Ipv4AddressChecker'])
register_Ns3Ipv4AddressValue_methods(root_module, root_module['ns3::Ipv4AddressValue'])
register_Ns3Ipv4L3Protocol_methods(root_module, root_module['ns3::Ipv4L3Protocol'])
register_Ns3Ipv4MaskChecker_methods(root_module, root_module['ns3::Ipv4MaskChecker'])
register_Ns3Ipv4MaskValue_methods(root_module, root_module['ns3::Ipv4MaskValue'])
register_Ns3Ipv4MulticastRoute_methods(root_module, root_module['ns3::Ipv4MulticastRoute'])
register_Ns3Ipv4Route_methods(root_module, root_module['ns3::Ipv4Route'])
register_Ns3Ipv4RoutingProtocol_methods(root_module, root_module['ns3::Ipv4RoutingProtocol'])
register_Ns3Ipv6AddressChecker_methods(root_module, root_module['ns3::Ipv6AddressChecker'])
register_Ns3Ipv6AddressValue_methods(root_module, root_module['ns3::Ipv6AddressValue'])
register_Ns3Ipv6PrefixChecker_methods(root_module, root_module['ns3::Ipv6PrefixChecker'])
register_Ns3Ipv6PrefixValue_methods(root_module, root_module['ns3::Ipv6PrefixValue'])
register_Ns3Mac48AddressChecker_methods(root_module, root_module['ns3::Mac48AddressChecker'])
register_Ns3Mac48AddressValue_methods(root_module, root_module['ns3::Mac48AddressValue'])
register_Ns3NetDevice_methods(root_module, root_module['ns3::NetDevice'])
register_Ns3NetDeviceQueue_methods(root_module, root_module['ns3::NetDeviceQueue'])
register_Ns3NetDeviceQueueInterface_methods(root_module, root_module['ns3::NetDeviceQueueInterface'])
register_Ns3NixVector_methods(root_module, root_module['ns3::NixVector'])
register_Ns3Node_methods(root_module, root_module['ns3::Node'])
register_Ns3ObjectFactoryChecker_methods(root_module, root_module['ns3::ObjectFactoryChecker'])
register_Ns3ObjectFactoryValue_methods(root_module, root_module['ns3::ObjectFactoryValue'])
register_Ns3OutputStreamWrapper_methods(root_module, root_module['ns3::OutputStreamWrapper'])
register_Ns3Packet_methods(root_module, root_module['ns3::Packet'])
register_Ns3QueueItem_methods(root_module, root_module['ns3::QueueItem'])
register_Ns3TimeValue_methods(root_module, root_module['ns3::TimeValue'])
register_Ns3TypeIdChecker_methods(root_module, root_module['ns3::TypeIdChecker'])
register_Ns3TypeIdValue_methods(root_module, root_module['ns3::TypeIdValue'])
register_Ns3AddressChecker_methods(root_module, root_module['ns3::AddressChecker'])
register_Ns3AddressValue_methods(root_module, root_module['ns3::AddressValue'])
register_Ns3HashImplementation_methods(root_module, root_module['ns3::Hash::Implementation'])
register_Ns3HashFunctionFnv1a_methods(root_module, root_module['ns3::Hash::Function::Fnv1a'])
register_Ns3HashFunctionHash32_methods(root_module, root_module['ns3::Hash::Function::Hash32'])
register_Ns3HashFunctionHash64_methods(root_module, root_module['ns3::Hash::Function::Hash64'])
register_Ns3HashFunctionMurmur3_methods(root_module, root_module['ns3::Hash::Function::Murmur3'])
return
def register_Ns3Address_methods(root_module, cls):
cls.add_binary_comparison_operator('<')
cls.add_binary_comparison_operator('!=')
cls.add_output_stream_operator()
cls.add_binary_comparison_operator('==')
## address.h (module 'network'): ns3::Address::Address() [constructor]
cls.add_constructor([])
## address.h (module 'network'): ns3::Address::Address(uint8_t type, uint8_t const * buffer, uint8_t len) [constructor]
cls.add_constructor([param('uint8_t', 'type'), param('uint8_t const *', 'buffer'), param('uint8_t', 'len')])
## address.h (module 'network'): ns3::Address::Address(ns3::Address const & address) [copy constructor]
cls.add_constructor([param('ns3::Address const &', 'address')])
## address.h (module 'network'): bool ns3::Address::CheckCompatible(uint8_t type, uint8_t len) const [member function]
cls.add_method('CheckCompatible',
'bool',
[param('uint8_t', 'type'), param('uint8_t', 'len')],
is_const=True)
## address.h (module 'network'): uint32_t ns3::Address::CopyAllFrom(uint8_t const * buffer, uint8_t len) [member function]
cls.add_method('CopyAllFrom',
'uint32_t',
[param('uint8_t const *', 'buffer'), param('uint8_t', 'len')])
## address.h (module 'network'): uint32_t ns3::Address::CopyAllTo(uint8_t * buffer, uint8_t len) const [member function]
cls.add_method('CopyAllTo',
'uint32_t',
[param('uint8_t *', 'buffer'), param('uint8_t', 'len')],
is_const=True)
## address.h (module 'network'): uint32_t ns3::Address::CopyFrom(uint8_t const * buffer, uint8_t len) [member function]
cls.add_method('CopyFrom',
'uint32_t',
[param('uint8_t const *', 'buffer'), param('uint8_t', 'len')])
## address.h (module 'network'): uint32_t ns3::Address::CopyTo(uint8_t * buffer) const [member function]
cls.add_method('CopyTo',
'uint32_t',
[param('uint8_t *', 'buffer')],
is_const=True)
## address.h (module 'network'): void ns3::Address::Deserialize(ns3::TagBuffer buffer) [member function]
cls.add_method('Deserialize',
'void',
[param('ns3::TagBuffer', 'buffer')])
## address.h (module 'network'): uint8_t ns3::Address::GetLength() const [member function]
cls.add_method('GetLength',
'uint8_t',
[],
is_const=True)
## address.h (module 'network'): uint32_t ns3::Address::GetSerializedSize() const [member function]
cls.add_method('GetSerializedSize',
'uint32_t',
[],
is_const=True)
## address.h (module 'network'): bool ns3::Address::IsInvalid() const [member function]
cls.add_method('IsInvalid',
'bool',
[],
is_const=True)
## address.h (module 'network'): bool ns3::Address::IsMatchingType(uint8_t type) const [member function]
cls.add_method('IsMatchingType',
'bool',
[param('uint8_t', 'type')],
is_const=True)
## address.h (module 'network'): static uint8_t ns3::Address::Register() [member function]
cls.add_method('Register',
'uint8_t',
[],
is_static=True)
## address.h (module 'network'): void ns3::Address::Serialize(ns3::TagBuffer buffer) const [member function]
cls.add_method('Serialize',
'void',
[param('ns3::TagBuffer', 'buffer')],
is_const=True)
return
def register_Ns3AttributeConstructionList_methods(root_module, cls):
## attribute-construction-list.h (module 'core'): ns3::AttributeConstructionList::AttributeConstructionList(ns3::AttributeConstructionList const & arg0) [copy constructor]
cls.add_constructor([param('ns3::AttributeConstructionList const &', 'arg0')])
## attribute-construction-list.h (module 'core'): ns3::AttributeConstructionList::AttributeConstructionList() [constructor]
cls.add_constructor([])
## attribute-construction-list.h (module 'core'): void ns3::AttributeConstructionList::Add(std::string name, ns3::Ptr<ns3::AttributeChecker const> checker, ns3::Ptr<ns3::AttributeValue> value) [member function]
cls.add_method('Add',
'void',
[param('std::string', 'name'), param('ns3::Ptr< ns3::AttributeChecker const >', 'checker'), param('ns3::Ptr< ns3::AttributeValue >', 'value')])
## attribute-construction-list.h (module 'core'): std::_List_const_iterator<ns3::AttributeConstructionList::Item> ns3::AttributeConstructionList::Begin() const [member function]
cls.add_method('Begin',
'std::_List_const_iterator< ns3::AttributeConstructionList::Item >',
[],
is_const=True)
## attribute-construction-list.h (module 'core'): std::_List_const_iterator<ns3::AttributeConstructionList::Item> ns3::AttributeConstructionList::End() const [member function]
cls.add_method('End',
'std::_List_const_iterator< ns3::AttributeConstructionList::Item >',
[],
is_const=True)
## attribute-construction-list.h (module 'core'): ns3::Ptr<ns3::AttributeValue> ns3::AttributeConstructionList::Find(ns3::Ptr<ns3::AttributeChecker const> checker) const [member function]
cls.add_method('Find',
'ns3::Ptr< ns3::AttributeValue >',
[param('ns3::Ptr< ns3::AttributeChecker const >', 'checker')],
is_const=True)
return
def register_Ns3AttributeConstructionListItem_methods(root_module, cls):
## attribute-construction-list.h (module 'core'): ns3::AttributeConstructionList::Item::Item() [constructor]
cls.add_constructor([])
## attribute-construction-list.h (module 'core'): ns3::AttributeConstructionList::Item::Item(ns3::AttributeConstructionList::Item const & arg0) [copy constructor]
cls.add_constructor([param('ns3::AttributeConstructionList::Item const &', 'arg0')])
## attribute-construction-list.h (module 'core'): ns3::AttributeConstructionList::Item::checker [variable]
cls.add_instance_attribute('checker', 'ns3::Ptr< ns3::AttributeChecker const >', is_const=False)
## attribute-construction-list.h (module 'core'): ns3::AttributeConstructionList::Item::name [variable]
cls.add_instance_attribute('name', 'std::string', is_const=False)
## attribute-construction-list.h (module 'core'): ns3::AttributeConstructionList::Item::value [variable]
cls.add_instance_attribute('value', 'ns3::Ptr< ns3::AttributeValue >', is_const=False)
return
def register_Ns3Buffer_methods(root_module, cls):
## buffer.h (module 'network'): ns3::Buffer::Buffer() [constructor]
cls.add_constructor([])
## buffer.h (module 'network'): ns3::Buffer::Buffer(uint32_t dataSize) [constructor]
cls.add_constructor([param('uint32_t', 'dataSize')])
## buffer.h (module 'network'): ns3::Buffer::Buffer(uint32_t dataSize, bool initialize) [constructor]
cls.add_constructor([param('uint32_t', 'dataSize'), param('bool', 'initialize')])
## buffer.h (module 'network'): ns3::Buffer::Buffer(ns3::Buffer const & o) [copy constructor]
cls.add_constructor([param('ns3::Buffer const &', 'o')])
## buffer.h (module 'network'): void ns3::Buffer::AddAtEnd(uint32_t end) [member function]
cls.add_method('AddAtEnd',
'void',
[param('uint32_t', 'end')])
## buffer.h (module 'network'): void ns3::Buffer::AddAtEnd(ns3::Buffer const & o) [member function]
cls.add_method('AddAtEnd',
'void',
[param('ns3::Buffer const &', 'o')])
## buffer.h (module 'network'): void ns3::Buffer::AddAtStart(uint32_t start) [member function]
cls.add_method('AddAtStart',
'void',
[param('uint32_t', 'start')])
## buffer.h (module 'network'): ns3::Buffer::Iterator ns3::Buffer::Begin() const [member function]
cls.add_method('Begin',
'ns3::Buffer::Iterator',
[],
is_const=True)
## buffer.h (module 'network'): void ns3::Buffer::CopyData(std::ostream * os, uint32_t size) const [member function]
cls.add_method('CopyData',
'void',
[param('std::ostream *', 'os'), param('uint32_t', 'size')],
is_const=True)
## buffer.h (module 'network'): uint32_t ns3::Buffer::CopyData(uint8_t * buffer, uint32_t size) const [member function]
cls.add_method('CopyData',
'uint32_t',
[param('uint8_t *', 'buffer'), param('uint32_t', 'size')],
is_const=True)
## buffer.h (module 'network'): ns3::Buffer ns3::Buffer::CreateFragment(uint32_t start, uint32_t length) const [member function]
cls.add_method('CreateFragment',
'ns3::Buffer',
[param('uint32_t', 'start'), param('uint32_t', 'length')],
is_const=True)
## buffer.h (module 'network'): uint32_t ns3::Buffer::Deserialize(uint8_t const * buffer, uint32_t size) [member function]
cls.add_method('Deserialize',
'uint32_t',
[param('uint8_t const *', 'buffer'), param('uint32_t', 'size')])
## buffer.h (module 'network'): ns3::Buffer::Iterator ns3::Buffer::End() const [member function]
cls.add_method('End',
'ns3::Buffer::Iterator',
[],
is_const=True)
## buffer.h (module 'network'): uint32_t ns3::Buffer::GetSerializedSize() const [member function]
cls.add_method('GetSerializedSize',
'uint32_t',
[],
is_const=True)
## buffer.h (module 'network'): uint32_t ns3::Buffer::GetSize() const [member function]
cls.add_method('GetSize',
'uint32_t',
[],
is_const=True)
## buffer.h (module 'network'): uint8_t const * ns3::Buffer::PeekData() const [member function]
cls.add_method('PeekData',
'uint8_t const *',
[],
is_const=True)
## buffer.h (module 'network'): void ns3::Buffer::RemoveAtEnd(uint32_t end) [member function]
cls.add_method('RemoveAtEnd',
'void',
[param('uint32_t', 'end')])
## buffer.h (module 'network'): void ns3::Buffer::RemoveAtStart(uint32_t start) [member function]
cls.add_method('RemoveAtStart',
'void',
[param('uint32_t', 'start')])
## buffer.h (module 'network'): uint32_t ns3::Buffer::Serialize(uint8_t * buffer, uint32_t maxSize) const [member function]
cls.add_method('Serialize',
'uint32_t',
[param('uint8_t *', 'buffer'), param('uint32_t', 'maxSize')],
is_const=True)
return
def register_Ns3BufferIterator_methods(root_module, cls):
## buffer.h (module 'network'): ns3::Buffer::Iterator::Iterator(ns3::Buffer::Iterator const & arg0) [copy constructor]
cls.add_constructor([param('ns3::Buffer::Iterator const &', 'arg0')])
## buffer.h (module 'network'): ns3::Buffer::Iterator::Iterator() [constructor]
cls.add_constructor([])
## buffer.h (module 'network'): uint16_t ns3::Buffer::Iterator::CalculateIpChecksum(uint16_t size) [member function]
cls.add_method('CalculateIpChecksum',
'uint16_t',
[param('uint16_t', 'size')])
## buffer.h (module 'network'): uint16_t ns3::Buffer::Iterator::CalculateIpChecksum(uint16_t size, uint32_t initialChecksum) [member function]
cls.add_method('CalculateIpChecksum',
'uint16_t',
[param('uint16_t', 'size'), param('uint32_t', 'initialChecksum')])
## buffer.h (module 'network'): uint32_t ns3::Buffer::Iterator::GetDistanceFrom(ns3::Buffer::Iterator const & o) const [member function]
cls.add_method('GetDistanceFrom',
'uint32_t',
[param('ns3::Buffer::Iterator const &', 'o')],
is_const=True)
## buffer.h (module 'network'): uint32_t ns3::Buffer::Iterator::GetRemainingSize() const [member function]
cls.add_method('GetRemainingSize',
'uint32_t',
[],
is_const=True)
## buffer.h (module 'network'): uint32_t ns3::Buffer::Iterator::GetSize() const [member function]
cls.add_method('GetSize',
'uint32_t',
[],
is_const=True)
## buffer.h (module 'network'): bool ns3::Buffer::Iterator::IsEnd() const [member function]
cls.add_method('IsEnd',
'bool',
[],
is_const=True)
## buffer.h (module 'network'): bool ns3::Buffer::Iterator::IsStart() const [member function]
cls.add_method('IsStart',
'bool',
[],
is_const=True)
## buffer.h (module 'network'): void ns3::Buffer::Iterator::Next() [member function]
cls.add_method('Next',
'void',
[])
## buffer.h (module 'network'): void ns3::Buffer::Iterator::Next(uint32_t delta) [member function]
cls.add_method('Next',
'void',
[param('uint32_t', 'delta')])
## buffer.h (module 'network'): uint8_t ns3::Buffer::Iterator::PeekU8() [member function]
cls.add_method('PeekU8',
'uint8_t',
[])
## buffer.h (module 'network'): void ns3::Buffer::Iterator::Prev() [member function]
cls.add_method('Prev',
'void',
[])
## buffer.h (module 'network'): void ns3::Buffer::Iterator::Prev(uint32_t delta) [member function]
cls.add_method('Prev',
'void',
[param('uint32_t', 'delta')])
## buffer.h (module 'network'): void ns3::Buffer::Iterator::Read(uint8_t * buffer, uint32_t size) [member function]
cls.add_method('Read',
'void',
[param('uint8_t *', 'buffer'), param('uint32_t', 'size')])
## buffer.h (module 'network'): void ns3::Buffer::Iterator::Read(ns3::Buffer::Iterator start, uint32_t size) [member function]
cls.add_method('Read',
'void',
[param('ns3::Buffer::Iterator', 'start'), param('uint32_t', 'size')])
## buffer.h (module 'network'): uint16_t ns3::Buffer::Iterator::ReadLsbtohU16() [member function]
cls.add_method('ReadLsbtohU16',
'uint16_t',
[])
## buffer.h (module 'network'): uint32_t ns3::Buffer::Iterator::ReadLsbtohU32() [member function]
cls.add_method('ReadLsbtohU32',
'uint32_t',
[])
## buffer.h (module 'network'): uint64_t ns3::Buffer::Iterator::ReadLsbtohU64() [member function]
cls.add_method('ReadLsbtohU64',
'uint64_t',
[])
## buffer.h (module 'network'): uint16_t ns3::Buffer::Iterator::ReadNtohU16() [member function]
cls.add_method('ReadNtohU16',
'uint16_t',
[])
## buffer.h (module 'network'): uint32_t ns3::Buffer::Iterator::ReadNtohU32() [member function]
cls.add_method('ReadNtohU32',
'uint32_t',
[])
## buffer.h (module 'network'): uint64_t ns3::Buffer::Iterator::ReadNtohU64() [member function]
cls.add_method('ReadNtohU64',
'uint64_t',
[])
## buffer.h (module 'network'): uint16_t ns3::Buffer::Iterator::ReadU16() [member function]
cls.add_method('ReadU16',
'uint16_t',
[])
## buffer.h (module 'network'): uint32_t ns3::Buffer::Iterator::ReadU32() [member function]
cls.add_method('ReadU32',
'uint32_t',
[])
## buffer.h (module 'network'): uint64_t ns3::Buffer::Iterator::ReadU64() [member function]
cls.add_method('ReadU64',
'uint64_t',
[])
## buffer.h (module 'network'): uint8_t ns3::Buffer::Iterator::ReadU8() [member function]
cls.add_method('ReadU8',
'uint8_t',
[])
## buffer.h (module 'network'): void ns3::Buffer::Iterator::Write(uint8_t const * buffer, uint32_t size) [member function]
cls.add_method('Write',
'void',
[param('uint8_t const *', 'buffer'), param('uint32_t', 'size')])
## buffer.h (module 'network'): void ns3::Buffer::Iterator::Write(ns3::Buffer::Iterator start, ns3::Buffer::Iterator end) [member function]
cls.add_method('Write',
'void',
[param('ns3::Buffer::Iterator', 'start'), param('ns3::Buffer::Iterator', 'end')])
## buffer.h (module 'network'): void ns3::Buffer::Iterator::WriteHtolsbU16(uint16_t data) [member function]
cls.add_method('WriteHtolsbU16',
'void',
[param('uint16_t', 'data')])
## buffer.h (module 'network'): void ns3::Buffer::Iterator::WriteHtolsbU32(uint32_t data) [member function]
cls.add_method('WriteHtolsbU32',
'void',
[param('uint32_t', 'data')])
## buffer.h (module 'network'): void ns3::Buffer::Iterator::WriteHtolsbU64(uint64_t data) [member function]
cls.add_method('WriteHtolsbU64',
'void',
[param('uint64_t', 'data')])
## buffer.h (module 'network'): void ns3::Buffer::Iterator::WriteHtonU16(uint16_t data) [member function]
cls.add_method('WriteHtonU16',
'void',
[param('uint16_t', 'data')])
## buffer.h (module 'network'): void ns3::Buffer::Iterator::WriteHtonU32(uint32_t data) [member function]
cls.add_method('WriteHtonU32',
'void',
[param('uint32_t', 'data')])
## buffer.h (module 'network'): void ns3::Buffer::Iterator::WriteHtonU64(uint64_t data) [member function]
cls.add_method('WriteHtonU64',
'void',
[param('uint64_t', 'data')])
## buffer.h (module 'network'): void ns3::Buffer::Iterator::WriteU16(uint16_t data) [member function]
cls.add_method('WriteU16',
'void',
[param('uint16_t', 'data')])
## buffer.h (module 'network'): void ns3::Buffer::Iterator::WriteU32(uint32_t data) [member function]
cls.add_method('WriteU32',
'void',
[param('uint32_t', 'data')])
## buffer.h (module 'network'): void ns3::Buffer::Iterator::WriteU64(uint64_t data) [member function]
cls.add_method('WriteU64',
'void',
[param('uint64_t', 'data')])
## buffer.h (module 'network'): void ns3::Buffer::Iterator::WriteU8(uint8_t data) [member function]
cls.add_method('WriteU8',
'void',
[param('uint8_t', 'data')])
## buffer.h (module 'network'): void ns3::Buffer::Iterator::WriteU8(uint8_t data, uint32_t len) [member function]
cls.add_method('WriteU8',
'void',
[param('uint8_t', 'data'), param('uint32_t', 'len')])
return
def register_Ns3ByteTagIterator_methods(root_module, cls):
## packet.h (module 'network'): ns3::ByteTagIterator::ByteTagIterator(ns3::ByteTagIterator const & arg0) [copy constructor]
cls.add_constructor([param('ns3::ByteTagIterator const &', 'arg0')])
## packet.h (module 'network'): bool ns3::ByteTagIterator::HasNext() const [member function]
cls.add_method('HasNext',
'bool',
[],
is_const=True)
## packet.h (module 'network'): ns3::ByteTagIterator::Item ns3::ByteTagIterator::Next() [member function]
cls.add_method('Next',
'ns3::ByteTagIterator::Item',
[])
return
def register_Ns3ByteTagIteratorItem_methods(root_module, cls):
## packet.h (module 'network'): ns3::ByteTagIterator::Item::Item(ns3::ByteTagIterator::Item const & arg0) [copy constructor]
cls.add_constructor([param('ns3::ByteTagIterator::Item const &', 'arg0')])
## packet.h (module 'network'): uint32_t ns3::ByteTagIterator::Item::GetEnd() const [member function]
cls.add_method('GetEnd',
'uint32_t',
[],
is_const=True)
## packet.h (module 'network'): uint32_t ns3::ByteTagIterator::Item::GetStart() const [member function]
cls.add_method('GetStart',
'uint32_t',
[],
is_const=True)
## packet.h (module 'network'): void ns3::ByteTagIterator::Item::GetTag(ns3::Tag & tag) const [member function]
cls.add_method('GetTag',
'void',
[param('ns3::Tag &', 'tag')],
is_const=True)
## packet.h (module 'network'): ns3::TypeId ns3::ByteTagIterator::Item::GetTypeId() const [member function]
cls.add_method('GetTypeId',
'ns3::TypeId',
[],
is_const=True)
return
def register_Ns3ByteTagList_methods(root_module, cls):
## byte-tag-list.h (module 'network'): ns3::ByteTagList::ByteTagList() [constructor]
cls.add_constructor([])
## byte-tag-list.h (module 'network'): ns3::ByteTagList::ByteTagList(ns3::ByteTagList const & o) [copy constructor]
cls.add_constructor([param('ns3::ByteTagList const &', 'o')])
## byte-tag-list.h (module 'network'): ns3::TagBuffer ns3::ByteTagList::Add(ns3::TypeId tid, uint32_t bufferSize, int32_t start, int32_t end) [member function]
cls.add_method('Add',
'ns3::TagBuffer',
[param('ns3::TypeId', 'tid'), param('uint32_t', 'bufferSize'), param('int32_t', 'start'), param('int32_t', 'end')])
## byte-tag-list.h (module 'network'): void ns3::ByteTagList::Add(ns3::ByteTagList const & o) [member function]
cls.add_method('Add',
'void',
[param('ns3::ByteTagList const &', 'o')])
## byte-tag-list.h (module 'network'): void ns3::ByteTagList::AddAtEnd(int32_t appendOffset) [member function]
cls.add_method('AddAtEnd',
'void',
[param('int32_t', 'appendOffset')])
## byte-tag-list.h (module 'network'): void ns3::ByteTagList::AddAtStart(int32_t prependOffset) [member function]
cls.add_method('AddAtStart',
'void',
[param('int32_t', 'prependOffset')])
## byte-tag-list.h (module 'network'): void ns3::ByteTagList::Adjust(int32_t adjustment) [member function]
cls.add_method('Adjust',
'void',
[param('int32_t', 'adjustment')])
## byte-tag-list.h (module 'network'): ns3::ByteTagList::Iterator ns3::ByteTagList::Begin(int32_t offsetStart, int32_t offsetEnd) const [member function]
cls.add_method('Begin',
'ns3::ByteTagList::Iterator',
[param('int32_t', 'offsetStart'), param('int32_t', 'offsetEnd')],
is_const=True)
## byte-tag-list.h (module 'network'): void ns3::ByteTagList::RemoveAll() [member function]
cls.add_method('RemoveAll',
'void',
[])
return
def register_Ns3ByteTagListIterator_methods(root_module, cls):
## byte-tag-list.h (module 'network'): ns3::ByteTagList::Iterator::Iterator(ns3::ByteTagList::Iterator const & arg0) [copy constructor]
cls.add_constructor([param('ns3::ByteTagList::Iterator const &', 'arg0')])
## byte-tag-list.h (module 'network'): uint32_t ns3::ByteTagList::Iterator::GetOffsetStart() const [member function]
cls.add_method('GetOffsetStart',
'uint32_t',
[],
is_const=True)
## byte-tag-list.h (module 'network'): bool ns3::ByteTagList::Iterator::HasNext() const [member function]
cls.add_method('HasNext',
'bool',
[],
is_const=True)
## byte-tag-list.h (module 'network'): ns3::ByteTagList::Iterator::Item ns3::ByteTagList::Iterator::Next() [member function]
cls.add_method('Next',
'ns3::ByteTagList::Iterator::Item',
[])
return
def register_Ns3ByteTagListIteratorItem_methods(root_module, cls):
## byte-tag-list.h (module 'network'): ns3::ByteTagList::Iterator::Item::Item(ns3::ByteTagList::Iterator::Item const & arg0) [copy constructor]
cls.add_constructor([param('ns3::ByteTagList::Iterator::Item const &', 'arg0')])
## byte-tag-list.h (module 'network'): ns3::ByteTagList::Iterator::Item::Item(ns3::TagBuffer buf) [constructor]
cls.add_constructor([param('ns3::TagBuffer', 'buf')])
## byte-tag-list.h (module 'network'): ns3::ByteTagList::Iterator::Item::buf [variable]
cls.add_instance_attribute('buf', 'ns3::TagBuffer', is_const=False)
## byte-tag-list.h (module 'network'): ns3::ByteTagList::Iterator::Item::end [variable]
cls.add_instance_attribute('end', 'int32_t', is_const=False)
## byte-tag-list.h (module 'network'): ns3::ByteTagList::Iterator::Item::size [variable]
cls.add_instance_attribute('size', 'uint32_t', is_const=False)
## byte-tag-list.h (module 'network'): ns3::ByteTagList::Iterator::Item::start [variable]
cls.add_instance_attribute('start', 'int32_t', is_const=False)
## byte-tag-list.h (module 'network'): ns3::ByteTagList::Iterator::Item::tid [variable]
cls.add_instance_attribute('tid', 'ns3::TypeId', is_const=False)
return
def register_Ns3CallbackBase_methods(root_module, cls):
## callback.h (module 'core'): ns3::CallbackBase::CallbackBase(ns3::CallbackBase const & arg0) [copy constructor]
cls.add_constructor([param('ns3::CallbackBase const &', 'arg0')])
## callback.h (module 'core'): ns3::CallbackBase::CallbackBase() [constructor]
cls.add_constructor([])
## callback.h (module 'core'): ns3::Ptr<ns3::CallbackImplBase> ns3::CallbackBase::GetImpl() const [member function]
cls.add_method('GetImpl',
'ns3::Ptr< ns3::CallbackImplBase >',
[],
is_const=True)
## callback.h (module 'core'): ns3::CallbackBase::CallbackBase(ns3::Ptr<ns3::CallbackImplBase> impl) [constructor]
cls.add_constructor([param('ns3::Ptr< ns3::CallbackImplBase >', 'impl')],
visibility='protected')
return
def register_Ns3EventId_methods(root_module, cls):
cls.add_binary_comparison_operator('!=')
cls.add_binary_comparison_operator('==')
## event-id.h (module 'core'): ns3::EventId::EventId(ns3::EventId const & arg0) [copy constructor]
cls.add_constructor([param('ns3::EventId const &', 'arg0')])
## event-id.h (module 'core'): ns3::EventId::EventId() [constructor]
cls.add_constructor([])
## event-id.h (module 'core'): ns3::EventId::EventId(ns3::Ptr<ns3::EventImpl> const & impl, uint64_t ts, uint32_t context, uint32_t uid) [constructor]
cls.add_constructor([param('ns3::Ptr< ns3::EventImpl > const &', 'impl'), param('uint64_t', 'ts'), param('uint32_t', 'context'), param('uint32_t', 'uid')])
## event-id.h (module 'core'): void ns3::EventId::Cancel() [member function]
cls.add_method('Cancel',
'void',
[])
## event-id.h (module 'core'): uint32_t ns3::EventId::GetContext() const [member function]
cls.add_method('GetContext',
'uint32_t',
[],
is_const=True)
## event-id.h (module 'core'): uint64_t ns3::EventId::GetTs() const [member function]
cls.add_method('GetTs',
'uint64_t',
[],
is_const=True)
## event-id.h (module 'core'): uint32_t ns3::EventId::GetUid() const [member function]
cls.add_method('GetUid',
'uint32_t',
[],
is_const=True)
## event-id.h (module 'core'): bool ns3::EventId::IsExpired() const [member function]
cls.add_method('IsExpired',
'bool',
[],
is_const=True)
## event-id.h (module 'core'): bool ns3::EventId::IsRunning() const [member function]
cls.add_method('IsRunning',
'bool',
[],
is_const=True)
## event-id.h (module 'core'): ns3::EventImpl * ns3::EventId::PeekEventImpl() const [member function]
cls.add_method('PeekEventImpl',
'ns3::EventImpl *',
[],
is_const=True)
return
def register_Ns3Hasher_methods(root_module, cls):
## hash.h (module 'core'): ns3::Hasher::Hasher(ns3::Hasher const & arg0) [copy constructor]
cls.add_constructor([param('ns3::Hasher const &', 'arg0')])
## hash.h (module 'core'): ns3::Hasher::Hasher() [constructor]
cls.add_constructor([])
## hash.h (module 'core'): ns3::Hasher::Hasher(ns3::Ptr<ns3::Hash::Implementation> hp) [constructor]
cls.add_constructor([param('ns3::Ptr< ns3::Hash::Implementation >', 'hp')])
## hash.h (module 'core'): uint32_t ns3::Hasher::GetHash32(char const * buffer, size_t const size) [member function]
cls.add_method('GetHash32',
'uint32_t',
[param('char const *', 'buffer'), param('size_t const', 'size')])
## hash.h (module 'core'): uint32_t ns3::Hasher::GetHash32(std::string const s) [member function]
cls.add_method('GetHash32',
'uint32_t',
[param('std::string const', 's')])
## hash.h (module 'core'): uint64_t ns3::Hasher::GetHash64(char const * buffer, size_t const size) [member function]
cls.add_method('GetHash64',
'uint64_t',
[param('char const *', 'buffer'), param('size_t const', 'size')])
## hash.h (module 'core'): uint64_t ns3::Hasher::GetHash64(std::string const s) [member function]
cls.add_method('GetHash64',
'uint64_t',
[param('std::string const', 's')])
## hash.h (module 'core'): ns3::Hasher & ns3::Hasher::clear() [member function]
cls.add_method('clear',
'ns3::Hasher &',
[])
return
def register_Ns3Inet6SocketAddress_methods(root_module, cls):
## inet6-socket-address.h (module 'network'): ns3::Inet6SocketAddress::Inet6SocketAddress(ns3::Inet6SocketAddress const & arg0) [copy constructor]
cls.add_constructor([param('ns3::Inet6SocketAddress const &', 'arg0')])
## inet6-socket-address.h (module 'network'): ns3::Inet6SocketAddress::Inet6SocketAddress(ns3::Ipv6Address ipv6, uint16_t port) [constructor]
cls.add_constructor([param('ns3::Ipv6Address', 'ipv6'), param('uint16_t', 'port')])
## inet6-socket-address.h (module 'network'): ns3::Inet6SocketAddress::Inet6SocketAddress(ns3::Ipv6Address ipv6) [constructor]
cls.add_constructor([param('ns3::Ipv6Address', 'ipv6')])
## inet6-socket-address.h (module 'network'): ns3::Inet6SocketAddress::Inet6SocketAddress(uint16_t port) [constructor]
cls.add_constructor([param('uint16_t', 'port')])
## inet6-socket-address.h (module 'network'): ns3::Inet6SocketAddress::Inet6SocketAddress(char const * ipv6, uint16_t port) [constructor]
cls.add_constructor([param('char const *', 'ipv6'), param('uint16_t', 'port')])
## inet6-socket-address.h (module 'network'): ns3::Inet6SocketAddress::Inet6SocketAddress(char const * ipv6) [constructor]
cls.add_constructor([param('char const *', 'ipv6')])
## inet6-socket-address.h (module 'network'): static ns3::Inet6SocketAddress ns3::Inet6SocketAddress::ConvertFrom(ns3::Address const & addr) [member function]
cls.add_method('ConvertFrom',
'ns3::Inet6SocketAddress',
[param('ns3::Address const &', 'addr')],
is_static=True)
## inet6-socket-address.h (module 'network'): ns3::Ipv6Address ns3::Inet6SocketAddress::GetIpv6() const [member function]
cls.add_method('GetIpv6',
'ns3::Ipv6Address',
[],
is_const=True)
## inet6-socket-address.h (module 'network'): uint16_t ns3::Inet6SocketAddress::GetPort() const [member function]
cls.add_method('GetPort',
'uint16_t',
[],
is_const=True)
## inet6-socket-address.h (module 'network'): static bool ns3::Inet6SocketAddress::IsMatchingType(ns3::Address const & addr) [member function]
cls.add_method('IsMatchingType',
'bool',
[param('ns3::Address const &', 'addr')],
is_static=True)
## inet6-socket-address.h (module 'network'): void ns3::Inet6SocketAddress::SetIpv6(ns3::Ipv6Address ipv6) [member function]
cls.add_method('SetIpv6',
'void',
[param('ns3::Ipv6Address', 'ipv6')])
## inet6-socket-address.h (module 'network'): void ns3::Inet6SocketAddress::SetPort(uint16_t port) [member function]
cls.add_method('SetPort',
'void',
[param('uint16_t', 'port')])
return
def register_Ns3InetSocketAddress_methods(root_module, cls):
## inet-socket-address.h (module 'network'): ns3::InetSocketAddress::InetSocketAddress(ns3::InetSocketAddress const & arg0) [copy constructor]
cls.add_constructor([param('ns3::InetSocketAddress const &', 'arg0')])
## inet-socket-address.h (module 'network'): ns3::InetSocketAddress::InetSocketAddress(ns3::Ipv4Address ipv4, uint16_t port) [constructor]
cls.add_constructor([param('ns3::Ipv4Address', 'ipv4'), param('uint16_t', 'port')])
## inet-socket-address.h (module 'network'): ns3::InetSocketAddress::InetSocketAddress(ns3::Ipv4Address ipv4) [constructor]
cls.add_constructor([param('ns3::Ipv4Address', 'ipv4')])
## inet-socket-address.h (module 'network'): ns3::InetSocketAddress::InetSocketAddress(uint16_t port) [constructor]
cls.add_constructor([param('uint16_t', 'port')])
## inet-socket-address.h (module 'network'): ns3::InetSocketAddress::InetSocketAddress(char const * ipv4, uint16_t port) [constructor]
cls.add_constructor([param('char const *', 'ipv4'), param('uint16_t', 'port')])
## inet-socket-address.h (module 'network'): ns3::InetSocketAddress::InetSocketAddress(char const * ipv4) [constructor]
cls.add_constructor([param('char const *', 'ipv4')])
## inet-socket-address.h (module 'network'): static ns3::InetSocketAddress ns3::InetSocketAddress::ConvertFrom(ns3::Address const & address) [member function]
cls.add_method('ConvertFrom',
'ns3::InetSocketAddress',
[param('ns3::Address const &', 'address')],
is_static=True)
## inet-socket-address.h (module 'network'): ns3::Ipv4Address ns3::InetSocketAddress::GetIpv4() const [member function]
cls.add_method('GetIpv4',
'ns3::Ipv4Address',
[],
is_const=True)
## inet-socket-address.h (module 'network'): uint16_t ns3::InetSocketAddress::GetPort() const [member function]
cls.add_method('GetPort',
'uint16_t',
[],
is_const=True)
## inet-socket-address.h (module 'network'): uint8_t ns3::InetSocketAddress::GetTos() const [member function]
cls.add_method('GetTos',
'uint8_t',
[],
is_const=True)
## inet-socket-address.h (module 'network'): static bool ns3::InetSocketAddress::IsMatchingType(ns3::Address const & address) [member function]
cls.add_method('IsMatchingType',
'bool',
[param('ns3::Address const &', 'address')],
is_static=True)
## inet-socket-address.h (module 'network'): void ns3::InetSocketAddress::SetIpv4(ns3::Ipv4Address address) [member function]
cls.add_method('SetIpv4',
'void',
[param('ns3::Ipv4Address', 'address')])
## inet-socket-address.h (module 'network'): void ns3::InetSocketAddress::SetPort(uint16_t port) [member function]
cls.add_method('SetPort',
'void',
[param('uint16_t', 'port')])
## inet-socket-address.h (module 'network'): void ns3::InetSocketAddress::SetTos(uint8_t tos) [member function]
cls.add_method('SetTos',
'void',
[param('uint8_t', 'tos')])
return
def register_Ns3Ipv4Address_methods(root_module, cls):
cls.add_binary_comparison_operator('<')
cls.add_binary_comparison_operator('!=')
cls.add_output_stream_operator()
cls.add_binary_comparison_operator('==')
## ipv4-address.h (module 'network'): ns3::Ipv4Address::Ipv4Address(ns3::Ipv4Address const & arg0) [copy constructor]
cls.add_constructor([param('ns3::Ipv4Address const &', 'arg0')])
## ipv4-address.h (module 'network'): ns3::Ipv4Address::Ipv4Address() [constructor]
cls.add_constructor([])
## ipv4-address.h (module 'network'): ns3::Ipv4Address::Ipv4Address(uint32_t address) [constructor]
cls.add_constructor([param('uint32_t', 'address')])
## ipv4-address.h (module 'network'): ns3::Ipv4Address::Ipv4Address(char const * address) [constructor]
cls.add_constructor([param('char const *', 'address')])
## ipv4-address.h (module 'network'): ns3::Ipv4Address ns3::Ipv4Address::CombineMask(ns3::Ipv4Mask const & mask) const [member function]
cls.add_method('CombineMask',
'ns3::Ipv4Address',
[param('ns3::Ipv4Mask const &', 'mask')],
is_const=True)
## ipv4-address.h (module 'network'): static ns3::Ipv4Address ns3::Ipv4Address::ConvertFrom(ns3::Address const & address) [member function]
cls.add_method('ConvertFrom',
'ns3::Ipv4Address',
[param('ns3::Address const &', 'address')],
is_static=True)
## ipv4-address.h (module 'network'): static ns3::Ipv4Address ns3::Ipv4Address::Deserialize(uint8_t const * buf) [member function]
cls.add_method('Deserialize',
'ns3::Ipv4Address',
[param('uint8_t const *', 'buf')],
is_static=True)
## ipv4-address.h (module 'network'): uint32_t ns3::Ipv4Address::Get() const [member function]
cls.add_method('Get',
'uint32_t',
[],
is_const=True)
## ipv4-address.h (module 'network'): static ns3::Ipv4Address ns3::Ipv4Address::GetAny() [member function]
cls.add_method('GetAny',
'ns3::Ipv4Address',
[],
is_static=True)
## ipv4-address.h (module 'network'): static ns3::Ipv4Address ns3::Ipv4Address::GetBroadcast() [member function]
cls.add_method('GetBroadcast',
'ns3::Ipv4Address',
[],
is_static=True)
## ipv4-address.h (module 'network'): static ns3::Ipv4Address ns3::Ipv4Address::GetLoopback() [member function]
cls.add_method('GetLoopback',
'ns3::Ipv4Address',
[],
is_static=True)
## ipv4-address.h (module 'network'): ns3::Ipv4Address ns3::Ipv4Address::GetSubnetDirectedBroadcast(ns3::Ipv4Mask const & mask) const [member function]
cls.add_method('GetSubnetDirectedBroadcast',
'ns3::Ipv4Address',
[param('ns3::Ipv4Mask const &', 'mask')],
is_const=True)
## ipv4-address.h (module 'network'): static ns3::Ipv4Address ns3::Ipv4Address::GetZero() [member function]
cls.add_method('GetZero',
'ns3::Ipv4Address',
[],
is_static=True)
## ipv4-address.h (module 'network'): bool ns3::Ipv4Address::IsAny() const [member function]
cls.add_method('IsAny',
'bool',
[],
is_const=True)
## ipv4-address.h (module 'network'): bool ns3::Ipv4Address::IsBroadcast() const [member function]
cls.add_method('IsBroadcast',
'bool',
[],
is_const=True)
## ipv4-address.h (module 'network'): bool ns3::Ipv4Address::IsEqual(ns3::Ipv4Address const & other) const [member function]
cls.add_method('IsEqual',
'bool',
[param('ns3::Ipv4Address const &', 'other')],
is_const=True)
## ipv4-address.h (module 'network'): bool ns3::Ipv4Address::IsLocalMulticast() const [member function]
cls.add_method('IsLocalMulticast',
'bool',
[],
is_const=True)
## ipv4-address.h (module 'network'): bool ns3::Ipv4Address::IsLocalhost() const [member function]
cls.add_method('IsLocalhost',
'bool',
[],
is_const=True)
## ipv4-address.h (module 'network'): static bool ns3::Ipv4Address::IsMatchingType(ns3::Address const & address) [member function]
cls.add_method('IsMatchingType',
'bool',
[param('ns3::Address const &', 'address')],
is_static=True)
## ipv4-address.h (module 'network'): bool ns3::Ipv4Address::IsMulticast() const [member function]
cls.add_method('IsMulticast',
'bool',
[],
is_const=True)
## ipv4-address.h (module 'network'): bool ns3::Ipv4Address::IsSubnetDirectedBroadcast(ns3::Ipv4Mask const & mask) const [member function]
cls.add_method('IsSubnetDirectedBroadcast',
'bool',
[param('ns3::Ipv4Mask const &', 'mask')],
is_const=True)
## ipv4-address.h (module 'network'): void ns3::Ipv4Address::Print(std::ostream & os) const [member function]
cls.add_method('Print',
'void',
[param('std::ostream &', 'os')],
is_const=True)
## ipv4-address.h (module 'network'): void ns3::Ipv4Address::Serialize(uint8_t * buf) const [member function]
cls.add_method('Serialize',
'void',
[param('uint8_t *', 'buf')],
is_const=True)
## ipv4-address.h (module 'network'): void ns3::Ipv4Address::Set(uint32_t address) [member function]
cls.add_method('Set',
'void',
[param('uint32_t', 'address')])
## ipv4-address.h (module 'network'): void ns3::Ipv4Address::Set(char const * address) [member function]
cls.add_method('Set',
'void',
[param('char const *', 'address')])
return
def register_Ns3Ipv4InterfaceAddress_methods(root_module, cls):
cls.add_binary_comparison_operator('!=')
cls.add_output_stream_operator()
cls.add_binary_comparison_operator('==')
## ipv4-interface-address.h (module 'internet'): ns3::Ipv4InterfaceAddress::Ipv4InterfaceAddress() [constructor]
cls.add_constructor([])
## ipv4-interface-address.h (module 'internet'): ns3::Ipv4InterfaceAddress::Ipv4InterfaceAddress(ns3::Ipv4Address local, ns3::Ipv4Mask mask) [constructor]
cls.add_constructor([param('ns3::Ipv4Address', 'local'), param('ns3::Ipv4Mask', 'mask')])
## ipv4-interface-address.h (module 'internet'): ns3::Ipv4InterfaceAddress::Ipv4InterfaceAddress(ns3::Ipv4InterfaceAddress const & o) [copy constructor]
cls.add_constructor([param('ns3::Ipv4InterfaceAddress const &', 'o')])
## ipv4-interface-address.h (module 'internet'): ns3::Ipv4Address ns3::Ipv4InterfaceAddress::GetBroadcast() const [member function]
cls.add_method('GetBroadcast',
'ns3::Ipv4Address',
[],
is_const=True)
## ipv4-interface-address.h (module 'internet'): ns3::Ipv4Address ns3::Ipv4InterfaceAddress::GetLocal() const [member function]
cls.add_method('GetLocal',
'ns3::Ipv4Address',
[],
is_const=True)
## ipv4-interface-address.h (module 'internet'): ns3::Ipv4Mask ns3::Ipv4InterfaceAddress::GetMask() const [member function]
cls.add_method('GetMask',
'ns3::Ipv4Mask',
[],
is_const=True)
## ipv4-interface-address.h (module 'internet'): ns3::Ipv4InterfaceAddress::InterfaceAddressScope_e ns3::Ipv4InterfaceAddress::GetScope() const [member function]
cls.add_method('GetScope',
'ns3::Ipv4InterfaceAddress::InterfaceAddressScope_e',
[],
is_const=True)
## ipv4-interface-address.h (module 'internet'): bool ns3::Ipv4InterfaceAddress::IsSecondary() const [member function]
cls.add_method('IsSecondary',
'bool',
[],
is_const=True)
## ipv4-interface-address.h (module 'internet'): void ns3::Ipv4InterfaceAddress::SetBroadcast(ns3::Ipv4Address broadcast) [member function]
cls.add_method('SetBroadcast',
'void',
[param('ns3::Ipv4Address', 'broadcast')])
## ipv4-interface-address.h (module 'internet'): void ns3::Ipv4InterfaceAddress::SetLocal(ns3::Ipv4Address local) [member function]
cls.add_method('SetLocal',
'void',
[param('ns3::Ipv4Address', 'local')])
## ipv4-interface-address.h (module 'internet'): void ns3::Ipv4InterfaceAddress::SetMask(ns3::Ipv4Mask mask) [member function]
cls.add_method('SetMask',
'void',
[param('ns3::Ipv4Mask', 'mask')])
## ipv4-interface-address.h (module 'internet'): void ns3::Ipv4InterfaceAddress::SetPrimary() [member function]
cls.add_method('SetPrimary',
'void',
[])
## ipv4-interface-address.h (module 'internet'): void ns3::Ipv4InterfaceAddress::SetScope(ns3::Ipv4InterfaceAddress::InterfaceAddressScope_e scope) [member function]
cls.add_method('SetScope',
'void',
[param('ns3::Ipv4InterfaceAddress::InterfaceAddressScope_e', 'scope')])
## ipv4-interface-address.h (module 'internet'): void ns3::Ipv4InterfaceAddress::SetSecondary() [member function]
cls.add_method('SetSecondary',
'void',
[])
return
def register_Ns3Ipv4Mask_methods(root_module, cls):
cls.add_binary_comparison_operator('!=')
cls.add_output_stream_operator()
cls.add_binary_comparison_operator('==')
## ipv4-address.h (module 'network'): ns3::Ipv4Mask::Ipv4Mask(ns3::Ipv4Mask const & arg0) [copy constructor]
cls.add_constructor([param('ns3::Ipv4Mask const &', 'arg0')])
## ipv4-address.h (module 'network'): ns3::Ipv4Mask::Ipv4Mask() [constructor]
cls.add_constructor([])
## ipv4-address.h (module 'network'): ns3::Ipv4Mask::Ipv4Mask(uint32_t mask) [constructor]
cls.add_constructor([param('uint32_t', 'mask')])
## ipv4-address.h (module 'network'): ns3::Ipv4Mask::Ipv4Mask(char const * mask) [constructor]
cls.add_constructor([param('char const *', 'mask')])
## ipv4-address.h (module 'network'): uint32_t ns3::Ipv4Mask::Get() const [member function]
cls.add_method('Get',
'uint32_t',
[],
is_const=True)
## ipv4-address.h (module 'network'): uint32_t ns3::Ipv4Mask::GetInverse() const [member function]
cls.add_method('GetInverse',
'uint32_t',
[],
is_const=True)
## ipv4-address.h (module 'network'): static ns3::Ipv4Mask ns3::Ipv4Mask::GetLoopback() [member function]
cls.add_method('GetLoopback',
'ns3::Ipv4Mask',
[],
is_static=True)
## ipv4-address.h (module 'network'): static ns3::Ipv4Mask ns3::Ipv4Mask::GetOnes() [member function]
cls.add_method('GetOnes',
'ns3::Ipv4Mask',
[],
is_static=True)
## ipv4-address.h (module 'network'): uint16_t ns3::Ipv4Mask::GetPrefixLength() const [member function]
cls.add_method('GetPrefixLength',
'uint16_t',
[],
is_const=True)
## ipv4-address.h (module 'network'): static ns3::Ipv4Mask ns3::Ipv4Mask::GetZero() [member function]
cls.add_method('GetZero',
'ns3::Ipv4Mask',
[],
is_static=True)
## ipv4-address.h (module 'network'): bool ns3::Ipv4Mask::IsEqual(ns3::Ipv4Mask other) const [member function]
cls.add_method('IsEqual',
'bool',
[param('ns3::Ipv4Mask', 'other')],
is_const=True)
## ipv4-address.h (module 'network'): bool ns3::Ipv4Mask::IsMatch(ns3::Ipv4Address a, ns3::Ipv4Address b) const [member function]
cls.add_method('IsMatch',
'bool',
[param('ns3::Ipv4Address', 'a'), param('ns3::Ipv4Address', 'b')],
is_const=True)
## ipv4-address.h (module 'network'): void ns3::Ipv4Mask::Print(std::ostream & os) const [member function]
cls.add_method('Print',
'void',
[param('std::ostream &', 'os')],
is_const=True)
## ipv4-address.h (module 'network'): void ns3::Ipv4Mask::Set(uint32_t mask) [member function]
cls.add_method('Set',
'void',
[param('uint32_t', 'mask')])
return
def register_Ns3Ipv6Address_methods(root_module, cls):
cls.add_binary_comparison_operator('<')
cls.add_binary_comparison_operator('!=')
cls.add_output_stream_operator()
cls.add_binary_comparison_operator('==')
## ipv6-address.h (module 'network'): ns3::Ipv6Address::Ipv6Address() [constructor]
cls.add_constructor([])
## ipv6-address.h (module 'network'): ns3::Ipv6Address::Ipv6Address(char const * address) [constructor]
cls.add_constructor([param('char const *', 'address')])
## ipv6-address.h (module 'network'): ns3::Ipv6Address::Ipv6Address(uint8_t * address) [constructor]
cls.add_constructor([param('uint8_t *', 'address')])
## ipv6-address.h (module 'network'): ns3::Ipv6Address::Ipv6Address(ns3::Ipv6Address const & addr) [copy constructor]
cls.add_constructor([param('ns3::Ipv6Address const &', 'addr')])
## ipv6-address.h (module 'network'): ns3::Ipv6Address::Ipv6Address(ns3::Ipv6Address const * addr) [constructor]
cls.add_constructor([param('ns3::Ipv6Address const *', 'addr')])
## ipv6-address.h (module 'network'): ns3::Ipv6Address ns3::Ipv6Address::CombinePrefix(ns3::Ipv6Prefix const & prefix) [member function]
cls.add_method('CombinePrefix',
'ns3::Ipv6Address',
[param('ns3::Ipv6Prefix const &', 'prefix')])
## ipv6-address.h (module 'network'): static ns3::Ipv6Address ns3::Ipv6Address::ConvertFrom(ns3::Address const & address) [member function]
cls.add_method('ConvertFrom',
'ns3::Ipv6Address',
[param('ns3::Address const &', 'address')],
is_static=True)
## ipv6-address.h (module 'network'): static ns3::Ipv6Address ns3::Ipv6Address::Deserialize(uint8_t const * buf) [member function]
cls.add_method('Deserialize',
'ns3::Ipv6Address',
[param('uint8_t const *', 'buf')],
is_static=True)
## ipv6-address.h (module 'network'): static ns3::Ipv6Address ns3::Ipv6Address::GetAllHostsMulticast() [member function]
cls.add_method('GetAllHostsMulticast',
'ns3::Ipv6Address',
[],
is_static=True)
## ipv6-address.h (module 'network'): static ns3::Ipv6Address ns3::Ipv6Address::GetAllNodesMulticast() [member function]
cls.add_method('GetAllNodesMulticast',
'ns3::Ipv6Address',
[],
is_static=True)
## ipv6-address.h (module 'network'): static ns3::Ipv6Address ns3::Ipv6Address::GetAllRoutersMulticast() [member function]
cls.add_method('GetAllRoutersMulticast',
'ns3::Ipv6Address',
[],
is_static=True)
## ipv6-address.h (module 'network'): static ns3::Ipv6Address ns3::Ipv6Address::GetAny() [member function]
cls.add_method('GetAny',
'ns3::Ipv6Address',
[],
is_static=True)
## ipv6-address.h (module 'network'): void ns3::Ipv6Address::GetBytes(uint8_t * buf) const [member function]
cls.add_method('GetBytes',
'void',
[param('uint8_t *', 'buf')],
is_const=True)
## ipv6-address.h (module 'network'): ns3::Ipv4Address ns3::Ipv6Address::GetIpv4MappedAddress() const [member function]
cls.add_method('GetIpv4MappedAddress',
'ns3::Ipv4Address',
[],
is_const=True)
## ipv6-address.h (module 'network'): static ns3::Ipv6Address ns3::Ipv6Address::GetLoopback() [member function]
cls.add_method('GetLoopback',
'ns3::Ipv6Address',
[],
is_static=True)
## ipv6-address.h (module 'network'): static ns3::Ipv6Address ns3::Ipv6Address::GetOnes() [member function]
cls.add_method('GetOnes',
'ns3::Ipv6Address',
[],
is_static=True)
## ipv6-address.h (module 'network'): static ns3::Ipv6Address ns3::Ipv6Address::GetZero() [member function]
cls.add_method('GetZero',
'ns3::Ipv6Address',
[],
is_static=True)
## ipv6-address.h (module 'network'): bool ns3::Ipv6Address::IsAllHostsMulticast() const [member function]
cls.add_method('IsAllHostsMulticast',
'bool',
[],
deprecated=True, is_const=True)
## ipv6-address.h (module 'network'): bool ns3::Ipv6Address::IsAllNodesMulticast() const [member function]
cls.add_method('IsAllNodesMulticast',
'bool',
[],
is_const=True)
## ipv6-address.h (module 'network'): bool ns3::Ipv6Address::IsAllRoutersMulticast() const [member function]
cls.add_method('IsAllRoutersMulticast',
'bool',
[],
is_const=True)
## ipv6-address.h (module 'network'): bool ns3::Ipv6Address::IsAny() const [member function]
cls.add_method('IsAny',
'bool',
[],
is_const=True)
## ipv6-address.h (module 'network'): bool ns3::Ipv6Address::IsDocumentation() const [member function]
cls.add_method('IsDocumentation',
'bool',
[],
is_const=True)
## ipv6-address.h (module 'network'): bool ns3::Ipv6Address::IsEqual(ns3::Ipv6Address const & other) const [member function]
cls.add_method('IsEqual',
'bool',
[param('ns3::Ipv6Address const &', 'other')],
is_const=True)
## ipv6-address.h (module 'network'): bool ns3::Ipv6Address::IsIpv4MappedAddress() const [member function]
cls.add_method('IsIpv4MappedAddress',
'bool',
[],
is_const=True)
## ipv6-address.h (module 'network'): bool ns3::Ipv6Address::IsLinkLocal() const [member function]
cls.add_method('IsLinkLocal',
'bool',
[],
is_const=True)
## ipv6-address.h (module 'network'): bool ns3::Ipv6Address::IsLinkLocalMulticast() const [member function]
cls.add_method('IsLinkLocalMulticast',
'bool',
[],
is_const=True)
## ipv6-address.h (module 'network'): bool ns3::Ipv6Address::IsLocalhost() const [member function]
cls.add_method('IsLocalhost',
'bool',
[],
is_const=True)
## ipv6-address.h (module 'network'): static bool ns3::Ipv6Address::IsMatchingType(ns3::Address const & address) [member function]
cls.add_method('IsMatchingType',
'bool',
[param('ns3::Address const &', 'address')],
is_static=True)
## ipv6-address.h (module 'network'): bool ns3::Ipv6Address::IsMulticast() const [member function]
cls.add_method('IsMulticast',
'bool',
[],
is_const=True)
## ipv6-address.h (module 'network'): bool ns3::Ipv6Address::IsSolicitedMulticast() const [member function]
cls.add_method('IsSolicitedMulticast',
'bool',
[],
is_const=True)
## ipv6-address.h (module 'network'): static ns3::Ipv6Address ns3::Ipv6Address::MakeAutoconfiguredAddress(ns3::Mac16Address addr, ns3::Ipv6Address prefix) [member function]
cls.add_method('MakeAutoconfiguredAddress',
'ns3::Ipv6Address',
[param('ns3::Mac16Address', 'addr'), param('ns3::Ipv6Address', 'prefix')],
is_static=True)
## ipv6-address.h (module 'network'): static ns3::Ipv6Address ns3::Ipv6Address::MakeAutoconfiguredAddress(ns3::Mac48Address addr, ns3::Ipv6Address prefix) [member function]
cls.add_method('MakeAutoconfiguredAddress',
'ns3::Ipv6Address',
[param('ns3::Mac48Address', 'addr'), param('ns3::Ipv6Address', 'prefix')],
is_static=True)
## ipv6-address.h (module 'network'): static ns3::Ipv6Address ns3::Ipv6Address::MakeAutoconfiguredAddress(ns3::Mac64Address addr, ns3::Ipv6Address prefix) [member function]
cls.add_method('MakeAutoconfiguredAddress',
'ns3::Ipv6Address',
[param('ns3::Mac64Address', 'addr'), param('ns3::Ipv6Address', 'prefix')],
is_static=True)
## ipv6-address.h (module 'network'): static ns3::Ipv6Address ns3::Ipv6Address::MakeAutoconfiguredLinkLocalAddress(ns3::Mac16Address mac) [member function]
cls.add_method('MakeAutoconfiguredLinkLocalAddress',
'ns3::Ipv6Address',
[param('ns3::Mac16Address', 'mac')],
is_static=True)
## ipv6-address.h (module 'network'): static ns3::Ipv6Address ns3::Ipv6Address::MakeAutoconfiguredLinkLocalAddress(ns3::Mac48Address mac) [member function]
cls.add_method('MakeAutoconfiguredLinkLocalAddress',
'ns3::Ipv6Address',
[param('ns3::Mac48Address', 'mac')],
is_static=True)
## ipv6-address.h (module 'network'): static ns3::Ipv6Address ns3::Ipv6Address::MakeAutoconfiguredLinkLocalAddress(ns3::Mac64Address mac) [member function]
cls.add_method('MakeAutoconfiguredLinkLocalAddress',
'ns3::Ipv6Address',
[param('ns3::Mac64Address', 'mac')],
is_static=True)
## ipv6-address.h (module 'network'): static ns3::Ipv6Address ns3::Ipv6Address::MakeIpv4MappedAddress(ns3::Ipv4Address addr) [member function]
cls.add_method('MakeIpv4MappedAddress',
'ns3::Ipv6Address',
[param('ns3::Ipv4Address', 'addr')],
is_static=True)
## ipv6-address.h (module 'network'): static ns3::Ipv6Address ns3::Ipv6Address::MakeSolicitedAddress(ns3::Ipv6Address addr) [member function]
cls.add_method('MakeSolicitedAddress',
'ns3::Ipv6Address',
[param('ns3::Ipv6Address', 'addr')],
is_static=True)
## ipv6-address.h (module 'network'): void ns3::Ipv6Address::Print(std::ostream & os) const [member function]
cls.add_method('Print',
'void',
[param('std::ostream &', 'os')],
is_const=True)
## ipv6-address.h (module 'network'): void ns3::Ipv6Address::Serialize(uint8_t * buf) const [member function]
cls.add_method('Serialize',
'void',
[param('uint8_t *', 'buf')],
is_const=True)
## ipv6-address.h (module 'network'): void ns3::Ipv6Address::Set(char const * address) [member function]
cls.add_method('Set',
'void',
[param('char const *', 'address')])
## ipv6-address.h (module 'network'): void ns3::Ipv6Address::Set(uint8_t * address) [member function]
cls.add_method('Set',
'void',
[param('uint8_t *', 'address')])
return
def register_Ns3Ipv6Prefix_methods(root_module, cls):
cls.add_binary_comparison_operator('!=')
cls.add_output_stream_operator()
cls.add_binary_comparison_operator('==')
## ipv6-address.h (module 'network'): ns3::Ipv6Prefix::Ipv6Prefix() [constructor]
cls.add_constructor([])
## ipv6-address.h (module 'network'): ns3::Ipv6Prefix::Ipv6Prefix(uint8_t * prefix) [constructor]
cls.add_constructor([param('uint8_t *', 'prefix')])
## ipv6-address.h (module 'network'): ns3::Ipv6Prefix::Ipv6Prefix(char const * prefix) [constructor]
cls.add_constructor([param('char const *', 'prefix')])
## ipv6-address.h (module 'network'): ns3::Ipv6Prefix::Ipv6Prefix(uint8_t prefix) [constructor]
cls.add_constructor([param('uint8_t', 'prefix')])
## ipv6-address.h (module 'network'): ns3::Ipv6Prefix::Ipv6Prefix(ns3::Ipv6Prefix const & prefix) [copy constructor]
cls.add_constructor([param('ns3::Ipv6Prefix const &', 'prefix')])
## ipv6-address.h (module 'network'): ns3::Ipv6Prefix::Ipv6Prefix(ns3::Ipv6Prefix const * prefix) [constructor]
cls.add_constructor([param('ns3::Ipv6Prefix const *', 'prefix')])
## ipv6-address.h (module 'network'): void ns3::Ipv6Prefix::GetBytes(uint8_t * buf) const [member function]
cls.add_method('GetBytes',
'void',
[param('uint8_t *', 'buf')],
is_const=True)
## ipv6-address.h (module 'network'): static ns3::Ipv6Prefix ns3::Ipv6Prefix::GetLoopback() [member function]
cls.add_method('GetLoopback',
'ns3::Ipv6Prefix',
[],
is_static=True)
## ipv6-address.h (module 'network'): static ns3::Ipv6Prefix ns3::Ipv6Prefix::GetOnes() [member function]
cls.add_method('GetOnes',
'ns3::Ipv6Prefix',
[],
is_static=True)
## ipv6-address.h (module 'network'): uint8_t ns3::Ipv6Prefix::GetPrefixLength() const [member function]
cls.add_method('GetPrefixLength',
'uint8_t',
[],
is_const=True)
## ipv6-address.h (module 'network'): static ns3::Ipv6Prefix ns3::Ipv6Prefix::GetZero() [member function]
cls.add_method('GetZero',
'ns3::Ipv6Prefix',
[],
is_static=True)
## ipv6-address.h (module 'network'): bool ns3::Ipv6Prefix::IsEqual(ns3::Ipv6Prefix const & other) const [member function]
cls.add_method('IsEqual',
'bool',
[param('ns3::Ipv6Prefix const &', 'other')],
is_const=True)
## ipv6-address.h (module 'network'): bool ns3::Ipv6Prefix::IsMatch(ns3::Ipv6Address a, ns3::Ipv6Address b) const [member function]
cls.add_method('IsMatch',
'bool',
[param('ns3::Ipv6Address', 'a'), param('ns3::Ipv6Address', 'b')],
is_const=True)
## ipv6-address.h (module 'network'): void ns3::Ipv6Prefix::Print(std::ostream & os) const [member function]
cls.add_method('Print',
'void',
[param('std::ostream &', 'os')],
is_const=True)
return
def register_Ns3Mac48Address_methods(root_module, cls):
cls.add_binary_comparison_operator('<')
cls.add_binary_comparison_operator('!=')
cls.add_output_stream_operator()
cls.add_binary_comparison_operator('==')
## mac48-address.h (module 'network'): ns3::Mac48Address::Mac48Address(ns3::Mac48Address const & arg0) [copy constructor]
cls.add_constructor([param('ns3::Mac48Address const &', 'arg0')])
## mac48-address.h (module 'network'): ns3::Mac48Address::Mac48Address() [constructor]
cls.add_constructor([])
## mac48-address.h (module 'network'): ns3::Mac48Address::Mac48Address(char const * str) [constructor]
cls.add_constructor([param('char const *', 'str')])
## mac48-address.h (module 'network'): static ns3::Mac48Address ns3::Mac48Address::Allocate() [member function]
cls.add_method('Allocate',
'ns3::Mac48Address',
[],
is_static=True)
## mac48-address.h (module 'network'): static ns3::Mac48Address ns3::Mac48Address::ConvertFrom(ns3::Address const & address) [member function]
cls.add_method('ConvertFrom',
'ns3::Mac48Address',
[param('ns3::Address const &', 'address')],
is_static=True)
## mac48-address.h (module 'network'): void ns3::Mac48Address::CopyFrom(uint8_t const * buffer) [member function]
cls.add_method('CopyFrom',
'void',
[param('uint8_t const *', 'buffer')])
## mac48-address.h (module 'network'): void ns3::Mac48Address::CopyTo(uint8_t * buffer) const [member function]
cls.add_method('CopyTo',
'void',
[param('uint8_t *', 'buffer')],
is_const=True)
## mac48-address.h (module 'network'): static ns3::Mac48Address ns3::Mac48Address::GetBroadcast() [member function]
cls.add_method('GetBroadcast',
'ns3::Mac48Address',
[],
is_static=True)
## mac48-address.h (module 'network'): static ns3::Mac48Address ns3::Mac48Address::GetMulticast(ns3::Ipv4Address address) [member function]
cls.add_method('GetMulticast',
'ns3::Mac48Address',
[param('ns3::Ipv4Address', 'address')],
is_static=True)
## mac48-address.h (module 'network'): static ns3::Mac48Address ns3::Mac48Address::GetMulticast(ns3::Ipv6Address address) [member function]
cls.add_method('GetMulticast',
'ns3::Mac48Address',
[param('ns3::Ipv6Address', 'address')],
is_static=True)
## mac48-address.h (module 'network'): static ns3::Mac48Address ns3::Mac48Address::GetMulticast6Prefix() [member function]
cls.add_method('GetMulticast6Prefix',
'ns3::Mac48Address',
[],
is_static=True)
## mac48-address.h (module 'network'): static ns3::Mac48Address ns3::Mac48Address::GetMulticastPrefix() [member function]
cls.add_method('GetMulticastPrefix',
'ns3::Mac48Address',
[],
is_static=True)
## mac48-address.h (module 'network'): bool ns3::Mac48Address::IsBroadcast() const [member function]
cls.add_method('IsBroadcast',
'bool',
[],
is_const=True)
## mac48-address.h (module 'network'): bool ns3::Mac48Address::IsGroup() const [member function]
cls.add_method('IsGroup',
'bool',
[],
is_const=True)
## mac48-address.h (module 'network'): static bool ns3::Mac48Address::IsMatchingType(ns3::Address const & address) [member function]
cls.add_method('IsMatchingType',
'bool',
[param('ns3::Address const &', 'address')],
is_static=True)
return
def register_Ns3ObjectBase_methods(root_module, cls):
## object-base.h (module 'core'): ns3::ObjectBase::ObjectBase() [constructor]
cls.add_constructor([])
## object-base.h (module 'core'): ns3::ObjectBase::ObjectBase(ns3::ObjectBase const & arg0) [copy constructor]
cls.add_constructor([param('ns3::ObjectBase const &', 'arg0')])
## object-base.h (module 'core'): void ns3::ObjectBase::GetAttribute(std::string name, ns3::AttributeValue & value) const [member function]
cls.add_method('GetAttribute',
'void',
[param('std::string', 'name'), param('ns3::AttributeValue &', 'value')],
is_const=True)
## object-base.h (module 'core'): bool ns3::ObjectBase::GetAttributeFailSafe(std::string name, ns3::AttributeValue & value) const [member function]
cls.add_method('GetAttributeFailSafe',
'bool',
[param('std::string', 'name'), param('ns3::AttributeValue &', 'value')],
is_const=True)
## object-base.h (module 'core'): ns3::TypeId ns3::ObjectBase::GetInstanceTypeId() const [member function]
cls.add_method('GetInstanceTypeId',
'ns3::TypeId',
[],
is_pure_virtual=True, is_const=True, is_virtual=True)
## object-base.h (module 'core'): static ns3::TypeId ns3::ObjectBase::GetTypeId() [member function]
cls.add_method('GetTypeId',
'ns3::TypeId',
[],
is_static=True)
## object-base.h (module 'core'): void ns3::ObjectBase::SetAttribute(std::string name, ns3::AttributeValue const & value) [member function]
cls.add_method('SetAttribute',
'void',
[param('std::string', 'name'), param('ns3::AttributeValue const &', 'value')])
## object-base.h (module 'core'): bool ns3::ObjectBase::SetAttributeFailSafe(std::string name, ns3::AttributeValue const & value) [member function]
cls.add_method('SetAttributeFailSafe',
'bool',
[param('std::string', 'name'), param('ns3::AttributeValue const &', 'value')])
## object-base.h (module 'core'): bool ns3::ObjectBase::TraceConnect(std::string name, std::string context, ns3::CallbackBase const & cb) [member function]
cls.add_method('TraceConnect',
'bool',
[param('std::string', 'name'), param('std::string', 'context'), param('ns3::CallbackBase const &', 'cb')])
## object-base.h (module 'core'): bool ns3::ObjectBase::TraceConnectWithoutContext(std::string name, ns3::CallbackBase const & cb) [member function]
cls.add_method('TraceConnectWithoutContext',
'bool',
[param('std::string', 'name'), param('ns3::CallbackBase const &', 'cb')])
## object-base.h (module 'core'): bool ns3::ObjectBase::TraceDisconnect(std::string name, std::string context, ns3::CallbackBase const & cb) [member function]
cls.add_method('TraceDisconnect',
'bool',
[param('std::string', 'name'), param('std::string', 'context'), param('ns3::CallbackBase const &', 'cb')])
## object-base.h (module 'core'): bool ns3::ObjectBase::TraceDisconnectWithoutContext(std::string name, ns3::CallbackBase const & cb) [member function]
cls.add_method('TraceDisconnectWithoutContext',
'bool',
[param('std::string', 'name'), param('ns3::CallbackBase const &', 'cb')])
## object-base.h (module 'core'): void ns3::ObjectBase::ConstructSelf(ns3::AttributeConstructionList const & attributes) [member function]
cls.add_method('ConstructSelf',
'void',
[param('ns3::AttributeConstructionList const &', 'attributes')],
visibility='protected')
## object-base.h (module 'core'): void ns3::ObjectBase::NotifyConstructionCompleted() [member function]
cls.add_method('NotifyConstructionCompleted',
'void',
[],
visibility='protected', is_virtual=True)
return
def register_Ns3ObjectDeleter_methods(root_module, cls):
## object.h (module 'core'): ns3::ObjectDeleter::ObjectDeleter() [constructor]
cls.add_constructor([])
## object.h (module 'core'): ns3::ObjectDeleter::ObjectDeleter(ns3::ObjectDeleter const & arg0) [copy constructor]
cls.add_constructor([param('ns3::ObjectDeleter const &', 'arg0')])
## object.h (module 'core'): static void ns3::ObjectDeleter::Delete(ns3::Object * object) [member function]
cls.add_method('Delete',
'void',
[param('ns3::Object *', 'object')],
is_static=True)
return
def register_Ns3ObjectFactory_methods(root_module, cls):
cls.add_output_stream_operator()
## object-factory.h (module 'core'): ns3::ObjectFactory::ObjectFactory(ns3::ObjectFactory const & arg0) [copy constructor]
cls.add_constructor([param('ns3::ObjectFactory const &', 'arg0')])
## object-factory.h (module 'core'): ns3::ObjectFactory::ObjectFactory() [constructor]
cls.add_constructor([])
## object-factory.h (module 'core'): ns3::ObjectFactory::ObjectFactory(std::string typeId) [constructor]
cls.add_constructor([param('std::string', 'typeId')])
## object-factory.h (module 'core'): ns3::Ptr<ns3::Object> ns3::ObjectFactory::Create() const [member function]
cls.add_method('Create',
'ns3::Ptr< ns3::Object >',
[],
is_const=True)
## object-factory.h (module 'core'): ns3::TypeId ns3::ObjectFactory::GetTypeId() const [member function]
cls.add_method('GetTypeId',
'ns3::TypeId',
[],
is_const=True)
## object-factory.h (module 'core'): void ns3::ObjectFactory::Set(std::string name, ns3::AttributeValue const & value) [member function]
cls.add_method('Set',
'void',
[param('std::string', 'name'), param('ns3::AttributeValue const &', 'value')])
## object-factory.h (module 'core'): void ns3::ObjectFactory::SetTypeId(ns3::TypeId tid) [member function]
cls.add_method('SetTypeId',
'void',
[param('ns3::TypeId', 'tid')])
## object-factory.h (module 'core'): void ns3::ObjectFactory::SetTypeId(char const * tid) [member function]
cls.add_method('SetTypeId',
'void',
[param('char const *', 'tid')])
## object-factory.h (module 'core'): void ns3::ObjectFactory::SetTypeId(std::string tid) [member function]
cls.add_method('SetTypeId',
'void',
[param('std::string', 'tid')])
return
def register_Ns3PacketMetadata_methods(root_module, cls):
## packet-metadata.h (module 'network'): ns3::PacketMetadata::PacketMetadata(uint64_t uid, uint32_t size) [constructor]
cls.add_constructor([param('uint64_t', 'uid'), param('uint32_t', 'size')])
## packet-metadata.h (module 'network'): ns3::PacketMetadata::PacketMetadata(ns3::PacketMetadata const & o) [copy constructor]
cls.add_constructor([param('ns3::PacketMetadata const &', 'o')])
## packet-metadata.h (module 'network'): void ns3::PacketMetadata::AddAtEnd(ns3::PacketMetadata const & o) [member function]
cls.add_method('AddAtEnd',
'void',
[param('ns3::PacketMetadata const &', 'o')])
## packet-metadata.h (module 'network'): void ns3::PacketMetadata::AddHeader(ns3::Header const & header, uint32_t size) [member function]
cls.add_method('AddHeader',
'void',
[param('ns3::Header const &', 'header'), param('uint32_t', 'size')])
## packet-metadata.h (module 'network'): void ns3::PacketMetadata::AddPaddingAtEnd(uint32_t end) [member function]
cls.add_method('AddPaddingAtEnd',
'void',
[param('uint32_t', 'end')])
## packet-metadata.h (module 'network'): void ns3::PacketMetadata::AddTrailer(ns3::Trailer const & trailer, uint32_t size) [member function]
cls.add_method('AddTrailer',
'void',
[param('ns3::Trailer const &', 'trailer'), param('uint32_t', 'size')])
## packet-metadata.h (module 'network'): ns3::PacketMetadata::ItemIterator ns3::PacketMetadata::BeginItem(ns3::Buffer buffer) const [member function]
cls.add_method('BeginItem',
'ns3::PacketMetadata::ItemIterator',
[param('ns3::Buffer', 'buffer')],
is_const=True)
## packet-metadata.h (module 'network'): ns3::PacketMetadata ns3::PacketMetadata::CreateFragment(uint32_t start, uint32_t end) const [member function]
cls.add_method('CreateFragment',
'ns3::PacketMetadata',
[param('uint32_t', 'start'), param('uint32_t', 'end')],
is_const=True)
## packet-metadata.h (module 'network'): uint32_t ns3::PacketMetadata::Deserialize(uint8_t const * buffer, uint32_t size) [member function]
cls.add_method('Deserialize',
'uint32_t',
[param('uint8_t const *', 'buffer'), param('uint32_t', 'size')])
## packet-metadata.h (module 'network'): static void ns3::PacketMetadata::Enable() [member function]
cls.add_method('Enable',
'void',
[],
is_static=True)
## packet-metadata.h (module 'network'): static void ns3::PacketMetadata::EnableChecking() [member function]
cls.add_method('EnableChecking',
'void',
[],
is_static=True)
## packet-metadata.h (module 'network'): uint32_t ns3::PacketMetadata::GetSerializedSize() const [member function]
cls.add_method('GetSerializedSize',
'uint32_t',
[],
is_const=True)
## packet-metadata.h (module 'network'): uint64_t ns3::PacketMetadata::GetUid() const [member function]
cls.add_method('GetUid',
'uint64_t',
[],
is_const=True)
## packet-metadata.h (module 'network'): void ns3::PacketMetadata::RemoveAtEnd(uint32_t end) [member function]
cls.add_method('RemoveAtEnd',
'void',
[param('uint32_t', 'end')])
## packet-metadata.h (module 'network'): void ns3::PacketMetadata::RemoveAtStart(uint32_t start) [member function]
cls.add_method('RemoveAtStart',
'void',
[param('uint32_t', 'start')])
## packet-metadata.h (module 'network'): void ns3::PacketMetadata::RemoveHeader(ns3::Header const & header, uint32_t size) [member function]
cls.add_method('RemoveHeader',
'void',
[param('ns3::Header const &', 'header'), param('uint32_t', 'size')])
## packet-metadata.h (module 'network'): void ns3::PacketMetadata::RemoveTrailer(ns3::Trailer const & trailer, uint32_t size) [member function]
cls.add_method('RemoveTrailer',
'void',
[param('ns3::Trailer const &', 'trailer'), param('uint32_t', 'size')])
## packet-metadata.h (module 'network'): uint32_t ns3::PacketMetadata::Serialize(uint8_t * buffer, uint32_t maxSize) const [member function]
cls.add_method('Serialize',
'uint32_t',
[param('uint8_t *', 'buffer'), param('uint32_t', 'maxSize')],
is_const=True)
return
def register_Ns3PacketMetadataItem_methods(root_module, cls):
## packet-metadata.h (module 'network'): ns3::PacketMetadata::Item::Item() [constructor]
cls.add_constructor([])
## packet-metadata.h (module 'network'): ns3::PacketMetadata::Item::Item(ns3::PacketMetadata::Item const & arg0) [copy constructor]
cls.add_constructor([param('ns3::PacketMetadata::Item const &', 'arg0')])
## packet-metadata.h (module 'network'): ns3::PacketMetadata::Item::current [variable]
cls.add_instance_attribute('current', 'ns3::Buffer::Iterator', is_const=False)
## packet-metadata.h (module 'network'): ns3::PacketMetadata::Item::currentSize [variable]
cls.add_instance_attribute('currentSize', 'uint32_t', is_const=False)
## packet-metadata.h (module 'network'): ns3::PacketMetadata::Item::currentTrimedFromEnd [variable]
cls.add_instance_attribute('currentTrimedFromEnd', 'uint32_t', is_const=False)
## packet-metadata.h (module 'network'): ns3::PacketMetadata::Item::currentTrimedFromStart [variable]
cls.add_instance_attribute('currentTrimedFromStart', 'uint32_t', is_const=False)
## packet-metadata.h (module 'network'): ns3::PacketMetadata::Item::isFragment [variable]
cls.add_instance_attribute('isFragment', 'bool', is_const=False)
## packet-metadata.h (module 'network'): ns3::PacketMetadata::Item::tid [variable]
cls.add_instance_attribute('tid', 'ns3::TypeId', is_const=False)
return
def register_Ns3PacketMetadataItemIterator_methods(root_module, cls):
## packet-metadata.h (module 'network'): ns3::PacketMetadata::ItemIterator::ItemIterator(ns3::PacketMetadata::ItemIterator const & arg0) [copy constructor]
cls.add_constructor([param('ns3::PacketMetadata::ItemIterator const &', 'arg0')])
## packet-metadata.h (module 'network'): ns3::PacketMetadata::ItemIterator::ItemIterator(ns3::PacketMetadata const * metadata, ns3::Buffer buffer) [constructor]
cls.add_constructor([param('ns3::PacketMetadata const *', 'metadata'), param('ns3::Buffer', 'buffer')])
## packet-metadata.h (module 'network'): bool ns3::PacketMetadata::ItemIterator::HasNext() const [member function]
cls.add_method('HasNext',
'bool',
[],
is_const=True)
## packet-metadata.h (module 'network'): ns3::PacketMetadata::Item ns3::PacketMetadata::ItemIterator::Next() [member function]
cls.add_method('Next',
'ns3::PacketMetadata::Item',
[])
return
def register_Ns3PacketTagIterator_methods(root_module, cls):
## packet.h (module 'network'): ns3::PacketTagIterator::PacketTagIterator(ns3::PacketTagIterator const & arg0) [copy constructor]
cls.add_constructor([param('ns3::PacketTagIterator const &', 'arg0')])
## packet.h (module 'network'): bool ns3::PacketTagIterator::HasNext() const [member function]
cls.add_method('HasNext',
'bool',
[],
is_const=True)
## packet.h (module 'network'): ns3::PacketTagIterator::Item ns3::PacketTagIterator::Next() [member function]
cls.add_method('Next',
'ns3::PacketTagIterator::Item',
[])
return
def register_Ns3PacketTagIteratorItem_methods(root_module, cls):
## packet.h (module 'network'): ns3::PacketTagIterator::Item::Item(ns3::PacketTagIterator::Item const & arg0) [copy constructor]
cls.add_constructor([param('ns3::PacketTagIterator::Item const &', 'arg0')])
## packet.h (module 'network'): void ns3::PacketTagIterator::Item::GetTag(ns3::Tag & tag) const [member function]
cls.add_method('GetTag',
'void',
[param('ns3::Tag &', 'tag')],
is_const=True)
## packet.h (module 'network'): ns3::TypeId ns3::PacketTagIterator::Item::GetTypeId() const [member function]
cls.add_method('GetTypeId',
'ns3::TypeId',
[],
is_const=True)
return
def register_Ns3PacketTagList_methods(root_module, cls):
## packet-tag-list.h (module 'network'): ns3::PacketTagList::PacketTagList() [constructor]
cls.add_constructor([])
## packet-tag-list.h (module 'network'): ns3::PacketTagList::PacketTagList(ns3::PacketTagList const & o) [copy constructor]
cls.add_constructor([param('ns3::PacketTagList const &', 'o')])
## packet-tag-list.h (module 'network'): void ns3::PacketTagList::Add(ns3::Tag const & tag) const [member function]
cls.add_method('Add',
'void',
[param('ns3::Tag const &', 'tag')],
is_const=True)
## packet-tag-list.h (module 'network'): ns3::PacketTagList::TagData const * ns3::PacketTagList::Head() const [member function]
cls.add_method('Head',
'ns3::PacketTagList::TagData const *',
[],
is_const=True)
## packet-tag-list.h (module 'network'): bool ns3::PacketTagList::Peek(ns3::Tag & tag) const [member function]
cls.add_method('Peek',
'bool',
[param('ns3::Tag &', 'tag')],
is_const=True)
## packet-tag-list.h (module 'network'): bool ns3::PacketTagList::Remove(ns3::Tag & tag) [member function]
cls.add_method('Remove',
'bool',
[param('ns3::Tag &', 'tag')])
## packet-tag-list.h (module 'network'): void ns3::PacketTagList::RemoveAll() [member function]
cls.add_method('RemoveAll',
'void',
[])
## packet-tag-list.h (module 'network'): bool ns3::PacketTagList::Replace(ns3::Tag & tag) [member function]
cls.add_method('Replace',
'bool',
[param('ns3::Tag &', 'tag')])
return
def register_Ns3PacketTagListTagData_methods(root_module, cls):
## packet-tag-list.h (module 'network'): ns3::PacketTagList::TagData::TagData() [constructor]
cls.add_constructor([])
## packet-tag-list.h (module 'network'): ns3::PacketTagList::TagData::TagData(ns3::PacketTagList::TagData const & arg0) [copy constructor]
cls.add_constructor([param('ns3::PacketTagList::TagData const &', 'arg0')])
## packet-tag-list.h (module 'network'): ns3::PacketTagList::TagData::count [variable]
cls.add_instance_attribute('count', 'uint32_t', is_const=False)
## packet-tag-list.h (module 'network'): ns3::PacketTagList::TagData::data [variable]
cls.add_instance_attribute('data', 'uint8_t [ 21 ]', is_const=False)
## packet-tag-list.h (module 'network'): ns3::PacketTagList::TagData::next [variable]
cls.add_instance_attribute('next', 'ns3::PacketTagList::TagData *', is_const=False)
## packet-tag-list.h (module 'network'): ns3::PacketTagList::TagData::tid [variable]
cls.add_instance_attribute('tid', 'ns3::TypeId', is_const=False)
return
def register_Ns3PyViz_methods(root_module, cls):
## pyviz.h (module 'visualizer'): ns3::PyViz::PyViz(ns3::PyViz const & arg0) [copy constructor]
cls.add_constructor([param('ns3::PyViz const &', 'arg0')])
## pyviz.h (module 'visualizer'): ns3::PyViz::PyViz() [constructor]
cls.add_constructor([])
## pyviz.h (module 'visualizer'): ns3::PyViz::LastPacketsSample ns3::PyViz::GetLastPackets(uint32_t nodeId) const [member function]
cls.add_method('GetLastPackets',
'ns3::PyViz::LastPacketsSample',
[param('uint32_t', 'nodeId')],
is_const=True)
## pyviz.h (module 'visualizer'): std::vector<ns3::PyViz::NodeStatistics,std::allocator<ns3::PyViz::NodeStatistics> > ns3::PyViz::GetNodesStatistics() const [member function]
cls.add_method('GetNodesStatistics',
'std::vector< ns3::PyViz::NodeStatistics >',
[],
is_const=True)
## pyviz.h (module 'visualizer'): std::vector<ns3::PyViz::PacketDropSample,std::allocator<ns3::PyViz::PacketDropSample> > ns3::PyViz::GetPacketDropSamples() const [member function]
cls.add_method('GetPacketDropSamples',
'std::vector< ns3::PyViz::PacketDropSample >',
[],
is_const=True)
## pyviz.h (module 'visualizer'): std::vector<std::string, std::allocator<std::string> > ns3::PyViz::GetPauseMessages() const [member function]
cls.add_method('GetPauseMessages',
'std::vector< std::string >',
[],
is_const=True)
## pyviz.h (module 'visualizer'): std::vector<ns3::PyViz::TransmissionSample,std::allocator<ns3::PyViz::TransmissionSample> > ns3::PyViz::GetTransmissionSamples() const [member function]
cls.add_method('GetTransmissionSamples',
'std::vector< ns3::PyViz::TransmissionSample >',
[],
is_const=True)
## pyviz.h (module 'visualizer'): static void ns3::PyViz::LineClipping(double boundsX1, double boundsY1, double boundsX2, double boundsY2, double & lineX1, double & lineY1, double & lineX2, double & lineY2) [member function]
cls.add_method('LineClipping',
'void',
[param('double', 'boundsX1'), param('double', 'boundsY1'), param('double', 'boundsX2'), param('double', 'boundsY2'), param('double &', 'lineX1', direction=3), param('double &', 'lineY1', direction=3), param('double &', 'lineX2', direction=3), param('double &', 'lineY2', direction=3)],
is_static=True)
## pyviz.h (module 'visualizer'): static void ns3::PyViz::Pause(std::string const & message) [member function]
cls.add_method('Pause',
'void',
[param('std::string const &', 'message')],
is_static=True)
## pyviz.h (module 'visualizer'): void ns3::PyViz::RegisterCsmaLikeDevice(std::string const & deviceTypeName) [member function]
cls.add_method('RegisterCsmaLikeDevice',
'void',
[param('std::string const &', 'deviceTypeName')])
## pyviz.h (module 'visualizer'): void ns3::PyViz::RegisterDropTracePath(std::string const & tracePath) [member function]
cls.add_method('RegisterDropTracePath',
'void',
[param('std::string const &', 'tracePath')])
## pyviz.h (module 'visualizer'): void ns3::PyViz::RegisterPointToPointLikeDevice(std::string const & deviceTypeName) [member function]
cls.add_method('RegisterPointToPointLikeDevice',
'void',
[param('std::string const &', 'deviceTypeName')])
## pyviz.h (module 'visualizer'): void ns3::PyViz::RegisterWifiLikeDevice(std::string const & deviceTypeName) [member function]
cls.add_method('RegisterWifiLikeDevice',
'void',
[param('std::string const &', 'deviceTypeName')])
## pyviz.h (module 'visualizer'): void ns3::PyViz::SetNodesOfInterest(std::set<unsigned int, std::less<unsigned int>, std::allocator<unsigned int> > nodes) [member function]
cls.add_method('SetNodesOfInterest',
'void',
[param('std::set< unsigned int >', 'nodes')])
## pyviz.h (module 'visualizer'): void ns3::PyViz::SetPacketCaptureOptions(uint32_t nodeId, ns3::PyViz::PacketCaptureOptions options) [member function]
cls.add_method('SetPacketCaptureOptions',
'void',
[param('uint32_t', 'nodeId'), param('ns3::PyViz::PacketCaptureOptions', 'options')])
## pyviz.h (module 'visualizer'): void ns3::PyViz::SimulatorRunUntil(ns3::Time time) [member function]
cls.add_method('SimulatorRunUntil',
'void',
[param('ns3::Time', 'time')])
return
def register_Ns3PyVizLastPacketsSample_methods(root_module, cls):
## pyviz.h (module 'visualizer'): ns3::PyViz::LastPacketsSample::LastPacketsSample() [constructor]
cls.add_constructor([])
## pyviz.h (module 'visualizer'): ns3::PyViz::LastPacketsSample::LastPacketsSample(ns3::PyViz::LastPacketsSample const & arg0) [copy constructor]
cls.add_constructor([param('ns3::PyViz::LastPacketsSample const &', 'arg0')])
## pyviz.h (module 'visualizer'): ns3::PyViz::LastPacketsSample::lastDroppedPackets [variable]
cls.add_instance_attribute('lastDroppedPackets', 'std::vector< ns3::PyViz::PacketSample >', is_const=False)
## pyviz.h (module 'visualizer'): ns3::PyViz::LastPacketsSample::lastReceivedPackets [variable]
cls.add_instance_attribute('lastReceivedPackets', 'std::vector< ns3::PyViz::RxPacketSample >', is_const=False)
## pyviz.h (module 'visualizer'): ns3::PyViz::LastPacketsSample::lastTransmittedPackets [variable]
cls.add_instance_attribute('lastTransmittedPackets', 'std::vector< ns3::PyViz::TxPacketSample >', is_const=False)
return
def register_Ns3PyVizNetDeviceStatistics_methods(root_module, cls):
## pyviz.h (module 'visualizer'): ns3::PyViz::NetDeviceStatistics::NetDeviceStatistics(ns3::PyViz::NetDeviceStatistics const & arg0) [copy constructor]
cls.add_constructor([param('ns3::PyViz::NetDeviceStatistics const &', 'arg0')])
## pyviz.h (module 'visualizer'): ns3::PyViz::NetDeviceStatistics::NetDeviceStatistics() [constructor]
cls.add_constructor([])
## pyviz.h (module 'visualizer'): ns3::PyViz::NetDeviceStatistics::receivedBytes [variable]
cls.add_instance_attribute('receivedBytes', 'uint64_t', is_const=False)
## pyviz.h (module 'visualizer'): ns3::PyViz::NetDeviceStatistics::receivedPackets [variable]
cls.add_instance_attribute('receivedPackets', 'uint32_t', is_const=False)
## pyviz.h (module 'visualizer'): ns3::PyViz::NetDeviceStatistics::transmittedBytes [variable]
cls.add_instance_attribute('transmittedBytes', 'uint64_t', is_const=False)
## pyviz.h (module 'visualizer'): ns3::PyViz::NetDeviceStatistics::transmittedPackets [variable]
cls.add_instance_attribute('transmittedPackets', 'uint32_t', is_const=False)
return
def register_Ns3PyVizNodeStatistics_methods(root_module, cls):
## pyviz.h (module 'visualizer'): ns3::PyViz::NodeStatistics::NodeStatistics() [constructor]
cls.add_constructor([])
## pyviz.h (module 'visualizer'): ns3::PyViz::NodeStatistics::NodeStatistics(ns3::PyViz::NodeStatistics const & arg0) [copy constructor]
cls.add_constructor([param('ns3::PyViz::NodeStatistics const &', 'arg0')])
## pyviz.h (module 'visualizer'): ns3::PyViz::NodeStatistics::nodeId [variable]
cls.add_instance_attribute('nodeId', 'uint32_t', is_const=False)
## pyviz.h (module 'visualizer'): ns3::PyViz::NodeStatistics::statistics [variable]
cls.add_instance_attribute('statistics', 'std::vector< ns3::PyViz::NetDeviceStatistics >', is_const=False)
return
def register_Ns3PyVizPacketCaptureOptions_methods(root_module, cls):
## pyviz.h (module 'visualizer'): ns3::PyViz::PacketCaptureOptions::PacketCaptureOptions() [constructor]
cls.add_constructor([])
## pyviz.h (module 'visualizer'): ns3::PyViz::PacketCaptureOptions::PacketCaptureOptions(ns3::PyViz::PacketCaptureOptions const & arg0) [copy constructor]
cls.add_constructor([param('ns3::PyViz::PacketCaptureOptions const &', 'arg0')])
## pyviz.h (module 'visualizer'): ns3::PyViz::PacketCaptureOptions::headers [variable]
cls.add_instance_attribute('headers', 'std::set< ns3::TypeId >', is_const=False)
## pyviz.h (module 'visualizer'): ns3::PyViz::PacketCaptureOptions::mode [variable]
cls.add_instance_attribute('mode', 'ns3::PyViz::PacketCaptureMode', is_const=False)
## pyviz.h (module 'visualizer'): ns3::PyViz::PacketCaptureOptions::numLastPackets [variable]
cls.add_instance_attribute('numLastPackets', 'uint32_t', is_const=False)
return
def register_Ns3PyVizPacketDropSample_methods(root_module, cls):
## pyviz.h (module 'visualizer'): ns3::PyViz::PacketDropSample::PacketDropSample() [constructor]
cls.add_constructor([])
## pyviz.h (module 'visualizer'): ns3::PyViz::PacketDropSample::PacketDropSample(ns3::PyViz::PacketDropSample const & arg0) [copy constructor]
cls.add_constructor([param('ns3::PyViz::PacketDropSample const &', 'arg0')])
## pyviz.h (module 'visualizer'): ns3::PyViz::PacketDropSample::bytes [variable]
cls.add_instance_attribute('bytes', 'uint32_t', is_const=False)
## pyviz.h (module 'visualizer'): ns3::PyViz::PacketDropSample::transmitter [variable]
cls.add_instance_attribute('transmitter', 'ns3::Ptr< ns3::Node >', is_const=False)
return
def register_Ns3PyVizPacketSample_methods(root_module, cls):
## pyviz.h (module 'visualizer'): ns3::PyViz::PacketSample::PacketSample() [constructor]
cls.add_constructor([])
## pyviz.h (module 'visualizer'): ns3::PyViz::PacketSample::PacketSample(ns3::PyViz::PacketSample const & arg0) [copy constructor]
cls.add_constructor([param('ns3::PyViz::PacketSample const &', 'arg0')])
## pyviz.h (module 'visualizer'): ns3::PyViz::PacketSample::device [variable]
cls.add_instance_attribute('device', 'ns3::Ptr< ns3::NetDevice >', is_const=False)
## pyviz.h (module 'visualizer'): ns3::PyViz::PacketSample::packet [variable]
cls.add_instance_attribute('packet', 'ns3::Ptr< ns3::Packet >', is_const=False)
## pyviz.h (module 'visualizer'): ns3::PyViz::PacketSample::time [variable]
cls.add_instance_attribute('time', 'ns3::Time', is_const=False)
return
def register_Ns3PyVizRxPacketSample_methods(root_module, cls):
## pyviz.h (module 'visualizer'): ns3::PyViz::RxPacketSample::RxPacketSample() [constructor]
cls.add_constructor([])
## pyviz.h (module 'visualizer'): ns3::PyViz::RxPacketSample::RxPacketSample(ns3::PyViz::RxPacketSample const & arg0) [copy constructor]
cls.add_constructor([param('ns3::PyViz::RxPacketSample const &', 'arg0')])
## pyviz.h (module 'visualizer'): ns3::PyViz::RxPacketSample::from [variable]
cls.add_instance_attribute('from', 'ns3::Mac48Address', is_const=False)
return
def register_Ns3PyVizTransmissionSample_methods(root_module, cls):
## pyviz.h (module 'visualizer'): ns3::PyViz::TransmissionSample::TransmissionSample() [constructor]
cls.add_constructor([])
## pyviz.h (module 'visualizer'): ns3::PyViz::TransmissionSample::TransmissionSample(ns3::PyViz::TransmissionSample const & arg0) [copy constructor]
cls.add_constructor([param('ns3::PyViz::TransmissionSample const &', 'arg0')])
## pyviz.h (module 'visualizer'): ns3::PyViz::TransmissionSample::bytes [variable]
cls.add_instance_attribute('bytes', 'uint32_t', is_const=False)
## pyviz.h (module 'visualizer'): ns3::PyViz::TransmissionSample::channel [variable]
cls.add_instance_attribute('channel', 'ns3::Ptr< ns3::Channel >', is_const=False)
## pyviz.h (module 'visualizer'): ns3::PyViz::TransmissionSample::receiver [variable]
cls.add_instance_attribute('receiver', 'ns3::Ptr< ns3::Node >', is_const=False)
## pyviz.h (module 'visualizer'): ns3::PyViz::TransmissionSample::transmitter [variable]
cls.add_instance_attribute('transmitter', 'ns3::Ptr< ns3::Node >', is_const=False)
return
def register_Ns3PyVizTxPacketSample_methods(root_module, cls):
## pyviz.h (module 'visualizer'): ns3::PyViz::TxPacketSample::TxPacketSample() [constructor]
cls.add_constructor([])
## pyviz.h (module 'visualizer'): ns3::PyViz::TxPacketSample::TxPacketSample(ns3::PyViz::TxPacketSample const & arg0) [copy constructor]
cls.add_constructor([param('ns3::PyViz::TxPacketSample const &', 'arg0')])
## pyviz.h (module 'visualizer'): ns3::PyViz::TxPacketSample::to [variable]
cls.add_instance_attribute('to', 'ns3::Mac48Address', is_const=False)
return
def register_Ns3SimpleRefCount__Ns3Object_Ns3ObjectBase_Ns3ObjectDeleter_methods(root_module, cls):
## simple-ref-count.h (module 'core'): ns3::SimpleRefCount<ns3::Object, ns3::ObjectBase, ns3::ObjectDeleter>::SimpleRefCount() [constructor]
cls.add_constructor([])
## simple-ref-count.h (module 'core'): ns3::SimpleRefCount<ns3::Object, ns3::ObjectBase, ns3::ObjectDeleter>::SimpleRefCount(ns3::SimpleRefCount<ns3::Object, ns3::ObjectBase, ns3::ObjectDeleter> const & o) [copy constructor]
cls.add_constructor([param('ns3::SimpleRefCount< ns3::Object, ns3::ObjectBase, ns3::ObjectDeleter > const &', 'o')])
## simple-ref-count.h (module 'core'): static void ns3::SimpleRefCount<ns3::Object, ns3::ObjectBase, ns3::ObjectDeleter>::Cleanup() [member function]
cls.add_method('Cleanup',
'void',
[],
is_static=True)
return
def register_Ns3Simulator_methods(root_module, cls):
## simulator.h (module 'core'): ns3::Simulator::Simulator(ns3::Simulator const & arg0) [copy constructor]
cls.add_constructor([param('ns3::Simulator const &', 'arg0')])
## simulator.h (module 'core'): static void ns3::Simulator::Cancel(ns3::EventId const & id) [member function]
cls.add_method('Cancel',
'void',
[param('ns3::EventId const &', 'id')],
is_static=True)
## simulator.h (module 'core'): static void ns3::Simulator::Destroy() [member function]
cls.add_method('Destroy',
'void',
[],
is_static=True)
## simulator.h (module 'core'): static uint32_t ns3::Simulator::GetContext() [member function]
cls.add_method('GetContext',
'uint32_t',
[],
is_static=True)
## simulator.h (module 'core'): static ns3::Time ns3::Simulator::GetDelayLeft(ns3::EventId const & id) [member function]
cls.add_method('GetDelayLeft',
'ns3::Time',
[param('ns3::EventId const &', 'id')],
is_static=True)
## simulator.h (module 'core'): static ns3::Ptr<ns3::SimulatorImpl> ns3::Simulator::GetImplementation() [member function]
cls.add_method('GetImplementation',
'ns3::Ptr< ns3::SimulatorImpl >',
[],
is_static=True)
## simulator.h (module 'core'): static ns3::Time ns3::Simulator::GetMaximumSimulationTime() [member function]
cls.add_method('GetMaximumSimulationTime',
'ns3::Time',
[],
is_static=True)
## simulator.h (module 'core'): static uint32_t ns3::Simulator::GetSystemId() [member function]
cls.add_method('GetSystemId',
'uint32_t',
[],
is_static=True)
## simulator.h (module 'core'): static bool ns3::Simulator::IsExpired(ns3::EventId const & id) [member function]
cls.add_method('IsExpired',
'bool',
[param('ns3::EventId const &', 'id')],
is_static=True)
## simulator.h (module 'core'): static bool ns3::Simulator::IsFinished() [member function]
cls.add_method('IsFinished',
'bool',
[],
is_static=True)
## simulator.h (module 'core'): static ns3::Time ns3::Simulator::Now() [member function]
cls.add_method('Now',
'ns3::Time',
[],
is_static=True)
## simulator.h (module 'core'): static void ns3::Simulator::Remove(ns3::EventId const & id) [member function]
cls.add_method('Remove',
'void',
[param('ns3::EventId const &', 'id')],
is_static=True)
## simulator.h (module 'core'): static void ns3::Simulator::SetImplementation(ns3::Ptr<ns3::SimulatorImpl> impl) [member function]
cls.add_method('SetImplementation',
'void',
[param('ns3::Ptr< ns3::SimulatorImpl >', 'impl')],
is_static=True)
## simulator.h (module 'core'): static void ns3::Simulator::SetScheduler(ns3::ObjectFactory schedulerFactory) [member function]
cls.add_method('SetScheduler',
'void',
[param('ns3::ObjectFactory', 'schedulerFactory')],
is_static=True)
## simulator.h (module 'core'): static void ns3::Simulator::Stop() [member function]
cls.add_method('Stop',
'void',
[],
is_static=True)
## simulator.h (module 'core'): static void ns3::Simulator::Stop(ns3::Time const & delay) [member function]
cls.add_method('Stop',
'void',
[param('ns3::Time const &', 'delay')],
is_static=True)
return
def register_Ns3Tag_methods(root_module, cls):
## tag.h (module 'network'): ns3::Tag::Tag() [constructor]
cls.add_constructor([])
## tag.h (module 'network'): ns3::Tag::Tag(ns3::Tag const & arg0) [copy constructor]
cls.add_constructor([param('ns3::Tag const &', 'arg0')])
## tag.h (module 'network'): void ns3::Tag::Deserialize(ns3::TagBuffer i) [member function]
cls.add_method('Deserialize',
'void',
[param('ns3::TagBuffer', 'i')],
is_pure_virtual=True, is_virtual=True)
## tag.h (module 'network'): uint32_t ns3::Tag::GetSerializedSize() const [member function]
cls.add_method('GetSerializedSize',
'uint32_t',
[],
is_pure_virtual=True, is_const=True, is_virtual=True)
## tag.h (module 'network'): static ns3::TypeId ns3::Tag::GetTypeId() [member function]
cls.add_method('GetTypeId',
'ns3::TypeId',
[],
is_static=True)
## tag.h (module 'network'): void ns3::Tag::Print(std::ostream & os) const [member function]
cls.add_method('Print',
'void',
[param('std::ostream &', 'os')],
is_pure_virtual=True, is_const=True, is_virtual=True)
## tag.h (module 'network'): void ns3::Tag::Serialize(ns3::TagBuffer i) const [member function]
cls.add_method('Serialize',
'void',
[param('ns3::TagBuffer', 'i')],
is_pure_virtual=True, is_const=True, is_virtual=True)
return
def register_Ns3TagBuffer_methods(root_module, cls):
## tag-buffer.h (module 'network'): ns3::TagBuffer::TagBuffer(ns3::TagBuffer const & arg0) [copy constructor]
cls.add_constructor([param('ns3::TagBuffer const &', 'arg0')])
## tag-buffer.h (module 'network'): ns3::TagBuffer::TagBuffer(uint8_t * start, uint8_t * end) [constructor]
cls.add_constructor([param('uint8_t *', 'start'), param('uint8_t *', 'end')])
## tag-buffer.h (module 'network'): void ns3::TagBuffer::CopyFrom(ns3::TagBuffer o) [member function]
cls.add_method('CopyFrom',
'void',
[param('ns3::TagBuffer', 'o')])
## tag-buffer.h (module 'network'): void ns3::TagBuffer::Read(uint8_t * buffer, uint32_t size) [member function]
cls.add_method('Read',
'void',
[param('uint8_t *', 'buffer'), param('uint32_t', 'size')])
## tag-buffer.h (module 'network'): double ns3::TagBuffer::ReadDouble() [member function]
cls.add_method('ReadDouble',
'double',
[])
## tag-buffer.h (module 'network'): uint16_t ns3::TagBuffer::ReadU16() [member function]
cls.add_method('ReadU16',
'uint16_t',
[])
## tag-buffer.h (module 'network'): uint32_t ns3::TagBuffer::ReadU32() [member function]
cls.add_method('ReadU32',
'uint32_t',
[])
## tag-buffer.h (module 'network'): uint64_t ns3::TagBuffer::ReadU64() [member function]
cls.add_method('ReadU64',
'uint64_t',
[])
## tag-buffer.h (module 'network'): uint8_t ns3::TagBuffer::ReadU8() [member function]
cls.add_method('ReadU8',
'uint8_t',
[])
## tag-buffer.h (module 'network'): void ns3::TagBuffer::TrimAtEnd(uint32_t trim) [member function]
cls.add_method('TrimAtEnd',
'void',
[param('uint32_t', 'trim')])
## tag-buffer.h (module 'network'): void ns3::TagBuffer::Write(uint8_t const * buffer, uint32_t size) [member function]
cls.add_method('Write',
'void',
[param('uint8_t const *', 'buffer'), param('uint32_t', 'size')])
## tag-buffer.h (module 'network'): void ns3::TagBuffer::WriteDouble(double v) [member function]
cls.add_method('WriteDouble',
'void',
[param('double', 'v')])
## tag-buffer.h (module 'network'): void ns3::TagBuffer::WriteU16(uint16_t data) [member function]
cls.add_method('WriteU16',
'void',
[param('uint16_t', 'data')])
## tag-buffer.h (module 'network'): void ns3::TagBuffer::WriteU32(uint32_t data) [member function]
cls.add_method('WriteU32',
'void',
[param('uint32_t', 'data')])
## tag-buffer.h (module 'network'): void ns3::TagBuffer::WriteU64(uint64_t v) [member function]
cls.add_method('WriteU64',
'void',
[param('uint64_t', 'v')])
## tag-buffer.h (module 'network'): void ns3::TagBuffer::WriteU8(uint8_t v) [member function]
cls.add_method('WriteU8',
'void',
[param('uint8_t', 'v')])
return
def register_Ns3TimeWithUnit_methods(root_module, cls):
cls.add_output_stream_operator()
## nstime.h (module 'core'): ns3::TimeWithUnit::TimeWithUnit(ns3::TimeWithUnit const & arg0) [copy constructor]
cls.add_constructor([param('ns3::TimeWithUnit const &', 'arg0')])
## nstime.h (module 'core'): ns3::TimeWithUnit::TimeWithUnit(ns3::Time const time, ns3::Time::Unit const unit) [constructor]
cls.add_constructor([param('ns3::Time const', 'time'), param('ns3::Time::Unit const', 'unit')])
return
def register_Ns3TypeId_methods(root_module, cls):
cls.add_binary_comparison_operator('<')
cls.add_binary_comparison_operator('!=')
cls.add_output_stream_operator()
cls.add_binary_comparison_operator('==')
## type-id.h (module 'core'): ns3::TypeId::TypeId(char const * name) [constructor]
cls.add_constructor([param('char const *', 'name')])
## type-id.h (module 'core'): ns3::TypeId::TypeId() [constructor]
cls.add_constructor([])
## type-id.h (module 'core'): ns3::TypeId::TypeId(ns3::TypeId const & o) [copy constructor]
cls.add_constructor([param('ns3::TypeId const &', 'o')])
## type-id.h (module 'core'): ns3::TypeId ns3::TypeId::AddAttribute(std::string name, std::string help, ns3::AttributeValue const & initialValue, ns3::Ptr<ns3::AttributeAccessor const> accessor, ns3::Ptr<ns3::AttributeChecker const> checker, ns3::TypeId::SupportLevel supportLevel=::ns3::TypeId::SUPPORTED, std::string const & supportMsg="") [member function]
cls.add_method('AddAttribute',
'ns3::TypeId',
[param('std::string', 'name'), param('std::string', 'help'), param('ns3::AttributeValue const &', 'initialValue'), param('ns3::Ptr< ns3::AttributeAccessor const >', 'accessor'), param('ns3::Ptr< ns3::AttributeChecker const >', 'checker'), param('ns3::TypeId::SupportLevel', 'supportLevel', default_value='::ns3::TypeId::SUPPORTED'), param('std::string const &', 'supportMsg', default_value='""')])
## type-id.h (module 'core'): ns3::TypeId ns3::TypeId::AddAttribute(std::string name, std::string help, uint32_t flags, ns3::AttributeValue const & initialValue, ns3::Ptr<ns3::AttributeAccessor const> accessor, ns3::Ptr<ns3::AttributeChecker const> checker, ns3::TypeId::SupportLevel supportLevel=::ns3::TypeId::SUPPORTED, std::string const & supportMsg="") [member function]
cls.add_method('AddAttribute',
'ns3::TypeId',
[param('std::string', 'name'), param('std::string', 'help'), param('uint32_t', 'flags'), param('ns3::AttributeValue const &', 'initialValue'), param('ns3::Ptr< ns3::AttributeAccessor const >', 'accessor'), param('ns3::Ptr< ns3::AttributeChecker const >', 'checker'), param('ns3::TypeId::SupportLevel', 'supportLevel', default_value='::ns3::TypeId::SUPPORTED'), param('std::string const &', 'supportMsg', default_value='""')])
## type-id.h (module 'core'): ns3::TypeId ns3::TypeId::AddTraceSource(std::string name, std::string help, ns3::Ptr<ns3::TraceSourceAccessor const> accessor) [member function]
cls.add_method('AddTraceSource',
'ns3::TypeId',
[param('std::string', 'name'), param('std::string', 'help'), param('ns3::Ptr< ns3::TraceSourceAccessor const >', 'accessor')],
deprecated=True)
## type-id.h (module 'core'): ns3::TypeId ns3::TypeId::AddTraceSource(std::string name, std::string help, ns3::Ptr<ns3::TraceSourceAccessor const> accessor, std::string callback, ns3::TypeId::SupportLevel supportLevel=::ns3::TypeId::SUPPORTED, std::string const & supportMsg="") [member function]
cls.add_method('AddTraceSource',
'ns3::TypeId',
[param('std::string', 'name'), param('std::string', 'help'), param('ns3::Ptr< ns3::TraceSourceAccessor const >', 'accessor'), param('std::string', 'callback'), param('ns3::TypeId::SupportLevel', 'supportLevel', default_value='::ns3::TypeId::SUPPORTED'), param('std::string const &', 'supportMsg', default_value='""')])
## type-id.h (module 'core'): ns3::TypeId::AttributeInformation ns3::TypeId::GetAttribute(uint32_t i) const [member function]
cls.add_method('GetAttribute',
'ns3::TypeId::AttributeInformation',
[param('uint32_t', 'i')],
is_const=True)
## type-id.h (module 'core'): std::string ns3::TypeId::GetAttributeFullName(uint32_t i) const [member function]
cls.add_method('GetAttributeFullName',
'std::string',
[param('uint32_t', 'i')],
is_const=True)
## type-id.h (module 'core'): uint32_t ns3::TypeId::GetAttributeN() const [member function]
cls.add_method('GetAttributeN',
'uint32_t',
[],
is_const=True)
## type-id.h (module 'core'): ns3::Callback<ns3::ObjectBase*,ns3::empty,ns3::empty,ns3::empty,ns3::empty,ns3::empty,ns3::empty,ns3::empty,ns3::empty,ns3::empty> ns3::TypeId::GetConstructor() const [member function]
cls.add_method('GetConstructor',
'ns3::Callback< ns3::ObjectBase *, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty >',
[],
is_const=True)
## type-id.h (module 'core'): std::string ns3::TypeId::GetGroupName() const [member function]
cls.add_method('GetGroupName',
'std::string',
[],
is_const=True)
## type-id.h (module 'core'): uint32_t ns3::TypeId::GetHash() const [member function]
cls.add_method('GetHash',
'uint32_t',
[],
is_const=True)
## type-id.h (module 'core'): std::string ns3::TypeId::GetName() const [member function]
cls.add_method('GetName',
'std::string',
[],
is_const=True)
## type-id.h (module 'core'): ns3::TypeId ns3::TypeId::GetParent() const [member function]
cls.add_method('GetParent',
'ns3::TypeId',
[],
is_const=True)
## type-id.h (module 'core'): static ns3::TypeId ns3::TypeId::GetRegistered(uint32_t i) [member function]
cls.add_method('GetRegistered',
'ns3::TypeId',
[param('uint32_t', 'i')],
is_static=True)
## type-id.h (module 'core'): static uint32_t ns3::TypeId::GetRegisteredN() [member function]
cls.add_method('GetRegisteredN',
'uint32_t',
[],
is_static=True)
## type-id.h (module 'core'): std::size_t ns3::TypeId::GetSize() const [member function]
cls.add_method('GetSize',
'std::size_t',
[],
is_const=True)
## type-id.h (module 'core'): ns3::TypeId::TraceSourceInformation ns3::TypeId::GetTraceSource(uint32_t i) const [member function]
cls.add_method('GetTraceSource',
'ns3::TypeId::TraceSourceInformation',
[param('uint32_t', 'i')],
is_const=True)
## type-id.h (module 'core'): uint32_t ns3::TypeId::GetTraceSourceN() const [member function]
cls.add_method('GetTraceSourceN',
'uint32_t',
[],
is_const=True)
## type-id.h (module 'core'): uint16_t ns3::TypeId::GetUid() const [member function]
cls.add_method('GetUid',
'uint16_t',
[],
is_const=True)
## type-id.h (module 'core'): bool ns3::TypeId::HasConstructor() const [member function]
cls.add_method('HasConstructor',
'bool',
[],
is_const=True)
## type-id.h (module 'core'): bool ns3::TypeId::HasParent() const [member function]
cls.add_method('HasParent',
'bool',
[],
is_const=True)
## type-id.h (module 'core'): ns3::TypeId ns3::TypeId::HideFromDocumentation() [member function]
cls.add_method('HideFromDocumentation',
'ns3::TypeId',
[])
## type-id.h (module 'core'): bool ns3::TypeId::IsChildOf(ns3::TypeId other) const [member function]
cls.add_method('IsChildOf',
'bool',
[param('ns3::TypeId', 'other')],
is_const=True)
## type-id.h (module 'core'): bool ns3::TypeId::LookupAttributeByName(std::string name, ns3::TypeId::AttributeInformation * info) const [member function]
cls.add_method('LookupAttributeByName',
'bool',
[param('std::string', 'name'), param('ns3::TypeId::AttributeInformation *', 'info', transfer_ownership=False)],
is_const=True)
## type-id.h (module 'core'): static ns3::TypeId ns3::TypeId::LookupByHash(uint32_t hash) [member function]
cls.add_method('LookupByHash',
'ns3::TypeId',
[param('uint32_t', 'hash')],
is_static=True)
## type-id.h (module 'core'): static bool ns3::TypeId::LookupByHashFailSafe(uint32_t hash, ns3::TypeId * tid) [member function]
cls.add_method('LookupByHashFailSafe',
'bool',
[param('uint32_t', 'hash'), param('ns3::TypeId *', 'tid')],
is_static=True)
## type-id.h (module 'core'): static ns3::TypeId ns3::TypeId::LookupByName(std::string name) [member function]
cls.add_method('LookupByName',
'ns3::TypeId',
[param('std::string', 'name')],
is_static=True)
## type-id.h (module 'core'): ns3::Ptr<ns3::TraceSourceAccessor const> ns3::TypeId::LookupTraceSourceByName(std::string name) const [member function]
cls.add_method('LookupTraceSourceByName',
'ns3::Ptr< ns3::TraceSourceAccessor const >',
[param('std::string', 'name')],
is_const=True)
## type-id.h (module 'core'): ns3::Ptr<ns3::TraceSourceAccessor const> ns3::TypeId::LookupTraceSourceByName(std::string name, ns3::TypeId::TraceSourceInformation * info) const [member function]
cls.add_method('LookupTraceSourceByName',
'ns3::Ptr< ns3::TraceSourceAccessor const >',
[param('std::string', 'name'), param('ns3::TypeId::TraceSourceInformation *', 'info')],
is_const=True)
## type-id.h (module 'core'): bool ns3::TypeId::MustHideFromDocumentation() const [member function]
cls.add_method('MustHideFromDocumentation',
'bool',
[],
is_const=True)
## type-id.h (module 'core'): bool ns3::TypeId::SetAttributeInitialValue(uint32_t i, ns3::Ptr<ns3::AttributeValue const> initialValue) [member function]
cls.add_method('SetAttributeInitialValue',
'bool',
[param('uint32_t', 'i'), param('ns3::Ptr< ns3::AttributeValue const >', 'initialValue')])
## type-id.h (module 'core'): ns3::TypeId ns3::TypeId::SetGroupName(std::string groupName) [member function]
cls.add_method('SetGroupName',
'ns3::TypeId',
[param('std::string', 'groupName')])
## type-id.h (module 'core'): ns3::TypeId ns3::TypeId::SetParent(ns3::TypeId tid) [member function]
cls.add_method('SetParent',
'ns3::TypeId',
[param('ns3::TypeId', 'tid')])
## type-id.h (module 'core'): ns3::TypeId ns3::TypeId::SetSize(std::size_t size) [member function]
cls.add_method('SetSize',
'ns3::TypeId',
[param('std::size_t', 'size')])
## type-id.h (module 'core'): void ns3::TypeId::SetUid(uint16_t uid) [member function]
cls.add_method('SetUid',
'void',
[param('uint16_t', 'uid')])
return
def register_Ns3TypeIdAttributeInformation_methods(root_module, cls):
## type-id.h (module 'core'): ns3::TypeId::AttributeInformation::AttributeInformation() [constructor]
cls.add_constructor([])
## type-id.h (module 'core'): ns3::TypeId::AttributeInformation::AttributeInformation(ns3::TypeId::AttributeInformation const & arg0) [copy constructor]
cls.add_constructor([param('ns3::TypeId::AttributeInformation const &', 'arg0')])
## type-id.h (module 'core'): ns3::TypeId::AttributeInformation::accessor [variable]
cls.add_instance_attribute('accessor', 'ns3::Ptr< ns3::AttributeAccessor const >', is_const=False)
## type-id.h (module 'core'): ns3::TypeId::AttributeInformation::checker [variable]
cls.add_instance_attribute('checker', 'ns3::Ptr< ns3::AttributeChecker const >', is_const=False)
## type-id.h (module 'core'): ns3::TypeId::AttributeInformation::flags [variable]
cls.add_instance_attribute('flags', 'uint32_t', is_const=False)
## type-id.h (module 'core'): ns3::TypeId::AttributeInformation::help [variable]
cls.add_instance_attribute('help', 'std::string', is_const=False)
## type-id.h (module 'core'): ns3::TypeId::AttributeInformation::initialValue [variable]
cls.add_instance_attribute('initialValue', 'ns3::Ptr< ns3::AttributeValue const >', is_const=False)
## type-id.h (module 'core'): ns3::TypeId::AttributeInformation::name [variable]
cls.add_instance_attribute('name', 'std::string', is_const=False)
## type-id.h (module 'core'): ns3::TypeId::AttributeInformation::originalInitialValue [variable]
cls.add_instance_attribute('originalInitialValue', 'ns3::Ptr< ns3::AttributeValue const >', is_const=False)
## type-id.h (module 'core'): ns3::TypeId::AttributeInformation::supportLevel [variable]
cls.add_instance_attribute('supportLevel', 'ns3::TypeId::SupportLevel', is_const=False)
## type-id.h (module 'core'): ns3::TypeId::AttributeInformation::supportMsg [variable]
cls.add_instance_attribute('supportMsg', 'std::string', is_const=False)
return
def register_Ns3TypeIdTraceSourceInformation_methods(root_module, cls):
## type-id.h (module 'core'): ns3::TypeId::TraceSourceInformation::TraceSourceInformation() [constructor]
cls.add_constructor([])
## type-id.h (module 'core'): ns3::TypeId::TraceSourceInformation::TraceSourceInformation(ns3::TypeId::TraceSourceInformation const & arg0) [copy constructor]
cls.add_constructor([param('ns3::TypeId::TraceSourceInformation const &', 'arg0')])
## type-id.h (module 'core'): ns3::TypeId::TraceSourceInformation::accessor [variable]
cls.add_instance_attribute('accessor', 'ns3::Ptr< ns3::TraceSourceAccessor const >', is_const=False)
## type-id.h (module 'core'): ns3::TypeId::TraceSourceInformation::callback [variable]
cls.add_instance_attribute('callback', 'std::string', is_const=False)
## type-id.h (module 'core'): ns3::TypeId::TraceSourceInformation::help [variable]
cls.add_instance_attribute('help', 'std::string', is_const=False)
## type-id.h (module 'core'): ns3::TypeId::TraceSourceInformation::name [variable]
cls.add_instance_attribute('name', 'std::string', is_const=False)
## type-id.h (module 'core'): ns3::TypeId::TraceSourceInformation::supportLevel [variable]
cls.add_instance_attribute('supportLevel', 'ns3::TypeId::SupportLevel', is_const=False)
## type-id.h (module 'core'): ns3::TypeId::TraceSourceInformation::supportMsg [variable]
cls.add_instance_attribute('supportMsg', 'std::string', is_const=False)
return
def register_Ns3Empty_methods(root_module, cls):
## empty.h (module 'core'): ns3::empty::empty() [constructor]
cls.add_constructor([])
## empty.h (module 'core'): ns3::empty::empty(ns3::empty const & arg0) [copy constructor]
cls.add_constructor([param('ns3::empty const &', 'arg0')])
return
def register_Ns3Int64x64_t_methods(root_module, cls):
cls.add_binary_numeric_operator('*', root_module['ns3::int64x64_t'], root_module['ns3::int64x64_t'], param('ns3::int64x64_t const &', u'right'))
cls.add_binary_numeric_operator('+', root_module['ns3::int64x64_t'], root_module['ns3::int64x64_t'], param('ns3::int64x64_t const &', u'right'))
cls.add_binary_numeric_operator('-', root_module['ns3::int64x64_t'], root_module['ns3::int64x64_t'], param('ns3::int64x64_t const &', u'right'))
cls.add_unary_numeric_operator('-')
cls.add_binary_numeric_operator('/', root_module['ns3::int64x64_t'], root_module['ns3::int64x64_t'], param('ns3::int64x64_t const &', u'right'))
cls.add_binary_comparison_operator('<')
cls.add_binary_comparison_operator('>')
cls.add_binary_comparison_operator('!=')
cls.add_inplace_numeric_operator('*=', param('ns3::int64x64_t const &', u'right'))
cls.add_inplace_numeric_operator('+=', param('ns3::int64x64_t const &', u'right'))
cls.add_inplace_numeric_operator('-=', param('ns3::int64x64_t const &', u'right'))
cls.add_inplace_numeric_operator('/=', param('ns3::int64x64_t const &', u'right'))
cls.add_output_stream_operator()
cls.add_binary_comparison_operator('<=')
cls.add_binary_comparison_operator('==')
cls.add_binary_comparison_operator('>=')
## int64x64-double.h (module 'core'): ns3::int64x64_t::int64x64_t() [constructor]
cls.add_constructor([])
## int64x64-double.h (module 'core'): ns3::int64x64_t::int64x64_t(double v) [constructor]
cls.add_constructor([param('double', 'v')])
## int64x64-double.h (module 'core'): ns3::int64x64_t::int64x64_t(long double v) [constructor]
cls.add_constructor([param('long double', 'v')])
## int64x64-double.h (module 'core'): ns3::int64x64_t::int64x64_t(int v) [constructor]
cls.add_constructor([param('int', 'v')])
## int64x64-double.h (module 'core'): ns3::int64x64_t::int64x64_t(long int v) [constructor]
cls.add_constructor([param('long int', 'v')])
## int64x64-double.h (module 'core'): ns3::int64x64_t::int64x64_t(long long int v) [constructor]
cls.add_constructor([param('long long int', 'v')])
## int64x64-double.h (module 'core'): ns3::int64x64_t::int64x64_t(unsigned int v) [constructor]
cls.add_constructor([param('unsigned int', 'v')])
## int64x64-double.h (module 'core'): ns3::int64x64_t::int64x64_t(long unsigned int v) [constructor]
cls.add_constructor([param('long unsigned int', 'v')])
## int64x64-double.h (module 'core'): ns3::int64x64_t::int64x64_t(long long unsigned int v) [constructor]
cls.add_constructor([param('long long unsigned int', 'v')])
## int64x64-double.h (module 'core'): ns3::int64x64_t::int64x64_t(int64_t hi, uint64_t lo) [constructor]
cls.add_constructor([param('int64_t', 'hi'), param('uint64_t', 'lo')])
## int64x64-double.h (module 'core'): ns3::int64x64_t::int64x64_t(ns3::int64x64_t const & o) [copy constructor]
cls.add_constructor([param('ns3::int64x64_t const &', 'o')])
## int64x64-double.h (module 'core'): double ns3::int64x64_t::GetDouble() const [member function]
cls.add_method('GetDouble',
'double',
[],
is_const=True)
## int64x64-double.h (module 'core'): int64_t ns3::int64x64_t::GetHigh() const [member function]
cls.add_method('GetHigh',
'int64_t',
[],
is_const=True)
## int64x64-double.h (module 'core'): uint64_t ns3::int64x64_t::GetLow() const [member function]
cls.add_method('GetLow',
'uint64_t',
[],
is_const=True)
## int64x64-double.h (module 'core'): static ns3::int64x64_t ns3::int64x64_t::Invert(uint64_t v) [member function]
cls.add_method('Invert',
'ns3::int64x64_t',
[param('uint64_t', 'v')],
is_static=True)
## int64x64-double.h (module 'core'): void ns3::int64x64_t::MulByInvert(ns3::int64x64_t const & o) [member function]
cls.add_method('MulByInvert',
'void',
[param('ns3::int64x64_t const &', 'o')])
## int64x64-double.h (module 'core'): ns3::int64x64_t::implementation [variable]
cls.add_static_attribute('implementation', 'ns3::int64x64_t::impl_type const', is_const=True)
return
def register_Ns3Chunk_methods(root_module, cls):
## chunk.h (module 'network'): ns3::Chunk::Chunk() [constructor]
cls.add_constructor([])
## chunk.h (module 'network'): ns3::Chunk::Chunk(ns3::Chunk const & arg0) [copy constructor]
cls.add_constructor([param('ns3::Chunk const &', 'arg0')])
## chunk.h (module 'network'): uint32_t ns3::Chunk::Deserialize(ns3::Buffer::Iterator start) [member function]
cls.add_method('Deserialize',
'uint32_t',
[param('ns3::Buffer::Iterator', 'start')],
is_pure_virtual=True, is_virtual=True)
## chunk.h (module 'network'): static ns3::TypeId ns3::Chunk::GetTypeId() [member function]
cls.add_method('GetTypeId',
'ns3::TypeId',
[],
is_static=True)
## chunk.h (module 'network'): void ns3::Chunk::Print(std::ostream & os) const [member function]
cls.add_method('Print',
'void',
[param('std::ostream &', 'os')],
is_pure_virtual=True, is_const=True, is_virtual=True)
return
def register_Ns3Header_methods(root_module, cls):
cls.add_output_stream_operator()
## header.h (module 'network'): ns3::Header::Header() [constructor]
cls.add_constructor([])
## header.h (module 'network'): ns3::Header::Header(ns3::Header const & arg0) [copy constructor]
cls.add_constructor([param('ns3::Header const &', 'arg0')])
## header.h (module 'network'): uint32_t ns3::Header::Deserialize(ns3::Buffer::Iterator start) [member function]
cls.add_method('Deserialize',
'uint32_t',
[param('ns3::Buffer::Iterator', 'start')],
is_pure_virtual=True, is_virtual=True)
## header.h (module 'network'): uint32_t ns3::Header::GetSerializedSize() const [member function]
cls.add_method('GetSerializedSize',
'uint32_t',
[],
is_pure_virtual=True, is_const=True, is_virtual=True)
## header.h (module 'network'): static ns3::TypeId ns3::Header::GetTypeId() [member function]
cls.add_method('GetTypeId',
'ns3::TypeId',
[],
is_static=True)
## header.h (module 'network'): void ns3::Header::Print(std::ostream & os) const [member function]
cls.add_method('Print',
'void',
[param('std::ostream &', 'os')],
is_pure_virtual=True, is_const=True, is_virtual=True)
## header.h (module 'network'): void ns3::Header::Serialize(ns3::Buffer::Iterator start) const [member function]
cls.add_method('Serialize',
'void',
[param('ns3::Buffer::Iterator', 'start')],
is_pure_virtual=True, is_const=True, is_virtual=True)
return
def register_Ns3Ipv4Header_methods(root_module, cls):
## ipv4-header.h (module 'internet'): ns3::Ipv4Header::Ipv4Header(ns3::Ipv4Header const & arg0) [copy constructor]
cls.add_constructor([param('ns3::Ipv4Header const &', 'arg0')])
## ipv4-header.h (module 'internet'): ns3::Ipv4Header::Ipv4Header() [constructor]
cls.add_constructor([])
## ipv4-header.h (module 'internet'): uint32_t ns3::Ipv4Header::Deserialize(ns3::Buffer::Iterator start) [member function]
cls.add_method('Deserialize',
'uint32_t',
[param('ns3::Buffer::Iterator', 'start')],
is_virtual=True)
## ipv4-header.h (module 'internet'): std::string ns3::Ipv4Header::DscpTypeToString(ns3::Ipv4Header::DscpType dscp) const [member function]
cls.add_method('DscpTypeToString',
'std::string',
[param('ns3::Ipv4Header::DscpType', 'dscp')],
is_const=True)
## ipv4-header.h (module 'internet'): std::string ns3::Ipv4Header::EcnTypeToString(ns3::Ipv4Header::EcnType ecn) const [member function]
cls.add_method('EcnTypeToString',
'std::string',
[param('ns3::Ipv4Header::EcnType', 'ecn')],
is_const=True)
## ipv4-header.h (module 'internet'): void ns3::Ipv4Header::EnableChecksum() [member function]
cls.add_method('EnableChecksum',
'void',
[])
## ipv4-header.h (module 'internet'): ns3::Ipv4Address ns3::Ipv4Header::GetDestination() const [member function]
cls.add_method('GetDestination',
'ns3::Ipv4Address',
[],
is_const=True)
## ipv4-header.h (module 'internet'): ns3::Ipv4Header::DscpType ns3::Ipv4Header::GetDscp() const [member function]
cls.add_method('GetDscp',
'ns3::Ipv4Header::DscpType',
[],
is_const=True)
## ipv4-header.h (module 'internet'): ns3::Ipv4Header::EcnType ns3::Ipv4Header::GetEcn() const [member function]
cls.add_method('GetEcn',
'ns3::Ipv4Header::EcnType',
[],
is_const=True)
## ipv4-header.h (module 'internet'): uint16_t ns3::Ipv4Header::GetFragmentOffset() const [member function]
cls.add_method('GetFragmentOffset',
'uint16_t',
[],
is_const=True)
## ipv4-header.h (module 'internet'): uint16_t ns3::Ipv4Header::GetIdentification() const [member function]
cls.add_method('GetIdentification',
'uint16_t',
[],
is_const=True)
## ipv4-header.h (module 'internet'): ns3::TypeId ns3::Ipv4Header::GetInstanceTypeId() const [member function]
cls.add_method('GetInstanceTypeId',
'ns3::TypeId',
[],
is_const=True, is_virtual=True)
## ipv4-header.h (module 'internet'): uint16_t ns3::Ipv4Header::GetPayloadSize() const [member function]
cls.add_method('GetPayloadSize',
'uint16_t',
[],
is_const=True)
## ipv4-header.h (module 'internet'): uint8_t ns3::Ipv4Header::GetProtocol() const [member function]
cls.add_method('GetProtocol',
'uint8_t',
[],
is_const=True)
## ipv4-header.h (module 'internet'): uint32_t ns3::Ipv4Header::GetSerializedSize() const [member function]
cls.add_method('GetSerializedSize',
'uint32_t',
[],
is_const=True, is_virtual=True)
## ipv4-header.h (module 'internet'): ns3::Ipv4Address ns3::Ipv4Header::GetSource() const [member function]
cls.add_method('GetSource',
'ns3::Ipv4Address',
[],
is_const=True)
## ipv4-header.h (module 'internet'): uint8_t ns3::Ipv4Header::GetTos() const [member function]
cls.add_method('GetTos',
'uint8_t',
[],
is_const=True)
## ipv4-header.h (module 'internet'): uint8_t ns3::Ipv4Header::GetTtl() const [member function]
cls.add_method('GetTtl',
'uint8_t',
[],
is_const=True)
## ipv4-header.h (module 'internet'): static ns3::TypeId ns3::Ipv4Header::GetTypeId() [member function]
cls.add_method('GetTypeId',
'ns3::TypeId',
[],
is_static=True)
## ipv4-header.h (module 'internet'): bool ns3::Ipv4Header::IsChecksumOk() const [member function]
cls.add_method('IsChecksumOk',
'bool',
[],
is_const=True)
## ipv4-header.h (module 'internet'): bool ns3::Ipv4Header::IsDontFragment() const [member function]
cls.add_method('IsDontFragment',
'bool',
[],
is_const=True)
## ipv4-header.h (module 'internet'): bool ns3::Ipv4Header::IsLastFragment() const [member function]
cls.add_method('IsLastFragment',
'bool',
[],
is_const=True)
## ipv4-header.h (module 'internet'): void ns3::Ipv4Header::Print(std::ostream & os) const [member function]
cls.add_method('Print',
'void',
[param('std::ostream &', 'os')],
is_const=True, is_virtual=True)
## ipv4-header.h (module 'internet'): void ns3::Ipv4Header::Serialize(ns3::Buffer::Iterator start) const [member function]
cls.add_method('Serialize',
'void',
[param('ns3::Buffer::Iterator', 'start')],
is_const=True, is_virtual=True)
## ipv4-header.h (module 'internet'): void ns3::Ipv4Header::SetDestination(ns3::Ipv4Address destination) [member function]
cls.add_method('SetDestination',
'void',
[param('ns3::Ipv4Address', 'destination')])
## ipv4-header.h (module 'internet'): void ns3::Ipv4Header::SetDontFragment() [member function]
cls.add_method('SetDontFragment',
'void',
[])
## ipv4-header.h (module 'internet'): void ns3::Ipv4Header::SetDscp(ns3::Ipv4Header::DscpType dscp) [member function]
cls.add_method('SetDscp',
'void',
[param('ns3::Ipv4Header::DscpType', 'dscp')])
## ipv4-header.h (module 'internet'): void ns3::Ipv4Header::SetEcn(ns3::Ipv4Header::EcnType ecn) [member function]
cls.add_method('SetEcn',
'void',
[param('ns3::Ipv4Header::EcnType', 'ecn')])
## ipv4-header.h (module 'internet'): void ns3::Ipv4Header::SetFragmentOffset(uint16_t offsetBytes) [member function]
cls.add_method('SetFragmentOffset',
'void',
[param('uint16_t', 'offsetBytes')])
## ipv4-header.h (module 'internet'): void ns3::Ipv4Header::SetIdentification(uint16_t identification) [member function]
cls.add_method('SetIdentification',
'void',
[param('uint16_t', 'identification')])
## ipv4-header.h (module 'internet'): void ns3::Ipv4Header::SetLastFragment() [member function]
cls.add_method('SetLastFragment',
'void',
[])
## ipv4-header.h (module 'internet'): void ns3::Ipv4Header::SetMayFragment() [member function]
cls.add_method('SetMayFragment',
'void',
[])
## ipv4-header.h (module 'internet'): void ns3::Ipv4Header::SetMoreFragments() [member function]
cls.add_method('SetMoreFragments',
'void',
[])
## ipv4-header.h (module 'internet'): void ns3::Ipv4Header::SetPayloadSize(uint16_t size) [member function]
cls.add_method('SetPayloadSize',
'void',
[param('uint16_t', 'size')])
## ipv4-header.h (module 'internet'): void ns3::Ipv4Header::SetProtocol(uint8_t num) [member function]
cls.add_method('SetProtocol',
'void',
[param('uint8_t', 'num')])
## ipv4-header.h (module 'internet'): void ns3::Ipv4Header::SetSource(ns3::Ipv4Address source) [member function]
cls.add_method('SetSource',
'void',
[param('ns3::Ipv4Address', 'source')])
## ipv4-header.h (module 'internet'): void ns3::Ipv4Header::SetTos(uint8_t tos) [member function]
cls.add_method('SetTos',
'void',
[param('uint8_t', 'tos')])
## ipv4-header.h (module 'internet'): void ns3::Ipv4Header::SetTtl(uint8_t ttl) [member function]
cls.add_method('SetTtl',
'void',
[param('uint8_t', 'ttl')])
return
def register_Ns3Object_methods(root_module, cls):
## object.h (module 'core'): ns3::Object::Object() [constructor]
cls.add_constructor([])
## object.h (module 'core'): void ns3::Object::AggregateObject(ns3::Ptr<ns3::Object> other) [member function]
cls.add_method('AggregateObject',
'void',
[param('ns3::Ptr< ns3::Object >', 'other')])
## object.h (module 'core'): void ns3::Object::Dispose() [member function]
cls.add_method('Dispose',
'void',
[])
## object.h (module 'core'): ns3::Object::AggregateIterator ns3::Object::GetAggregateIterator() const [member function]
cls.add_method('GetAggregateIterator',
'ns3::Object::AggregateIterator',
[],
is_const=True)
## object.h (module 'core'): ns3::TypeId ns3::Object::GetInstanceTypeId() const [member function]
cls.add_method('GetInstanceTypeId',
'ns3::TypeId',
[],
is_const=True, is_virtual=True)
## object.h (module 'core'): static ns3::TypeId ns3::Object::GetTypeId() [member function]
cls.add_method('GetTypeId',
'ns3::TypeId',
[],
is_static=True)
## object.h (module 'core'): void ns3::Object::Initialize() [member function]
cls.add_method('Initialize',
'void',
[])
## object.h (module 'core'): bool ns3::Object::IsInitialized() const [member function]
cls.add_method('IsInitialized',
'bool',
[],
is_const=True)
## object.h (module 'core'): ns3::Object::Object(ns3::Object const & o) [copy constructor]
cls.add_constructor([param('ns3::Object const &', 'o')],
visibility='protected')
## object.h (module 'core'): void ns3::Object::DoDispose() [member function]
cls.add_method('DoDispose',
'void',
[],
visibility='protected', is_virtual=True)
## object.h (module 'core'): void ns3::Object::DoInitialize() [member function]
cls.add_method('DoInitialize',
'void',
[],
visibility='protected', is_virtual=True)
## object.h (module 'core'): void ns3::Object::NotifyNewAggregate() [member function]
cls.add_method('NotifyNewAggregate',
'void',
[],
visibility='protected', is_virtual=True)
return
def register_Ns3ObjectAggregateIterator_methods(root_module, cls):
## object.h (module 'core'): ns3::Object::AggregateIterator::AggregateIterator(ns3::Object::AggregateIterator const & arg0) [copy constructor]
cls.add_constructor([param('ns3::Object::AggregateIterator const &', 'arg0')])
## object.h (module 'core'): ns3::Object::AggregateIterator::AggregateIterator() [constructor]
cls.add_constructor([])
## object.h (module 'core'): bool ns3::Object::AggregateIterator::HasNext() const [member function]
cls.add_method('HasNext',
'bool',
[],
is_const=True)
## object.h (module 'core'): ns3::Ptr<ns3::Object const> ns3::Object::AggregateIterator::Next() [member function]
cls.add_method('Next',
'ns3::Ptr< ns3::Object const >',
[])
return
def register_Ns3SimpleRefCount__Ns3AttributeAccessor_Ns3Empty_Ns3DefaultDeleter__lt__ns3AttributeAccessor__gt___methods(root_module, cls):
## simple-ref-count.h (module 'core'): ns3::SimpleRefCount<ns3::AttributeAccessor, ns3::empty, ns3::DefaultDeleter<ns3::AttributeAccessor> >::SimpleRefCount() [constructor]
cls.add_constructor([])
## simple-ref-count.h (module 'core'): ns3::SimpleRefCount<ns3::AttributeAccessor, ns3::empty, ns3::DefaultDeleter<ns3::AttributeAccessor> >::SimpleRefCount(ns3::SimpleRefCount<ns3::AttributeAccessor, ns3::empty, ns3::DefaultDeleter<ns3::AttributeAccessor> > const & o) [copy constructor]
cls.add_constructor([param('ns3::SimpleRefCount< ns3::AttributeAccessor, ns3::empty, ns3::DefaultDeleter< ns3::AttributeAccessor > > const &', 'o')])
## simple-ref-count.h (module 'core'): static void ns3::SimpleRefCount<ns3::AttributeAccessor, ns3::empty, ns3::DefaultDeleter<ns3::AttributeAccessor> >::Cleanup() [member function]
cls.add_method('Cleanup',
'void',
[],
is_static=True)
return
def register_Ns3SimpleRefCount__Ns3AttributeChecker_Ns3Empty_Ns3DefaultDeleter__lt__ns3AttributeChecker__gt___methods(root_module, cls):
## simple-ref-count.h (module 'core'): ns3::SimpleRefCount<ns3::AttributeChecker, ns3::empty, ns3::DefaultDeleter<ns3::AttributeChecker> >::SimpleRefCount() [constructor]
cls.add_constructor([])
## simple-ref-count.h (module 'core'): ns3::SimpleRefCount<ns3::AttributeChecker, ns3::empty, ns3::DefaultDeleter<ns3::AttributeChecker> >::SimpleRefCount(ns3::SimpleRefCount<ns3::AttributeChecker, ns3::empty, ns3::DefaultDeleter<ns3::AttributeChecker> > const & o) [copy constructor]
cls.add_constructor([param('ns3::SimpleRefCount< ns3::AttributeChecker, ns3::empty, ns3::DefaultDeleter< ns3::AttributeChecker > > const &', 'o')])
## simple-ref-count.h (module 'core'): static void ns3::SimpleRefCount<ns3::AttributeChecker, ns3::empty, ns3::DefaultDeleter<ns3::AttributeChecker> >::Cleanup() [member function]
cls.add_method('Cleanup',
'void',
[],
is_static=True)
return
def register_Ns3SimpleRefCount__Ns3AttributeValue_Ns3Empty_Ns3DefaultDeleter__lt__ns3AttributeValue__gt___methods(root_module, cls):
## simple-ref-count.h (module 'core'): ns3::SimpleRefCount<ns3::AttributeValue, ns3::empty, ns3::DefaultDeleter<ns3::AttributeValue> >::SimpleRefCount() [constructor]
cls.add_constructor([])
## simple-ref-count.h (module 'core'): ns3::SimpleRefCount<ns3::AttributeValue, ns3::empty, ns3::DefaultDeleter<ns3::AttributeValue> >::SimpleRefCount(ns3::SimpleRefCount<ns3::AttributeValue, ns3::empty, ns3::DefaultDeleter<ns3::AttributeValue> > const & o) [copy constructor]
cls.add_constructor([param('ns3::SimpleRefCount< ns3::AttributeValue, ns3::empty, ns3::DefaultDeleter< ns3::AttributeValue > > const &', 'o')])
## simple-ref-count.h (module 'core'): static void ns3::SimpleRefCount<ns3::AttributeValue, ns3::empty, ns3::DefaultDeleter<ns3::AttributeValue> >::Cleanup() [member function]
cls.add_method('Cleanup',
'void',
[],
is_static=True)
return
def register_Ns3SimpleRefCount__Ns3CallbackImplBase_Ns3Empty_Ns3DefaultDeleter__lt__ns3CallbackImplBase__gt___methods(root_module, cls):
## simple-ref-count.h (module 'core'): ns3::SimpleRefCount<ns3::CallbackImplBase, ns3::empty, ns3::DefaultDeleter<ns3::CallbackImplBase> >::SimpleRefCount() [constructor]
cls.add_constructor([])
## simple-ref-count.h (module 'core'): ns3::SimpleRefCount<ns3::CallbackImplBase, ns3::empty, ns3::DefaultDeleter<ns3::CallbackImplBase> >::SimpleRefCount(ns3::SimpleRefCount<ns3::CallbackImplBase, ns3::empty, ns3::DefaultDeleter<ns3::CallbackImplBase> > const & o) [copy constructor]
cls.add_constructor([param('ns3::SimpleRefCount< ns3::CallbackImplBase, ns3::empty, ns3::DefaultDeleter< ns3::CallbackImplBase > > const &', 'o')])
## simple-ref-count.h (module 'core'): static void ns3::SimpleRefCount<ns3::CallbackImplBase, ns3::empty, ns3::DefaultDeleter<ns3::CallbackImplBase> >::Cleanup() [member function]
cls.add_method('Cleanup',
'void',
[],
is_static=True)
return
def register_Ns3SimpleRefCount__Ns3EventImpl_Ns3Empty_Ns3DefaultDeleter__lt__ns3EventImpl__gt___methods(root_module, cls):
## simple-ref-count.h (module 'core'): ns3::SimpleRefCount<ns3::EventImpl, ns3::empty, ns3::DefaultDeleter<ns3::EventImpl> >::SimpleRefCount() [constructor]
cls.add_constructor([])
## simple-ref-count.h (module 'core'): ns3::SimpleRefCount<ns3::EventImpl, ns3::empty, ns3::DefaultDeleter<ns3::EventImpl> >::SimpleRefCount(ns3::SimpleRefCount<ns3::EventImpl, ns3::empty, ns3::DefaultDeleter<ns3::EventImpl> > const & o) [copy constructor]
cls.add_constructor([param('ns3::SimpleRefCount< ns3::EventImpl, ns3::empty, ns3::DefaultDeleter< ns3::EventImpl > > const &', 'o')])
## simple-ref-count.h (module 'core'): static void ns3::SimpleRefCount<ns3::EventImpl, ns3::empty, ns3::DefaultDeleter<ns3::EventImpl> >::Cleanup() [member function]
cls.add_method('Cleanup',
'void',
[],
is_static=True)
return
def register_Ns3SimpleRefCount__Ns3HashImplementation_Ns3Empty_Ns3DefaultDeleter__lt__ns3HashImplementation__gt___methods(root_module, cls):
## simple-ref-count.h (module 'core'): ns3::SimpleRefCount<ns3::Hash::Implementation, ns3::empty, ns3::DefaultDeleter<ns3::Hash::Implementation> >::SimpleRefCount() [constructor]
cls.add_constructor([])
## simple-ref-count.h (module 'core'): ns3::SimpleRefCount<ns3::Hash::Implementation, ns3::empty, ns3::DefaultDeleter<ns3::Hash::Implementation> >::SimpleRefCount(ns3::SimpleRefCount<ns3::Hash::Implementation, ns3::empty, ns3::DefaultDeleter<ns3::Hash::Implementation> > const & o) [copy constructor]
cls.add_constructor([param('ns3::SimpleRefCount< ns3::Hash::Implementation, ns3::empty, ns3::DefaultDeleter< ns3::Hash::Implementation > > const &', 'o')])
## simple-ref-count.h (module 'core'): static void ns3::SimpleRefCount<ns3::Hash::Implementation, ns3::empty, ns3::DefaultDeleter<ns3::Hash::Implementation> >::Cleanup() [member function]
cls.add_method('Cleanup',
'void',
[],
is_static=True)
return
def register_Ns3SimpleRefCount__Ns3Ipv4MulticastRoute_Ns3Empty_Ns3DefaultDeleter__lt__ns3Ipv4MulticastRoute__gt___methods(root_module, cls):
## simple-ref-count.h (module 'core'): ns3::SimpleRefCount<ns3::Ipv4MulticastRoute, ns3::empty, ns3::DefaultDeleter<ns3::Ipv4MulticastRoute> >::SimpleRefCount() [constructor]
cls.add_constructor([])
## simple-ref-count.h (module 'core'): ns3::SimpleRefCount<ns3::Ipv4MulticastRoute, ns3::empty, ns3::DefaultDeleter<ns3::Ipv4MulticastRoute> >::SimpleRefCount(ns3::SimpleRefCount<ns3::Ipv4MulticastRoute, ns3::empty, ns3::DefaultDeleter<ns3::Ipv4MulticastRoute> > const & o) [copy constructor]
cls.add_constructor([param('ns3::SimpleRefCount< ns3::Ipv4MulticastRoute, ns3::empty, ns3::DefaultDeleter< ns3::Ipv4MulticastRoute > > const &', 'o')])
## simple-ref-count.h (module 'core'): static void ns3::SimpleRefCount<ns3::Ipv4MulticastRoute, ns3::empty, ns3::DefaultDeleter<ns3::Ipv4MulticastRoute> >::Cleanup() [member function]
cls.add_method('Cleanup',
'void',
[],
is_static=True)
return
def register_Ns3SimpleRefCount__Ns3Ipv4Route_Ns3Empty_Ns3DefaultDeleter__lt__ns3Ipv4Route__gt___methods(root_module, cls):
## simple-ref-count.h (module 'core'): ns3::SimpleRefCount<ns3::Ipv4Route, ns3::empty, ns3::DefaultDeleter<ns3::Ipv4Route> >::SimpleRefCount() [constructor]
cls.add_constructor([])
## simple-ref-count.h (module 'core'): ns3::SimpleRefCount<ns3::Ipv4Route, ns3::empty, ns3::DefaultDeleter<ns3::Ipv4Route> >::SimpleRefCount(ns3::SimpleRefCount<ns3::Ipv4Route, ns3::empty, ns3::DefaultDeleter<ns3::Ipv4Route> > const & o) [copy constructor]
cls.add_constructor([param('ns3::SimpleRefCount< ns3::Ipv4Route, ns3::empty, ns3::DefaultDeleter< ns3::Ipv4Route > > const &', 'o')])
## simple-ref-count.h (module 'core'): static void ns3::SimpleRefCount<ns3::Ipv4Route, ns3::empty, ns3::DefaultDeleter<ns3::Ipv4Route> >::Cleanup() [member function]
cls.add_method('Cleanup',
'void',
[],
is_static=True)
return
def register_Ns3SimpleRefCount__Ns3NetDeviceQueue_Ns3Empty_Ns3DefaultDeleter__lt__ns3NetDeviceQueue__gt___methods(root_module, cls):
## simple-ref-count.h (module 'core'): ns3::SimpleRefCount<ns3::NetDeviceQueue, ns3::empty, ns3::DefaultDeleter<ns3::NetDeviceQueue> >::SimpleRefCount() [constructor]
cls.add_constructor([])
## simple-ref-count.h (module 'core'): ns3::SimpleRefCount<ns3::NetDeviceQueue, ns3::empty, ns3::DefaultDeleter<ns3::NetDeviceQueue> >::SimpleRefCount(ns3::SimpleRefCount<ns3::NetDeviceQueue, ns3::empty, ns3::DefaultDeleter<ns3::NetDeviceQueue> > const & o) [copy constructor]
cls.add_constructor([param('ns3::SimpleRefCount< ns3::NetDeviceQueue, ns3::empty, ns3::DefaultDeleter< ns3::NetDeviceQueue > > const &', 'o')])
## simple-ref-count.h (module 'core'): static void ns3::SimpleRefCount<ns3::NetDeviceQueue, ns3::empty, ns3::DefaultDeleter<ns3::NetDeviceQueue> >::Cleanup() [member function]
cls.add_method('Cleanup',
'void',
[],
is_static=True)
return
def register_Ns3SimpleRefCount__Ns3NixVector_Ns3Empty_Ns3DefaultDeleter__lt__ns3NixVector__gt___methods(root_module, cls):
## simple-ref-count.h (module 'core'): ns3::SimpleRefCount<ns3::NixVector, ns3::empty, ns3::DefaultDeleter<ns3::NixVector> >::SimpleRefCount() [constructor]
cls.add_constructor([])
## simple-ref-count.h (module 'core'): ns3::SimpleRefCount<ns3::NixVector, ns3::empty, ns3::DefaultDeleter<ns3::NixVector> >::SimpleRefCount(ns3::SimpleRefCount<ns3::NixVector, ns3::empty, ns3::DefaultDeleter<ns3::NixVector> > const & o) [copy constructor]
cls.add_constructor([param('ns3::SimpleRefCount< ns3::NixVector, ns3::empty, ns3::DefaultDeleter< ns3::NixVector > > const &', 'o')])
## simple-ref-count.h (module 'core'): static void ns3::SimpleRefCount<ns3::NixVector, ns3::empty, ns3::DefaultDeleter<ns3::NixVector> >::Cleanup() [member function]
cls.add_method('Cleanup',
'void',
[],
is_static=True)
return
def register_Ns3SimpleRefCount__Ns3OutputStreamWrapper_Ns3Empty_Ns3DefaultDeleter__lt__ns3OutputStreamWrapper__gt___methods(root_module, cls):
## simple-ref-count.h (module 'core'): ns3::SimpleRefCount<ns3::OutputStreamWrapper, ns3::empty, ns3::DefaultDeleter<ns3::OutputStreamWrapper> >::SimpleRefCount() [constructor]
cls.add_constructor([])
## simple-ref-count.h (module 'core'): ns3::SimpleRefCount<ns3::OutputStreamWrapper, ns3::empty, ns3::DefaultDeleter<ns3::OutputStreamWrapper> >::SimpleRefCount(ns3::SimpleRefCount<ns3::OutputStreamWrapper, ns3::empty, ns3::DefaultDeleter<ns3::OutputStreamWrapper> > const & o) [copy constructor]
cls.add_constructor([param('ns3::SimpleRefCount< ns3::OutputStreamWrapper, ns3::empty, ns3::DefaultDeleter< ns3::OutputStreamWrapper > > const &', 'o')])
## simple-ref-count.h (module 'core'): static void ns3::SimpleRefCount<ns3::OutputStreamWrapper, ns3::empty, ns3::DefaultDeleter<ns3::OutputStreamWrapper> >::Cleanup() [member function]
cls.add_method('Cleanup',
'void',
[],
is_static=True)
return
def register_Ns3SimpleRefCount__Ns3Packet_Ns3Empty_Ns3DefaultDeleter__lt__ns3Packet__gt___methods(root_module, cls):
## simple-ref-count.h (module 'core'): ns3::SimpleRefCount<ns3::Packet, ns3::empty, ns3::DefaultDeleter<ns3::Packet> >::SimpleRefCount() [constructor]
cls.add_constructor([])
## simple-ref-count.h (module 'core'): ns3::SimpleRefCount<ns3::Packet, ns3::empty, ns3::DefaultDeleter<ns3::Packet> >::SimpleRefCount(ns3::SimpleRefCount<ns3::Packet, ns3::empty, ns3::DefaultDeleter<ns3::Packet> > const & o) [copy constructor]
cls.add_constructor([param('ns3::SimpleRefCount< ns3::Packet, ns3::empty, ns3::DefaultDeleter< ns3::Packet > > const &', 'o')])
## simple-ref-count.h (module 'core'): static void ns3::SimpleRefCount<ns3::Packet, ns3::empty, ns3::DefaultDeleter<ns3::Packet> >::Cleanup() [member function]
cls.add_method('Cleanup',
'void',
[],
is_static=True)
return
def register_Ns3SimpleRefCount__Ns3QueueItem_Ns3Empty_Ns3DefaultDeleter__lt__ns3QueueItem__gt___methods(root_module, cls):
## simple-ref-count.h (module 'core'): ns3::SimpleRefCount<ns3::QueueItem, ns3::empty, ns3::DefaultDeleter<ns3::QueueItem> >::SimpleRefCount() [constructor]
cls.add_constructor([])
## simple-ref-count.h (module 'core'): ns3::SimpleRefCount<ns3::QueueItem, ns3::empty, ns3::DefaultDeleter<ns3::QueueItem> >::SimpleRefCount(ns3::SimpleRefCount<ns3::QueueItem, ns3::empty, ns3::DefaultDeleter<ns3::QueueItem> > const & o) [copy constructor]
cls.add_constructor([param('ns3::SimpleRefCount< ns3::QueueItem, ns3::empty, ns3::DefaultDeleter< ns3::QueueItem > > const &', 'o')])
## simple-ref-count.h (module 'core'): static void ns3::SimpleRefCount<ns3::QueueItem, ns3::empty, ns3::DefaultDeleter<ns3::QueueItem> >::Cleanup() [member function]
cls.add_method('Cleanup',
'void',
[],
is_static=True)
return
def register_Ns3SimpleRefCount__Ns3TraceSourceAccessor_Ns3Empty_Ns3DefaultDeleter__lt__ns3TraceSourceAccessor__gt___methods(root_module, cls):
## simple-ref-count.h (module 'core'): ns3::SimpleRefCount<ns3::TraceSourceAccessor, ns3::empty, ns3::DefaultDeleter<ns3::TraceSourceAccessor> >::SimpleRefCount() [constructor]
cls.add_constructor([])
## simple-ref-count.h (module 'core'): ns3::SimpleRefCount<ns3::TraceSourceAccessor, ns3::empty, ns3::DefaultDeleter<ns3::TraceSourceAccessor> >::SimpleRefCount(ns3::SimpleRefCount<ns3::TraceSourceAccessor, ns3::empty, ns3::DefaultDeleter<ns3::TraceSourceAccessor> > const & o) [copy constructor]
cls.add_constructor([param('ns3::SimpleRefCount< ns3::TraceSourceAccessor, ns3::empty, ns3::DefaultDeleter< ns3::TraceSourceAccessor > > const &', 'o')])
## simple-ref-count.h (module 'core'): static void ns3::SimpleRefCount<ns3::TraceSourceAccessor, ns3::empty, ns3::DefaultDeleter<ns3::TraceSourceAccessor> >::Cleanup() [member function]
cls.add_method('Cleanup',
'void',
[],
is_static=True)
return
def register_Ns3Socket_methods(root_module, cls):
## socket.h (module 'network'): ns3::Socket::Socket(ns3::Socket const & arg0) [copy constructor]
cls.add_constructor([param('ns3::Socket const &', 'arg0')])
## socket.h (module 'network'): ns3::Socket::Socket() [constructor]
cls.add_constructor([])
## socket.h (module 'network'): int ns3::Socket::Bind(ns3::Address const & address) [member function]
cls.add_method('Bind',
'int',
[param('ns3::Address const &', 'address')],
is_pure_virtual=True, is_virtual=True)
## socket.h (module 'network'): int ns3::Socket::Bind() [member function]
cls.add_method('Bind',
'int',
[],
is_pure_virtual=True, is_virtual=True)
## socket.h (module 'network'): int ns3::Socket::Bind6() [member function]
cls.add_method('Bind6',
'int',
[],
is_pure_virtual=True, is_virtual=True)
## socket.h (module 'network'): void ns3::Socket::BindToNetDevice(ns3::Ptr<ns3::NetDevice> netdevice) [member function]
cls.add_method('BindToNetDevice',
'void',
[param('ns3::Ptr< ns3::NetDevice >', 'netdevice')],
is_virtual=True)
## socket.h (module 'network'): int ns3::Socket::Close() [member function]
cls.add_method('Close',
'int',
[],
is_pure_virtual=True, is_virtual=True)
## socket.h (module 'network'): int ns3::Socket::Connect(ns3::Address const & address) [member function]
cls.add_method('Connect',
'int',
[param('ns3::Address const &', 'address')],
is_pure_virtual=True, is_virtual=True)
## socket.h (module 'network'): static ns3::Ptr<ns3::Socket> ns3::Socket::CreateSocket(ns3::Ptr<ns3::Node> node, ns3::TypeId tid) [member function]
cls.add_method('CreateSocket',
'ns3::Ptr< ns3::Socket >',
[param('ns3::Ptr< ns3::Node >', 'node'), param('ns3::TypeId', 'tid')],
is_static=True)
## socket.h (module 'network'): bool ns3::Socket::GetAllowBroadcast() const [member function]
cls.add_method('GetAllowBroadcast',
'bool',
[],
is_pure_virtual=True, is_const=True, is_virtual=True)
## socket.h (module 'network'): ns3::Ptr<ns3::NetDevice> ns3::Socket::GetBoundNetDevice() [member function]
cls.add_method('GetBoundNetDevice',
'ns3::Ptr< ns3::NetDevice >',
[])
## socket.h (module 'network'): ns3::Socket::SocketErrno ns3::Socket::GetErrno() const [member function]
cls.add_method('GetErrno',
'ns3::Socket::SocketErrno',
[],
is_pure_virtual=True, is_const=True, is_virtual=True)
## socket.h (module 'network'): uint8_t ns3::Socket::GetIpTos() const [member function]
cls.add_method('GetIpTos',
'uint8_t',
[],
is_const=True)
## socket.h (module 'network'): uint8_t ns3::Socket::GetIpTtl() const [member function]
cls.add_method('GetIpTtl',
'uint8_t',
[],
is_const=True, is_virtual=True)
## socket.h (module 'network'): uint8_t ns3::Socket::GetIpv6HopLimit() const [member function]
cls.add_method('GetIpv6HopLimit',
'uint8_t',
[],
is_const=True, is_virtual=True)
## socket.h (module 'network'): uint8_t ns3::Socket::GetIpv6Tclass() const [member function]
cls.add_method('GetIpv6Tclass',
'uint8_t',
[],
is_const=True)
## socket.h (module 'network'): ns3::Ptr<ns3::Node> ns3::Socket::GetNode() const [member function]
cls.add_method('GetNode',
'ns3::Ptr< ns3::Node >',
[],
is_pure_virtual=True, is_const=True, is_virtual=True)
## socket.h (module 'network'): int ns3::Socket::GetPeerName(ns3::Address & address) const [member function]
cls.add_method('GetPeerName',
'int',
[param('ns3::Address &', 'address')],
is_pure_virtual=True, is_const=True, is_virtual=True)
## socket.h (module 'network'): uint8_t ns3::Socket::GetPriority() const [member function]
cls.add_method('GetPriority',
'uint8_t',
[],
is_const=True)
## socket.h (module 'network'): uint32_t ns3::Socket::GetRxAvailable() const [member function]
cls.add_method('GetRxAvailable',
'uint32_t',
[],
is_pure_virtual=True, is_const=True, is_virtual=True)
## socket.h (module 'network'): int ns3::Socket::GetSockName(ns3::Address & address) const [member function]
cls.add_method('GetSockName',
'int',
[param('ns3::Address &', 'address')],
is_pure_virtual=True, is_const=True, is_virtual=True)
## socket.h (module 'network'): ns3::Socket::SocketType ns3::Socket::GetSocketType() const [member function]
cls.add_method('GetSocketType',
'ns3::Socket::SocketType',
[],
is_pure_virtual=True, is_const=True, is_virtual=True)
## socket.h (module 'network'): uint32_t ns3::Socket::GetTxAvailable() const [member function]
cls.add_method('GetTxAvailable',
'uint32_t',
[],
is_pure_virtual=True, is_const=True, is_virtual=True)
## socket.h (module 'network'): static ns3::TypeId ns3::Socket::GetTypeId() [member function]
cls.add_method('GetTypeId',
'ns3::TypeId',
[],
is_static=True)
## socket.h (module 'network'): static uint8_t ns3::Socket::IpTos2Priority(uint8_t ipTos) [member function]
cls.add_method('IpTos2Priority',
'uint8_t',
[param('uint8_t', 'ipTos')],
is_static=True)
## socket.h (module 'network'): void ns3::Socket::Ipv6JoinGroup(ns3::Ipv6Address address, ns3::Socket::Ipv6MulticastFilterMode filterMode, std::vector<ns3::Ipv6Address,std::allocator<ns3::Ipv6Address> > sourceAddresses) [member function]
cls.add_method('Ipv6JoinGroup',
'void',
[param('ns3::Ipv6Address', 'address'), param('ns3::Socket::Ipv6MulticastFilterMode', 'filterMode'), param('std::vector< ns3::Ipv6Address >', 'sourceAddresses')],
is_virtual=True)
## socket.h (module 'network'): void ns3::Socket::Ipv6JoinGroup(ns3::Ipv6Address address) [member function]
cls.add_method('Ipv6JoinGroup',
'void',
[param('ns3::Ipv6Address', 'address')],
is_virtual=True)
## socket.h (module 'network'): void ns3::Socket::Ipv6LeaveGroup() [member function]
cls.add_method('Ipv6LeaveGroup',
'void',
[],
is_virtual=True)
## socket.h (module 'network'): bool ns3::Socket::IsIpRecvTos() const [member function]
cls.add_method('IsIpRecvTos',
'bool',
[],
is_const=True)
## socket.h (module 'network'): bool ns3::Socket::IsIpRecvTtl() const [member function]
cls.add_method('IsIpRecvTtl',
'bool',
[],
is_const=True)
## socket.h (module 'network'): bool ns3::Socket::IsIpv6RecvHopLimit() const [member function]
cls.add_method('IsIpv6RecvHopLimit',
'bool',
[],
is_const=True)
## socket.h (module 'network'): bool ns3::Socket::IsIpv6RecvTclass() const [member function]
cls.add_method('IsIpv6RecvTclass',
'bool',
[],
is_const=True)
## socket.h (module 'network'): bool ns3::Socket::IsRecvPktInfo() const [member function]
cls.add_method('IsRecvPktInfo',
'bool',
[],
is_const=True)
## socket.h (module 'network'): int ns3::Socket::Listen() [member function]
cls.add_method('Listen',
'int',
[],
is_pure_virtual=True, is_virtual=True)
## socket.h (module 'network'): ns3::Ptr<ns3::Packet> ns3::Socket::Recv(uint32_t maxSize, uint32_t flags) [member function]
cls.add_method('Recv',
'ns3::Ptr< ns3::Packet >',
[param('uint32_t', 'maxSize'), param('uint32_t', 'flags')],
is_pure_virtual=True, is_virtual=True)
## socket.h (module 'network'): ns3::Ptr<ns3::Packet> ns3::Socket::Recv() [member function]
cls.add_method('Recv',
'ns3::Ptr< ns3::Packet >',
[])
## socket.h (module 'network'): int ns3::Socket::Recv(uint8_t * buf, uint32_t size, uint32_t flags) [member function]
cls.add_method('Recv',
'int',
[param('uint8_t *', 'buf'), param('uint32_t', 'size'), param('uint32_t', 'flags')])
## socket.h (module 'network'): ns3::Ptr<ns3::Packet> ns3::Socket::RecvFrom(uint32_t maxSize, uint32_t flags, ns3::Address & fromAddress) [member function]
cls.add_method('RecvFrom',
'ns3::Ptr< ns3::Packet >',
[param('uint32_t', 'maxSize'), param('uint32_t', 'flags'), param('ns3::Address &', 'fromAddress')],
is_pure_virtual=True, is_virtual=True)
## socket.h (module 'network'): ns3::Ptr<ns3::Packet> ns3::Socket::RecvFrom(ns3::Address & fromAddress) [member function]
cls.add_method('RecvFrom',
'ns3::Ptr< ns3::Packet >',
[param('ns3::Address &', 'fromAddress')])
## socket.h (module 'network'): int ns3::Socket::RecvFrom(uint8_t * buf, uint32_t size, uint32_t flags, ns3::Address & fromAddress) [member function]
cls.add_method('RecvFrom',
'int',
[param('uint8_t *', 'buf'), param('uint32_t', 'size'), param('uint32_t', 'flags'), param('ns3::Address &', 'fromAddress')])
## socket.h (module 'network'): int ns3::Socket::Send(ns3::Ptr<ns3::Packet> p, uint32_t flags) [member function]
cls.add_method('Send',
'int',
[param('ns3::Ptr< ns3::Packet >', 'p'), param('uint32_t', 'flags')],
is_pure_virtual=True, is_virtual=True)
## socket.h (module 'network'): int ns3::Socket::Send(ns3::Ptr<ns3::Packet> p) [member function]
cls.add_method('Send',
'int',
[param('ns3::Ptr< ns3::Packet >', 'p')])
## socket.h (module 'network'): int ns3::Socket::Send(uint8_t const * buf, uint32_t size, uint32_t flags) [member function]
cls.add_method('Send',
'int',
[param('uint8_t const *', 'buf'), param('uint32_t', 'size'), param('uint32_t', 'flags')])
## socket.h (module 'network'): int ns3::Socket::SendTo(ns3::Ptr<ns3::Packet> p, uint32_t flags, ns3::Address const & toAddress) [member function]
cls.add_method('SendTo',
'int',
[param('ns3::Ptr< ns3::Packet >', 'p'), param('uint32_t', 'flags'), param('ns3::Address const &', 'toAddress')],
is_pure_virtual=True, is_virtual=True)
## socket.h (module 'network'): int ns3::Socket::SendTo(uint8_t const * buf, uint32_t size, uint32_t flags, ns3::Address const & address) [member function]
cls.add_method('SendTo',
'int',
[param('uint8_t const *', 'buf'), param('uint32_t', 'size'), param('uint32_t', 'flags'), param('ns3::Address const &', 'address')])
## socket.h (module 'network'): void ns3::Socket::SetAcceptCallback(ns3::Callback<bool, ns3::Ptr<ns3::Socket>, ns3::Address const&, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty> connectionRequest, ns3::Callback<void, ns3::Ptr<ns3::Socket>, ns3::Address const&, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty> newConnectionCreated) [member function]
cls.add_method('SetAcceptCallback',
'void',
[param('ns3::Callback< bool, ns3::Ptr< ns3::Socket >, ns3::Address const &, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty >', 'connectionRequest'), param('ns3::Callback< void, ns3::Ptr< ns3::Socket >, ns3::Address const &, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty >', 'newConnectionCreated')])
## socket.h (module 'network'): bool ns3::Socket::SetAllowBroadcast(bool allowBroadcast) [member function]
cls.add_method('SetAllowBroadcast',
'bool',
[param('bool', 'allowBroadcast')],
is_pure_virtual=True, is_virtual=True)
## socket.h (module 'network'): void ns3::Socket::SetCloseCallbacks(ns3::Callback<void, ns3::Ptr<ns3::Socket>, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty> normalClose, ns3::Callback<void, ns3::Ptr<ns3::Socket>, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty> errorClose) [member function]
cls.add_method('SetCloseCallbacks',
'void',
[param('ns3::Callback< void, ns3::Ptr< ns3::Socket >, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty >', 'normalClose'), param('ns3::Callback< void, ns3::Ptr< ns3::Socket >, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty >', 'errorClose')])
## socket.h (module 'network'): void ns3::Socket::SetConnectCallback(ns3::Callback<void, ns3::Ptr<ns3::Socket>, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty> connectionSucceeded, ns3::Callback<void, ns3::Ptr<ns3::Socket>, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty> connectionFailed) [member function]
cls.add_method('SetConnectCallback',
'void',
[param('ns3::Callback< void, ns3::Ptr< ns3::Socket >, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty >', 'connectionSucceeded'), param('ns3::Callback< void, ns3::Ptr< ns3::Socket >, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty >', 'connectionFailed')])
## socket.h (module 'network'): void ns3::Socket::SetDataSentCallback(ns3::Callback<void, ns3::Ptr<ns3::Socket>, unsigned int, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty> dataSent) [member function]
cls.add_method('SetDataSentCallback',
'void',
[param('ns3::Callback< void, ns3::Ptr< ns3::Socket >, unsigned int, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty >', 'dataSent')])
## socket.h (module 'network'): void ns3::Socket::SetIpRecvTos(bool ipv4RecvTos) [member function]
cls.add_method('SetIpRecvTos',
'void',
[param('bool', 'ipv4RecvTos')])
## socket.h (module 'network'): void ns3::Socket::SetIpRecvTtl(bool ipv4RecvTtl) [member function]
cls.add_method('SetIpRecvTtl',
'void',
[param('bool', 'ipv4RecvTtl')])
## socket.h (module 'network'): void ns3::Socket::SetIpTos(uint8_t ipTos) [member function]
cls.add_method('SetIpTos',
'void',
[param('uint8_t', 'ipTos')])
## socket.h (module 'network'): void ns3::Socket::SetIpTtl(uint8_t ipTtl) [member function]
cls.add_method('SetIpTtl',
'void',
[param('uint8_t', 'ipTtl')],
is_virtual=True)
## socket.h (module 'network'): void ns3::Socket::SetIpv6HopLimit(uint8_t ipHopLimit) [member function]
cls.add_method('SetIpv6HopLimit',
'void',
[param('uint8_t', 'ipHopLimit')],
is_virtual=True)
## socket.h (module 'network'): void ns3::Socket::SetIpv6RecvHopLimit(bool ipv6RecvHopLimit) [member function]
cls.add_method('SetIpv6RecvHopLimit',
'void',
[param('bool', 'ipv6RecvHopLimit')])
## socket.h (module 'network'): void ns3::Socket::SetIpv6RecvTclass(bool ipv6RecvTclass) [member function]
cls.add_method('SetIpv6RecvTclass',
'void',
[param('bool', 'ipv6RecvTclass')])
## socket.h (module 'network'): void ns3::Socket::SetIpv6Tclass(int ipTclass) [member function]
cls.add_method('SetIpv6Tclass',
'void',
[param('int', 'ipTclass')])
## socket.h (module 'network'): void ns3::Socket::SetPriority(uint8_t priority) [member function]
cls.add_method('SetPriority',
'void',
[param('uint8_t', 'priority')])
## socket.h (module 'network'): void ns3::Socket::SetRecvCallback(ns3::Callback<void, ns3::Ptr<ns3::Socket>, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty> arg0) [member function]
cls.add_method('SetRecvCallback',
'void',
[param('ns3::Callback< void, ns3::Ptr< ns3::Socket >, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty >', 'arg0')])
## socket.h (module 'network'): void ns3::Socket::SetRecvPktInfo(bool flag) [member function]
cls.add_method('SetRecvPktInfo',
'void',
[param('bool', 'flag')])
## socket.h (module 'network'): void ns3::Socket::SetSendCallback(ns3::Callback<void, ns3::Ptr<ns3::Socket>, unsigned int, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty> sendCb) [member function]
cls.add_method('SetSendCallback',
'void',
[param('ns3::Callback< void, ns3::Ptr< ns3::Socket >, unsigned int, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty >', 'sendCb')])
## socket.h (module 'network'): int ns3::Socket::ShutdownRecv() [member function]
cls.add_method('ShutdownRecv',
'int',
[],
is_pure_virtual=True, is_virtual=True)
## socket.h (module 'network'): int ns3::Socket::ShutdownSend() [member function]
cls.add_method('ShutdownSend',
'int',
[],
is_pure_virtual=True, is_virtual=True)
## socket.h (module 'network'): void ns3::Socket::DoDispose() [member function]
cls.add_method('DoDispose',
'void',
[],
visibility='protected', is_virtual=True)
## socket.h (module 'network'): bool ns3::Socket::IsManualIpTtl() const [member function]
cls.add_method('IsManualIpTtl',
'bool',
[],
is_const=True, visibility='protected')
## socket.h (module 'network'): bool ns3::Socket::IsManualIpv6HopLimit() const [member function]
cls.add_method('IsManualIpv6HopLimit',
'bool',
[],
is_const=True, visibility='protected')
## socket.h (module 'network'): bool ns3::Socket::IsManualIpv6Tclass() const [member function]
cls.add_method('IsManualIpv6Tclass',
'bool',
[],
is_const=True, visibility='protected')
## socket.h (module 'network'): void ns3::Socket::NotifyConnectionFailed() [member function]
cls.add_method('NotifyConnectionFailed',
'void',
[],
visibility='protected')
## socket.h (module 'network'): bool ns3::Socket::NotifyConnectionRequest(ns3::Address const & from) [member function]
cls.add_method('NotifyConnectionRequest',
'bool',
[param('ns3::Address const &', 'from')],
visibility='protected')
## socket.h (module 'network'): void ns3::Socket::NotifyConnectionSucceeded() [member function]
cls.add_method('NotifyConnectionSucceeded',
'void',
[],
visibility='protected')
## socket.h (module 'network'): void ns3::Socket::NotifyDataRecv() [member function]
cls.add_method('NotifyDataRecv',
'void',
[],
visibility='protected')
## socket.h (module 'network'): void ns3::Socket::NotifyDataSent(uint32_t size) [member function]
cls.add_method('NotifyDataSent',
'void',
[param('uint32_t', 'size')],
visibility='protected')
## socket.h (module 'network'): void ns3::Socket::NotifyErrorClose() [member function]
cls.add_method('NotifyErrorClose',
'void',
[],
visibility='protected')
## socket.h (module 'network'): void ns3::Socket::NotifyNewConnectionCreated(ns3::Ptr<ns3::Socket> socket, ns3::Address const & from) [member function]
cls.add_method('NotifyNewConnectionCreated',
'void',
[param('ns3::Ptr< ns3::Socket >', 'socket'), param('ns3::Address const &', 'from')],
visibility='protected')
## socket.h (module 'network'): void ns3::Socket::NotifyNormalClose() [member function]
cls.add_method('NotifyNormalClose',
'void',
[],
visibility='protected')
## socket.h (module 'network'): void ns3::Socket::NotifySend(uint32_t spaceAvailable) [member function]
cls.add_method('NotifySend',
'void',
[param('uint32_t', 'spaceAvailable')],
visibility='protected')
return
def register_Ns3SocketIpTosTag_methods(root_module, cls):
## socket.h (module 'network'): ns3::SocketIpTosTag::SocketIpTosTag(ns3::SocketIpTosTag const & arg0) [copy constructor]
cls.add_constructor([param('ns3::SocketIpTosTag const &', 'arg0')])
## socket.h (module 'network'): ns3::SocketIpTosTag::SocketIpTosTag() [constructor]
cls.add_constructor([])
## socket.h (module 'network'): void ns3::SocketIpTosTag::Deserialize(ns3::TagBuffer i) [member function]
cls.add_method('Deserialize',
'void',
[param('ns3::TagBuffer', 'i')],
is_virtual=True)
## socket.h (module 'network'): ns3::TypeId ns3::SocketIpTosTag::GetInstanceTypeId() const [member function]
cls.add_method('GetInstanceTypeId',
'ns3::TypeId',
[],
is_const=True, is_virtual=True)
## socket.h (module 'network'): uint32_t ns3::SocketIpTosTag::GetSerializedSize() const [member function]
cls.add_method('GetSerializedSize',
'uint32_t',
[],
is_const=True, is_virtual=True)
## socket.h (module 'network'): uint8_t ns3::SocketIpTosTag::GetTos() const [member function]
cls.add_method('GetTos',
'uint8_t',
[],
is_const=True)
## socket.h (module 'network'): static ns3::TypeId ns3::SocketIpTosTag::GetTypeId() [member function]
cls.add_method('GetTypeId',
'ns3::TypeId',
[],
is_static=True)
## socket.h (module 'network'): void ns3::SocketIpTosTag::Print(std::ostream & os) const [member function]
cls.add_method('Print',
'void',
[param('std::ostream &', 'os')],
is_const=True, is_virtual=True)
## socket.h (module 'network'): void ns3::SocketIpTosTag::Serialize(ns3::TagBuffer i) const [member function]
cls.add_method('Serialize',
'void',
[param('ns3::TagBuffer', 'i')],
is_const=True, is_virtual=True)
## socket.h (module 'network'): void ns3::SocketIpTosTag::SetTos(uint8_t tos) [member function]
cls.add_method('SetTos',
'void',
[param('uint8_t', 'tos')])
return
def register_Ns3SocketIpTtlTag_methods(root_module, cls):
## socket.h (module 'network'): ns3::SocketIpTtlTag::SocketIpTtlTag(ns3::SocketIpTtlTag const & arg0) [copy constructor]
cls.add_constructor([param('ns3::SocketIpTtlTag const &', 'arg0')])
## socket.h (module 'network'): ns3::SocketIpTtlTag::SocketIpTtlTag() [constructor]
cls.add_constructor([])
## socket.h (module 'network'): void ns3::SocketIpTtlTag::Deserialize(ns3::TagBuffer i) [member function]
cls.add_method('Deserialize',
'void',
[param('ns3::TagBuffer', 'i')],
is_virtual=True)
## socket.h (module 'network'): ns3::TypeId ns3::SocketIpTtlTag::GetInstanceTypeId() const [member function]
cls.add_method('GetInstanceTypeId',
'ns3::TypeId',
[],
is_const=True, is_virtual=True)
## socket.h (module 'network'): uint32_t ns3::SocketIpTtlTag::GetSerializedSize() const [member function]
cls.add_method('GetSerializedSize',
'uint32_t',
[],
is_const=True, is_virtual=True)
## socket.h (module 'network'): uint8_t ns3::SocketIpTtlTag::GetTtl() const [member function]
cls.add_method('GetTtl',
'uint8_t',
[],
is_const=True)
## socket.h (module 'network'): static ns3::TypeId ns3::SocketIpTtlTag::GetTypeId() [member function]
cls.add_method('GetTypeId',
'ns3::TypeId',
[],
is_static=True)
## socket.h (module 'network'): void ns3::SocketIpTtlTag::Print(std::ostream & os) const [member function]
cls.add_method('Print',
'void',
[param('std::ostream &', 'os')],
is_const=True, is_virtual=True)
## socket.h (module 'network'): void ns3::SocketIpTtlTag::Serialize(ns3::TagBuffer i) const [member function]
cls.add_method('Serialize',
'void',
[param('ns3::TagBuffer', 'i')],
is_const=True, is_virtual=True)
## socket.h (module 'network'): void ns3::SocketIpTtlTag::SetTtl(uint8_t ttl) [member function]
cls.add_method('SetTtl',
'void',
[param('uint8_t', 'ttl')])
return
def register_Ns3SocketIpv6HopLimitTag_methods(root_module, cls):
## socket.h (module 'network'): ns3::SocketIpv6HopLimitTag::SocketIpv6HopLimitTag(ns3::SocketIpv6HopLimitTag const & arg0) [copy constructor]
cls.add_constructor([param('ns3::SocketIpv6HopLimitTag const &', 'arg0')])
## socket.h (module 'network'): ns3::SocketIpv6HopLimitTag::SocketIpv6HopLimitTag() [constructor]
cls.add_constructor([])
## socket.h (module 'network'): void ns3::SocketIpv6HopLimitTag::Deserialize(ns3::TagBuffer i) [member function]
cls.add_method('Deserialize',
'void',
[param('ns3::TagBuffer', 'i')],
is_virtual=True)
## socket.h (module 'network'): uint8_t ns3::SocketIpv6HopLimitTag::GetHopLimit() const [member function]
cls.add_method('GetHopLimit',
'uint8_t',
[],
is_const=True)
## socket.h (module 'network'): ns3::TypeId ns3::SocketIpv6HopLimitTag::GetInstanceTypeId() const [member function]
cls.add_method('GetInstanceTypeId',
'ns3::TypeId',
[],
is_const=True, is_virtual=True)
## socket.h (module 'network'): uint32_t ns3::SocketIpv6HopLimitTag::GetSerializedSize() const [member function]
cls.add_method('GetSerializedSize',
'uint32_t',
[],
is_const=True, is_virtual=True)
## socket.h (module 'network'): static ns3::TypeId ns3::SocketIpv6HopLimitTag::GetTypeId() [member function]
cls.add_method('GetTypeId',
'ns3::TypeId',
[],
is_static=True)
## socket.h (module 'network'): void ns3::SocketIpv6HopLimitTag::Print(std::ostream & os) const [member function]
cls.add_method('Print',
'void',
[param('std::ostream &', 'os')],
is_const=True, is_virtual=True)
## socket.h (module 'network'): void ns3::SocketIpv6HopLimitTag::Serialize(ns3::TagBuffer i) const [member function]
cls.add_method('Serialize',
'void',
[param('ns3::TagBuffer', 'i')],
is_const=True, is_virtual=True)
## socket.h (module 'network'): void ns3::SocketIpv6HopLimitTag::SetHopLimit(uint8_t hopLimit) [member function]
cls.add_method('SetHopLimit',
'void',
[param('uint8_t', 'hopLimit')])
return
def register_Ns3SocketIpv6TclassTag_methods(root_module, cls):
## socket.h (module 'network'): ns3::SocketIpv6TclassTag::SocketIpv6TclassTag(ns3::SocketIpv6TclassTag const & arg0) [copy constructor]
cls.add_constructor([param('ns3::SocketIpv6TclassTag const &', 'arg0')])
## socket.h (module 'network'): ns3::SocketIpv6TclassTag::SocketIpv6TclassTag() [constructor]
cls.add_constructor([])
## socket.h (module 'network'): void ns3::SocketIpv6TclassTag::Deserialize(ns3::TagBuffer i) [member function]
cls.add_method('Deserialize',
'void',
[param('ns3::TagBuffer', 'i')],
is_virtual=True)
## socket.h (module 'network'): ns3::TypeId ns3::SocketIpv6TclassTag::GetInstanceTypeId() const [member function]
cls.add_method('GetInstanceTypeId',
'ns3::TypeId',
[],
is_const=True, is_virtual=True)
## socket.h (module 'network'): uint32_t ns3::SocketIpv6TclassTag::GetSerializedSize() const [member function]
cls.add_method('GetSerializedSize',
'uint32_t',
[],
is_const=True, is_virtual=True)
## socket.h (module 'network'): uint8_t ns3::SocketIpv6TclassTag::GetTclass() const [member function]
cls.add_method('GetTclass',
'uint8_t',
[],
is_const=True)
## socket.h (module 'network'): static ns3::TypeId ns3::SocketIpv6TclassTag::GetTypeId() [member function]
cls.add_method('GetTypeId',
'ns3::TypeId',
[],
is_static=True)
## socket.h (module 'network'): void ns3::SocketIpv6TclassTag::Print(std::ostream & os) const [member function]
cls.add_method('Print',
'void',
[param('std::ostream &', 'os')],
is_const=True, is_virtual=True)
## socket.h (module 'network'): void ns3::SocketIpv6TclassTag::Serialize(ns3::TagBuffer i) const [member function]
cls.add_method('Serialize',
'void',
[param('ns3::TagBuffer', 'i')],
is_const=True, is_virtual=True)
## socket.h (module 'network'): void ns3::SocketIpv6TclassTag::SetTclass(uint8_t tclass) [member function]
cls.add_method('SetTclass',
'void',
[param('uint8_t', 'tclass')])
return
def register_Ns3SocketPriorityTag_methods(root_module, cls):
## socket.h (module 'network'): ns3::SocketPriorityTag::SocketPriorityTag(ns3::SocketPriorityTag const & arg0) [copy constructor]
cls.add_constructor([param('ns3::SocketPriorityTag const &', 'arg0')])
## socket.h (module 'network'): ns3::SocketPriorityTag::SocketPriorityTag() [constructor]
cls.add_constructor([])
## socket.h (module 'network'): void ns3::SocketPriorityTag::Deserialize(ns3::TagBuffer i) [member function]
cls.add_method('Deserialize',
'void',
[param('ns3::TagBuffer', 'i')],
is_virtual=True)
## socket.h (module 'network'): ns3::TypeId ns3::SocketPriorityTag::GetInstanceTypeId() const [member function]
cls.add_method('GetInstanceTypeId',
'ns3::TypeId',
[],
is_const=True, is_virtual=True)
## socket.h (module 'network'): uint8_t ns3::SocketPriorityTag::GetPriority() const [member function]
cls.add_method('GetPriority',
'uint8_t',
[],
is_const=True)
## socket.h (module 'network'): uint32_t ns3::SocketPriorityTag::GetSerializedSize() const [member function]
cls.add_method('GetSerializedSize',
'uint32_t',
[],
is_const=True, is_virtual=True)
## socket.h (module 'network'): static ns3::TypeId ns3::SocketPriorityTag::GetTypeId() [member function]
cls.add_method('GetTypeId',
'ns3::TypeId',
[],
is_static=True)
## socket.h (module 'network'): void ns3::SocketPriorityTag::Print(std::ostream & os) const [member function]
cls.add_method('Print',
'void',
[param('std::ostream &', 'os')],
is_const=True, is_virtual=True)
## socket.h (module 'network'): void ns3::SocketPriorityTag::Serialize(ns3::TagBuffer i) const [member function]
cls.add_method('Serialize',
'void',
[param('ns3::TagBuffer', 'i')],
is_const=True, is_virtual=True)
## socket.h (module 'network'): void ns3::SocketPriorityTag::SetPriority(uint8_t priority) [member function]
cls.add_method('SetPriority',
'void',
[param('uint8_t', 'priority')])
return
def register_Ns3SocketSetDontFragmentTag_methods(root_module, cls):
## socket.h (module 'network'): ns3::SocketSetDontFragmentTag::SocketSetDontFragmentTag(ns3::SocketSetDontFragmentTag const & arg0) [copy constructor]
cls.add_constructor([param('ns3::SocketSetDontFragmentTag const &', 'arg0')])
## socket.h (module 'network'): ns3::SocketSetDontFragmentTag::SocketSetDontFragmentTag() [constructor]
cls.add_constructor([])
## socket.h (module 'network'): void ns3::SocketSetDontFragmentTag::Deserialize(ns3::TagBuffer i) [member function]
cls.add_method('Deserialize',
'void',
[param('ns3::TagBuffer', 'i')],
is_virtual=True)
## socket.h (module 'network'): void ns3::SocketSetDontFragmentTag::Disable() [member function]
cls.add_method('Disable',
'void',
[])
## socket.h (module 'network'): void ns3::SocketSetDontFragmentTag::Enable() [member function]
cls.add_method('Enable',
'void',
[])
## socket.h (module 'network'): ns3::TypeId ns3::SocketSetDontFragmentTag::GetInstanceTypeId() const [member function]
cls.add_method('GetInstanceTypeId',
'ns3::TypeId',
[],
is_const=True, is_virtual=True)
## socket.h (module 'network'): uint32_t ns3::SocketSetDontFragmentTag::GetSerializedSize() const [member function]
cls.add_method('GetSerializedSize',
'uint32_t',
[],
is_const=True, is_virtual=True)
## socket.h (module 'network'): static ns3::TypeId ns3::SocketSetDontFragmentTag::GetTypeId() [member function]
cls.add_method('GetTypeId',
'ns3::TypeId',
[],
is_static=True)
## socket.h (module 'network'): bool ns3::SocketSetDontFragmentTag::IsEnabled() const [member function]
cls.add_method('IsEnabled',
'bool',
[],
is_const=True)
## socket.h (module 'network'): void ns3::SocketSetDontFragmentTag::Print(std::ostream & os) const [member function]
cls.add_method('Print',
'void',
[param('std::ostream &', 'os')],
is_const=True, is_virtual=True)
## socket.h (module 'network'): void ns3::SocketSetDontFragmentTag::Serialize(ns3::TagBuffer i) const [member function]
cls.add_method('Serialize',
'void',
[param('ns3::TagBuffer', 'i')],
is_const=True, is_virtual=True)
return
def register_Ns3Time_methods(root_module, cls):
cls.add_binary_numeric_operator('*', root_module['ns3::Time'], root_module['ns3::Time'], param('int64_t const &', u'right'))
cls.add_binary_numeric_operator('+', root_module['ns3::Time'], root_module['ns3::Time'], param('ns3::Time const &', u'right'))
cls.add_binary_numeric_operator('-', root_module['ns3::Time'], root_module['ns3::Time'], param('ns3::Time const &', u'right'))
cls.add_binary_numeric_operator('/', root_module['ns3::Time'], root_module['ns3::Time'], param('int64_t const &', u'right'))
cls.add_binary_comparison_operator('<')
cls.add_binary_comparison_operator('>')
cls.add_binary_comparison_operator('!=')
cls.add_inplace_numeric_operator('+=', param('ns3::Time const &', u'right'))
cls.add_inplace_numeric_operator('-=', param('ns3::Time const &', u'right'))
cls.add_output_stream_operator()
cls.add_binary_comparison_operator('<=')
cls.add_binary_comparison_operator('==')
cls.add_binary_comparison_operator('>=')
## nstime.h (module 'core'): ns3::Time::Time() [constructor]
cls.add_constructor([])
## nstime.h (module 'core'): ns3::Time::Time(ns3::Time const & o) [copy constructor]
cls.add_constructor([param('ns3::Time const &', 'o')])
## nstime.h (module 'core'): ns3::Time::Time(double v) [constructor]
cls.add_constructor([param('double', 'v')])
## nstime.h (module 'core'): ns3::Time::Time(int v) [constructor]
cls.add_constructor([param('int', 'v')])
## nstime.h (module 'core'): ns3::Time::Time(long int v) [constructor]
cls.add_constructor([param('long int', 'v')])
## nstime.h (module 'core'): ns3::Time::Time(long long int v) [constructor]
cls.add_constructor([param('long long int', 'v')])
## nstime.h (module 'core'): ns3::Time::Time(unsigned int v) [constructor]
cls.add_constructor([param('unsigned int', 'v')])
## nstime.h (module 'core'): ns3::Time::Time(long unsigned int v) [constructor]
cls.add_constructor([param('long unsigned int', 'v')])
## nstime.h (module 'core'): ns3::Time::Time(long long unsigned int v) [constructor]
cls.add_constructor([param('long long unsigned int', 'v')])
## nstime.h (module 'core'): ns3::Time::Time(ns3::int64x64_t const & v) [constructor]
cls.add_constructor([param('ns3::int64x64_t const &', 'v')])
## nstime.h (module 'core'): ns3::Time::Time(std::string const & s) [constructor]
cls.add_constructor([param('std::string const &', 's')])
## nstime.h (module 'core'): ns3::TimeWithUnit ns3::Time::As(ns3::Time::Unit const unit) const [member function]
cls.add_method('As',
'ns3::TimeWithUnit',
[param('ns3::Time::Unit const', 'unit')],
is_const=True)
## nstime.h (module 'core'): int ns3::Time::Compare(ns3::Time const & o) const [member function]
cls.add_method('Compare',
'int',
[param('ns3::Time const &', 'o')],
is_const=True)
## nstime.h (module 'core'): static ns3::Time ns3::Time::From(ns3::int64x64_t const & value) [member function]
cls.add_method('From',
'ns3::Time',
[param('ns3::int64x64_t const &', 'value')],
is_static=True)
## nstime.h (module 'core'): static ns3::Time ns3::Time::From(ns3::int64x64_t const & value, ns3::Time::Unit unit) [member function]
cls.add_method('From',
'ns3::Time',
[param('ns3::int64x64_t const &', 'value'), param('ns3::Time::Unit', 'unit')],
is_static=True)
## nstime.h (module 'core'): static ns3::Time ns3::Time::FromDouble(double value, ns3::Time::Unit unit) [member function]
cls.add_method('FromDouble',
'ns3::Time',
[param('double', 'value'), param('ns3::Time::Unit', 'unit')],
is_static=True)
## nstime.h (module 'core'): static ns3::Time ns3::Time::FromInteger(uint64_t value, ns3::Time::Unit unit) [member function]
cls.add_method('FromInteger',
'ns3::Time',
[param('uint64_t', 'value'), param('ns3::Time::Unit', 'unit')],
is_static=True)
## nstime.h (module 'core'): double ns3::Time::GetDays() const [member function]
cls.add_method('GetDays',
'double',
[],
is_const=True)
## nstime.h (module 'core'): double ns3::Time::GetDouble() const [member function]
cls.add_method('GetDouble',
'double',
[],
is_const=True)
## nstime.h (module 'core'): int64_t ns3::Time::GetFemtoSeconds() const [member function]
cls.add_method('GetFemtoSeconds',
'int64_t',
[],
is_const=True)
## nstime.h (module 'core'): double ns3::Time::GetHours() const [member function]
cls.add_method('GetHours',
'double',
[],
is_const=True)
## nstime.h (module 'core'): int64_t ns3::Time::GetInteger() const [member function]
cls.add_method('GetInteger',
'int64_t',
[],
is_const=True)
## nstime.h (module 'core'): int64_t ns3::Time::GetMicroSeconds() const [member function]
cls.add_method('GetMicroSeconds',
'int64_t',
[],
is_const=True)
## nstime.h (module 'core'): int64_t ns3::Time::GetMilliSeconds() const [member function]
cls.add_method('GetMilliSeconds',
'int64_t',
[],
is_const=True)
## nstime.h (module 'core'): double ns3::Time::GetMinutes() const [member function]
cls.add_method('GetMinutes',
'double',
[],
is_const=True)
## nstime.h (module 'core'): int64_t ns3::Time::GetNanoSeconds() const [member function]
cls.add_method('GetNanoSeconds',
'int64_t',
[],
is_const=True)
## nstime.h (module 'core'): int64_t ns3::Time::GetPicoSeconds() const [member function]
cls.add_method('GetPicoSeconds',
'int64_t',
[],
is_const=True)
## nstime.h (module 'core'): static ns3::Time::Unit ns3::Time::GetResolution() [member function]
cls.add_method('GetResolution',
'ns3::Time::Unit',
[],
is_static=True)
## nstime.h (module 'core'): double ns3::Time::GetSeconds() const [member function]
cls.add_method('GetSeconds',
'double',
[],
is_const=True)
## nstime.h (module 'core'): int64_t ns3::Time::GetTimeStep() const [member function]
cls.add_method('GetTimeStep',
'int64_t',
[],
is_const=True)
## nstime.h (module 'core'): double ns3::Time::GetYears() const [member function]
cls.add_method('GetYears',
'double',
[],
is_const=True)
## nstime.h (module 'core'): bool ns3::Time::IsNegative() const [member function]
cls.add_method('IsNegative',
'bool',
[],
is_const=True)
## nstime.h (module 'core'): bool ns3::Time::IsPositive() const [member function]
cls.add_method('IsPositive',
'bool',
[],
is_const=True)
## nstime.h (module 'core'): bool ns3::Time::IsStrictlyNegative() const [member function]
cls.add_method('IsStrictlyNegative',
'bool',
[],
is_const=True)
## nstime.h (module 'core'): bool ns3::Time::IsStrictlyPositive() const [member function]
cls.add_method('IsStrictlyPositive',
'bool',
[],
is_const=True)
## nstime.h (module 'core'): bool ns3::Time::IsZero() const [member function]
cls.add_method('IsZero',
'bool',
[],
is_const=True)
## nstime.h (module 'core'): static ns3::Time ns3::Time::Max() [member function]
cls.add_method('Max',
'ns3::Time',
[],
is_static=True)
## nstime.h (module 'core'): static ns3::Time ns3::Time::Min() [member function]
cls.add_method('Min',
'ns3::Time',
[],
is_static=True)
## nstime.h (module 'core'): static void ns3::Time::SetResolution(ns3::Time::Unit resolution) [member function]
cls.add_method('SetResolution',
'void',
[param('ns3::Time::Unit', 'resolution')],
is_static=True)
## nstime.h (module 'core'): static bool ns3::Time::StaticInit() [member function]
cls.add_method('StaticInit',
'bool',
[],
is_static=True)
## nstime.h (module 'core'): ns3::int64x64_t ns3::Time::To(ns3::Time::Unit unit) const [member function]
cls.add_method('To',
'ns3::int64x64_t',
[param('ns3::Time::Unit', 'unit')],
is_const=True)
## nstime.h (module 'core'): double ns3::Time::ToDouble(ns3::Time::Unit unit) const [member function]
cls.add_method('ToDouble',
'double',
[param('ns3::Time::Unit', 'unit')],
is_const=True)
## nstime.h (module 'core'): int64_t ns3::Time::ToInteger(ns3::Time::Unit unit) const [member function]
cls.add_method('ToInteger',
'int64_t',
[param('ns3::Time::Unit', 'unit')],
is_const=True)
return
def register_Ns3TraceSourceAccessor_methods(root_module, cls):
## trace-source-accessor.h (module 'core'): ns3::TraceSourceAccessor::TraceSourceAccessor(ns3::TraceSourceAccessor const & arg0) [copy constructor]
cls.add_constructor([param('ns3::TraceSourceAccessor const &', 'arg0')])
## trace-source-accessor.h (module 'core'): ns3::TraceSourceAccessor::TraceSourceAccessor() [constructor]
cls.add_constructor([])
## trace-source-accessor.h (module 'core'): bool ns3::TraceSourceAccessor::Connect(ns3::ObjectBase * obj, std::string context, ns3::CallbackBase const & cb) const [member function]
cls.add_method('Connect',
'bool',
[param('ns3::ObjectBase *', 'obj', transfer_ownership=False), param('std::string', 'context'), param('ns3::CallbackBase const &', 'cb')],
is_pure_virtual=True, is_const=True, is_virtual=True)
## trace-source-accessor.h (module 'core'): bool ns3::TraceSourceAccessor::ConnectWithoutContext(ns3::ObjectBase * obj, ns3::CallbackBase const & cb) const [member function]
cls.add_method('ConnectWithoutContext',
'bool',
[param('ns3::ObjectBase *', 'obj', transfer_ownership=False), param('ns3::CallbackBase const &', 'cb')],
is_pure_virtual=True, is_const=True, is_virtual=True)
## trace-source-accessor.h (module 'core'): bool ns3::TraceSourceAccessor::Disconnect(ns3::ObjectBase * obj, std::string context, ns3::CallbackBase const & cb) const [member function]
cls.add_method('Disconnect',
'bool',
[param('ns3::ObjectBase *', 'obj', transfer_ownership=False), param('std::string', 'context'), param('ns3::CallbackBase const &', 'cb')],
is_pure_virtual=True, is_const=True, is_virtual=True)
## trace-source-accessor.h (module 'core'): bool ns3::TraceSourceAccessor::DisconnectWithoutContext(ns3::ObjectBase * obj, ns3::CallbackBase const & cb) const [member function]
cls.add_method('DisconnectWithoutContext',
'bool',
[param('ns3::ObjectBase *', 'obj', transfer_ownership=False), param('ns3::CallbackBase const &', 'cb')],
is_pure_virtual=True, is_const=True, is_virtual=True)
return
def register_Ns3Trailer_methods(root_module, cls):
cls.add_output_stream_operator()
## trailer.h (module 'network'): ns3::Trailer::Trailer() [constructor]
cls.add_constructor([])
## trailer.h (module 'network'): ns3::Trailer::Trailer(ns3::Trailer const & arg0) [copy constructor]
cls.add_constructor([param('ns3::Trailer const &', 'arg0')])
## trailer.h (module 'network'): uint32_t ns3::Trailer::Deserialize(ns3::Buffer::Iterator end) [member function]
cls.add_method('Deserialize',
'uint32_t',
[param('ns3::Buffer::Iterator', 'end')],
is_pure_virtual=True, is_virtual=True)
## trailer.h (module 'network'): uint32_t ns3::Trailer::GetSerializedSize() const [member function]
cls.add_method('GetSerializedSize',
'uint32_t',
[],
is_pure_virtual=True, is_const=True, is_virtual=True)
## trailer.h (module 'network'): static ns3::TypeId ns3::Trailer::GetTypeId() [member function]
cls.add_method('GetTypeId',
'ns3::TypeId',
[],
is_static=True)
## trailer.h (module 'network'): void ns3::Trailer::Print(std::ostream & os) const [member function]
cls.add_method('Print',
'void',
[param('std::ostream &', 'os')],
is_pure_virtual=True, is_const=True, is_virtual=True)
## trailer.h (module 'network'): void ns3::Trailer::Serialize(ns3::Buffer::Iterator start) const [member function]
cls.add_method('Serialize',
'void',
[param('ns3::Buffer::Iterator', 'start')],
is_pure_virtual=True, is_const=True, is_virtual=True)
return
def register_Ns3AttributeAccessor_methods(root_module, cls):
## attribute.h (module 'core'): ns3::AttributeAccessor::AttributeAccessor(ns3::AttributeAccessor const & arg0) [copy constructor]
cls.add_constructor([param('ns3::AttributeAccessor const &', 'arg0')])
## attribute.h (module 'core'): ns3::AttributeAccessor::AttributeAccessor() [constructor]
cls.add_constructor([])
## attribute.h (module 'core'): bool ns3::AttributeAccessor::Get(ns3::ObjectBase const * object, ns3::AttributeValue & attribute) const [member function]
cls.add_method('Get',
'bool',
[param('ns3::ObjectBase const *', 'object'), param('ns3::AttributeValue &', 'attribute')],
is_pure_virtual=True, is_const=True, is_virtual=True)
## attribute.h (module 'core'): bool ns3::AttributeAccessor::HasGetter() const [member function]
cls.add_method('HasGetter',
'bool',
[],
is_pure_virtual=True, is_const=True, is_virtual=True)
## attribute.h (module 'core'): bool ns3::AttributeAccessor::HasSetter() const [member function]
cls.add_method('HasSetter',
'bool',
[],
is_pure_virtual=True, is_const=True, is_virtual=True)
## attribute.h (module 'core'): bool ns3::AttributeAccessor::Set(ns3::ObjectBase * object, ns3::AttributeValue const & value) const [member function]
cls.add_method('Set',
'bool',
[param('ns3::ObjectBase *', 'object', transfer_ownership=False), param('ns3::AttributeValue const &', 'value')],
is_pure_virtual=True, is_const=True, is_virtual=True)
return
def register_Ns3AttributeChecker_methods(root_module, cls):
## attribute.h (module 'core'): ns3::AttributeChecker::AttributeChecker(ns3::AttributeChecker const & arg0) [copy constructor]
cls.add_constructor([param('ns3::AttributeChecker const &', 'arg0')])
## attribute.h (module 'core'): ns3::AttributeChecker::AttributeChecker() [constructor]
cls.add_constructor([])
## attribute.h (module 'core'): bool ns3::AttributeChecker::Check(ns3::AttributeValue const & value) const [member function]
cls.add_method('Check',
'bool',
[param('ns3::AttributeValue const &', 'value')],
is_pure_virtual=True, is_const=True, is_virtual=True)
## attribute.h (module 'core'): bool ns3::AttributeChecker::Copy(ns3::AttributeValue const & source, ns3::AttributeValue & destination) const [member function]
cls.add_method('Copy',
'bool',
[param('ns3::AttributeValue const &', 'source'), param('ns3::AttributeValue &', 'destination')],
is_pure_virtual=True, is_const=True, is_virtual=True)
## attribute.h (module 'core'): ns3::Ptr<ns3::AttributeValue> ns3::AttributeChecker::Create() const [member function]
cls.add_method('Create',
'ns3::Ptr< ns3::AttributeValue >',
[],
is_pure_virtual=True, is_const=True, is_virtual=True)
## attribute.h (module 'core'): ns3::Ptr<ns3::AttributeValue> ns3::AttributeChecker::CreateValidValue(ns3::AttributeValue const & value) const [member function]
cls.add_method('CreateValidValue',
'ns3::Ptr< ns3::AttributeValue >',
[param('ns3::AttributeValue const &', 'value')],
is_const=True)
## attribute.h (module 'core'): std::string ns3::AttributeChecker::GetUnderlyingTypeInformation() const [member function]
cls.add_method('GetUnderlyingTypeInformation',
'std::string',
[],
is_pure_virtual=True, is_const=True, is_virtual=True)
## attribute.h (module 'core'): std::string ns3::AttributeChecker::GetValueTypeName() const [member function]
cls.add_method('GetValueTypeName',
'std::string',
[],
is_pure_virtual=True, is_const=True, is_virtual=True)
## attribute.h (module 'core'): bool ns3::AttributeChecker::HasUnderlyingTypeInformation() const [member function]
cls.add_method('HasUnderlyingTypeInformation',
'bool',
[],
is_pure_virtual=True, is_const=True, is_virtual=True)
return
def register_Ns3AttributeValue_methods(root_module, cls):
## attribute.h (module 'core'): ns3::AttributeValue::AttributeValue(ns3::AttributeValue const & arg0) [copy constructor]
cls.add_constructor([param('ns3::AttributeValue const &', 'arg0')])
## attribute.h (module 'core'): ns3::AttributeValue::AttributeValue() [constructor]
cls.add_constructor([])
## attribute.h (module 'core'): ns3::Ptr<ns3::AttributeValue> ns3::AttributeValue::Copy() const [member function]
cls.add_method('Copy',
'ns3::Ptr< ns3::AttributeValue >',
[],
is_pure_virtual=True, is_const=True, is_virtual=True)
## attribute.h (module 'core'): bool ns3::AttributeValue::DeserializeFromString(std::string value, ns3::Ptr<ns3::AttributeChecker const> checker) [member function]
cls.add_method('DeserializeFromString',
'bool',
[param('std::string', 'value'), param('ns3::Ptr< ns3::AttributeChecker const >', 'checker')],
is_pure_virtual=True, is_virtual=True)
## attribute.h (module 'core'): std::string ns3::AttributeValue::SerializeToString(ns3::Ptr<ns3::AttributeChecker const> checker) const [member function]
cls.add_method('SerializeToString',
'std::string',
[param('ns3::Ptr< ns3::AttributeChecker const >', 'checker')],
is_pure_virtual=True, is_const=True, is_virtual=True)
return
def register_Ns3CallbackChecker_methods(root_module, cls):
## callback.h (module 'core'): ns3::CallbackChecker::CallbackChecker() [constructor]
cls.add_constructor([])
## callback.h (module 'core'): ns3::CallbackChecker::CallbackChecker(ns3::CallbackChecker const & arg0) [copy constructor]
cls.add_constructor([param('ns3::CallbackChecker const &', 'arg0')])
return
def register_Ns3CallbackImplBase_methods(root_module, cls):
## callback.h (module 'core'): ns3::CallbackImplBase::CallbackImplBase() [constructor]
cls.add_constructor([])
## callback.h (module 'core'): ns3::CallbackImplBase::CallbackImplBase(ns3::CallbackImplBase const & arg0) [copy constructor]
cls.add_constructor([param('ns3::CallbackImplBase const &', 'arg0')])
## callback.h (module 'core'): std::string ns3::CallbackImplBase::GetTypeid() const [member function]
cls.add_method('GetTypeid',
'std::string',
[],
is_pure_virtual=True, is_const=True, is_virtual=True)
## callback.h (module 'core'): bool ns3::CallbackImplBase::IsEqual(ns3::Ptr<ns3::CallbackImplBase const> other) const [member function]
cls.add_method('IsEqual',
'bool',
[param('ns3::Ptr< ns3::CallbackImplBase const >', 'other')],
is_pure_virtual=True, is_const=True, is_virtual=True)
## callback.h (module 'core'): static std::string ns3::CallbackImplBase::Demangle(std::string const & mangled) [member function]
cls.add_method('Demangle',
'std::string',
[param('std::string const &', 'mangled')],
is_static=True, visibility='protected')
return
def register_Ns3CallbackValue_methods(root_module, cls):
## callback.h (module 'core'): ns3::CallbackValue::CallbackValue(ns3::CallbackValue const & arg0) [copy constructor]
cls.add_constructor([param('ns3::CallbackValue const &', 'arg0')])
## callback.h (module 'core'): ns3::CallbackValue::CallbackValue() [constructor]
cls.add_constructor([])
## callback.h (module 'core'): ns3::CallbackValue::CallbackValue(ns3::CallbackBase const & base) [constructor]
cls.add_constructor([param('ns3::CallbackBase const &', 'base')])
## callback.h (module 'core'): ns3::Ptr<ns3::AttributeValue> ns3::CallbackValue::Copy() const [member function]
cls.add_method('Copy',
'ns3::Ptr< ns3::AttributeValue >',
[],
is_const=True, is_virtual=True)
## callback.h (module 'core'): bool ns3::CallbackValue::DeserializeFromString(std::string value, ns3::Ptr<ns3::AttributeChecker const> checker) [member function]
cls.add_method('DeserializeFromString',
'bool',
[param('std::string', 'value'), param('ns3::Ptr< ns3::AttributeChecker const >', 'checker')],
is_virtual=True)
## callback.h (module 'core'): std::string ns3::CallbackValue::SerializeToString(ns3::Ptr<ns3::AttributeChecker const> checker) const [member function]
cls.add_method('SerializeToString',
'std::string',
[param('ns3::Ptr< ns3::AttributeChecker const >', 'checker')],
is_const=True, is_virtual=True)
## callback.h (module 'core'): void ns3::CallbackValue::Set(ns3::CallbackBase base) [member function]
cls.add_method('Set',
'void',
[param('ns3::CallbackBase', 'base')])
return
def register_Ns3Channel_methods(root_module, cls):
## channel.h (module 'network'): ns3::Channel::Channel(ns3::Channel const & arg0) [copy constructor]
cls.add_constructor([param('ns3::Channel const &', 'arg0')])
## channel.h (module 'network'): ns3::Channel::Channel() [constructor]
cls.add_constructor([])
## channel.h (module 'network'): ns3::Ptr<ns3::NetDevice> ns3::Channel::GetDevice(uint32_t i) const [member function]
cls.add_method('GetDevice',
'ns3::Ptr< ns3::NetDevice >',
[param('uint32_t', 'i')],
is_pure_virtual=True, is_const=True, is_virtual=True)
## channel.h (module 'network'): uint32_t ns3::Channel::GetId() const [member function]
cls.add_method('GetId',
'uint32_t',
[],
is_const=True)
## channel.h (module 'network'): uint32_t ns3::Channel::GetNDevices() const [member function]
cls.add_method('GetNDevices',
'uint32_t',
[],
is_pure_virtual=True, is_const=True, is_virtual=True)
## channel.h (module 'network'): static ns3::TypeId ns3::Channel::GetTypeId() [member function]
cls.add_method('GetTypeId',
'ns3::TypeId',
[],
is_static=True)
return
def register_Ns3EmptyAttributeAccessor_methods(root_module, cls):
## attribute.h (module 'core'): ns3::EmptyAttributeAccessor::EmptyAttributeAccessor(ns3::EmptyAttributeAccessor const & arg0) [copy constructor]
cls.add_constructor([param('ns3::EmptyAttributeAccessor const &', 'arg0')])
## attribute.h (module 'core'): ns3::EmptyAttributeAccessor::EmptyAttributeAccessor() [constructor]
cls.add_constructor([])
## attribute.h (module 'core'): bool ns3::EmptyAttributeAccessor::Get(ns3::ObjectBase const * object, ns3::AttributeValue & attribute) const [member function]
cls.add_method('Get',
'bool',
[param('ns3::ObjectBase const *', 'object'), param('ns3::AttributeValue &', 'attribute')],
is_const=True, is_virtual=True)
## attribute.h (module 'core'): bool ns3::EmptyAttributeAccessor::HasGetter() const [member function]
cls.add_method('HasGetter',
'bool',
[],
is_const=True, is_virtual=True)
## attribute.h (module 'core'): bool ns3::EmptyAttributeAccessor::HasSetter() const [member function]
cls.add_method('HasSetter',
'bool',
[],
is_const=True, is_virtual=True)
## attribute.h (module 'core'): bool ns3::EmptyAttributeAccessor::Set(ns3::ObjectBase * object, ns3::AttributeValue const & value) const [member function]
cls.add_method('Set',
'bool',
[param('ns3::ObjectBase *', 'object'), param('ns3::AttributeValue const &', 'value')],
is_const=True, is_virtual=True)
return
def register_Ns3EmptyAttributeChecker_methods(root_module, cls):
## attribute.h (module 'core'): ns3::EmptyAttributeChecker::EmptyAttributeChecker(ns3::EmptyAttributeChecker const & arg0) [copy constructor]
cls.add_constructor([param('ns3::EmptyAttributeChecker const &', 'arg0')])
## attribute.h (module 'core'): ns3::EmptyAttributeChecker::EmptyAttributeChecker() [constructor]
cls.add_constructor([])
## attribute.h (module 'core'): bool ns3::EmptyAttributeChecker::Check(ns3::AttributeValue const & value) const [member function]
cls.add_method('Check',
'bool',
[param('ns3::AttributeValue const &', 'value')],
is_const=True, is_virtual=True)
## attribute.h (module 'core'): bool ns3::EmptyAttributeChecker::Copy(ns3::AttributeValue const & source, ns3::AttributeValue & destination) const [member function]
cls.add_method('Copy',
'bool',
[param('ns3::AttributeValue const &', 'source'), param('ns3::AttributeValue &', 'destination')],
is_const=True, is_virtual=True)
## attribute.h (module 'core'): ns3::Ptr<ns3::AttributeValue> ns3::EmptyAttributeChecker::Create() const [member function]
cls.add_method('Create',
'ns3::Ptr< ns3::AttributeValue >',
[],
is_const=True, is_virtual=True)
## attribute.h (module 'core'): std::string ns3::EmptyAttributeChecker::GetUnderlyingTypeInformation() const [member function]
cls.add_method('GetUnderlyingTypeInformation',
'std::string',
[],
is_const=True, is_virtual=True)
## attribute.h (module 'core'): std::string ns3::EmptyAttributeChecker::GetValueTypeName() const [member function]
cls.add_method('GetValueTypeName',
'std::string',
[],
is_const=True, is_virtual=True)
## attribute.h (module 'core'): bool ns3::EmptyAttributeChecker::HasUnderlyingTypeInformation() const [member function]
cls.add_method('HasUnderlyingTypeInformation',
'bool',
[],
is_const=True, is_virtual=True)
return
def register_Ns3EmptyAttributeValue_methods(root_module, cls):
## attribute.h (module 'core'): ns3::EmptyAttributeValue::EmptyAttributeValue(ns3::EmptyAttributeValue const & arg0) [copy constructor]
cls.add_constructor([param('ns3::EmptyAttributeValue const &', 'arg0')])
## attribute.h (module 'core'): ns3::EmptyAttributeValue::EmptyAttributeValue() [constructor]
cls.add_constructor([])
## attribute.h (module 'core'): ns3::Ptr<ns3::AttributeValue> ns3::EmptyAttributeValue::Copy() const [member function]
cls.add_method('Copy',
'ns3::Ptr< ns3::AttributeValue >',
[],
is_const=True, visibility='private', is_virtual=True)
## attribute.h (module 'core'): bool ns3::EmptyAttributeValue::DeserializeFromString(std::string value, ns3::Ptr<ns3::AttributeChecker const> checker) [member function]
cls.add_method('DeserializeFromString',
'bool',
[param('std::string', 'value'), param('ns3::Ptr< ns3::AttributeChecker const >', 'checker')],
visibility='private', is_virtual=True)
## attribute.h (module 'core'): std::string ns3::EmptyAttributeValue::SerializeToString(ns3::Ptr<ns3::AttributeChecker const> checker) const [member function]
cls.add_method('SerializeToString',
'std::string',
[param('ns3::Ptr< ns3::AttributeChecker const >', 'checker')],
is_const=True, visibility='private', is_virtual=True)
return
def register_Ns3EventImpl_methods(root_module, cls):
## event-impl.h (module 'core'): ns3::EventImpl::EventImpl(ns3::EventImpl const & arg0) [copy constructor]
cls.add_constructor([param('ns3::EventImpl const &', 'arg0')])
## event-impl.h (module 'core'): ns3::EventImpl::EventImpl() [constructor]
cls.add_constructor([])
## event-impl.h (module 'core'): void ns3::EventImpl::Cancel() [member function]
cls.add_method('Cancel',
'void',
[])
## event-impl.h (module 'core'): void ns3::EventImpl::Invoke() [member function]
cls.add_method('Invoke',
'void',
[])
## event-impl.h (module 'core'): bool ns3::EventImpl::IsCancelled() [member function]
cls.add_method('IsCancelled',
'bool',
[])
## event-impl.h (module 'core'): void ns3::EventImpl::Notify() [member function]
cls.add_method('Notify',
'void',
[],
is_pure_virtual=True, visibility='protected', is_virtual=True)
return
def register_Ns3Ipv4_methods(root_module, cls):
## ipv4.h (module 'internet'): ns3::Ipv4::Ipv4(ns3::Ipv4 const & arg0) [copy constructor]
cls.add_constructor([param('ns3::Ipv4 const &', 'arg0')])
## ipv4.h (module 'internet'): ns3::Ipv4::Ipv4() [constructor]
cls.add_constructor([])
## ipv4.h (module 'internet'): bool ns3::Ipv4::AddAddress(uint32_t interface, ns3::Ipv4InterfaceAddress address) [member function]
cls.add_method('AddAddress',
'bool',
[param('uint32_t', 'interface'), param('ns3::Ipv4InterfaceAddress', 'address')],
is_pure_virtual=True, is_virtual=True)
## ipv4.h (module 'internet'): uint32_t ns3::Ipv4::AddInterface(ns3::Ptr<ns3::NetDevice> device) [member function]
cls.add_method('AddInterface',
'uint32_t',
[param('ns3::Ptr< ns3::NetDevice >', 'device')],
is_pure_virtual=True, is_virtual=True)
## ipv4.h (module 'internet'): ns3::Ptr<ns3::Socket> ns3::Ipv4::CreateRawSocket() [member function]
cls.add_method('CreateRawSocket',
'ns3::Ptr< ns3::Socket >',
[],
is_pure_virtual=True, is_virtual=True)
## ipv4.h (module 'internet'): void ns3::Ipv4::DeleteRawSocket(ns3::Ptr<ns3::Socket> socket) [member function]
cls.add_method('DeleteRawSocket',
'void',
[param('ns3::Ptr< ns3::Socket >', 'socket')],
is_pure_virtual=True, is_virtual=True)
## ipv4.h (module 'internet'): ns3::Ipv4InterfaceAddress ns3::Ipv4::GetAddress(uint32_t interface, uint32_t addressIndex) const [member function]
cls.add_method('GetAddress',
'ns3::Ipv4InterfaceAddress',
[param('uint32_t', 'interface'), param('uint32_t', 'addressIndex')],
is_pure_virtual=True, is_const=True, is_virtual=True)
## ipv4.h (module 'internet'): int32_t ns3::Ipv4::GetInterfaceForAddress(ns3::Ipv4Address address) const [member function]
cls.add_method('GetInterfaceForAddress',
'int32_t',
[param('ns3::Ipv4Address', 'address')],
is_pure_virtual=True, is_const=True, is_virtual=True)
## ipv4.h (module 'internet'): int32_t ns3::Ipv4::GetInterfaceForDevice(ns3::Ptr<const ns3::NetDevice> device) const [member function]
cls.add_method('GetInterfaceForDevice',
'int32_t',
[param('ns3::Ptr< ns3::NetDevice const >', 'device')],
is_pure_virtual=True, is_const=True, is_virtual=True)
## ipv4.h (module 'internet'): int32_t ns3::Ipv4::GetInterfaceForPrefix(ns3::Ipv4Address address, ns3::Ipv4Mask mask) const [member function]
cls.add_method('GetInterfaceForPrefix',
'int32_t',
[param('ns3::Ipv4Address', 'address'), param('ns3::Ipv4Mask', 'mask')],
is_pure_virtual=True, is_const=True, is_virtual=True)
## ipv4.h (module 'internet'): uint16_t ns3::Ipv4::GetMetric(uint32_t interface) const [member function]
cls.add_method('GetMetric',
'uint16_t',
[param('uint32_t', 'interface')],
is_pure_virtual=True, is_const=True, is_virtual=True)
## ipv4.h (module 'internet'): uint16_t ns3::Ipv4::GetMtu(uint32_t interface) const [member function]
cls.add_method('GetMtu',
'uint16_t',
[param('uint32_t', 'interface')],
is_pure_virtual=True, is_const=True, is_virtual=True)
## ipv4.h (module 'internet'): uint32_t ns3::Ipv4::GetNAddresses(uint32_t interface) const [member function]
cls.add_method('GetNAddresses',
'uint32_t',
[param('uint32_t', 'interface')],
is_pure_virtual=True, is_const=True, is_virtual=True)
## ipv4.h (module 'internet'): uint32_t ns3::Ipv4::GetNInterfaces() const [member function]
cls.add_method('GetNInterfaces',
'uint32_t',
[],
is_pure_virtual=True, is_const=True, is_virtual=True)
## ipv4.h (module 'internet'): ns3::Ptr<ns3::NetDevice> ns3::Ipv4::GetNetDevice(uint32_t interface) [member function]
cls.add_method('GetNetDevice',
'ns3::Ptr< ns3::NetDevice >',
[param('uint32_t', 'interface')],
is_pure_virtual=True, is_virtual=True)
## ipv4.h (module 'internet'): ns3::Ptr<ns3::IpL4Protocol> ns3::Ipv4::GetProtocol(int protocolNumber) const [member function]
cls.add_method('GetProtocol',
'ns3::Ptr< ns3::IpL4Protocol >',
[param('int', 'protocolNumber')],
is_pure_virtual=True, is_const=True, is_virtual=True)
## ipv4.h (module 'internet'): ns3::Ptr<ns3::IpL4Protocol> ns3::Ipv4::GetProtocol(int protocolNumber, int32_t interfaceIndex) const [member function]
cls.add_method('GetProtocol',
'ns3::Ptr< ns3::IpL4Protocol >',
[param('int', 'protocolNumber'), param('int32_t', 'interfaceIndex')],
is_pure_virtual=True, is_const=True, is_virtual=True)
## ipv4.h (module 'internet'): ns3::Ptr<ns3::Ipv4RoutingProtocol> ns3::Ipv4::GetRoutingProtocol() const [member function]
cls.add_method('GetRoutingProtocol',
'ns3::Ptr< ns3::Ipv4RoutingProtocol >',
[],
is_pure_virtual=True, is_const=True, is_virtual=True)
## ipv4.h (module 'internet'): static ns3::TypeId ns3::Ipv4::GetTypeId() [member function]
cls.add_method('GetTypeId',
'ns3::TypeId',
[],
is_static=True)
## ipv4.h (module 'internet'): void ns3::Ipv4::Insert(ns3::Ptr<ns3::IpL4Protocol> protocol) [member function]
cls.add_method('Insert',
'void',
[param('ns3::Ptr< ns3::IpL4Protocol >', 'protocol')],
is_pure_virtual=True, is_virtual=True)
## ipv4.h (module 'internet'): void ns3::Ipv4::Insert(ns3::Ptr<ns3::IpL4Protocol> protocol, uint32_t interfaceIndex) [member function]
cls.add_method('Insert',
'void',
[param('ns3::Ptr< ns3::IpL4Protocol >', 'protocol'), param('uint32_t', 'interfaceIndex')],
is_pure_virtual=True, is_virtual=True)
## ipv4.h (module 'internet'): bool ns3::Ipv4::IsDestinationAddress(ns3::Ipv4Address address, uint32_t iif) const [member function]
cls.add_method('IsDestinationAddress',
'bool',
[param('ns3::Ipv4Address', 'address'), param('uint32_t', 'iif')],
is_pure_virtual=True, is_const=True, is_virtual=True)
## ipv4.h (module 'internet'): bool ns3::Ipv4::IsForwarding(uint32_t interface) const [member function]
cls.add_method('IsForwarding',
'bool',
[param('uint32_t', 'interface')],
is_pure_virtual=True, is_const=True, is_virtual=True)
## ipv4.h (module 'internet'): bool ns3::Ipv4::IsUp(uint32_t interface) const [member function]
cls.add_method('IsUp',
'bool',
[param('uint32_t', 'interface')],
is_pure_virtual=True, is_const=True, is_virtual=True)
## ipv4.h (module 'internet'): void ns3::Ipv4::Remove(ns3::Ptr<ns3::IpL4Protocol> protocol) [member function]
cls.add_method('Remove',
'void',
[param('ns3::Ptr< ns3::IpL4Protocol >', 'protocol')],
is_pure_virtual=True, is_virtual=True)
## ipv4.h (module 'internet'): void ns3::Ipv4::Remove(ns3::Ptr<ns3::IpL4Protocol> protocol, uint32_t interfaceIndex) [member function]
cls.add_method('Remove',
'void',
[param('ns3::Ptr< ns3::IpL4Protocol >', 'protocol'), param('uint32_t', 'interfaceIndex')],
is_pure_virtual=True, is_virtual=True)
## ipv4.h (module 'internet'): bool ns3::Ipv4::RemoveAddress(uint32_t interface, uint32_t addressIndex) [member function]
cls.add_method('RemoveAddress',
'bool',
[param('uint32_t', 'interface'), param('uint32_t', 'addressIndex')],
is_pure_virtual=True, is_virtual=True)
## ipv4.h (module 'internet'): bool ns3::Ipv4::RemoveAddress(uint32_t interface, ns3::Ipv4Address address) [member function]
cls.add_method('RemoveAddress',
'bool',
[param('uint32_t', 'interface'), param('ns3::Ipv4Address', 'address')],
is_pure_virtual=True, is_virtual=True)
## ipv4.h (module 'internet'): ns3::Ipv4Address ns3::Ipv4::SelectSourceAddress(ns3::Ptr<const ns3::NetDevice> device, ns3::Ipv4Address dst, ns3::Ipv4InterfaceAddress::InterfaceAddressScope_e scope) [member function]
cls.add_method('SelectSourceAddress',
'ns3::Ipv4Address',
[param('ns3::Ptr< ns3::NetDevice const >', 'device'), param('ns3::Ipv4Address', 'dst'), param('ns3::Ipv4InterfaceAddress::InterfaceAddressScope_e', 'scope')],
is_pure_virtual=True, is_virtual=True)
## ipv4.h (module 'internet'): void ns3::Ipv4::Send(ns3::Ptr<ns3::Packet> packet, ns3::Ipv4Address source, ns3::Ipv4Address destination, uint8_t protocol, ns3::Ptr<ns3::Ipv4Route> route) [member function]
cls.add_method('Send',
'void',
[param('ns3::Ptr< ns3::Packet >', 'packet'), param('ns3::Ipv4Address', 'source'), param('ns3::Ipv4Address', 'destination'), param('uint8_t', 'protocol'), param('ns3::Ptr< ns3::Ipv4Route >', 'route')],
is_pure_virtual=True, is_virtual=True)
## ipv4.h (module 'internet'): void ns3::Ipv4::SendWithHeader(ns3::Ptr<ns3::Packet> packet, ns3::Ipv4Header ipHeader, ns3::Ptr<ns3::Ipv4Route> route) [member function]
cls.add_method('SendWithHeader',
'void',
[param('ns3::Ptr< ns3::Packet >', 'packet'), param('ns3::Ipv4Header', 'ipHeader'), param('ns3::Ptr< ns3::Ipv4Route >', 'route')],
is_pure_virtual=True, is_virtual=True)
## ipv4.h (module 'internet'): void ns3::Ipv4::SetDown(uint32_t interface) [member function]
cls.add_method('SetDown',
'void',
[param('uint32_t', 'interface')],
is_pure_virtual=True, is_virtual=True)
## ipv4.h (module 'internet'): void ns3::Ipv4::SetForwarding(uint32_t interface, bool val) [member function]
cls.add_method('SetForwarding',
'void',
[param('uint32_t', 'interface'), param('bool', 'val')],
is_pure_virtual=True, is_virtual=True)
## ipv4.h (module 'internet'): void ns3::Ipv4::SetMetric(uint32_t interface, uint16_t metric) [member function]
cls.add_method('SetMetric',
'void',
[param('uint32_t', 'interface'), param('uint16_t', 'metric')],
is_pure_virtual=True, is_virtual=True)
## ipv4.h (module 'internet'): void ns3::Ipv4::SetRoutingProtocol(ns3::Ptr<ns3::Ipv4RoutingProtocol> routingProtocol) [member function]
cls.add_method('SetRoutingProtocol',
'void',
[param('ns3::Ptr< ns3::Ipv4RoutingProtocol >', 'routingProtocol')],
is_pure_virtual=True, is_virtual=True)
## ipv4.h (module 'internet'): void ns3::Ipv4::SetUp(uint32_t interface) [member function]
cls.add_method('SetUp',
'void',
[param('uint32_t', 'interface')],
is_pure_virtual=True, is_virtual=True)
## ipv4.h (module 'internet'): ns3::Ipv4Address ns3::Ipv4::SourceAddressSelection(uint32_t interface, ns3::Ipv4Address dest) [member function]
cls.add_method('SourceAddressSelection',
'ns3::Ipv4Address',
[param('uint32_t', 'interface'), param('ns3::Ipv4Address', 'dest')],
is_pure_virtual=True, is_virtual=True)
## ipv4.h (module 'internet'): ns3::Ipv4::IF_ANY [variable]
cls.add_static_attribute('IF_ANY', 'uint32_t const', is_const=True)
## ipv4.h (module 'internet'): bool ns3::Ipv4::GetIpForward() const [member function]
cls.add_method('GetIpForward',
'bool',
[],
is_pure_virtual=True, is_const=True, visibility='private', is_virtual=True)
## ipv4.h (module 'internet'): bool ns3::Ipv4::GetWeakEsModel() const [member function]
cls.add_method('GetWeakEsModel',
'bool',
[],
is_pure_virtual=True, is_const=True, visibility='private', is_virtual=True)
## ipv4.h (module 'internet'): void ns3::Ipv4::SetIpForward(bool forward) [member function]
cls.add_method('SetIpForward',
'void',
[param('bool', 'forward')],
is_pure_virtual=True, visibility='private', is_virtual=True)
## ipv4.h (module 'internet'): void ns3::Ipv4::SetWeakEsModel(bool model) [member function]
cls.add_method('SetWeakEsModel',
'void',
[param('bool', 'model')],
is_pure_virtual=True, visibility='private', is_virtual=True)
return
def register_Ns3Ipv4AddressChecker_methods(root_module, cls):
## ipv4-address.h (module 'network'): ns3::Ipv4AddressChecker::Ipv4AddressChecker() [constructor]
cls.add_constructor([])
## ipv4-address.h (module 'network'): ns3::Ipv4AddressChecker::Ipv4AddressChecker(ns3::Ipv4AddressChecker const & arg0) [copy constructor]
cls.add_constructor([param('ns3::Ipv4AddressChecker const &', 'arg0')])
return
def register_Ns3Ipv4AddressValue_methods(root_module, cls):
## ipv4-address.h (module 'network'): ns3::Ipv4AddressValue::Ipv4AddressValue() [constructor]
cls.add_constructor([])
## ipv4-address.h (module 'network'): ns3::Ipv4AddressValue::Ipv4AddressValue(ns3::Ipv4AddressValue const & arg0) [copy constructor]
cls.add_constructor([param('ns3::Ipv4AddressValue const &', 'arg0')])
## ipv4-address.h (module 'network'): ns3::Ipv4AddressValue::Ipv4AddressValue(ns3::Ipv4Address const & value) [constructor]
cls.add_constructor([param('ns3::Ipv4Address const &', 'value')])
## ipv4-address.h (module 'network'): ns3::Ptr<ns3::AttributeValue> ns3::Ipv4AddressValue::Copy() const [member function]
cls.add_method('Copy',
'ns3::Ptr< ns3::AttributeValue >',
[],
is_const=True, is_virtual=True)
## ipv4-address.h (module 'network'): bool ns3::Ipv4AddressValue::DeserializeFromString(std::string value, ns3::Ptr<ns3::AttributeChecker const> checker) [member function]
cls.add_method('DeserializeFromString',
'bool',
[param('std::string', 'value'), param('ns3::Ptr< ns3::AttributeChecker const >', 'checker')],
is_virtual=True)
## ipv4-address.h (module 'network'): ns3::Ipv4Address ns3::Ipv4AddressValue::Get() const [member function]
cls.add_method('Get',
'ns3::Ipv4Address',
[],
is_const=True)
## ipv4-address.h (module 'network'): std::string ns3::Ipv4AddressValue::SerializeToString(ns3::Ptr<ns3::AttributeChecker const> checker) const [member function]
cls.add_method('SerializeToString',
'std::string',
[param('ns3::Ptr< ns3::AttributeChecker const >', 'checker')],
is_const=True, is_virtual=True)
## ipv4-address.h (module 'network'): void ns3::Ipv4AddressValue::Set(ns3::Ipv4Address const & value) [member function]
cls.add_method('Set',
'void',
[param('ns3::Ipv4Address const &', 'value')])
return
def register_Ns3Ipv4L3Protocol_methods(root_module, cls):
## ipv4-l3-protocol.h (module 'internet'): ns3::Ipv4L3Protocol::Ipv4L3Protocol() [constructor]
cls.add_constructor([])
## ipv4-l3-protocol.h (module 'internet'): bool ns3::Ipv4L3Protocol::AddAddress(uint32_t i, ns3::Ipv4InterfaceAddress address) [member function]
cls.add_method('AddAddress',
'bool',
[param('uint32_t', 'i'), param('ns3::Ipv4InterfaceAddress', 'address')],
is_virtual=True)
## ipv4-l3-protocol.h (module 'internet'): uint32_t ns3::Ipv4L3Protocol::AddInterface(ns3::Ptr<ns3::NetDevice> device) [member function]
cls.add_method('AddInterface',
'uint32_t',
[param('ns3::Ptr< ns3::NetDevice >', 'device')],
is_virtual=True)
## ipv4-l3-protocol.h (module 'internet'): ns3::Ptr<ns3::Socket> ns3::Ipv4L3Protocol::CreateRawSocket() [member function]
cls.add_method('CreateRawSocket',
'ns3::Ptr< ns3::Socket >',
[],
is_virtual=True)
## ipv4-l3-protocol.h (module 'internet'): void ns3::Ipv4L3Protocol::DeleteRawSocket(ns3::Ptr<ns3::Socket> socket) [member function]
cls.add_method('DeleteRawSocket',
'void',
[param('ns3::Ptr< ns3::Socket >', 'socket')],
is_virtual=True)
## ipv4-l3-protocol.h (module 'internet'): ns3::Ipv4InterfaceAddress ns3::Ipv4L3Protocol::GetAddress(uint32_t interfaceIndex, uint32_t addressIndex) const [member function]
cls.add_method('GetAddress',
'ns3::Ipv4InterfaceAddress',
[param('uint32_t', 'interfaceIndex'), param('uint32_t', 'addressIndex')],
is_const=True, is_virtual=True)
## ipv4-l3-protocol.h (module 'internet'): ns3::Ptr<ns3::Ipv4Interface> ns3::Ipv4L3Protocol::GetInterface(uint32_t i) const [member function]
cls.add_method('GetInterface',
'ns3::Ptr< ns3::Ipv4Interface >',
[param('uint32_t', 'i')],
is_const=True)
## ipv4-l3-protocol.h (module 'internet'): int32_t ns3::Ipv4L3Protocol::GetInterfaceForAddress(ns3::Ipv4Address addr) const [member function]
cls.add_method('GetInterfaceForAddress',
'int32_t',
[param('ns3::Ipv4Address', 'addr')],
is_const=True, is_virtual=True)
## ipv4-l3-protocol.h (module 'internet'): int32_t ns3::Ipv4L3Protocol::GetInterfaceForDevice(ns3::Ptr<const ns3::NetDevice> device) const [member function]
cls.add_method('GetInterfaceForDevice',
'int32_t',
[param('ns3::Ptr< ns3::NetDevice const >', 'device')],
is_const=True, is_virtual=True)
## ipv4-l3-protocol.h (module 'internet'): int32_t ns3::Ipv4L3Protocol::GetInterfaceForPrefix(ns3::Ipv4Address addr, ns3::Ipv4Mask mask) const [member function]
cls.add_method('GetInterfaceForPrefix',
'int32_t',
[param('ns3::Ipv4Address', 'addr'), param('ns3::Ipv4Mask', 'mask')],
is_const=True, is_virtual=True)
## ipv4-l3-protocol.h (module 'internet'): uint16_t ns3::Ipv4L3Protocol::GetMetric(uint32_t i) const [member function]
cls.add_method('GetMetric',
'uint16_t',
[param('uint32_t', 'i')],
is_const=True, is_virtual=True)
## ipv4-l3-protocol.h (module 'internet'): uint16_t ns3::Ipv4L3Protocol::GetMtu(uint32_t i) const [member function]
cls.add_method('GetMtu',
'uint16_t',
[param('uint32_t', 'i')],
is_const=True, is_virtual=True)
## ipv4-l3-protocol.h (module 'internet'): uint32_t ns3::Ipv4L3Protocol::GetNAddresses(uint32_t interface) const [member function]
cls.add_method('GetNAddresses',
'uint32_t',
[param('uint32_t', 'interface')],
is_const=True, is_virtual=True)
## ipv4-l3-protocol.h (module 'internet'): uint32_t ns3::Ipv4L3Protocol::GetNInterfaces() const [member function]
cls.add_method('GetNInterfaces',
'uint32_t',
[],
is_const=True, is_virtual=True)
## ipv4-l3-protocol.h (module 'internet'): ns3::Ptr<ns3::NetDevice> ns3::Ipv4L3Protocol::GetNetDevice(uint32_t i) [member function]
cls.add_method('GetNetDevice',
'ns3::Ptr< ns3::NetDevice >',
[param('uint32_t', 'i')],
is_virtual=True)
## ipv4-l3-protocol.h (module 'internet'): ns3::Ptr<ns3::IpL4Protocol> ns3::Ipv4L3Protocol::GetProtocol(int protocolNumber) const [member function]
cls.add_method('GetProtocol',
'ns3::Ptr< ns3::IpL4Protocol >',
[param('int', 'protocolNumber')],
is_const=True, is_virtual=True)
## ipv4-l3-protocol.h (module 'internet'): ns3::Ptr<ns3::IpL4Protocol> ns3::Ipv4L3Protocol::GetProtocol(int protocolNumber, int32_t interfaceIndex) const [member function]
cls.add_method('GetProtocol',
'ns3::Ptr< ns3::IpL4Protocol >',
[param('int', 'protocolNumber'), param('int32_t', 'interfaceIndex')],
is_const=True, is_virtual=True)
## ipv4-l3-protocol.h (module 'internet'): ns3::Ptr<ns3::Ipv4RoutingProtocol> ns3::Ipv4L3Protocol::GetRoutingProtocol() const [member function]
cls.add_method('GetRoutingProtocol',
'ns3::Ptr< ns3::Ipv4RoutingProtocol >',
[],
is_const=True, is_virtual=True)
## ipv4-l3-protocol.h (module 'internet'): static ns3::TypeId ns3::Ipv4L3Protocol::GetTypeId() [member function]
cls.add_method('GetTypeId',
'ns3::TypeId',
[],
is_static=True)
## ipv4-l3-protocol.h (module 'internet'): void ns3::Ipv4L3Protocol::Insert(ns3::Ptr<ns3::IpL4Protocol> protocol) [member function]
cls.add_method('Insert',
'void',
[param('ns3::Ptr< ns3::IpL4Protocol >', 'protocol')],
is_virtual=True)
## ipv4-l3-protocol.h (module 'internet'): void ns3::Ipv4L3Protocol::Insert(ns3::Ptr<ns3::IpL4Protocol> protocol, uint32_t interfaceIndex) [member function]
cls.add_method('Insert',
'void',
[param('ns3::Ptr< ns3::IpL4Protocol >', 'protocol'), param('uint32_t', 'interfaceIndex')],
is_virtual=True)
## ipv4-l3-protocol.h (module 'internet'): bool ns3::Ipv4L3Protocol::IsDestinationAddress(ns3::Ipv4Address address, uint32_t iif) const [member function]
cls.add_method('IsDestinationAddress',
'bool',
[param('ns3::Ipv4Address', 'address'), param('uint32_t', 'iif')],
is_const=True, is_virtual=True)
## ipv4-l3-protocol.h (module 'internet'): bool ns3::Ipv4L3Protocol::IsForwarding(uint32_t i) const [member function]
cls.add_method('IsForwarding',
'bool',
[param('uint32_t', 'i')],
is_const=True, is_virtual=True)
## ipv4-l3-protocol.h (module 'internet'): bool ns3::Ipv4L3Protocol::IsUnicast(ns3::Ipv4Address ad) const [member function]
cls.add_method('IsUnicast',
'bool',
[param('ns3::Ipv4Address', 'ad')],
is_const=True)
## ipv4-l3-protocol.h (module 'internet'): bool ns3::Ipv4L3Protocol::IsUp(uint32_t i) const [member function]
cls.add_method('IsUp',
'bool',
[param('uint32_t', 'i')],
is_const=True, is_virtual=True)
## ipv4-l3-protocol.h (module 'internet'): void ns3::Ipv4L3Protocol::Receive(ns3::Ptr<ns3::NetDevice> device, ns3::Ptr<const ns3::Packet> p, uint16_t protocol, ns3::Address const & from, ns3::Address const & to, ns3::NetDevice::PacketType packetType) [member function]
cls.add_method('Receive',
'void',
[param('ns3::Ptr< ns3::NetDevice >', 'device'), param('ns3::Ptr< ns3::Packet const >', 'p'), param('uint16_t', 'protocol'), param('ns3::Address const &', 'from'), param('ns3::Address const &', 'to'), param('ns3::NetDevice::PacketType', 'packetType')])
## ipv4-l3-protocol.h (module 'internet'): void ns3::Ipv4L3Protocol::Remove(ns3::Ptr<ns3::IpL4Protocol> protocol) [member function]
cls.add_method('Remove',
'void',
[param('ns3::Ptr< ns3::IpL4Protocol >', 'protocol')],
is_virtual=True)
## ipv4-l3-protocol.h (module 'internet'): void ns3::Ipv4L3Protocol::Remove(ns3::Ptr<ns3::IpL4Protocol> protocol, uint32_t interfaceIndex) [member function]
cls.add_method('Remove',
'void',
[param('ns3::Ptr< ns3::IpL4Protocol >', 'protocol'), param('uint32_t', 'interfaceIndex')],
is_virtual=True)
## ipv4-l3-protocol.h (module 'internet'): bool ns3::Ipv4L3Protocol::RemoveAddress(uint32_t interfaceIndex, uint32_t addressIndex) [member function]
cls.add_method('RemoveAddress',
'bool',
[param('uint32_t', 'interfaceIndex'), param('uint32_t', 'addressIndex')],
is_virtual=True)
## ipv4-l3-protocol.h (module 'internet'): bool ns3::Ipv4L3Protocol::RemoveAddress(uint32_t interface, ns3::Ipv4Address address) [member function]
cls.add_method('RemoveAddress',
'bool',
[param('uint32_t', 'interface'), param('ns3::Ipv4Address', 'address')],
is_virtual=True)
## ipv4-l3-protocol.h (module 'internet'): ns3::Ipv4Address ns3::Ipv4L3Protocol::SelectSourceAddress(ns3::Ptr<const ns3::NetDevice> device, ns3::Ipv4Address dst, ns3::Ipv4InterfaceAddress::InterfaceAddressScope_e scope) [member function]
cls.add_method('SelectSourceAddress',
'ns3::Ipv4Address',
[param('ns3::Ptr< ns3::NetDevice const >', 'device'), param('ns3::Ipv4Address', 'dst'), param('ns3::Ipv4InterfaceAddress::InterfaceAddressScope_e', 'scope')],
is_virtual=True)
## ipv4-l3-protocol.h (module 'internet'): void ns3::Ipv4L3Protocol::Send(ns3::Ptr<ns3::Packet> packet, ns3::Ipv4Address source, ns3::Ipv4Address destination, uint8_t protocol, ns3::Ptr<ns3::Ipv4Route> route) [member function]
cls.add_method('Send',
'void',
[param('ns3::Ptr< ns3::Packet >', 'packet'), param('ns3::Ipv4Address', 'source'), param('ns3::Ipv4Address', 'destination'), param('uint8_t', 'protocol'), param('ns3::Ptr< ns3::Ipv4Route >', 'route')],
is_virtual=True)
## ipv4-l3-protocol.h (module 'internet'): void ns3::Ipv4L3Protocol::SendWithHeader(ns3::Ptr<ns3::Packet> packet, ns3::Ipv4Header ipHeader, ns3::Ptr<ns3::Ipv4Route> route) [member function]
cls.add_method('SendWithHeader',
'void',
[param('ns3::Ptr< ns3::Packet >', 'packet'), param('ns3::Ipv4Header', 'ipHeader'), param('ns3::Ptr< ns3::Ipv4Route >', 'route')],
is_virtual=True)
## ipv4-l3-protocol.h (module 'internet'): void ns3::Ipv4L3Protocol::SetDefaultTtl(uint8_t ttl) [member function]
cls.add_method('SetDefaultTtl',
'void',
[param('uint8_t', 'ttl')])
## ipv4-l3-protocol.h (module 'internet'): void ns3::Ipv4L3Protocol::SetDown(uint32_t i) [member function]
cls.add_method('SetDown',
'void',
[param('uint32_t', 'i')],
is_virtual=True)
## ipv4-l3-protocol.h (module 'internet'): void ns3::Ipv4L3Protocol::SetForwarding(uint32_t i, bool val) [member function]
cls.add_method('SetForwarding',
'void',
[param('uint32_t', 'i'), param('bool', 'val')],
is_virtual=True)
## ipv4-l3-protocol.h (module 'internet'): void ns3::Ipv4L3Protocol::SetMetric(uint32_t i, uint16_t metric) [member function]
cls.add_method('SetMetric',
'void',
[param('uint32_t', 'i'), param('uint16_t', 'metric')],
is_virtual=True)
## ipv4-l3-protocol.h (module 'internet'): void ns3::Ipv4L3Protocol::SetNode(ns3::Ptr<ns3::Node> node) [member function]
cls.add_method('SetNode',
'void',
[param('ns3::Ptr< ns3::Node >', 'node')])
## ipv4-l3-protocol.h (module 'internet'): void ns3::Ipv4L3Protocol::SetRoutingProtocol(ns3::Ptr<ns3::Ipv4RoutingProtocol> routingProtocol) [member function]
cls.add_method('SetRoutingProtocol',
'void',
[param('ns3::Ptr< ns3::Ipv4RoutingProtocol >', 'routingProtocol')],
is_virtual=True)
## ipv4-l3-protocol.h (module 'internet'): void ns3::Ipv4L3Protocol::SetUp(uint32_t i) [member function]
cls.add_method('SetUp',
'void',
[param('uint32_t', 'i')],
is_virtual=True)
## ipv4-l3-protocol.h (module 'internet'): ns3::Ipv4Address ns3::Ipv4L3Protocol::SourceAddressSelection(uint32_t interface, ns3::Ipv4Address dest) [member function]
cls.add_method('SourceAddressSelection',
'ns3::Ipv4Address',
[param('uint32_t', 'interface'), param('ns3::Ipv4Address', 'dest')],
is_virtual=True)
## ipv4-l3-protocol.h (module 'internet'): ns3::Ipv4L3Protocol::PROT_NUMBER [variable]
cls.add_static_attribute('PROT_NUMBER', 'uint16_t const', is_const=True)
## ipv4-l3-protocol.h (module 'internet'): void ns3::Ipv4L3Protocol::DoDispose() [member function]
cls.add_method('DoDispose',
'void',
[],
visibility='protected', is_virtual=True)
## ipv4-l3-protocol.h (module 'internet'): void ns3::Ipv4L3Protocol::NotifyNewAggregate() [member function]
cls.add_method('NotifyNewAggregate',
'void',
[],
visibility='protected', is_virtual=True)
## ipv4-l3-protocol.h (module 'internet'): bool ns3::Ipv4L3Protocol::GetIpForward() const [member function]
cls.add_method('GetIpForward',
'bool',
[],
is_const=True, visibility='private', is_virtual=True)
## ipv4-l3-protocol.h (module 'internet'): bool ns3::Ipv4L3Protocol::GetWeakEsModel() const [member function]
cls.add_method('GetWeakEsModel',
'bool',
[],
is_const=True, visibility='private', is_virtual=True)
## ipv4-l3-protocol.h (module 'internet'): void ns3::Ipv4L3Protocol::SetIpForward(bool forward) [member function]
cls.add_method('SetIpForward',
'void',
[param('bool', 'forward')],
visibility='private', is_virtual=True)
## ipv4-l3-protocol.h (module 'internet'): void ns3::Ipv4L3Protocol::SetWeakEsModel(bool model) [member function]
cls.add_method('SetWeakEsModel',
'void',
[param('bool', 'model')],
visibility='private', is_virtual=True)
return
def register_Ns3Ipv4MaskChecker_methods(root_module, cls):
## ipv4-address.h (module 'network'): ns3::Ipv4MaskChecker::Ipv4MaskChecker() [constructor]
cls.add_constructor([])
## ipv4-address.h (module 'network'): ns3::Ipv4MaskChecker::Ipv4MaskChecker(ns3::Ipv4MaskChecker const & arg0) [copy constructor]
cls.add_constructor([param('ns3::Ipv4MaskChecker const &', 'arg0')])
return
def register_Ns3Ipv4MaskValue_methods(root_module, cls):
## ipv4-address.h (module 'network'): ns3::Ipv4MaskValue::Ipv4MaskValue() [constructor]
cls.add_constructor([])
## ipv4-address.h (module 'network'): ns3::Ipv4MaskValue::Ipv4MaskValue(ns3::Ipv4MaskValue const & arg0) [copy constructor]
cls.add_constructor([param('ns3::Ipv4MaskValue const &', 'arg0')])
## ipv4-address.h (module 'network'): ns3::Ipv4MaskValue::Ipv4MaskValue(ns3::Ipv4Mask const & value) [constructor]
cls.add_constructor([param('ns3::Ipv4Mask const &', 'value')])
## ipv4-address.h (module 'network'): ns3::Ptr<ns3::AttributeValue> ns3::Ipv4MaskValue::Copy() const [member function]
cls.add_method('Copy',
'ns3::Ptr< ns3::AttributeValue >',
[],
is_const=True, is_virtual=True)
## ipv4-address.h (module 'network'): bool ns3::Ipv4MaskValue::DeserializeFromString(std::string value, ns3::Ptr<ns3::AttributeChecker const> checker) [member function]
cls.add_method('DeserializeFromString',
'bool',
[param('std::string', 'value'), param('ns3::Ptr< ns3::AttributeChecker const >', 'checker')],
is_virtual=True)
## ipv4-address.h (module 'network'): ns3::Ipv4Mask ns3::Ipv4MaskValue::Get() const [member function]
cls.add_method('Get',
'ns3::Ipv4Mask',
[],
is_const=True)
## ipv4-address.h (module 'network'): std::string ns3::Ipv4MaskValue::SerializeToString(ns3::Ptr<ns3::AttributeChecker const> checker) const [member function]
cls.add_method('SerializeToString',
'std::string',
[param('ns3::Ptr< ns3::AttributeChecker const >', 'checker')],
is_const=True, is_virtual=True)
## ipv4-address.h (module 'network'): void ns3::Ipv4MaskValue::Set(ns3::Ipv4Mask const & value) [member function]
cls.add_method('Set',
'void',
[param('ns3::Ipv4Mask const &', 'value')])
return
def register_Ns3Ipv4MulticastRoute_methods(root_module, cls):
## ipv4-route.h (module 'internet'): ns3::Ipv4MulticastRoute::Ipv4MulticastRoute(ns3::Ipv4MulticastRoute const & arg0) [copy constructor]
cls.add_constructor([param('ns3::Ipv4MulticastRoute const &', 'arg0')])
## ipv4-route.h (module 'internet'): ns3::Ipv4MulticastRoute::Ipv4MulticastRoute() [constructor]
cls.add_constructor([])
## ipv4-route.h (module 'internet'): ns3::Ipv4Address ns3::Ipv4MulticastRoute::GetGroup() const [member function]
cls.add_method('GetGroup',
'ns3::Ipv4Address',
[],
is_const=True)
## ipv4-route.h (module 'internet'): ns3::Ipv4Address ns3::Ipv4MulticastRoute::GetOrigin() const [member function]
cls.add_method('GetOrigin',
'ns3::Ipv4Address',
[],
is_const=True)
## ipv4-route.h (module 'internet'): std::map<unsigned int, unsigned int, std::less<unsigned int>, std::allocator<std::pair<unsigned int const, unsigned int> > > ns3::Ipv4MulticastRoute::GetOutputTtlMap() const [member function]
cls.add_method('GetOutputTtlMap',
'std::map< unsigned int, unsigned int >',
[],
is_const=True)
## ipv4-route.h (module 'internet'): uint32_t ns3::Ipv4MulticastRoute::GetParent() const [member function]
cls.add_method('GetParent',
'uint32_t',
[],
is_const=True)
## ipv4-route.h (module 'internet'): void ns3::Ipv4MulticastRoute::SetGroup(ns3::Ipv4Address const group) [member function]
cls.add_method('SetGroup',
'void',
[param('ns3::Ipv4Address const', 'group')])
## ipv4-route.h (module 'internet'): void ns3::Ipv4MulticastRoute::SetOrigin(ns3::Ipv4Address const origin) [member function]
cls.add_method('SetOrigin',
'void',
[param('ns3::Ipv4Address const', 'origin')])
## ipv4-route.h (module 'internet'): void ns3::Ipv4MulticastRoute::SetOutputTtl(uint32_t oif, uint32_t ttl) [member function]
cls.add_method('SetOutputTtl',
'void',
[param('uint32_t', 'oif'), param('uint32_t', 'ttl')])
## ipv4-route.h (module 'internet'): void ns3::Ipv4MulticastRoute::SetParent(uint32_t iif) [member function]
cls.add_method('SetParent',
'void',
[param('uint32_t', 'iif')])
## ipv4-route.h (module 'internet'): ns3::Ipv4MulticastRoute::MAX_INTERFACES [variable]
cls.add_static_attribute('MAX_INTERFACES', 'uint32_t const', is_const=True)
## ipv4-route.h (module 'internet'): ns3::Ipv4MulticastRoute::MAX_TTL [variable]
cls.add_static_attribute('MAX_TTL', 'uint32_t const', is_const=True)
return
def register_Ns3Ipv4Route_methods(root_module, cls):
cls.add_output_stream_operator()
## ipv4-route.h (module 'internet'): ns3::Ipv4Route::Ipv4Route(ns3::Ipv4Route const & arg0) [copy constructor]
cls.add_constructor([param('ns3::Ipv4Route const &', 'arg0')])
## ipv4-route.h (module 'internet'): ns3::Ipv4Route::Ipv4Route() [constructor]
cls.add_constructor([])
## ipv4-route.h (module 'internet'): ns3::Ipv4Address ns3::Ipv4Route::GetDestination() const [member function]
cls.add_method('GetDestination',
'ns3::Ipv4Address',
[],
is_const=True)
## ipv4-route.h (module 'internet'): ns3::Ipv4Address ns3::Ipv4Route::GetGateway() const [member function]
cls.add_method('GetGateway',
'ns3::Ipv4Address',
[],
is_const=True)
## ipv4-route.h (module 'internet'): ns3::Ptr<ns3::NetDevice> ns3::Ipv4Route::GetOutputDevice() const [member function]
cls.add_method('GetOutputDevice',
'ns3::Ptr< ns3::NetDevice >',
[],
is_const=True)
## ipv4-route.h (module 'internet'): ns3::Ipv4Address ns3::Ipv4Route::GetSource() const [member function]
cls.add_method('GetSource',
'ns3::Ipv4Address',
[],
is_const=True)
## ipv4-route.h (module 'internet'): void ns3::Ipv4Route::SetDestination(ns3::Ipv4Address dest) [member function]
cls.add_method('SetDestination',
'void',
[param('ns3::Ipv4Address', 'dest')])
## ipv4-route.h (module 'internet'): void ns3::Ipv4Route::SetGateway(ns3::Ipv4Address gw) [member function]
cls.add_method('SetGateway',
'void',
[param('ns3::Ipv4Address', 'gw')])
## ipv4-route.h (module 'internet'): void ns3::Ipv4Route::SetOutputDevice(ns3::Ptr<ns3::NetDevice> outputDevice) [member function]
cls.add_method('SetOutputDevice',
'void',
[param('ns3::Ptr< ns3::NetDevice >', 'outputDevice')])
## ipv4-route.h (module 'internet'): void ns3::Ipv4Route::SetSource(ns3::Ipv4Address src) [member function]
cls.add_method('SetSource',
'void',
[param('ns3::Ipv4Address', 'src')])
return
def register_Ns3Ipv4RoutingProtocol_methods(root_module, cls):
## ipv4-routing-protocol.h (module 'internet'): ns3::Ipv4RoutingProtocol::Ipv4RoutingProtocol() [constructor]
cls.add_constructor([])
## ipv4-routing-protocol.h (module 'internet'): ns3::Ipv4RoutingProtocol::Ipv4RoutingProtocol(ns3::Ipv4RoutingProtocol const & arg0) [copy constructor]
cls.add_constructor([param('ns3::Ipv4RoutingProtocol const &', 'arg0')])
## ipv4-routing-protocol.h (module 'internet'): static ns3::TypeId ns3::Ipv4RoutingProtocol::GetTypeId() [member function]
cls.add_method('GetTypeId',
'ns3::TypeId',
[],
is_static=True)
## ipv4-routing-protocol.h (module 'internet'): void ns3::Ipv4RoutingProtocol::NotifyAddAddress(uint32_t interface, ns3::Ipv4InterfaceAddress address) [member function]
cls.add_method('NotifyAddAddress',
'void',
[param('uint32_t', 'interface'), param('ns3::Ipv4InterfaceAddress', 'address')],
is_pure_virtual=True, is_virtual=True)
## ipv4-routing-protocol.h (module 'internet'): void ns3::Ipv4RoutingProtocol::NotifyInterfaceDown(uint32_t interface) [member function]
cls.add_method('NotifyInterfaceDown',
'void',
[param('uint32_t', 'interface')],
is_pure_virtual=True, is_virtual=True)
## ipv4-routing-protocol.h (module 'internet'): void ns3::Ipv4RoutingProtocol::NotifyInterfaceUp(uint32_t interface) [member function]
cls.add_method('NotifyInterfaceUp',
'void',
[param('uint32_t', 'interface')],
is_pure_virtual=True, is_virtual=True)
## ipv4-routing-protocol.h (module 'internet'): void ns3::Ipv4RoutingProtocol::NotifyRemoveAddress(uint32_t interface, ns3::Ipv4InterfaceAddress address) [member function]
cls.add_method('NotifyRemoveAddress',
'void',
[param('uint32_t', 'interface'), param('ns3::Ipv4InterfaceAddress', 'address')],
is_pure_virtual=True, is_virtual=True)
## ipv4-routing-protocol.h (module 'internet'): void ns3::Ipv4RoutingProtocol::PrintRoutingTable(ns3::Ptr<ns3::OutputStreamWrapper> stream) const [member function]
cls.add_method('PrintRoutingTable',
'void',
[param('ns3::Ptr< ns3::OutputStreamWrapper >', 'stream')],
is_pure_virtual=True, is_const=True, is_virtual=True)
## ipv4-routing-protocol.h (module 'internet'): bool ns3::Ipv4RoutingProtocol::RouteInput(ns3::Ptr<const ns3::Packet> p, ns3::Ipv4Header const & header, ns3::Ptr<const ns3::NetDevice> idev, ns3::Callback<void,ns3::Ptr<ns3::Ipv4Route>,ns3::Ptr<const ns3::Packet>,const ns3::Ipv4Header&,ns3::empty,ns3::empty,ns3::empty,ns3::empty,ns3::empty,ns3::empty> ucb, ns3::Callback<void,ns3::Ptr<ns3::Ipv4MulticastRoute>,ns3::Ptr<const ns3::Packet>,const ns3::Ipv4Header&,ns3::empty,ns3::empty,ns3::empty,ns3::empty,ns3::empty,ns3::empty> mcb, ns3::Callback<void,ns3::Ptr<const ns3::Packet>,const ns3::Ipv4Header&,unsigned int,ns3::empty,ns3::empty,ns3::empty,ns3::empty,ns3::empty,ns3::empty> lcb, ns3::Callback<void,ns3::Ptr<const ns3::Packet>,const ns3::Ipv4Header&,ns3::Socket::SocketErrno,ns3::empty,ns3::empty,ns3::empty,ns3::empty,ns3::empty,ns3::empty> ecb) [member function]
cls.add_method('RouteInput',
'bool',
[param('ns3::Ptr< ns3::Packet const >', 'p'), param('ns3::Ipv4Header const &', 'header'), param('ns3::Ptr< ns3::NetDevice const >', 'idev'), param('ns3::Callback< void, ns3::Ptr< ns3::Ipv4Route >, ns3::Ptr< ns3::Packet const >, ns3::Ipv4Header const &, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty >', 'ucb'), param('ns3::Callback< void, ns3::Ptr< ns3::Ipv4MulticastRoute >, ns3::Ptr< ns3::Packet const >, ns3::Ipv4Header const &, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty >', 'mcb'), param('ns3::Callback< void, ns3::Ptr< ns3::Packet const >, ns3::Ipv4Header const &, unsigned int, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty >', 'lcb'), param('ns3::Callback< void, ns3::Ptr< ns3::Packet const >, ns3::Ipv4Header const &, ns3::Socket::SocketErrno, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty >', 'ecb')],
is_pure_virtual=True, is_virtual=True)
## ipv4-routing-protocol.h (module 'internet'): ns3::Ptr<ns3::Ipv4Route> ns3::Ipv4RoutingProtocol::RouteOutput(ns3::Ptr<ns3::Packet> p, ns3::Ipv4Header const & header, ns3::Ptr<ns3::NetDevice> oif, ns3::Socket::SocketErrno & sockerr) [member function]
cls.add_method('RouteOutput',
'ns3::Ptr< ns3::Ipv4Route >',
[param('ns3::Ptr< ns3::Packet >', 'p'), param('ns3::Ipv4Header const &', 'header'), param('ns3::Ptr< ns3::NetDevice >', 'oif'), param('ns3::Socket::SocketErrno &', 'sockerr')],
is_pure_virtual=True, is_virtual=True)
## ipv4-routing-protocol.h (module 'internet'): void ns3::Ipv4RoutingProtocol::SetIpv4(ns3::Ptr<ns3::Ipv4> ipv4) [member function]
cls.add_method('SetIpv4',
'void',
[param('ns3::Ptr< ns3::Ipv4 >', 'ipv4')],
is_pure_virtual=True, is_virtual=True)
return
def register_Ns3Ipv6AddressChecker_methods(root_module, cls):
## ipv6-address.h (module 'network'): ns3::Ipv6AddressChecker::Ipv6AddressChecker() [constructor]
cls.add_constructor([])
## ipv6-address.h (module 'network'): ns3::Ipv6AddressChecker::Ipv6AddressChecker(ns3::Ipv6AddressChecker const & arg0) [copy constructor]
cls.add_constructor([param('ns3::Ipv6AddressChecker const &', 'arg0')])
return
def register_Ns3Ipv6AddressValue_methods(root_module, cls):
## ipv6-address.h (module 'network'): ns3::Ipv6AddressValue::Ipv6AddressValue() [constructor]
cls.add_constructor([])
## ipv6-address.h (module 'network'): ns3::Ipv6AddressValue::Ipv6AddressValue(ns3::Ipv6AddressValue const & arg0) [copy constructor]
cls.add_constructor([param('ns3::Ipv6AddressValue const &', 'arg0')])
## ipv6-address.h (module 'network'): ns3::Ipv6AddressValue::Ipv6AddressValue(ns3::Ipv6Address const & value) [constructor]
cls.add_constructor([param('ns3::Ipv6Address const &', 'value')])
## ipv6-address.h (module 'network'): ns3::Ptr<ns3::AttributeValue> ns3::Ipv6AddressValue::Copy() const [member function]
cls.add_method('Copy',
'ns3::Ptr< ns3::AttributeValue >',
[],
is_const=True, is_virtual=True)
## ipv6-address.h (module 'network'): bool ns3::Ipv6AddressValue::DeserializeFromString(std::string value, ns3::Ptr<ns3::AttributeChecker const> checker) [member function]
cls.add_method('DeserializeFromString',
'bool',
[param('std::string', 'value'), param('ns3::Ptr< ns3::AttributeChecker const >', 'checker')],
is_virtual=True)
## ipv6-address.h (module 'network'): ns3::Ipv6Address ns3::Ipv6AddressValue::Get() const [member function]
cls.add_method('Get',
'ns3::Ipv6Address',
[],
is_const=True)
## ipv6-address.h (module 'network'): std::string ns3::Ipv6AddressValue::SerializeToString(ns3::Ptr<ns3::AttributeChecker const> checker) const [member function]
cls.add_method('SerializeToString',
'std::string',
[param('ns3::Ptr< ns3::AttributeChecker const >', 'checker')],
is_const=True, is_virtual=True)
## ipv6-address.h (module 'network'): void ns3::Ipv6AddressValue::Set(ns3::Ipv6Address const & value) [member function]
cls.add_method('Set',
'void',
[param('ns3::Ipv6Address const &', 'value')])
return
def register_Ns3Ipv6PrefixChecker_methods(root_module, cls):
## ipv6-address.h (module 'network'): ns3::Ipv6PrefixChecker::Ipv6PrefixChecker() [constructor]
cls.add_constructor([])
## ipv6-address.h (module 'network'): ns3::Ipv6PrefixChecker::Ipv6PrefixChecker(ns3::Ipv6PrefixChecker const & arg0) [copy constructor]
cls.add_constructor([param('ns3::Ipv6PrefixChecker const &', 'arg0')])
return
def register_Ns3Ipv6PrefixValue_methods(root_module, cls):
## ipv6-address.h (module 'network'): ns3::Ipv6PrefixValue::Ipv6PrefixValue() [constructor]
cls.add_constructor([])
## ipv6-address.h (module 'network'): ns3::Ipv6PrefixValue::Ipv6PrefixValue(ns3::Ipv6PrefixValue const & arg0) [copy constructor]
cls.add_constructor([param('ns3::Ipv6PrefixValue const &', 'arg0')])
## ipv6-address.h (module 'network'): ns3::Ipv6PrefixValue::Ipv6PrefixValue(ns3::Ipv6Prefix const & value) [constructor]
cls.add_constructor([param('ns3::Ipv6Prefix const &', 'value')])
## ipv6-address.h (module 'network'): ns3::Ptr<ns3::AttributeValue> ns3::Ipv6PrefixValue::Copy() const [member function]
cls.add_method('Copy',
'ns3::Ptr< ns3::AttributeValue >',
[],
is_const=True, is_virtual=True)
## ipv6-address.h (module 'network'): bool ns3::Ipv6PrefixValue::DeserializeFromString(std::string value, ns3::Ptr<ns3::AttributeChecker const> checker) [member function]
cls.add_method('DeserializeFromString',
'bool',
[param('std::string', 'value'), param('ns3::Ptr< ns3::AttributeChecker const >', 'checker')],
is_virtual=True)
## ipv6-address.h (module 'network'): ns3::Ipv6Prefix ns3::Ipv6PrefixValue::Get() const [member function]
cls.add_method('Get',
'ns3::Ipv6Prefix',
[],
is_const=True)
## ipv6-address.h (module 'network'): std::string ns3::Ipv6PrefixValue::SerializeToString(ns3::Ptr<ns3::AttributeChecker const> checker) const [member function]
cls.add_method('SerializeToString',
'std::string',
[param('ns3::Ptr< ns3::AttributeChecker const >', 'checker')],
is_const=True, is_virtual=True)
## ipv6-address.h (module 'network'): void ns3::Ipv6PrefixValue::Set(ns3::Ipv6Prefix const & value) [member function]
cls.add_method('Set',
'void',
[param('ns3::Ipv6Prefix const &', 'value')])
return
def register_Ns3Mac48AddressChecker_methods(root_module, cls):
## mac48-address.h (module 'network'): ns3::Mac48AddressChecker::Mac48AddressChecker() [constructor]
cls.add_constructor([])
## mac48-address.h (module 'network'): ns3::Mac48AddressChecker::Mac48AddressChecker(ns3::Mac48AddressChecker const & arg0) [copy constructor]
cls.add_constructor([param('ns3::Mac48AddressChecker const &', 'arg0')])
return
def register_Ns3Mac48AddressValue_methods(root_module, cls):
## mac48-address.h (module 'network'): ns3::Mac48AddressValue::Mac48AddressValue() [constructor]
cls.add_constructor([])
## mac48-address.h (module 'network'): ns3::Mac48AddressValue::Mac48AddressValue(ns3::Mac48AddressValue const & arg0) [copy constructor]
cls.add_constructor([param('ns3::Mac48AddressValue const &', 'arg0')])
## mac48-address.h (module 'network'): ns3::Mac48AddressValue::Mac48AddressValue(ns3::Mac48Address const & value) [constructor]
cls.add_constructor([param('ns3::Mac48Address const &', 'value')])
## mac48-address.h (module 'network'): ns3::Ptr<ns3::AttributeValue> ns3::Mac48AddressValue::Copy() const [member function]
cls.add_method('Copy',
'ns3::Ptr< ns3::AttributeValue >',
[],
is_const=True, is_virtual=True)
## mac48-address.h (module 'network'): bool ns3::Mac48AddressValue::DeserializeFromString(std::string value, ns3::Ptr<ns3::AttributeChecker const> checker) [member function]
cls.add_method('DeserializeFromString',
'bool',
[param('std::string', 'value'), param('ns3::Ptr< ns3::AttributeChecker const >', 'checker')],
is_virtual=True)
## mac48-address.h (module 'network'): ns3::Mac48Address ns3::Mac48AddressValue::Get() const [member function]
cls.add_method('Get',
'ns3::Mac48Address',
[],
is_const=True)
## mac48-address.h (module 'network'): std::string ns3::Mac48AddressValue::SerializeToString(ns3::Ptr<ns3::AttributeChecker const> checker) const [member function]
cls.add_method('SerializeToString',
'std::string',
[param('ns3::Ptr< ns3::AttributeChecker const >', 'checker')],
is_const=True, is_virtual=True)
## mac48-address.h (module 'network'): void ns3::Mac48AddressValue::Set(ns3::Mac48Address const & value) [member function]
cls.add_method('Set',
'void',
[param('ns3::Mac48Address const &', 'value')])
return
def register_Ns3NetDevice_methods(root_module, cls):
## net-device.h (module 'network'): ns3::NetDevice::NetDevice() [constructor]
cls.add_constructor([])
## net-device.h (module 'network'): ns3::NetDevice::NetDevice(ns3::NetDevice const & arg0) [copy constructor]
cls.add_constructor([param('ns3::NetDevice const &', 'arg0')])
## net-device.h (module 'network'): void ns3::NetDevice::AddLinkChangeCallback(ns3::Callback<void, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty> callback) [member function]
cls.add_method('AddLinkChangeCallback',
'void',
[param('ns3::Callback< void, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty >', 'callback')],
is_pure_virtual=True, is_virtual=True)
## net-device.h (module 'network'): ns3::Address ns3::NetDevice::GetAddress() const [member function]
cls.add_method('GetAddress',
'ns3::Address',
[],
is_pure_virtual=True, is_const=True, is_virtual=True)
## net-device.h (module 'network'): ns3::Address ns3::NetDevice::GetBroadcast() const [member function]
cls.add_method('GetBroadcast',
'ns3::Address',
[],
is_pure_virtual=True, is_const=True, is_virtual=True)
## net-device.h (module 'network'): ns3::Ptr<ns3::Channel> ns3::NetDevice::GetChannel() const [member function]
cls.add_method('GetChannel',
'ns3::Ptr< ns3::Channel >',
[],
is_pure_virtual=True, is_const=True, is_virtual=True)
## net-device.h (module 'network'): uint32_t ns3::NetDevice::GetIfIndex() const [member function]
cls.add_method('GetIfIndex',
'uint32_t',
[],
is_pure_virtual=True, is_const=True, is_virtual=True)
## net-device.h (module 'network'): uint16_t ns3::NetDevice::GetMtu() const [member function]
cls.add_method('GetMtu',
'uint16_t',
[],
is_pure_virtual=True, is_const=True, is_virtual=True)
## net-device.h (module 'network'): ns3::Address ns3::NetDevice::GetMulticast(ns3::Ipv4Address multicastGroup) const [member function]
cls.add_method('GetMulticast',
'ns3::Address',
[param('ns3::Ipv4Address', 'multicastGroup')],
is_pure_virtual=True, is_const=True, is_virtual=True)
## net-device.h (module 'network'): ns3::Address ns3::NetDevice::GetMulticast(ns3::Ipv6Address addr) const [member function]
cls.add_method('GetMulticast',
'ns3::Address',
[param('ns3::Ipv6Address', 'addr')],
is_pure_virtual=True, is_const=True, is_virtual=True)
## net-device.h (module 'network'): ns3::Ptr<ns3::Node> ns3::NetDevice::GetNode() const [member function]
cls.add_method('GetNode',
'ns3::Ptr< ns3::Node >',
[],
is_pure_virtual=True, is_const=True, is_virtual=True)
## net-device.h (module 'network'): static ns3::TypeId ns3::NetDevice::GetTypeId() [member function]
cls.add_method('GetTypeId',
'ns3::TypeId',
[],
is_static=True)
## net-device.h (module 'network'): bool ns3::NetDevice::IsBridge() const [member function]
cls.add_method('IsBridge',
'bool',
[],
is_pure_virtual=True, is_const=True, is_virtual=True)
## net-device.h (module 'network'): bool ns3::NetDevice::IsBroadcast() const [member function]
cls.add_method('IsBroadcast',
'bool',
[],
is_pure_virtual=True, is_const=True, is_virtual=True)
## net-device.h (module 'network'): bool ns3::NetDevice::IsLinkUp() const [member function]
cls.add_method('IsLinkUp',
'bool',
[],
is_pure_virtual=True, is_const=True, is_virtual=True)
## net-device.h (module 'network'): bool ns3::NetDevice::IsMulticast() const [member function]
cls.add_method('IsMulticast',
'bool',
[],
is_pure_virtual=True, is_const=True, is_virtual=True)
## net-device.h (module 'network'): bool ns3::NetDevice::IsPointToPoint() const [member function]
cls.add_method('IsPointToPoint',
'bool',
[],
is_pure_virtual=True, is_const=True, is_virtual=True)
## net-device.h (module 'network'): bool ns3::NetDevice::NeedsArp() const [member function]
cls.add_method('NeedsArp',
'bool',
[],
is_pure_virtual=True, is_const=True, is_virtual=True)
## net-device.h (module 'network'): bool ns3::NetDevice::Send(ns3::Ptr<ns3::Packet> packet, ns3::Address const & dest, uint16_t protocolNumber) [member function]
cls.add_method('Send',
'bool',
[param('ns3::Ptr< ns3::Packet >', 'packet'), param('ns3::Address const &', 'dest'), param('uint16_t', 'protocolNumber')],
is_pure_virtual=True, is_virtual=True)
## net-device.h (module 'network'): bool ns3::NetDevice::SendFrom(ns3::Ptr<ns3::Packet> packet, ns3::Address const & source, ns3::Address const & dest, uint16_t protocolNumber) [member function]
cls.add_method('SendFrom',
'bool',
[param('ns3::Ptr< ns3::Packet >', 'packet'), param('ns3::Address const &', 'source'), param('ns3::Address const &', 'dest'), param('uint16_t', 'protocolNumber')],
is_pure_virtual=True, is_virtual=True)
## net-device.h (module 'network'): void ns3::NetDevice::SetAddress(ns3::Address address) [member function]
cls.add_method('SetAddress',
'void',
[param('ns3::Address', 'address')],
is_pure_virtual=True, is_virtual=True)
## net-device.h (module 'network'): void ns3::NetDevice::SetIfIndex(uint32_t const index) [member function]
cls.add_method('SetIfIndex',
'void',
[param('uint32_t const', 'index')],
is_pure_virtual=True, is_virtual=True)
## net-device.h (module 'network'): bool ns3::NetDevice::SetMtu(uint16_t const mtu) [member function]
cls.add_method('SetMtu',
'bool',
[param('uint16_t const', 'mtu')],
is_pure_virtual=True, is_virtual=True)
## net-device.h (module 'network'): void ns3::NetDevice::SetNode(ns3::Ptr<ns3::Node> node) [member function]
cls.add_method('SetNode',
'void',
[param('ns3::Ptr< ns3::Node >', 'node')],
is_pure_virtual=True, is_virtual=True)
## net-device.h (module 'network'): void ns3::NetDevice::SetPromiscReceiveCallback(ns3::Callback<bool,ns3::Ptr<ns3::NetDevice>,ns3::Ptr<const ns3::Packet>,short unsigned int,const ns3::Address&,const ns3::Address&,ns3::NetDevice::PacketType,ns3::empty,ns3::empty,ns3::empty> cb) [member function]
cls.add_method('SetPromiscReceiveCallback',
'void',
[param('ns3::Callback< bool, ns3::Ptr< ns3::NetDevice >, ns3::Ptr< ns3::Packet const >, short unsigned int, ns3::Address const &, ns3::Address const &, ns3::NetDevice::PacketType, ns3::empty, ns3::empty, ns3::empty >', 'cb')],
is_pure_virtual=True, is_virtual=True)
## net-device.h (module 'network'): void ns3::NetDevice::SetReceiveCallback(ns3::Callback<bool,ns3::Ptr<ns3::NetDevice>,ns3::Ptr<const ns3::Packet>,short unsigned int,const ns3::Address&,ns3::empty,ns3::empty,ns3::empty,ns3::empty,ns3::empty> cb) [member function]
cls.add_method('SetReceiveCallback',
'void',
[param('ns3::Callback< bool, ns3::Ptr< ns3::NetDevice >, ns3::Ptr< ns3::Packet const >, short unsigned int, ns3::Address const &, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty >', 'cb')],
is_pure_virtual=True, is_virtual=True)
## net-device.h (module 'network'): bool ns3::NetDevice::SupportsSendFrom() const [member function]
cls.add_method('SupportsSendFrom',
'bool',
[],
is_pure_virtual=True, is_const=True, is_virtual=True)
return
def register_Ns3NetDeviceQueue_methods(root_module, cls):
## net-device.h (module 'network'): ns3::NetDeviceQueue::NetDeviceQueue(ns3::NetDeviceQueue const & arg0) [copy constructor]
cls.add_constructor([param('ns3::NetDeviceQueue const &', 'arg0')])
## net-device.h (module 'network'): ns3::NetDeviceQueue::NetDeviceQueue() [constructor]
cls.add_constructor([])
## net-device.h (module 'network'): ns3::Ptr<ns3::QueueLimits> ns3::NetDeviceQueue::GetQueueLimits() [member function]
cls.add_method('GetQueueLimits',
'ns3::Ptr< ns3::QueueLimits >',
[])
## net-device.h (module 'network'): bool ns3::NetDeviceQueue::IsStopped() const [member function]
cls.add_method('IsStopped',
'bool',
[],
is_const=True)
## net-device.h (module 'network'): void ns3::NetDeviceQueue::NotifyQueuedBytes(uint32_t bytes) [member function]
cls.add_method('NotifyQueuedBytes',
'void',
[param('uint32_t', 'bytes')])
## net-device.h (module 'network'): void ns3::NetDeviceQueue::NotifyTransmittedBytes(uint32_t bytes) [member function]
cls.add_method('NotifyTransmittedBytes',
'void',
[param('uint32_t', 'bytes')])
## net-device.h (module 'network'): void ns3::NetDeviceQueue::ResetQueueLimits() [member function]
cls.add_method('ResetQueueLimits',
'void',
[])
## net-device.h (module 'network'): void ns3::NetDeviceQueue::SetQueueLimits(ns3::Ptr<ns3::QueueLimits> ql) [member function]
cls.add_method('SetQueueLimits',
'void',
[param('ns3::Ptr< ns3::QueueLimits >', 'ql')])
## net-device.h (module 'network'): void ns3::NetDeviceQueue::SetWakeCallback(ns3::Callback<void, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty> cb) [member function]
cls.add_method('SetWakeCallback',
'void',
[param('ns3::Callback< void, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty >', 'cb')],
is_virtual=True)
## net-device.h (module 'network'): void ns3::NetDeviceQueue::Start() [member function]
cls.add_method('Start',
'void',
[],
is_virtual=True)
## net-device.h (module 'network'): void ns3::NetDeviceQueue::Stop() [member function]
cls.add_method('Stop',
'void',
[],
is_virtual=True)
## net-device.h (module 'network'): void ns3::NetDeviceQueue::Wake() [member function]
cls.add_method('Wake',
'void',
[],
is_virtual=True)
return
def register_Ns3NetDeviceQueueInterface_methods(root_module, cls):
## net-device.h (module 'network'): ns3::NetDeviceQueueInterface::NetDeviceQueueInterface(ns3::NetDeviceQueueInterface const & arg0) [copy constructor]
cls.add_constructor([param('ns3::NetDeviceQueueInterface const &', 'arg0')])
## net-device.h (module 'network'): ns3::NetDeviceQueueInterface::NetDeviceQueueInterface() [constructor]
cls.add_constructor([])
## net-device.h (module 'network'): void ns3::NetDeviceQueueInterface::CreateTxQueues() [member function]
cls.add_method('CreateTxQueues',
'void',
[])
## net-device.h (module 'network'): uint8_t ns3::NetDeviceQueueInterface::GetNTxQueues() const [member function]
cls.add_method('GetNTxQueues',
'uint8_t',
[],
is_const=True)
## net-device.h (module 'network'): ns3::Callback<unsigned char, ns3::Ptr<ns3::QueueItem>, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty> ns3::NetDeviceQueueInterface::GetSelectQueueCallback() const [member function]
cls.add_method('GetSelectQueueCallback',
'ns3::Callback< unsigned char, ns3::Ptr< ns3::QueueItem >, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty >',
[],
is_const=True)
## net-device.h (module 'network'): ns3::Ptr<ns3::NetDeviceQueue> ns3::NetDeviceQueueInterface::GetTxQueue(uint8_t i) const [member function]
cls.add_method('GetTxQueue',
'ns3::Ptr< ns3::NetDeviceQueue >',
[param('uint8_t', 'i')],
is_const=True)
## net-device.h (module 'network'): static ns3::TypeId ns3::NetDeviceQueueInterface::GetTypeId() [member function]
cls.add_method('GetTypeId',
'ns3::TypeId',
[],
is_static=True)
## net-device.h (module 'network'): void ns3::NetDeviceQueueInterface::SetSelectQueueCallback(ns3::Callback<unsigned char, ns3::Ptr<ns3::QueueItem>, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty> cb) [member function]
cls.add_method('SetSelectQueueCallback',
'void',
[param('ns3::Callback< unsigned char, ns3::Ptr< ns3::QueueItem >, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty >', 'cb')])
## net-device.h (module 'network'): void ns3::NetDeviceQueueInterface::SetTxQueuesN(uint8_t numTxQueues) [member function]
cls.add_method('SetTxQueuesN',
'void',
[param('uint8_t', 'numTxQueues')])
## net-device.h (module 'network'): void ns3::NetDeviceQueueInterface::DoDispose() [member function]
cls.add_method('DoDispose',
'void',
[],
visibility='protected', is_virtual=True)
return
def register_Ns3NixVector_methods(root_module, cls):
cls.add_output_stream_operator()
## nix-vector.h (module 'network'): ns3::NixVector::NixVector() [constructor]
cls.add_constructor([])
## nix-vector.h (module 'network'): ns3::NixVector::NixVector(ns3::NixVector const & o) [copy constructor]
cls.add_constructor([param('ns3::NixVector const &', 'o')])
## nix-vector.h (module 'network'): void ns3::NixVector::AddNeighborIndex(uint32_t newBits, uint32_t numberOfBits) [member function]
cls.add_method('AddNeighborIndex',
'void',
[param('uint32_t', 'newBits'), param('uint32_t', 'numberOfBits')])
## nix-vector.h (module 'network'): uint32_t ns3::NixVector::BitCount(uint32_t numberOfNeighbors) const [member function]
cls.add_method('BitCount',
'uint32_t',
[param('uint32_t', 'numberOfNeighbors')],
is_const=True)
## nix-vector.h (module 'network'): ns3::Ptr<ns3::NixVector> ns3::NixVector::Copy() const [member function]
cls.add_method('Copy',
'ns3::Ptr< ns3::NixVector >',
[],
is_const=True)
## nix-vector.h (module 'network'): uint32_t ns3::NixVector::Deserialize(uint32_t const * buffer, uint32_t size) [member function]
cls.add_method('Deserialize',
'uint32_t',
[param('uint32_t const *', 'buffer'), param('uint32_t', 'size')])
## nix-vector.h (module 'network'): uint32_t ns3::NixVector::ExtractNeighborIndex(uint32_t numberOfBits) [member function]
cls.add_method('ExtractNeighborIndex',
'uint32_t',
[param('uint32_t', 'numberOfBits')])
## nix-vector.h (module 'network'): uint32_t ns3::NixVector::GetRemainingBits() [member function]
cls.add_method('GetRemainingBits',
'uint32_t',
[])
## nix-vector.h (module 'network'): uint32_t ns3::NixVector::GetSerializedSize() const [member function]
cls.add_method('GetSerializedSize',
'uint32_t',
[],
is_const=True)
## nix-vector.h (module 'network'): uint32_t ns3::NixVector::Serialize(uint32_t * buffer, uint32_t maxSize) const [member function]
cls.add_method('Serialize',
'uint32_t',
[param('uint32_t *', 'buffer'), param('uint32_t', 'maxSize')],
is_const=True)
return
def register_Ns3Node_methods(root_module, cls):
## node.h (module 'network'): ns3::Node::Node(ns3::Node const & arg0) [copy constructor]
cls.add_constructor([param('ns3::Node const &', 'arg0')])
## node.h (module 'network'): ns3::Node::Node() [constructor]
cls.add_constructor([])
## node.h (module 'network'): ns3::Node::Node(uint32_t systemId) [constructor]
cls.add_constructor([param('uint32_t', 'systemId')])
## node.h (module 'network'): uint32_t ns3::Node::AddApplication(ns3::Ptr<ns3::Application> application) [member function]
cls.add_method('AddApplication',
'uint32_t',
[param('ns3::Ptr< ns3::Application >', 'application')])
## node.h (module 'network'): uint32_t ns3::Node::AddDevice(ns3::Ptr<ns3::NetDevice> device) [member function]
cls.add_method('AddDevice',
'uint32_t',
[param('ns3::Ptr< ns3::NetDevice >', 'device')])
## node.h (module 'network'): static bool ns3::Node::ChecksumEnabled() [member function]
cls.add_method('ChecksumEnabled',
'bool',
[],
is_static=True)
## node.h (module 'network'): ns3::Ptr<ns3::Application> ns3::Node::GetApplication(uint32_t index) const [member function]
cls.add_method('GetApplication',
'ns3::Ptr< ns3::Application >',
[param('uint32_t', 'index')],
is_const=True)
## node.h (module 'network'): ns3::Ptr<ns3::NetDevice> ns3::Node::GetDevice(uint32_t index) const [member function]
cls.add_method('GetDevice',
'ns3::Ptr< ns3::NetDevice >',
[param('uint32_t', 'index')],
is_const=True)
## node.h (module 'network'): uint32_t ns3::Node::GetId() const [member function]
cls.add_method('GetId',
'uint32_t',
[],
is_const=True)
## node.h (module 'network'): ns3::Time ns3::Node::GetLocalTime() const [member function]
cls.add_method('GetLocalTime',
'ns3::Time',
[],
is_const=True)
## node.h (module 'network'): uint32_t ns3::Node::GetNApplications() const [member function]
cls.add_method('GetNApplications',
'uint32_t',
[],
is_const=True)
## node.h (module 'network'): uint32_t ns3::Node::GetNDevices() const [member function]
cls.add_method('GetNDevices',
'uint32_t',
[],
is_const=True)
## node.h (module 'network'): uint32_t ns3::Node::GetSystemId() const [member function]
cls.add_method('GetSystemId',
'uint32_t',
[],
is_const=True)
## node.h (module 'network'): static ns3::TypeId ns3::Node::GetTypeId() [member function]
cls.add_method('GetTypeId',
'ns3::TypeId',
[],
is_static=True)
## node.h (module 'network'): void ns3::Node::RegisterDeviceAdditionListener(ns3::Callback<void,ns3::Ptr<ns3::NetDevice>,ns3::empty,ns3::empty,ns3::empty,ns3::empty,ns3::empty,ns3::empty,ns3::empty,ns3::empty> listener) [member function]
cls.add_method('RegisterDeviceAdditionListener',
'void',
[param('ns3::Callback< void, ns3::Ptr< ns3::NetDevice >, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty >', 'listener')])
## node.h (module 'network'): void ns3::Node::RegisterProtocolHandler(ns3::Callback<void, ns3::Ptr<ns3::NetDevice>, ns3::Ptr<ns3::Packet const>, unsigned short, ns3::Address const&, ns3::Address const&, ns3::NetDevice::PacketType, ns3::empty, ns3::empty, ns3::empty> handler, uint16_t protocolType, ns3::Ptr<ns3::NetDevice> device, bool promiscuous=false) [member function]
cls.add_method('RegisterProtocolHandler',
'void',
[param('ns3::Callback< void, ns3::Ptr< ns3::NetDevice >, ns3::Ptr< ns3::Packet const >, unsigned short, ns3::Address const &, ns3::Address const &, ns3::NetDevice::PacketType, ns3::empty, ns3::empty, ns3::empty >', 'handler'), param('uint16_t', 'protocolType'), param('ns3::Ptr< ns3::NetDevice >', 'device'), param('bool', 'promiscuous', default_value='false')])
## node.h (module 'network'): void ns3::Node::UnregisterDeviceAdditionListener(ns3::Callback<void,ns3::Ptr<ns3::NetDevice>,ns3::empty,ns3::empty,ns3::empty,ns3::empty,ns3::empty,ns3::empty,ns3::empty,ns3::empty> listener) [member function]
cls.add_method('UnregisterDeviceAdditionListener',
'void',
[param('ns3::Callback< void, ns3::Ptr< ns3::NetDevice >, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty, ns3::empty >', 'listener')])
## node.h (module 'network'): void ns3::Node::UnregisterProtocolHandler(ns3::Callback<void, ns3::Ptr<ns3::NetDevice>, ns3::Ptr<ns3::Packet const>, unsigned short, ns3::Address const&, ns3::Address const&, ns3::NetDevice::PacketType, ns3::empty, ns3::empty, ns3::empty> handler) [member function]
cls.add_method('UnregisterProtocolHandler',
'void',
[param('ns3::Callback< void, ns3::Ptr< ns3::NetDevice >, ns3::Ptr< ns3::Packet const >, unsigned short, ns3::Address const &, ns3::Address const &, ns3::NetDevice::PacketType, ns3::empty, ns3::empty, ns3::empty >', 'handler')])
## node.h (module 'network'): void ns3::Node::DoDispose() [member function]
cls.add_method('DoDispose',
'void',
[],
visibility='protected', is_virtual=True)
## node.h (module 'network'): void ns3::Node::DoInitialize() [member function]
cls.add_method('DoInitialize',
'void',
[],
visibility='protected', is_virtual=True)
return
def register_Ns3ObjectFactoryChecker_methods(root_module, cls):
## object-factory.h (module 'core'): ns3::ObjectFactoryChecker::ObjectFactoryChecker() [constructor]
cls.add_constructor([])
## object-factory.h (module 'core'): ns3::ObjectFactoryChecker::ObjectFactoryChecker(ns3::ObjectFactoryChecker const & arg0) [copy constructor]
cls.add_constructor([param('ns3::ObjectFactoryChecker const &', 'arg0')])
return
def register_Ns3ObjectFactoryValue_methods(root_module, cls):
## object-factory.h (module 'core'): ns3::ObjectFactoryValue::ObjectFactoryValue() [constructor]
cls.add_constructor([])
## object-factory.h (module 'core'): ns3::ObjectFactoryValue::ObjectFactoryValue(ns3::ObjectFactoryValue const & arg0) [copy constructor]
cls.add_constructor([param('ns3::ObjectFactoryValue const &', 'arg0')])
## object-factory.h (module 'core'): ns3::ObjectFactoryValue::ObjectFactoryValue(ns3::ObjectFactory const & value) [constructor]
cls.add_constructor([param('ns3::ObjectFactory const &', 'value')])
## object-factory.h (module 'core'): ns3::Ptr<ns3::AttributeValue> ns3::ObjectFactoryValue::Copy() const [member function]
cls.add_method('Copy',
'ns3::Ptr< ns3::AttributeValue >',
[],
is_const=True, is_virtual=True)
## object-factory.h (module 'core'): bool ns3::ObjectFactoryValue::DeserializeFromString(std::string value, ns3::Ptr<ns3::AttributeChecker const> checker) [member function]
cls.add_method('DeserializeFromString',
'bool',
[param('std::string', 'value'), param('ns3::Ptr< ns3::AttributeChecker const >', 'checker')],
is_virtual=True)
## object-factory.h (module 'core'): ns3::ObjectFactory ns3::ObjectFactoryValue::Get() const [member function]
cls.add_method('Get',
'ns3::ObjectFactory',
[],
is_const=True)
## object-factory.h (module 'core'): std::string ns3::ObjectFactoryValue::SerializeToString(ns3::Ptr<ns3::AttributeChecker const> checker) const [member function]
cls.add_method('SerializeToString',
'std::string',
[param('ns3::Ptr< ns3::AttributeChecker const >', 'checker')],
is_const=True, is_virtual=True)
## object-factory.h (module 'core'): void ns3::ObjectFactoryValue::Set(ns3::ObjectFactory const & value) [member function]
cls.add_method('Set',
'void',
[param('ns3::ObjectFactory const &', 'value')])
return
def register_Ns3OutputStreamWrapper_methods(root_module, cls):
## output-stream-wrapper.h (module 'network'): ns3::OutputStreamWrapper::OutputStreamWrapper(ns3::OutputStreamWrapper const & arg0) [copy constructor]
cls.add_constructor([param('ns3::OutputStreamWrapper const &', 'arg0')])
## output-stream-wrapper.h (module 'network'): ns3::OutputStreamWrapper::OutputStreamWrapper(std::string filename, std::_Ios_Openmode filemode) [constructor]
cls.add_constructor([param('std::string', 'filename'), param('std::_Ios_Openmode', 'filemode')])
## output-stream-wrapper.h (module 'network'): ns3::OutputStreamWrapper::OutputStreamWrapper(std::ostream * os) [constructor]
cls.add_constructor([param('std::ostream *', 'os')])
## output-stream-wrapper.h (module 'network'): std::ostream * ns3::OutputStreamWrapper::GetStream() [member function]
cls.add_method('GetStream',
'std::ostream *',
[])
return
def register_Ns3Packet_methods(root_module, cls):
cls.add_output_stream_operator()
## packet.h (module 'network'): ns3::Packet::Packet() [constructor]
cls.add_constructor([])
## packet.h (module 'network'): ns3::Packet::Packet(ns3::Packet const & o) [copy constructor]
cls.add_constructor([param('ns3::Packet const &', 'o')])
## packet.h (module 'network'): ns3::Packet::Packet(uint32_t size) [constructor]
cls.add_constructor([param('uint32_t', 'size')])
## packet.h (module 'network'): ns3::Packet::Packet(uint8_t const * buffer, uint32_t size, bool magic) [constructor]
cls.add_constructor([param('uint8_t const *', 'buffer'), param('uint32_t', 'size'), param('bool', 'magic')])
## packet.h (module 'network'): ns3::Packet::Packet(uint8_t const * buffer, uint32_t size) [constructor]
cls.add_constructor([param('uint8_t const *', 'buffer'), param('uint32_t', 'size')])
## packet.h (module 'network'): void ns3::Packet::AddAtEnd(ns3::Ptr<const ns3::Packet> packet) [member function]
cls.add_method('AddAtEnd',
'void',
[param('ns3::Ptr< ns3::Packet const >', 'packet')])
## packet.h (module 'network'): void ns3::Packet::AddByteTag(ns3::Tag const & tag) const [member function]
cls.add_method('AddByteTag',
'void',
[param('ns3::Tag const &', 'tag')],
is_const=True)
## packet.h (module 'network'): void ns3::Packet::AddHeader(ns3::Header const & header) [member function]
cls.add_method('AddHeader',
'void',
[param('ns3::Header const &', 'header')])
## packet.h (module 'network'): void ns3::Packet::AddPacketTag(ns3::Tag const & tag) const [member function]
cls.add_method('AddPacketTag',
'void',
[param('ns3::Tag const &', 'tag')],
is_const=True)
## packet.h (module 'network'): void ns3::Packet::AddPaddingAtEnd(uint32_t size) [member function]
cls.add_method('AddPaddingAtEnd',
'void',
[param('uint32_t', 'size')])
## packet.h (module 'network'): void ns3::Packet::AddTrailer(ns3::Trailer const & trailer) [member function]
cls.add_method('AddTrailer',
'void',
[param('ns3::Trailer const &', 'trailer')])
## packet.h (module 'network'): ns3::PacketMetadata::ItemIterator ns3::Packet::BeginItem() const [member function]
cls.add_method('BeginItem',
'ns3::PacketMetadata::ItemIterator',
[],
is_const=True)
## packet.h (module 'network'): ns3::Ptr<ns3::Packet> ns3::Packet::Copy() const [member function]
cls.add_method('Copy',
'ns3::Ptr< ns3::Packet >',
[],
is_const=True)
## packet.h (module 'network'): uint32_t ns3::Packet::CopyData(uint8_t * buffer, uint32_t size) const [member function]
cls.add_method('CopyData',
'uint32_t',
[param('uint8_t *', 'buffer'), param('uint32_t', 'size')],
is_const=True)
## packet.h (module 'network'): void ns3::Packet::CopyData(std::ostream * os, uint32_t size) const [member function]
cls.add_method('CopyData',
'void',
[param('std::ostream *', 'os'), param('uint32_t', 'size')],
is_const=True)
## packet.h (module 'network'): ns3::Ptr<ns3::Packet> ns3::Packet::CreateFragment(uint32_t start, uint32_t length) const [member function]
cls.add_method('CreateFragment',
'ns3::Ptr< ns3::Packet >',
[param('uint32_t', 'start'), param('uint32_t', 'length')],
is_const=True)
## packet.h (module 'network'): static void ns3::Packet::EnableChecking() [member function]
cls.add_method('EnableChecking',
'void',
[],
is_static=True)
## packet.h (module 'network'): static void ns3::Packet::EnablePrinting() [member function]
cls.add_method('EnablePrinting',
'void',
[],
is_static=True)
## packet.h (module 'network'): bool ns3::Packet::FindFirstMatchingByteTag(ns3::Tag & tag) const [member function]
cls.add_method('FindFirstMatchingByteTag',
'bool',
[param('ns3::Tag &', 'tag')],
is_const=True)
## packet.h (module 'network'): ns3::ByteTagIterator ns3::Packet::GetByteTagIterator() const [member function]
cls.add_method('GetByteTagIterator',
'ns3::ByteTagIterator',
[],
is_const=True)
## packet.h (module 'network'): ns3::Ptr<ns3::NixVector> ns3::Packet::GetNixVector() const [member function]
cls.add_method('GetNixVector',
'ns3::Ptr< ns3::NixVector >',
[],
is_const=True)
## packet.h (module 'network'): ns3::PacketTagIterator ns3::Packet::GetPacketTagIterator() const [member function]
cls.add_method('GetPacketTagIterator',
'ns3::PacketTagIterator',
[],
is_const=True)
## packet.h (module 'network'): uint32_t ns3::Packet::GetSerializedSize() const [member function]
cls.add_method('GetSerializedSize',
'uint32_t',
[],
is_const=True)
## packet.h (module 'network'): uint32_t ns3::Packet::GetSize() const [member function]
cls.add_method('GetSize',
'uint32_t',
[],
is_const=True)
## packet.h (module 'network'): uint64_t ns3::Packet::GetUid() const [member function]
cls.add_method('GetUid',
'uint64_t',
[],
is_const=True)
## packet.h (module 'network'): uint32_t ns3::Packet::PeekHeader(ns3::Header & header) const [member function]
cls.add_method('PeekHeader',
'uint32_t',
[param('ns3::Header &', 'header')],
is_const=True)
## packet.h (module 'network'): bool ns3::Packet::PeekPacketTag(ns3::Tag & tag) const [member function]
cls.add_method('PeekPacketTag',
'bool',
[param('ns3::Tag &', 'tag')],
is_const=True)
## packet.h (module 'network'): uint32_t ns3::Packet::PeekTrailer(ns3::Trailer & trailer) [member function]
cls.add_method('PeekTrailer',
'uint32_t',
[param('ns3::Trailer &', 'trailer')])
## packet.h (module 'network'): void ns3::Packet::Print(std::ostream & os) const [member function]
cls.add_method('Print',
'void',
[param('std::ostream &', 'os')],
is_const=True)
## packet.h (module 'network'): void ns3::Packet::PrintByteTags(std::ostream & os) const [member function]
cls.add_method('PrintByteTags',
'void',
[param('std::ostream &', 'os')],
is_const=True)
## packet.h (module 'network'): void ns3::Packet::PrintPacketTags(std::ostream & os) const [member function]
cls.add_method('PrintPacketTags',
'void',
[param('std::ostream &', 'os')],
is_const=True)
## packet.h (module 'network'): void ns3::Packet::RemoveAllByteTags() [member function]
cls.add_method('RemoveAllByteTags',
'void',
[])
## packet.h (module 'network'): void ns3::Packet::RemoveAllPacketTags() [member function]
cls.add_method('RemoveAllPacketTags',
'void',
[])
## packet.h (module 'network'): void ns3::Packet::RemoveAtEnd(uint32_t size) [member function]
cls.add_method('RemoveAtEnd',
'void',
[param('uint32_t', 'size')])
## packet.h (module 'network'): void ns3::Packet::RemoveAtStart(uint32_t size) [member function]
cls.add_method('RemoveAtStart',
'void',
[param('uint32_t', 'size')])
## packet.h (module 'network'): uint32_t ns3::Packet::RemoveHeader(ns3::Header & header) [member function]
cls.add_method('RemoveHeader',
'uint32_t',
[param('ns3::Header &', 'header')])
## packet.h (module 'network'): bool ns3::Packet::RemovePacketTag(ns3::Tag & tag) [member function]
cls.add_method('RemovePacketTag',
'bool',
[param('ns3::Tag &', 'tag')])
## packet.h (module 'network'): uint32_t ns3::Packet::RemoveTrailer(ns3::Trailer & trailer) [member function]
cls.add_method('RemoveTrailer',
'uint32_t',
[param('ns3::Trailer &', 'trailer')])
## packet.h (module 'network'): bool ns3::Packet::ReplacePacketTag(ns3::Tag & tag) [member function]
cls.add_method('ReplacePacketTag',
'bool',
[param('ns3::Tag &', 'tag')])
## packet.h (module 'network'): uint32_t ns3::Packet::Serialize(uint8_t * buffer, uint32_t maxSize) const [member function]
cls.add_method('Serialize',
'uint32_t',
[param('uint8_t *', 'buffer'), param('uint32_t', 'maxSize')],
is_const=True)
## packet.h (module 'network'): void ns3::Packet::SetNixVector(ns3::Ptr<ns3::NixVector> nixVector) [member function]
cls.add_method('SetNixVector',
'void',
[param('ns3::Ptr< ns3::NixVector >', 'nixVector')])
## packet.h (module 'network'): std::string ns3::Packet::ToString() const [member function]
cls.add_method('ToString',
'std::string',
[],
is_const=True)
return
def register_Ns3QueueItem_methods(root_module, cls):
cls.add_output_stream_operator()
## net-device.h (module 'network'): ns3::QueueItem::QueueItem(ns3::Ptr<ns3::Packet> p) [constructor]
cls.add_constructor([param('ns3::Ptr< ns3::Packet >', 'p')])
## net-device.h (module 'network'): ns3::Ptr<ns3::Packet> ns3::QueueItem::GetPacket() const [member function]
cls.add_method('GetPacket',
'ns3::Ptr< ns3::Packet >',
[],
is_const=True)
## net-device.h (module 'network'): uint32_t ns3::QueueItem::GetPacketSize() const [member function]
cls.add_method('GetPacketSize',
'uint32_t',
[],
is_const=True, is_virtual=True)
## net-device.h (module 'network'): bool ns3::QueueItem::GetUint8Value(ns3::QueueItem::Uint8Values field, uint8_t & value) const [member function]
cls.add_method('GetUint8Value',
'bool',
[param('ns3::QueueItem::Uint8Values', 'field'), param('uint8_t &', 'value')],
is_const=True, is_virtual=True)
## net-device.h (module 'network'): void ns3::QueueItem::Print(std::ostream & os) const [member function]
cls.add_method('Print',
'void',
[param('std::ostream &', 'os')],
is_const=True, is_virtual=True)
return
def register_Ns3TimeValue_methods(root_module, cls):
## nstime.h (module 'core'): ns3::TimeValue::TimeValue() [constructor]
cls.add_constructor([])
## nstime.h (module 'core'): ns3::TimeValue::TimeValue(ns3::TimeValue const & arg0) [copy constructor]
cls.add_constructor([param('ns3::TimeValue const &', 'arg0')])
## nstime.h (module 'core'): ns3::TimeValue::TimeValue(ns3::Time const & value) [constructor]
cls.add_constructor([param('ns3::Time const &', 'value')])
## nstime.h (module 'core'): ns3::Ptr<ns3::AttributeValue> ns3::TimeValue::Copy() const [member function]
cls.add_method('Copy',
'ns3::Ptr< ns3::AttributeValue >',
[],
is_const=True, is_virtual=True)
## nstime.h (module 'core'): bool ns3::TimeValue::DeserializeFromString(std::string value, ns3::Ptr<ns3::AttributeChecker const> checker) [member function]
cls.add_method('DeserializeFromString',
'bool',
[param('std::string', 'value'), param('ns3::Ptr< ns3::AttributeChecker const >', 'checker')],
is_virtual=True)
## nstime.h (module 'core'): ns3::Time ns3::TimeValue::Get() const [member function]
cls.add_method('Get',
'ns3::Time',
[],
is_const=True)
## nstime.h (module 'core'): std::string ns3::TimeValue::SerializeToString(ns3::Ptr<ns3::AttributeChecker const> checker) const [member function]
cls.add_method('SerializeToString',
'std::string',
[param('ns3::Ptr< ns3::AttributeChecker const >', 'checker')],
is_const=True, is_virtual=True)
## nstime.h (module 'core'): void ns3::TimeValue::Set(ns3::Time const & value) [member function]
cls.add_method('Set',
'void',
[param('ns3::Time const &', 'value')])
return
def register_Ns3TypeIdChecker_methods(root_module, cls):
## type-id.h (module 'core'): ns3::TypeIdChecker::TypeIdChecker() [constructor]
cls.add_constructor([])
## type-id.h (module 'core'): ns3::TypeIdChecker::TypeIdChecker(ns3::TypeIdChecker const & arg0) [copy constructor]
cls.add_constructor([param('ns3::TypeIdChecker const &', 'arg0')])
return
def register_Ns3TypeIdValue_methods(root_module, cls):
## type-id.h (module 'core'): ns3::TypeIdValue::TypeIdValue() [constructor]
cls.add_constructor([])
## type-id.h (module 'core'): ns3::TypeIdValue::TypeIdValue(ns3::TypeIdValue const & arg0) [copy constructor]
cls.add_constructor([param('ns3::TypeIdValue const &', 'arg0')])
## type-id.h (module 'core'): ns3::TypeIdValue::TypeIdValue(ns3::TypeId const & value) [constructor]
cls.add_constructor([param('ns3::TypeId const &', 'value')])
## type-id.h (module 'core'): ns3::Ptr<ns3::AttributeValue> ns3::TypeIdValue::Copy() const [member function]
cls.add_method('Copy',
'ns3::Ptr< ns3::AttributeValue >',
[],
is_const=True, is_virtual=True)
## type-id.h (module 'core'): bool ns3::TypeIdValue::DeserializeFromString(std::string value, ns3::Ptr<ns3::AttributeChecker const> checker) [member function]
cls.add_method('DeserializeFromString',
'bool',
[param('std::string', 'value'), param('ns3::Ptr< ns3::AttributeChecker const >', 'checker')],
is_virtual=True)
## type-id.h (module 'core'): ns3::TypeId ns3::TypeIdValue::Get() const [member function]
cls.add_method('Get',
'ns3::TypeId',
[],
is_const=True)
## type-id.h (module 'core'): std::string ns3::TypeIdValue::SerializeToString(ns3::Ptr<ns3::AttributeChecker const> checker) const [member function]
cls.add_method('SerializeToString',
'std::string',
[param('ns3::Ptr< ns3::AttributeChecker const >', 'checker')],
is_const=True, is_virtual=True)
## type-id.h (module 'core'): void ns3::TypeIdValue::Set(ns3::TypeId const & value) [member function]
cls.add_method('Set',
'void',
[param('ns3::TypeId const &', 'value')])
return
def register_Ns3AddressChecker_methods(root_module, cls):
## address.h (module 'network'): ns3::AddressChecker::AddressChecker() [constructor]
cls.add_constructor([])
## address.h (module 'network'): ns3::AddressChecker::AddressChecker(ns3::AddressChecker const & arg0) [copy constructor]
cls.add_constructor([param('ns3::AddressChecker const &', 'arg0')])
return
def register_Ns3AddressValue_methods(root_module, cls):
## address.h (module 'network'): ns3::AddressValue::AddressValue() [constructor]
cls.add_constructor([])
## address.h (module 'network'): ns3::AddressValue::AddressValue(ns3::AddressValue const & arg0) [copy constructor]
cls.add_constructor([param('ns3::AddressValue const &', 'arg0')])
## address.h (module 'network'): ns3::AddressValue::AddressValue(ns3::Address const & value) [constructor]
cls.add_constructor([param('ns3::Address const &', 'value')])
## address.h (module 'network'): ns3::Ptr<ns3::AttributeValue> ns3::AddressValue::Copy() const [member function]
cls.add_method('Copy',
'ns3::Ptr< ns3::AttributeValue >',
[],
is_const=True, is_virtual=True)
## address.h (module 'network'): bool ns3::AddressValue::DeserializeFromString(std::string value, ns3::Ptr<ns3::AttributeChecker const> checker) [member function]
cls.add_method('DeserializeFromString',
'bool',
[param('std::string', 'value'), param('ns3::Ptr< ns3::AttributeChecker const >', 'checker')],
is_virtual=True)
## address.h (module 'network'): ns3::Address ns3::AddressValue::Get() const [member function]
cls.add_method('Get',
'ns3::Address',
[],
is_const=True)
## address.h (module 'network'): std::string ns3::AddressValue::SerializeToString(ns3::Ptr<ns3::AttributeChecker const> checker) const [member function]
cls.add_method('SerializeToString',
'std::string',
[param('ns3::Ptr< ns3::AttributeChecker const >', 'checker')],
is_const=True, is_virtual=True)
## address.h (module 'network'): void ns3::AddressValue::Set(ns3::Address const & value) [member function]
cls.add_method('Set',
'void',
[param('ns3::Address const &', 'value')])
return
def register_Ns3HashImplementation_methods(root_module, cls):
## hash-function.h (module 'core'): ns3::Hash::Implementation::Implementation(ns3::Hash::Implementation const & arg0) [copy constructor]
cls.add_constructor([param('ns3::Hash::Implementation const &', 'arg0')])
## hash-function.h (module 'core'): ns3::Hash::Implementation::Implementation() [constructor]
cls.add_constructor([])
## hash-function.h (module 'core'): uint32_t ns3::Hash::Implementation::GetHash32(char const * buffer, size_t const size) [member function]
cls.add_method('GetHash32',
'uint32_t',
[param('char const *', 'buffer'), param('size_t const', 'size')],
is_pure_virtual=True, is_virtual=True)
## hash-function.h (module 'core'): uint64_t ns3::Hash::Implementation::GetHash64(char const * buffer, size_t const size) [member function]
cls.add_method('GetHash64',
'uint64_t',
[param('char const *', 'buffer'), param('size_t const', 'size')],
is_virtual=True)
## hash-function.h (module 'core'): void ns3::Hash::Implementation::clear() [member function]
cls.add_method('clear',
'void',
[],
is_pure_virtual=True, is_virtual=True)
return
def register_Ns3HashFunctionFnv1a_methods(root_module, cls):
## hash-fnv.h (module 'core'): ns3::Hash::Function::Fnv1a::Fnv1a(ns3::Hash::Function::Fnv1a const & arg0) [copy constructor]
cls.add_constructor([param('ns3::Hash::Function::Fnv1a const &', 'arg0')])
## hash-fnv.h (module 'core'): ns3::Hash::Function::Fnv1a::Fnv1a() [constructor]
cls.add_constructor([])
## hash-fnv.h (module 'core'): uint32_t ns3::Hash::Function::Fnv1a::GetHash32(char const * buffer, size_t const size) [member function]
cls.add_method('GetHash32',
'uint32_t',
[param('char const *', 'buffer'), param('size_t const', 'size')],
is_virtual=True)
## hash-fnv.h (module 'core'): uint64_t ns3::Hash::Function::Fnv1a::GetHash64(char const * buffer, size_t const size) [member function]
cls.add_method('GetHash64',
'uint64_t',
[param('char const *', 'buffer'), param('size_t const', 'size')],
is_virtual=True)
## hash-fnv.h (module 'core'): void ns3::Hash::Function::Fnv1a::clear() [member function]
cls.add_method('clear',
'void',
[],
is_virtual=True)
return
def register_Ns3HashFunctionHash32_methods(root_module, cls):
## hash-function.h (module 'core'): ns3::Hash::Function::Hash32::Hash32(ns3::Hash::Function::Hash32 const & arg0) [copy constructor]
cls.add_constructor([param('ns3::Hash::Function::Hash32 const &', 'arg0')])
## hash-function.h (module 'core'): ns3::Hash::Function::Hash32::Hash32(ns3::Hash::Hash32Function_ptr hp) [constructor]
cls.add_constructor([param('ns3::Hash::Hash32Function_ptr', 'hp')])
## hash-function.h (module 'core'): uint32_t ns3::Hash::Function::Hash32::GetHash32(char const * buffer, size_t const size) [member function]
cls.add_method('GetHash32',
'uint32_t',
[param('char const *', 'buffer'), param('size_t const', 'size')],
is_virtual=True)
## hash-function.h (module 'core'): void ns3::Hash::Function::Hash32::clear() [member function]
cls.add_method('clear',
'void',
[],
is_virtual=True)
return
def register_Ns3HashFunctionHash64_methods(root_module, cls):
## hash-function.h (module 'core'): ns3::Hash::Function::Hash64::Hash64(ns3::Hash::Function::Hash64 const & arg0) [copy constructor]
cls.add_constructor([param('ns3::Hash::Function::Hash64 const &', 'arg0')])
## hash-function.h (module 'core'): ns3::Hash::Function::Hash64::Hash64(ns3::Hash::Hash64Function_ptr hp) [constructor]
cls.add_constructor([param('ns3::Hash::Hash64Function_ptr', 'hp')])
## hash-function.h (module 'core'): uint32_t ns3::Hash::Function::Hash64::GetHash32(char const * buffer, size_t const size) [member function]
cls.add_method('GetHash32',
'uint32_t',
[param('char const *', 'buffer'), param('size_t const', 'size')],
is_virtual=True)
## hash-function.h (module 'core'): uint64_t ns3::Hash::Function::Hash64::GetHash64(char const * buffer, size_t const size) [member function]
cls.add_method('GetHash64',
'uint64_t',
[param('char const *', 'buffer'), param('size_t const', 'size')],
is_virtual=True)
## hash-function.h (module 'core'): void ns3::Hash::Function::Hash64::clear() [member function]
cls.add_method('clear',
'void',
[],
is_virtual=True)
return
def register_Ns3HashFunctionMurmur3_methods(root_module, cls):
## hash-murmur3.h (module 'core'): ns3::Hash::Function::Murmur3::Murmur3(ns3::Hash::Function::Murmur3 const & arg0) [copy constructor]
cls.add_constructor([param('ns3::Hash::Function::Murmur3 const &', 'arg0')])
## hash-murmur3.h (module 'core'): ns3::Hash::Function::Murmur3::Murmur3() [constructor]
cls.add_constructor([])
## hash-murmur3.h (module 'core'): uint32_t ns3::Hash::Function::Murmur3::GetHash32(char const * buffer, size_t const size) [member function]
cls.add_method('GetHash32',
'uint32_t',
[param('char const *', 'buffer'), param('size_t const', 'size')],
is_virtual=True)
## hash-murmur3.h (module 'core'): uint64_t ns3::Hash::Function::Murmur3::GetHash64(char const * buffer, size_t const size) [member function]
cls.add_method('GetHash64',
'uint64_t',
[param('char const *', 'buffer'), param('size_t const', 'size')],
is_virtual=True)
## hash-murmur3.h (module 'core'): void ns3::Hash::Function::Murmur3::clear() [member function]
cls.add_method('clear',
'void',
[],
is_virtual=True)
return
def register_functions(root_module):
module = root_module
register_functions_ns3_FatalImpl(module.get_submodule('FatalImpl'), root_module)
register_functions_ns3_Hash(module.get_submodule('Hash'), root_module)
register_functions_ns3_TracedValueCallback(module.get_submodule('TracedValueCallback'), root_module)
return
def register_functions_ns3_FatalImpl(module, root_module):
return
def register_functions_ns3_Hash(module, root_module):
register_functions_ns3_Hash_Function(module.get_submodule('Function'), root_module)
return
def register_functions_ns3_Hash_Function(module, root_module):
return
def register_functions_ns3_TracedValueCallback(module, root_module):
return
def main():
out = FileCodeSink(sys.stdout)
root_module = module_init()
register_types(root_module)
register_methods(root_module)
register_functions(root_module)
root_module.generate(out)
if __name__ == '__main__':
main()
| 64.233 | 934 | 0.624277 |
7d93b75165a7e8b230cab1db0603290b95648605 | 20,627 | py | Python | mmdet/core/evaluation/eval_hooks.py | opencv/mmdetection | 6a7dfa5b954d6bbad7f8d33db8268b0fafc7d555 | [
"Apache-2.0"
] | 24 | 2020-04-15T14:54:44.000Z | 2020-08-12T12:45:57.000Z | mmdet/core/evaluation/eval_hooks.py | opencv/mmdetection | 6a7dfa5b954d6bbad7f8d33db8268b0fafc7d555 | [
"Apache-2.0"
] | 46 | 2020-04-10T12:01:59.000Z | 2020-09-04T06:25:56.000Z | mmdet/core/evaluation/eval_hooks.py | opencv/mmdetection | 6a7dfa5b954d6bbad7f8d33db8268b0fafc7d555 | [
"Apache-2.0"
] | 11 | 2020-04-16T17:55:29.000Z | 2020-08-25T11:13:58.000Z | # Copyright (C) 2018-2021 OpenMMLab
# SPDX-License-Identifier: Apache-2.0
#
# Copyright (C) 2020-2021 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
#
# Is based on
# * https://github.com/open-mmlab/mmcv/blob/master/mmcv/runner/hooks/evaluation.py
import os
import os.path as osp
import torch.distributed as dist
import warnings
from math import inf
from mmcv.runner import Hook
from mmcv.utils import is_seq_of
from torch.nn.modules.batchnorm import _BatchNorm
from torch.utils.data import DataLoader
class EvalHook(Hook):
"""Non-Distributed evaluation hook.
This hook will regularly perform evaluation in a given interval when
performing in non-distributed environment.
Args:
dataloader (DataLoader): A PyTorch dataloader, whose dataset has
implemented ``evaluate`` function.
start (int | None, optional): Evaluation starting epoch. It enables
evaluation before the training starts if ``start`` <= the resuming
epoch. If None, whether to evaluate is merely decided by
``interval``. Default: None.
interval (int): Evaluation interval. Default: 1.
by_epoch (bool): Determine perform evaluation by epoch or by iteration.
If set to True, it will perform by epoch. Otherwise, by iteration.
default: True.
save_best (str, optional): If a metric is specified, it would measure
the best checkpoint during evaluation. The information about best
checkpoint would be saved in ``runner.meta['hook_msgs']`` to keep
best score value and best checkpoint path, which will be also
loaded when resume checkpoint. Options are the evaluation metrics
on the test dataset. e.g., ``bbox_mAP``, ``segm_mAP`` for bbox
detection and instance segmentation. ``AR@100`` for proposal
recall. If ``save_best`` is ``auto``, the first key of the returned
``OrderedDict`` result will be used. Default: None.
rule (str | None, optional): Comparison rule for best score. If set to
None, it will infer a reasonable rule. Keys such as 'acc', 'top'
.etc will be inferred by 'greater' rule. Keys contain 'loss' will
be inferred by 'less' rule. Options are 'greater', 'less', None.
Default: None.
test_fn (callable, optional): test a model with samples from a
dataloader, and return the test results. If ``None``, the default
test function ``mmcv.engine.single_gpu_test`` will be used.
(default: ``None``)
greater_keys (List[str] | None, optional): Metric keys that will be
inferred by 'greater' comparison rule. If ``None``,
_default_greater_keys will be used. (default: ``None``)
less_keys (List[str] | None, optional): Metric keys that will be
inferred by 'less' comparison rule. If ``None``, _default_less_keys
will be used. (default: ``None``)
**eval_kwargs: Evaluation arguments fed into the evaluate function of
the dataset.
Notes:
If new arguments are added for EvalHook, tools/test.py,
tools/eval_metric.py may be affected.
"""
# Since the key for determine greater or less is related to the downstream
# tasks, downstream repos may need to overwrite the following inner
# variable accordingly.
rule_map = {'greater': lambda x, y: x > y, 'less': lambda x, y: x < y}
init_value_map = {'greater': -inf, 'less': inf}
_default_greater_keys = ['mAP', 'AR', 'mIoU']
_default_less_keys = ['loss']
def __init__(self,
dataloader,
start=None,
interval=1,
by_epoch=True,
save_best=None,
rule=None,
test_fn=None,
greater_keys=None,
less_keys=None,
best_ckpt_path=None,
**eval_kwargs):
if not isinstance(dataloader, DataLoader):
raise TypeError(f'dataloader must be a pytorch DataLoader, '
f'but got {type(dataloader)}')
if interval <= 0:
raise ValueError(f'interval must be a positive number, '
f'but got {interval}')
assert isinstance(by_epoch, bool), '``by_epoch`` should be a boolean'
if start is not None and start < 0:
warnings.warn(
f'The evaluation start epoch {start} is smaller than 0, '
f'use 0 instead', UserWarning)
start = 0
self.dataloader = dataloader
self.interval = interval
self.start = start
self.by_epoch = by_epoch
assert isinstance(save_best, str) or save_best is None, \
'""save_best"" should be a str or None ' \
f'rather than {type(save_best)}'
self.save_best = save_best
self.eval_kwargs = eval_kwargs
self.initial_flag = True
if test_fn is None:
from mmdet.apis import single_gpu_test
self.test_fn = single_gpu_test
else:
self.test_fn = test_fn
if greater_keys is None:
self.greater_keys = self._default_greater_keys
else:
if not isinstance(greater_keys, (list, tuple)):
greater_keys = (greater_keys, )
assert is_seq_of(greater_keys, str)
self.greater_keys = greater_keys
if less_keys is None:
self.less_keys = self._default_less_keys
else:
if not isinstance(less_keys, (list, tuple)):
less_keys = (less_keys, )
assert is_seq_of(less_keys, str)
self.less_keys = less_keys
if self.save_best is not None:
self.best_ckpt_path = best_ckpt_path
self._init_rule(rule, self.save_best)
def _init_rule(self, rule, key_indicator):
"""Initialize rule, key_indicator, comparison_func, and best score.
Here is the rule to determine which rule is used for key indicator
when the rule is not specific (note that the key indicator matching
is case-insensitive):
1. If the key indicator is in ``self.greater_keys``, the rule will be
specified as 'greater'.
2. Or if the key indicator is in ``self.less_keys``, the rule will be
specified as 'less'.
3. Or if the key indicator is equal to the substring in any one item
in ``self.greater_keys``, the rule will be specified as 'greater'.
4. Or if the key indicator is equal to the substring in any one item
in ``self.less_keys``, the rule will be specified as 'less'.
Args:
rule (str | None): Comparison rule for best score.
key_indicator (str | None): Key indicator to determine the
comparison rule.
"""
if rule not in self.rule_map and rule is not None:
raise KeyError(f'rule must be greater, less or None, '
f'but got {rule}.')
if rule is None:
if key_indicator != 'auto':
# `_lc` here means we use the lower case of keys for
# case-insensitive matching
key_indicator_lc = key_indicator.lower()
greater_keys = [key.lower() for key in self.greater_keys]
less_keys = [key.lower() for key in self.less_keys]
if key_indicator_lc in greater_keys:
rule = 'greater'
elif key_indicator_lc in less_keys:
rule = 'less'
elif any(key in key_indicator_lc for key in greater_keys):
rule = 'greater'
elif any(key in key_indicator_lc for key in less_keys):
rule = 'less'
else:
raise ValueError(f'Cannot infer the rule for key '
f'{key_indicator}, thus a specific rule '
f'must be specified.')
self.rule = rule
self.key_indicator = key_indicator
if self.rule is not None:
self.compare_func = self.rule_map[self.rule]
def before_run(self, runner):
if self.save_best is not None:
if runner.meta is None:
warnings.warn('runner.meta is None. Creating an empty one.')
runner.meta = dict()
runner.meta.setdefault('hook_msgs', dict())
self.best_ckpt_path = runner.meta['hook_msgs'].get(
'best_ckpt', None)
def before_train_iter(self, runner):
"""Evaluate the model only at the start of training by iteration."""
if self.by_epoch or not self.initial_flag:
return
if self.start is not None and runner.iter >= self.start:
self.after_train_iter(runner)
self.initial_flag = False
def before_train_epoch(self, runner):
"""Evaluate the model only at the start of training by epoch."""
if not (self.by_epoch and self.initial_flag):
return
if self.start is not None and runner.epoch >= self.start:
self.after_train_epoch(runner)
self.initial_flag = False
def after_train_iter(self, runner):
"""Called after every training iter to evaluate the results."""
if not self.by_epoch:
self._do_evaluate(runner)
def after_train_epoch(self, runner):
"""Called after every training epoch to evaluate the results."""
if self.by_epoch:
self._do_evaluate(runner)
def _do_evaluate(self, runner):
"""perform evaluation and save ckpt."""
if not self._should_evaluate(runner):
return
from mmdet.apis import single_gpu_test
results = single_gpu_test(runner.model, self.dataloader, show=False)
runner.log_buffer.output['eval_iter_num'] = len(self.dataloader)
key_score = self.evaluate(runner, results)
if self.save_best:
self._save_ckpt(runner, key_score)
def _should_evaluate(self, runner):
"""Judge whether to perform evaluation.
Here is the rule to judge whether to perform evaluation:
1. It will not perform evaluation during the epoch/iteration interval,
which is determined by ``self.interval``.
2. It will not perform evaluation if the start time is larger than
current time.
3. It will not perform evaluation when current time is larger than
the start time but during epoch/iteration interval.
Returns:
bool: The flag indicating whether to perform evaluation.
"""
if self.by_epoch:
current = runner.epoch
check_time = self.every_n_epochs
else:
current = runner.iter
check_time = self.every_n_iters
if self.start is None:
if not check_time(runner, self.interval):
# No evaluation during the interval.
return False
elif (current + 1) < self.start:
# No evaluation if start is larger than the current time.
return False
else:
# Evaluation only at epochs/iters 3, 5, 7...
# if start==3 and interval==2
if (current + 1 - self.start) % self.interval:
return False
return True
def _save_ckpt(self, runner, key_score):
"""Save the best checkpoint.
It will compare the score according to the compare function, write
related information (best score, best checkpoint path) and save the
best checkpoint into ``work_dir``.
"""
if self.by_epoch:
current = f'epoch_{runner.epoch + 1}'
cur_type, cur_time = 'epoch', runner.epoch + 1
else:
current = f'iter_{runner.iter + 1}'
cur_type, cur_time = 'iter', runner.iter + 1
best_score = runner.meta['hook_msgs'].get(
'best_score', self.init_value_map[self.rule])
if self.compare_func(key_score, best_score):
best_score = key_score
runner.meta['hook_msgs']['best_score'] = best_score
if self.best_ckpt_path and osp.isfile(self.best_ckpt_path):
os.remove(self.best_ckpt_path)
best_ckpt_name = f'best_{self.key_indicator}_{current}.pth'
self.best_ckpt_path = osp.join(runner.work_dir, best_ckpt_name)
runner.meta['hook_msgs']['best_ckpt'] = self.best_ckpt_path
runner.save_checkpoint(
runner.work_dir, best_ckpt_name, create_symlink=False)
runner.logger.info(
f'Now best checkpoint is saved as {best_ckpt_name}.')
runner.logger.info(
f'Best {self.key_indicator} is {best_score:0.4f} '
f'at {cur_time} {cur_type}.')
def evaluate(self, runner, results):
"""Evaluate the results.
Args:
runner (:obj:`mmcv.Runner`): The underlined training runner.
results (list): Output results.
"""
eval_res = self.dataloader.dataset.evaluate(
results, logger=runner.logger, **self.eval_kwargs)
for name, val in eval_res.items():
runner.log_buffer.output[name] = val
# TODO: Log is cleared in Logger.after_train_iter before ReduceOnPlateau could get the metric
setattr(runner, name, val)
runner.log_buffer.ready = True
if self.save_best is not None:
if self.key_indicator == 'auto':
# infer from eval_results
self._init_rule(self.rule, list(eval_res.keys())[0])
return eval_res.get(self.key_indicator, 0.0)
return None
class DistEvalHook(EvalHook):
"""Distributed evaluation hook.
This hook will regularly perform evaluation in a given interval when
performing in distributed environment.
Args:
dataloader (DataLoader): A PyTorch dataloader, whose dataset has
implemented ``evaluate`` function.
start (int | None, optional): Evaluation starting epoch. It enables
evaluation before the training starts if ``start`` <= the resuming
epoch. If None, whether to evaluate is merely decided by
``interval``. Default: None.
interval (int): Evaluation interval. Default: 1.
by_epoch (bool): Determine perform evaluation by epoch or by iteration.
If set to True, it will perform by epoch. Otherwise, by iteration.
default: True.
save_best (str, optional): If a metric is specified, it would measure
the best checkpoint during evaluation. The information about best
checkpoint would be saved in ``runner.meta['hook_msgs']`` to keep
best score value and best checkpoint path, which will be also
loaded when resume checkpoint. Options are the evaluation metrics
on the test dataset. e.g., ``bbox_mAP``, ``segm_mAP`` for bbox
detection and instance segmentation. ``AR@100`` for proposal
recall. If ``save_best`` is ``auto``, the first key of the returned
``OrderedDict`` result will be used. Default: None.
rule (str | None, optional): Comparison rule for best score. If set to
None, it will infer a reasonable rule. Keys such as 'acc', 'top'
.etc will be inferred by 'greater' rule. Keys contain 'loss' will
be inferred by 'less' rule. Options are 'greater', 'less', None.
Default: None.
test_fn (callable, optional): test a model with samples from a
dataloader in a multi-gpu manner, and return the test results. If
``None``, the default test function ``mmcv.engine.multi_gpu_test``
will be used. (default: ``None``)
tmpdir (str | None): Temporary directory to save the results of all
processes. Default: None.
gpu_collect (bool): Whether to use gpu or cpu to collect results.
Default: False.
broadcast_bn_buffer (bool): Whether to broadcast the
buffer(running_mean and running_var) of rank 0 to other rank
before evaluation. Default: True.
**eval_kwargs: Evaluation arguments fed into the evaluate function of
the dataset.
"""
def __init__(self,
dataloader,
start=None,
interval=1,
by_epoch=True,
save_best=None,
rule=None,
test_fn=None,
greater_keys=None,
less_keys=None,
broadcast_bn_buffer=True,
tmpdir=None,
gpu_collect=False,
**eval_kwargs):
if test_fn is None:
from mmdet.apis import multi_gpu_test
test_fn = multi_gpu_test
super().__init__(
dataloader,
start=start,
interval=interval,
by_epoch=by_epoch,
save_best=save_best,
rule=rule,
test_fn=test_fn,
greater_keys=greater_keys,
less_keys=less_keys,
**eval_kwargs)
self.broadcast_bn_buffer = broadcast_bn_buffer
self.tmpdir = tmpdir
self.gpu_collect = gpu_collect
def broadcast(self, data):
broadcast_obj = [data]
if dist.is_initialized():
dist.broadcast_object_list(broadcast_obj, src=0)
return broadcast_obj[0]
def _do_evaluate(self, runner):
"""perform evaluation and save ckpt."""
# Synchronization of BatchNorm's buffer (running_mean
# and running_var) is not supported in the DDP of pytorch,
# which may cause the inconsistent performance of models in
# different ranks, so we broadcast BatchNorm's buffers
# of rank 0 to other ranks to avoid this.
if self.broadcast_bn_buffer:
model = runner.model
for name, module in model.named_modules():
if isinstance(module,
_BatchNorm) and module.track_running_stats:
dist.broadcast(module.running_var, 0)
dist.broadcast(module.running_mean, 0)
if not self._should_evaluate(runner):
return
tmpdir = self.tmpdir
if tmpdir is None:
tmpdir = osp.join(runner.work_dir, '.eval_hook')
from mmdet.apis import multi_gpu_test
results = multi_gpu_test(
runner.model,
self.dataloader,
tmpdir=tmpdir,
gpu_collect=self.gpu_collect)
broadcast_data = None
if runner.rank == 0:
print('\n')
runner.log_buffer.output['eval_iter_num'] = len(self.dataloader)
key_score = self.evaluate(runner, results)
# TODO: Log is cleared in Logger.after_train_iter before ReduceOnPlateau could get the metric
for name, val in runner.log_buffer.output.items():
setattr(runner, name, val)
if self.save_best:
self._save_ckpt(runner, key_score)
if self.save_best == 'auto':
broadcast_data = runner.log_buffer.output[
self.key_indicator]
else:
broadcast_data = runner.log_buffer.output[self.save_best]
score = self.broadcast(broadcast_data)
if runner.rank != 0 and self.save_best:
setattr(runner, self.save_best, score)
class EvalPlusBeforeRunHook(EvalHook):
"""Evaluation hook, adds evaluation before training.
"""
def before_run(self, runner):
super().before_run(runner)
from mmdet.apis import single_gpu_test
results = single_gpu_test(runner.model, self.dataloader, show=False)
self.evaluate(runner, results)
class DistEvalPlusBeforeRunHook(EvalPlusBeforeRunHook, DistEvalHook):
"""Distributed evaluation hook, adds evaluation before training.
"""
def before_run(self, runner):
from mmdet.apis import multi_gpu_test
results = multi_gpu_test(
runner.model,
self.dataloader,
tmpdir=osp.join(runner.work_dir, '.eval_hook'),
gpu_collect=self.gpu_collect)
if runner.rank == 0:
print('\n')
self.evaluate(runner, results)
| 42.442387 | 105 | 0.602608 |
70b31579fb7a81e51c07058fd91c64e633bedc5f | 599 | py | Python | addons/bi_hr_payroll/models/hr_employee.py | nathanbangwa243/house-location | fa38203b2c92dd97f253fc3b4354af228f1b0338 | [
"MIT"
] | 1 | 2021-11-17T18:49:44.000Z | 2021-11-17T18:49:44.000Z | addons/bi_hr_payroll/models/hr_employee.py | nathanbangwa243/house-location | fa38203b2c92dd97f253fc3b4354af228f1b0338 | [
"MIT"
] | null | null | null | addons/bi_hr_payroll/models/hr_employee.py | nathanbangwa243/house-location | fa38203b2c92dd97f253fc3b4354af228f1b0338 | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
# Part of BrowseInfo. See LICENSE file for full copyright and licensing details.
from odoo import api, fields, models
class HrEmployee(models.Model):
_inherit = 'hr.employee'
_description = 'Employee'
slip_ids = fields.One2many('hr.payslip', 'employee_id', string='Payslips', readonly=True)
payslip_count = fields.Integer(compute='_compute_payslip_count', string='Payslip Count', groups="bi_hr_payroll.group_hr_payroll_user")
def _compute_payslip_count(self):
for employee in self:
employee.payslip_count = len(employee.slip_ids)
| 35.235294 | 138 | 0.72621 |
c49869593f4ded53c42023304e6098f3cc065118 | 731 | py | Python | dataset_script/analysis_predict.py | TITC/bert | bed2ff5dc4cdf2f01599cfdcb9862f6016bf44f6 | [
"Apache-2.0"
] | null | null | null | dataset_script/analysis_predict.py | TITC/bert | bed2ff5dc4cdf2f01599cfdcb9862f6016bf44f6 | [
"Apache-2.0"
] | null | null | null | dataset_script/analysis_predict.py | TITC/bert | bed2ff5dc4cdf2f01599cfdcb9862f6016bf44f6 | [
"Apache-2.0"
] | null | null | null | in_csv = '/content/bert/tmp/predict/test_results.tsv'
file1 = open(in_csv, 'r')
Lines_predict = file1.readlines()
number_lines = sum(1 for row in (open(in_csv)))
in_csv = '/content/bert/datasets/chinese_dictionary-master/ant_syn_datasets/test.tsv'
file1 = open(in_csv, 'r')
Lines_test = file1.readlines()
correct = 0
for i in range(number_lines):
cur_test = Lines_test[i+1].replace('\n', '')
cur_pre = Lines_predict[i]
cur_pre = cur_pre.replace('\n', '').split("\t")
max_prob = max([float(ele) for ele in cur_pre])
predict = cur_pre.index(str(max_prob))
cur_test = cur_test.split('\t')
if predict == int(cur_test[0]):
correct += 1
else:
print(cur_test)
print(correct/number_lines)
| 31.782609 | 85 | 0.677155 |
5b3ea335d97d318e9ebd0514855f1d47ab5a194c | 9,641 | py | Python | research/object_detection/models/retinanet_feature_extractor.py | y-kallel/models | 4d073d82d988d0147cb2d17b4390e8fab1f46e6d | [
"Apache-2.0"
] | null | null | null | research/object_detection/models/retinanet_feature_extractor.py | y-kallel/models | 4d073d82d988d0147cb2d17b4390e8fab1f46e6d | [
"Apache-2.0"
] | null | null | null | research/object_detection/models/retinanet_feature_extractor.py | y-kallel/models | 4d073d82d988d0147cb2d17b4390e8fab1f46e6d | [
"Apache-2.0"
] | null | null | null | # Copyright 2017 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.
# ==============================================================================
"""RetinaNet feature extractors based on Resnet v1.
See https://arxiv.org/abs/1708.02002 for details.
"""
import tensorflow as tf
from object_detection.meta_architectures import ssd_meta_arch
from object_detection.utils import context_manager
from object_detection.utils import ops
from object_detection.utils import shape_utils
from object_detection.models.retinanet import retinanet_fpn
RESNET_ARCH_BLOCK = {"resnet50": [3, 4, 6, 3],
"resnet101": [3, 4, 23, 3]}
class RetinaNetFeatureExtractor(ssd_meta_arch.SSDFeatureExtractor):
"""SSD FPN feature extractor based on Resnet v1 architecture."""
def __init__(self,
is_training,
depth_multiplier,
min_depth,
conv_hyperparams_fn,
pad_to_multiple,
backbone,
fpn_scope_name,
min_level=3,
max_level=7,
additional_layer_depth=256,
reuse_weights=None,
use_explicit_padding=False,
use_depthwise=False,
override_base_feature_extractor_hyperparams=False):
"""RetinaNet feature extractor.
Args:
is_training: whether the network is in training mode.
depth_multiplier: float depth multiplier for feature extractor.
min_depth: minimum feature extractor depth.
pad_to_multiple: the nearest multiple to zero pad the input height and
width dimensions to.
fpn_scope_name: scope name under which to construct the feature pyramid
network.
additional_layer_depth: additional feature map layer channel depth.
reuse_weights: Whether to reuse variables. Default is None.
use_explicit_padding: Whether to use explicit padding when extracting
features. Default is False. UNUSED currently.
use_depthwise: Whether to use depthwise convolutions. UNUSED currently.
override_base_feature_extractor_hyperparams: Whether to override
hyperparameters of the base feature extractor with the one from
`conv_hyperparams_fn`.
Raises:
ValueError: On supplying invalid arguments for unused arguments.
"""
super(RetinaNetFeatureExtractor, self).__init__(
is_training=is_training,
depth_multiplier=depth_multiplier,
min_depth=min_depth,
conv_hyperparams_fn=conv_hyperparams_fn,
pad_to_multiple=pad_to_multiple,
reuse_weights=reuse_weights,
use_explicit_padding=use_explicit_padding,
use_depthwise=use_depthwise,
override_base_feature_extractor_hyperparams=
override_base_feature_extractor_hyperparams)
if self._use_explicit_padding is True:
raise ValueError('Explicit padding is not a valid option.')
self._backbone = backbone
self._fpn_scope_name = fpn_scope_name
self._min_level = min_level
self._max_level = max_level
self._additional_layer_depth = additional_layer_depth
def preprocess(self, resized_inputs):
"""SSD preprocessing.
VGG style channel mean subtraction as described here:
https://gist.github.com/ksimonyan/211839e770f7b538e2d8#file-readme-mdnge.
Note that if the number of channels is not equal to 3, the mean subtraction
will be skipped and the original resized_inputs will be returned.
Args:
resized_inputs: a [batch, height, width, channels] float tensor
representing a batch of images.
Returns:
preprocessed_inputs: a [batch, height, width, channels] float tensor
representing a batch of images.
"""
if resized_inputs.shape.as_list()[3] == 3:
channel_means = [123.68, 116.779, 103.939]
return resized_inputs - [[channel_means]]
else:
return resized_inputs
def extract_features(self, preprocessed_inputs):
"""Extract features from preprocessed inputs.
Args:
preprocessed_inputs: a [batch, height, width, channels] float tensor
representing a batch of images.
Returns:
feature_maps: a list of tensors where the ith tensor has shape
[batch, height_i, width_i, depth_i]
"""
preprocessed_inputs = shape_utils.check_min_image_dim(
129, preprocessed_inputs)
with tf.variable_scope(
self._fpn_scope_name, reuse=self._reuse_weights) as scope:
if self._backbone in list(RESNET_ARCH_BLOCK.keys()):
block_layers = RESNET_ARCH_BLOCK[self._backbone]
else:
raise ValueError("Unknown backbone found! Only resnet50 or resnet101 is allowed!")
image_features = retinanet_fpn(inputs=preprocessed_inputs,
block_layers=block_layers,
depth=self._additional_layer_depth,
is_training=self._is_training)
return [image_features[x] for x in range(self._min_level, self._max_level+1)]
class RetinaNet50FeatureExtractor(RetinaNetFeatureExtractor):
"""Resnet 50 RetinaNet feature extractor."""
def __init__(self,
is_training,
depth_multiplier,
min_depth,
conv_hyperparams_fn,
pad_to_multiple,
backbone='resnet50',
additional_layer_depth=256,
reuse_weights=None,
use_explicit_padding=False,
use_depthwise=False,
override_base_feature_extractor_hyperparams=False):
"""
Args:
is_training: whether the network is in training mode.
depth_multiplier: float depth multiplier for feature extractor.
UNUSED currently.
min_depth: minimum feature extractor depth. UNUSED Currently.
pad_to_multiple: the nearest multiple to zero pad the input height and
width dimensions to.
additional_layer_depth: additional feature map layer channel depth.
reuse_weights: Whether to reuse variables. Default is None.
use_explicit_padding: Whether to use explicit padding when extracting
features. Default is False. UNUSED currently.
use_depthwise: Whether to use depthwise convolutions. UNUSED currently.
override_base_feature_extractor_hyperparams: Whether to override
hyperparameters of the base feature extractor with the one from
`conv_hyperparams_fn`.
"""
super(RetinaNet50FeatureExtractor, self).__init__(
is_training=is_training,
depth_multiplier=depth_multiplier,
min_depth=min_depth,
conv_hyperparams_fn=conv_hyperparams_fn,
pad_to_multiple=pad_to_multiple,
backbone='resnet50',
fpn_scope_name='retinanet50',
additional_layer_depth=additional_layer_depth,
reuse_weights=reuse_weights,
use_explicit_padding=use_explicit_padding,
use_depthwise=use_depthwise,
override_base_feature_extractor_hyperparams=
override_base_feature_extractor_hyperparams)
class RetinaNet101FeatureExtractor(RetinaNetFeatureExtractor):
"""Resnet 101 RetinaNet feature extractor."""
def __init__(self,
is_training,
depth_multiplier,
min_depth,
conv_hyperparams_fn,
pad_to_multiple,
backbone='resnet101',
additional_layer_depth=256,
reuse_weights=None,
use_explicit_padding=False,
use_depthwise=False,
override_base_feature_extractor_hyperparams=False):
"""
Args:
is_training: whether the network is in training mode.
depth_multiplier: float depth multiplier for feature extractor.
UNUSED currently.
min_depth: minimum feature extractor depth. UNUSED Currently.
pad_to_multiple: the nearest multiple to zero pad the input height and
width dimensions to.
additional_layer_depth: additional feature map layer channel depth.
reuse_weights: Whether to reuse variables. Default is None.
use_explicit_padding: Whether to use explicit padding when extracting
features. Default is False. UNUSED currently.
use_depthwise: Whether to use depthwise convolutions. UNUSED currently.
override_base_feature_extractor_hyperparams: Whether to override
hyperparameters of the base feature extractor with the one from
`conv_hyperparams_fn`.
"""
super(RetinaNet101FeatureExtractor, self).__init__(
is_training=is_training,
depth_multiplier=depth_multiplier,
min_depth=min_depth,
conv_hyperparams_fn=conv_hyperparams_fn,
pad_to_multiple=pad_to_multiple,
backbone='resnet101',
fpn_scope_name='retinanet101',
additional_layer_depth=additional_layer_depth,
reuse_weights=reuse_weights,
use_explicit_padding=use_explicit_padding,
use_depthwise=use_depthwise,
override_base_feature_extractor_hyperparams=
override_base_feature_extractor_hyperparams)
| 43.624434 | 92 | 0.695467 |
246720425b71f6f9968abd5573e054fe3530dbbb | 1,943 | py | Python | csc301-winter-2020/assignments/assignment2/coverage_grader.py | shibshib/gitomator-classroom | 7d3c504063ebf8cb34de3872f78baf86fdbeec52 | [
"MIT"
] | null | null | null | csc301-winter-2020/assignments/assignment2/coverage_grader.py | shibshib/gitomator-classroom | 7d3c504063ebf8cb34de3872f78baf86fdbeec52 | [
"MIT"
] | null | null | null | csc301-winter-2020/assignments/assignment2/coverage_grader.py | shibshib/gitomator-classroom | 7d3c504063ebf8cb34de3872f78baf86fdbeec52 | [
"MIT"
] | null | null | null | import xmltodict
import json
import argparse
from loguru import logger
import os
COV_GRADE_FILE = "coverage_grade.txt"
def evaluate_line_rate(line_rate):
logger.info("Evaluating line rate of {}".format(line_rate))
grade = 0
if line_rate > 90:
grade = 35
elif line_rate > 80 and line_rate < 90:
grade = 30
elif line_rate > 70 and line_rate < 80:
grade = 25
elif line_rate > 60 and line_rate < 70:
grade = 20
return grade
def extract_folderpath(filepath):
return os.path.dirname(os.path.abspath(filepath))
def generate_json_file(xml_file, json_file):
with open(xml_file) as in_file:
xml = in_file.read()
with open(json_file, 'w+') as out_file:
json_coverage = xmltodict.parse(xml)
json.dump(xmltodict.parse(xml), out_file)
return json_coverage
def analyze_tests_coverage(coverage_grade_file_location, coverage):
grade_file = "{}/{}".format(coverage_grade_file_location, COV_GRADE_FILE)
coverage = coverage['coverage']
if coverage:
line_rate = coverage.get("@line-rate")
grade = evaluate_line_rate(float(line_rate)*100)
with open(grade_file, 'w+') as grade_file:
grade_file.write("Coverage grade: {}".format(grade))
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument(
'--xml_file',
default='./autograder_coverage.xml',
type=str,
help='Path to coverage XML file.'
)
parser.add_argument(
'--json_file',
default='./autograder_coverage.json',
type=str,
help='Path to target JSON file.'
)
args = parser.parse_args()
json_coverage = generate_json_file(args.xml_file, args.json_file)
coverage_grade_file_location = extract_folderpath(args.json_file)
analyze_tests_coverage(coverage_grade_file_location, json_coverage)
| 29.439394 | 77 | 0.661863 |
c474dbb5f76c2f0fa6fc82e7ead58ed2c61d5cab | 4,332 | py | Python | metalibm_functions/unit_tests/function_formats.py | nibrunie/metalibm | 776b044f5f323ef907a8724d9ce9a27a482f6cc5 | [
"MIT"
] | 2 | 2019-02-18T13:42:04.000Z | 2021-03-12T18:54:53.000Z | metalibm_functions/unit_tests/function_formats.py | nibrunie/metalibm | 776b044f5f323ef907a8724d9ce9a27a482f6cc5 | [
"MIT"
] | null | null | null | metalibm_functions/unit_tests/function_formats.py | nibrunie/metalibm | 776b044f5f323ef907a8724d9ce9a27a482f6cc5 | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
###############################################################################
# This file is part of metalibm (https://github.com/kalray/metalibm)
###############################################################################
# MIT License
#
# Copyright (c) 2018 Kalray
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in all
# copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.
###############################################################################
# last-modified: Mar 7th, 2018
# Author(s): Nicolas Brunie <nbrunie@kalray.eu>
###############################################################################
import sys
from metalibm_core.core.ml_function import ML_Function, ML_FunctionBasis
from metalibm_core.core.attributes import ML_Debug
from metalibm_core.core.ml_operations import *
from metalibm_core.core.ml_formats import *
from metalibm_core.core.ml_complex_formats import ML_Mpfr_t
from metalibm_core.code_generation.c_code_generator import CCodeGenerator
from metalibm_core.code_generation.generic_processor import GenericProcessor
from metalibm_core.code_generation.mpfr_backend import MPFRProcessor
from metalibm_core.code_generation.code_object import CodeObject
from metalibm_core.code_generation.code_function import CodeFunction
from metalibm_core.code_generation.code_constant import C_Code
from metalibm_core.core.ml_optimization_engine import OptimizationEngine
from metalibm_core.core.polynomials import *
from metalibm_core.core.ml_table import ML_Table
from metalibm_core.code_generation.gappa_code_generator import GappaCodeGenerator
from metalibm_core.utility.gappa_utils import execute_gappa_script_extract
from metalibm_core.utility.ml_template import *
from metalibm_core.utility.arg_utils import test_flag_option, extract_option_value
from metalibm_core.utility.debug_utils import *
class ML_UT_FunctionFormat(ML_Function("ml_ut_function_format")):
def __init__(self, args=DefaultArgTemplate):
# initializing base class
ML_FunctionBasis.__init__(self, args)
@staticmethod
def get_default_args(**kw):
""" Return a structure containing the arguments for current class,
builtin from a default argument mapping overloaded with @p kw """
default_args = {
"output_file": "ut_function_format.c",
"function_name": "ut_function_format",
"precision": ML_Binary32,
"target": MPFRProcessor(),
"fast_path_extract": True,
"fuse_fma": True,
"libm_compliant": True
}
default_args.update(kw)
return DefaultArgTemplate(**default_args)
def generate_scheme(self):
#func_implementation = CodeFunction(self.function_name, output_format = self.precision)
vx = self.implementation.add_input_variable("x", self.get_input_precision())
mpfr_x = Conversion(vx, precision = ML_Mpfr_t)
result = mpfr_x + mpfr_x
result.set_precision(ML_Mpfr_t)
scheme = Statement(Return(Conversion(result, precision = self.precision)))
return scheme
def run_test(args):
ml_ut_function_format = ML_UT_FunctionFormat(args)
ml_ut_function_format.gen_implementation()
return True
if __name__ == "__main__":
# auto-test
arg_template = ML_NewArgTemplate(default_arg=ML_UT_FunctionFormat.get_default_args())
args = arg_template.arg_extraction()
if run_test(args):
exit(0)
else:
exit(1)
| 39.381818 | 91 | 0.724608 |
aa6a7f67ae524865af85cc0252b61c21372e92c1 | 12,276 | py | Python | official/resnet/imagenet_main.py | kichiro09/object-detection | b7087955bb5f2689b0ef42ab5400931cd8f416b6 | [
"Apache-2.0"
] | 48 | 2018-12-19T13:09:14.000Z | 2021-11-12T12:04:36.000Z | official/resnet/imagenet_main.py | bhushan23/models | e498d28503fd4a12d1fa9ade41891f2f9601c674 | [
"Apache-2.0"
] | 12 | 2018-12-13T18:04:36.000Z | 2019-06-14T20:49:33.000Z | official/resnet/imagenet_main.py | bhushan23/models | e498d28503fd4a12d1fa9ade41891f2f9601c674 | [
"Apache-2.0"
] | 44 | 2018-11-09T21:04:52.000Z | 2019-06-24T07:40:28.000Z | # Copyright 2017 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.
# ==============================================================================
"""Runs a ResNet model on the ImageNet dataset."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
from absl import app as absl_app
from absl import flags
import tensorflow as tf # pylint: disable=g-bad-import-order
from official.utils.flags import core as flags_core
from official.utils.logs import logger
from official.resnet import imagenet_preprocessing
from official.resnet import resnet_model
from official.resnet import resnet_run_loop
_DEFAULT_IMAGE_SIZE = 224
_NUM_CHANNELS = 3
_NUM_CLASSES = 1001
_NUM_IMAGES = {
'train': 1281167,
'validation': 50000,
}
_NUM_TRAIN_FILES = 1024
_SHUFFLE_BUFFER = 10000
DATASET_NAME = 'ImageNet'
###############################################################################
# Data processing
###############################################################################
def get_filenames(is_training, data_dir):
"""Return filenames for dataset."""
if is_training:
return [
os.path.join(data_dir, 'train-%05d-of-01024' % i)
for i in range(_NUM_TRAIN_FILES)]
else:
return [
os.path.join(data_dir, 'validation-%05d-of-00128' % i)
for i in range(128)]
def _parse_example_proto(example_serialized):
"""Parses an Example proto containing a training example of an image.
The output of the build_image_data.py image preprocessing script is a dataset
containing serialized Example protocol buffers. Each Example proto contains
the following fields (values are included as examples):
image/height: 462
image/width: 581
image/colorspace: 'RGB'
image/channels: 3
image/class/label: 615
image/class/synset: 'n03623198'
image/class/text: 'knee pad'
image/object/bbox/xmin: 0.1
image/object/bbox/xmax: 0.9
image/object/bbox/ymin: 0.2
image/object/bbox/ymax: 0.6
image/object/bbox/label: 615
image/format: 'JPEG'
image/filename: 'ILSVRC2012_val_00041207.JPEG'
image/encoded: <JPEG encoded string>
Args:
example_serialized: scalar Tensor tf.string containing a serialized
Example protocol buffer.
Returns:
image_buffer: Tensor tf.string containing the contents of a JPEG file.
label: Tensor tf.int32 containing the label.
bbox: 3-D float Tensor of bounding boxes arranged [1, num_boxes, coords]
where each coordinate is [0, 1) and the coordinates are arranged as
[ymin, xmin, ymax, xmax].
"""
# Dense features in Example proto.
feature_map = {
'image/encoded': tf.FixedLenFeature([], dtype=tf.string,
default_value=''),
'image/class/label': tf.FixedLenFeature([], dtype=tf.int64,
default_value=-1),
'image/class/text': tf.FixedLenFeature([], dtype=tf.string,
default_value=''),
}
sparse_float32 = tf.VarLenFeature(dtype=tf.float32)
# Sparse features in Example proto.
feature_map.update(
{k: sparse_float32 for k in ['image/object/bbox/xmin',
'image/object/bbox/ymin',
'image/object/bbox/xmax',
'image/object/bbox/ymax']})
features = tf.parse_single_example(example_serialized, feature_map)
label = tf.cast(features['image/class/label'], dtype=tf.int32)
xmin = tf.expand_dims(features['image/object/bbox/xmin'].values, 0)
ymin = tf.expand_dims(features['image/object/bbox/ymin'].values, 0)
xmax = tf.expand_dims(features['image/object/bbox/xmax'].values, 0)
ymax = tf.expand_dims(features['image/object/bbox/ymax'].values, 0)
# Note that we impose an ordering of (y, x) just to make life difficult.
bbox = tf.concat([ymin, xmin, ymax, xmax], 0)
# Force the variable number of bounding boxes into the shape
# [1, num_boxes, coords].
bbox = tf.expand_dims(bbox, 0)
bbox = tf.transpose(bbox, [0, 2, 1])
return features['image/encoded'], label, bbox
def parse_record(raw_record, is_training, dtype):
"""Parses a record containing a training example of an image.
The input record is parsed into a label and image, and the image is passed
through preprocessing steps (cropping, flipping, and so on).
Args:
raw_record: scalar Tensor tf.string containing a serialized
Example protocol buffer.
is_training: A boolean denoting whether the input is for training.
dtype: data type to use for images/features.
Returns:
Tuple with processed image tensor and one-hot-encoded label tensor.
"""
image_buffer, label, bbox = _parse_example_proto(raw_record)
image = imagenet_preprocessing.preprocess_image(
image_buffer=image_buffer,
bbox=bbox,
output_height=_DEFAULT_IMAGE_SIZE,
output_width=_DEFAULT_IMAGE_SIZE,
num_channels=_NUM_CHANNELS,
is_training=is_training)
image = tf.cast(image, dtype)
return image, label
def input_fn(is_training, data_dir, batch_size, num_epochs=1,
dtype=tf.float32, datasets_num_private_threads=None,
num_parallel_batches=1):
"""Input function which provides batches for train or eval.
Args:
is_training: A boolean denoting whether the input is for training.
data_dir: The directory containing the input data.
batch_size: The number of samples per batch.
num_epochs: The number of epochs to repeat the dataset.
dtype: Data type to use for images/features
datasets_num_private_threads: Number of private threads for tf.data.
num_parallel_batches: Number of parallel batches for tf.data.
Returns:
A dataset that can be used for iteration.
"""
filenames = get_filenames(is_training, data_dir)
dataset = tf.data.Dataset.from_tensor_slices(filenames)
if is_training:
# Shuffle the input files
dataset = dataset.shuffle(buffer_size=_NUM_TRAIN_FILES)
# Convert to individual records.
# cycle_length = 10 means 10 files will be read and deserialized in parallel.
# This number is low enough to not cause too much contention on small systems
# but high enough to provide the benefits of parallelization. You may want
# to increase this number if you have a large number of CPU cores.
dataset = dataset.apply(tf.contrib.data.parallel_interleave(
tf.data.TFRecordDataset, cycle_length=10))
return resnet_run_loop.process_record_dataset(
dataset=dataset,
is_training=is_training,
batch_size=batch_size,
shuffle_buffer=_SHUFFLE_BUFFER,
parse_record_fn=parse_record,
num_epochs=num_epochs,
dtype=dtype,
datasets_num_private_threads=datasets_num_private_threads,
num_parallel_batches=num_parallel_batches
)
def get_synth_input_fn(dtype):
return resnet_run_loop.get_synth_input_fn(
_DEFAULT_IMAGE_SIZE, _DEFAULT_IMAGE_SIZE, _NUM_CHANNELS, _NUM_CLASSES,
dtype=dtype)
###############################################################################
# Running the model
###############################################################################
class ImagenetModel(resnet_model.Model):
"""Model class with appropriate defaults for Imagenet data."""
def __init__(self, resnet_size, data_format=None, num_classes=_NUM_CLASSES,
resnet_version=resnet_model.DEFAULT_VERSION,
dtype=resnet_model.DEFAULT_DTYPE):
"""These are the parameters that work for Imagenet data.
Args:
resnet_size: The number of convolutional layers needed in the model.
data_format: Either 'channels_first' or 'channels_last', specifying which
data format to use when setting up the model.
num_classes: The number of output classes needed from the model. This
enables users to extend the same model to their own datasets.
resnet_version: Integer representing which version of the ResNet network
to use. See README for details. Valid values: [1, 2]
dtype: The TensorFlow dtype to use for calculations.
"""
# For bigger models, we want to use "bottleneck" layers
if resnet_size < 50:
bottleneck = False
else:
bottleneck = True
super(ImagenetModel, self).__init__(
resnet_size=resnet_size,
bottleneck=bottleneck,
num_classes=num_classes,
num_filters=64,
kernel_size=7,
conv_stride=2,
first_pool_size=3,
first_pool_stride=2,
block_sizes=_get_block_sizes(resnet_size),
block_strides=[1, 2, 2, 2],
resnet_version=resnet_version,
data_format=data_format,
dtype=dtype
)
def _get_block_sizes(resnet_size):
"""Retrieve the size of each block_layer in the ResNet model.
The number of block layers used for the Resnet model varies according
to the size of the model. This helper grabs the layer set we want, throwing
an error if a non-standard size has been selected.
Args:
resnet_size: The number of convolutional layers needed in the model.
Returns:
A list of block sizes to use in building the model.
Raises:
KeyError: if invalid resnet_size is received.
"""
choices = {
18: [2, 2, 2, 2],
34: [3, 4, 6, 3],
50: [3, 4, 6, 3],
101: [3, 4, 23, 3],
152: [3, 8, 36, 3],
200: [3, 24, 36, 3]
}
try:
return choices[resnet_size]
except KeyError:
err = ('Could not find layers for selected Resnet size.\n'
'Size received: {}; sizes allowed: {}.'.format(
resnet_size, choices.keys()))
raise ValueError(err)
def imagenet_model_fn(features, labels, mode, params):
"""Our model_fn for ResNet to be used with our Estimator."""
# Warmup and higher lr may not be valid for fine tuning with small batches
# and smaller numbers of training images.
if params['fine_tune']:
warmup = False
base_lr = .1
else:
warmup = True
base_lr = .128
learning_rate_fn = resnet_run_loop.learning_rate_with_decay(
batch_size=params['batch_size'], batch_denom=256,
num_images=_NUM_IMAGES['train'], boundary_epochs=[30, 60, 80, 90],
decay_rates=[1, 0.1, 0.01, 0.001, 1e-4], warmup=warmup, base_lr=base_lr)
return resnet_run_loop.resnet_model_fn(
features=features,
labels=labels,
mode=mode,
model_class=ImagenetModel,
resnet_size=params['resnet_size'],
weight_decay=1e-4,
learning_rate_fn=learning_rate_fn,
momentum=0.9,
data_format=params['data_format'],
resnet_version=params['resnet_version'],
loss_scale=params['loss_scale'],
loss_filter_fn=None,
dtype=params['dtype'],
fine_tune=params['fine_tune']
)
def define_imagenet_flags():
resnet_run_loop.define_resnet_flags(
resnet_size_choices=['18', '34', '50', '101', '152', '200'])
flags.adopt_module_key_flags(resnet_run_loop)
flags_core.set_defaults(train_epochs=90)
def run_imagenet(flags_obj):
"""Run ResNet ImageNet training and eval loop.
Args:
flags_obj: An object containing parsed flag values.
"""
input_function = (flags_obj.use_synthetic_data and
get_synth_input_fn(flags_core.get_tf_dtype(flags_obj)) or
input_fn)
resnet_run_loop.resnet_main(
flags_obj, imagenet_model_fn, input_function, DATASET_NAME,
shape=[_DEFAULT_IMAGE_SIZE, _DEFAULT_IMAGE_SIZE, _NUM_CHANNELS])
def main(_):
with logger.benchmark_context(flags.FLAGS):
run_imagenet(flags.FLAGS)
if __name__ == '__main__':
tf.logging.set_verbosity(tf.logging.INFO)
define_imagenet_flags()
absl_app.run(main)
| 34.386555 | 80 | 0.678804 |
78de34db1136d45b305fa61e25c62b02195ed359 | 168 | py | Python | Pcolors/shortcuts/__init__.py | rafalou38/Pcolors | a4dc57c57d6a142a23a8ce8bc422581028fc8abd | [
"MIT"
] | 1 | 2020-08-31T09:45:28.000Z | 2020-08-31T09:45:28.000Z | Pcolors/shortcuts/__init__.py | rafalou38/Pcolors | a4dc57c57d6a142a23a8ce8bc422581028fc8abd | [
"MIT"
] | null | null | null | Pcolors/shortcuts/__init__.py | rafalou38/Pcolors | a4dc57c57d6a142a23a8ce8bc422581028fc8abd | [
"MIT"
] | null | null | null | from . import dark, light, format
def to_bg(id):
"""
:param id: id of a color (light or dark)
:return: id of the color for background
"""
return str(int(id) + 10) | 21 | 41 | 0.654762 |
80bc55b42901ad1ac86043ba360ea5d3fe5ba8b1 | 9,865 | py | Python | src/retroasm/asm_parser.py | mthuurne/retroasm | 90b6617f7b24da05f55efceb1447314b251192e8 | [
"MIT"
] | 2 | 2019-11-29T22:57:42.000Z | 2022-03-29T21:31:47.000Z | src/retroasm/asm_parser.py | mthuurne/retroasm | 90b6617f7b24da05f55efceb1447314b251192e8 | [
"MIT"
] | null | null | null | src/retroasm/asm_parser.py | mthuurne/retroasm | 90b6617f7b24da05f55efceb1447314b251192e8 | [
"MIT"
] | null | null | null | from __future__ import annotations
from logging import getLogger
from pathlib import Path
from typing import Iterable, Iterator
from .asm_directives import DataDirective, OriginDirective, StringDirective
from .expression import Expression, IntLiteral, truncate
from .expression_nodes import IdentifierNode, NumberNode, ParseError, parseDigits
from .instrset import InstructionSet
from .linereader import DelayedError, InputLocation, LineReader
from .reference import FixedValueReference
from .symbol import SymbolValue
from .tokens import TokenEnum, Tokenizer
from .types import IntType, unlimited
from .utils import bad_type
logger = getLogger("parse-asm")
class AsmToken(TokenEnum):
number = r"\$\w+|%\w+|\d\w*|0[xXbB]\w+"
word = r"[\w.]+"
string = r'"[^"]*"|\'[^\']*\''
comment = r";.*$"
symbol = r"."
Token = tuple[AsmToken, InputLocation]
def parse_number(location: InputLocation) -> NumberNode:
"""
Parse a numeric literal in one of several formats.
Raise `ValueError` if the location does not contain a valid number.
"""
value = location.text
if value[0] == "$":
digits = value[1:]
digit_width = 4
elif value[0] == "%":
digits = value[1:]
digit_width = 1
elif value[0] == "0" and len(value) >= 2 and value[1] in "xXbB":
digits = value[2:]
digit_width = 4 if value[1] in "xX" else 1
elif value[-1].isdigit():
# Decimal numbers have no integer per-digit width.
return NumberNode(parseDigits(value, 10), unlimited, location)
else:
digits = value[:-1]
try:
digit_width = {"b": 1, "h": 4}[value[-1].casefold()]
except KeyError:
raise ValueError(f'bad number suffix "{value[-1]}"') from None
return NumberNode(
parseDigits(digits, 1 << digit_width), len(digits) * digit_width, location
)
def create_match_sequence(
nodes: Iterable[IdentifierNode | NumberNode],
) -> Iterator[type[int] | str]:
"""Convert tokens to a match sequence."""
for node in nodes:
if isinstance(node, IdentifierNode):
yield node.name
elif isinstance(node, NumberNode):
yield int
else:
bad_type(node)
def parse_instruction(
tokens: Tokenizer[AsmToken], reader: LineReader
) -> Iterator[IdentifierNode | NumberNode]:
for kind, location in tokens:
if kind is AsmToken.word:
yield IdentifierNode(location.text, location)
elif kind is AsmToken.symbol:
# TODO: Treating symbols as identifiers is weird, but it works for now.
yield IdentifierNode(location.text, location)
elif kind is AsmToken.number:
try:
yield parse_number(location)
except ValueError as ex:
reader.error("%s", ex, location=location)
elif kind is AsmToken.string:
# Arbitrary strings are not allowed as instruction
# operands, but single characters should be replaced
# by their character numbers.
value = location.text
assert len(value) >= 2, value
assert value[0] == value[-1], value
if len(value) == 2:
reader.error("empty string in instruction operand", location=location)
elif len(value) == 3:
yield NumberNode(ord(value[1]), 8, location)
else:
reader.error(
"multi-character string in instruction operand",
location=location,
)
elif kind is AsmToken.comment:
pass
else:
assert False, kind
def build_instruction(tokens: Tokenizer[AsmToken], reader: LineReader) -> None:
name = tokens.location
try:
with reader.checkErrors():
match_seq = tuple(create_match_sequence(parse_instruction(tokens, reader)))
except DelayedError:
return
reader.info(
"instruction %s", " ".join(str(elem) for elem in match_seq), location=name
)
def parse_value(tokens: Tokenizer[AsmToken]) -> Expression:
if (location := tokens.eat(AsmToken.number)) is not None:
number = parse_number(location)
return IntLiteral(number.value)
elif (location := tokens.eat(AsmToken.word)) is not None:
# We don't know at this stage whether a symbol is a label or a constant,
# so assume the width is unlimited.
return SymbolValue(location.text, unlimited)
elif tokens.end:
raise ParseError("missing value", tokens.location)
else:
# TODO: Implement.
raise ParseError.withText(
"unexpected token; expression parsing not implemented yet", tokens.location
)
_data_widths = {
"db": 8,
"defb": 8,
"dw": 16,
"defw": 16,
"dd": 32,
"defd": 32,
"dq": 64,
"defq": 64,
}
def parse_directive(
tokens: Tokenizer[AsmToken], instr_set: InstructionSet
) -> DataDirective | OriginDirective | StringDirective:
# TODO: It would be good to store the expression locations, so we can print
# a proper error report if we later discover the value is bad.
name = tokens.eat(AsmToken.word)
assert name is not None
keyword = name.text.casefold()
if (width := _data_widths.get(keyword)) is not None:
data_type = IntType.u(width)
data_class: type[DataDirective | StringDirective] = DataDirective
data: list[FixedValueReference | bytes] = []
while True:
if (location := tokens.eat(AsmToken.string)) is not None:
if width != 8:
raise ParseError(
f'the "{keyword}" directive does not support string literals',
location,
)
data_class = StringDirective
text = location.text
assert text[0] == text[-1], text
# TODO: Support other encodings?
try:
data.append(text[1:-1].encode("ascii"))
except UnicodeError as ex:
raise ParseError(
f"string literal is not pure ASCII: {ex}", location
) from None
else:
value = parse_value(tokens)
# TODO: I don't like the use of truncation here, since it might silence
# errors.
# One alternative would be to add an expression node that performs
# a range check. Perhaps this could also store the location (see
# TODO at the top of this function).
# Another alternative would be to not use FixedValueReference for
# storing the values. Instead, we could store expressions (ignore
# width, since it's implied by the directive) or we could store
# ASTs (preserves more of the original code when reformatting).
data.append(FixedValueReference(truncate(value, width), data_type))
if tokens.end:
break
if tokens.eat(AsmToken.symbol, ",") is None:
raise ParseError.withText(
"unexpected token after value", tokens.location
)
return data_class(*data) # type: ignore[arg-type]
elif keyword == "org":
addr = parse_value(tokens)
if tokens.end:
return OriginDirective(FixedValueReference(addr, instr_set.addrType))
else:
raise ParseError.withText("unexpected token after value", tokens.location)
else:
raise ParseError.withText(
"statement is not a known instruction or directive", name
)
def parse_label(tokens: Tokenizer[AsmToken]) -> InputLocation | None:
"""Consume and return a label if one is defined at the start of this line."""
lookahead = tokens.copy()
label = lookahead.eat(AsmToken.word)
if label is None:
return None
elif lookahead.peek(AsmToken.symbol, ":"):
# Explicit label declaration.
tokens.eat(AsmToken.word)
tokens.eat(AsmToken.symbol)
return label
elif lookahead.peek(AsmToken.word) and tokens.value.lower() == "equ":
# EQU directive.
tokens.eat(AsmToken.word)
return label
else:
return None
def parse_asm(reader: LineReader, instr_set: InstructionSet) -> None:
instruction_names = instr_set.instructionNames
for line in reader:
tokens = AsmToken.scan(line)
# Look for a label.
label = parse_label(tokens)
if label is not None:
reader.info("label: %s", label.text, location=label)
# Look for a directive or instruction.
if tokens.peek(AsmToken.word):
if tokens.value.casefold() in instruction_names:
build_instruction(tokens, reader)
else:
location = tokens.location
try:
directive = parse_directive(tokens, instr_set)
except ParseError as ex:
reader.error("%s", ex, location=ex.locations)
else:
reader.info("directive: %s", directive, location=location)
elif tokens.eat(AsmToken.comment) is not None:
assert tokens.end, tokens.kind
elif not tokens.end:
reader.error(
"expected directive or instruction, got %s",
tokens.kind.name,
location=tokens.location,
)
def read_source(path: Path, instr_set: InstructionSet) -> None:
with LineReader.open(path, logger) as reader:
with reader.checkErrors():
parse_asm(reader, instr_set)
reader.summarize()
| 36.402214 | 88 | 0.597567 |
bd3a0d0c2b71afda19f90c92c54c25c94c187e0e | 744 | py | Python | kubernetes_engine/django_tutorial/mysite/wsgi.py | yshalabi/python-docs-samples | 591787c01d94102ba9205f998d95a05b39ccad2f | [
"Apache-2.0"
] | 5,938 | 2015-05-18T05:04:37.000Z | 2022-03-31T20:16:39.000Z | kubernetes_engine/django_tutorial/mysite/wsgi.py | yshalabi/python-docs-samples | 591787c01d94102ba9205f998d95a05b39ccad2f | [
"Apache-2.0"
] | 4,730 | 2015-05-07T19:00:38.000Z | 2022-03-31T21:59:41.000Z | kubernetes_engine/django_tutorial/mysite/wsgi.py | yshalabi/python-docs-samples | 591787c01d94102ba9205f998d95a05b39ccad2f | [
"Apache-2.0"
] | 6,734 | 2015-05-05T17:06:20.000Z | 2022-03-31T12:02:51.000Z | # Copyright 2015 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.
import os
from django.core.wsgi import get_wsgi_application
os.environ.setdefault("DJANGO_SETTINGS_MODULE", "mysite.settings")
application = get_wsgi_application()
| 32.347826 | 74 | 0.774194 |
df82a27c999d633f6a723a63f73f2a48e8f853e1 | 9,121 | py | Python | libs/sdc_etl_libs/api_helpers/apis/Ultipro/UltiproServices.py | darknegma/docker-airflow | 44e3d02d7ac43c8876145ae47acfbbbde67230df | [
"Apache-2.0"
] | null | null | null | libs/sdc_etl_libs/api_helpers/apis/Ultipro/UltiproServices.py | darknegma/docker-airflow | 44e3d02d7ac43c8876145ae47acfbbbde67230df | [
"Apache-2.0"
] | 3 | 2021-03-31T19:26:57.000Z | 2021-12-13T20:33:01.000Z | libs/sdc_etl_libs/api_helpers/apis/Ultipro/UltiproServices.py | darknegma/docker-airflow | 44e3d02d7ac43c8876145ae47acfbbbde67230df | [
"Apache-2.0"
] | null | null | null |
import datetime
import decimal
import json
import logging
import zeep
from sdc_etl_libs.api_helpers.apis.Ultipro.Ultipro import Ultipro
from sdc_etl_libs.sdc_dataframe.Dataframe import Dataframe, SDCDFTypes
from sdc_etl_libs.sdc_file_helpers.SDCFileHelpers import SDCFileHelpers
logging.basicConfig(level=logging.INFO)
class UltiproServices(Ultipro):
def __init__(self):
super().__init__()
def convert_to_literals(self, dict_):
"""
Recursively travels a data set dictionary - at both the dictionary
and list level - and converts Decimal() objects to literal floats and
datetime.datetimes objects to literal datetime strings.
:param dict_: Dictionary to evaluate.
:return: None
"""
for key, value in dict_.items():
if isinstance(value, dict):
self.convert_to_literals(value)
elif isinstance(value, list):
for num, item in enumerate(value):
if isinstance(item, dict):
self.convert_to_literals(item)
else:
if isinstance(value, decimal.Decimal):
dict_[key] = float(value)
elif isinstance(value, datetime.datetime):
dict_[key] = value.strftime('%Y-%m-%d %H:%M:%S')
def get_service(self, service_name_):
"""
Given an endpoint, creaetes the Zeep client, authenticates and returns
the service function for use.
:param service_name_: Ultipro SOAP service name.
:return: Zeep client service for Ultipro endpoint.
"""
if service_name_ == 'FindCompensations':
endpoint = 'EmployeeCompensation'
zeep_client = zeep.Client(f"{self.base_url}{endpoint}")
service = zeep_client.service.FindCompensations
elif service_name_ == 'EmployeeEmploymentInformation':
endpoint = "EmployeeEmploymentInformation"
zeep_client = zeep.Client(f"{self.base_url}{endpoint}")
service = zeep_client.service.FindEmploymentInformations
elif service_name_ == 'FindLastPayStatement':
endpoint = "EmployeePayStatement"
zeep_client = zeep.Client(f"{self.base_url}{endpoint}")
service = zeep_client.service.FindLastPayStatement
else:
raise Exception(f"{service_name_} is no currently supported.")
self.soap_authenticate()
return service, endpoint, zeep_client
def process_endpoint(self, service_name_, query_=None, limit_=None):
"""
Processes an Ultipro SOAP endpoint.
:param service_name_: Ultipro SOAP service name.
:param query_: SOAP query as a dictionary.
:param limit_: Page results limit.
:return: Results as Zeep array object
"""
results = []
if query_ == None:
query_ = {}
elif query_ and not isinstance(query_, dict):
raise Exception("Query for Ultipro SOAP must be in dictionary format.")
# Paginate by updating the query in with a new PageNumber. The current_page
# and total_pages are evaluated to determine if we got every page. To start,
# set current_page to 1 and total_pages to 2 (to ensure the first call is made).
# The first call will update to the correct total_pages.
query_["PageNumber"] = "1"
query_["PageSize"] = limit_
current_page = 1
total_pages = 2
service, endpoint, zeep_client = self.get_service(service_name_)
while current_page < total_pages:
response = service(_soapheaders=[self.session_header], query=query_)
if response["OperationResult"]["Success"] == True:
total_pages = int(
response["OperationResult"]["PagingInfo"]["PageTotal"])
current_page = int(
response["OperationResult"]["PagingInfo"]["CurrentPage"])
records = response["Results"][endpoint]
if current_page == 1:
logging.info(f"Total pages: {total_pages}.")
results.extend(records)
logging.info(f'Grabbed {query_["PageSize"]} record(s) from Page #{current_page}.')
query_["PageNumber"] = \
str(int(response["OperationResult"]["PagingInfo"][
"CurrentPage"]) + 1)
else:
msg = response["OperationResult"]["Messages"]
raise Exception(f"Grabbing from {endpoint} failed. {msg}")
return results
def convert_zeep_result_to_dict(self, data_):
"""
Converts a Ultipro Services Zeep array object to a list of flattened
dictionaries.
:param data_: Ultipro Services Zeep array to process.
:return: List of flattened dictionaries.
"""
data = []
for result in data_:
empId = dict(zeep.helpers.serialize_object(result, target_cls=dict))
empInfo = dict(empId.popitem()[1]).popitem()[1]
for item in empInfo:
item.update(empId)
data.append(item)
return data
def get_employee_employement_information(self, query_=None, limit_=500):
"""
Processes Ultipro SOAP Employee Employment Information endpoint results.
https://connect.ultipro.com/documentation#/api/1168
:param query_: SOAP query as a dictionary.
:param limit_: Page results limit.
:return: SDCDataFrame object with data in dataframe.
"""
file_name = SDCFileHelpers.get_file_path(
"schema", "Ultipro/services/employee-employment-information.json")
json_data = json.loads(open(file_name).read())
if "data_source" in json_data and json_data["data_source"][
"type"] == "api": self.base_url = json_data["data_source"]["base_url"]
else:
raise Exception("Missing data_source metadata in schema definition.")
df = Dataframe(SDCDFTypes.PANDAS, json_data)
results = self.process_endpoint('EmployeeEmploymentInformation',
query_=query_, limit_=limit_)
data = self.convert_zeep_result_to_dict(results)
if len(data) >= 1:
df.load_data(data)
return df
else:
logging.warning("Received no data")
return None
def get_employee_compensation(self, query_=None, limit_=500):
"""
Processes Ultipro SOAP Employee Compensation endpoint results.
https://connect.ultipro.com/documentation#/api/1144
:param query_: SOAP query as a dictionary.
:param limit_: Page results limit.
:return: SDCDataFrame object with data in dataframe.
"""
file_name = SDCFileHelpers.get_file_path(
"schema", "Ultipro/services/employee-compensation.json")
json_data = json.loads(open(file_name).read())
if "data_source" in json_data and json_data["data_source"][
"type"] == "api":
self.base_url = json_data["data_source"]["base_url"]
else:
raise Exception("Missing data_source metadata in schema definition.")
df = Dataframe(SDCDFTypes.PANDAS, json_data)
results = self.process_endpoint('FindCompensations', query_=query_,
limit_=limit_)
data = self.convert_zeep_result_to_dict(results)
if len(data) >= 1:
df.load_data(data)
return df
else:
logging.warning("Received no data")
return None
def get_employee_latest_pay_statement(self, query_=None, limit_=1000):
"""
Processes Ultipro SOAP Employee Pay Statement endpoint results. Pulls
the most recent pay statement for each Employee in system.
https://connect.ultipro.com/documentation#/api/1150
:param query_: SOAP query as a dictionary.
:param limit_: Page results limit.
:return: SDCDataFrame object with data in dataframe.
"""
file_name = SDCFileHelpers.get_file_path(
"schema", "Ultipro/services/employee-pay-statement.json")
json_data = json.loads(open(file_name).read())
if "data_source" in json_data and json_data["data_source"]["type"] == "api":
self.base_url = json_data["data_source"]["base_url"]
else:
raise Exception("Missing data_source metadata in schema definition.")
df = Dataframe(SDCDFTypes.PANDAS, json_data)
results = self.process_endpoint('FindLastPayStatement', query_=query_,
limit_=limit_)
data = self.convert_zeep_result_to_dict(results)
for i in data:
self.convert_to_literals(i)
if len(data) >= 1:
df.load_data(data)
df.drop_columns(["SSN"])
return df
else:
logging.warning("Received no data")
return None
| 36.484 | 98 | 0.612871 |
1e2d427612b4edf234eaddeb1d90644a8def46ea | 9,653 | py | Python | vcx/wrappers/python3/demo/vcxdemo.py | dastardlychimp/indy-sdk | febdc881ccfba7a0b1b19e1c2c985142ff147548 | [
"Apache-2.0"
] | null | null | null | vcx/wrappers/python3/demo/vcxdemo.py | dastardlychimp/indy-sdk | febdc881ccfba7a0b1b19e1c2c985142ff147548 | [
"Apache-2.0"
] | 2 | 2018-09-13T20:07:09.000Z | 2021-12-29T20:52:05.000Z | vcx/wrappers/python3/demo/vcxdemo.py | dastardlychimp/indy-sdk | febdc881ccfba7a0b1b19e1c2c985142ff147548 | [
"Apache-2.0"
] | 1 | 2021-08-16T23:07:17.000Z | 2021-08-16T23:07:17.000Z | from vcx.api.connection import Connection
from demo.wait import wait_for_state
from demo.vcxbase import VCXBase
import json
import asyncio
from vcx.state import State
from vcx.api.issuer_credential import IssuerCredential
from vcx.api.schema import Schema
from vcx.api.credential_def import CredentialDef
from vcx.api.proof import Proof
import qrcode
ENTERPRISE_DID = '2hoqvcwupRTUNkXn6ArYzs'
class Vcxdemo(VCXBase):
proof_requests = {}
schemas = []
credential_defs = {}
did = ENTERPRISE_DID
def __init__(self, source_id, details=None, phone_number='8888675309'):
self.source_id = source_id
self.details = details
self.state = {}
self.state['connection'] = State.Undefined
self.state['credential'] = State.Undefined
self.loop = Vcxdemo.get_loop()
self.connection = None
self.credential = None
self.phone_number = phone_number
self.invite_details = None
@classmethod
def set_did(cls, did):
cls.did = did
@classmethod
def get_did(cls):
return cls.did
def create_qr_code(self, dest):
img = qrcode.make(str(json.dumps(self.invite_details)))
img.save(dest)
async def _wait_for_credential_state(self, target_state):
self.state['credential'] = await self.credential.update_state()
while self.state['credential'] != target_state:
print('waiting for credential to be [%s]...\ncurrent %s' % (target_state, self.state['credential']))
await asyncio.sleep(5)
self.state['credential'] = await self.credential.update_state()
print('Successful state change for credential to be [%s]...\ncurrent %s' % (target_state, self.state['credential']))
async def create_and_connect(self):
self.connection = await Connection.create(self.source_id)
self.state['connection'] = await self.connection.get_state()
await self.connection.connect(self.phone_number)
self.invite_details = await self.connection.invite_details(True)
print('\n %s \n' % str(json.dumps(self.invite_details)))
self.create_qr_code('./qrcode1.png')
self.state['connection'] = await self.wait_for_connection_state(State.Accepted)
def connect(self):
self.loop.run_until_complete(asyncio.gather(self.create_and_connect()))
def create_credential(self, schema_seq_number, attr, credential_name):
self.loop.run_until_complete(asyncio.gather(self._create_credential(schema_seq_number, attr, credential_name)))
async def _create_credential(self, schema_seq_number, attr, credential_name):
self.credential = await IssuerCredential.create(self.source_id,
attr,
schema_seq_number,
credential_name)
def request_proof(self, proof_id):
proof = self.get_proof_request(proof_id)
res = Vcxdemo.get_loop().run_until_complete(proof.request_proof(self.connection))
async def _serialize_connection(self):
return await self.connection.serialize()
def serialize_connection(self):
res = self.loop.run_until_complete(asyncio.gather(self._serialize_connection()))
if len(res) > 0:
return res[0]
async def _serialize_credential(self):
return await self.credential.serialize()
def serialize_credential(self):
res = self.loop.run_until_complete(asyncio.gather(self._serialize_credential()))
if len(res) > 0:
return res[0]
async def _deserialize_connection(self, data):
self.connection = await Connection.deserialize(data)
async def _deserialize_credential(self, data):
self.credential = await IssuerCredential.deserialize(data)
def deserialize_connection(self, filename):
try:
with open(filename) as in_file:
res = self.loop.run_until_complete(asyncio.gather(self._deserialize_connection(json.load(in_file))))
except IOError as e:
print("Error opening file %s: %s" % (filename, e))
def deserialize_credential(self,filename):
try:
with open(filename) as in_file:
res = self.loop.run_until_complete(asyncio.gather(self._deserialize_credential(json.load(in_file))))
except IOError as e:
print("Error opening file %s: %s" % (filename, e))
async def _update_credential_state(self):
self.state['credential'] = await self.credential.update_state()
async def _update_proof_state(self, proof_id):
await self.get_proof_request(proof_id).update_state()
async def _get_proof_state(self, proof_id):
return await self.get_proof_request(proof_id).get_state()
def update_proof_state(self, proof_id):
Vcxdemo.get_loop().run_until_complete(asyncio.gather(self._update_proof_state(proof_id)))
def get_proof_state(self, proof_id):
res = Vcxdemo.get_loop().run_until_complete(asyncio.gather(self._get_proof_state(proof_id)))
return res[0]
def update_credential_state(self):
res = self.loop.run_until_complete(asyncio.gather(self._update_credential_state()))
if len(res) > 0:
return res[0]
async def _send_offer(self):
await self.credential.send_offer(self.connection)
await self.credential.update_state()
self.state['credential'] = await self.credential.get_state()
def issue_credential_offer(self):
res = self.loop.run_until_complete(asyncio.gather(self._send_offer()))
if len(res) > 0:
return res[0]
async def _send_issuer_credential(self):
await self.credential.send_credential(self.connection)
await self.credential.update_state()
def send_issuer_credential(self):
res = self.loop.run_until_complete(asyncio.gather(self._send_issuer_credential()))
if len(res) > 0:
return res[0]
@classmethod
def create_schema(cls, source_id: str, name: str, attr: dict):
res = Vcxdemo.get_loop().run_until_complete(asyncio.gather(Vcxdemo._create_schema(source_id, name, attr)))
print(res[0])
cls.schemas.append(res[0])
@classmethod
def get_schema(cls, index):
return cls.schemas[index]
@classmethod
def serialize_schema(cls, schema_number):
res = Vcxdemo.get_loop().run_until_complete(asyncio.gather(
cls._serialize_schema(cls.schemas[schema_number])))
if len(res) > 0:
return res[0]
@classmethod
def get_schema_sequence_number(cls, index):
res = Vcxdemo.get_loop().run_until_complete(asyncio.gather(cls.schemas[index].get_sequence_number()))
return res[0]
@classmethod
def deserialize_schema(cls, filename):
try:
with open(filename, 'r') as in_file:
data = json.load(in_file)
res = Vcxdemo.get_loop().run_until_complete(asyncio.gather(Schema.deserialize(data)))
cls.schemas.append(res[0])
except IOError as e:
print('Error opening %s: %s', (filename, e))
@classmethod
def create_credential_def(cls, source_id, name, schema_number, revocation=False):
cls.credential_defs[name] = Vcxdemo.get_loop().run_until_complete(CredentialDef.create(source_id, name, schema_number, revocation))
def create_proof_request(self, source_id, name, proof_attr):
res = Vcxdemo.get_loop().run_until_complete(asyncio.gather(Proof.create(source_id, name, proof_attr)))
if len(res) > 0:
self.proof_requests[source_id] = res[0]
def get_proof_request(self, source_id):
return self.proof_requests[source_id]
@classmethod
def get_schema_attr_list(cls, index):
return cls.schemas[index].attrs
async def _wait_for_proof_state(self, proof_id, target_state):
proof = self.get_proof_request(proof_id)
state = await proof.get_state()
while state != target_state:
print('waiting for Proof Request %s to be [%s]...\ncurrent %s' % (proof_id, target_state, state))
await asyncio.sleep(5)
await proof.update_state()
state = await proof.get_state()
print('Successful state change for Proof Request %s to [%s]...\ncurrent %s' % (proof_id, target_state, state))
async def wait_for_connection_state(self, target_state):
await self.connection.update_state()
state = await self.connection.get_state()
while state != target_state:
print('waiting for connection to be accepted...\ncurrent %s' % state)
await asyncio.sleep(5)
await self.connection.update_state()
state = await self.connection.get_state()
return state
def wait_for_credential_state(self, target_state):
self.loop.run_until_complete(asyncio.gather(self._wait_for_credential_state(target_state)))
def wait_for_proof_state(self, proof_id, target_state):
proof = self.get_proof_request(proof_id)
Vcxdemo.get_loop().run_until_complete(asyncio.gather(self._wait_for_proof_state(proof_id, target_state)))
# Vcxdemo.get_loop().run_until_complete(asyncio.gather(wait_for_state(proof, target_state)))
def retrieve_proof(self, proof_id):
proof = self.get_proof_request(proof_id)
res = Vcxdemo.get_loop().run_until_complete(asyncio.gather(proof.get_proof(self.connection)))
print(res[0])
if len(res) > 0:
return res[0]
else:
return None
| 39.88843 | 139 | 0.673469 |
7f56bbf8631758a7a2a0a36430ae46dd483f58fc | 61,876 | py | Python | src/sage/symbolic/units.py | bopopescu/classic_diff_geom | 2b1d88becbc8cb30962e0995cc78e429e0f5589f | [
"BSL-1.0"
] | null | null | null | src/sage/symbolic/units.py | bopopescu/classic_diff_geom | 2b1d88becbc8cb30962e0995cc78e429e0f5589f | [
"BSL-1.0"
] | null | null | null | src/sage/symbolic/units.py | bopopescu/classic_diff_geom | 2b1d88becbc8cb30962e0995cc78e429e0f5589f | [
"BSL-1.0"
] | 1 | 2020-07-24T12:08:30.000Z | 2020-07-24T12:08:30.000Z | """
Units of measurement
This is the units package. It contains information about many units
and conversions between them.
TUTORIAL:
To return a unit::
sage: units.length.meter
meter
This unit acts exactly like a symbolic variable::
sage: s = units.length.meter
sage: s^2
meter^2
sage: s + var('x')
meter + x
Units have additional information in their docstring::
sage: # You would type: units.force.dyne?
sage: print units.force.dyne._sage_doc_()
CGS unit for force defined to be gram*centimeter/second^2.
Equal to 10^-5 newtons.
You may call the convert function with units::
sage: t = units.mass.gram*units.length.centimeter/units.time.second^2
sage: t.convert(units.mass.pound*units.length.foot/units.time.hour^2)
5400000000000/5760623099*(foot*pound/hour^2)
sage: t.convert(units.force.newton)
1/100000*newton
Calling the convert function with no target returns base SI units::
sage: t.convert()
1/100000*kilogram*meter/second^2
Giving improper units to convert to raises a ValueError::
sage: t.convert(units.charge.coulomb)
Traceback (most recent call last):
...
ValueError: Incompatible units
Converting temperatures works as well::
sage: s = 68*units.temperature.fahrenheit
sage: s.convert(units.temperature.celsius)
20*celsius
sage: s.convert()
293.150000000000*kelvin
Trying to multiply temperatures by another unit then converting raises a ValueError::
sage: wrong = 50*units.temperature.celsius*units.length.foot
sage: wrong.convert()
Traceback (most recent call last):
...
ValueError: Cannot convert
TESTS:
Check that Trac 12373 if fixed::
sage: b = units.amount_of_substance.mole
sage: b.convert(units.amount_of_substance.elementary_entity)
6.02214129000000e23*elementary_entity
AUTHORS:
- David Ackerman
- William Stein
"""
###############################################################################
# Sage: Open Source Mathematical Software
# Copyright (C) 2009 David Ackerman <davidnackerman@gmail.com>
# William Stein <wstein@gmail.com>
# Distributed under the terms of the GNU General Public License (GPL),
# version 2 or any later version. The full text of the GPL is available at:
# http://www.gnu.org/licenses/
###############################################################################
# standard Python libraries
import re
# Sage library
from ring import SR
from expression import Expression
###############################################################################
# Unit conversions dictionary.
###############################################################################
unitdict = {
'acceleration':
{'gal':'1/100',
'galileo':'1/100',
'gravity':'9.80665000000000'},
'amount_of_substance':
{'elementary_entity':'1/6.02214129000000e23',
'mole':'1'},
'angles':
{'arc_minute':'1/10800*pi',
'arc_second':'1/648000*pi',
'degree':'1/180*pi',
'grade':'1/200*pi',
'quadrant':'1/2*pi',
'radian':'1',
'right_angle':'1/2*pi'},
'area':
{'acre':'316160658/78125',
'are':'100',
'barn':'1/10000000000000000000000000000',
'hectare':'10000',
'rood':'158080329/156250',
'section':'40468564224/15625',
'square_chain':'158080329/390625',
'square_meter':'1',
'township':'1456868312064/15625'},
'capacitance':
{'abfarad':'1000000000',
'farad':'1',
'statfarad':'25000/22468879468420441'},
'charge':
{'abcoulomb':'10',
'coulomb':'1',
'elementary_charge':'1.60217646200000e-19',
'faraday':'96485.3399000000',
'franklin':'1/2997924580',
'statcoulomb':'1/2997924580'},
'conductance':
{'abmho':'1000000000',
'mho':'1',
'siemens':'1'},
'current':
{'abampere':'10',
'amp':'1',
'ampere':'1',
'biot':'10',
'statampere':'1/2997924580'},
'electric_potential':
{'abvolt':'1/100000000',
'statvolt':'149896229/500000',
'volt':'1'},
'energy':
{'british_thermal_unit':'52752792631/50000000',
'btu':'52752792631/50000000',
'calorie':'10467/2500',
'electron_volt':'1.60217733000000e-19',
'erg':'1/10000000',
'ev':'1.60217733000000e-19',
'joule':'1',
'rydberg':'2.17987200000000e-18',
'therm':'52752792631/500'},
'fiber_linear_mass_density':
{'denier':'1/9000000',
'tex':'1/1000000'},
'force':
{'dyne':'1/100000',
'gram_weight':'196133/20000000',
'kilogram_force':'196133/20000',
'kilogram_weight':'196133/20000',
'newton':'1',
'pound_force':'8896443230521/2000000000000',
'pound_weight':'8896443230521/2000000000000',
'poundal':'17281869297/125000000000',
'ton_force':'8896443230521/1000000000'},
'frequency':
{'1/second':'1',
'hertz':'1'},
'illuminance':
{'foot_candle':'1562500/145161',
'lux':'1',
'phot':'10000'},
'inductance':
{'abhenry':'1/1000000000',
'henry':'1',
'stathenry':'22468879468420441/25000'},
'information':
{'bit':'1',
'byte':'8',
'nibble':'4'},
'information_rate':
{'baud':'1'},
'inverse_length':
{'diopter':'1',
'kayser':'100'},
'length':
{'angstrom':'1/10000000000',
'astronomical_unit':'149597870691',
'bolt':'4572/125',
'cable_international':'926/5',
'cable_us':'27432/125',
'caliber':'127/500000',
'centimeter':'1/100',
'chain':'12573/625',
'cicero':'125/27706',
'cubit':'1143/2500',
'didot':'125/332472',
'dtp_point':'127/360000',
'ell':'1143/1000',
'fathom':'1143/625',
'feet':'381/1250',
'fermi':'1/1000000000000000',
'foot':'381/1250',
'furlong':'25146/125',
'hand':'127/1250',
'inch':'127/5000',
'kilometer':'1000',
'league':'603504/125',
'light_year':'9460730472580800',
'link':'12573/62500',
'meter':'1',
'micron':'1/1000000',
'mil':'127/5000000',
'millimeter':'1/1000',
'mile':'201168/125',
'nautical_mile':'1852',
'parsec':'3.08570000000000e16',
'perch':'12573/2500',
'pica':'127/30000',
'pole':'12573/2500',
'rod':'12573/2500',
'rope':'762/125',
'skein':'13716/125',
'stadion':'118491/625',
'stadium':'115443/625',
'statute_mile':'201168/125',
'survey_foot':'1200/3937',
'survey_mile':'6336000/3937',
'x_unit':'1.00210000000000e-13',
'yard':'1143/1250'},
'luminance':
{'apostilb':'1/pi',
'lambert':'10000/pi',
'nit':'1',
'stilb':'10000'},
'luminous_energy':
{'lumerg':'1',
'talbot':'1'},
'luminous_flux':
{'lumen':'1'},
'luminous_intensity':
{'candela':'1',
'candle':'1',
'hefnerkerze':'1019/1128'},
'magnetic_field':
{'gauss':'1/10000',
'tesla':'1'},
'magnetic_flux':
{'maxwell':'1/100000000',
'weber':'1'},
'magnetic_intensity':
{'oersted':'250/pi'},
'magnetic_moment':
{'bohr_magneton':'9.27400915000000e-24',
'nuclear_magneton':'5.05078324000000e-27'},
'magnetomotive_force':
{'ampere_turn':'1',
'gilbert':'5/2/pi'},
'mass':
{'amu':'1.66053878200000e-27',
'assay_ton':'7/240',
'atomic_mass_unit':'1.66053878200000e-27',
'avoirdupois_ounce':'45359237/1600000000',
'avoirdupois_pound':'45359237/100000000',
'bale':'45359237/200000',
'carat':'1/5000',
'cental':'45359237/1000000',
'dalton':'1.66053878200000e-27',
'drachma':"(0.00429234000000000, {'greek':1})",
'geepound':'14593903/1000000',
'grain':'6479891/100000000000',
'gram':'1/1000',
'gross_hundredweight':'317514659/6250000',
'hundredweight':'317514659/6250000',
'kilogram':'1',
'libra':'0.325971000000000',
'long_ton':'317514659/312500',
'metric_ton':'1000',
'mina':"(0.429234000000000, {'greek':100})",
'net_hundredweight':'45359237/1000000',
'obol':"(0.000715380000000000,{'greek':1/6})",
'ounce':'45359237/1600000000',
'ounce_troy':'19439673/625000000',
'pennyweight':'19439673/12500000000',
'pondus':'0.325969000000000',
'pound':'45359237/100000000',
'pound_troy':'58319019/156250000',
'quintal':'100',
'shekel':'0.0141000000000000',
'short_hundredweight':'45359237/1000000',
'short_ton':'45359237/50000',
'slug':'14593903/1000000',
'solar_mass':'1.98892000000000e30',
'stone':'317514659/50000000',
'talent':"(25.7540400000000, {'greek':6000})",
'ton':'45359237/50000',
'tonne':'1000',
'wey':'2857631931/25000000'},
'power':
{'cheval_vapeur':'588399/800',
'horsepower':'37284993579113511/50000000000000',
'watt':'1'},
'pressure':
{'atmosphere':'101325',
'bar':'100000',
'barye':'1/10',
'inch_mercury':'3386.38900000000',
'millimeter_mercury':'133.322400000000',
'mmhg':'133.322400000000',
'pa':'1',
'pascal':'1',
'pounds_per_square_inch':'8896443230521/1290320000',
'psi':'8896443230521/1290320000',
'torr':'20265/152'},
'radiation':
{'becquerel':'1',
'curie':'37000000000',
'rutherford':'1000000'},
'radiation_absorbed':
{'gray':'1',
'rad':'1/100'},
'radiation_ionizing':
{'roentgen':'0.000258000000000000',
'rontgen':'0.000258000000000000'},
'resistance':
{'abohm':'1/1000000000',
'ohm':'1',
'statohm':'22468879468420441/25000'},
'si_prefixes':
{'atto':'1/1000000000000000000',
'centi':'1/100',
'deca':'10',
'deci':'1/10',
'exa':'1000000000000000000',
'femto':'1/1000000000000000',
'giga':'1000000000',
'hecto':'100',
'kilo':'1000',
'mega':'1000000',
'micro':'1/1000000',
'milli':'1/1000',
'nano':'1/1000000000',
'peta':'1000000000000000',
'pico':'1/1000000000000',
'tera':'1000000000000',
'yocto':'1/1000000000000000000000000',
'yotta':'1000000000000000000000000',
'zepto':'1/1000000000000000000000',
'zetta':'1000000000000000000000'},
'solid_angle':
{'steradian':'1'},
'temperature':
{'celsius':'(x + 273.15), (x), (x*9/5 + 32), ((x+273.15)*9/5)',
'centigrade':'(x + 273.15), (x), (x*9/5 + 32), ((x+273.15)*9/5)',
'fahrenheit':'(5/9*(x + 459.67)), ((x - 32)*5/9), (x), (x+459.67)',
'kelvin':'(x), (x - 273.15), (x*9/5 - 459.67), (x*9/5)',
'rankine':'(5/9*x), ((x-491.67)*5/9), (x-459.67), (x)'},
'time':
{'century':'3153600000',
'day':'86400',
'decade':'315360000',
'fortnight':'1209600',
'hour':'3600',
'millenium':'31536000000',
'minute':'60',
'month':'2628000',
'second':'1',
'sidereal_day':"(86164.0905308330, {'sidereal':86400})",
'sidereal_second':"(0.997269566329086, {'sidereal':1})",
'sidereal_year':'3.15581497632000e7',
'tropical_year':'3.15569251779840e7',
'week':'604800',
'year':'31536000'},
'unit_multipliers':
{'bakers_dozen':'13',
'dozen':'12',
'gross':'144',
'percent':'1/100'},
'velocity':
{'knot':'463/900'},
'viscosity_absolute':
{'poise':'1/10',
'reyn':'8896443230521/1290320000'},
'viscosity_kinematic':
{'stokes':'1/10000'},
'viscosity_other':
{'rhes':'10'},
'volume':
{'bag':'660732565629/6250000000000',
'barrel':'9936705933/62500000000',
'board_foot':'18435447/7812500000',
'bucket':'473176473/31250000000',
'bushel':'220244188543/6250000000000',
'butt':'29810117799/62500000000',
'cord':'884901456/244140625',
'cubic_meter':'1',
'cup':'473176473/2000000000000',
'ephah':'1982197696887/50000000000000',
'fifth':'473176473/625000000000',
'firkin':'4091481/100000000',
'fluid_dram':'473176473/128000000000000',
'fluid_ounce':'473176473/16000000000000',
'gallon':'473176473/125000000000',
'gill':'473176473/4000000000000',
'hogshead':'29810117799/125000000000',
'imperial_gallon':'454609/100000000',
'imperial_pint':'454609/800000000',
'jeroboam':'473176473/156250000000',
'jigger':'1419529419/32000000000000',
'liter':'1/1000',
'magnum':'473176473/250000000000',
'minim':'157725491/2560000000000000',
'noggin':'473176473/4000000000000',
'omer':'1982197696887/500000000000000',
'peck':'220244188543/25000000000000',
'pint':'473176473/1000000000000',
'pony':'1419529419/64000000000000',
'puncheon':'9936705933/31250000000',
'quart':'473176473/500000000000',
'register_ton':'55306341/19531250',
'seam':'220244188543/781250000000',
'shot':'473176473/16000000000000',
'stere':'1',
'tablespoon':'473176473/32000000000000',
'teaspoon':'157725491/32000000000000',
'tun':'29810117799/31250000000',
'uk_gallon':'454609/100000000',
'uk_pint':'454609/800000000',
'wine_bottle':'3/4000'}
}
unit_to_type = {}
value_to_unit = {}
def evalunitdict():
"""
Replace all the string values of the unitdict variable by their
evaluated forms, and builds some other tables for ease of use.
This function is mainly used internally, for efficiency (and
flexibility) purposes, making it easier to describe the units.
EXAMPLES::
sage: sage.symbolic.units.evalunitdict()
"""
from sage.misc.all import sage_eval
for key, value in unitdict.iteritems():
unitdict[key] = dict([(a,sage_eval(repr(b))) for a, b in value.iteritems()])
# FEATURE IDEA: create a function that would allow users to add
# new entries to the table without having to know anything about
# how the table is stored internally.
#
# Format the table for easier use.
#
for k, v in unitdict.iteritems():
for a in v: unit_to_type[a] = k
for w in unitdict.iterkeys():
for j in unitdict[w].iterkeys():
if isinstance(unitdict[w][j], tuple): unitdict[w][j] = unitdict[w][j][0]
value_to_unit[w] = dict(zip(unitdict[w].itervalues(), unitdict[w].iterkeys()))
###############################################################################
# Documentation for individual units.
# Appears in unit's docstring.
###############################################################################
unit_docs = {
'acceleration_docs':
{'gal':'Abbreviation for galileo.\nDefined to be 1/100 meter/second^2.',
'galileo':'Defined to be 1/100 meter/second^2.',
'gravity':'Also called standard gravity.\nPhysical constant defined to be 9.80665 meter/second^2.'},
'amount_of_substance_docs':
{'elementary_entity':'Defined to be one elementary unit of choice, usually atoms or other elementary particles.\nApproximately equal to 1.6605e-24 moles.',
'mole':'SI base unit of quantity.\nDefined to be the amount of substance that has an equal number of elementary entities as there are atoms in 12 grams of carbon-12.\nEquivalent to Avogadros constant elementary entities or approximately equal to 6.022*10^23 elementary entities.'},
'angles_docs':
{'arc_minute':'Defined to be 1/60 of a degree or pi/10800 radians.',
'arc_second':'Defined to be 1/3600 of a degree or pi/648000 radians.',
'degree':'Defined to be pi/180 radians.',
'grade':'Defined to be pi/200 radians.',
'quadrant':'Equivalent to a right angle.\nDefined to be pi/2 radians.',
'radian':'SI derived unit of angle.\nDefined to be the angle subtended at the center of a circle by an arc that is equal in length to the radius of the circle.',
'right_angle':'Equivalent to a quadrant.\nDefined to be pi/2 radians.'},
'area_docs':
{'acre':'Defined to be 10 square chains or 4840 square yards.\nApproximately equal to 4046.856 square meters.',
'are':'Defined to be 100 square meters.',
'barn':'Defined to be 100 square femtometers or 10^-28 square meters.',
'hectare':'Defined to be 10000 square meters.',
'rood':'Defined to be 1/4 of an acre.\nApproximately equal to 1011.714 square meters.',
'section':'Equivalent to a square mile.\nApproximately equal to 2.59*10^6 square meters.',
'square_chain':'Defined to be 4356 square feet.\nApproximately equal to 404.9856 square meters.',
'square_meter':'SI derived unit of area.\nDefined to be meter^2.',
'township':'Defined to be 36 square miles.\nApproximately equal to 9.324*10^7 square meters.'},
'capacitance_docs':
{'abfarad':'Defined to be 10^9 farads.',
'farad':'SI derived unit of capacitance.\nDefined to be the charge in coulombs a capacitor will accept for the potential across it to change one volt.\nEquivalent to coulomb/volt.',
'statfarad':'CGS unit defined to be statcoulomb/statvolt.\nApproximately equal to 1.11265*10^-12 farads.'},
'charge_docs':
{'abcoulomb':'CGS unit defined to be 10 coulombs.',
'coulomb':'SI derived unit of charge.\nDefined to be the amount of electric charge transported by 1 ampere in 1 second.',
'elementary_charge':'Defined to be the amount of electric charge carried by a single proton or negative charge carried by a single electron.\nApproximately equal to 1.602176462*10^-19 coulombs.',
'faraday':'Defined to be the magnitude of electric charge in one mole of electrons.\nApproximately equal to 96485.3399 coulombs.',
'franklin':'CGS unit defined to be the amount of electric charge necessary such that if two stationary objects placed one centimeter apart had one franklin of charge each they would repel each other with a force of one dyne.\nApproximately equal to 3.3356*10^-10 coulombs.',
'statcoulomb':'Equivalent to franklin.\nApproximately equal to 3.3356*10^-10 coulombs.'},
'conductance_docs':
{'abmho':'Defined to be 10^9 siemens.',
'mho':'Equivalent to siemens.',
'siemens':'SI derived unit of conductance.\nDefined to be an ampere per volt or 1/ohm.'},
'current_docs':
{'abampere':'CGS unit defined to be 10 amperes.',
'amp':'Abbreviation for ampere.',
'ampere':'SI base unit of current.\nDefined to be the constant current which will produce an attractive force of 2*10^-7 newtons per meter between two straight, parallel conductors of infinite length and negligible circular cross section placed one meter apart in free space.',
'biot':'Equivalent to abampere.\nEqual to 10 amperes.',
'statampere':'CGS unit defined to be statcoulomb/second.\nApproximately equal to 3.335641*10^-10 amperes.'},
'electric_potential_docs':
{'abvolt':'Defined to be 10^-8 volts.',
'statvolt':'CGS unit defined to be the speed of light in a vacuum/10^6 volts or approximately 299.792 volts.',
'volt':'SI derived unit of electric potential.\nDefined to be the value of voltage across a conductor when a current of one ampere dissipates one watt of power.'},
'energy_docs':
{'british_thermal_unit':'Defined to be the amount of energy required to raise the temperature of one pound of liquid water from 60 degrees Fahrenheit to 61 degrees Fahrenheit at a constant pressure of one atmosphere.\nApproximately equal to 1055.05585 joules.',
'btu':'Abbreviation for British thermal unit.\nApproximately equal to 1055.05585 joules.',
'calorie':'Defined to be the amount of energy required to raise the temperature of one gram of liquid water one degree Celsius.\nEqual to 4.1868 joules.',
'electron_volt':'Defined to be the amount of kinetic energy gained by a single unbound electron when it accelerates through an electrostatic potential difference of 1 volt.\nApproximately equal to 1.602*10^-19 joules.',
'erg':'CGS unit for energy defined to be gram*centimeter^2/second^2.\nEqual to 10^-7 joules.',
'ev':'Abbreviation for electron volt.\nApproximately equal to 1.602*10^-19 joules.',
'joule':'SI derived unit of energy.\nDefined to be kilogram*meter^2/second^2.',
'rydberg':'Defined to be the absolute value of the binding energy of the electron in the ground state hydrogen atom.\nApproximately equal to 2.17987*10^-18 joules.',
'therm':'Defined to be 100,000 British thermal units.\nApproximately equal to 1.05505585*10^8 joules.'},
'fiber_linear_mass_density_docs':
{'denier':'Defined to be 1 gram per 9000 meters.\nEqual to 1/9000000 of a kilogram/meter.',
'tex':'Defined to be 1 gram per 1000 meters.\nEqual to 1/1000000 of a kilogram/meter.'},
'force_docs':
{'dyne':'CGS unit for force defined to be gram*centimeter/second^2.\nEqual to 10^-5 newtons.',
'gram_weight':'Defined to be the magnitude of the force exerted on one gram of mass by a 9.80665 meter/second^2 gravitational field.\nEqual to 1/1000 of a kilogram weight.\nEqual to 0.00980665 newtons.',
'kilogram_force':'Equivalent to a kilogram weight.\nEqual to 9.80665 newtons.',
'kilogram_weight':'Defined to be the magnitude of the force exerted on one kilogram of mass by a 9.80665 meter/second^2 gravitational field.\nEqual to 9.80665 newtons.',
'newton':'SI derived unit of force.\nDefined to be kilogram*meter/second^2.',
'pound_force':'Equivalent to a pound weight.\nApproximately equal to 4.44822 newtons.',
'pound_weight':'Defined to be the magnitude of the force exerted on one pound of mass by a 9.80665 meter/second^2 gravitational field.\nApproximately equal to 4.44822 newtons.',
'poundal':'Defined to be pound*foot/second^2.\nApproximately equal to 0.13825 newtons.',
'ton_force':'Defined to be 2000 pounds of force.\nApproximately equal to 8896.4432 newtons.'},
'frequency_docs':
{'hertz':'SI derived unit of frequency.\nDefined to be one complete cycle per second.'},
'illuminance_docs':
{'foot_candle':'Defined to be lumen/foot^2.\nApproximately equal to 10.764 lux.',
'lux':'SI derived unit of illuminance.\nDefined to be lumen/meter^2.',
'phot':'CGS unit defined to be 10000 lux.'},
'inductance_docs':
{'abhenry':'Defined to be 10^-9 henries.',
'henry':'SI derived unit of inductance./nDefined to be a volt per ampere per second.',
'stathenry':'CGS unit defined to be one statvolt*second/statampere.\nApproximately equal to 8.98758*10^11 henries.'},
'information_docs':
{'bit':'Base unit of information.\nDefined to be the maximum amount of information that can be stored by a device of other physical system that can normally exist in only two distinct states.',
'byte':'Defined to be 8 bits.',
'nibble':'Defined to be 4 bits.'},
'information_rate_docs':
{'baud':'Defined to be 1 bit/second.'},
'inverse_length_docs':
{'diopter':'Defined to be 1/meter.',
'kayser':'Defined to be 100/meter.'},
'length_docs':
{'angstrom':'Defined to be 10^-10 meters.',
'astronomical_unit':'Originally defined as the length of the semi-major axis of the elliptical orbit of the Earth around the Sun.\nRedefined for accuracy to be the radius of an unperturbed circular Newtonian orbit about the Sun of a particle having infinitesimal mass, moving with a mean motion of 0.01720209895 radians per day.\nApproximately equal to 1.496*10^11 meters.',
'bolt':'Defined to be 40 yards.\nEqual to 36.576 meters.',
'cable_international':'Nautical unit defined to be 1/10 of a nautical mile.\nEqual to 185.2 meters.',
'cable_us':'Nautical unit defined to be equal to 720 feet or 120 fathoms.\nEqual to 219.456 meters.',
'caliber':'Equal to 1/100 of an inch.\nEqual to 0.000254 meters.',
'centimeter':'Equal to 1/100 of a meter.',
'chain':'Surveying unit defined to be 66 feet.\nApproximately equal to 20.12 meters.',
'cicero':'Printing unit defined to be 12 didot points.\nApproximately equal to 0.004512 meters.',
'cubit':'Ancient unit of length defined to be 18 inches.\nEqual to 0.4572 meters.',
'didot':'Printing unit equal to 1/12 of a cicero.\nApproximately equal to 0.00037597 meters.',
'dtp_point':'The desktop publishing point is defined to be 1/72 of an inch.\nApproximately equal to 0.0003528 meters.',
'ell':'Ancient unit of length defined to be 45 inches.\nEqual to 1.143 meters.',
'fathom':'Nautical unit defined to be 6 feet.\nEqual to 1.8288 meters.',
'feet':'Equal to 12 inches.\nDefined to be 0.3048 meters.',
'fermi':'Equivalent to a femtometer.\nEqual to 10^-15 meters.',
'foot':'Equal to 12 inches.\nDefined to be 0.3048 meters.',
'furlong':'Defined to be 660 feet, or 1/8 of a mile.\nEqual to 201.168 meters.',
'hand':'Defined to be 4 inches.\nEqual to 0.1016 meters.',
'inch':'Equal to 1/12 of a foot.\nEqual to 0.0254 meters.',
'kilometer':'Equal to 1000 meters.\nEqual to 3280.8399 feet.',
'league':'Defined to be 3 miles.\nConventionally equal to the distance a person or horse can walk in one hour.\nEqual to 4828.032 meters.',
'light_year':'Defined to be the distance light travels in vacuum in 365.25 days.\nApproximately equal to 9.4607*10^15 meters.',
'link':'Surveying unit defined to be 1/100 of a chain.\nEqual to 0.201168 meters.',
'meter':'SI base unit of length.\nDefined to be the distance light travels in vacuum in 1/299792458 of a second.',
'micron':'Defined to be 10^-6 meters.',
'mil':'Defined to be 1/1000 of an inch.\nEqual to 0.0000254 meters.',
'millimeter':'Defined to be 1/1000 of a meter.\nEqual to 0.001 meters.',
'mile':'Defined to be 5280 feet.\nEqual to 1609.344 meters.',
'nautical_mile':'Nautical unit defined to be 1852 meters.',
'parsec':'Defined to be the length of the adjacent side of a right triangle whose angle is 1 arcsecond and opposite side equal to 1 astronomical unit, or 1 AU/arctan(1 arcsecond).\nApproximately equal to 30.857*10^15 meters.',
'perch':'Equivalent to rod.\nDefined to be 16.5 feet.\nEqual to 5.0292 meters.',
'pica':'Printing unit defined to be 12 dtp points.\nEqual to 1/72 of a foot.\nApproximately equal to 0.004233 meters.',
'pole':'Equivalent to rod.\nDefined to be 16.5 feet.\nEqual to 5.0292 meters.',
'rod':'Defined to be 16.5 feet.\nEqual to 5.0292 meters.',
'rope':'Defined to be 20 feet.\nEqual to 6.096 meters.',
'skein':'Defined to be 360 feet.\nEqual to 109.728 meters.',
'stadion':'Ancient unit of length defined to be 622 feet.\nEqual to 189.5856 meters.',
'stadium':'Defined to be 202 yards or 606 feet.\nEqual to 184.7088 meters.',
'statute_mile':'Equivalent to mile.\nDefined to be 5280 feet.\nEqual to 1609.344 meters.',
'survey_foot':'Defined to be 1200/3937 or approximately 0.3048006 meters.',
'survey_mile':'Defined to be 5280 survey feet.\nApproximately equal to 1609.347 meters.',
'x_unit':'Unit of length used to quote wavelengths of X-rays and gamma rays.\nApproximately equal to 1.0021*10^-13 meters.',
'yard':'Defined to be 3 feet.\nEqual to 0.9144 meters.'},
'luminance_docs':
{'apostilb':'Defined to be 10^-4 lamberts.\nEqual to 1/pi*candela/meter^2.',
'lambert':'Defined to be 10^4/pi candela/meter^2.',
'nit':'Equivalent to candela/meter^2.',
'stilb':'CGS unit equal to 10000 candela/meter^2.'},
'luminous_energy_docs':
{'lumerg':'Equivalent to lumen*second',
'talbot':'Equivalent to lumen*second.'},
'luminous_flux_docs':
{'lumen':'SI derived unit of luminous flux.\nDefined to be candela*steradian.'},
'luminous_intensity_docs':
{'candela':'SI base unit of luminous intensity.\nDefined to be the luminous intensity, in a given direction, of a source that emits monochromatic radiation of frequency 540*10^12 hertz and that has a radiant intensity in that direction of 1/683 watt per steradian.',
'candle':'Equivalent to candela.',
'hefnerkerze':'Old German unit defined to be a 8 millimeter wick burning amyl acetate with a flame height of 40 millimeters.\nApproximately equal to 0.9034 candelas.'},
'magnetic_field_docs':
{'gauss':'CGS unit defined to be a maxwell/centimeter^2.\nEqual to 1/10000 of a tesla.',
'tesla':'SI derived unit of magnetic field.\nDefined to be the magnitude of a magnetic field such that a particle with a charge of 1 coulomb passing through that field at 1 meter/second will experience a force of 1 newton.'},
'magnetic_flux_docs':
{'maxwell':'CGS unit defined to be a gauss*centimeter^2 or 10^-8 webers.',
'weber':'SI derived unit of magnetic flux.\nDefined to be a change in magnetic flux of 1 weber per second will induce an electromotive force of 1 volt.'},
'magnetic_intensity_docs':
{'oersted':'CGS unit defined to be 1000/(4*pi) amperes per meter of flux path.'},
'magnetic_moment_docs':
{'bohr_magneton':'Physical constant defined to be the magnetic moment of an electron, or elementary_charge*h_bar/2*electron_rest_mass.\nApproximately equal to 9.274*10^-24 joules/tesla.',
'nuclear_magneton':'Physical constant defined to be the magnetic moment of a proton, or elementary_charge*h_bar/2*proton_rest_mass.\nApproximately equal to 5.05078324*10^-27 joules/tesla.'},
'magnetomotive_force_docs':
{'ampere_turn':'SI derived unit of magnetomotive force.\nDefined to be a direct current of 1 ampere flowing through a single turn loop in a vacuum.',
'gilbert':'CGS unit defined to be 10/(4*pi) ampere turns.'},
'mass_docs':
{'amu':'Abbreviation for atomic mass unit.\nApproximately equal to 1.660538782*10^-27 kilograms.',
'assay_ton':'Defined to be milligram*short_ton/ounce_troy.\nEqual to 7/240 of a kilogram.',
'atomic_mass_unit':'Defined to be one twelfth of the mass of an isolated atom of carbon-12 at rest and in its ground state.\nApproximately equal to 1.660538782*10^-27 kilograms.',
'avoirdupois_ounce':'Equivalent to ounce.\nEqual to 1/16 of an avoirdupois pound.\nApproximately equal to 0.02835 kilograms.',
'avoirdupois_pound':'Equivalent to pound.\nEqual to 16 avoirdupois ounces.\nApproximately equal to 0.45359 kilograms.',
'bale':'Equal to 500 pounds.\nApproximately equal to 226.796 kilograms.',
'carat':'Defined to be equal to 200 milligrams.\nCommonly denoted ct.',
'cental':'Equal to 100 pounds.\nApproximately equal to 45.36 kilograms.',
'dalton':'Equivalent to atomic_mass_unit.\nApproximately equal to 1.660538782*10^-27 kilograms.',
'drachma':'Ancient Greek unit of mass.\nEqual to 6 obols.\nApproximately equal to 0.00429234 kilograms.',
'geepound':'Equivalent to slug.\nApproximately equal to 14.5939 kilograms.',
'grain':'Historically based on the average mass of a single seed of a typical cereal.\nDefined in 1958 to be 64.79891 milligrams.',
'gram':'Equal to 0.0001 kilograms.',
'gross_hundredweight':'Equivalent to hundredweight.\nEqual to 112 pounds.\nApproximately equal to 50.802 kilograms.',
'hundredweight':'Defined to be 112 pounds.\nApproximately equal to 50.802 kilograms.',
'kilogram':'SI base unit of mass.\nDefined to be equal to the mass of the International Prototype Kilogram.\nAlmost exactly equal to the amount of mass in one liter of water.',
'libra':'Ancient Roman unit of mass.\nApproximately equal to 0.325971 kilogram.',
'long_ton':'Defined to be 2240 pounds.\nApproximately equal to 1016.05 kilograms.',
'metric_ton':'Defined to be 1000 kilograms.',
'mina':'Ancient Greek unit of mass.\nEqual to 100 drachma.\nApproximately equal to 0.429234 kilograms.',
'net_hundredweight':'Equivalent to cental.\nEqual to 100 pounds.\nApproximately equal to 45.36 kilograms.',
'obol':'Ancient Greek unit of mass.\nEqual to 1/6 of drachma.\nApproximately equal to 0.00071538 kilograms.',
'ounce':'Equal to 1/16 of pound.\nCommonly abbreviated oz.\nApproximately equal to 0.02835 kilograms.',
'ounce_troy':'Equal to 1/12 of pound_troy.\nApproximately equal to 0.031103 kilograms.',
'pennyweight':'Equal to 1/20 of ounce_troy.\nCommonly abbreviated dwt.\nApproximately equal to 0.001555 kilograms.',
'pondus':'Ancient Roman unit of mass.\nApproximately equal to 0.325969 kilograms.',
'pound':'Equal to 16 ounces.\nDefined to be exactly 0.45359237 kilograms.',
'pound_troy':'Equal to 12 ounce_troy.\nApproximately equal to 0.37324 kilograms.',
'quintal':'Equal to 100 kilograms.',
'shekel':'Ancient Hebrew unit of mass.\nApproximately equal to 0.0141 kilograms.',
'short_hundredweight':'Equivalent to cental.\nEqual to 100 pounds.\nApproximately equal to 45.36 kilograms.',
'short_ton':'Equivalent to ton.\nEqual to 2000 pounds.\nApproximately equal to 907.18 kilograms.',
'slug':'Defined to be a mass that is accelerated 1 ft/s^2 when 1 pound_force is exerted on it.\nApproximately equal to 14.5939 kilograms.',
'solar_mass':'Defined to be the mass of the Sun.\nAbout 332,950 times the mass of the Earth or 1,048 times the mass of Jupiter.\nApproximately equal to 1.98892*10^30 kilograms.',
'stone':'Defined to be 14 pounds.\nApproximately equal to 6.35 kilograms.',
'talent':'Ancient Greek unit of mass.\nEqual to 6000 drachmae.\nApproximately equal to 25.754 kilograms.',
'ton':'Equal to 2000 pounds.\nApproximately equal to 907.18 kilograms.',
'tonne':'Equivalent to metric_ton.\nDefined to be 1000 kilograms.',
'wey':'Defined to be 252 pounds.\nApproximately equal to 114.305 kilograms.'},
'power_docs':
{'cheval_vapeur':'Defined to be 75 kilogram force*meter/second.\nAlso known as metric horsepower.\nEqual to 735.49875 watts.',
'horsepower':'Defined to be 550 feet*pound force/second.\nApproximately equal to 745.7 watts.',
'watt':'SI derived unit of power.\nDefined to be joule/second or, in base units, kilogram*meter^2/second^3.'},
'pressure_docs':
{'atmosphere':'Defined to be 101325 pascals.',
'bar':'Defined to be 100000 pascals.',
'barye':'CGS unit defined to be dyne/centimeter^2.\nEqual to 1/10 of a pascal.',
'inch_mercury':'Defined to be 13595.1 kilogram/meter^3*inch*gravity.\nApproximately equal to 3386.389 pascals.',
'millimeter_mercury':'Defined to be 13595.1 kilogram/meter^3*millimeter*gravity.\nApproximately equal to 133.3224 pascals.',
'mmhg':'Abbreviation for millimeter mercury.\nApproximately equal to 133.3224 pascals.',
'pa':'Abbreviation for pascal.',
'pascal':'SI derived unit of pressure.\nDefined to be newton/meter^2 or, in base units, kilogram/(meter*second^2).',
'pounds_per_square_inch':'Defined to be pound force/inch^2.\nApproximately equal to 6894.76 pascals.',
'psi':'Abbreviation for pounds per square inch.\nApproximately equal to 6894.76 pascals.',
'torr':'Defined to be 1/760 of an atmosphere.\nApproximately equal to 133.322 pascals.'},
'radiation_absorbed_docs':
{'gray':'SI derived unit of absorbed radiation.\nDefined to be the absorption of one joule of ionizing radiation by one kilogram of matter.',
'rad':'Defined to be 1/100 of a gray.'},
'radiation_docs':
{'becquerel':'SI derived unit of radiation.\nDefined to be the activity of a quantity of radioactive material in which one nucleus decays per second.',
'curie':'Defined to be 37*10^9 becquerels.',
'rutherford':'Defined to be 10^6 becquerels.'},
'radiation_ionizing_docs':
{'roentgen':'Defined to be .000258 coulombs/kilogram.',
'rontgen':'Equivalent to roentgen.\nDefined to be .000258 coulombs/kilogram.'},
'resistance_docs':
{'abohm':'Defined to be 10^-9 ohms.',
'ohm':'SI derived unit of resistance.\nDefined to be a volt per ampere.',
'statohm':'CGS unit defined to be statvolt/statampere.\nApproximately equal to 8.98758*10^11 ohms.'},
'solid_angle_docs':
{'steradian':'SI derived unit of solid angle.\nDefined to be the solid angle subtended at the center of a sphere of radius r by a portion of the surface of the sphere having an area of r^2.'},
'temperature_docs':
{'celsius':'Defined to be -273.15 at absolute zero and 0.01 at the triple point of Vienna Standard Mean Ocean Water.\nCelsius is related to kelvin by the equation K = 273.15 + degrees Celsius.\nA change of 1 degree Celsius is equivalent to a change of 1 degree kelvin.',
'centigrade':'Equivalent to celsius.',
'fahrenheit':'Defined to be 32 degrees at the freezing point of water and 212 degrees at the boiling point of water, both at standard pressure (1 atmosphere).\nFahrenheit is related to kelvin by the equation K = 5/9*(degrees Fahrenheit + 459.67).\nA change of 1 degree fahrenheit is equal to a change of 5/9 kelvin.',
'kelvin':'SI base unit of temperature.\nDefined to be exactly 0 at absolute zero and 273.16 at the triple point of Vienna Standard Mean Ocean Water.',
'rankine':'Defined to be 0 at absolute zero and to have the same degree increment as Fahrenheit.\nRankine is related to kelvin by the equation K = 5/9*R.'},
'time_docs':
{'century':'Defined to be 100 years.\nEqual to 3153600000 seconds.',
'day':'Defined to be 24 hours.\nEqual to 86400 seconds.',
'decade':'Defined to be 10 years.\nEqual to 315360000 seconds.',
'fortnight':'Defined to be 2 weeks or 14 days.\nEqual to 1209600 seconds.',
'hour':'Defined to be 60 minutes.\nEqual to 3600 seconds.',
'millenium':'Defined to be 1000 years.\nEqual to 31536000000 seconds.',
'minute':'Defined to be 60 seconds.',
'month':'Defined to be 30 days.\nEqual to 2628000 seconds.',
'second':'SI base unit of time.\nDefined to be the duration of 9,192,631,770 periods of the radiation corresponding to the transition between the two hyperfine levels of the ground state of the caesium 133 atom.',
'sidereal_day':'Defined to be the time it takes for the Earth to make one complete rotation relative to the stars.\nApproximately equal to 86164.09 seconds.',
'sidereal_second':'Defined to be 1/86400 of a sidereal day.\nApproximately equal to 0.997269566329086 seconds.',
'sidereal_year':'Defined to be the time taken by the Earth to orbit the Sun once with respect to the fixed stars.\nApproximately equal to 31558149.7632 seconds.',
'tropical_year':'Defined to be the length of time that the Sun takes to return to the same position in the cycle of seasons, as seen from the Earth.\nApproximately equal to 31556925.1779840 seconds.',
'week':'Defined to be 7 days.\nEqual to 604800 seconds.',
'year':'Defined to be 365 days.\nEqual to 31536000 seconds.'},
'unit_multipliers_docs':
{'bakers_dozen':'Defined to be 13 items.',
'dozen':'Defined to be 12 items.',
'gross':'Defined to be 144 items.',
'percent':'Defined to be 1/100 of a quantity.'},
'velocity_docs':
{'knot':'Nautical unit of velocity defined to be a nautical mile per hour.\nApproximately equal to 0.5144 meter/second.'},
'viscosity_absolute_docs':
{'poise':'CGS unit defined to be 1/10 of pascal*second.',
'reyn':'Defined to be a pound_force*second/inch^2.\nApproximately equal to 6894.76 pascal*second.'},
'viscosity_kinematic_docs':
{'stokes':'CGS unit defined to be 1/10000 of meter^2/second.'},
'viscosity_other_docs':
{'rhes':'Defined to be 1/poise or 10/(pascal*second).'},
'volume_docs':
{'bag':'Defined to be 3 bushels.\nApproximately equal to 0.10572 cubic meters.',
'barrel':'Defined to be 42 gallons.\nApproximately equal to 0.15899 cubic meters.',
'board_foot':'Defined to be 144 cubic inches.\nApproximately equal to 0.0023597 cubic meters.',
'bucket':'Defined to be 4 gallons.\nApproximately equal to 0.0151416 cubic meters.',
'bushel':'Defined to be 2150.42 cubic inches.\nEquivalent to 4 pecks.\nApproximately equal to 0.035239 cubic meters.',
'butt':'Old English unit of wine casks defined to be 2 hogsheads or 126 gallons.\nApproximately equal to 0.476962 cubic meters.',
'cord':'Defined to be 8 feet x 8 feet x 4 feet.\nApproximately equal to 3.624556 cubic meters.',
'cubic_meter':'SI derived unit of volume.\nDefined to be meter^3.',
'cup':'Defined to be 8 fluid ounces.\nApproximately equal to 0.000236588 cubic meters.',
'ephah':'Ancient Hebrew unit of volume equal to 10 omers.\nApproximately equal to 0.03964 cubic meters.',
'fifth':'Defined to be 1/5 of a gallon.\nApproximately equal to 0.00075708 cubic meters.',
'firkin':'Defined to be 9 imperial gallons.\nApproximately equal to 0.04091 cubic meters.',
'fluid_dram':'Defined to be 1/8 of a fluid ounce.\nApproximately equal to 3.69669*10^-6 cubic meters.',
'fluid_ounce':'Defined to be 1/128 of a gallon.\nApproximately equal to 0.000029574 cubic meters.',
'gallon':'Defined to be 231 cubic inches.\nApproximately equal to 0.0037854 cubic meters.',
'gill':'Defined to be 4 fluid ounces.\nApproximately equal to 0.00011829 cubic meters.',
'hogshead':'Old English unit of wine casks defined to be 63 gallons.\nApproximately equal to 0.23848 cubic meters.',
'imperial_gallon':'Defined to be 4.54609 liters.\nEqual to 0.00454609 cubic meters.',
'imperial_pint':'Defined to be 1/8 of an imperial gallon.\nApproximately equal to 0.00056826 cubic meters.',
'jeroboam':'Defined to be 4/5 of a gallon.\nApproximately equal to 0.0030283 cubic meters.',
'jigger':'Defined to be 1 1/2 fluid ounces.\nApproximately equal to 0.00004436 cubic meters.',
'liter':'Defined to be 1 decimeter^3.\nEqual to 1/1000 of a cubic meter.',
'magnum':'Defined to be 1/2 a gallon.\nApproximately equal to 0.0018927 cubic meters.',
'minim':'Defined to be 1/480 of a fluid ounce.\nApproximately equal to 6.16115*10^-8 cubic meters.',
'noggin':'Equivalent to gill.\nDefined to be 4 fluid ounces.\nApproximately equal to 0.00011829 cubic meters.',
'omer':'Ancient Hebrew unit of volume equal to 9/20 of a peck.\nApproximately equal to 0.0039644 cubic meters.',
'peck':'Defined to be 1/4 of a bushel.\nApproximately equal to 0.0088098 cubic meters.',
'pint':'Defined to be 1/8 of a gallon.\nApproximately equal to 0.00047318 cubic meters.',
'pony':'Defined to be 3/4 of a fluid ounce.\nApproximately equal to 0.00002218 cubic meters.',
'puncheon':'Old English unit of wine casks defined to be 84 gallons.\nApproximately equal to 0.31797 cubic meters.',
'quart':'Defined to be 1/4 of a gallon.\nApproximately equal to 0.00094635 cubic meters.',
'register_ton':'Defined to be 100 cubic feet.\nApproximately equal to 2.83168 cubic meters.',
'seam':'Defined to be 8 bushels.\nApproximately equal to 0.281913 cubic meters.',
'shot':'Defined to be 1 fluid ounce.\nApproximately equal to 0.000029574 cubic meters.',
'stere':'Equivalent to cubic meter.',
'tablespoon':'Defined to be 1/2 of a fluid ounce.\nApproximately equal to 0.000014787 cubic meters.',
'teaspoon':'Defined to be 1/6 of a fluid ounce.\nEqual to 1/3 of a tablespoon.\nApproximately equal to 4.9289*10^-6 cubic meters.',
'tun':'Old English unit of wine casks defined to be 252 gallons.\nApproximately equal to 0.95392 cubic meters.',
'uk_gallon':'Equivalent to an imperial gallon.\nEqual to 0.00454609 cubic meters.',
'uk_pint':'Equivalent to and imperial pint.\nApproximately equal to 0.00056826 cubic meters.',
'wine_bottle':'Defined to be 750 milliliters.\nEqual to 0.00075 cubic meters.'}
}
###############################################################################
# Dictionary for converting from derived units to base SI units.
###############################################################################
unit_derivations = {'acceleration':'length/time^2',
'area':'length^2',
'capacitance':'time^4*current^2/(length^2*mass)',
'charge':'current*time',
'conductance':'current^2*time^3/(mass*length^2)',
'electric_potential':'mass*length^2/(current*time^3)',
'energy':'mass*length^2/time^2',
'fiber_linear_mass_density':'mass/length',
'force':'mass*length/time^2',
'frequency':'1/time',
'illuminance':'luminous_intensity*solid_angle/length^2',
'inductance':'length^2*mass/(time^2*current^2)',
'information_rate':'information/time',
'inverse_length':'1/length',
'luminance':'luminous_intensity/length^2',
'luminous_energy':'luminous_intensity*solid_angle*time',
'luminous_flux':'luminous_intensity*solid_angle',
'magnetic_field':'mass/(current*time^2)',
'magnetic_flux':'mass*length^2/(current*time^2)',
'magnetic_intensity':'current/length',
'magnetic_moment':'current*length^2',
'power':'mass*length^2/time^3',
'pressure':'mass/(length*time^2)',
'radiation':'1/time',
'radiation_absorbed':'length^2/time^2',
'radiation_ionizing':'current*time/mass',
'resistance':'mass*length^2/(current^2*time^3)',
'velocity':'length/time',
'viscosity_absolute':'mass/(length*time)',
'viscosity_kinematic':'length^2/time',
'viscosity_other':'length*time/mass',
'volume':'length^3'
}
def vars_in_str(s):
"""
Given a string like 'mass/(length*time)', return the list
['mass', 'length', 'time'].
INPUT:
- `s` -- string
OUTPUT:
- list of strings (unit names)
EXAMPLES::
sage: sage.symbolic.units.vars_in_str('mass/(length*time)')
['mass', 'length', 'time']
"""
return re.findall('[a-z|_]+', s)
def unit_derivations_expr(v):
"""
Given derived units name, returns the corresponding units
expression. For example, given 'acceleration' output the symbolic
expression length/time^2.
INPUT:
- `v` -- string, name of a unit type such as 'area', 'volume', etc.
OUTPUT:
- symbolic expression
EXAMPLES::
sage: sage.symbolic.units.unit_derivations_expr('volume')
length^3
sage: sage.symbolic.units.unit_derivations_expr('electric_potential')
length^2*mass/(current*time^3)
If the unit name is unknown, a KeyError is raised::
sage: sage.symbolic.units.unit_derivations_expr('invalid')
Traceback (most recent call last):
...
KeyError: 'invalid'
"""
v = str(v)
Z = unit_derivations[v]
if isinstance(Z,str):
d = dict([(x,str_to_unit(x)) for x in vars_in_str(Z)])
from sage.misc.all import sage_eval
Z = sage_eval(Z, d)
unit_derivations[v] = Z
return Z
class UnitExpression(Expression):
"""
A symbolic unit.
EXAMPLES::
sage: acre = units.area.acre
sage: type(acre)
<class 'sage.symbolic.units.UnitExpression'>
TESTS::
sage: bool(loads(dumps(acre)) == acre)
True
sage: type(loads(dumps(acre)))
<class 'sage.symbolic.units.UnitExpression'>
"""
def _sage_doc_(self):
"""
Return docstring for this unit.
EXAMPLES::
sage: print units.area.acre._sage_doc_()
Defined to be 10 square chains or 4840 square yards.
Approximately equal to 4046.856 square meters.
"""
return unitdocs(self)
def str_to_unit(name):
"""
Create the symbolic unit with given name. A symbolic unit is a
class that derives from symbolic expression, and has a specialized
docstring.
INPUT:
- ``name`` -- string
OUTPUT:
- UnitExpression
EXAMPLES::
sage: sage.symbolic.units.str_to_unit('acre')
acre
sage: type(sage.symbolic.units.str_to_unit('acre'))
<class 'sage.symbolic.units.UnitExpression'>
"""
return UnitExpression(SR, SR.var(name))
class Units:
"""
A collection of units of a some type.
EXAMPLES::
sage: units.power
Collection of units of power: cheval_vapeur horsepower watt
"""
def __init__(self, data, name=''):
"""
EXAMPLES::
sage: sage.symbolic.units.Units(sage.symbolic.units.unitdict, 'all units')
Collection of units of all units: acceleration ... volume
"""
self.__name = name
self.__data = data
self.__units = {}
def __getstate__(self):
"""
Used for pickling. We throw away all cached information.
EXAMPLES::
sage: type(units.__getstate__()[0])
<type 'str'>
sage: type(units.__getstate__()[1])
<type 'dict'>
sage: loads(dumps(units)) == units
True
sage: loads(dumps(units.area)) == units.area
True
sage: bool(loads(dumps(units.area.acre)) == units.area.acre)
True
"""
return (self.__name, self.__data)
def __setstate__(self, state):
"""
Used for unpickling. See __getstate__.
EXAMPLES::
sage: state = units.__getstate__()
sage: units.__setstate__(state)
"""
self.__name = state[0]
self.__data = state[1]
self.__units = {}
def __cmp__(self, other):
"""
Compare two collections of units, or a collection of units with some other object.
EXAMPLES::
sage: units.length == 10
False
sage: units.length == units.length
True
sage: units.length == units.mass
False
"""
if not isinstance(other, Units):
return cmp(type(self), type(other))
return cmp((self.__name, self.__data), (other.__name, other.__data))
def trait_names(self):
"""
Return completions of this unit objects. This is used by the
Sage command line and notebook to create the list of method
names.
EXAMPLES::
sage: units.area.trait_names()
['acre', 'are', 'barn', 'hectare', 'rood', 'section', 'square_chain', 'square_meter', 'township']
"""
return sorted([x for x in self.__data.keys() if '/' not in x])
def __getattr__(self, name):
"""
Return the unit with the given name.
EXAMPLES::
sage: units.area
Collection of units of area: acre are barn hectare rood section square_chain square_meter township
sage: units.area.barn
barn
Units are cached::
sage: units.area.acre is units.area.acre
True
"""
if name in self.__units:
return self.__units[name]
if len(unit_to_type) == 0:
evalunitdict()
try:
v = self.__data[name]
except KeyError:
raise AttributeError
if isinstance(v, dict):
U = Units(self.__data[name], name)
else:
U = str_to_unit(name)
self.__units[name] = U
return U
def __repr__(self):
"""
Return string representation of this collection of units.
EXAMPLES::
sage: units.__repr__()
'Collection of units: acceleration ... volume'
sage: units.area.__repr__()
'Collection of units of area: acre are barn hectare rood section square_chain square_meter township'
"""
name = ' of ' + self.__name if self.__name else ''
return "Collection of units{0}: {1}".format(name, ' '.join(sorted([str(x) for x in self.__data])))
units = Units(unitdict, '')
def unitdocs(unit):
r"""
Returns docstring for the given unit.
INPUT:
- ``unit``
OUTPUT:
- ``string``
EXAMPLES::
sage: sage.symbolic.units.unitdocs('meter')
'SI base unit of length.\nDefined to be the distance light travels in vacuum in 1/299792458 of a second.'
sage: sage.symbolic.units.unitdocs('amu')
'Abbreviation for atomic mass unit.\nApproximately equal to 1.660538782*10^-27 kilograms.'
Units not in the list unit_docs will raise a ValueError::
sage: sage.symbolic.units.unitdocs('earth')
Traceback (most recent call last):
...
ValueError: No documentation exists for the unit earth.
"""
if is_unit(unit):
return unit_docs[unit_to_type[str(unit)]+"_docs"][str(unit)]
else:
raise ValueError("No documentation exists for the unit %s."%unit)
def is_unit(s):
"""
Returns a boolean when asked whether the input is in the list of units.
INPUT:
- `s` -- an object
OUTPUT:
- ``bool``
EXAMPLES::
sage: sage.symbolic.units.is_unit(1)
False
sage: sage.symbolic.units.is_unit(units.length.meter)
True
The square of a unit is not a unit::
sage: sage.symbolic.units.is_unit(units.length.meter^2)
False
You can also directly create units using var, though they won't have
a nice docstring describing the unit::
sage: sage.symbolic.units.is_unit(var('meter'))
True
"""
return str(s) in unit_to_type
def convert(expr, target):
"""
Converts units between expr and target. If target is None then converts to SI base units.
INPUT:
- `expr` -- the symbolic expression converting from
- `target` -- (default None) the symbolic expression converting to
OUTPUT:
- `symbolic expression`
EXAMPLES::
sage: sage.symbolic.units.convert(units.length.foot, None)
381/1250*meter
sage: sage.symbolic.units.convert(units.mass.kilogram, units.mass.pound)
100000000/45359237*pound
Raises ValueError if expr and target are not convertible::
sage: sage.symbolic.units.convert(units.mass.kilogram, units.length.foot)
Traceback (most recent call last):
...
ValueError: Incompatible units
sage: sage.symbolic.units.convert(units.length.meter^2, units.length.foot)
Traceback (most recent call last):
...
ValueError: Incompatible units
Recognizes derived unit relationships to base units and other derived units::
sage: sage.symbolic.units.convert(units.length.foot/units.time.second^2, units.acceleration.galileo)
762/25*galileo
sage: sage.symbolic.units.convert(units.mass.kilogram*units.length.meter/units.time.second^2, units.force.newton)
newton
sage: sage.symbolic.units.convert(units.length.foot^3, units.area.acre*units.length.inch)
1/3630*(acre*inch)
sage: sage.symbolic.units.convert(units.charge.coulomb, units.current.ampere*units.time.second)
(ampere*second)
sage: sage.symbolic.units.convert(units.pressure.pascal*units.si_prefixes.kilo, units.pressure.pounds_per_square_inch)
1290320000000/8896443230521*pounds_per_square_inch
For decimal answers multiply 1.0::
sage: sage.symbolic.units.convert(units.pressure.pascal*units.si_prefixes.kilo, units.pressure.pounds_per_square_inch)*1.0
0.145037737730209*pounds_per_square_inch
You can also convert quantities of units::
sage: sage.symbolic.units.convert(cos(50) * units.angles.radian, units.angles.degree)
degree*(180*cos(50)/pi)
sage: sage.symbolic.units.convert(cos(30) * units.angles.radian, units.angles.degree).polynomial(RR)
8.83795706233228*degree
sage: sage.symbolic.units.convert(50 * units.length.light_year / units.time.year, units.length.foot / units.time.second)
6249954068750/127*(foot/second)
Quantities may contain variables (not for temperature conversion, though)::
sage: sage.symbolic.units.convert(50 * x * units.area.square_meter, units.area.acre)
acre*(1953125/158080329*x)
"""
base_target = target
z = {}
tz = {}
for x in expr.variables():
if is_unit(x):
if unit_to_type[str(x)] == 'temperature':
return convert_temperature(expr, target)
else:
z[x] = base_units(x)
expr = expr.subs(z)
if target is None:
return expr
else:
for y in base_target.variables():
if is_unit(y):
tz[y] = base_units(y)
base_target = base_target.subs(tz)
coeff = (expr/base_target).expand()
for variable in coeff.variables():
if is_unit(str(variable)):
raise ValueError("Incompatible units")
return coeff.mul(target, hold=True)
def base_units(unit):
"""
Converts unit to base SI units.
INPUT:
- ``unit``
OUTPUT:
- `symbolic expression`
EXAMPLES::
sage: sage.symbolic.units.base_units(units.length.foot)
381/1250*meter
If unit is already a base unit, it just returns that unit::
sage: sage.symbolic.units.base_units(units.length.meter)
meter
Derived units get broken down into their base parts::
sage: sage.symbolic.units.base_units(units.force.newton)
kilogram*meter/second^2
sage: sage.symbolic.units.base_units(units.volume.liter)
1/1000*meter^3
Returns variable if 'unit' is not a unit::
sage: sage.symbolic.units.base_units(var('x'))
x
"""
from sage.misc.all import sage_eval
if str(unit) not in unit_to_type:
return unit
elif unit_to_type[str(unit)] == 'si_prefixes' or unit_to_type[str(unit)] == 'unit_multipliers':
return sage_eval(unitdict[unit_to_type[str(unit)]][str(unit)])
else:
v = SR.var(unit_to_type[str(unit)])
if str(v) in unit_derivations:
base = unit_derivations_expr(v)
for i in base.variables():
base = base.subs({i:SR.var(value_to_unit[str(i)]['1'])})
return base*sage_eval(unitdict[str(v)][str(unit)])
else:
base = SR.var(value_to_unit[str(v)]['1'])*sage_eval(unitdict[str(v)][str(unit)])
return base
def convert_temperature(expr, target):
"""
Function for converting between temperatures.
INPUT:
- `expr` -- a unit of temperature
- `target` -- a units of temperature
OUTPUT:
- `symbolic expression`
EXAMPLES::
sage: t = 32*units.temperature.fahrenheit
sage: t.convert(units.temperature.celsius)
0
sage: t.convert(units.temperature.kelvin)
273.150000000000*kelvin
If target is None then it defaults to kelvin::
sage: t.convert()
273.150000000000*kelvin
Raises ValueError when either input is not a unit of temperature::
sage: t.convert(units.length.foot)
Traceback (most recent call last):
...
ValueError: Cannot convert
sage: wrong = units.length.meter*units.temperature.fahrenheit
sage: wrong.convert()
Traceback (most recent call last):
...
ValueError: Cannot convert
We directly call the convert_temperature function::
sage: sage.symbolic.units.convert_temperature(37*units.temperature.celsius, units.temperature.fahrenheit)
493/5*fahrenheit
sage: 493/5.0
98.6000000000000
"""
if len(expr.variables()) != 1:
raise ValueError("Cannot convert")
elif target == None or unit_to_type[str(target)] == 'temperature':
from sage.misc.all import sage_eval
expr_temp = expr.variables()[0]
coeff = expr/expr_temp
if target != None:
target_temp = target.variables()[0]
a = sage_eval(unitdict['temperature'][str(expr_temp)], locals = {'x':coeff})
if target == None or target_temp == units.temperature.kelvin:
return a[0]*units.temperature.kelvin
elif target_temp == units.temperature.celsius or target_temp == units.temperature.centigrade:
return a[1]*target_temp
elif target_temp == units.temperature.fahrenheit:
return a[2]*units.temperature.fahrenheit
elif target_temp == units.temperature.rankine:
return a[3]*target_temp
else:
raise ValueError("Cannot convert")
| 43.149233 | 382 | 0.63658 |
b78c1e5aa1c6406208f62c223bc7eb41761a4311 | 1,127 | py | Python | Examples/Basic/chatting.py | NekoGamiYuki/SpicyTwitch | b74b64026ba64c2303d7cc32da094f5c80cab325 | [
"MIT"
] | null | null | null | Examples/Basic/chatting.py | NekoGamiYuki/SpicyTwitch | b74b64026ba64c2303d7cc32da094f5c80cab325 | [
"MIT"
] | null | null | null | Examples/Basic/chatting.py | NekoGamiYuki/SpicyTwitch | b74b64026ba64c2303d7cc32da094f5c80cab325 | [
"MIT"
] | null | null | null | """
This example file shows how to send a message to a twitch channel. It waits
30 seconds before sending the same message again, so as to not spam the channel.
WARNING: Please do not remove the time.sleep(), or lower it, as you may get
banned from twitch for a certain amount of time. Do so only if you know what
you are doing.
Replace the necessary parameters (such as "username") with your own.
"""
import sys
import time
from spicytwitch import irc
# Connect to twitch, make sure we've logged in.
if not irc.connect("username", "oauth:..."):
print("Unable to login!")
sys.exit(1) # Close the program if we can't login
# Go ahead and set it to your own channel.
my_channel = "my_channel"
irc.join_channel(my_channel)
while True:
if irc.get_info():
# Wait 30 seconds before sending another message as we don't want to
# spam the channel...
time.sleep(30)
# chat() requires two parameters; First is the message you'd like to
# send. Second is the channel you would like to send that message to.
irc.chat("Hey! I'm chatting! Kappa Kappa MingLee", my_channel)
| 34.151515 | 80 | 0.704525 |
5a9d30f852d1adc98dcd88d5ec1624df21b1d59c | 1,575 | py | Python | app/models/calendar.py | Joeper214/barm | 77cd8ddcf73ceacf86b13ca819d8e56471e43574 | [
"MIT"
] | 2 | 2015-03-04T07:05:57.000Z | 2015-03-04T07:06:00.000Z | app/models/calendar.py | Joeper214/barm | 77cd8ddcf73ceacf86b13ca819d8e56471e43574 | [
"MIT"
] | null | null | null | app/models/calendar.py | Joeper214/barm | 77cd8ddcf73ceacf86b13ca819d8e56471e43574 | [
"MIT"
] | null | null | null | from ferris import BasicModel, ndb
from datetime import datetime, timedelta
from google.appengine.ext import deferred
class Calendar(BasicModel):
event_id = ndb.KeyProperty(required=True)
calendar_id = ndb.StringProperty(required=True)
alloc_date = ndb.DateProperty(required=True)
alloc_end = ndb.DateProperty(required=True)
alloc_hours = ndb.FloatProperty(required=True)
project_name = ndb.StringProperty(required=True)
resource_name = ndb.StringProperty(required=True)
email = ndb.StringProperty(required=True)
color = ndb.StringProperty(required=True)
# class Meta:
# behaviors = (EventBehavior, )
@classmethod
def list_all(cls):
return cls.query().order(cls.alloc_date).fetch()
@classmethod
def get(cls, key):
return cls(parent=key)
@classmethod
def create(cls, params):
item = cls()
item.populate(**params)
item.put()
return item
def update(self, params):
self.populate(**params)
self.put()
@classmethod
def find_by_event_id(cls, id):
return cls.query().filter(cls.allocation_id == id).order(cls.end_date).fetch()
def delete(self):
ndb.delete_multi(ndb.Query(ancestor=self.key).iter(keys_only=True))
@classmethod
def delete_by_event_id(cls,id):
allocs = cls.find_by_event_id(id)
for a in allocs:
deferred.defer(cls.del_calendar, a.key.urlsafe())
@classmethod
def del_calendar(cls, key):
key = ndb.Key(urlsafe=key)
key.delete()
| 28.125 | 86 | 0.664127 |
aab0b4d85864d5dfba3206393c38dde21b19d0cc | 1,608 | py | Python | firewall/app/main/controllers/ipController.py | vivitek/box | 82b8f9fec3b92b38b8587e18bdfeb08d50708d03 | [
"CC-BY-4.0"
] | 2 | 2020-05-28T14:39:46.000Z | 2020-06-19T18:38:46.000Z | firewall/app/main/controllers/ipController.py | vivitek/deep-thought | 9f0e3ec1e1c1dbc14466ec8ebd24ae83e6fcee94 | [
"CC-BY-4.0"
] | 35 | 2020-06-19T18:43:47.000Z | 2021-04-02T13:23:30.000Z | firewall/app/main/controllers/ipController.py | vivitek/box | 82b8f9fec3b92b38b8587e18bdfeb08d50708d03 | [
"CC-BY-4.0"
] | 1 | 2020-09-01T16:08:49.000Z | 2020-09-01T16:08:49.000Z | from flask import Blueprint, request, abort
from flask_api import status
from app.main import redis_client
from app.main.firewall_manager import FWManager
from app.main.utils.custom_exception import CustomException
import app.main.utils.validate_form as validateForm
bp = Blueprint('ip', __name__, url_prefix='/ip')
PyNFT = FWManager()
IP_FORMAT = "^((25[0-5]|2[0-4][0-9]|1[0-9][0-9]|[1-9]?[0-9])\.){3}(25[0-5]|2[0-4][0-9]|1[0-9][0-9]|[1-9]?[0-9])$"
@bp.route('/ban', methods=['POST'])
def banIP():
try:
body = request.get_json()
address = body.get('address')
# bandwith
# setBandwith()
validateForm.validateForm(address, IP_FORMAT)
response = PyNFT.ban_ipv4(address)
if (response['error']):
raise Exception(response['error'])
redis_client.zadd('ipBan', {address: 0})
return response, status.HTTP_200_OK
except CustomException as e:
return(e.reason, e.code)
except Exception as e:
return (str(e), status.HTTP_500_INTERNAL_SERVER_ERROR)
@bp.route('/unban', methods=['POST'])
def unbanIp():
try:
body = request.get_json()
address = body.get('address')
validateForm.validateForm(address, IP_FORMAT)
response = PyNFT.unban_ipv4(address)
if (response['error']):
raise Exception(response['error'])
redis_client.zrem('ipBan', address)
return response, status.HTTP_200_OK
except CustomException as e:
return(e.reason, e.code)
except Exception as e:
return (str(e), status.HTTP_500_INTERNAL_SERVER_ERROR)
| 34.956522 | 113 | 0.648632 |
3319ef9f8f12dbab4d86177de680b7204b490299 | 651 | py | Python | Lib/site-packages/registration/__init__.py | pablotose/Curso-Django | 812ffc0b45cf8c26b3b052ad2e5a5ce22fa7ad7f | [
"bzip2-1.0.6"
] | 16 | 2016-09-01T20:34:48.000Z | 2020-03-20T06:16:25.000Z | Lib/site-packages/registration/__init__.py | pablotose/Curso-Django | 812ffc0b45cf8c26b3b052ad2e5a5ce22fa7ad7f | [
"bzip2-1.0.6"
] | 1 | 2017-01-26T19:50:36.000Z | 2017-01-26T20:01:41.000Z | Lib/site-packages/registration/__init__.py | pablotose/Curso-Django | 812ffc0b45cf8c26b3b052ad2e5a5ce22fa7ad7f | [
"bzip2-1.0.6"
] | 5 | 2016-09-28T20:24:26.000Z | 2019-10-07T08:33:13.000Z | VERSION = (1, 4, 0, 'final', 0)
def get_version():
"Returns a PEP 386-compliant version number from VERSION."
assert len(VERSION) == 5
assert VERSION[3] in ('alpha', 'beta', 'rc', 'final')
# Now build the two parts of the version number:
# main = X.Y[.Z]
# sub = .devN - for pre-alpha releases
# | {a|b|c}N - for alpha, beta and rc releases
parts = 2 if VERSION[2] == 0 else 3
main = '.'.join(str(x) for x in VERSION[:parts])
sub = ''
if VERSION[3] != 'final':
mapping = {'alpha': 'a', 'beta': 'b', 'rc': 'c'}
sub = mapping[VERSION[3]] + str(VERSION[4])
return str(main + sub)
| 28.304348 | 62 | 0.554531 |
10f52a70b0562e02b5160d6512b8fdef69d24e54 | 14,613 | py | Python | Python_Tello(DJI_UAV)/tello_image_ros/2022_2_12/TelloGO_IMAG/src/tello_control/tello_control/tello_base.py | Chentao2000/practice_code | aa4fb6bbc26ac1ea0fb40e6e0889050b7e9f096c | [
"Apache-2.0"
] | 4 | 2022-01-07T13:07:48.000Z | 2022-02-08T04:46:02.000Z | Python_Tello(DJI_UAV)/tello_image_ros/2022_2_12/TelloGO_IMAG/src/tello_control/tello_control/tello_base.py | Chentao2000/practice_code | aa4fb6bbc26ac1ea0fb40e6e0889050b7e9f096c | [
"Apache-2.0"
] | null | null | null | Python_Tello(DJI_UAV)/tello_image_ros/2022_2_12/TelloGO_IMAG/src/tello_control/tello_control/tello_base.py | Chentao2000/practice_code | aa4fb6bbc26ac1ea0fb40e6e0889050b7e9f096c | [
"Apache-2.0"
] | null | null | null | import socket
import threading
import time
import numpy as np
import libh264decoder
from stats import Stats
class Tello:
"""Wrapper class to interact with the Tello drone."""
def __init__(self, local_ip, local_port, imperial=False, command_timeout=.3, tello_ip='192.168.10.1',
tello_port=8889):
"""
Binds to the local IP/port and puts the Tello into command mode.
:param local_ip (str): Local IP address to bind.
:param local_port (int): Local port to bind.
:param imperial (bool): If True, speed is MPH and distance is feet.
If False, speed is KPH and distance is meters.
:param command_timeout (int|float): Number of seconds to wait for a response to a command.
:param tello_ip (str): Tello IP.
:param tello_port (int): Tello port.
"""
self.last = False
self.command = "" #for debug
self.abort_flag = False
self.decoder = libh264decoder.H264Decoder()
self.command_timeout = command_timeout
self.imperial = imperial
self.response = None
self.frame = None # numpy array BGR -- current camera output frame
self.is_freeze = False # freeze current camera output
self.last_frame = None
self.log = []
self.MAX_TIME_OUT = 10.0
self.socket = socket.socket(socket.AF_INET, socket.SOCK_DGRAM) # socket for sending cmd
self.socket_video = socket.socket(socket.AF_INET, socket.SOCK_DGRAM) # socket for receiving video stream
self.socket_state=socket.socket(socket.AF_INET, socket.SOCK_DGRAM)#state socket
self.tello_ip=tello_ip
self.tello_address = (tello_ip, tello_port)
self.local_video_port = 11111 # port for receiving video stream
self.last_height = 0
self.socket.bind((local_ip, local_port))
# thread for receiving cmd ack
self.receive_thread = threading.Thread(target=self._receive_thread)
self.receive_thread.daemon = True
self.receive_thread.start()
# to receive video -- send cmd: command, streamon
self.socket.sendto(b'command', self.tello_address)
print ('sent: command')
self.socket.sendto(b'streamon', self.tello_address)
print ('sent: streamon')
self.socket_video.bind((local_ip, self.local_video_port))
# thread for receiving video
self.receive_video_thread = threading.Thread(target=self._receive_video_thread)
self.receive_video_thread.daemon = True
self.receive_video_thread.start()
#state receive
self.results=None
self.socket_state.bind((local_ip,8890))
self.receive_state_thread=threading.Thread(target=self._recevie_state_thread)
self.receive_state_thread.daemon=True
self.receive_state_thread.start()
def __del__(self):
"""Closes the local socket."""
self.socket.close()
self.socket_video.close()
self.socket_state.close()
def read_frame(self):
"""Return the last frame from camera."""
if self.is_freeze:
return self.last_frame
else:
return self.frame
def read_state(self):
if self.results=='ok' or self.results==None:
return self.results
else:
return self.results[0:8]
def video_freeze(self, is_freeze=True):
"""Pause video output -- set is_freeze to True"""
self.is_freeze = is_freeze
if is_freeze:
self.last_frame = self.frame
def _receive_thread(self):
"""Listen to responses from the Tello.
Runs as a thread, sets self.response to whatever the Tello last returned.
"""
while True:
try:
self.response, ip = self.socket.recvfrom(3000)
if len(self.log)!=0:
self.log[-1].add_response(self.response)
#print(self.response)
except socket.error as exc:
print ("Caught exception socket.error : %s" % exc)
def _receive_video_thread(self):
"""
Listens for video streaming (raw h264) from the Tello.
Runs as a thread, sets self.frame to the most recent frame Tello captured.
"""
packet_data = ""
while True:
try:
res_string, ip = self.socket_video.recvfrom(2048)
packet_data += res_string
# end of frame
if len(res_string) != 1460:
for frame in self._h264_decode(packet_data):
self.frame = frame
packet_data = ""
except socket.error as exc:
print ("Caught exception socket.error : %s" % exc)
def _recevie_state_thread(self):
while True:
try:
state, ip = self.socket_state.recvfrom(1024)
out = state.replace(';', ';\n')
self.results = out.split()
#print("received result: " + str(self.results) )
except socket.error as exc:
print ("Caught exception socket.error : %s" % exc)
def _h264_decode(self, packet_data):
"""
decode raw h264 format data from Tello
:param packet_data: raw h264 data array
:return: a list of decoded frame
"""
res_frame_list = []
frames = self.decoder.decode(packet_data)
for framedata in frames:
(frame, w, h, ls) = framedata
if frame is not None:
# print 'frame size %i bytes, w %i, h %i, linesize %i' % (len(frame), w, h, ls)
frame = np.fromstring(frame, dtype=np.ubyte, count=len(frame), sep='')
frame = (frame.reshape((h, ls / 3, 3)))
frame = frame[:, :w, :]
res_frame_list.append(frame)
return res_frame_list
def send_command(self, command):
"""
Send a command to the Tello and wait for a response.
:param command: Command to send.
:return (str): Response from Tello.
"""
self.log.append(Stats(command, len(self.log)))
print(">> send cmd: {}".format(command))
print(len(self.log),self.log[-1].got_response())
self.socket.sendto(command.encode('utf-8'), self.tello_address)
print(len(self.log),self.log[-1].got_response())
self.last = self.log[-1].got_response()
start = time.time()
#print(self.log[-1].got_response())
timelen = 0.
while True:
if not self.log[-1].got_response():
continue
elif (not self.last) and('ok' in str(self.log[-1].got_response())):
break
elif ('ok' in str(self.last)) and('ok' in str(self.log[-1].got_response())):
self.last = self.log[-1].got_response()
continue
elif 'ok' not in str(self.log[-1].got_response()):
now = time.time()
diff = now - start
if diff > timelen:
print(self.log[-1].got_response())
timelen += 1.
self.socket.sendto(command.encode('utf-8'), self.tello_address)
#print(len(self.log))
if diff > self.MAX_TIME_OUT:
print ('Max timeout exceeded... command %s' % command)
raise Exception('command timeout')
print ('Done!!! sent command: %s to %s' % (command, self.tello_ip))
print (self.log[-1].got_response())
return self.log[-1].got_response()
def set_abort_flag(self):
"""
Sets self.abort_flag to True.
Used by the timer in Tello.send_command() to indicate to that a response
timeout has occurred.
"""
self.abort_flag = True
def takeoff(self):
"""
Initiates take-off.
Returns:
str: Response from Tello, 'OK' or 'FALSE'.
"""
return self.send_command('takeoff')
def set_speed(self, speed):
"""
Sets speed.
This method expects KPH or MPH. The Tello API expects speeds from
1 to 100 centimeters/second.
Metric: .1 to 3.6 KPH
Imperial: .1 to 2.2 MPH
Args:
speed (int|float): Speed.
Returns:
str: Response from Tello, 'OK' or 'FALSE'.
"""
speed = float(speed)
if self.imperial is True:
speed = int(round(speed * 44.704))
else:
speed = int(round(speed * 27.7778))
return self.send_command('speed %s' % speed)
def rotate_cw(self, degrees):
"""
Rotates clockwise.
Args:
degrees (int): Degrees to rotate, 1 to 360.
Returns:
str: Response from Tello, 'OK' or 'FALSE'.
"""
return self.send_command('cw %s' % degrees)
def rotate_ccw(self, degrees):
"""
Rotates counter-clockwise.
Args:
degrees (int): Degrees to rotate, 1 to 360.
Returns:
str: Response from Tello, 'OK' or 'FALSE'.
"""
return self.send_command('ccw %s' % degrees)
def flip(self, direction):
"""
Flips.
Args:
direction (str): Direction to flip, 'l', 'r', 'f', 'b'.
Returns:
str: Response from Tello, 'OK' or 'FALSE'.
"""
return self.send_command('flip %s' % direction)
def get_response(self):
"""
Returns response of tello.
Returns:
int: response of tello.
"""
response = self.response
return response
def get_height(self):
"""Returns height(dm) of tello.
Returns:
int: Height(dm) of tello.
"""
height = self.send_command('height?')
height = str(height)
height = filter(str.isdigit, height)
try:
height = int(height)
self.last_height = height
except:
height = self.last_height
pass
return height
def get_battery(self):
"""Returns percent battery life remaining.
Returns:
int: Percent battery life remaining.
"""
battery = self.send_command('battery?')
try:
battery = int(battery)
except:
pass
return battery
def get_flight_time(self):
"""Returns the number of seconds elapsed during flight.
Returns:
int: Seconds elapsed during flight.
"""
flight_time = self.send_command('time?')
try:
flight_time = int(flight_time)
except:
pass
return flight_time
def get_speed(self):
"""Returns the current speed.
Returns:
int: Current speed in KPH or MPH.
"""
speed = self.send_command('speed?')
try:
speed = float(speed)
if self.imperial is True:
speed = round((speed / 44.704), 1)
else:
speed = round((speed / 27.7778), 1)
except:
pass
return speed
def land(self):
"""Initiates landing.
Returns:
str: Response from Tello, 'OK' or 'FALSE'.
"""
return self.send_command('land')
def move(self, direction, distance):
"""Moves in a direction for a distance.
This method expects meters or feet. The Tello API expects distances
from 20 to 500 centimeters.
Metric: .02 to 5 meters
Imperial: .7 to 16.4 feet
Args:
direction (str): Direction to move, 'forward', 'back', 'right' or 'left'.
distance (int|float): Distance to move.
Returns:
str: Response from Tello, 'OK' or 'FALSE'.
"""
distance = float(distance)
if self.imperial is True:
distance = int(round(distance * 30.48))
else:
distance = int(round(distance * 100))
return self.send_command('%s %s' % (direction, distance))
def move_backward(self, distance):
"""Moves backward for a distance.
See comments for Tello.move().
Args:
distance (int): Distance to move.
Returns:
str: Response from Tello, 'OK' or 'FALSE'.
"""
return self.move('back', distance)
def move_down(self, distance):
"""Moves down for a distance.
See comments for Tello.move().
Args:
distance (int): Distance to move.
Returns:
str: Response from Tello, 'OK' or 'FALSE'.
"""
return self.move('down', distance)
def move_forward(self, distance):
"""Moves forward for a distance.
See comments for Tello.move().
Args:
distance (int): Distance to move.
Returns:
str: Response from Tello, 'OK' or 'FALSE'.
"""
return self.move('forward', distance)
def move_left(self, distance):
"""Moves left for a distance.
See comments for Tello.move().
Args:
distance (int): Distance to move.
Returns:
str: Response from Tello, 'OK' or 'FALSE'.
"""
return self.move('left', distance)
def move_right(self, distance):
"""Moves right for a distance.
See comments for Tello.move().
Args:
distance (int): Distance to move.
"""
return self.move('right', distance)
def move_up(self, distance):
"""Moves up for a distance.
See comments for Tello.move().
Args:
distance (int): Distance to move.
Returns:
str: Response from Tello, 'OK' or 'FALSE'.
"""
return self.move('up', distance)
| 28.822485 | 114 | 0.529665 |
37478165cbb1270124f8fd9d85f2a48e92615606 | 910 | py | Python | docs/source/examples/FB2.0/post_quotas_users.py | Flav-STOR-WL/py-pure-client | 03b889c997d90380ac5d6380ca5d5432792d3e89 | [
"BSD-2-Clause"
] | 14 | 2018-12-07T18:30:27.000Z | 2022-02-22T09:12:33.000Z | docs/source/examples/FB2.0/post_quotas_users.py | Flav-STOR-WL/py-pure-client | 03b889c997d90380ac5d6380ca5d5432792d3e89 | [
"BSD-2-Clause"
] | 28 | 2019-09-17T21:03:52.000Z | 2022-03-29T22:07:35.000Z | docs/source/examples/FB2.0/post_quotas_users.py | Flav-STOR-WL/py-pure-client | 03b889c997d90380ac5d6380ca5d5432792d3e89 | [
"BSD-2-Clause"
] | 15 | 2020-06-11T15:50:08.000Z | 2022-03-21T09:27:25.000Z | from pypureclient.flashblade import UserQuota
file_system_name = "quotaFs"
# Add a quota of 1024 for the file system to apply to the users with ids 123 and 124
res = client.post_quotas_users(file_system_names=[file_system_name], uids=[123, 124],
quota=UserQuota(quota=1024))
# print the created quotas
print(res)
if type(res) == pypureclient.responses.ValidResponse:
print(list(res.items))
# Add a quota of 2048 for the file system to apply to the users with names user1 and user2
res = client.post_quotas_users(file_system_names=[file_system_name],
user_names=["user1", "user2"],
quota=UserQuota(quota=2048))
# print the created quotas
print(res)
if type(res) == pypureclient.responses.ValidResponse:
print(list(res.items))
# Other valid fields: file_system_ids
# See section "Common Fields" for examples
| 39.565217 | 90 | 0.696703 |
3a30879e0d09658c2b82e6bd126f4eec74259c1e | 1,068 | py | Python | dingo/migrations/0001_initial.py | MartorSkull/Tomu | 8bcc2676b030fca1720efce185c398a52eed005a | [
"MIT"
] | null | null | null | dingo/migrations/0001_initial.py | MartorSkull/Tomu | 8bcc2676b030fca1720efce185c398a52eed005a | [
"MIT"
] | null | null | null | dingo/migrations/0001_initial.py | MartorSkull/Tomu | 8bcc2676b030fca1720efce185c398a52eed005a | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
# Generated by Django 1.11.2 on 2017-07-19 18:58
from __future__ import unicode_literals
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies = [
migrations.swappable_dependency(settings.AUTH_USER_MODEL),
]
operations = [
migrations.CreateModel(
name='Chatter',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('discord_id', models.IntegerField()),
('discord_username', models.CharField(max_length=32)),
('banned', models.BooleanField(default=False)),
('user', models.OneToOneField(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL)),
],
options={
'verbose_name': 'Chatter',
'verbose_name_plural': 'Chatters',
},
),
]
| 31.411765 | 121 | 0.608614 |
42cc51a10a19fd868be3bffb77ded5505a8ee90b | 4,113 | py | Python | misc/model-builder/quant/tflite.py | jackwish/shrub | acd14c72269c88e3143997288efcc6f0130c4c8e | [
"Apache-2.0"
] | 2 | 2020-09-23T01:16:39.000Z | 2022-01-26T23:16:21.000Z | misc/model-builder/quant/tflite.py | jackwish/shrub | acd14c72269c88e3143997288efcc6f0130c4c8e | [
"Apache-2.0"
] | 1 | 2020-09-23T01:09:54.000Z | 2020-09-23T01:09:54.000Z | misc/model-builder/quant/tflite.py | jackwish/shrub | acd14c72269c88e3143997288efcc6f0130c4c8e | [
"Apache-2.0"
] | null | null | null | import os
import numpy as np
import tensorflow as tf
from tensorflow.python.platform import gfile
from tensorflow.core.framework import graph_pb2
from tensorflow.python.framework import graph_util
class OpChecker:
def __init__(self, op, ishape, range_min, range_max, mode="MIN_COMBINED"):
# args in TensorFlow style
self.op = op
self.name = 'gen'
self.ishape = ishape
self.oshape = ishape
self.min = range_min
self.max = range_max
self.mode = mode
self.iname = 'input'
self.oname = 'output'
if op == tf.quantize:
self.idtype = tf.float32
self.odtype = tf.quint8
self.tflite_model_path = "quant.tflite"
self.tflite_dtype = tf.float32
elif op == tf.dequantize:
self.idtype = tf.quint8
self.odtype = tf.float32
self.tflite_model_path = "dequant.tflite"
self.tflite_dtype = tf.float32
else:
raise ValueError("Unkown op")
def genModels(self):
print("Generating Models...")
with tf.Session(graph=tf.Graph()) as sess:
data = tf.placeholder(
self.idtype,
shape=self.ishape,
name=self.iname)
output = self.op(
data,
self.min,
self.max,
tf.quint8,
mode=self.mode,
name=self.oname)
sess.run(tf.global_variables_initializer())
constant_graph = graph_util.convert_variables_to_constants(
sess, sess.graph_def, [self.oname])
with tf.gfile.FastGFile(self.name + ".pb", mode='wb') as f:
f.write(constant_graph.SerializeToString())
def genTFLiteModel(self):
print("Generating TensorFlow Lite model...")
converter = tf.lite.TFLiteConverter.from_frozen_graph(
self.name + ".pb",
input_arrays=[self.iname],
output_arrays=[self.oname, ])
# converter.inference_type = self.tflite_dtype
# converter.inference_inpute_type = self.tflite_dtype
converter.default_ranges_stats = (0, 6)
converter.quantized_input_stats = {self.iname: (100, 100.0)}
# converter.post_training_quantize = True
# converter.target_ops = set([OpsSet.TFLITE_BUILTINS])
tflite_model = converter.convert()
open(self.name + ".tflite", "wb").write(tflite_model)
def preRun(self):
self.input_nhwc = np.random.uniform(
size=self.ishape).astype(
self.dtype)
self.input_nchw = self.input_nhwc.transpose(0, 3, 1, 2)
def runTensorFlow(self):
print("run TensorFlow...")
tf.reset_default_graph()
graph_def = graph_pb2.GraphDef()
with open(self.name + ".pb", 'rb') as f:
graph_def.ParseFromString(f.read())
g = tf.import_graph_def(graph_def)
with tf.Session(graph=g) as sess:
image_input_tensor = sess.graph.get_tensor_by_name(
'import/' + self.iname + ":0")
outputs = [
sess.graph.get_tensor_by_name(
"import/" + self.oname + ":0")]
self.output_tf = sess.run(
outputs, feed_dict={
image_input_tensor: self.input_nhwc})[0]
def test_OP(op, input_shape, range_min, range_max, mode="MIN_COMBINED"):
op = OpChecker(op, input_shape, range_min, range_max, mode=mode)
op.genModels()
op.genTFLiteModel()
def test_dequant():
print("[START] test_dequant")
print("")
input_shape = (1, 256, 256, 32) # NHWC
range_min = 0.0
range_max = 6.0
# see
# http://tensorflow.biotecan.com/python/Python_1.8/tensorflow.google.cn/api_docs/python/tf/dequantize.html
mode = 'MIN_COMBINED'
# mode='MIN_FIRST'
# mode='SCALED'
quant_op = tf.dequantize
quant_op = tf.quantize
test_OP(quant_op, input_shape, range_min, range_max, mode=mode)
print("")
print("[DONE] test_dequant")
test_dequant()
| 32.904 | 110 | 0.592025 |
952eb3ab8d7cc0df19291f01e960de255a4ae1a4 | 2,005 | py | Python | solutions/2021/day_13.py | mokytis/advent-of-code | 7bddbc87411388bb0da8284c3daa5252f9d5007d | [
"MIT"
] | null | null | null | solutions/2021/day_13.py | mokytis/advent-of-code | 7bddbc87411388bb0da8284c3daa5252f9d5007d | [
"MIT"
] | null | null | null | solutions/2021/day_13.py | mokytis/advent-of-code | 7bddbc87411388bb0da8284c3daa5252f9d5007d | [
"MIT"
] | null | null | null | #!/usr/bin/env python
"""
Puzzle Title: AoC 2021 Day 13: Transparent Origami
Puzzle Link: https://adventofcode.com/2021/day/13
Solution Author: Luke Spademan <info@lukespademan.com>
Solution License: MIT
"""
import fileinput
from dataclasses import dataclass
import copy
@dataclass
class Fold:
axis: str
value: int
def parse_input():
points = set()
folds = []
for line in map(lambda x: x.rstrip(), fileinput.input()):
if line:
if line.startswith("fold along "):
axis, value = line[11:].split("=")
folds.append(Fold(axis, int(value)))
else:
num1, num2 = line.split(",")
points.add((int(num1), int(num2)))
return points, folds
def fold_points(points, fold):
if fold.axis == "x":
i = 0
else:
i = 1
for point in copy.copy(points):
if point[i] == fold.value:
points.remove(point)
elif point[i] > fold.value:
points.remove(point)
distance = point[i] - fold.value
if i == 0:
points.add((fold.value - distance, point[1]))
else:
points.add((point[0], fold.value - distance))
return len(points)
def output(points):
ys = [point[1] for point in points]
xs = [point[0] for point in points]
for row in range(min(ys), max(ys) + 1):
for value in range(min(xs), max(xs) + 1):
if (value, row) in points:
print("#", end="")
else:
print(" ", end="")
print()
def solve_part1(points, fold):
return fold_points(points, fold)
def solve_part2(points, folds):
for fold in folds:
fold_points(points, fold)
output(points)
def main():
points, folds = parse_input()
part1_ans = solve_part1(points, folds[0])
print(f"Part 1: {part1_ans}")
print("Part 2:")
solve_part2(points, folds)
if __name__ == "__main__":
main()
| 22.784091 | 61 | 0.555611 |
36713fc18c6674c212407ad55c4487c7aec9645d | 4,512 | py | Python | db/Student.py | sysu-team1/BackEnd | 4773545897fee3aa7a767cbe6d011372623e1e58 | [
"MIT"
] | 1 | 2019-11-19T09:08:50.000Z | 2019-11-19T09:08:50.000Z | db/Student.py | sysu-team1/BackEnd | 4773545897fee3aa7a767cbe6d011372623e1e58 | [
"MIT"
] | null | null | null | db/Student.py | sysu-team1/BackEnd | 4773545897fee3aa7a767cbe6d011372623e1e58 | [
"MIT"
] | null | null | null | import copy
import random
from .prepare import app, db, model_repr, SEX, EDUBG, ALL_TAGS
class Student(db.Model):
'''
使用的sql语句:
```sql
CREATE TABLE `students` (
`openid` int(11) NOT NULL AUTO_INCREMENT COMMENT '用户的唯一标识符',
`email` varchar(40) NOT NULL COMMENT '学校邮箱',
`password` varchar(20) NOT NULL COMMENT '密码',
`student_id` varchar(10) NOT NULL DEFAULT '' COMMENT '学号',
`name` varchar(100) DEFAULT '' COMMENT '名称',
`sex` enum('unknown','male','female') DEFAULT 'unknown' COMMENT '用户性别',
`collage` varchar(20) DEFAULT '' COMMENT '学院',
`grade` int(11) NOT NULL DEFAULT '2016' COMMENT '入学年级',
`edu_bg` enum('undergraduate','masterofscience','doctor') DEFAULT 'undergraduate' COMMENT '学历',
`tag` varchar(100) DEFAULT '' COMMENT '与任务相关的标签',
`signature` varchar(300) DEFAULT '' COMMENT '用户签名',
`cash` int(11) DEFAULT '0' COMMENT '拥有的币',
PRIMARY KEY (`openid`),
FULLTEXT KEY `stu_tag` (`tag`)
) ENGINE=InnoDB AUTO_INCREMENT=1000000 DEFAULT CHARSET=utf8
```
属性:
基础属性
accepts: 表示接收的任务
tasks: 表示发布的任务
'''
__tablename__ = 'students'
openid = db.Column('openid', db.Integer(
), autoincrement=True, nullable=False, comment='用户的唯一标识符')
email = db.Column('email', db.VARCHAR(
40), nullable=False, comment='学校邮箱')
password = db.Column('password', db.VARCHAR(
20), nullable=False, comment='密码')
student_id = db.Column('student_id', db.VARCHAR(
10), nullable=False, server_default='', comment='学号')
name = db.Column('name', db.VARCHAR(
100), server_default='', comment='名称')
sex = db.Column('sex', db.Enum(
*SEX), server_default=SEX[0], comment='用户性别') # default的话是在插入时才有的
collage = db.Column('collage', db.VARCHAR(
20), server_default='', comment='学院')
grade = db.Column('grade', db.Integer(
), nullable=False, server_default='2016', comment='入学年级')
edu_bg = db.Column('edu_bg', db.Enum(
*EDUBG), server_default=EDUBG[0], comment='学历')
tag = db.Column('tag', db.VARCHAR(
100), server_default='', comment='与任务相关的标签')
signature = db.Column('signature', db.VARCHAR(
300), server_default='', comment='用户签名')
cash = db.Column('cash', db.Integer(), server_default='0', comment='拥有的币')
__table_args__ = (
db.PrimaryKeyConstraint('openid'),
db.Index('stu_tag', 'tag', mysql_prefix='FULLTEXT'),
)
accepts = db.relationship(
'Accept', back_populates='student', cascade='delete')
tasks = None
# _tasks = None
# get_tasks = None
# get_tasks = None
# def __getattribute__(self, name):
# if name == 'tasks' and self.task is None and Student.get_tasks is not None: # 无限递归
# self.tasks = Student.get_tasks(self.openid)
# return super(Student, self).__getattribute__(name)
def __repr__(self):
# return '<Student(email={}, password={}, sex={}, collage={}, grade={}, edu_bg={}, tag={}, signature={})>'.format(
# self.email, self.password, self.sex, self.collage, self.grade, self.edu_bg, self.tag, self.signature)
# return model_repr(self, config.STUDENT_JSON_PATTERN, config.STUDENT_JSON_ATTR_ORDER)
return model_repr(self, app.config['STUDENT_JSON_PATTERN'], app.config['STUDENT_JSON_ATTR_ORDER'])
def random_stus(num):
rand_collages = ['药学院', '数据科学与计算机学院', '法学院', '心理学院', '哲学院', '医学院']
tag_len = len(ALL_TAGS)
stus = []
for i in range(num):
sex = random.choice(SEX)
edu_bg = random.choice(EDUBG)
collage = random.choice(rand_collages)
grade = 2019 - random.randint(0, 10)
rnum = random.randint(0, tag_len)
tag = []
all_tags = copy.deepcopy(ALL_TAGS)
while len(tag) < rnum:
index = random.randint(0, len(all_tags) - 1)
tag.append(all_tags[index])
all_tags.pop(index)
tag = ','.join(tag)
start, length = random.randint(1, 20), random.randint(10, 15)
signature = ' '.join(['word{}'.format(
j) for j in range(start, start + length)])
cash = random.randint(10, 5000)
stus.append(Student(email='email{}@qq.com'.format(i), password='pass{}'.format(
i), student_id="16340{:0>3d}".format(i), name="16340{:0>3d}".format(i), sex=sex, collage=collage, grade=grade, edu_bg=edu_bg, tag=tag, signature=signature, cash=cash))
return stus
| 41.777778 | 179 | 0.61547 |
2b506051142c4cac247166250931716794b59bc6 | 647 | py | Python | md5sum/md5sum/handler.py | quartz010/OpenAPI | a62383e7ec606a1106c56e7ddc840142711250a7 | [
"MIT"
] | null | null | null | md5sum/md5sum/handler.py | quartz010/OpenAPI | a62383e7ec606a1106c56e7ddc840142711250a7 | [
"MIT"
] | null | null | null | md5sum/md5sum/handler.py | quartz010/OpenAPI | a62383e7ec606a1106c56e7ddc840142711250a7 | [
"MIT"
] | null | null | null |
import json
import random
import hashlib
def handle(req):
"""handle a request to the function
Args:
req (str): request body
"""
ret = {
"code": 0,
"msg": ""
}
if req == "":
ret["code"] = 0
ret["msg"] = "invalid parameters"
return json.dumps(ret)
else:
try:
hash = hashlib.md5(req.encode("utf-8")).hexdigest()
ret["code"] = 0
ret["msg"] = hash
return json.dumps(ret)
except Exception as e:
ret["code"] = -1
ret["msg"] = e
return json.dumps(ret)
return json.dumps(ret) | 23.107143 | 63 | 0.476043 |
936d2d5340df81b206be3de68bd604659ede6009 | 6,290 | py | Python | utils/metric.py | zhoufangquan/sccl | 4a30cca7980f1e7319d4ce727196ea74854025b8 | [
"MIT-0"
] | null | null | null | utils/metric.py | zhoufangquan/sccl | 4a30cca7980f1e7319d4ce727196ea74854025b8 | [
"MIT-0"
] | null | null | null | utils/metric.py | zhoufangquan/sccl | 4a30cca7980f1e7319d4ce727196ea74854025b8 | [
"MIT-0"
] | null | null | null | """
Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved
Author: Dejiao Zhang (dejiaoz@amazon.com)
Date: 02/26/2021
"""
from __future__ import print_function
import time
import torch
import numpy as np
from scipy.optimize import linear_sum_assignment as hungarian
from sklearn.metrics.cluster import normalized_mutual_info_score, adjusted_rand_score, adjusted_mutual_info_score
cluster_nmi = normalized_mutual_info_score
def cluster_acc(y_true, y_pred):
y_true = y_true.astype(np.int64)
assert y_pred.size == y_true.size
D = max(y_pred.max(), y_true.max()) + 1
w = np.zeros((D, D), dtype=np.int64)
for i in range(y_pred.size):
w[y_pred[i], y_true[i]] += 1
# ind = sklearn.utils.linear_assignment_.linear_assignment(w.max() - w)
# row_ind, col_ind = linear_assignment(w.max() - w)
row_ind, col_ind = hungarian(w.max() - w)
return sum([w[i, j] for i, j in zip(row_ind, col_ind)]) * 1.0 / y_pred.size
class AverageMeter(object):
"""Computes and stores the average and current value"""
def __init__(self):
self.reset()
def reset(self):
self.val = 0
self.avg = 0
self.sum = 0
self.count = 0
def update(self, val, n=1):
self.val = val
self.sum += val * n
self.count += n
self.avg = float(self.sum) / self.count
class Timer(object):
"""
"""
def __init__(self):
self.reset()
def reset(self):
self.interval = 0
self.time = time.time()
def value(self):
return time.time() - self.time
def tic(self):
self.time = time.time()
def toc(self):
self.interval = time.time() - self.time
self.time = time.time()
return self.interval
class Confusion(object):
"""
column of confusion matrix: predicted index
row of confusion matrix: target index
"""
def __init__(self, k, normalized = False):
super(Confusion, self).__init__()
self.k = k
self.conf = torch.LongTensor(k,k)
self.normalized = normalized
self.reset()
def reset(self):
self.conf.fill_(0)
self.gt_n_cluster = None
def cuda(self):
self.conf = self.conf.cuda()
def add(self, output, target):
output = output.squeeze()
target = target.squeeze()
assert output.size(0) == target.size(0), \
'number of targets and outputs do not match'
if output.ndimension()>1: #it is the raw probabilities over classes
assert output.size(1) == self.conf.size(0), \
'number of outputs does not match size of confusion matrix'
_,pred = output.max(1) #find the predicted class
else: #it is already the predicted class
pred = output
indices = ((target-1)*self.conf.stride(0) + pred.squeeze_().type_as(target)).type_as(self.conf)
ones = torch.ones(1).type_as(self.conf).expand(indices.size(0))
self._conf_flat = self.conf.view(-1)
self._conf_flat.index_add_(0, indices, ones)
def classIoU(self,ignore_last=False):
confusion_tensor = self.conf
if ignore_last:
confusion_tensor = self.conf.narrow(0,0,self.k-1).narrow(1,0,self.k-1)
union = confusion_tensor.sum(0).view(-1) + confusion_tensor.sum(1).view(-1) - confusion_tensor.diag().view(-1)
acc = confusion_tensor.diag().float().view(-1).div(union.float()+1)
return acc
def recall(self,clsId):
i = clsId
TP = self.conf[i,i].sum().item()
TPuFN = self.conf[i,:].sum().item()
if TPuFN==0:
return 0
return float(TP)/TPuFN
def precision(self,clsId):
i = clsId
TP = self.conf[i,i].sum().item()
TPuFP = self.conf[:,i].sum().item()
if TPuFP==0:
return 0
return float(TP)/TPuFP
def f1score(self,clsId):
r = self.recall(clsId)
p = self.precision(clsId)
print("classID:{}, precision:{:.4f}, recall:{:.4f}".format(clsId, p, r))
if (p+r)==0:
return 0
return 2*float(p*r)/(p+r)
def acc(self):
TP = self.conf.diag().sum().item()
total = self.conf.sum().item()
if total==0:
return 0
return float(TP)/total
def optimal_assignment(self,gt_n_cluster=None,assign=None):
if assign is None:
mat = -self.conf.cpu().numpy() #hungaian finds the minimum cost
r,assign = hungarian(mat)
self.conf = self.conf[:,assign]
self.gt_n_cluster = gt_n_cluster
return assign
def show(self,width=6,row_labels=None,column_labels=None):
print("Confusion Matrix:")
conf = self.conf
rows = self.gt_n_cluster or conf.size(0)
cols = conf.size(1)
if column_labels is not None:
print(("%" + str(width) + "s") % '', end='')
for c in column_labels:
print(("%" + str(width) + "s") % c, end='')
print('')
for i in range(0,rows):
if row_labels is not None:
print(("%" + str(width) + "s|") % row_labels[i], end='')
for j in range(0,cols):
print(("%"+str(width)+".d")%conf[i,j],end='')
print('')
def conf2label(self):
conf=self.conf
gt_classes_count=conf.sum(1).squeeze()
n_sample = gt_classes_count.sum().item()
gt_label = torch.zeros(n_sample)
pred_label = torch.zeros(n_sample)
cur_idx = 0
for c in range(conf.size(0)):
if gt_classes_count[c]>0:
gt_label[cur_idx:cur_idx+gt_classes_count[c]].fill_(c)
for p in range(conf.size(1)):
if conf[c][p]>0:
pred_label[cur_idx:cur_idx+conf[c][p]].fill_(p)
cur_idx = cur_idx + conf[c][p];
return gt_label,pred_label
def clusterscores(self):
target,pred = self.conf2label()
NMI = normalized_mutual_info_score(target,pred)
ARI = adjusted_rand_score(target,pred)
AMI = adjusted_mutual_info_score(target,pred)
return {'NMI':NMI,'ARI':ARI,'AMI':AMI}
| 33.280423 | 118 | 0.574245 |
f4728ba13f09797b37c9db6214f9680bb58f6aab | 5,848 | py | Python | ironic_inspector/conf/default.py | xudan16/ironic-inspector | 1d8383d0ae82730c7a107dbe85712171430b237a | [
"Apache-2.0"
] | null | null | null | ironic_inspector/conf/default.py | xudan16/ironic-inspector | 1d8383d0ae82730c7a107dbe85712171430b237a | [
"Apache-2.0"
] | null | null | null | ironic_inspector/conf/default.py | xudan16/ironic-inspector | 1d8383d0ae82730c7a107dbe85712171430b237a | [
"Apache-2.0"
] | null | null | null | # 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 socket
from oslo_config import cfg
from oslo_config import types as cfg_types
from ironic_inspector.common.i18n import _
class Octal(cfg_types.Integer):
def __call__(self, value):
if isinstance(value, int):
return value
else:
return int(str(value), 8)
_OPTS = [
cfg.StrOpt('listen_address',
default='::',
help=_('IP to listen on.')),
cfg.PortOpt('listen_port',
default=5050,
help=_('Port to listen on.')),
cfg.StrOpt('listen_unix_socket',
help=_('Unix socket to listen on. Disables listen_address and '
'listen_port.')),
cfg.Opt('listen_unix_socket_mode', type=Octal(),
help=_('File mode (an octal number) of the unix socket to '
'listen on. Ignored if listen_unix_socket is not set.')),
cfg.StrOpt('host',
default=socket.getfqdn(),
sample_default='localhost',
help=_('Name of this node. This can be an opaque identifier. '
'It is not necessarily a hostname, FQDN, or IP address. '
'However, the node name must be valid within '
'an AMQP key, and if using ZeroMQ, a valid '
'hostname, FQDN, or IP address.')),
cfg.StrOpt('auth_strategy',
default='keystone',
choices=[('noauth', _('no authentication')),
('keystone', _('use the Identity service for '
'authentication')),
('http_basic', _('HTTP basic authentication'))],
help=_('Authentication method used on the ironic-inspector '
'API. "noauth", "keystone" or "http_basic" are valid '
'options. "noauth" will disable all authentication.')),
cfg.StrOpt('http_basic_auth_user_file',
default='/etc/ironic-inspector/htpasswd',
help=_('Path to Apache format user authentication file used '
'when auth_strategy=http_basic')),
cfg.IntOpt('timeout',
default=3600,
# We're using timedelta which can overflow if somebody sets this
# too high, so limit to a sane value of 10 years.
max=315576000,
help=_('Timeout after which introspection is considered '
'failed, set to 0 to disable.')),
cfg.IntOpt('clean_up_period',
default=60,
min=0,
help=_('Amount of time in seconds, after which repeat clean up '
'of timed out nodes and old nodes status information. '
'WARNING: If set to a value of 0, then the periodic '
'task is disabled and inspector will not sync with '
'ironic to complete the internal clean-up process. '
'Not advisable if the deployment uses a PXE filter, '
'and will result in the ironic-inspector ceasing '
'periodic cleanup activities.')),
cfg.IntOpt('leader_election_interval',
default=10,
help=_('Interval (in seconds) between leader elections.')),
cfg.BoolOpt('use_ssl',
default=False,
help=_('SSL Enabled/Disabled')),
cfg.IntOpt('max_concurrency',
default=1000, min=2,
help=_('The green thread pool size.')),
cfg.IntOpt('introspection_delay',
default=5,
help=_('Delay (in seconds) between two introspections. Only '
'applies when boot is managed by ironic-inspector (i.e. '
'manage_boot==True).')),
cfg.ListOpt('ipmi_address_fields',
default=['redfish_address', 'ilo_address', 'drac_host',
'drac_address', 'ibmc_address'],
help=_('Ironic driver_info fields that are equivalent '
'to ipmi_address.')),
cfg.StrOpt('rootwrap_config',
default="/etc/ironic-inspector/rootwrap.conf",
help=_('Path to the rootwrap configuration file to use for '
'running commands as root')),
cfg.IntOpt('api_max_limit', default=1000, min=1,
help=_('Limit the number of elements an API list-call '
'returns')),
cfg.BoolOpt('can_manage_boot', default=True,
help=_('Whether the current installation of ironic-inspector '
'can manage PXE booting of nodes. If set to False, '
'the API will reject introspection requests with '
'manage_boot missing or set to True.')),
cfg.BoolOpt('enable_mdns', default=False,
help=_('Whether to enable publishing the ironic-inspector API '
'endpoint via multicast DNS.')),
cfg.BoolOpt('standalone', default=True,
help=_('Whether to run ironic-inspector as a standalone '
'service. It\'s EXPERIMENTAL to set to False.')),
]
def register_opts(conf):
conf.register_opts(_OPTS)
def list_opts():
return _OPTS
| 45.333333 | 79 | 0.569596 |
adec575a6cfd91740bba0af163e0cda71cc2cc6a | 5,984 | py | Python | fracdiff/fracdiffstat.py | vishalbelsare/fracdiff | d51d575b147dbabd9eff9833ef207716d69f9e40 | [
"BSD-3-Clause"
] | 44 | 2019-12-23T12:25:50.000Z | 2022-01-08T16:04:33.000Z | fracdiff/fracdiffstat.py | simaki/fracdiff | d51d575b147dbabd9eff9833ef207716d69f9e40 | [
"BSD-3-Clause"
] | 71 | 2019-12-23T12:55:54.000Z | 2021-04-30T10:14:09.000Z | fracdiff/fracdiffstat.py | vishalbelsare/fracdiff | d51d575b147dbabd9eff9833ef207716d69f9e40 | [
"BSD-3-Clause"
] | 19 | 2020-06-23T01:34:44.000Z | 2022-02-19T21:01:51.000Z | import numpy
from sklearn.base import BaseEstimator
from sklearn.base import TransformerMixin
from sklearn.utils.validation import check_array
from sklearn.utils.validation import check_is_fitted
from fracdiff import Fracdiff
from fracdiff.stat import StatTester
class FracdiffStat(TransformerMixin, BaseEstimator):
"""
Carry out fractional derivative with the minumum order
with which the differentiation becomes stationary.
Parameters
----------
window : int > 0 or None, default 10
Number of observations to compute each element in the output.
mode : {"full", "valid"}, default "full"
"full" (default) :
Return elements where at least one coefficient is used.
Shape of a transformed array is the same with the original array.
At the beginning of a transformed array, boundary effects may be seen.
"valid" :
Return elements where all coefficients are used.
Output size along axis 1 is `n_features - window_`.
At the beginning of a time-series, boundary effects is not seen.
window_policy : {"fixed"}, default "fixed"
If "fixed" :
Fixed window method.
Every term in the output is evaluated using `window_` observations.
In other words, a fracdiff operator, which is a polynominal of a backshift
operator, is truncated up to the `window_`-th term.
The beginning `window_ - 1` elements in output are filled with
``numpy.nan``.
If "expanding" (not available) :
Expanding window method.
Every term in fracdiff time-series is evaluated using at least `window_`
observations.
The beginning `window_ - 1` elements in output are filled with
``numpy.nan``.
stattest : {"ADF"}, default "ADF"
Method of stationarity test.
pvalue : float, default 0.05
Threshold of p-value to judge stationarity.
precision : float, default .01
Precision for the order of differentiation.
upper : float, default 1.0
Upper limit of the range to search the order.
lower : float, default 0.0
Lower limit of the range to search the order.
Attributes
----------
d_ : numpy.array, shape (n_features,)
Minimum order of fractional differentiation
that makes time-series stationary.
Note
----
If `upper`th differentiation of series is still non-stationary,
order_ is set to ``numpy.nan``.
If `lower`th differentiation of series is already stationary,
order_ is set to `lower`, but the true value may be smaller.
Examples
--------
>>> numpy.random.seed(42)
>>> X = numpy.random.randn(100, 4).cumsum(0)
>>> f = FracdiffStat().fit(X)
>>> f.d_
array([0.140625 , 0.5078125, 0.3984375, 0.140625 ])
>>> X = f.transform(X)
"""
def __init__(
self,
window=10,
mode="full",
window_policy="fixed",
stattest="ADF",
pvalue=0.05,
precision=0.01,
upper=1.0,
lower=0.0,
):
self.window = window
self.mode = mode
self.window_policy = window_policy
self.stattest = stattest
self.pvalue = pvalue
self.precision = precision
self.upper = upper
self.lower = lower
def fit(self, X, y=None):
"""
Fit the model with `X`.
Parameters
----------
X : array_like, shape (n_samples, n_features)
Time-series to perform fractional differentiation.
Here `n_samples` is the number of samples and `n_features` is the number of
features.
y : array_like, optional
Ignored.
Returns
-------
self : object
Returns the instance itself.
"""
check_array(X)
self.d_ = numpy.array([self._find_d(X[:, i]) for i in range(X.shape[1])])
return self
def transform(self, X, y=None) -> numpy.array:
"""
Return the fractional differentiation of `X`.
Parameters
----------
X : array_like, shape (n_samples, n_series)
Time-series to perform fractional differentiation.
Raises ValueError if `n_samples < self.window_`.
y : array_like, optional
Ignored.
Returns
-------
fdiff : ``numpy.array``, shape (n_samples, n_series)
The fractional differentiation of `X`.
"""
check_is_fitted(self, ["d_"])
check_array(X)
prototype = Fracdiff(0.5, window=self.window, mode=self.mode).fit_transform(X)
out = numpy.empty_like(prototype[:, :0])
for i in range(X.shape[1]):
f = Fracdiff(self.d_[i], window=self.window, mode=self.mode)
d = f.fit_transform(X[:, [i]])[-out.shape[0] :]
out = numpy.concatenate((out, d), 1)
return out
def _is_stat(self, x) -> bool:
return StatTester(method=self.stattest).is_stat(x, pvalue=self.pvalue)
def _find_d(self, x) -> float:
"""
Carry out binary search of minimum order of fractional
differentiation to make the time-series stationary.
Parameters
----------
x : array, shape (n,)
Returns
-------
d : float
"""
def diff(d):
fracdiff = Fracdiff(d, window=self.window, mode=self.mode)
return fracdiff.fit_transform(x.reshape(-1, 1)).reshape(-1)
if not self._is_stat(diff(self.upper)):
return numpy.nan
if self._is_stat(diff(self.lower)):
return self.lower
upper, lower = self.upper, self.lower
while upper - lower > self.precision:
m = (upper + lower) / 2
if self._is_stat(diff(m)):
upper = m
else:
lower = m
return upper
| 32.172043 | 87 | 0.586397 |
2007ecff4db118c8dacb9f8abdbef4203b900a64 | 14,581 | py | Python | dev-docs/extlibs/rar_SSokolow.py | VenoMpie/pyrescene | f75d98d9173f1576b5d8fd42da300673e918707c | [
"MIT"
] | 18 | 2020-08-09T02:17:46.000Z | 2022-02-18T09:17:25.000Z | dev-docs/extlibs/rar_SSokolow.py | VenoMpie/pyrescene | f75d98d9173f1576b5d8fd42da300673e918707c | [
"MIT"
] | 1 | 2021-11-23T21:13:37.000Z | 2021-11-23T21:13:37.000Z | dev-docs/extlibs/rar_SSokolow.py | VenoMpie/pyrescene | f75d98d9173f1576b5d8fd42da300673e918707c | [
"MIT"
] | 9 | 2020-10-15T11:02:49.000Z | 2022-03-15T10:36:14.000Z | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
A pure-Python module for identifying and examining RAR files developed without
any exposure to the original unrar code. (Just format docs from wotsit.org)
It was, however, influenced by the zipfile module in the Python standard
library as, having already decided to match the zipfile.ZipFile API as closely
as feasibly possible, I didn't see a point to doing extra work to come up with
new ways of laying out my code for no good reason.
@todo: Determine how rarfile (http://rarfile.berlios.de/) compares to this in
various target metrics. If it is superior or close enough on all fronts,
patch it as necessary and plan a migration path. Otherwise, do the following:
- Complete the parsing of the RAR metadata.
(eg. Get data from archive header, check CRCs, read cleartext comments, etc.)
- Optimize further and write a test suite.
- Double-check that ZipFile/ZipInfo API compatibility has been maintained
wherever feasible.
- Support extraction of files stored with no compression.
- Look into supporting split and password-protected RARs.
- Some password-protected RAR files use blocks with types 0x30, 0x60, and 0xAD
according to this code. Figure out whether it's a bug or whether they're really
completely new kinds of blocks. (Encrypted headers for filename-hiding?)
- When the appropriate code is available, use the following message for failure
to extract compressed files::
For reasons of patent, performance, and a general lack of motivation on the
author's part, this module does not extract compressed files.
"""
__appname__ = "rar.py"
__author__ = "Stephan Sokolow (deitarion/SSokolow)"
__version__ = "0.2.99.0"
__license__ = "PSF License 2.4 or higher (The Python License)"
#{ Settings for findRarHeader()
CHUNK_SIZE = 4096
MARKER_BLOCK = "\x52\x61\x72\x21\x1a\x07\x00"
FIND_LIMIT = 1024**2 #: 1MiB
# A Compromise. Override FIND_LIMIT with 0 to be sure but potentially very slow.
#{ Packing method values
RAR_STORED = 0x30
RAR_FASTEST = 0x31
RAR_FAST = 0x32
RAR_NORMAL = 0x33
RAR_GOOD = 0x34
RAR_BEST = 0x35
#}
import math, struct, sys, time, zlib
_struct_blockHeader = struct.Struct("<HBHH")
_struct_addSize = struct.Struct('<L')
_struct_fileHead_add1 = struct.Struct("<LBLLBBHL") # Plus FILE_NAME and everything after it
class BadRarFile(Exception):
"""Raised when no valid RAR header is found in a given file."""
class RarInfo(object):
"""The metadata for a file stored in a RAR archive.
@attention: API compatibility with ZipInfo could not be maintained in the
following fields:
- C{create_version} (Not stored in RAR files)
- C{flag_bits} (Zip and RAR use different file header flags)
- C{volume} (Zip files specify volume number. RAR files just have
"File is continued from previous" and "File continues in next" flags and
an archive-level "is volume" flag)
- C{comment} (RAR files may have multiple comments per file and they may be
stored using compression... which rar.py doesn't support)
@todo: How do I interpret the raw file timestamp?
@todo: Is the file's CRC of the compressed or uncompressed data?
@todo: Does RAR perform any kind of path separator normalization?
"""
os_map = ['MS DOS', 'OS/2', 'Win32', 'Unix'] #: Interpretations for possible L{create_system} values.
compress_size = None #: File's compressed size
compress_type = None #: Packing method (C{0x30} indicates no compression)
create_system = None #: Type of system on which the file originated (See L{os_map})
date_time = None #: File's timestamp
external_attr = None #: File's attributes
extract_version = None #: Minimum RAR version needed to extract (major * 10 + minor)
filename = None #: Filename relative to the archive root
file_size = None #: File's uncompressed size
flag_bits = 0 #: Raw flag bits from the RAR header
header_offset = None #: Offset of the compressed data within the file
is_directory = False #: The entry describes a folder/directory
is_encrypted = False #: The file has been encrypted with a password
is_solid = False #: Information from previous files has been used
not_first_piece = False #: File is continued from previous volume
not_last_piece = False #: File continues in next volume
CRC = None #: File's CRC
_raw_time = None #: Raw integer time value extracted from the header
#TODO: comment, extra, reserved, internal_attr
def __init__(self, filename, ftime=0):
"""
@param filename: The file's name and path relative to the archive root.
@note: Since I know of no filesystem which allows null bytes in paths,
this borrows a trick from C{ZipInfo} and truncates L{filename} at the
first null byte to protect against certain kinds of virus tricks.
@todo: Implement support for taking ints OR tuples for L{ftime}.
"""
null_byte = filename.find(chr(0))
if null_byte >= 0:
filename = filename[0:null_byte]
self.filename = filename
self.orig_filename = filename # Match ZipInfo for better compatibility
self._raw_time = ftime
self.date_time = time.gmtime(self._raw_time) #TODO: Verify this is correct.
class RarFile(object):
"""A simple parser for RAR archives capable of retrieving content metadata
and, possibly in the future, of extracting entries stored without
compression.
@note: Whenever feasible, this class replicates the API of
C{zipfile.ZipFile}. As a side-effect, design decisions the author
has no strong feelings about (eg. naming of private methods)
will generally closely follow those made C{in zipfile.ZipFile}.
"""
_block_types = {
0x72: 'Marker Block ( MARK_HEAD )',
0x73: 'Archive Heaver ( MAIN_HEAD )',
0x74: 'File Header',
0x75: 'Comment Header',
0x76: 'Extra Info',
0x77: 'Subblock',
0x78: 'Recovery Record',
0x7b: 'Terminator?'
} #: Raw HEAD_TYPE values used in block headers.
# According to the comment in zipfile.ZipFile, __del__ needs fp here.
fp = None #: The file handle used to read the metadata.
_filePassed = None #: Whether an already-open file handle was passed in.
# I just put all public members here as a matter of course.
filelist = None #: A C{list} of L{RarInfo} objects corresponding to the contents.
debug = 0 #: Debugging verbosity. Effective range is currently 0 to 1.
def __init__(self, handle):
# If we've been given a path, get our desired file-like object.
if isinstance(handle, basestring):
self_filePassed = False
self.filename = handle
self.fp = open(handle, 'rb')
else:
self._filePassed = True
self.fp = handle
self.filename = getattr(handle, 'name', None)
# Find the header, skipping the SFX module if present.
start_offset = findRarHeader(self.fp)
if start_offset:
self.fp.seek(start_offset)
else:
if not self._filePassed:
self.fp.close()
self.fp = None
raise BadRarFile("Not a valid RAR file")
self.filelist = []
# Actually read the file metadata.
self._getContents()
def __del__(self):
"""Close the file handle if we opened it... just in case the underlying
Python implementation doesn't do refcount closing."""
if self.fp and not self._filePassed:
self.fp.close()
def _getContents(self):
"""Content-reading code is here separated from L{__init__} so that, if
the author so chooses, writing of uncompressed RAR files may be
implemented in a later version more easily.
"""
while True:
offset = self.fp.tell()
# Read the fields present in every type of block header
try:
head_crc, head_type, head_flags, head_size = self._read_struct(_struct_blockHeader)
except struct.error:
# If it fails here, we've reached the end of the file.
return
# Read the optional field ADD_SIZE if present.
if head_flags & 0x8000:
add_size = self._read_struct(_struct_addSize)[0]
else:
add_size = 0
# TODO: Rework handling of archive headers.
if head_type == 0x73:
#TODO: Try to factor this out to reduce time spent in syscalls.
self.fp.seek(offset + 2) # Seek to just after HEAD_CRC
#FIXME: Check header CRC on all blocks.
assert self._check_crc(self.fp.read(11), head_crc)
# TODO: Rework handling of file headers.
elif head_type == 0x74:
unp_size, host_os, file_crc, ftime, unp_ver, method, name_size, attr = self._read_struct(_struct_fileHead_add1)
# FIXME: What encoding does WinRAR use for filenames?
# TODO: Verify that ftime is seconds since the epoch as it seems
fileinfo = RarInfo(self.fp.read(name_size), ftime)
fileinfo.compress_size = add_size
fileinfo.header_offset = offset
fileinfo.file_size = unp_size #TODO: What about >2GiB files? (Zip64 equivalent?)
fileinfo.CRC = file_crc #TODO: Verify the format matches that ZipInfo uses.
fileinfo.compress_type = method
# Note: RAR seems to have copied the encoding methods used by
# Zip for these values.
fileinfo.create_system = host_os
fileinfo.extract_version = unp_ver
fileinfo.external_attr = attr #TODO: Verify that this is correct.
# Handle flags
fileinfo.flag_bits = head_flags
fileinfo.not_first_piece = head_flags & 0x01
fileinfo.not_last_piece = head_flags & 0x02
fileinfo.is_encrypted = head_flags & 0x04
#TODO: Handle comments
fileinfo.is_solid = head_flags & 0x10
# TODO: Verify this is correct handling of bits 7,6,5 == 111
fileinfo.is_directory = head_flags & 0xe0
self.filelist.append(fileinfo)
elif self.debug > 0:
sys.stderr.write("Unhandled block: %s\n" % self._block_types.get(head_type, 'Unknown (0x%x)' % head_type))
# Line up for the next block
#TODO: Try to factor this out to reduce time spent in syscalls.
self.fp.seek(offset + head_size + add_size)
def _read_struct(self, fmt):
"""Simplifies the process of extracting a struct from the open file."""
return fmt.unpack(self.fp.read(fmt.size))
def _check_crc(self, data, crc):
"""Check some data against a stored CRC.
Note: For header CRCs, RAR calculates a CRC32 and then throws out the high-order bytes.
@bug: This method of parsing is deprecated.
@todo: I've only tested this out on 2-byte CRCs, not 4-byte file data CRCs.
@todo: Isn't there some better way to do the check for CRC bitwidth?
@bug: Figure out why I can't get a match on valid File Header CRCs.
"""
if isinstance(crc, int):
if crc < 65536:
crc = struct.pack('>H', crc)
else:
crc = struct.pack('>L', crc)
return struct.pack('>L',zlib.crc32(data)).endswith(crc)
def infolist(self):
"""Return a list of L{RarInfo} instances for the files in the archive."""
return self.filelist
def namelist(self):
"""Return a list of filenames for the files in the archive."""
return [x.filename for x in self.filelist]
def findRarHeader(handle, limit=FIND_LIMIT):
"""Searches a file-like object for a RAR header.
@returns: The in-file offset of the first byte after the header block or
C{None} if no RAR header was found.
@warning: The given file-like object must support C{seek()} up to the size
of C{limit}.
@note: C{limit} is rounded up to the nearest multiple of L{CHUNK_SIZE}.
@todo: Audit this to ensure it can't raise an exception L{is_rarfile()}
won't catch.
"""
startPos, chunk = handle.tell(), ""
limit = math.ceil(limit / float(CHUNK_SIZE)) * CHUNK_SIZE
# Find the RAR header and line up for further reads. (Support SFX bundles)
while True:
temp = handle.read(CHUNK_SIZE)
curr_pos = handle.tell()
# If we hit the end of the file without finding a RAR marker block...
if not temp or (limit > 0 and curr_pos > limit):
handle.seek(startPos)
return None
chunk += temp
marker_offset = chunk.find(MARKER_BLOCK)
if marker_offset > -1:
handle.seek(startPos)
return curr_pos - len(chunk) + marker_offset + len(MARKER_BLOCK)
# Obviously we haven't found the marker yet...
chunk = chunk[len(temp):] # Use a rolling window to minimize memory consumption.
def is_rarfile(filename, limit=FIND_LIMIT):
"""Convenience wrapper for L{findRarHeader} equivalent to C{is_zipfile}.
Returns C{True} if C{filename} is a valid RAR file based on its magic
number, otherwise returns C{False}.
Optionally takes a limiting value for the maximum amount of data to sift
through. Defaults to L{FIND_LIMIT} to set a sane bound on performance. Set
it to 0 to perform an exhaustive search for a RAR header.
@note: findRarHeader rounds this limit up to the nearest multiple of
L{CHUNK_SIZE}.
"""
try:
handle = file(filename, 'rb')
return findRarHeader(handle, limit) is not None
except IOError:
pass
return False
if __name__ == '__main__':
from optparse import OptionParser
parser = OptionParser(description=__doc__.split('\n\n')[0],
version="%%prog v%s" % __version__, usage="%prog <path> ...")
opts, args = parser.parse_args()
if args:
RarFile.debug = 1
for fpath in args:
print "File: %s" % fpath
if is_rarfile(fpath):
for line in RarFile(fpath).namelist():
print "\t%s" % line
else:
print "Not a RAR file"
| 41.77937 | 127 | 0.646183 |
1588a4c8fc8dec91174e5dd32a884294dd46addb | 23,832 | py | Python | tests/conftest.py | iMajna/nipyapi | 5480af8fe8c6b470249837835cb1a067abb6678e | [
"Apache-2.0"
] | null | null | null | tests/conftest.py | iMajna/nipyapi | 5480af8fe8c6b470249837835cb1a067abb6678e | [
"Apache-2.0"
] | 1 | 2020-03-16T10:02:46.000Z | 2020-03-16T13:37:42.000Z | tests/conftest.py | iMajna/nipyapi | 5480af8fe8c6b470249837835cb1a067abb6678e | [
"Apache-2.0"
] | null | null | null | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Configuration fixtures for pytest for `nipyapi` package."""
from __future__ import absolute_import
import logging
import pytest
from os import environ, path
from collections import namedtuple
from time import sleep
import nipyapi
log = logging.getLogger(__name__)
# Test Suite Controls
test_default = True # Default to True for release
test_security = False # Default to False for release
test_regression = False # Default to False for release
# Test Configuration parameters
test_host = nipyapi.config.default_host
test_basename = "nipyapi_test"
test_pg_name = test_basename + "_ProcessGroup"
test_another_pg_name = test_basename + "_AnotherProcessGroup"
test_registry_client_name = test_basename + "_reg_client"
test_processor_name = test_basename + "_proc"
test_bucket_name = test_basename + "_bucket"
test_versioned_flow_name = test_basename + "_ver_flow"
test_cloned_ver_flow_name = test_basename + '_cloned_ver_flow'
test_variable_registry_entry = [
(test_basename + '_name', test_basename + '_name' + '_value')
]
test_write_file_path = test_basename + '_fs_write_dir'
test_read_file_path = test_basename + '_fs_read_dir'
test_write_file_name = test_basename + '_fs_write_file'
test_ver_export_tmpdir = test_basename + '_ver_flow_dir'
test_ver_export_filename = test_basename + "_ver_flow_export"
test_parameter_context_name = test_basename + "_parameter_context"
test_user_name = test_basename + '_user'
test_user_group_name = test_basename + '_user_group'
test_resource_dir = 'resources'
# Test template filenames should match the template PG name
test_templates = {
'basic': test_basename + 'Template_00',
'greedy': test_basename + 'Template_00_greedy',
'complex': test_basename + 'Template_01'
}
# Determining test environment
# Can't use skiptest with parametrize for Travis
# Mostly because loading up all the environments takes too long
default_nifi_endpoints = ['http://' + test_host + ':8080/nifi-api']
regress_nifi_endpoints = [
'http://' + test_host + ':10112/nifi-api',
'http://' + test_host + ':10120/nifi-api',
'http://' + test_host + ':10180/nifi-api',
'http://' + test_host + ':10192/nifi-api',
]
secure_nifi_endpoints = ['https://' + test_host + ':8443/nifi-api']
default_registry_endpoints = [
('http://' + test_host + ':18080/nifi-registry-api',
'http://registry:18080',
'http://' + test_host + ':8080/nifi-api'
)
]
regress_registry_endpoints = [
('http://' + test_host + ':18010/nifi-registry-api',
'http://registry-010:18010',
'http://' + test_host + ':8080/nifi-api'
),
('http://' + test_host + ':18030/nifi-registry-api',
'http://registry-030:18030',
'http://' + test_host + ':10192/nifi-api'
)
]
secure_registry_endpoints = [
('https://' + test_host + ':18443/nifi-registry-api',
'https://secure-registry:18443',
'https://' + test_host + ':8443/nifi-api'
)]
if "TRAVIS" in environ and environ["TRAVIS"] == "true":
log.info("Running tests on TRAVIS, skipping regression suite")
nifi_test_endpoints = default_nifi_endpoints
registry_test_endpoints = default_registry_endpoints
else:
log.info("Running tests on NOT TRAVIS, enabling regression suite")
# Note that these endpoints are assumed to be available
# look in Nipyapi/test_env_config/docker_compose_full_test for
# convenient Docker configs and port mappings.
# NOTE: it is important that the latest version is the last in the list
# So that after a parametrized test we leave the single tests against
# The latest release without bulking the test suite ensuring they change
# back each time.
nifi_test_endpoints = []
registry_test_endpoints = []
if test_default:
nifi_test_endpoints += default_nifi_endpoints
registry_test_endpoints += default_registry_endpoints
if test_regression:
nifi_test_endpoints += regress_nifi_endpoints
registry_test_endpoints += regress_registry_endpoints
if test_security:
nifi_test_endpoints += secure_nifi_endpoints
registry_test_endpoints += secure_registry_endpoints
# 'regress' generates tests against previous versions of NiFi or sub-projects.
# If you are using regression, note that you have to create NiFi objects within
# the Test itself. This is because the fixture is generated before the
# PyTest parametrize call, making the order
# new test_func > fixtures > parametrize > run_test_func > teardown > next
def pytest_generate_tests(metafunc):
log.info("Metafunc Fixturenames are %s", metafunc.fixturenames)
if 'regress_nifi' in metafunc.fixturenames:
log.info("NiFi Regression testing requested for ({0})."
.format(metafunc.function.__name__))
metafunc.parametrize(
argnames='regress_nifi',
argvalues=nifi_test_endpoints,
indirect=True
)
elif 'regress_flow_reg' in metafunc.fixturenames:
log.info("NiFi Flow Registry Regression testing requested for ({0})."
.format(metafunc.function.__name__))
metafunc.parametrize(
argnames='regress_flow_reg',
argvalues=registry_test_endpoints,
indirect=True
)
# Note that it's important that the regress function is the first called if
# you are stacking fixtures
@pytest.fixture(scope="function")
def regress_nifi(request):
log.info("NiFi Regression test setup called against endpoint %s",
request.param)
nipyapi.utils.set_endpoint(request.param, True, True)
def remove_test_registry_client():
_ = [nipyapi.versioning.delete_registry_client(li) for
li in nipyapi.versioning.list_registry_clients().registries
if test_registry_client_name in li.component.name
]
def ensure_registry_client(uri):
try:
client = nipyapi.versioning.create_registry_client(
name=test_registry_client_name + uri,
uri=uri,
description=uri
)
except ValueError as e:
if 'already exists with the name' in str(e):
client = nipyapi.versioning.get_registry_client(
identifier=test_registry_client_name + uri
)
else:
raise e
if isinstance(client, nipyapi.nifi.RegistryClientEntity):
return client
else:
raise ValueError("Could not create Registry Client")
@pytest.fixture(scope="function")
def regress_flow_reg(request):
log.info("NiFi-Registry regression test called against endpoints %s",
request.param)
# Set Registry connection
nipyapi.utils.set_endpoint(request.param[0], True, True)
# Set paired NiFi connection
nipyapi.utils.set_endpoint(request.param[2], True, True)
# because pytest won't let you easily cascade parameters through fixtures
# we set the docker URI in the config for retrieval later on
nipyapi.config.registry_local_name = request.param[1]
# Tests that the Docker test environment is available before running test suite
@pytest.fixture(scope="session", autouse=True)
def session_setup(request):
log.info("Commencing test session setup")
for url in nifi_test_endpoints + [x[0] for x in registry_test_endpoints]:
log.debug("Now Checking URL [{0}]".format(url))
nipyapi.utils.set_endpoint(url, ssl=True, login=True)
# ssl and login will only work if https is in the url, else will silently skip
gui_url = url.replace('-api', '')
if not nipyapi.utils.wait_to_complete(
nipyapi.utils.is_endpoint_up,
gui_url,
nipyapi_delay=nipyapi.config.long_retry_delay,
nipyapi_max_wait=nipyapi.config.long_max_wait):
pytest.exit(
"Expected Service endpoint ({0}) is not responding"
.format(gui_url)
)
# Test API client connection
if 'nifi-api' in url:
if not nipyapi.canvas.get_root_pg_id():
raise ValueError("No Response from NiFi test call")
# that should've created a new API client connection
api_host = nipyapi.config.nifi_config.api_client.host
if api_host != url:
raise ValueError("Client expected [{0}], but got [{1}] "
"instead".format(url, api_host))
log.info("Tested NiFi client connection, got response from %s",
url)
if 'https://' in url:
nipyapi.security.bootstrap_security_policies(service='nifi')
cleanup_nifi()
elif 'nifi-registry-api' in url:
if nipyapi.registry.FlowsApi().get_available_flow_fields():
log.info("Tested NiFi-Registry client connection, got "
"response from %s", url)
if 'https://' in url:
nipyapi.security.bootstrap_security_policies(service='registry')
cleanup_reg()
else:
raise ValueError("No Response from NiFi-Registry test call"
)
else:
raise ValueError("Bad API Endpoint")
request.addfinalizer(final_cleanup)
log.info("Completing Test Session Setup")
def remove_test_templates():
all_templates = nipyapi.templates.list_all_templates(native=False)
if all_templates is not None:
for this_template in all_templates:
if test_basename in this_template.template.name:
nipyapi.templates.delete_template(this_template.id)
def remove_test_pgs():
_ = [
nipyapi.canvas.delete_process_group(x, True, True)
for x in nipyapi.nifi.ProcessGroupsApi().get_process_groups('root').process_groups
if test_basename in x.status.name
]
def remove_test_processors():
_ = [
nipyapi.canvas.delete_processor(x, force=True)
for x in nipyapi.canvas.list_all_processors()
if test_basename in x.status.name
]
def remove_test_funnels():
# Note that Funnels cannot be given labels so scoping is by PG only
remove_test_connections()
_ = [
nipyapi.canvas.delete_funnel(x)
for x in nipyapi.canvas.list_all_funnels()
]
def remove_test_parameter_contexts():
if nipyapi.utils.check_version('1.10.0') < 1:
_ = [
nipyapi.parameters.delete_parameter_context(li) for li
in nipyapi.parameters.list_all_parameter_contexts() if
test_basename in li.component.name
]
else:
log.info("NiFi version is older than 1.10, skipping Parameter Context cleanup")
def remove_test_buckets():
_ = [nipyapi.versioning.delete_registry_bucket(li) for li
in nipyapi.versioning.list_registry_buckets() if
test_bucket_name in li.name]
def final_cleanup():
for url in nifi_test_endpoints + [x[0] for x in registry_test_endpoints]:
nipyapi.utils.set_endpoint(url, True, True)
if 'nifi-api' in url:
cleanup_nifi()
elif 'nifi-registry-api' in url:
cleanup_reg()
def remove_test_service_users(service='both'):
nifi_test_users = [
x for x in
nipyapi.security.list_service_users('nifi')
if x.component.identity.startswith(test_basename)
]
reg_test_users = [
x for x in
nipyapi.security.list_service_users('registry')
if x.identity.startswith(test_basename)
]
if service != 'registry':
_ = [
nipyapi.security.remove_service_user(x, 'nifi')
for x in nifi_test_users
]
if service != 'nifi':
_ = [
nipyapi.security.remove_service_user(x, 'registry')
for x in reg_test_users
]
def remove_test_service_user_groups(service='both'):
nifi_test_user_groups = [
x for x in
nipyapi.security.list_service_user_groups('nifi')
if x.component.identity.startswith(test_basename)
]
reg_test_user_groups = [
x for x in
nipyapi.security.list_service_user_groups('registry')
if x.identity.startswith(test_basename)
]
if service != 'registry':
_ = [
nipyapi.security.remove_service_user_group(x, 'nifi')
for x in nifi_test_user_groups
]
if service != 'nifi':
_ = [
nipyapi.security.remove_service_user_group(x, 'registry')
for x in reg_test_user_groups
]
def cleanup_nifi():
# Only bulk-cleanup universally compatible components
# Ideally we would clean each test environment, but it's too slow to do it
# per test, so we rely on individual fixture cleanup
log.info("Bulk cleanup called on host %s",
nipyapi.config.nifi_config.host)
remove_test_templates()
remove_test_pgs()
remove_test_connections()
remove_test_controllers()
remove_test_processors()
remove_test_ports()
remove_test_funnels()
remove_test_rpgs()
remove_test_parameter_contexts()
if test_security and 'https' in nipyapi.nifi.configuration.host:
remove_test_service_user_groups('nifi')
remove_test_service_users('nifi')
def remove_test_rpgs():
_ = [
nipyapi.canvas.delete_remote_process_group(x)
for x in nipyapi.canvas.list_all_remote_process_groups()
]
def remove_test_connections():
# Funnels don't have a name, have to go by type
_ = [
nipyapi.canvas.delete_connection(x, True)
for x in nipyapi.canvas.list_all_connections()
if x.destination_type == 'FUNNEL'
or x.source_type == 'FUNNEL'
or test_basename in x.component.name
]
def remove_test_ports():
_ = [
nipyapi.canvas.delete_port(x)
for x in nipyapi.canvas.list_all_by_kind('input_ports')
if test_basename in x.component.name
]
_ = [
nipyapi.canvas.delete_port(x)
for x in nipyapi.canvas.list_all_by_kind('output_ports')
if test_basename in x.component.name
]
def remove_test_controllers():
_ = [nipyapi.canvas.delete_controller(li, True) for li
in nipyapi.canvas.list_all_controllers() if
test_basename in li.component.name]
def cleanup_reg():
# Bulk cleanup for tests involving NiFi Registry
remove_test_pgs()
remove_test_buckets()
remove_test_registry_client()
if test_security and 'https' in nipyapi.registry.configuration.host:
remove_test_service_user_groups('registry')
remove_test_service_users('registry')
@pytest.fixture(name='fix_templates', scope='function')
def fixture_templates(request, fix_pg):
log.info("Creating PyTest Fixture fix_templates on endpoint %s",
nipyapi.config.nifi_config.host)
FixtureTemplates = namedtuple(
'FixtureTemplates', ('pg', 'b_file', 'b_name', 'c_file',
'c_name', 'g_name', 'g_file')
)
f_pg = fix_pg
f_b_file = path.join(
path.dirname(__file__),
test_resource_dir,
test_templates['basic'] + '.xml'
)
f_b_name = 'nipyapi_testTemplate_00'
f_c_file = path.join(
path.dirname(__file__),
test_resource_dir,
test_templates['complex'] + '.xml'
)
f_c_name = 'nipyapi_testTemplate_01'
f_g_file = path.join(
path.dirname(__file__),
test_resource_dir,
test_templates['greedy'] + '.xml'
)
f_g_name = 'nipyapi_testTemplate_00_greedy'
out = FixtureTemplates(
pg=f_pg,
b_name=f_b_name,
c_name=f_c_name,
g_name=f_g_name,
b_file=f_b_file,
g_file=f_g_file,
c_file=f_c_file
)
request.addfinalizer(remove_test_templates)
log.info("- Returning PyTest Fixture fix_templates")
return out
@pytest.fixture(name='fix_pg')
def fixture_pg(request):
class Dummy:
def __init__(self):
pass
def generate(self, parent_pg=None, suffix=''):
if parent_pg is None:
target_pg = nipyapi.canvas.get_process_group(
nipyapi.canvas.get_root_pg_id(), 'id'
)
else:
target_pg = parent_pg
return nipyapi.canvas.create_process_group(
target_pg,
test_pg_name + suffix,
location=(400.0, 400.0)
)
request.addfinalizer(remove_test_pgs)
return Dummy()
@pytest.fixture(name='fix_proc')
def fixture_proc(request):
class Dummy:
def __init__(self):
pass
def generate(self, parent_pg=None, suffix='', kind=None, config=None):
if parent_pg is None:
target_pg = nipyapi.canvas.get_process_group(
nipyapi.canvas.get_root_pg_id(), 'id'
)
else:
target_pg = parent_pg
kind = kind if kind else 'GenerateFlowFile'
return nipyapi.canvas.create_processor(
parent_pg=target_pg,
processor=nipyapi.canvas.get_processor_type(
kind),
location=(400.0, 400.0),
name=test_processor_name + suffix,
config=nipyapi.nifi.ProcessorConfigDTO(
scheduling_period='1s',
auto_terminated_relationships=['success']
)
)
request.addfinalizer(remove_test_processors)
return Dummy()
@pytest.fixture(name='fix_context')
def fixture_context(request):
class Dummy:
def __init__(self):
pass
def generate(self, name=test_parameter_context_name):
return nipyapi.parameters.create_parameter_context(name)
request.addfinalizer(remove_test_parameter_contexts)
return Dummy()
@pytest.fixture(name='fix_funnel')
def fixture_funnel(request):
class Dummy:
def __init__(self):
pass
def generate(self, parent_pg=None, position=(400, 400)):
if parent_pg is None:
target_pg = nipyapi.canvas.get_process_group(
nipyapi.canvas.get_root_pg_id(), 'id'
)
else:
target_pg = parent_pg
return nipyapi.canvas.create_funnel(target_pg.id, position)
request.addfinalizer(remove_test_funnels)
return Dummy()
@pytest.fixture(name='fix_bucket', scope='function')
def fixture_bucket(request):
class Dummy:
def __init__(self):
pass
def __call__(self, name=test_bucket_name, suffix=''):
return nipyapi.versioning.create_registry_bucket(
name + suffix
)
request.addfinalizer(remove_test_buckets)
return Dummy()
@pytest.fixture(name='fix_ver_flow', scope='function')
def fixture_ver_flow(request, fix_bucket, fix_pg, fix_proc):
log.info("Starting setup of Fixture fix_ver_flow")
FixtureVerFlow = namedtuple(
'FixtureVerFlow', ('client', 'bucket', 'pg', 'proc', 'info',
'flow', 'snapshot', 'dto')
)
f_reg_client = ensure_registry_client(nipyapi.config.registry_local_name)
f_pg = fix_pg.generate()
f_bucket = fix_bucket()
f_proc = fix_proc.generate(parent_pg=f_pg)
f_info = nipyapi.versioning.save_flow_ver(
process_group=f_pg,
registry_client=f_reg_client,
bucket=f_bucket,
flow_name=test_versioned_flow_name,
comment='NiPyApi Test',
desc='NiPyApi Test'
)
sleep(0.5)
f_flow = nipyapi.versioning.get_flow_in_bucket(
bucket_id=f_bucket.identifier,
identifier=f_info.version_control_information.flow_id,
identifier_type='id'
)
f_snapshot = nipyapi.versioning.get_latest_flow_ver(
f_bucket.identifier,
f_flow.identifier
)
f_dto = ('registry', 'VersionedFlowSnapshot')
request.addfinalizer(cleanup_reg)
log.info("Finished setting up Fixture fix_ver_flow")
return FixtureVerFlow(
client=f_reg_client,
bucket=f_bucket,
pg=f_pg,
proc=f_proc,
info=f_info,
flow=f_flow,
snapshot=f_snapshot,
dto=f_dto
)
@pytest.fixture(name='fix_flow_serde', scope='function')
def fixture_flow_serde(request, tmpdir, fix_ver_flow):
FixtureFlowSerde = namedtuple(
'FixtureFlowSerde',
getattr(fix_ver_flow, '_fields') + ('filepath', 'json', 'yaml', 'raw')
)
f_filepath = str(tmpdir.mkdir(test_ver_export_tmpdir)
.join(test_ver_export_filename))
f_raw = nipyapi.versioning.get_flow_version(
bucket_id=fix_ver_flow.bucket.identifier,
flow_id=fix_ver_flow.flow.identifier,
export=True
)
f_json = nipyapi.versioning.export_flow_version(
bucket_id=fix_ver_flow.bucket.identifier,
flow_id=fix_ver_flow.flow.identifier,
file_path=f_filepath + '.json',
mode='json'
)
f_yaml = nipyapi.versioning.export_flow_version(
bucket_id=fix_ver_flow.bucket.identifier,
flow_id=fix_ver_flow.flow.identifier,
file_path=f_filepath + '.yaml',
mode='yaml'
)
request.addfinalizer(cleanup_reg)
return FixtureFlowSerde(
*fix_ver_flow,
filepath=f_filepath,
json=f_json,
yaml=f_yaml,
raw=f_raw
)
@pytest.fixture(name='fix_cont', scope='function')
def fixture_controller(request):
class Dummy:
def __init__(self):
pass
def __call__(self, parent_pg=None, kind=None):
if parent_pg is None:
target_pg = nipyapi.canvas.get_process_group(
nipyapi.canvas.get_root_pg_id(), 'id'
)
else:
target_pg = parent_pg
kind = kind if kind else 'DistributedMapCacheClientService'
cont_type = [
x for x in nipyapi.canvas.list_all_controller_types()
if kind in x.type
][0]
c_1 = nipyapi.canvas.create_controller(
parent_pg=target_pg,
controller=cont_type
)
c_2 = nipyapi.canvas.update_controller(
c_1,
nipyapi.nifi.ControllerServiceDTO(
name=test_basename + c_1.component.name
)
)
return c_2
request.addfinalizer(remove_test_controllers)
return Dummy()
@pytest.fixture(name='fix_users', scope='function')
def fixture_users(request):
class Dummy:
def __init__(self):
pass
def __call__(self, name=test_user_name, suffix=''):
return (
nipyapi.security.create_service_user(name + suffix),
nipyapi.security.create_service_user(name + suffix, 'registry')
)
request.addfinalizer(remove_test_service_users)
return Dummy()
@pytest.fixture(name='fix_user_groups', scope='function')
def fixture_user_groups(request, fix_users):
class Dummy:
def __init__(self):
pass
def __call__(self, name=test_user_group_name, suffix=''):
n_user, r_user = fix_users()
return (
nipyapi.security.create_service_user_group(
name + suffix, service='nifi', users=[n_user]),
nipyapi.security.create_service_user_group(
name + suffix, service='registry', users=[r_user])
)
request.addfinalizer(remove_test_service_user_groups)
return Dummy()
| 34.489146 | 90 | 0.642707 |
a2883339c046d6caa326d2d2e642068f9d2e2994 | 1,081 | py | Python | src/interface/main.py | NikolaTesla13/Hackerman-chat | 8422a1ee45a08231c83572a8926ba571d3e29146 | [
"MIT"
] | null | null | null | src/interface/main.py | NikolaTesla13/Hackerman-chat | 8422a1ee45a08231c83572a8926ba571d3e29146 | [
"MIT"
] | null | null | null | src/interface/main.py | NikolaTesla13/Hackerman-chat | 8422a1ee45a08231c83572a8926ba571d3e29146 | [
"MIT"
] | null | null | null | import sys
import string
import random
import requests
import pretty_errors
args = []
other_token = ""
my_token = ""
status = None
def generate_token():
token = ""
for i in range(0, 20):
token += random.choice(string.ascii_letters + string.digits)
return token
if __name__ == "__main__":
args = sys.argv
if len(args) == 2:
other_token = args[1]
my_token = generate_token()
print("Your token is " + my_token)
if other_token == "":
print("Enter your friend's token: ", end="")
other_token = input()
if other_token != "":
status = requests.get("http://127.0.0.1:5000/add/"+my_token+"/"+other_token)
if status.status_code == 200:
print("Connected sucsessfully!")
else:
status = requests.get("http://127.0.0.1:5000/check/"+my_token)
if status.text != 404:
other_token = status.text
print("Connected sucsessfully! Your friend token is " + other_token)
else:
print("Error finding friend!")
sys.exit(-1)
| 24.022222 | 84 | 0.592044 |
033ed341967cbdcafb87f52cee71b1b9bc88a026 | 497 | py | Python | env/lib/python3.8/site-packages/plotly/validators/scattergl/_xaxis.py | acrucetta/Chicago_COVI_WebApp | a37c9f492a20dcd625f8647067394617988de913 | [
"MIT",
"Unlicense"
] | 76 | 2020-07-06T14:44:05.000Z | 2022-02-14T15:30:21.000Z | env/lib/python3.8/site-packages/plotly/validators/scattergl/_xaxis.py | acrucetta/Chicago_COVI_WebApp | a37c9f492a20dcd625f8647067394617988de913 | [
"MIT",
"Unlicense"
] | 11 | 2020-08-09T02:30:14.000Z | 2022-03-12T00:50:14.000Z | env/lib/python3.8/site-packages/plotly/validators/scattergl/_xaxis.py | acrucetta/Chicago_COVI_WebApp | a37c9f492a20dcd625f8647067394617988de913 | [
"MIT",
"Unlicense"
] | 11 | 2020-07-12T16:18:07.000Z | 2022-02-05T16:48:35.000Z | import _plotly_utils.basevalidators
class XaxisValidator(_plotly_utils.basevalidators.SubplotidValidator):
def __init__(self, plotly_name="xaxis", parent_name="scattergl", **kwargs):
super(XaxisValidator, self).__init__(
plotly_name=plotly_name,
parent_name=parent_name,
dflt=kwargs.pop("dflt", "x"),
edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"),
role=kwargs.pop("role", "info"),
**kwargs
)
| 35.5 | 79 | 0.641851 |
d8cfee4089c96d7f7a68007b0367260a4f424572 | 4,016 | py | Python | Assets/PrefixAllAssets.py | ChinaArvin/UnrealEditorPythonScripts | 3bed2f3e1cf7f0ce93eac13726a18b3094e63145 | [
"MIT"
] | 414 | 2019-01-23T10:54:47.000Z | 2022-03-31T02:58:18.000Z | Assets/PrefixAllAssets.py | ChinaArvin/UnrealEditorPythonScripts | 3bed2f3e1cf7f0ce93eac13726a18b3094e63145 | [
"MIT"
] | 3 | 2019-08-29T21:42:21.000Z | 2022-01-04T04:05:02.000Z | Assets/PrefixAllAssets.py | ColaTAL/UnrealEditorPythonScripts | b4478befb4764cae95ddc09bb7c6b3a23155e987 | [
"MIT"
] | 161 | 2019-01-21T08:55:44.000Z | 2022-03-31T02:58:22.000Z | # _
# (_)
# _ __ ___ __ _ _ __ ___ ___ _ __ _ ___ _ __ ___
# | '_ ` _ \ / _` | '_ ` _ \ / _ \| '_ \| |/ _ \ '_ ` _ \
# | | | | | | (_| | | | | | | (_) | | | | | __/ | | | | |
# |_| |_| |_|\__,_|_| |_| |_|\___/|_| |_|_|\___|_| |_| |_|
# www.mamoniem.com
# www.ue4u.xyz
#Copyright 2021 Muhammad A.Moniem (@_mamoniem). All Rights Reserved.
#
import unreal
#You can set the prefix of your choice here
prefixAnimationBlueprint = "animBP"
prefixAnimationSequence = "anim"
prefixAnimation = "anim"
prefixBlendSpace = "animBlnd"
prefixBlueprint = "bp"
prefixCurveFloat = "crvF"
prefixCurveLinearColor = "crvL"
prefixLevel = "lvl"
prefixMaterial = "mat"
prefixMaterialFunction = "mat_func"
prefixMaterialInstance = "mat_inst"
prefixParticleSystem = "fx"
prefixPhysicsAsset = "phsx"
prefixSkeletalMesh = "sk"
prefixSkeleton = "skln"
prefixSoundCue = "cue"
prefixSoundWave = "wv"
prefixStaticMesh = "sm"
prefixTexture2D = "tex"
prefixTextureCube = "HDRI"
workingPath = "/Game/"
@unreal.uclass()
class GetEditorAssetLibrary(unreal.EditorAssetLibrary):
pass
def GetProperPrefix(className):
_prefix = ""
if className == "AnimBlueprint":
_prefix = prefixAnimationBlueprint
elif className == "AnimSequence":
_prefix = prefixAnimationSequence
elif className == "Animation":
_prefix = prefixAnimation
elif className == "BlendSpace1D":
_prefix = prefixBlendSpace
elif className == "Blueprint":
_prefix = prefixBlueprint
elif className == "CurveFloat":
_prefix = prefixCurveFloat
elif className == "CurveLinearColor":
_prefix = prefixCurveLinearColor
elif className == "Material":
_prefix = prefixMaterial
elif className == "MaterialFunction":
_prefix = prefixMaterialFunction
elif className == "MaterialInstance":
_prefix = prefixMaterialInstance
elif className == "ParticleSystem":
_prefix = prefixParticleSystem
elif className == "PhysicsAsset":
_prefix = prefixPhysicsAsset
elif className == "SkeletalMesh":
_prefix = prefixSkeletalMesh
elif className == "Skeleton":
_prefix = prefixSkeleton
elif className == "SoundCue":
_prefix = prefixSoundCue
elif className == "SoundWave":
_prefix = prefixSoundWave
elif className == "StaticMesh":
_prefix = prefixStaticMesh
elif className == "Texture2D":
_prefix = prefixTexture2D
elif className == "TextureCube":
_prefix = prefixTextureCube
else:
_prefix = ""
return _prefix
editorAssetLib = GetEditorAssetLibrary()
allAssets = editorAssetLib.list_assets(workingPath, True, False)
allAssetsCount = len(allAssets)
selectedAssetPath = workingPath
with unreal.ScopedSlowTask(allAssetsCount, selectedAssetPath) as slowTask:
slowTask.make_dialog(True)
for asset in allAssets:
_assetData = editorAssetLib.find_asset_data(asset)
_assetName = _assetData.get_asset().get_name()
_assetPathName = _assetData.get_asset().get_path_name()
_assetPathOnly = _assetPathName.replace((_assetName + "." + _assetName), "")
_assetClassName = _assetData.get_asset().get_class().get_name()
_assetPrefix = GetProperPrefix(_assetClassName)
if _assetPrefix in _assetName:
continue
elif _assetPrefix == "":
continue
else:
_targetPathName = _assetPathOnly + ("%s%s%s%s%s%s%s" % (_assetPrefix, "_", _assetName, ".", _assetPrefix, "_", _assetName))
editorAssetLib.rename_asset(_assetPathName, _targetPathName)
print (">>> Renaming [%s] to [%s]" % (_assetPathName, _targetPathName))
if slowTask.should_cancel():
break
slowTask.enter_progress_frame(1, asset) | 34.033898 | 135 | 0.626992 |
9c6bc99833193bf2b0aa8290d9c5cda0ff3c26d3 | 274 | py | Python | modules/mod_reload.py | crdx/face | d2980e3ab47934ab7c8097c37f18abad6a96aa06 | [
"MIT"
] | null | null | null | modules/mod_reload.py | crdx/face | d2980e3ab47934ab7c8097c37f18abad6a96aa06 | [
"MIT"
] | null | null | null | modules/mod_reload.py | crdx/face | d2980e3ab47934ab7c8097c37f18abad6a96aa06 | [
"MIT"
] | null | null | null | name = "Module reloader"
desc = "Reloads modules"
def on_pubmsg(p):
words = p.event.arguments[0].split()
if words[0] == "!r":
p.connection.privmsg(p.event.target, "Rehashing")
p.face.reload()
# we've handled this event
return True
| 21.076923 | 57 | 0.59854 |
a6e8d7ce89f10d0b16487484edb33a34f47a26da | 3,215 | py | Python | auth0/v3/management/rules.py | mdornseif/auth0-python | e87afb3754a1a10fef2c9197df1e3a7681c9eb61 | [
"MIT"
] | null | null | null | auth0/v3/management/rules.py | mdornseif/auth0-python | e87afb3754a1a10fef2c9197df1e3a7681c9eb61 | [
"MIT"
] | null | null | null | auth0/v3/management/rules.py | mdornseif/auth0-python | e87afb3754a1a10fef2c9197df1e3a7681c9eb61 | [
"MIT"
] | null | null | null | from .rest import RestClient
class Rules(object):
"""Rules endpoint implementation.
Args:
domain (str): Your Auth0 domain, e.g: 'username.auth0.com'
token (str): Management API v2 Token
telemetry (bool, optional): Enable or disable Telemetry
(defaults to True)
"""
def __init__(self, domain, token, telemetry=True):
self.domain = domain
self.client = RestClient(jwt=token, telemetry=telemetry)
def _url(self, id=None):
url = 'https://%s/api/v2/rules' % self.domain
if id is not None:
return url + '/' + id
return url
def all(self, stage='login_success', enabled=True, fields=[],
include_fields=True):
"""Retrieves a list of all rules.
Args:
enabled (bool, optional): If provided, retrieves rules that match
the value, otherwise all rules are retrieved.
fields (list, optional): A list of fields to include or exclude
(depending on include_fields) from the result, empty to
retrieve all fields.
include_fields (bool, optional): True if the fields specified are
to be included in the result, False otherwise
(defaults to true).
stage (str, optional): Retrieves rules that match the execution
stage (defaults to login_success).
"""
params = {'fields': ','.join(fields) or None,
'include_fields': str(include_fields).lower(),
'stage': stage}
if enabled != None:
params['enabled'] = str(enabled).lower()
return self.client.get(self._url(), params=params)
def create(self, body):
"""Creates a new rule.
Args:
body (dict): Attributes for the newly created rule,
please see: https://auth0.com/docs/api/v2#!/Rules/post_rules
"""
return self.client.post(self._url(), data=body)
def get(self, id, fields=[], include_fields=True):
"""Retrieves a rule by its ID.
Args:
id (str): The id of the rule to retrieve.
fields (list, optional): A list of fields to include or exclude
(depending on include_fields) from the result, empty to
retrieve all fields.
include_fields (bool, optional): True if the fields specified are
to be included in the result, False otherwise
(defaults to true).
"""
params = {'fields': ','.join(fields) or None,
'include_fields': str(include_fields).lower()}
return self.client.get(self._url(id), params=params)
def delete(self, id):
"""Delete a rule.
Args:
id (str): The id of the rule to delete.
"""
return self.client.delete(self._url(id))
def update(self, id, body):
"""Update an existing rule
Args:
id (str): The id of the rule to modify.
body (dict): Please see: https://auth0.com/docs/api/v2#!/Rules/patch_rules_by_id
"""
return self.client.patch(self._url(id), data=body)
| 32.15 | 92 | 0.570762 |
a96d98149365a6eeece426ca15a19325bddcf684 | 5,035 | py | Python | Packages/matplotlib-2.2.2/lib/mpl_examples/lines_bars_and_markers/psd_demo.py | NightKirie/NCKU_NLP_2108_industry3 | 23ac13644b140587e23cfeffb114c7c6f46f17a2 | [
"MIT"
] | 1 | 2018-06-11T07:36:04.000Z | 2018-06-11T07:36:04.000Z | Packages/matplotlib-2.2.2/lib/mpl_examples/lines_bars_and_markers/psd_demo.py | NightKirie/NCKU_NLP_2108_industry3 | 23ac13644b140587e23cfeffb114c7c6f46f17a2 | [
"MIT"
] | null | null | null | Packages/matplotlib-2.2.2/lib/mpl_examples/lines_bars_and_markers/psd_demo.py | NightKirie/NCKU_NLP_2108_industry3 | 23ac13644b140587e23cfeffb114c7c6f46f17a2 | [
"MIT"
] | 4 | 2018-05-19T11:31:20.000Z | 2018-07-01T20:58:29.000Z | """
========
Psd Demo
========
Plotting Power Spectral Density (PSD) in Matplotlib.
The PSD is a common plot in the field of signal processing. NumPy has
many useful libraries for computing a PSD. Below we demo a few examples
of how this can be accomplished and visualized with Matplotlib.
"""
import matplotlib.pyplot as plt
import numpy as np
import matplotlib.mlab as mlab
# Fixing random state for reproducibility
np.random.seed(19680801)
dt = 0.01
t = np.arange(0, 10, dt)
nse = np.random.randn(len(t))
r = np.exp(-t / 0.05)
cnse = np.convolve(nse, r) * dt
cnse = cnse[:len(t)]
s = 0.1 * np.sin(2 * np.pi * t) + cnse
plt.subplot(211)
plt.plot(t, s)
plt.subplot(212)
plt.psd(s, 512, 1 / dt)
plt.show()
###############################################################################
# Compare this with the equivalent Matlab code to accomplish the same thing::
#
# dt = 0.01;
# t = [0:dt:10];
# nse = randn(size(t));
# r = exp(-t/0.05);
# cnse = conv(nse, r)*dt;
# cnse = cnse(1:length(t));
# s = 0.1*sin(2*pi*t) + cnse;
#
# subplot(211)
# plot(t,s)
# subplot(212)
# psd(s, 512, 1/dt)
#
# Below we'll show a slightly more complex example that demonstrates
# how padding affects the resulting PSD.
dt = np.pi / 100.
fs = 1. / dt
t = np.arange(0, 8, dt)
y = 10. * np.sin(2 * np.pi * 4 * t) + 5. * np.sin(2 * np.pi * 4.25 * t)
y = y + np.random.randn(*t.shape)
# Plot the raw time series
fig = plt.figure()
fig.subplots_adjust(hspace=0.45, wspace=0.3)
ax = fig.add_subplot(2, 1, 1)
ax.plot(t, y)
# Plot the PSD with different amounts of zero padding. This uses the entire
# time series at once
ax2 = fig.add_subplot(2, 3, 4)
ax2.psd(y, NFFT=len(t), pad_to=len(t), Fs=fs)
ax2.psd(y, NFFT=len(t), pad_to=len(t) * 2, Fs=fs)
ax2.psd(y, NFFT=len(t), pad_to=len(t) * 4, Fs=fs)
plt.title('zero padding')
# Plot the PSD with different block sizes, Zero pad to the length of the
# original data sequence.
ax3 = fig.add_subplot(2, 3, 5, sharex=ax2, sharey=ax2)
ax3.psd(y, NFFT=len(t), pad_to=len(t), Fs=fs)
ax3.psd(y, NFFT=len(t) // 2, pad_to=len(t), Fs=fs)
ax3.psd(y, NFFT=len(t) // 4, pad_to=len(t), Fs=fs)
ax3.set_ylabel('')
plt.title('block size')
# Plot the PSD with different amounts of overlap between blocks
ax4 = fig.add_subplot(2, 3, 6, sharex=ax2, sharey=ax2)
ax4.psd(y, NFFT=len(t) // 2, pad_to=len(t), noverlap=0, Fs=fs)
ax4.psd(y, NFFT=len(t) // 2, pad_to=len(t),
noverlap=int(0.05 * len(t) / 2.), Fs=fs)
ax4.psd(y, NFFT=len(t) // 2, pad_to=len(t),
noverlap=int(0.2 * len(t) / 2.), Fs=fs)
ax4.set_ylabel('')
plt.title('overlap')
plt.show()
###############################################################################
# This is a ported version of a MATLAB example from the signal
# processing toolbox that showed some difference at one time between
# Matplotlib's and MATLAB's scaling of the PSD.
fs = 1000
t = np.linspace(0, 0.3, 301)
A = np.array([2, 8]).reshape(-1, 1)
f = np.array([150, 140]).reshape(-1, 1)
xn = (A * np.sin(2 * np.pi * f * t)).sum(axis=0)
xn += 5 * np.random.randn(*t.shape)
fig, (ax0, ax1) = plt.subplots(ncols=2)
fig.subplots_adjust(hspace=0.45, wspace=0.3)
yticks = np.arange(-50, 30, 10)
yrange = (yticks[0], yticks[-1])
xticks = np.arange(0, 550, 100)
ax0.psd(xn, NFFT=301, Fs=fs, window=mlab.window_none, pad_to=1024,
scale_by_freq=True)
ax0.set_title('Periodogram')
ax0.set_yticks(yticks)
ax0.set_xticks(xticks)
ax0.grid(True)
ax0.set_ylim(yrange)
ax1.psd(xn, NFFT=150, Fs=fs, window=mlab.window_none, pad_to=512, noverlap=75,
scale_by_freq=True)
ax1.set_title('Welch')
ax1.set_xticks(xticks)
ax1.set_yticks(yticks)
ax1.set_ylabel('') # overwrite the y-label added by `psd`
ax1.grid(True)
ax1.set_ylim(yrange)
plt.show()
###############################################################################
# This is a ported version of a MATLAB example from the signal
# processing toolbox that showed some difference at one time between
# Matplotlib's and MATLAB's scaling of the PSD.
#
# It uses a complex signal so we can see that complex PSD's work properly.
prng = np.random.RandomState(19680801) # to ensure reproducibility
fs = 1000
t = np.linspace(0, 0.3, 301)
A = np.array([2, 8]).reshape(-1, 1)
f = np.array([150, 140]).reshape(-1, 1)
xn = (A * np.exp(2j * np.pi * f * t)).sum(axis=0) + 5 * prng.randn(*t.shape)
fig, (ax0, ax1) = plt.subplots(ncols=2)
fig.subplots_adjust(hspace=0.45, wspace=0.3)
yticks = np.arange(-50, 30, 10)
yrange = (yticks[0], yticks[-1])
xticks = np.arange(-500, 550, 200)
ax0.psd(xn, NFFT=301, Fs=fs, window=mlab.window_none, pad_to=1024,
scale_by_freq=True)
ax0.set_title('Periodogram')
ax0.set_yticks(yticks)
ax0.set_xticks(xticks)
ax0.grid(True)
ax0.set_ylim(yrange)
ax1.psd(xn, NFFT=150, Fs=fs, window=mlab.window_none, pad_to=512, noverlap=75,
scale_by_freq=True)
ax1.set_title('Welch')
ax1.set_xticks(xticks)
ax1.set_yticks(yticks)
ax1.set_ylabel('') # overwrite the y-label added by `psd`
ax1.grid(True)
ax1.set_ylim(yrange)
plt.show()
| 28.771429 | 79 | 0.636941 |
15c505a74a81a49bff17b4a0ef55b4fd5b09973e | 17,485 | py | Python | pines/gpr/__init__.py | jpn--/pine | 3980a9f0b09dd36b2fed7e52750847637be5f067 | [
"MIT"
] | 2 | 2017-08-09T02:42:37.000Z | 2020-06-16T14:14:16.000Z | pines/gpr/__init__.py | jpn--/pine | 3980a9f0b09dd36b2fed7e52750847637be5f067 | [
"MIT"
] | null | null | null | pines/gpr/__init__.py | jpn--/pine | 3980a9f0b09dd36b2fed7e52750847637be5f067 | [
"MIT"
] | null | null | null |
from sklearn.linear_model import LinearRegression as _sklearn_LinearRegression
from sklearn.gaussian_process import GaussianProcessRegressor
from sklearn import preprocessing
from sklearn.base import TransformerMixin
from sklearn.gaussian_process.kernels import RBF, ConstantKernel as C, RationalQuadratic as RQ
from sklearn.base import RegressorMixin, BaseEstimator
from sklearn.model_selection import cross_val_score, cross_val_predict
from sklearn.preprocessing import StandardScaler
from sklearn.metrics import r2_score
from sklearn.feature_selection import SelectKBest
from sklearn.feature_selection import f_regression, mutual_info_regression
from sklearn.exceptions import DataConversionWarning
import numpy, pandas
import scipy.stats
import warnings
import contextlib
from pines.attribute_dict import dicta
def feature_concat(*args):
if all(isinstance(a, pandas.DataFrame) for a in args):
return pandas.concat(args, axis=1)
if any(isinstance(a, pandas.DataFrame) for a in args):
ref = 0
while not isinstance(args[ref], pandas.DataFrame):
ref += 1
ix = args[ref].index
return pandas.concat([pandas.DataFrame(a, index=ix) for a in args], axis=1)
return numpy.concatenate(args, axis=1)
class LinearRegression(_sklearn_LinearRegression):
def fit(self, X, y, sample_weight=None):
# print(" LR FIT on",len(X))
super().fit(X, y, sample_weight=sample_weight)
if isinstance(X, pandas.DataFrame):
self.names_ = X.columns.copy()
sse = numpy.sum((self.predict(X) - y) ** 2, axis=0) / float(X.shape[0] - X.shape[1])
if sse.shape == ():
sse = sse.reshape(1,)
inv_X_XT = numpy.linalg.inv(numpy.dot(X.T, X))
with warnings.catch_warnings():
warnings.simplefilter("ignore", category=RuntimeWarning)
try:
se = numpy.array([
numpy.sqrt(numpy.diagonal(sse[i] * inv_X_XT))
for i in range(sse.shape[0])
])
except:
print("sse.shape",sse.shape)
print(sse)
raise
self.t_ = self.coef_ / se
self.p_ = 2 * (1 - scipy.stats.t.cdf(numpy.abs(self.t_), y.shape[0] - X.shape[1]))
# try:
# print(y.values[0])
# except AttributeError:
# print(y[0])
return self
def predict(self, X):
# print(" "*55,"LR PREDICT on", len(X))
return super().predict(X)
class GaussianProcessRegressor_(GaussianProcessRegressor):
def fit(self, X, y):
# print(" GPR FIT on",len(X))
q = super().fit(X,y)
# try:
# print(y.values[0])
# except AttributeError:
# print(y[0])
return q
def predict(self, X, return_std=False, return_cov=False):
#print(" "*55,"GPR PREDICT on", len(X))
return super().predict(X, return_std=return_std, return_cov=return_cov)
def _make_as_vector(y):
# if isinstance(y, (pandas.DataFrame, pandas.Series)):
# y = y.values.ravel()
return y
@contextlib.contextmanager
def ignore_warnings(category=Warning):
with warnings.catch_warnings():
warnings.simplefilter("ignore", category=category)
yield
class LinearAndGaussianProcessRegression(
BaseEstimator,
RegressorMixin,
):
def __init__(self, core_features=None, keep_other_features=3, use_linear=True):
"""
Parameters
----------
core_features
feature columns to definitely keep for both LR and GPR
"""
self.core_features = core_features
self.keep_other_features = keep_other_features
self.lr = LinearRegression()
self.gpr = GaussianProcessRegressor_(n_restarts_optimizer=9)
self.y_residual = None
self.kernel_generator = lambda dims: C() * RBF([1.0] * dims)
self.use_linear = use_linear
def _feature_selection(self, X, y=None):
"""
Parameters
----------
X : pandas.DataFrame
y : ndarray
If given, the SelectKBest feature selector will be re-fit to find the best features. If not given,
then the previously fit SelectKBest will be used; if it has never been fit, an error is raised.
Returns
-------
pandas.DataFrame
Contains all the core features plus the K best other features.
"""
if not isinstance(X, pandas.DataFrame):
raise TypeError('must use pandas.DataFrame for X')
if self.core_features is None:
return X
y = _make_as_vector(y)
X_core = X.loc[:,self.core_features]
X_other = X.loc[:, X.columns.difference(self.core_features)]
if X_other.shape[1] <= self.keep_other_features:
return X
# If self.keep_other_features is zero, there is no feature selecting to do and we return only the core.
if self.keep_other_features == 0:
return X_core
if y is not None:
self.feature_selector = SelectKBest(mutual_info_regression, k=self.keep_other_features).fit(X_other, y)
try:
X_other = pandas.DataFrame(
self.feature_selector.transform(X_other),
columns=X_other.columns[self.feature_selector.get_support()],
index=X_other.index,
)
except:
print("X_other.info")
print(X_other.info(1))
print("X_other")
print(X_other)
raise
try:
return pandas.concat([X_core, X_other], axis=1)
except:
print("X_core")
print(X_core)
print("X_other")
print(X_other)
print(X_core.info())
print(X_other.info())
raise
def fit(self, X, y):
"""
Fit linear and gaussian model.
Parameters
----------
X : numpy array or sparse matrix of shape [n_samples, n_features]
Training data
y : numpy array of shape [n_samples, n_targets]
Target values.
Returns
-------
self : returns an instance of self.
"""
# print("META FIT on",len(X))
# if not isinstance(X, pandas.DataFrame):
# # X = pandas.DataFrame(X)
# raise TypeError('must use pandas.DataFrame for X')
#
# if self.core_features is None:
# X_core = X
# X_other = X.loc[:,[]]
# else:
# X_core = X.loc[:,self.core_features]
# X_other = X.loc[:, X.columns.difference(self.core_features)]
#
# self.feature_selector = SelectKBest(mutual_info_regression, k=self.keep_other_features).fit(X_other, y)
#
# X_other = self.feature_selector.transform(X_other)
with ignore_warnings(DataConversionWarning):
if isinstance(y, pandas.DataFrame):
self.Y_columns = y.columns
elif isinstance(y, pandas.Series):
self.Y_columns = [y.name]
else:
self.Y_columns = None
y = _make_as_vector(y)
X_core_plus = self._feature_selection(X, y)
if self.use_linear:
try:
self.lr.fit(X_core_plus, y)
except:
print("X_core_plus.shape",X_core_plus.shape)
print("y.shape",y.shape)
print(X_core_plus)
print(y)
raise
self.y_residual = y - self.lr.predict(X_core_plus)
else:
self.y_residual = y
dims = X_core_plus.shape[1]
self.gpr.kernel = self.kernel_generator(dims)
self.gpr.fit(X_core_plus, self.y_residual)
# print(self.y_residual.values[0])
return self
def predict(self, X, return_std=False, return_cov=False):
"""Predict using the model
Parameters
----------
X : {array-like, sparse matrix}, shape = (n_samples, n_features)
Samples.
Returns
-------
C : array, shape = (n_samples,)
Returns predicted values.
"""
if not isinstance(X, pandas.DataFrame):
raise TypeError('must use pandas.DataFrame for X')
X_core_plus = self._feature_selection(X)
if self.use_linear:
y_hat_lr = self.lr.predict(X=X_core_plus)
else:
y_hat_lr = 0
if return_std:
y_hat_gpr, y_hat_std = self.gpr.predict(X_core_plus, return_std=True)
if self.Y_columns is not None:
y_result = pandas.DataFrame(
y_hat_lr + y_hat_gpr,
columns=self.Y_columns,
index=X.index,
)
else:
y_result = y_hat_lr + y_hat_gpr
return y_result, y_hat_std
else:
y_hat_gpr = self.gpr.predict(X_core_plus)
if self.Y_columns is not None:
y_result = pandas.DataFrame(
y_hat_lr + y_hat_gpr,
columns=self.Y_columns,
index=X.index,
)
else:
y_result = y_hat_lr + y_hat_gpr
return y_result
def cross_val_scores(self, X, Y, cv=3):
p = self.cross_val_predict(X, Y, cv=cv)
return pandas.Series(
r2_score(Y, p, sample_weight=None, multioutput='raw_values'),
index=Y.columns
)
#
# def cross_val_scores(self, X, y, cv=3):
# with ignore_warnings(DataConversionWarning):
# y = _make_as_vector(y)
# X_core_plus = self._feature_selection(X, y)
# total = cross_val_score(self, X_core_plus, y, cv=cv)
# return total
def cross_val_scores_full(self, X, y, cv=3, alt_y=None):
with ignore_warnings(DataConversionWarning):
y = _make_as_vector(y)
X_core_plus = self._feature_selection(X, y)
total = cross_val_score(self, X_core_plus, y, cv=cv)
if self.use_linear:
linear_cv_score = cross_val_score(self.lr, X_core_plus, y, cv=cv)
linear_cv_predict = cross_val_predict(self.lr, X_core_plus, y, cv=cv)
linear_cv_residual = y-linear_cv_predict
gpr_cv_score = cross_val_score(self.gpr, X_core_plus, linear_cv_residual, cv=cv)
self.lr.fit(X_core_plus, y)
y_residual = y - self.lr.predict(X_core_plus)
gpr_cv_score2 = cross_val_score(self.gpr, X_core_plus, y_residual, cv=cv)
result = dicta(
total=total,
linear=linear_cv_score,
net_gpr=total-linear_cv_score,
gpr=gpr_cv_score,
gpr2=gpr_cv_score2,
)
else:
result = dicta(
total=total,
)
if alt_y is not None:
result['gpr_alt'] = cross_val_score(self.gpr, X, alt_y, cv=cv)
# print()
# print(numpy.concatenate([y_residual, alt_y, y_residual-alt_y], axis=1 ))
# print()
# print(result['gpr_alt'])
# print(result['gpr2'])
# print()
return result
def cross_val_predict(self, X, y, cv=3):
with ignore_warnings(DataConversionWarning):
X_core_plus = self._feature_selection(X, y)
if isinstance(y, pandas.DataFrame):
y_columns = y.columns
elif isinstance(y, pandas.Series):
y_columns = [y.name]
else:
y_columns = ['Unnamed']
total = cross_val_predict(self, X_core_plus, y, cv=cv)
return pandas.DataFrame(
total,
index=y.index,
columns=y_columns,
)
def cross_val_predicts(self, X, y, cv=3):
with ignore_warnings(DataConversionWarning):
y = _make_as_vector(y)
X_core_plus = self._feature_selection(X, y)
total = cross_val_predict(self, X_core_plus, y, cv=cv)
if self.use_linear:
linear_cv_predict = cross_val_predict(self.lr, X_core_plus, y, cv=cv)
linear_cv_residual = y-linear_cv_predict
gpr_cv_predict_over_cv_linear = cross_val_predict(self.gpr, X_core_plus, linear_cv_residual, cv=cv)
self.lr.fit(X_core_plus, y)
linear_full_predict = self.lr.predict(X_core_plus)
y_residual = y - linear_full_predict
gpr_cv_predict_over_full_linear = cross_val_predict(self.gpr, X_core_plus, y_residual, cv=cv)
return dicta(
total=total,
linear=linear_cv_predict,
net_gpr=total-linear_cv_predict,
gpr=gpr_cv_predict_over_cv_linear+linear_cv_predict,
gpr2=gpr_cv_predict_over_full_linear+linear_full_predict,
)
else:
return dicta(
total=total,
)
def cross_val_scores(pipe, X, y, cv=3):
# For pipelines
y = _make_as_vector(y)
self = pipe.steps[-1][1]
total = cross_val_score(self, X, y, cv=cv)
linear_cv_score = cross_val_score(self.lr, X, y, cv=cv)
linear_cv_predict = cross_val_predict(self.lr, X, y, cv=cv)
linear_cv_residual = y-linear_cv_predict
gpr_cv_score = cross_val_score(self.gpr, X, linear_cv_residual, cv=cv)
self.lr.fit(X, y)
y_residual = y - self.lr.predict(X)
gpr_cv_score2 = cross_val_score(self.gpr, X, y_residual, cv=cv)
return dicta(
total=total,
linear=linear_cv_score,
net_gpr=total-linear_cv_score,
gpr=gpr_cv_score,
gpr2=gpr_cv_score2,
)
class PartialStandardScaler(StandardScaler):
def __init__(self, copy=True, with_mean=True, with_std=True, omit=()):
super().__init__(copy=copy, with_mean=with_mean, with_std=with_std)
self._omit = omit
self._names = None
def fit(self, X, y=None):
result = super().fit(X, y)
omit = [i for i in self._omit]
if isinstance(X, pandas.DataFrame):
self._names = X.columns.copy()
for n,k in enumerate(omit):
if isinstance(k, str):
omit[n] = X.columns.get_loc(k)
for k in omit:
if self.with_mean:
self.mean_[k] = 0
if self.with_std:
self.scale_[k] = 1
return result
def transform(self, X, y='deprecated', copy=None):
result = super().transform(X, y, copy)
if isinstance(X, pandas.DataFrame):
return pandas.DataFrame(
data=result,
index=X.index,
columns=[(f'{i}†' if i not in self._omit else i) for i in X.columns]
)
return result
def inverse_transform_by_name(self, X, name):
ix = self._names.get_loc(name)
if self.with_std:
X *= self.scale_[ix]
if self.with_mean:
X += self.mean_[ix]
return X
def transform_by_name(self, X, name):
ix = self._names.get_loc(name)
if self.with_mean:
X -= self.mean_[ix]
if self.with_std:
X /= self.scale_[ix]
return X
class Log1pStandardScaler(StandardScaler):
def __init__(self, copy=True, with_mean=True, with_std=True):
super().__init__(copy=copy, with_mean=with_mean, with_std=with_std)
def fit(self, X, y=None):
return super().fit(numpy.log1p(X), y)
def transform(self, X, y='deprecated', copy=None):
result = super().transform(numpy.log1p(X), y, copy)
if isinstance(X, pandas.DataFrame):
return pandas.DataFrame(
data=result,
index=X.index,
columns=[f'{i}†' for i in X.columns]
)
return result
def inverse_transform(self, X, copy=None):
result = super().inverse_transform(X)
result = numpy.expm1(result)
if isinstance(X, pandas.DataFrame):
return pandas.DataFrame(
data=result,
index=X.index,
columns=[i.rstrip('†') for i in X.columns]
)
return result
class ExponentialFeatures(BaseEstimator, TransformerMixin):
def __init__(self):
pass
def fit(self, X, y=None):
"""
Compute number of output features.
Parameters
----------
X : array-like, shape (n_samples, n_features)
The data.
Returns
-------
self : instance
"""
return self
def transform(self, X):
"""Transform data to add exponential features
Parameters
----------
X : array-like, shape [n_samples, n_features]
The data to transform, row by row.
Returns
-------
XP : np.ndarray shape [n_samples, NP]
The matrix of features, where NP is the number of polynomial
features generated from the combination of inputs.
"""
from sklearn.utils import check_array
from sklearn.utils.validation import check_is_fitted, check_random_state, FLOAT_DTYPES
from scipy.stats.stats import pearsonr
X = check_array(X, dtype=FLOAT_DTYPES)
n_samples, n_features = X.shape
# allocate output data
XP = numpy.empty((n_samples, n_features*2), dtype=X.dtype)
XP_use = numpy.ones((n_features*2,), dtype=bool)
for i in range(n_features):
XP[:, i] = X[:, i]
exp_x = numpy.exp(X[:, i])
correlation = pearsonr(X[:, i], exp_x)[0]
# print("correlation is",correlation)
if numpy.fabs(correlation) < 0.99:
XP[:, i+n_features] = exp_x
else:
XP_use[i+n_features] = 0
if isinstance(X, pandas.DataFrame):
result = pandas.DataFrame(
data=XP,
columns=list(X.columns) + [f'exp({c})' for c in X.columns],
index=X.index,
)
return result.iloc[:, XP_use]
return XP[:,XP_use]
class InteractionFeatures(BaseEstimator, TransformerMixin):
def __init__(self, interaction_point):
self._interaction_name = interaction_point
def fit(self, X, y=None):
"""
Compute number of output features.
Parameters
----------
X : array-like, shape (n_samples, n_features)
The data.
Returns
-------
self : instance
"""
return self
def transform(self, X):
"""Transform data to add exponential features
Parameters
----------
X : array-like, shape [n_samples, n_features]
The data to transform, row by row.
Returns
-------
XP : np.ndarray shape [n_samples, NP]
The matrix of features, where NP is the number of polynomial
features generated from the combination of inputs.
"""
from sklearn.utils import check_array
from sklearn.utils.validation import check_is_fitted, check_random_state, FLOAT_DTYPES
from scipy.stats.stats import pearsonr
interact_point = None
if isinstance(self._interaction_name, int):
interact_point = self._interaction_name
else:
if isinstance(X, pandas.DataFrame):
interact_point = X.columns.get_loc(self._interaction_name)
else:
raise TypeError("X must be DataFrame when interaction_name is string")
if interact_point is None:
raise TypeError('interact_point is None')
Xa = check_array(X, dtype=FLOAT_DTYPES)
n_samples, n_features = Xa.shape
# allocate output data
XP = numpy.empty((n_samples, n_features*2), dtype=Xa.dtype)
XP_use = numpy.ones((n_features*2,), dtype=bool)
XP_fresh = numpy.zeros((n_features*2,), dtype=bool)
for i in range(n_features):
XP[:, i] = Xa[:, i]
exp_x = Xa[:, i] * Xa[:, interact_point]
#correlation = pearsonr(Xa[:, i], exp_x)[0]
correlation1 = numpy.corrcoef(Xa, exp_x, rowvar=False)[-1, :-1]
if XP_fresh.sum():
correlation2 = numpy.corrcoef(XP[:,XP_fresh], exp_x, rowvar=False)[-1, :-1]
else:
correlation2 = [0]
correlation = max( numpy.fabs(correlation1).max(), numpy.fabs(correlation2).max())
if numpy.fabs(correlation) < 0.99:
XP[:, i+n_features] = exp_x
XP_fresh[i+n_features] = True
else:
XP_use[i+n_features] = 0
if isinstance(X, pandas.DataFrame):
result = pandas.DataFrame(
data=XP,
columns=list(X.columns) + [f'{c} ~ {self._interaction_name}' for c in X.columns],
index=X.index,
)
return result.iloc[:, XP_use]
return XP[:,XP_use]
| 25.903704 | 107 | 0.693795 |
8ee309537169151d1fc3e6f22eae7b5685388650 | 2,690 | py | Python | src/cryptojwt/jws/utils.py | openid/JWTConnect-Python-CryptoJWT | ec79b98f62f033afc596a4be5229a0ded4ee771b | [
"Apache-2.0"
] | 4 | 2018-10-02T14:47:43.000Z | 2019-09-12T02:53:46.000Z | src/cryptojwt/jws/utils.py | IdentityPython/JWTConnect-Python-CryptoJWT | a7dd24f07e7bab2ce2580d7111340cc753a965c0 | [
"Apache-2.0"
] | 67 | 2020-01-23T17:33:56.000Z | 2022-03-26T17:58:33.000Z | src/cryptojwt/jws/utils.py | openid/JWTConnect-Python-CryptoJWT | ec79b98f62f033afc596a4be5229a0ded4ee771b | [
"Apache-2.0"
] | 5 | 2018-06-22T07:08:28.000Z | 2019-12-20T09:57:03.000Z | # import struct
from cryptography.hazmat.primitives import hashes
from cryptography.hazmat.primitives.asymmetric import padding
from ..exception import UnsupportedAlgorithm
from ..jwk.hmac import sha256_digest
from ..jwk.hmac import sha384_digest
from ..jwk.hmac import sha512_digest
from ..utils import as_unicode
from ..utils import b64e
def left_hash(msg, func="HS256"):
"""Calculate left hash as described in
https://openid.net/specs/openid-connect-core-1_0.html#CodeIDToken
for at_hash and in
for c_hash
:param msg: The message over which the hash should be calculated
:param func: Which hash function that was used for the ID token
"""
if func == "HS256":
return as_unicode(b64e(sha256_digest(msg)[:16]))
elif func == "HS384":
return as_unicode(b64e(sha384_digest(msg)[:24]))
elif func == "HS512":
return as_unicode(b64e(sha512_digest(msg)[:32]))
# def mpint(b):
# b += b"\x00"
# return struct.pack(">L", len(b)) + b
#
def alg2keytype(alg):
"""
Go from algorithm name to key type.
:param alg: The algorithm name
:return: The key type
"""
if not alg or alg.lower() == "none":
return "none"
elif alg.startswith("RS") or alg.startswith("PS"):
return "RSA"
elif alg.startswith("HS") or alg.startswith("A"):
return "oct"
elif alg.startswith("ES") or alg.startswith("ECDH-ES"):
return "EC"
else:
return None
def parse_rsa_algorithm(algorithm):
"""
Parses a RSA algorithm and returns tuple (hash, padding).
:param algorithm: string, RSA algorithm as defined at
https://tools.ietf.org/html/rfc7518#section-3.1.
:raises: UnsupportedAlgorithm: if the algorithm is not supported.
:returns: (hash, padding) tuple.
"""
if algorithm == "RS256":
return hashes.SHA256(), padding.PKCS1v15()
elif algorithm == "RS384":
return hashes.SHA384(), padding.PKCS1v15()
elif algorithm == "RS512":
return hashes.SHA512(), padding.PKCS1v15()
elif algorithm == "PS256":
return (
hashes.SHA256(),
padding.PSS(mgf=padding.MGF1(hashes.SHA256()), salt_length=padding.PSS.MAX_LENGTH),
)
elif algorithm == "PS384":
return (
hashes.SHA384(),
padding.PSS(mgf=padding.MGF1(hashes.SHA384()), salt_length=padding.PSS.MAX_LENGTH),
)
elif algorithm == "PS512":
return (
hashes.SHA512(),
padding.PSS(mgf=padding.MGF1(hashes.SHA512()), salt_length=padding.PSS.MAX_LENGTH),
)
else:
raise UnsupportedAlgorithm("Unknown algorithm: {}".format(algorithm))
| 30.568182 | 95 | 0.641636 |
c413df3e531e6990ed380923836adcfe61080053 | 5,140 | py | Python | djangae/contrib/processing/mapreduce/tests/mapreduce_tests.py | ikedaosushi/djangae | 5fd2f8d70699fbbf155740effe42a36b205a6540 | [
"BSD-3-Clause"
] | null | null | null | djangae/contrib/processing/mapreduce/tests/mapreduce_tests.py | ikedaosushi/djangae | 5fd2f8d70699fbbf155740effe42a36b205a6540 | [
"BSD-3-Clause"
] | null | null | null | djangae/contrib/processing/mapreduce/tests/mapreduce_tests.py | ikedaosushi/djangae | 5fd2f8d70699fbbf155740effe42a36b205a6540 | [
"BSD-3-Clause"
] | null | null | null | from __future__ import absolute_import
from mapreduce.mapreduce_pipeline import MapreducePipeline
from django.db import models
from djangae.test import TestCase
from djangae.test import process_task_queues
from djangae.contrib.processing.mapreduce.helpers import DjangoInputReader
from djangae.contrib.processing.mapreduce.utils import qualname
# from djangae.contrib.processing.mapreduce.pipelines import MapPipeline
class MRTestNode(models.Model):
data = models.CharField(max_length=32)
counter = models.IntegerField()
class Meta:
app_label = "mapreduce"
# class MapPipelineTestCase(TestCase):
#
# def setUp(self):
# for x in range(100):
# self.testnode = TestNode()
# self.testnode.data = 'Lol'
# self.testnode.counter = 1
# self.testnode.save()
# super(MapPipelineTestCase, self).setUp()
#
# def test_map_works(self):
# pipe = MapPipeline(
# "increment",
# "djangae.contrib.processing.mapreduce.tests.mapreduce.model_counter_increment",
# "djangae.contrib.processing.mapreduce.input_readers.DjangoInputReader",
# mapper_params={'input_reader': {'model': 'mapreduce.TestNode'}},
# shards=10
# )
# pipe.start()
# process_task_queues()
# nodes = TestNode.objects.all()
# for node in nodes:
# self.assertEqual(node.counter, 2)
#
class DjangoInputReaderTestCase(TestCase):
ENTITY_COUNT = 300
def setUp(self):
for x in range(self.ENTITY_COUNT):
self.testnode = MRTestNode()
self.testnode.data = 'Lol'
self.testnode.counter = 1
if x < self.ENTITY_COUNT / 4:
self.testnode.id = x + 1
self.testnode.save()
super(DjangoInputReaderTestCase, self).setUp()
def _test_split_input_on_n_shards(self, shards):
from mapreduce.model import MapperSpec
mapper_spec = MapperSpec(
'',
'',
{
'input_reader': {
'model': 'mapreduce.MRTestNode'
}
},
shards,
)
readers = DjangoInputReader.split_input(mapper_spec)
self.assertEqual(len(readers), shards)
models = []
for reader in readers:
for model in reader:
models.append(model.pk)
self.assertEqual(len(models), self.ENTITY_COUNT)
self.assertEqual(len(models), len(set(models)))
def test_split_input_on_one_shard(self):
self._test_split_input_on_n_shards(1)
def test_split_input_on_two_shards(self):
self._test_split_input_on_n_shards(2)
def test_split_input_one_batch_per_shard(self):
self._test_split_input_on_n_shards(6)
class MapreduceTestCase(TestCase):
def setUp(self):
for x in range(20):
self.testnode = MRTestNode()
self.testnode.data = 'Lol'
self.testnode.counter = 1
self.testnode.save()
super(MapreduceTestCase, self).setUp()
def test_mapreduce_basic(self):
"""
Tests basic mapreduce with random input
"""
pipe = MapreducePipeline(
"word_count",
qualname(letter_count_map),
qualname(word_count_reduce),
"mapreduce.input_readers.RandomStringInputReader",
"mapreduce.output_writers.GoogleCloudStorageOutputWriter",
mapper_params={'count': 10},
reducer_params={"mime_type": "text/plain", 'output_writer': {'bucket_name': 'test'}},
shards=1
)
pipe.start()
process_task_queues()
def test_mapreduce_django_input(self):
"""
Test basic django operations inside a map task, this shows that
our handlers are working
"""
nodes = MRTestNode.objects.all()
for node in nodes:
self.assertEqual(node.counter, 1)
pipe = MapreducePipeline(
"word_count",
qualname(model_counter_increment),
qualname(word_count_reduce),
"djangae.contrib.processing.mapreduce.input_readers.DjangoInputReader",
"mapreduce.output_writers.GoogleCloudStorageOutputWriter",
mapper_params={'count': 10, 'input_reader': {'model': 'mapreduce.MRTestNode'}},
reducer_params={"mime_type": "text/plain", 'output_writer': {'bucket_name': 'test'}},
shards=5
)
pipe.start()
process_task_queues()
nodes = MRTestNode.objects.all()
for node in nodes:
self.assertEqual(node.counter, 2)
def letter_count_map(data):
"""Word Count map function."""
letters = [x for x in data]
for l in letters:
yield (l, "")
def model_counter_increment(instance):
"""Word Count map function."""
instance.counter += 1
instance.save()
yield (instance.pk, "{0}".format(instance.counter))
def word_count_reduce(key, values):
"""Word Count reduce function."""
yield "%s: %d\n" % (key, len(values))
| 32.948718 | 97 | 0.615175 |
3918496e46d3aa23a4f2631ef5731b89994d5935 | 3,434 | py | Python | metachains/synchronizer.py | Storj/metachains | ed68e29eaf49da77a6fb924cdb9790de4e5e8965 | [
"MIT"
] | 2 | 2015-01-03T00:08:36.000Z | 2015-10-10T03:32:23.000Z | metachains/synchronizer.py | StorjOld/metachains | ed68e29eaf49da77a6fb924cdb9790de4e5e8965 | [
"MIT"
] | null | null | null | metachains/synchronizer.py | StorjOld/metachains | ed68e29eaf49da77a6fb924cdb9790de4e5e8965 | [
"MIT"
] | 4 | 2015-06-15T19:49:01.000Z | 2015-10-16T03:29:02.000Z |
from decimal import Decimal
from collections import defaultdict
import operator
import logging
class Synchronizer(object):
"""Synchronizer accesses data from and to a blockchain.
Synchronizer must be instantiated with three objects:
coin -- An object that responds to blocks() and transactions(block)
cloud -- An object that responds to data_dump(bytes) and data_load(data, txid)
"""
ConfirmationThreshold = 10
TransactionAmount = Decimal('0.05')
TransactionAddress = "F94Vd1E6Hx2uhntGRo8mn3aJvQLS4KXmSA"
def __init__(self, coin, cloud):
self.coin = coin
self.cloud = cloud
self._log = logging.getLogger('storj.metachains')
def scan_database(self):
"""Scan database for non published data."""
while True:
payload = self.cloud.data_dump(self.coin.MaxPayloadSize)
if payload is None:
return
self._log.info('scan_database: processing payload')
self.process_database(payload)
def scan_blockchain(self):
"""Scan blockchain for non registered data, reassembling the
data regions.
"""
outstanding_txns = {}
for block in self.coin.blocks(self.cloud.last_known_block()):
self._log.info('scan_blockchain: indexing block #{}'.format(block['height'])) # Todo make this debug
for txid, entry in self.coin.transactions(block):
if not txid:
continue
outstanding_txns[txid] = (entry, block)
linked_entries = defaultdict(list)
heads = {}
for txid, (entry, block) in outstanding_txns.items():
if entry['prev_txid'] == None:
heads[txid] = (entry, block)
elif entry['prev_txid'] in outstanding_txns:
linked_entries[entry['first_txid']].append(entry)
def is_complete(txid):
return heads[txid][0]['total_length'] == sum([len(entry['region']) for entry in linked_entries[txid]], len(heads[txid][0]['region']))
lowest_incomplete_block = list(self.coin.blocks(self.coin.block_count() - 1))[-1]
for txid, (head_entry, head_block) in heads.items():
if not is_complete(txid):
# The blockchain does not yet contain all constituent
# fragments for this entry
if head_block['height'] < lowest_incomplete_block['height']:
lowest_incomplete_block = head_block
continue
tail = b''.join(entry['region'] for entry in sorted(linked_entries[txid], key=operator.itemgetter('index')))
data = head_entry['region'] + tail
try:
self.process_blockchain(txid, data)
except: #FIXME: this can't be what we want?
pass
self.confirm(lowest_incomplete_block) # FIXME off by one
def process_blockchain(self, txid, info):
"""Load payload into local database."""
self.cloud.data_load(info, txid)
def process_database(self, payload):
"""Publish payload into blockchain."""
self.coin.send_data_address(
payload,
self.TransactionAddress,
self.TransactionAmount)
def confirm(self, block):
self.cloud.visit_block(
max(block["height"] - self.ConfirmationThreshold, 0))
| 38.155556 | 145 | 0.610076 |
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