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"""
NetworkX
========
NetworkX (NX) is a Python package for the creation, manipulation, and
study of the structure, dynamics, and functions of complex networks.
https://networkx.lanl.gov/
Using
-----
Just write in Python
>>> import networkx as nx
>>> G=nx.Graph()
>>> G.add_edge(1,2)
>>> G.add_node(42)
>>> print(sorted(G.nodes()))
[1, 2, 42]
>>> print(sorted(G.edges()))
[(1, 2)]
"""
# Copyright (C) 2004-2015 by
# Aric Hagberg <hagberg@lanl.gov>
# Dan Schult <dschult@colgate.edu>
# Pieter Swart <swart@lanl.gov>
# All rights reserved.
# BSD license.
#
# Add platform dependent shared library path to sys.path
#
from __future__ import absolute_import
import sys
if sys.version_info[:2] < (2, 7):
m = "Python 2.7 or later is required for NetworkX (%d.%d detected)."
raise ImportError(m % sys.version_info[:2])
del sys
# Release data
from networkx import release
__author__ = '%s <%s>\n%s <%s>\n%s <%s>' % \
(release.authors['Hagberg'] + release.authors['Schult'] +
release.authors['Swart'])
__license__ = release.license
__date__ = release.date
__version__ = release.version
__bibtex__ = """@inproceedings{hagberg-2008-exploring,
author = {Aric A. Hagberg and Daniel A. Schult and Pieter J. Swart},
title = {Exploring network structure, dynamics, and function using {NetworkX}},
year = {2008},
month = Aug,
urlpdf = {http://math.lanl.gov/~hagberg/Papers/hagberg-2008-exploring.pdf},
booktitle = {Proceedings of the 7th Python in Science Conference (SciPy2008)},
editors = {G\"{a}el Varoquaux, Travis Vaught, and Jarrod Millman},
address = {Pasadena, CA USA},
pages = {11--15}
}"""
# These are import orderwise
from networkx.exception import *
import networkx.external
import networkx.utils
import networkx.classes
from networkx.classes import *
import networkx.convert
from networkx.convert import *
import networkx.convert_matrix
from networkx.convert_matrix import *
import networkx.relabel
from networkx.relabel import *
import networkx.generators
from networkx.generators import *
import networkx.readwrite
from networkx.readwrite import *
# Need to test with SciPy, when available
import networkx.algorithms
from networkx.algorithms import *
import networkx.linalg
from networkx.linalg import *
from networkx.tests.test import run as test
import networkx.drawing
from networkx.drawing import *
|
