python-networkx_2.1-1_all.deb
Install the package
sudo apt-get install python-networkx=2.1-1
tool to create, manipulate and study complex networks (Python2)
Full description: tool to create, manipulate and study complex networks (Python2) NetworkX is a Python-based package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. . The structure of a graph or network is encoded in the edges (connections, links, ties, arcs, bonds) between nodes (vertices, sites, actors). If unqualified, by graph it's meant a simple undirected graph, i.e. no self-loops and no multiple edges are allowed. By a network it's usually meant a graph with weights (fields, properties) on nodes and/or edges. . The potential audience for NetworkX includes: mathematicians, physicists, biologists, computer scientists, social scientists. . This package contains the Python 2 version of NetworkX.
Checksums
MD5 | 72d54ad56f351fdac05bc4aac594f94f |
SHA1 | 40c5d67be1885214b429f9962bb1fa077dec6227 |
SHA256 | 977e8c61c67939f1f7181069ca1d5329316ed88a3bbac144aabe446b1080edb3 |
SHA512 | 635897b306e1da66a98d96dc499f646f09ae177280581184c20a5841d43dedb267f04e20fff1225c472b9abb82754f14e9a0fdc39f12b5d65b6a5e22e09757c4 |
Depends
- python3-decorator (>= 4.1.0), python-decorator, python:any (<< 2.8), python:any (>= 2.7.5-5~)
Suggests
- python-networkx-doc
Files
- /usr/lib/python2.7/dist-packages/networkx/algorithms/connectivity/tests/test_kcomponents.py
- /usr/lib/python2.7/dist-packages/networkx/algorithms/connectivity/tests/test_edge_kcomponents.py
- /usr/lib/python2.7/dist-packages/networkx/algorithms/connectivity/tests/test_edge_augmentation.py
- /usr/lib/python2.7/dist-packages/networkx/algorithms/connectivity/tests/test_disjoint_paths.py
- /usr/lib/python2.7/dist-packages/networkx/algorithms/connectivity/tests/test_cuts.py
- /usr/lib/python2.7/dist-packages/networkx/algorithms/connectivity/tests/test_connectivity.py
- /usr/lib/python2.7/dist-packages/networkx/algorithms/connectivity/stoerwagner.py
- /usr/lib/python2.7/dist-packages/networkx/algorithms/connectivity/kcutsets.py
- /usr/lib/python2.7/dist-packages/networkx/algorithms/connectivity/kcomponents.py
- /usr/lib/python2.7/dist-packages/networkx/algorithms/connectivity/edge_kcomponents.py
- /usr/lib/python2.7/dist-packages/networkx/algorithms/connectivity/edge_augmentation.py
- /usr/lib/python2.7/dist-packages/networkx/algorithms/connectivity/disjoint_paths.py
- /usr/lib/python2.7/dist-packages/networkx/algorithms/connectivity/cuts.py
- /usr/lib/python2.7/dist-packages/networkx/algorithms/connectivity/connectivity.py
- /usr/lib/python2.7/dist-packages/networkx/algorithms/connectivity/__init__.py
- /usr/lib/python2.7/dist-packages/networkx/algorithms/components/weakly_connected.py
- /usr/lib/python2.7/dist-packages/networkx/algorithms/components/tests/test_weakly_connected.py
- /usr/lib/python2.7/dist-packages/networkx/algorithms/components/tests/test_subgraph_copies.py
- /usr/lib/python2.7/dist-packages/networkx/algorithms/components/tests/test_strongly_connected.py
- /usr/lib/python2.7/dist-packages/networkx/algorithms/components/tests/test_semiconnected.py
- /usr/lib/python2.7/dist-packages/networkx/algorithms/components/tests/test_connected.py
- /usr/lib/python2.7/dist-packages/networkx/algorithms/components/tests/test_biconnected.py
- /usr/lib/python2.7/dist-packages/networkx/algorithms/components/tests/test_attracting.py
- /usr/lib/python2.7/dist-packages/networkx/algorithms/components/strongly_connected.py
- /usr/lib/python2.7/dist-packages/networkx/algorithms/components/semiconnected.py
- /usr/lib/python2.7/dist-packages/networkx/algorithms/components/connected.py
- /usr/lib/python2.7/dist-packages/networkx/algorithms/components/biconnected.py
- /usr/lib/python2.7/dist-packages/networkx/algorithms/components/attracting.py
- /usr/lib/python2.7/dist-packages/networkx/algorithms/components/__init__.py
- /usr/lib/python2.7/dist-packages/networkx/algorithms/community/tests/test_utils.py
Uploaded
about 7 years agoPackage Size
945 KBInstalled Size
4.37 MBDownloads
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