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Update math/py-networkx to 1.2. From PR pkg/43790 by Kamel Derouiche pkgsrc changes: - re-set LICENSE (modified-bsd). upstream changes: Networkx-1.2 Release date: 28 July 2010 See: https://networkx.lanl.gov/trac/timeline New features * Ford-Fulkerson max flow and min cut * Closness vitality * Eulerian circuits * Functions for isolates * Simpler s_max generator * Compatible with IronPython-2.6 * Improved testing functionality: import networkx; networkx.test() tests entire package and skips tests with missing optional packages * All tests work with Python-2.4 * and more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.2 Networkx-1.1 Release date: 21 April 2010 See: https://networkx.lanl.gov/trac/timeline New features * Algorithm for finding a basis for graph cycles * Blockmodeling * Assortativity and mixing matrices * in-degree and out-degree centrality * Attracting components and condensation. * Weakly connected components * Simpler interface to shortest path algorithms * Edgelist format to read and write data with attributes * Attribute matrices * GML reader for nested attributes * Current-flow (random walk) betweenness and closeness. * Directed configuration model, and directed random graph model. * Improved documentation of drawing, shortest paths, and other algorithms * Many more tests, can be run with ?import networkx; networkx.test()? * and much more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.1 API Changes Returning dictionaries Several of the algorithms and the degree() method now return dictionaries keyed by node instead of lists. In some cases there was a with_labels keyword which is no longer necessary. For example, >>> G=nx.Graph() >>> G.add_edge('a','b') >>> G.degree() # returns dictionary of degree keyed by node {'a': 1, 'b': 1} Asking for the degree of a single node still returns a single number >>> G.degree('a') 1 The following now return dictionaries by default (instead of lists) and the with_labels keyword has been removed: * Graph.degree(), MultiGraph.degree(), DiGraph.degree(), DiGraph.in_degree(), DiGraph.out_degree(), MultiDiGraph.degree(), MultiDiGraph.in_degree(), MultiDiGraph.out_degree(). * clustering(), triangles() * node_clique_number(), number_of_cliques(), cliques_containing_node() * eccentricity() The following now return dictionaries by default (instead of lists) * pagerank() * hits() Adding nodes add_nodes_from now accepts (node,attrdict) two-tuples >>> G=nx.Graph() >>> G.add_nodes_from([(1,{'color':'red'})]) Examples * Mayvi2 drawing * Blockmodel * Sampson?s monastery * Ego graph Bug fixes * Support graph attributes with union, intersection, and other graph operations * Improve subgraph speed (and related algorithms such as connected_components_subgraphs()) * Handle multigraphs in more operators (e.g. union) * Handle double-quoted labels with pydot * Normalize betweeness_centrality for undirected graphs correctly * Normalize eigenvector_centrality by l2 norm * read_gml() now returns multigraphs
2010-08-27 05:09:18 +02:00
@comment $NetBSD: PLIST,v 1.6 2010/08/27 03:09:18 gls Exp $
Add math/py-networkx package.
2008-08-27 20:53:42 +02:00
${PYSITELIB}/networkx/__init__.py
${PYSITELIB}/networkx/__init__.pyc
${PYSITELIB}/networkx/__init__.pyo
Update py-networkx to 1.0.1. Based on PR#42834 by Wen Heping. Update MASTER_SITES, set LICENSE=modified-bsd, 3-caulse BSD. ====================================================================== Networkx-1.0.1 Release date: 11 Jan 2010 See: https://networkx.lanl.gov/trac/timeline Bug fix release for missing setup.py in manifest. ====================================================================== Networkx-1.0 Release date: 8 Jan 2010 See: https://networkx.lanl.gov/trac/timeline New features This release has sigificant changes to parts of the graph API to allow graph, node, and edge attributes. See http://networkx.lanl.gov//reference/api_changes.html * Update Graph, DiGraph, and MultiGraph classes to allow attributes. * Default edge data is now an empty dictionary (was the integer 1) * Difference and intersection operators * Average shortest path * A* (A-Star) algorithm * PageRank, HITS, and eigenvector centrality * Read Pajek files * Line graphs * Minimum spanning tree (Kruskal¡Çs algorithm) * Dense and sparse Fruchterman-Reingold layout * Random clustered graph generator * Directed scale-free graph generator * Faster random regular graph generator * Improved edge color and label drawing with Matplotlib * and much more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.0 Examples * Update to work with networkx-1.0 API * Graph subclass example ====================================================================== Networkx-0.99 Release date: 18 November 2008 See: https://networkx.lanl.gov/trac/timeline New features¢ù This release has sigificant changes to parts of the graph API. See http://networkx.lanl.gov//reference/api_changes.html * Update Graph and DiGraph classes to use weighted graphs as default Change in API for performance and code simplicity. * New MultiGraph and MultiDiGraph classes (replace XGraph and XDiGraph) * Update to use Sphinx documentation system http://networkx.lanl.gov/ * Developer site at https://networkx.lanl.gov/trac/ * Experimental LabeledGraph and LabeledDiGraph * Moved package and file layout to subdirectories. Bug fixes * handle root= option to draw_graphviz correctly Examples * Update to work with networkx-0.99 API * Drawing examples now use matplotlib.pyplot interface * Improved drawings in many examples * New examples - see http://networkx.lanl.gov/examples/
2010-03-03 13:00:59 +01:00
${PYSITELIB}/networkx/algorithms/__init__.py
${PYSITELIB}/networkx/algorithms/__init__.pyc
${PYSITELIB}/networkx/algorithms/__init__.pyo
${PYSITELIB}/networkx/algorithms/bipartite.py
${PYSITELIB}/networkx/algorithms/bipartite.pyc
${PYSITELIB}/networkx/algorithms/bipartite.pyo
Update math/py-networkx to 1.2. From PR pkg/43790 by Kamel Derouiche pkgsrc changes: - re-set LICENSE (modified-bsd). upstream changes: Networkx-1.2 Release date: 28 July 2010 See: https://networkx.lanl.gov/trac/timeline New features * Ford-Fulkerson max flow and min cut * Closness vitality * Eulerian circuits * Functions for isolates * Simpler s_max generator * Compatible with IronPython-2.6 * Improved testing functionality: import networkx; networkx.test() tests entire package and skips tests with missing optional packages * All tests work with Python-2.4 * and more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.2 Networkx-1.1 Release date: 21 April 2010 See: https://networkx.lanl.gov/trac/timeline New features * Algorithm for finding a basis for graph cycles * Blockmodeling * Assortativity and mixing matrices * in-degree and out-degree centrality * Attracting components and condensation. * Weakly connected components * Simpler interface to shortest path algorithms * Edgelist format to read and write data with attributes * Attribute matrices * GML reader for nested attributes * Current-flow (random walk) betweenness and closeness. * Directed configuration model, and directed random graph model. * Improved documentation of drawing, shortest paths, and other algorithms * Many more tests, can be run with ?import networkx; networkx.test()? * and much more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.1 API Changes Returning dictionaries Several of the algorithms and the degree() method now return dictionaries keyed by node instead of lists. In some cases there was a with_labels keyword which is no longer necessary. For example, >>> G=nx.Graph() >>> G.add_edge('a','b') >>> G.degree() # returns dictionary of degree keyed by node {'a': 1, 'b': 1} Asking for the degree of a single node still returns a single number >>> G.degree('a') 1 The following now return dictionaries by default (instead of lists) and the with_labels keyword has been removed: * Graph.degree(), MultiGraph.degree(), DiGraph.degree(), DiGraph.in_degree(), DiGraph.out_degree(), MultiDiGraph.degree(), MultiDiGraph.in_degree(), MultiDiGraph.out_degree(). * clustering(), triangles() * node_clique_number(), number_of_cliques(), cliques_containing_node() * eccentricity() The following now return dictionaries by default (instead of lists) * pagerank() * hits() Adding nodes add_nodes_from now accepts (node,attrdict) two-tuples >>> G=nx.Graph() >>> G.add_nodes_from([(1,{'color':'red'})]) Examples * Mayvi2 drawing * Blockmodel * Sampson?s monastery * Ego graph Bug fixes * Support graph attributes with union, intersection, and other graph operations * Improve subgraph speed (and related algorithms such as connected_components_subgraphs()) * Handle multigraphs in more operators (e.g. union) * Handle double-quoted labels with pydot * Normalize betweeness_centrality for undirected graphs correctly * Normalize eigenvector_centrality by l2 norm * read_gml() now returns multigraphs
2010-08-27 05:09:18 +02:00
${PYSITELIB}/networkx/algorithms/block.py
${PYSITELIB}/networkx/algorithms/block.pyc
${PYSITELIB}/networkx/algorithms/block.pyo
Update py-networkx to 1.0.1. Based on PR#42834 by Wen Heping. Update MASTER_SITES, set LICENSE=modified-bsd, 3-caulse BSD. ====================================================================== Networkx-1.0.1 Release date: 11 Jan 2010 See: https://networkx.lanl.gov/trac/timeline Bug fix release for missing setup.py in manifest. ====================================================================== Networkx-1.0 Release date: 8 Jan 2010 See: https://networkx.lanl.gov/trac/timeline New features This release has sigificant changes to parts of the graph API to allow graph, node, and edge attributes. See http://networkx.lanl.gov//reference/api_changes.html * Update Graph, DiGraph, and MultiGraph classes to allow attributes. * Default edge data is now an empty dictionary (was the integer 1) * Difference and intersection operators * Average shortest path * A* (A-Star) algorithm * PageRank, HITS, and eigenvector centrality * Read Pajek files * Line graphs * Minimum spanning tree (Kruskal¡Çs algorithm) * Dense and sparse Fruchterman-Reingold layout * Random clustered graph generator * Directed scale-free graph generator * Faster random regular graph generator * Improved edge color and label drawing with Matplotlib * and much more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.0 Examples * Update to work with networkx-1.0 API * Graph subclass example ====================================================================== Networkx-0.99 Release date: 18 November 2008 See: https://networkx.lanl.gov/trac/timeline New features¢ù This release has sigificant changes to parts of the graph API. See http://networkx.lanl.gov//reference/api_changes.html * Update Graph and DiGraph classes to use weighted graphs as default Change in API for performance and code simplicity. * New MultiGraph and MultiDiGraph classes (replace XGraph and XDiGraph) * Update to use Sphinx documentation system http://networkx.lanl.gov/ * Developer site at https://networkx.lanl.gov/trac/ * Experimental LabeledGraph and LabeledDiGraph * Moved package and file layout to subdirectories. Bug fixes * handle root= option to draw_graphviz correctly Examples * Update to work with networkx-0.99 API * Drawing examples now use matplotlib.pyplot interface * Improved drawings in many examples * New examples - see http://networkx.lanl.gov/examples/
2010-03-03 13:00:59 +01:00
${PYSITELIB}/networkx/algorithms/boundary.py
${PYSITELIB}/networkx/algorithms/boundary.pyc
${PYSITELIB}/networkx/algorithms/boundary.pyo
Update math/py-networkx to 1.2. From PR pkg/43790 by Kamel Derouiche pkgsrc changes: - re-set LICENSE (modified-bsd). upstream changes: Networkx-1.2 Release date: 28 July 2010 See: https://networkx.lanl.gov/trac/timeline New features * Ford-Fulkerson max flow and min cut * Closness vitality * Eulerian circuits * Functions for isolates * Simpler s_max generator * Compatible with IronPython-2.6 * Improved testing functionality: import networkx; networkx.test() tests entire package and skips tests with missing optional packages * All tests work with Python-2.4 * and more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.2 Networkx-1.1 Release date: 21 April 2010 See: https://networkx.lanl.gov/trac/timeline New features * Algorithm for finding a basis for graph cycles * Blockmodeling * Assortativity and mixing matrices * in-degree and out-degree centrality * Attracting components and condensation. * Weakly connected components * Simpler interface to shortest path algorithms * Edgelist format to read and write data with attributes * Attribute matrices * GML reader for nested attributes * Current-flow (random walk) betweenness and closeness. * Directed configuration model, and directed random graph model. * Improved documentation of drawing, shortest paths, and other algorithms * Many more tests, can be run with ?import networkx; networkx.test()? * and much more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.1 API Changes Returning dictionaries Several of the algorithms and the degree() method now return dictionaries keyed by node instead of lists. In some cases there was a with_labels keyword which is no longer necessary. For example, >>> G=nx.Graph() >>> G.add_edge('a','b') >>> G.degree() # returns dictionary of degree keyed by node {'a': 1, 'b': 1} Asking for the degree of a single node still returns a single number >>> G.degree('a') 1 The following now return dictionaries by default (instead of lists) and the with_labels keyword has been removed: * Graph.degree(), MultiGraph.degree(), DiGraph.degree(), DiGraph.in_degree(), DiGraph.out_degree(), MultiDiGraph.degree(), MultiDiGraph.in_degree(), MultiDiGraph.out_degree(). * clustering(), triangles() * node_clique_number(), number_of_cliques(), cliques_containing_node() * eccentricity() The following now return dictionaries by default (instead of lists) * pagerank() * hits() Adding nodes add_nodes_from now accepts (node,attrdict) two-tuples >>> G=nx.Graph() >>> G.add_nodes_from([(1,{'color':'red'})]) Examples * Mayvi2 drawing * Blockmodel * Sampson?s monastery * Ego graph Bug fixes * Support graph attributes with union, intersection, and other graph operations * Improve subgraph speed (and related algorithms such as connected_components_subgraphs()) * Handle multigraphs in more operators (e.g. union) * Handle double-quoted labels with pydot * Normalize betweeness_centrality for undirected graphs correctly * Normalize eigenvector_centrality by l2 norm * read_gml() now returns multigraphs
2010-08-27 05:09:18 +02:00
${PYSITELIB}/networkx/algorithms/centrality/__init__.py
${PYSITELIB}/networkx/algorithms/centrality/__init__.pyc
${PYSITELIB}/networkx/algorithms/centrality/__init__.pyo
${PYSITELIB}/networkx/algorithms/centrality/betweenness.py
${PYSITELIB}/networkx/algorithms/centrality/betweenness.pyc
${PYSITELIB}/networkx/algorithms/centrality/betweenness.pyo
${PYSITELIB}/networkx/algorithms/centrality/betweenness_subset.py
${PYSITELIB}/networkx/algorithms/centrality/betweenness_subset.pyc
${PYSITELIB}/networkx/algorithms/centrality/betweenness_subset.pyo
${PYSITELIB}/networkx/algorithms/centrality/closeness.py
${PYSITELIB}/networkx/algorithms/centrality/closeness.pyc
${PYSITELIB}/networkx/algorithms/centrality/closeness.pyo
${PYSITELIB}/networkx/algorithms/centrality/current_flow_betweenness.py
${PYSITELIB}/networkx/algorithms/centrality/current_flow_betweenness.pyc
${PYSITELIB}/networkx/algorithms/centrality/current_flow_betweenness.pyo
${PYSITELIB}/networkx/algorithms/centrality/current_flow_betweenness_subset.py
${PYSITELIB}/networkx/algorithms/centrality/current_flow_betweenness_subset.pyc
${PYSITELIB}/networkx/algorithms/centrality/current_flow_betweenness_subset.pyo
${PYSITELIB}/networkx/algorithms/centrality/current_flow_closeness.py
${PYSITELIB}/networkx/algorithms/centrality/current_flow_closeness.pyc
${PYSITELIB}/networkx/algorithms/centrality/current_flow_closeness.pyo
${PYSITELIB}/networkx/algorithms/centrality/degree_alg.py
${PYSITELIB}/networkx/algorithms/centrality/degree_alg.pyc
${PYSITELIB}/networkx/algorithms/centrality/degree_alg.pyo
${PYSITELIB}/networkx/algorithms/centrality/eigenvector.py
${PYSITELIB}/networkx/algorithms/centrality/eigenvector.pyc
${PYSITELIB}/networkx/algorithms/centrality/eigenvector.pyo
${PYSITELIB}/networkx/algorithms/centrality/load.py
${PYSITELIB}/networkx/algorithms/centrality/load.pyc
${PYSITELIB}/networkx/algorithms/centrality/load.pyo
${PYSITELIB}/networkx/algorithms/centrality/tests/test_betweenness_centrality.py
${PYSITELIB}/networkx/algorithms/centrality/tests/test_betweenness_centrality.pyc
${PYSITELIB}/networkx/algorithms/centrality/tests/test_betweenness_centrality.pyo
${PYSITELIB}/networkx/algorithms/centrality/tests/test_betweenness_centrality_subset.py
${PYSITELIB}/networkx/algorithms/centrality/tests/test_betweenness_centrality_subset.pyc
${PYSITELIB}/networkx/algorithms/centrality/tests/test_betweenness_centrality_subset.pyo
${PYSITELIB}/networkx/algorithms/centrality/tests/test_current_flow_betweenness_centrality.py
${PYSITELIB}/networkx/algorithms/centrality/tests/test_current_flow_betweenness_centrality.pyc
${PYSITELIB}/networkx/algorithms/centrality/tests/test_current_flow_betweenness_centrality.pyo
${PYSITELIB}/networkx/algorithms/centrality/tests/test_current_flow_betweenness_centrality_subset.py
${PYSITELIB}/networkx/algorithms/centrality/tests/test_current_flow_betweenness_centrality_subset.pyc
${PYSITELIB}/networkx/algorithms/centrality/tests/test_current_flow_betweenness_centrality_subset.pyo
${PYSITELIB}/networkx/algorithms/centrality/tests/test_current_flow_closeness.py
${PYSITELIB}/networkx/algorithms/centrality/tests/test_current_flow_closeness.pyc
${PYSITELIB}/networkx/algorithms/centrality/tests/test_current_flow_closeness.pyo
${PYSITELIB}/networkx/algorithms/centrality/tests/test_degree_centrality.py
${PYSITELIB}/networkx/algorithms/centrality/tests/test_degree_centrality.pyc
${PYSITELIB}/networkx/algorithms/centrality/tests/test_degree_centrality.pyo
${PYSITELIB}/networkx/algorithms/centrality/tests/test_eigenvector_centrality.py
${PYSITELIB}/networkx/algorithms/centrality/tests/test_eigenvector_centrality.pyc
${PYSITELIB}/networkx/algorithms/centrality/tests/test_eigenvector_centrality.pyo
${PYSITELIB}/networkx/algorithms/centrality/tests/test_load_centrality.py
${PYSITELIB}/networkx/algorithms/centrality/tests/test_load_centrality.pyc
${PYSITELIB}/networkx/algorithms/centrality/tests/test_load_centrality.pyo
Update py-networkx to 1.0.1. Based on PR#42834 by Wen Heping. Update MASTER_SITES, set LICENSE=modified-bsd, 3-caulse BSD. ====================================================================== Networkx-1.0.1 Release date: 11 Jan 2010 See: https://networkx.lanl.gov/trac/timeline Bug fix release for missing setup.py in manifest. ====================================================================== Networkx-1.0 Release date: 8 Jan 2010 See: https://networkx.lanl.gov/trac/timeline New features This release has sigificant changes to parts of the graph API to allow graph, node, and edge attributes. See http://networkx.lanl.gov//reference/api_changes.html * Update Graph, DiGraph, and MultiGraph classes to allow attributes. * Default edge data is now an empty dictionary (was the integer 1) * Difference and intersection operators * Average shortest path * A* (A-Star) algorithm * PageRank, HITS, and eigenvector centrality * Read Pajek files * Line graphs * Minimum spanning tree (Kruskal¡Çs algorithm) * Dense and sparse Fruchterman-Reingold layout * Random clustered graph generator * Directed scale-free graph generator * Faster random regular graph generator * Improved edge color and label drawing with Matplotlib * and much more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.0 Examples * Update to work with networkx-1.0 API * Graph subclass example ====================================================================== Networkx-0.99 Release date: 18 November 2008 See: https://networkx.lanl.gov/trac/timeline New features¢ù This release has sigificant changes to parts of the graph API. See http://networkx.lanl.gov//reference/api_changes.html * Update Graph and DiGraph classes to use weighted graphs as default Change in API for performance and code simplicity. * New MultiGraph and MultiDiGraph classes (replace XGraph and XDiGraph) * Update to use Sphinx documentation system http://networkx.lanl.gov/ * Developer site at https://networkx.lanl.gov/trac/ * Experimental LabeledGraph and LabeledDiGraph * Moved package and file layout to subdirectories. Bug fixes * handle root= option to draw_graphviz correctly Examples * Update to work with networkx-0.99 API * Drawing examples now use matplotlib.pyplot interface * Improved drawings in many examples * New examples - see http://networkx.lanl.gov/examples/
2010-03-03 13:00:59 +01:00
${PYSITELIB}/networkx/algorithms/clique.py
${PYSITELIB}/networkx/algorithms/clique.pyc
${PYSITELIB}/networkx/algorithms/clique.pyo
${PYSITELIB}/networkx/algorithms/cluster.py
${PYSITELIB}/networkx/algorithms/cluster.pyc
${PYSITELIB}/networkx/algorithms/cluster.pyo
Update math/py-networkx to 1.2. From PR pkg/43790 by Kamel Derouiche pkgsrc changes: - re-set LICENSE (modified-bsd). upstream changes: Networkx-1.2 Release date: 28 July 2010 See: https://networkx.lanl.gov/trac/timeline New features * Ford-Fulkerson max flow and min cut * Closness vitality * Eulerian circuits * Functions for isolates * Simpler s_max generator * Compatible with IronPython-2.6 * Improved testing functionality: import networkx; networkx.test() tests entire package and skips tests with missing optional packages * All tests work with Python-2.4 * and more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.2 Networkx-1.1 Release date: 21 April 2010 See: https://networkx.lanl.gov/trac/timeline New features * Algorithm for finding a basis for graph cycles * Blockmodeling * Assortativity and mixing matrices * in-degree and out-degree centrality * Attracting components and condensation. * Weakly connected components * Simpler interface to shortest path algorithms * Edgelist format to read and write data with attributes * Attribute matrices * GML reader for nested attributes * Current-flow (random walk) betweenness and closeness. * Directed configuration model, and directed random graph model. * Improved documentation of drawing, shortest paths, and other algorithms * Many more tests, can be run with ?import networkx; networkx.test()? * and much more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.1 API Changes Returning dictionaries Several of the algorithms and the degree() method now return dictionaries keyed by node instead of lists. In some cases there was a with_labels keyword which is no longer necessary. For example, >>> G=nx.Graph() >>> G.add_edge('a','b') >>> G.degree() # returns dictionary of degree keyed by node {'a': 1, 'b': 1} Asking for the degree of a single node still returns a single number >>> G.degree('a') 1 The following now return dictionaries by default (instead of lists) and the with_labels keyword has been removed: * Graph.degree(), MultiGraph.degree(), DiGraph.degree(), DiGraph.in_degree(), DiGraph.out_degree(), MultiDiGraph.degree(), MultiDiGraph.in_degree(), MultiDiGraph.out_degree(). * clustering(), triangles() * node_clique_number(), number_of_cliques(), cliques_containing_node() * eccentricity() The following now return dictionaries by default (instead of lists) * pagerank() * hits() Adding nodes add_nodes_from now accepts (node,attrdict) two-tuples >>> G=nx.Graph() >>> G.add_nodes_from([(1,{'color':'red'})]) Examples * Mayvi2 drawing * Blockmodel * Sampson?s monastery * Ego graph Bug fixes * Support graph attributes with union, intersection, and other graph operations * Improve subgraph speed (and related algorithms such as connected_components_subgraphs()) * Handle multigraphs in more operators (e.g. union) * Handle double-quoted labels with pydot * Normalize betweeness_centrality for undirected graphs correctly * Normalize eigenvector_centrality by l2 norm * read_gml() now returns multigraphs
2010-08-27 05:09:18 +02:00
${PYSITELIB}/networkx/algorithms/components/__init__.py
${PYSITELIB}/networkx/algorithms/components/__init__.pyc
${PYSITELIB}/networkx/algorithms/components/__init__.pyo
${PYSITELIB}/networkx/algorithms/components/attracting.py
${PYSITELIB}/networkx/algorithms/components/attracting.pyc
${PYSITELIB}/networkx/algorithms/components/attracting.pyo
${PYSITELIB}/networkx/algorithms/components/connected.py
${PYSITELIB}/networkx/algorithms/components/connected.pyc
${PYSITELIB}/networkx/algorithms/components/connected.pyo
${PYSITELIB}/networkx/algorithms/components/strongly_connected.py
${PYSITELIB}/networkx/algorithms/components/strongly_connected.pyc
${PYSITELIB}/networkx/algorithms/components/strongly_connected.pyo
${PYSITELIB}/networkx/algorithms/components/tests/test_attracting.py
${PYSITELIB}/networkx/algorithms/components/tests/test_attracting.pyc
${PYSITELIB}/networkx/algorithms/components/tests/test_attracting.pyo
${PYSITELIB}/networkx/algorithms/components/tests/test_connected.py
${PYSITELIB}/networkx/algorithms/components/tests/test_connected.pyc
${PYSITELIB}/networkx/algorithms/components/tests/test_connected.pyo
${PYSITELIB}/networkx/algorithms/components/tests/test_strongly_connected.py
${PYSITELIB}/networkx/algorithms/components/tests/test_strongly_connected.pyc
${PYSITELIB}/networkx/algorithms/components/tests/test_strongly_connected.pyo
${PYSITELIB}/networkx/algorithms/components/tests/test_weakly_connected.py
${PYSITELIB}/networkx/algorithms/components/tests/test_weakly_connected.pyc
${PYSITELIB}/networkx/algorithms/components/tests/test_weakly_connected.pyo
${PYSITELIB}/networkx/algorithms/components/weakly_connected.py
${PYSITELIB}/networkx/algorithms/components/weakly_connected.pyc
${PYSITELIB}/networkx/algorithms/components/weakly_connected.pyo
Update py-networkx to 1.0.1. Based on PR#42834 by Wen Heping. Update MASTER_SITES, set LICENSE=modified-bsd, 3-caulse BSD. ====================================================================== Networkx-1.0.1 Release date: 11 Jan 2010 See: https://networkx.lanl.gov/trac/timeline Bug fix release for missing setup.py in manifest. ====================================================================== Networkx-1.0 Release date: 8 Jan 2010 See: https://networkx.lanl.gov/trac/timeline New features This release has sigificant changes to parts of the graph API to allow graph, node, and edge attributes. See http://networkx.lanl.gov//reference/api_changes.html * Update Graph, DiGraph, and MultiGraph classes to allow attributes. * Default edge data is now an empty dictionary (was the integer 1) * Difference and intersection operators * Average shortest path * A* (A-Star) algorithm * PageRank, HITS, and eigenvector centrality * Read Pajek files * Line graphs * Minimum spanning tree (Kruskal¡Çs algorithm) * Dense and sparse Fruchterman-Reingold layout * Random clustered graph generator * Directed scale-free graph generator * Faster random regular graph generator * Improved edge color and label drawing with Matplotlib * and much more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.0 Examples * Update to work with networkx-1.0 API * Graph subclass example ====================================================================== Networkx-0.99 Release date: 18 November 2008 See: https://networkx.lanl.gov/trac/timeline New features¢ù This release has sigificant changes to parts of the graph API. See http://networkx.lanl.gov//reference/api_changes.html * Update Graph and DiGraph classes to use weighted graphs as default Change in API for performance and code simplicity. * New MultiGraph and MultiDiGraph classes (replace XGraph and XDiGraph) * Update to use Sphinx documentation system http://networkx.lanl.gov/ * Developer site at https://networkx.lanl.gov/trac/ * Experimental LabeledGraph and LabeledDiGraph * Moved package and file layout to subdirectories. Bug fixes * handle root= option to draw_graphviz correctly Examples * Update to work with networkx-0.99 API * Drawing examples now use matplotlib.pyplot interface * Improved drawings in many examples * New examples - see http://networkx.lanl.gov/examples/
2010-03-03 13:00:59 +01:00
${PYSITELIB}/networkx/algorithms/core.py
${PYSITELIB}/networkx/algorithms/core.pyc
${PYSITELIB}/networkx/algorithms/core.pyo
Update math/py-networkx to 1.2. From PR pkg/43790 by Kamel Derouiche pkgsrc changes: - re-set LICENSE (modified-bsd). upstream changes: Networkx-1.2 Release date: 28 July 2010 See: https://networkx.lanl.gov/trac/timeline New features * Ford-Fulkerson max flow and min cut * Closness vitality * Eulerian circuits * Functions for isolates * Simpler s_max generator * Compatible with IronPython-2.6 * Improved testing functionality: import networkx; networkx.test() tests entire package and skips tests with missing optional packages * All tests work with Python-2.4 * and more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.2 Networkx-1.1 Release date: 21 April 2010 See: https://networkx.lanl.gov/trac/timeline New features * Algorithm for finding a basis for graph cycles * Blockmodeling * Assortativity and mixing matrices * in-degree and out-degree centrality * Attracting components and condensation. * Weakly connected components * Simpler interface to shortest path algorithms * Edgelist format to read and write data with attributes * Attribute matrices * GML reader for nested attributes * Current-flow (random walk) betweenness and closeness. * Directed configuration model, and directed random graph model. * Improved documentation of drawing, shortest paths, and other algorithms * Many more tests, can be run with ?import networkx; networkx.test()? * and much more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.1 API Changes Returning dictionaries Several of the algorithms and the degree() method now return dictionaries keyed by node instead of lists. In some cases there was a with_labels keyword which is no longer necessary. For example, >>> G=nx.Graph() >>> G.add_edge('a','b') >>> G.degree() # returns dictionary of degree keyed by node {'a': 1, 'b': 1} Asking for the degree of a single node still returns a single number >>> G.degree('a') 1 The following now return dictionaries by default (instead of lists) and the with_labels keyword has been removed: * Graph.degree(), MultiGraph.degree(), DiGraph.degree(), DiGraph.in_degree(), DiGraph.out_degree(), MultiDiGraph.degree(), MultiDiGraph.in_degree(), MultiDiGraph.out_degree(). * clustering(), triangles() * node_clique_number(), number_of_cliques(), cliques_containing_node() * eccentricity() The following now return dictionaries by default (instead of lists) * pagerank() * hits() Adding nodes add_nodes_from now accepts (node,attrdict) two-tuples >>> G=nx.Graph() >>> G.add_nodes_from([(1,{'color':'red'})]) Examples * Mayvi2 drawing * Blockmodel * Sampson?s monastery * Ego graph Bug fixes * Support graph attributes with union, intersection, and other graph operations * Improve subgraph speed (and related algorithms such as connected_components_subgraphs()) * Handle multigraphs in more operators (e.g. union) * Handle double-quoted labels with pydot * Normalize betweeness_centrality for undirected graphs correctly * Normalize eigenvector_centrality by l2 norm * read_gml() now returns multigraphs
2010-08-27 05:09:18 +02:00
${PYSITELIB}/networkx/algorithms/cycles.py
${PYSITELIB}/networkx/algorithms/cycles.pyc
${PYSITELIB}/networkx/algorithms/cycles.pyo
${PYSITELIB}/networkx/algorithms/dag.py
${PYSITELIB}/networkx/algorithms/dag.pyc
${PYSITELIB}/networkx/algorithms/dag.pyo
${PYSITELIB}/networkx/algorithms/distance_measures.py
${PYSITELIB}/networkx/algorithms/distance_measures.pyc
${PYSITELIB}/networkx/algorithms/distance_measures.pyo
${PYSITELIB}/networkx/algorithms/euler.py
${PYSITELIB}/networkx/algorithms/euler.pyc
${PYSITELIB}/networkx/algorithms/euler.pyo
${PYSITELIB}/networkx/algorithms/flow/__init__.py
${PYSITELIB}/networkx/algorithms/flow/__init__.pyc
${PYSITELIB}/networkx/algorithms/flow/__init__.pyo
${PYSITELIB}/networkx/algorithms/flow/maxflow.py
${PYSITELIB}/networkx/algorithms/flow/maxflow.pyc
${PYSITELIB}/networkx/algorithms/flow/maxflow.pyo
${PYSITELIB}/networkx/algorithms/flow/tests/test_maxflow.py
${PYSITELIB}/networkx/algorithms/flow/tests/test_maxflow.pyc
${PYSITELIB}/networkx/algorithms/flow/tests/test_maxflow.pyo
${PYSITELIB}/networkx/algorithms/flow/tests/test_maxflow_large_graph.py
${PYSITELIB}/networkx/algorithms/flow/tests/test_maxflow_large_graph.pyc
${PYSITELIB}/networkx/algorithms/flow/tests/test_maxflow_large_graph.pyo
${PYSITELIB}/networkx/algorithms/isolates.py
${PYSITELIB}/networkx/algorithms/isolates.pyc
${PYSITELIB}/networkx/algorithms/isolates.pyo
Update py-networkx to 1.0.1. Based on PR#42834 by Wen Heping. Update MASTER_SITES, set LICENSE=modified-bsd, 3-caulse BSD. ====================================================================== Networkx-1.0.1 Release date: 11 Jan 2010 See: https://networkx.lanl.gov/trac/timeline Bug fix release for missing setup.py in manifest. ====================================================================== Networkx-1.0 Release date: 8 Jan 2010 See: https://networkx.lanl.gov/trac/timeline New features This release has sigificant changes to parts of the graph API to allow graph, node, and edge attributes. See http://networkx.lanl.gov//reference/api_changes.html * Update Graph, DiGraph, and MultiGraph classes to allow attributes. * Default edge data is now an empty dictionary (was the integer 1) * Difference and intersection operators * Average shortest path * A* (A-Star) algorithm * PageRank, HITS, and eigenvector centrality * Read Pajek files * Line graphs * Minimum spanning tree (Kruskal¡Çs algorithm) * Dense and sparse Fruchterman-Reingold layout * Random clustered graph generator * Directed scale-free graph generator * Faster random regular graph generator * Improved edge color and label drawing with Matplotlib * and much more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.0 Examples * Update to work with networkx-1.0 API * Graph subclass example ====================================================================== Networkx-0.99 Release date: 18 November 2008 See: https://networkx.lanl.gov/trac/timeline New features¢ù This release has sigificant changes to parts of the graph API. See http://networkx.lanl.gov//reference/api_changes.html * Update Graph and DiGraph classes to use weighted graphs as default Change in API for performance and code simplicity. * New MultiGraph and MultiDiGraph classes (replace XGraph and XDiGraph) * Update to use Sphinx documentation system http://networkx.lanl.gov/ * Developer site at https://networkx.lanl.gov/trac/ * Experimental LabeledGraph and LabeledDiGraph * Moved package and file layout to subdirectories. Bug fixes * handle root= option to draw_graphviz correctly Examples * Update to work with networkx-0.99 API * Drawing examples now use matplotlib.pyplot interface * Improved drawings in many examples * New examples - see http://networkx.lanl.gov/examples/
2010-03-03 13:00:59 +01:00
${PYSITELIB}/networkx/algorithms/isomorphism/__init__.py
${PYSITELIB}/networkx/algorithms/isomorphism/__init__.pyc
${PYSITELIB}/networkx/algorithms/isomorphism/__init__.pyo
${PYSITELIB}/networkx/algorithms/isomorphism/isomorph.py
${PYSITELIB}/networkx/algorithms/isomorphism/isomorph.pyc
${PYSITELIB}/networkx/algorithms/isomorphism/isomorph.pyo
${PYSITELIB}/networkx/algorithms/isomorphism/isomorphvf2.py
${PYSITELIB}/networkx/algorithms/isomorphism/isomorphvf2.pyc
${PYSITELIB}/networkx/algorithms/isomorphism/isomorphvf2.pyo
Update math/py-networkx to 1.2. From PR pkg/43790 by Kamel Derouiche pkgsrc changes: - re-set LICENSE (modified-bsd). upstream changes: Networkx-1.2 Release date: 28 July 2010 See: https://networkx.lanl.gov/trac/timeline New features * Ford-Fulkerson max flow and min cut * Closness vitality * Eulerian circuits * Functions for isolates * Simpler s_max generator * Compatible with IronPython-2.6 * Improved testing functionality: import networkx; networkx.test() tests entire package and skips tests with missing optional packages * All tests work with Python-2.4 * and more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.2 Networkx-1.1 Release date: 21 April 2010 See: https://networkx.lanl.gov/trac/timeline New features * Algorithm for finding a basis for graph cycles * Blockmodeling * Assortativity and mixing matrices * in-degree and out-degree centrality * Attracting components and condensation. * Weakly connected components * Simpler interface to shortest path algorithms * Edgelist format to read and write data with attributes * Attribute matrices * GML reader for nested attributes * Current-flow (random walk) betweenness and closeness. * Directed configuration model, and directed random graph model. * Improved documentation of drawing, shortest paths, and other algorithms * Many more tests, can be run with ?import networkx; networkx.test()? * and much more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.1 API Changes Returning dictionaries Several of the algorithms and the degree() method now return dictionaries keyed by node instead of lists. In some cases there was a with_labels keyword which is no longer necessary. For example, >>> G=nx.Graph() >>> G.add_edge('a','b') >>> G.degree() # returns dictionary of degree keyed by node {'a': 1, 'b': 1} Asking for the degree of a single node still returns a single number >>> G.degree('a') 1 The following now return dictionaries by default (instead of lists) and the with_labels keyword has been removed: * Graph.degree(), MultiGraph.degree(), DiGraph.degree(), DiGraph.in_degree(), DiGraph.out_degree(), MultiDiGraph.degree(), MultiDiGraph.in_degree(), MultiDiGraph.out_degree(). * clustering(), triangles() * node_clique_number(), number_of_cliques(), cliques_containing_node() * eccentricity() The following now return dictionaries by default (instead of lists) * pagerank() * hits() Adding nodes add_nodes_from now accepts (node,attrdict) two-tuples >>> G=nx.Graph() >>> G.add_nodes_from([(1,{'color':'red'})]) Examples * Mayvi2 drawing * Blockmodel * Sampson?s monastery * Ego graph Bug fixes * Support graph attributes with union, intersection, and other graph operations * Improve subgraph speed (and related algorithms such as connected_components_subgraphs()) * Handle multigraphs in more operators (e.g. union) * Handle double-quoted labels with pydot * Normalize betweeness_centrality for undirected graphs correctly * Normalize eigenvector_centrality by l2 norm * read_gml() now returns multigraphs
2010-08-27 05:09:18 +02:00
${PYSITELIB}/networkx/algorithms/isomorphism/tests/iso_r01_s80.A99
${PYSITELIB}/networkx/algorithms/isomorphism/tests/iso_r01_s80.B99
${PYSITELIB}/networkx/algorithms/isomorphism/tests/si2_b06_m200.A99
${PYSITELIB}/networkx/algorithms/isomorphism/tests/si2_b06_m200.B99
${PYSITELIB}/networkx/algorithms/isomorphism/tests/test_isomorphvf2.py
${PYSITELIB}/networkx/algorithms/isomorphism/tests/test_isomorphvf2.pyc
${PYSITELIB}/networkx/algorithms/isomorphism/tests/test_isomorphvf2.pyo
${PYSITELIB}/networkx/algorithms/isomorphism/tests/test_vf2weighted.py
${PYSITELIB}/networkx/algorithms/isomorphism/tests/test_vf2weighted.pyc
${PYSITELIB}/networkx/algorithms/isomorphism/tests/test_vf2weighted.pyo
Update py-networkx to 1.0.1. Based on PR#42834 by Wen Heping. Update MASTER_SITES, set LICENSE=modified-bsd, 3-caulse BSD. ====================================================================== Networkx-1.0.1 Release date: 11 Jan 2010 See: https://networkx.lanl.gov/trac/timeline Bug fix release for missing setup.py in manifest. ====================================================================== Networkx-1.0 Release date: 8 Jan 2010 See: https://networkx.lanl.gov/trac/timeline New features This release has sigificant changes to parts of the graph API to allow graph, node, and edge attributes. See http://networkx.lanl.gov//reference/api_changes.html * Update Graph, DiGraph, and MultiGraph classes to allow attributes. * Default edge data is now an empty dictionary (was the integer 1) * Difference and intersection operators * Average shortest path * A* (A-Star) algorithm * PageRank, HITS, and eigenvector centrality * Read Pajek files * Line graphs * Minimum spanning tree (Kruskal¡Çs algorithm) * Dense and sparse Fruchterman-Reingold layout * Random clustered graph generator * Directed scale-free graph generator * Faster random regular graph generator * Improved edge color and label drawing with Matplotlib * and much more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.0 Examples * Update to work with networkx-1.0 API * Graph subclass example ====================================================================== Networkx-0.99 Release date: 18 November 2008 See: https://networkx.lanl.gov/trac/timeline New features¢ù This release has sigificant changes to parts of the graph API. See http://networkx.lanl.gov//reference/api_changes.html * Update Graph and DiGraph classes to use weighted graphs as default Change in API for performance and code simplicity. * New MultiGraph and MultiDiGraph classes (replace XGraph and XDiGraph) * Update to use Sphinx documentation system http://networkx.lanl.gov/ * Developer site at https://networkx.lanl.gov/trac/ * Experimental LabeledGraph and LabeledDiGraph * Moved package and file layout to subdirectories. Bug fixes * handle root= option to draw_graphviz correctly Examples * Update to work with networkx-0.99 API * Drawing examples now use matplotlib.pyplot interface * Improved drawings in many examples * New examples - see http://networkx.lanl.gov/examples/
2010-03-03 13:00:59 +01:00
${PYSITELIB}/networkx/algorithms/isomorphism/vf2weighted.py
${PYSITELIB}/networkx/algorithms/isomorphism/vf2weighted.pyc
${PYSITELIB}/networkx/algorithms/isomorphism/vf2weighted.pyo
Update math/py-networkx to 1.2. From PR pkg/43790 by Kamel Derouiche pkgsrc changes: - re-set LICENSE (modified-bsd). upstream changes: Networkx-1.2 Release date: 28 July 2010 See: https://networkx.lanl.gov/trac/timeline New features * Ford-Fulkerson max flow and min cut * Closness vitality * Eulerian circuits * Functions for isolates * Simpler s_max generator * Compatible with IronPython-2.6 * Improved testing functionality: import networkx; networkx.test() tests entire package and skips tests with missing optional packages * All tests work with Python-2.4 * and more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.2 Networkx-1.1 Release date: 21 April 2010 See: https://networkx.lanl.gov/trac/timeline New features * Algorithm for finding a basis for graph cycles * Blockmodeling * Assortativity and mixing matrices * in-degree and out-degree centrality * Attracting components and condensation. * Weakly connected components * Simpler interface to shortest path algorithms * Edgelist format to read and write data with attributes * Attribute matrices * GML reader for nested attributes * Current-flow (random walk) betweenness and closeness. * Directed configuration model, and directed random graph model. * Improved documentation of drawing, shortest paths, and other algorithms * Many more tests, can be run with ?import networkx; networkx.test()? * and much more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.1 API Changes Returning dictionaries Several of the algorithms and the degree() method now return dictionaries keyed by node instead of lists. In some cases there was a with_labels keyword which is no longer necessary. For example, >>> G=nx.Graph() >>> G.add_edge('a','b') >>> G.degree() # returns dictionary of degree keyed by node {'a': 1, 'b': 1} Asking for the degree of a single node still returns a single number >>> G.degree('a') 1 The following now return dictionaries by default (instead of lists) and the with_labels keyword has been removed: * Graph.degree(), MultiGraph.degree(), DiGraph.degree(), DiGraph.in_degree(), DiGraph.out_degree(), MultiDiGraph.degree(), MultiDiGraph.in_degree(), MultiDiGraph.out_degree(). * clustering(), triangles() * node_clique_number(), number_of_cliques(), cliques_containing_node() * eccentricity() The following now return dictionaries by default (instead of lists) * pagerank() * hits() Adding nodes add_nodes_from now accepts (node,attrdict) two-tuples >>> G=nx.Graph() >>> G.add_nodes_from([(1,{'color':'red'})]) Examples * Mayvi2 drawing * Blockmodel * Sampson?s monastery * Ego graph Bug fixes * Support graph attributes with union, intersection, and other graph operations * Improve subgraph speed (and related algorithms such as connected_components_subgraphs()) * Handle multigraphs in more operators (e.g. union) * Handle double-quoted labels with pydot * Normalize betweeness_centrality for undirected graphs correctly * Normalize eigenvector_centrality by l2 norm * read_gml() now returns multigraphs
2010-08-27 05:09:18 +02:00
${PYSITELIB}/networkx/algorithms/link_analysis/__init__.py
${PYSITELIB}/networkx/algorithms/link_analysis/__init__.pyc
${PYSITELIB}/networkx/algorithms/link_analysis/__init__.pyo
${PYSITELIB}/networkx/algorithms/link_analysis/hits_alg.py
${PYSITELIB}/networkx/algorithms/link_analysis/hits_alg.pyc
${PYSITELIB}/networkx/algorithms/link_analysis/hits_alg.pyo
${PYSITELIB}/networkx/algorithms/link_analysis/pagerank_alg.py
${PYSITELIB}/networkx/algorithms/link_analysis/pagerank_alg.pyc
${PYSITELIB}/networkx/algorithms/link_analysis/pagerank_alg.pyo
${PYSITELIB}/networkx/algorithms/link_analysis/tests/test_hits.py
${PYSITELIB}/networkx/algorithms/link_analysis/tests/test_hits.pyc
${PYSITELIB}/networkx/algorithms/link_analysis/tests/test_hits.pyo
${PYSITELIB}/networkx/algorithms/link_analysis/tests/test_pagerank.py
${PYSITELIB}/networkx/algorithms/link_analysis/tests/test_pagerank.pyc
${PYSITELIB}/networkx/algorithms/link_analysis/tests/test_pagerank.pyo
Update py-networkx to 1.0.1. Based on PR#42834 by Wen Heping. Update MASTER_SITES, set LICENSE=modified-bsd, 3-caulse BSD. ====================================================================== Networkx-1.0.1 Release date: 11 Jan 2010 See: https://networkx.lanl.gov/trac/timeline Bug fix release for missing setup.py in manifest. ====================================================================== Networkx-1.0 Release date: 8 Jan 2010 See: https://networkx.lanl.gov/trac/timeline New features This release has sigificant changes to parts of the graph API to allow graph, node, and edge attributes. See http://networkx.lanl.gov//reference/api_changes.html * Update Graph, DiGraph, and MultiGraph classes to allow attributes. * Default edge data is now an empty dictionary (was the integer 1) * Difference and intersection operators * Average shortest path * A* (A-Star) algorithm * PageRank, HITS, and eigenvector centrality * Read Pajek files * Line graphs * Minimum spanning tree (Kruskal¡Çs algorithm) * Dense and sparse Fruchterman-Reingold layout * Random clustered graph generator * Directed scale-free graph generator * Faster random regular graph generator * Improved edge color and label drawing with Matplotlib * and much more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.0 Examples * Update to work with networkx-1.0 API * Graph subclass example ====================================================================== Networkx-0.99 Release date: 18 November 2008 See: https://networkx.lanl.gov/trac/timeline New features¢ù This release has sigificant changes to parts of the graph API. See http://networkx.lanl.gov//reference/api_changes.html * Update Graph and DiGraph classes to use weighted graphs as default Change in API for performance and code simplicity. * New MultiGraph and MultiDiGraph classes (replace XGraph and XDiGraph) * Update to use Sphinx documentation system http://networkx.lanl.gov/ * Developer site at https://networkx.lanl.gov/trac/ * Experimental LabeledGraph and LabeledDiGraph * Moved package and file layout to subdirectories. Bug fixes * handle root= option to draw_graphviz correctly Examples * Update to work with networkx-0.99 API * Drawing examples now use matplotlib.pyplot interface * Improved drawings in many examples * New examples - see http://networkx.lanl.gov/examples/
2010-03-03 13:00:59 +01:00
${PYSITELIB}/networkx/algorithms/matching.py
${PYSITELIB}/networkx/algorithms/matching.pyc
${PYSITELIB}/networkx/algorithms/matching.pyo
Update math/py-networkx to 1.2. From PR pkg/43790 by Kamel Derouiche pkgsrc changes: - re-set LICENSE (modified-bsd). upstream changes: Networkx-1.2 Release date: 28 July 2010 See: https://networkx.lanl.gov/trac/timeline New features * Ford-Fulkerson max flow and min cut * Closness vitality * Eulerian circuits * Functions for isolates * Simpler s_max generator * Compatible with IronPython-2.6 * Improved testing functionality: import networkx; networkx.test() tests entire package and skips tests with missing optional packages * All tests work with Python-2.4 * and more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.2 Networkx-1.1 Release date: 21 April 2010 See: https://networkx.lanl.gov/trac/timeline New features * Algorithm for finding a basis for graph cycles * Blockmodeling * Assortativity and mixing matrices * in-degree and out-degree centrality * Attracting components and condensation. * Weakly connected components * Simpler interface to shortest path algorithms * Edgelist format to read and write data with attributes * Attribute matrices * GML reader for nested attributes * Current-flow (random walk) betweenness and closeness. * Directed configuration model, and directed random graph model. * Improved documentation of drawing, shortest paths, and other algorithms * Many more tests, can be run with ?import networkx; networkx.test()? * and much more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.1 API Changes Returning dictionaries Several of the algorithms and the degree() method now return dictionaries keyed by node instead of lists. In some cases there was a with_labels keyword which is no longer necessary. For example, >>> G=nx.Graph() >>> G.add_edge('a','b') >>> G.degree() # returns dictionary of degree keyed by node {'a': 1, 'b': 1} Asking for the degree of a single node still returns a single number >>> G.degree('a') 1 The following now return dictionaries by default (instead of lists) and the with_labels keyword has been removed: * Graph.degree(), MultiGraph.degree(), DiGraph.degree(), DiGraph.in_degree(), DiGraph.out_degree(), MultiDiGraph.degree(), MultiDiGraph.in_degree(), MultiDiGraph.out_degree(). * clustering(), triangles() * node_clique_number(), number_of_cliques(), cliques_containing_node() * eccentricity() The following now return dictionaries by default (instead of lists) * pagerank() * hits() Adding nodes add_nodes_from now accepts (node,attrdict) two-tuples >>> G=nx.Graph() >>> G.add_nodes_from([(1,{'color':'red'})]) Examples * Mayvi2 drawing * Blockmodel * Sampson?s monastery * Ego graph Bug fixes * Support graph attributes with union, intersection, and other graph operations * Improve subgraph speed (and related algorithms such as connected_components_subgraphs()) * Handle multigraphs in more operators (e.g. union) * Handle double-quoted labels with pydot * Normalize betweeness_centrality for undirected graphs correctly * Normalize eigenvector_centrality by l2 norm * read_gml() now returns multigraphs
2010-08-27 05:09:18 +02:00
${PYSITELIB}/networkx/algorithms/mixing.py
${PYSITELIB}/networkx/algorithms/mixing.pyc
${PYSITELIB}/networkx/algorithms/mixing.pyo
Update py-networkx to 1.0.1. Based on PR#42834 by Wen Heping. Update MASTER_SITES, set LICENSE=modified-bsd, 3-caulse BSD. ====================================================================== Networkx-1.0.1 Release date: 11 Jan 2010 See: https://networkx.lanl.gov/trac/timeline Bug fix release for missing setup.py in manifest. ====================================================================== Networkx-1.0 Release date: 8 Jan 2010 See: https://networkx.lanl.gov/trac/timeline New features This release has sigificant changes to parts of the graph API to allow graph, node, and edge attributes. See http://networkx.lanl.gov//reference/api_changes.html * Update Graph, DiGraph, and MultiGraph classes to allow attributes. * Default edge data is now an empty dictionary (was the integer 1) * Difference and intersection operators * Average shortest path * A* (A-Star) algorithm * PageRank, HITS, and eigenvector centrality * Read Pajek files * Line graphs * Minimum spanning tree (Kruskal¡Çs algorithm) * Dense and sparse Fruchterman-Reingold layout * Random clustered graph generator * Directed scale-free graph generator * Faster random regular graph generator * Improved edge color and label drawing with Matplotlib * and much more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.0 Examples * Update to work with networkx-1.0 API * Graph subclass example ====================================================================== Networkx-0.99 Release date: 18 November 2008 See: https://networkx.lanl.gov/trac/timeline New features¢ù This release has sigificant changes to parts of the graph API. See http://networkx.lanl.gov//reference/api_changes.html * Update Graph and DiGraph classes to use weighted graphs as default Change in API for performance and code simplicity. * New MultiGraph and MultiDiGraph classes (replace XGraph and XDiGraph) * Update to use Sphinx documentation system http://networkx.lanl.gov/ * Developer site at https://networkx.lanl.gov/trac/ * Experimental LabeledGraph and LabeledDiGraph * Moved package and file layout to subdirectories. Bug fixes * handle root= option to draw_graphviz correctly Examples * Update to work with networkx-0.99 API * Drawing examples now use matplotlib.pyplot interface * Improved drawings in many examples * New examples - see http://networkx.lanl.gov/examples/
2010-03-03 13:00:59 +01:00
${PYSITELIB}/networkx/algorithms/mst.py
${PYSITELIB}/networkx/algorithms/mst.pyc
${PYSITELIB}/networkx/algorithms/mst.pyo
Update math/py-networkx to 1.2. From PR pkg/43790 by Kamel Derouiche pkgsrc changes: - re-set LICENSE (modified-bsd). upstream changes: Networkx-1.2 Release date: 28 July 2010 See: https://networkx.lanl.gov/trac/timeline New features * Ford-Fulkerson max flow and min cut * Closness vitality * Eulerian circuits * Functions for isolates * Simpler s_max generator * Compatible with IronPython-2.6 * Improved testing functionality: import networkx; networkx.test() tests entire package and skips tests with missing optional packages * All tests work with Python-2.4 * and more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.2 Networkx-1.1 Release date: 21 April 2010 See: https://networkx.lanl.gov/trac/timeline New features * Algorithm for finding a basis for graph cycles * Blockmodeling * Assortativity and mixing matrices * in-degree and out-degree centrality * Attracting components and condensation. * Weakly connected components * Simpler interface to shortest path algorithms * Edgelist format to read and write data with attributes * Attribute matrices * GML reader for nested attributes * Current-flow (random walk) betweenness and closeness. * Directed configuration model, and directed random graph model. * Improved documentation of drawing, shortest paths, and other algorithms * Many more tests, can be run with ?import networkx; networkx.test()? * and much more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.1 API Changes Returning dictionaries Several of the algorithms and the degree() method now return dictionaries keyed by node instead of lists. In some cases there was a with_labels keyword which is no longer necessary. For example, >>> G=nx.Graph() >>> G.add_edge('a','b') >>> G.degree() # returns dictionary of degree keyed by node {'a': 1, 'b': 1} Asking for the degree of a single node still returns a single number >>> G.degree('a') 1 The following now return dictionaries by default (instead of lists) and the with_labels keyword has been removed: * Graph.degree(), MultiGraph.degree(), DiGraph.degree(), DiGraph.in_degree(), DiGraph.out_degree(), MultiDiGraph.degree(), MultiDiGraph.in_degree(), MultiDiGraph.out_degree(). * clustering(), triangles() * node_clique_number(), number_of_cliques(), cliques_containing_node() * eccentricity() The following now return dictionaries by default (instead of lists) * pagerank() * hits() Adding nodes add_nodes_from now accepts (node,attrdict) two-tuples >>> G=nx.Graph() >>> G.add_nodes_from([(1,{'color':'red'})]) Examples * Mayvi2 drawing * Blockmodel * Sampson?s monastery * Ego graph Bug fixes * Support graph attributes with union, intersection, and other graph operations * Improve subgraph speed (and related algorithms such as connected_components_subgraphs()) * Handle multigraphs in more operators (e.g. union) * Handle double-quoted labels with pydot * Normalize betweeness_centrality for undirected graphs correctly * Normalize eigenvector_centrality by l2 norm * read_gml() now returns multigraphs
2010-08-27 05:09:18 +02:00
${PYSITELIB}/networkx/algorithms/operators.py
${PYSITELIB}/networkx/algorithms/operators.pyc
${PYSITELIB}/networkx/algorithms/operators.pyo
${PYSITELIB}/networkx/algorithms/shortest_paths/__init__.py
${PYSITELIB}/networkx/algorithms/shortest_paths/__init__.pyc
${PYSITELIB}/networkx/algorithms/shortest_paths/__init__.pyo
${PYSITELIB}/networkx/algorithms/shortest_paths/astar.py
${PYSITELIB}/networkx/algorithms/shortest_paths/astar.pyc
${PYSITELIB}/networkx/algorithms/shortest_paths/astar.pyo
${PYSITELIB}/networkx/algorithms/shortest_paths/generic.py
${PYSITELIB}/networkx/algorithms/shortest_paths/generic.pyc
${PYSITELIB}/networkx/algorithms/shortest_paths/generic.pyo
${PYSITELIB}/networkx/algorithms/shortest_paths/tests/test_astar.py
${PYSITELIB}/networkx/algorithms/shortest_paths/tests/test_astar.pyc
${PYSITELIB}/networkx/algorithms/shortest_paths/tests/test_astar.pyo
${PYSITELIB}/networkx/algorithms/shortest_paths/tests/test_generic.py
${PYSITELIB}/networkx/algorithms/shortest_paths/tests/test_generic.pyc
${PYSITELIB}/networkx/algorithms/shortest_paths/tests/test_generic.pyo
${PYSITELIB}/networkx/algorithms/shortest_paths/tests/test_unweighted.py
${PYSITELIB}/networkx/algorithms/shortest_paths/tests/test_unweighted.pyc
${PYSITELIB}/networkx/algorithms/shortest_paths/tests/test_unweighted.pyo
${PYSITELIB}/networkx/algorithms/shortest_paths/tests/test_weighted.py
${PYSITELIB}/networkx/algorithms/shortest_paths/tests/test_weighted.pyc
${PYSITELIB}/networkx/algorithms/shortest_paths/tests/test_weighted.pyo
${PYSITELIB}/networkx/algorithms/shortest_paths/unweighted.py
${PYSITELIB}/networkx/algorithms/shortest_paths/unweighted.pyc
${PYSITELIB}/networkx/algorithms/shortest_paths/unweighted.pyo
${PYSITELIB}/networkx/algorithms/shortest_paths/weighted.py
${PYSITELIB}/networkx/algorithms/shortest_paths/weighted.pyc
${PYSITELIB}/networkx/algorithms/shortest_paths/weighted.pyo
${PYSITELIB}/networkx/algorithms/smetric.py
${PYSITELIB}/networkx/algorithms/smetric.pyc
${PYSITELIB}/networkx/algorithms/smetric.pyo
${PYSITELIB}/networkx/algorithms/tests/test_bipartite.py
${PYSITELIB}/networkx/algorithms/tests/test_bipartite.pyc
${PYSITELIB}/networkx/algorithms/tests/test_bipartite.pyo
${PYSITELIB}/networkx/algorithms/tests/test_block.py
${PYSITELIB}/networkx/algorithms/tests/test_block.pyc
${PYSITELIB}/networkx/algorithms/tests/test_block.pyo
${PYSITELIB}/networkx/algorithms/tests/test_cluster.py
${PYSITELIB}/networkx/algorithms/tests/test_cluster.pyc
${PYSITELIB}/networkx/algorithms/tests/test_cluster.pyo
${PYSITELIB}/networkx/algorithms/tests/test_cycles.py
${PYSITELIB}/networkx/algorithms/tests/test_cycles.pyc
${PYSITELIB}/networkx/algorithms/tests/test_cycles.pyo
${PYSITELIB}/networkx/algorithms/tests/test_distance_measures.py
${PYSITELIB}/networkx/algorithms/tests/test_distance_measures.pyc
${PYSITELIB}/networkx/algorithms/tests/test_distance_measures.pyo
${PYSITELIB}/networkx/algorithms/tests/test_euler.py
${PYSITELIB}/networkx/algorithms/tests/test_euler.pyc
${PYSITELIB}/networkx/algorithms/tests/test_euler.pyo
${PYSITELIB}/networkx/algorithms/tests/test_mixing_attributes.py
${PYSITELIB}/networkx/algorithms/tests/test_mixing_attributes.pyc
${PYSITELIB}/networkx/algorithms/tests/test_mixing_attributes.pyo
${PYSITELIB}/networkx/algorithms/tests/test_mixing_degree.py
${PYSITELIB}/networkx/algorithms/tests/test_mixing_degree.pyc
${PYSITELIB}/networkx/algorithms/tests/test_mixing_degree.pyo
${PYSITELIB}/networkx/algorithms/tests/test_mst.py
${PYSITELIB}/networkx/algorithms/tests/test_mst.pyc
${PYSITELIB}/networkx/algorithms/tests/test_mst.pyo
${PYSITELIB}/networkx/algorithms/tests/test_operators.py
${PYSITELIB}/networkx/algorithms/tests/test_operators.pyc
${PYSITELIB}/networkx/algorithms/tests/test_operators.pyo
${PYSITELIB}/networkx/algorithms/tests/test_smetric.py
${PYSITELIB}/networkx/algorithms/tests/test_smetric.pyc
${PYSITELIB}/networkx/algorithms/tests/test_smetric.pyo
${PYSITELIB}/networkx/algorithms/tests/test_vitality.py
${PYSITELIB}/networkx/algorithms/tests/test_vitality.pyc
${PYSITELIB}/networkx/algorithms/tests/test_vitality.pyo
Update py-networkx to 1.0.1. Based on PR#42834 by Wen Heping. Update MASTER_SITES, set LICENSE=modified-bsd, 3-caulse BSD. ====================================================================== Networkx-1.0.1 Release date: 11 Jan 2010 See: https://networkx.lanl.gov/trac/timeline Bug fix release for missing setup.py in manifest. ====================================================================== Networkx-1.0 Release date: 8 Jan 2010 See: https://networkx.lanl.gov/trac/timeline New features This release has sigificant changes to parts of the graph API to allow graph, node, and edge attributes. See http://networkx.lanl.gov//reference/api_changes.html * Update Graph, DiGraph, and MultiGraph classes to allow attributes. * Default edge data is now an empty dictionary (was the integer 1) * Difference and intersection operators * Average shortest path * A* (A-Star) algorithm * PageRank, HITS, and eigenvector centrality * Read Pajek files * Line graphs * Minimum spanning tree (Kruskal¡Çs algorithm) * Dense and sparse Fruchterman-Reingold layout * Random clustered graph generator * Directed scale-free graph generator * Faster random regular graph generator * Improved edge color and label drawing with Matplotlib * and much more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.0 Examples * Update to work with networkx-1.0 API * Graph subclass example ====================================================================== Networkx-0.99 Release date: 18 November 2008 See: https://networkx.lanl.gov/trac/timeline New features¢ù This release has sigificant changes to parts of the graph API. See http://networkx.lanl.gov//reference/api_changes.html * Update Graph and DiGraph classes to use weighted graphs as default Change in API for performance and code simplicity. * New MultiGraph and MultiDiGraph classes (replace XGraph and XDiGraph) * Update to use Sphinx documentation system http://networkx.lanl.gov/ * Developer site at https://networkx.lanl.gov/trac/ * Experimental LabeledGraph and LabeledDiGraph * Moved package and file layout to subdirectories. Bug fixes * handle root= option to draw_graphviz correctly Examples * Update to work with networkx-0.99 API * Drawing examples now use matplotlib.pyplot interface * Improved drawings in many examples * New examples - see http://networkx.lanl.gov/examples/
2010-03-03 13:00:59 +01:00
${PYSITELIB}/networkx/algorithms/traversal/__init__.py
${PYSITELIB}/networkx/algorithms/traversal/__init__.pyc
${PYSITELIB}/networkx/algorithms/traversal/__init__.pyo
Update math/py-networkx to 1.2. From PR pkg/43790 by Kamel Derouiche pkgsrc changes: - re-set LICENSE (modified-bsd). upstream changes: Networkx-1.2 Release date: 28 July 2010 See: https://networkx.lanl.gov/trac/timeline New features * Ford-Fulkerson max flow and min cut * Closness vitality * Eulerian circuits * Functions for isolates * Simpler s_max generator * Compatible with IronPython-2.6 * Improved testing functionality: import networkx; networkx.test() tests entire package and skips tests with missing optional packages * All tests work with Python-2.4 * and more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.2 Networkx-1.1 Release date: 21 April 2010 See: https://networkx.lanl.gov/trac/timeline New features * Algorithm for finding a basis for graph cycles * Blockmodeling * Assortativity and mixing matrices * in-degree and out-degree centrality * Attracting components and condensation. * Weakly connected components * Simpler interface to shortest path algorithms * Edgelist format to read and write data with attributes * Attribute matrices * GML reader for nested attributes * Current-flow (random walk) betweenness and closeness. * Directed configuration model, and directed random graph model. * Improved documentation of drawing, shortest paths, and other algorithms * Many more tests, can be run with ?import networkx; networkx.test()? * and much more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.1 API Changes Returning dictionaries Several of the algorithms and the degree() method now return dictionaries keyed by node instead of lists. In some cases there was a with_labels keyword which is no longer necessary. For example, >>> G=nx.Graph() >>> G.add_edge('a','b') >>> G.degree() # returns dictionary of degree keyed by node {'a': 1, 'b': 1} Asking for the degree of a single node still returns a single number >>> G.degree('a') 1 The following now return dictionaries by default (instead of lists) and the with_labels keyword has been removed: * Graph.degree(), MultiGraph.degree(), DiGraph.degree(), DiGraph.in_degree(), DiGraph.out_degree(), MultiDiGraph.degree(), MultiDiGraph.in_degree(), MultiDiGraph.out_degree(). * clustering(), triangles() * node_clique_number(), number_of_cliques(), cliques_containing_node() * eccentricity() The following now return dictionaries by default (instead of lists) * pagerank() * hits() Adding nodes add_nodes_from now accepts (node,attrdict) two-tuples >>> G=nx.Graph() >>> G.add_nodes_from([(1,{'color':'red'})]) Examples * Mayvi2 drawing * Blockmodel * Sampson?s monastery * Ego graph Bug fixes * Support graph attributes with union, intersection, and other graph operations * Improve subgraph speed (and related algorithms such as connected_components_subgraphs()) * Handle multigraphs in more operators (e.g. union) * Handle double-quoted labels with pydot * Normalize betweeness_centrality for undirected graphs correctly * Normalize eigenvector_centrality by l2 norm * read_gml() now returns multigraphs
2010-08-27 05:09:18 +02:00
${PYSITELIB}/networkx/algorithms/traversal/depth_first_search.py
${PYSITELIB}/networkx/algorithms/traversal/depth_first_search.pyc
${PYSITELIB}/networkx/algorithms/traversal/depth_first_search.pyo
${PYSITELIB}/networkx/algorithms/vitality.py
${PYSITELIB}/networkx/algorithms/vitality.pyc
${PYSITELIB}/networkx/algorithms/vitality.pyo
Update py-networkx to 1.0.1. Based on PR#42834 by Wen Heping. Update MASTER_SITES, set LICENSE=modified-bsd, 3-caulse BSD. ====================================================================== Networkx-1.0.1 Release date: 11 Jan 2010 See: https://networkx.lanl.gov/trac/timeline Bug fix release for missing setup.py in manifest. ====================================================================== Networkx-1.0 Release date: 8 Jan 2010 See: https://networkx.lanl.gov/trac/timeline New features This release has sigificant changes to parts of the graph API to allow graph, node, and edge attributes. See http://networkx.lanl.gov//reference/api_changes.html * Update Graph, DiGraph, and MultiGraph classes to allow attributes. * Default edge data is now an empty dictionary (was the integer 1) * Difference and intersection operators * Average shortest path * A* (A-Star) algorithm * PageRank, HITS, and eigenvector centrality * Read Pajek files * Line graphs * Minimum spanning tree (Kruskal¡Çs algorithm) * Dense and sparse Fruchterman-Reingold layout * Random clustered graph generator * Directed scale-free graph generator * Faster random regular graph generator * Improved edge color and label drawing with Matplotlib * and much more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.0 Examples * Update to work with networkx-1.0 API * Graph subclass example ====================================================================== Networkx-0.99 Release date: 18 November 2008 See: https://networkx.lanl.gov/trac/timeline New features¢ù This release has sigificant changes to parts of the graph API. See http://networkx.lanl.gov//reference/api_changes.html * Update Graph and DiGraph classes to use weighted graphs as default Change in API for performance and code simplicity. * New MultiGraph and MultiDiGraph classes (replace XGraph and XDiGraph) * Update to use Sphinx documentation system http://networkx.lanl.gov/ * Developer site at https://networkx.lanl.gov/trac/ * Experimental LabeledGraph and LabeledDiGraph * Moved package and file layout to subdirectories. Bug fixes * handle root= option to draw_graphviz correctly Examples * Update to work with networkx-0.99 API * Drawing examples now use matplotlib.pyplot interface * Improved drawings in many examples * New examples - see http://networkx.lanl.gov/examples/
2010-03-03 13:00:59 +01:00
${PYSITELIB}/networkx/classes/__init__.py
${PYSITELIB}/networkx/classes/__init__.pyc
${PYSITELIB}/networkx/classes/__init__.pyo
${PYSITELIB}/networkx/classes/digraph.py
${PYSITELIB}/networkx/classes/digraph.pyc
${PYSITELIB}/networkx/classes/digraph.pyo
${PYSITELIB}/networkx/classes/function.py
${PYSITELIB}/networkx/classes/function.pyc
${PYSITELIB}/networkx/classes/function.pyo
${PYSITELIB}/networkx/classes/graph.py
${PYSITELIB}/networkx/classes/graph.pyc
${PYSITELIB}/networkx/classes/graph.pyo
${PYSITELIB}/networkx/classes/multidigraph.py
${PYSITELIB}/networkx/classes/multidigraph.pyc
${PYSITELIB}/networkx/classes/multidigraph.pyo
${PYSITELIB}/networkx/classes/multigraph.py
${PYSITELIB}/networkx/classes/multigraph.pyc
${PYSITELIB}/networkx/classes/multigraph.pyo
Update math/py-networkx to 1.2. From PR pkg/43790 by Kamel Derouiche pkgsrc changes: - re-set LICENSE (modified-bsd). upstream changes: Networkx-1.2 Release date: 28 July 2010 See: https://networkx.lanl.gov/trac/timeline New features * Ford-Fulkerson max flow and min cut * Closness vitality * Eulerian circuits * Functions for isolates * Simpler s_max generator * Compatible with IronPython-2.6 * Improved testing functionality: import networkx; networkx.test() tests entire package and skips tests with missing optional packages * All tests work with Python-2.4 * and more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.2 Networkx-1.1 Release date: 21 April 2010 See: https://networkx.lanl.gov/trac/timeline New features * Algorithm for finding a basis for graph cycles * Blockmodeling * Assortativity and mixing matrices * in-degree and out-degree centrality * Attracting components and condensation. * Weakly connected components * Simpler interface to shortest path algorithms * Edgelist format to read and write data with attributes * Attribute matrices * GML reader for nested attributes * Current-flow (random walk) betweenness and closeness. * Directed configuration model, and directed random graph model. * Improved documentation of drawing, shortest paths, and other algorithms * Many more tests, can be run with ?import networkx; networkx.test()? * and much more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.1 API Changes Returning dictionaries Several of the algorithms and the degree() method now return dictionaries keyed by node instead of lists. In some cases there was a with_labels keyword which is no longer necessary. For example, >>> G=nx.Graph() >>> G.add_edge('a','b') >>> G.degree() # returns dictionary of degree keyed by node {'a': 1, 'b': 1} Asking for the degree of a single node still returns a single number >>> G.degree('a') 1 The following now return dictionaries by default (instead of lists) and the with_labels keyword has been removed: * Graph.degree(), MultiGraph.degree(), DiGraph.degree(), DiGraph.in_degree(), DiGraph.out_degree(), MultiDiGraph.degree(), MultiDiGraph.in_degree(), MultiDiGraph.out_degree(). * clustering(), triangles() * node_clique_number(), number_of_cliques(), cliques_containing_node() * eccentricity() The following now return dictionaries by default (instead of lists) * pagerank() * hits() Adding nodes add_nodes_from now accepts (node,attrdict) two-tuples >>> G=nx.Graph() >>> G.add_nodes_from([(1,{'color':'red'})]) Examples * Mayvi2 drawing * Blockmodel * Sampson?s monastery * Ego graph Bug fixes * Support graph attributes with union, intersection, and other graph operations * Improve subgraph speed (and related algorithms such as connected_components_subgraphs()) * Handle multigraphs in more operators (e.g. union) * Handle double-quoted labels with pydot * Normalize betweeness_centrality for undirected graphs correctly * Normalize eigenvector_centrality by l2 norm * read_gml() now returns multigraphs
2010-08-27 05:09:18 +02:00
${PYSITELIB}/networkx/classes/tests/test_digraph.py
${PYSITELIB}/networkx/classes/tests/test_digraph.pyc
${PYSITELIB}/networkx/classes/tests/test_digraph.pyo
${PYSITELIB}/networkx/classes/tests/test_function.py
${PYSITELIB}/networkx/classes/tests/test_function.pyc
${PYSITELIB}/networkx/classes/tests/test_function.pyo
${PYSITELIB}/networkx/classes/tests/test_graph.py
${PYSITELIB}/networkx/classes/tests/test_graph.pyc
${PYSITELIB}/networkx/classes/tests/test_graph.pyo
${PYSITELIB}/networkx/classes/tests/test_multidigraph.py
${PYSITELIB}/networkx/classes/tests/test_multidigraph.pyc
${PYSITELIB}/networkx/classes/tests/test_multidigraph.pyo
${PYSITELIB}/networkx/classes/tests/test_multigraph.py
${PYSITELIB}/networkx/classes/tests/test_multigraph.pyc
${PYSITELIB}/networkx/classes/tests/test_multigraph.pyo
Add math/py-networkx package.
2008-08-27 20:53:42 +02:00
${PYSITELIB}/networkx/convert.py
${PYSITELIB}/networkx/convert.pyc
${PYSITELIB}/networkx/convert.pyo
${PYSITELIB}/networkx/drawing/__init__.py
${PYSITELIB}/networkx/drawing/__init__.pyc
${PYSITELIB}/networkx/drawing/__init__.pyo
${PYSITELIB}/networkx/drawing/layout.py
${PYSITELIB}/networkx/drawing/layout.pyc
${PYSITELIB}/networkx/drawing/layout.pyo
${PYSITELIB}/networkx/drawing/nx_agraph.py
${PYSITELIB}/networkx/drawing/nx_agraph.pyc
${PYSITELIB}/networkx/drawing/nx_agraph.pyo
${PYSITELIB}/networkx/drawing/nx_pydot.py
${PYSITELIB}/networkx/drawing/nx_pydot.pyc
${PYSITELIB}/networkx/drawing/nx_pydot.pyo
${PYSITELIB}/networkx/drawing/nx_pylab.py
${PYSITELIB}/networkx/drawing/nx_pylab.pyc
${PYSITELIB}/networkx/drawing/nx_pylab.pyo
Update math/py-networkx to 1.2. From PR pkg/43790 by Kamel Derouiche pkgsrc changes: - re-set LICENSE (modified-bsd). upstream changes: Networkx-1.2 Release date: 28 July 2010 See: https://networkx.lanl.gov/trac/timeline New features * Ford-Fulkerson max flow and min cut * Closness vitality * Eulerian circuits * Functions for isolates * Simpler s_max generator * Compatible with IronPython-2.6 * Improved testing functionality: import networkx; networkx.test() tests entire package and skips tests with missing optional packages * All tests work with Python-2.4 * and more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.2 Networkx-1.1 Release date: 21 April 2010 See: https://networkx.lanl.gov/trac/timeline New features * Algorithm for finding a basis for graph cycles * Blockmodeling * Assortativity and mixing matrices * in-degree and out-degree centrality * Attracting components and condensation. * Weakly connected components * Simpler interface to shortest path algorithms * Edgelist format to read and write data with attributes * Attribute matrices * GML reader for nested attributes * Current-flow (random walk) betweenness and closeness. * Directed configuration model, and directed random graph model. * Improved documentation of drawing, shortest paths, and other algorithms * Many more tests, can be run with ?import networkx; networkx.test()? * and much more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.1 API Changes Returning dictionaries Several of the algorithms and the degree() method now return dictionaries keyed by node instead of lists. In some cases there was a with_labels keyword which is no longer necessary. For example, >>> G=nx.Graph() >>> G.add_edge('a','b') >>> G.degree() # returns dictionary of degree keyed by node {'a': 1, 'b': 1} Asking for the degree of a single node still returns a single number >>> G.degree('a') 1 The following now return dictionaries by default (instead of lists) and the with_labels keyword has been removed: * Graph.degree(), MultiGraph.degree(), DiGraph.degree(), DiGraph.in_degree(), DiGraph.out_degree(), MultiDiGraph.degree(), MultiDiGraph.in_degree(), MultiDiGraph.out_degree(). * clustering(), triangles() * node_clique_number(), number_of_cliques(), cliques_containing_node() * eccentricity() The following now return dictionaries by default (instead of lists) * pagerank() * hits() Adding nodes add_nodes_from now accepts (node,attrdict) two-tuples >>> G=nx.Graph() >>> G.add_nodes_from([(1,{'color':'red'})]) Examples * Mayvi2 drawing * Blockmodel * Sampson?s monastery * Ego graph Bug fixes * Support graph attributes with union, intersection, and other graph operations * Improve subgraph speed (and related algorithms such as connected_components_subgraphs()) * Handle multigraphs in more operators (e.g. union) * Handle double-quoted labels with pydot * Normalize betweeness_centrality for undirected graphs correctly * Normalize eigenvector_centrality by l2 norm * read_gml() now returns multigraphs
2010-08-27 05:09:18 +02:00
${PYSITELIB}/networkx/drawing/tests/test_agraph.py
${PYSITELIB}/networkx/drawing/tests/test_agraph.pyc
${PYSITELIB}/networkx/drawing/tests/test_agraph.pyo
${PYSITELIB}/networkx/drawing/tests/test_layout.py
${PYSITELIB}/networkx/drawing/tests/test_layout.pyc
${PYSITELIB}/networkx/drawing/tests/test_layout.pyo
${PYSITELIB}/networkx/drawing/tests/test_pydot.py
${PYSITELIB}/networkx/drawing/tests/test_pydot.pyc
${PYSITELIB}/networkx/drawing/tests/test_pydot.pyo
${PYSITELIB}/networkx/drawing/tests/test_pylab.py
${PYSITELIB}/networkx/drawing/tests/test_pylab.pyc
${PYSITELIB}/networkx/drawing/tests/test_pylab.pyo
Add math/py-networkx package.
2008-08-27 20:53:42 +02:00
${PYSITELIB}/networkx/exception.py
${PYSITELIB}/networkx/exception.pyc
${PYSITELIB}/networkx/exception.pyo
${PYSITELIB}/networkx/generators/__init__.py
${PYSITELIB}/networkx/generators/__init__.pyc
${PYSITELIB}/networkx/generators/__init__.pyo
${PYSITELIB}/networkx/generators/atlas.py
${PYSITELIB}/networkx/generators/atlas.pyc
${PYSITELIB}/networkx/generators/atlas.pyo
${PYSITELIB}/networkx/generators/bipartite.py
${PYSITELIB}/networkx/generators/bipartite.pyc
${PYSITELIB}/networkx/generators/bipartite.pyo
${PYSITELIB}/networkx/generators/classic.py
${PYSITELIB}/networkx/generators/classic.pyc
${PYSITELIB}/networkx/generators/classic.pyo
${PYSITELIB}/networkx/generators/degree_seq.py
${PYSITELIB}/networkx/generators/degree_seq.pyc
${PYSITELIB}/networkx/generators/degree_seq.pyo
${PYSITELIB}/networkx/generators/directed.py
${PYSITELIB}/networkx/generators/directed.pyc
${PYSITELIB}/networkx/generators/directed.pyo
Update math/py-networkx to 1.2. From PR pkg/43790 by Kamel Derouiche pkgsrc changes: - re-set LICENSE (modified-bsd). upstream changes: Networkx-1.2 Release date: 28 July 2010 See: https://networkx.lanl.gov/trac/timeline New features * Ford-Fulkerson max flow and min cut * Closness vitality * Eulerian circuits * Functions for isolates * Simpler s_max generator * Compatible with IronPython-2.6 * Improved testing functionality: import networkx; networkx.test() tests entire package and skips tests with missing optional packages * All tests work with Python-2.4 * and more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.2 Networkx-1.1 Release date: 21 April 2010 See: https://networkx.lanl.gov/trac/timeline New features * Algorithm for finding a basis for graph cycles * Blockmodeling * Assortativity and mixing matrices * in-degree and out-degree centrality * Attracting components and condensation. * Weakly connected components * Simpler interface to shortest path algorithms * Edgelist format to read and write data with attributes * Attribute matrices * GML reader for nested attributes * Current-flow (random walk) betweenness and closeness. * Directed configuration model, and directed random graph model. * Improved documentation of drawing, shortest paths, and other algorithms * Many more tests, can be run with ?import networkx; networkx.test()? * and much more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.1 API Changes Returning dictionaries Several of the algorithms and the degree() method now return dictionaries keyed by node instead of lists. In some cases there was a with_labels keyword which is no longer necessary. For example, >>> G=nx.Graph() >>> G.add_edge('a','b') >>> G.degree() # returns dictionary of degree keyed by node {'a': 1, 'b': 1} Asking for the degree of a single node still returns a single number >>> G.degree('a') 1 The following now return dictionaries by default (instead of lists) and the with_labels keyword has been removed: * Graph.degree(), MultiGraph.degree(), DiGraph.degree(), DiGraph.in_degree(), DiGraph.out_degree(), MultiDiGraph.degree(), MultiDiGraph.in_degree(), MultiDiGraph.out_degree(). * clustering(), triangles() * node_clique_number(), number_of_cliques(), cliques_containing_node() * eccentricity() The following now return dictionaries by default (instead of lists) * pagerank() * hits() Adding nodes add_nodes_from now accepts (node,attrdict) two-tuples >>> G=nx.Graph() >>> G.add_nodes_from([(1,{'color':'red'})]) Examples * Mayvi2 drawing * Blockmodel * Sampson?s monastery * Ego graph Bug fixes * Support graph attributes with union, intersection, and other graph operations * Improve subgraph speed (and related algorithms such as connected_components_subgraphs()) * Handle multigraphs in more operators (e.g. union) * Handle double-quoted labels with pydot * Normalize betweeness_centrality for undirected graphs correctly * Normalize eigenvector_centrality by l2 norm * read_gml() now returns multigraphs
2010-08-27 05:09:18 +02:00
${PYSITELIB}/networkx/generators/ego.py
${PYSITELIB}/networkx/generators/ego.pyc
${PYSITELIB}/networkx/generators/ego.pyo
Add math/py-networkx package.
2008-08-27 20:53:42 +02:00
${PYSITELIB}/networkx/generators/geometric.py
${PYSITELIB}/networkx/generators/geometric.pyc
${PYSITELIB}/networkx/generators/geometric.pyo
Update py-networkx to 1.0.1. Based on PR#42834 by Wen Heping. Update MASTER_SITES, set LICENSE=modified-bsd, 3-caulse BSD. ====================================================================== Networkx-1.0.1 Release date: 11 Jan 2010 See: https://networkx.lanl.gov/trac/timeline Bug fix release for missing setup.py in manifest. ====================================================================== Networkx-1.0 Release date: 8 Jan 2010 See: https://networkx.lanl.gov/trac/timeline New features This release has sigificant changes to parts of the graph API to allow graph, node, and edge attributes. See http://networkx.lanl.gov//reference/api_changes.html * Update Graph, DiGraph, and MultiGraph classes to allow attributes. * Default edge data is now an empty dictionary (was the integer 1) * Difference and intersection operators * Average shortest path * A* (A-Star) algorithm * PageRank, HITS, and eigenvector centrality * Read Pajek files * Line graphs * Minimum spanning tree (Kruskal¡Çs algorithm) * Dense and sparse Fruchterman-Reingold layout * Random clustered graph generator * Directed scale-free graph generator * Faster random regular graph generator * Improved edge color and label drawing with Matplotlib * and much more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.0 Examples * Update to work with networkx-1.0 API * Graph subclass example ====================================================================== Networkx-0.99 Release date: 18 November 2008 See: https://networkx.lanl.gov/trac/timeline New features¢ù This release has sigificant changes to parts of the graph API. See http://networkx.lanl.gov//reference/api_changes.html * Update Graph and DiGraph classes to use weighted graphs as default Change in API for performance and code simplicity. * New MultiGraph and MultiDiGraph classes (replace XGraph and XDiGraph) * Update to use Sphinx documentation system http://networkx.lanl.gov/ * Developer site at https://networkx.lanl.gov/trac/ * Experimental LabeledGraph and LabeledDiGraph * Moved package and file layout to subdirectories. Bug fixes * handle root= option to draw_graphviz correctly Examples * Update to work with networkx-0.99 API * Drawing examples now use matplotlib.pyplot interface * Improved drawings in many examples * New examples - see http://networkx.lanl.gov/examples/
2010-03-03 13:00:59 +01:00
${PYSITELIB}/networkx/generators/hybrid.py
${PYSITELIB}/networkx/generators/hybrid.pyc
${PYSITELIB}/networkx/generators/hybrid.pyo
Update math/py-networkx to 1.2. From PR pkg/43790 by Kamel Derouiche pkgsrc changes: - re-set LICENSE (modified-bsd). upstream changes: Networkx-1.2 Release date: 28 July 2010 See: https://networkx.lanl.gov/trac/timeline New features * Ford-Fulkerson max flow and min cut * Closness vitality * Eulerian circuits * Functions for isolates * Simpler s_max generator * Compatible with IronPython-2.6 * Improved testing functionality: import networkx; networkx.test() tests entire package and skips tests with missing optional packages * All tests work with Python-2.4 * and more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.2 Networkx-1.1 Release date: 21 April 2010 See: https://networkx.lanl.gov/trac/timeline New features * Algorithm for finding a basis for graph cycles * Blockmodeling * Assortativity and mixing matrices * in-degree and out-degree centrality * Attracting components and condensation. * Weakly connected components * Simpler interface to shortest path algorithms * Edgelist format to read and write data with attributes * Attribute matrices * GML reader for nested attributes * Current-flow (random walk) betweenness and closeness. * Directed configuration model, and directed random graph model. * Improved documentation of drawing, shortest paths, and other algorithms * Many more tests, can be run with ?import networkx; networkx.test()? * and much more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.1 API Changes Returning dictionaries Several of the algorithms and the degree() method now return dictionaries keyed by node instead of lists. In some cases there was a with_labels keyword which is no longer necessary. For example, >>> G=nx.Graph() >>> G.add_edge('a','b') >>> G.degree() # returns dictionary of degree keyed by node {'a': 1, 'b': 1} Asking for the degree of a single node still returns a single number >>> G.degree('a') 1 The following now return dictionaries by default (instead of lists) and the with_labels keyword has been removed: * Graph.degree(), MultiGraph.degree(), DiGraph.degree(), DiGraph.in_degree(), DiGraph.out_degree(), MultiDiGraph.degree(), MultiDiGraph.in_degree(), MultiDiGraph.out_degree(). * clustering(), triangles() * node_clique_number(), number_of_cliques(), cliques_containing_node() * eccentricity() The following now return dictionaries by default (instead of lists) * pagerank() * hits() Adding nodes add_nodes_from now accepts (node,attrdict) two-tuples >>> G=nx.Graph() >>> G.add_nodes_from([(1,{'color':'red'})]) Examples * Mayvi2 drawing * Blockmodel * Sampson?s monastery * Ego graph Bug fixes * Support graph attributes with union, intersection, and other graph operations * Improve subgraph speed (and related algorithms such as connected_components_subgraphs()) * Handle multigraphs in more operators (e.g. union) * Handle double-quoted labels with pydot * Normalize betweeness_centrality for undirected graphs correctly * Normalize eigenvector_centrality by l2 norm * read_gml() now returns multigraphs
2010-08-27 05:09:18 +02:00
${PYSITELIB}/networkx/generators/line.py
${PYSITELIB}/networkx/generators/line.pyc
${PYSITELIB}/networkx/generators/line.pyo
Add math/py-networkx package.
2008-08-27 20:53:42 +02:00
${PYSITELIB}/networkx/generators/random_graphs.py
${PYSITELIB}/networkx/generators/random_graphs.pyc
${PYSITELIB}/networkx/generators/random_graphs.pyo
${PYSITELIB}/networkx/generators/small.py
${PYSITELIB}/networkx/generators/small.pyc
${PYSITELIB}/networkx/generators/small.pyo
Update math/py-networkx to 1.2. From PR pkg/43790 by Kamel Derouiche pkgsrc changes: - re-set LICENSE (modified-bsd). upstream changes: Networkx-1.2 Release date: 28 July 2010 See: https://networkx.lanl.gov/trac/timeline New features * Ford-Fulkerson max flow and min cut * Closness vitality * Eulerian circuits * Functions for isolates * Simpler s_max generator * Compatible with IronPython-2.6 * Improved testing functionality: import networkx; networkx.test() tests entire package and skips tests with missing optional packages * All tests work with Python-2.4 * and more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.2 Networkx-1.1 Release date: 21 April 2010 See: https://networkx.lanl.gov/trac/timeline New features * Algorithm for finding a basis for graph cycles * Blockmodeling * Assortativity and mixing matrices * in-degree and out-degree centrality * Attracting components and condensation. * Weakly connected components * Simpler interface to shortest path algorithms * Edgelist format to read and write data with attributes * Attribute matrices * GML reader for nested attributes * Current-flow (random walk) betweenness and closeness. * Directed configuration model, and directed random graph model. * Improved documentation of drawing, shortest paths, and other algorithms * Many more tests, can be run with ?import networkx; networkx.test()? * and much more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.1 API Changes Returning dictionaries Several of the algorithms and the degree() method now return dictionaries keyed by node instead of lists. In some cases there was a with_labels keyword which is no longer necessary. For example, >>> G=nx.Graph() >>> G.add_edge('a','b') >>> G.degree() # returns dictionary of degree keyed by node {'a': 1, 'b': 1} Asking for the degree of a single node still returns a single number >>> G.degree('a') 1 The following now return dictionaries by default (instead of lists) and the with_labels keyword has been removed: * Graph.degree(), MultiGraph.degree(), DiGraph.degree(), DiGraph.in_degree(), DiGraph.out_degree(), MultiDiGraph.degree(), MultiDiGraph.in_degree(), MultiDiGraph.out_degree(). * clustering(), triangles() * node_clique_number(), number_of_cliques(), cliques_containing_node() * eccentricity() The following now return dictionaries by default (instead of lists) * pagerank() * hits() Adding nodes add_nodes_from now accepts (node,attrdict) two-tuples >>> G=nx.Graph() >>> G.add_nodes_from([(1,{'color':'red'})]) Examples * Mayvi2 drawing * Blockmodel * Sampson?s monastery * Ego graph Bug fixes * Support graph attributes with union, intersection, and other graph operations * Improve subgraph speed (and related algorithms such as connected_components_subgraphs()) * Handle multigraphs in more operators (e.g. union) * Handle double-quoted labels with pydot * Normalize betweeness_centrality for undirected graphs correctly * Normalize eigenvector_centrality by l2 norm * read_gml() now returns multigraphs
2010-08-27 05:09:18 +02:00
${PYSITELIB}/networkx/generators/stochastic.py
${PYSITELIB}/networkx/generators/stochastic.pyc
${PYSITELIB}/networkx/generators/stochastic.pyo
${PYSITELIB}/networkx/generators/tests/test_degree_seq.py
${PYSITELIB}/networkx/generators/tests/test_degree_seq.pyc
${PYSITELIB}/networkx/generators/tests/test_degree_seq.pyo
Update py-networkx to 1.0.1. Based on PR#42834 by Wen Heping. Update MASTER_SITES, set LICENSE=modified-bsd, 3-caulse BSD. ====================================================================== Networkx-1.0.1 Release date: 11 Jan 2010 See: https://networkx.lanl.gov/trac/timeline Bug fix release for missing setup.py in manifest. ====================================================================== Networkx-1.0 Release date: 8 Jan 2010 See: https://networkx.lanl.gov/trac/timeline New features This release has sigificant changes to parts of the graph API to allow graph, node, and edge attributes. See http://networkx.lanl.gov//reference/api_changes.html * Update Graph, DiGraph, and MultiGraph classes to allow attributes. * Default edge data is now an empty dictionary (was the integer 1) * Difference and intersection operators * Average shortest path * A* (A-Star) algorithm * PageRank, HITS, and eigenvector centrality * Read Pajek files * Line graphs * Minimum spanning tree (Kruskal¡Çs algorithm) * Dense and sparse Fruchterman-Reingold layout * Random clustered graph generator * Directed scale-free graph generator * Faster random regular graph generator * Improved edge color and label drawing with Matplotlib * and much more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.0 Examples * Update to work with networkx-1.0 API * Graph subclass example ====================================================================== Networkx-0.99 Release date: 18 November 2008 See: https://networkx.lanl.gov/trac/timeline New features¢ù This release has sigificant changes to parts of the graph API. See http://networkx.lanl.gov//reference/api_changes.html * Update Graph and DiGraph classes to use weighted graphs as default Change in API for performance and code simplicity. * New MultiGraph and MultiDiGraph classes (replace XGraph and XDiGraph) * Update to use Sphinx documentation system http://networkx.lanl.gov/ * Developer site at https://networkx.lanl.gov/trac/ * Experimental LabeledGraph and LabeledDiGraph * Moved package and file layout to subdirectories. Bug fixes * handle root= option to draw_graphviz correctly Examples * Update to work with networkx-0.99 API * Drawing examples now use matplotlib.pyplot interface * Improved drawings in many examples * New examples - see http://networkx.lanl.gov/examples/
2010-03-03 13:00:59 +01:00
${PYSITELIB}/networkx/generators/threshold.py
${PYSITELIB}/networkx/generators/threshold.pyc
${PYSITELIB}/networkx/generators/threshold.pyo
${PYSITELIB}/networkx/linalg/__init__.py
${PYSITELIB}/networkx/linalg/__init__.pyc
${PYSITELIB}/networkx/linalg/__init__.pyo
Update math/py-networkx to 1.2. From PR pkg/43790 by Kamel Derouiche pkgsrc changes: - re-set LICENSE (modified-bsd). upstream changes: Networkx-1.2 Release date: 28 July 2010 See: https://networkx.lanl.gov/trac/timeline New features * Ford-Fulkerson max flow and min cut * Closness vitality * Eulerian circuits * Functions for isolates * Simpler s_max generator * Compatible with IronPython-2.6 * Improved testing functionality: import networkx; networkx.test() tests entire package and skips tests with missing optional packages * All tests work with Python-2.4 * and more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.2 Networkx-1.1 Release date: 21 April 2010 See: https://networkx.lanl.gov/trac/timeline New features * Algorithm for finding a basis for graph cycles * Blockmodeling * Assortativity and mixing matrices * in-degree and out-degree centrality * Attracting components and condensation. * Weakly connected components * Simpler interface to shortest path algorithms * Edgelist format to read and write data with attributes * Attribute matrices * GML reader for nested attributes * Current-flow (random walk) betweenness and closeness. * Directed configuration model, and directed random graph model. * Improved documentation of drawing, shortest paths, and other algorithms * Many more tests, can be run with ?import networkx; networkx.test()? * and much more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.1 API Changes Returning dictionaries Several of the algorithms and the degree() method now return dictionaries keyed by node instead of lists. In some cases there was a with_labels keyword which is no longer necessary. For example, >>> G=nx.Graph() >>> G.add_edge('a','b') >>> G.degree() # returns dictionary of degree keyed by node {'a': 1, 'b': 1} Asking for the degree of a single node still returns a single number >>> G.degree('a') 1 The following now return dictionaries by default (instead of lists) and the with_labels keyword has been removed: * Graph.degree(), MultiGraph.degree(), DiGraph.degree(), DiGraph.in_degree(), DiGraph.out_degree(), MultiDiGraph.degree(), MultiDiGraph.in_degree(), MultiDiGraph.out_degree(). * clustering(), triangles() * node_clique_number(), number_of_cliques(), cliques_containing_node() * eccentricity() The following now return dictionaries by default (instead of lists) * pagerank() * hits() Adding nodes add_nodes_from now accepts (node,attrdict) two-tuples >>> G=nx.Graph() >>> G.add_nodes_from([(1,{'color':'red'})]) Examples * Mayvi2 drawing * Blockmodel * Sampson?s monastery * Ego graph Bug fixes * Support graph attributes with union, intersection, and other graph operations * Improve subgraph speed (and related algorithms such as connected_components_subgraphs()) * Handle multigraphs in more operators (e.g. union) * Handle double-quoted labels with pydot * Normalize betweeness_centrality for undirected graphs correctly * Normalize eigenvector_centrality by l2 norm * read_gml() now returns multigraphs
2010-08-27 05:09:18 +02:00
${PYSITELIB}/networkx/linalg/attrmatrix.py
${PYSITELIB}/networkx/linalg/attrmatrix.pyc
${PYSITELIB}/networkx/linalg/attrmatrix.pyo
Update py-networkx to 1.0.1. Based on PR#42834 by Wen Heping. Update MASTER_SITES, set LICENSE=modified-bsd, 3-caulse BSD. ====================================================================== Networkx-1.0.1 Release date: 11 Jan 2010 See: https://networkx.lanl.gov/trac/timeline Bug fix release for missing setup.py in manifest. ====================================================================== Networkx-1.0 Release date: 8 Jan 2010 See: https://networkx.lanl.gov/trac/timeline New features This release has sigificant changes to parts of the graph API to allow graph, node, and edge attributes. See http://networkx.lanl.gov//reference/api_changes.html * Update Graph, DiGraph, and MultiGraph classes to allow attributes. * Default edge data is now an empty dictionary (was the integer 1) * Difference and intersection operators * Average shortest path * A* (A-Star) algorithm * PageRank, HITS, and eigenvector centrality * Read Pajek files * Line graphs * Minimum spanning tree (Kruskal¡Çs algorithm) * Dense and sparse Fruchterman-Reingold layout * Random clustered graph generator * Directed scale-free graph generator * Faster random regular graph generator * Improved edge color and label drawing with Matplotlib * and much more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.0 Examples * Update to work with networkx-1.0 API * Graph subclass example ====================================================================== Networkx-0.99 Release date: 18 November 2008 See: https://networkx.lanl.gov/trac/timeline New features¢ù This release has sigificant changes to parts of the graph API. See http://networkx.lanl.gov//reference/api_changes.html * Update Graph and DiGraph classes to use weighted graphs as default Change in API for performance and code simplicity. * New MultiGraph and MultiDiGraph classes (replace XGraph and XDiGraph) * Update to use Sphinx documentation system http://networkx.lanl.gov/ * Developer site at https://networkx.lanl.gov/trac/ * Experimental LabeledGraph and LabeledDiGraph * Moved package and file layout to subdirectories. Bug fixes * handle root= option to draw_graphviz correctly Examples * Update to work with networkx-0.99 API * Drawing examples now use matplotlib.pyplot interface * Improved drawings in many examples * New examples - see http://networkx.lanl.gov/examples/
2010-03-03 13:00:59 +01:00
${PYSITELIB}/networkx/linalg/spectrum.py
${PYSITELIB}/networkx/linalg/spectrum.pyc
${PYSITELIB}/networkx/linalg/spectrum.pyo
Update math/py-networkx to 1.2. From PR pkg/43790 by Kamel Derouiche pkgsrc changes: - re-set LICENSE (modified-bsd). upstream changes: Networkx-1.2 Release date: 28 July 2010 See: https://networkx.lanl.gov/trac/timeline New features * Ford-Fulkerson max flow and min cut * Closness vitality * Eulerian circuits * Functions for isolates * Simpler s_max generator * Compatible with IronPython-2.6 * Improved testing functionality: import networkx; networkx.test() tests entire package and skips tests with missing optional packages * All tests work with Python-2.4 * and more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.2 Networkx-1.1 Release date: 21 April 2010 See: https://networkx.lanl.gov/trac/timeline New features * Algorithm for finding a basis for graph cycles * Blockmodeling * Assortativity and mixing matrices * in-degree and out-degree centrality * Attracting components and condensation. * Weakly connected components * Simpler interface to shortest path algorithms * Edgelist format to read and write data with attributes * Attribute matrices * GML reader for nested attributes * Current-flow (random walk) betweenness and closeness. * Directed configuration model, and directed random graph model. * Improved documentation of drawing, shortest paths, and other algorithms * Many more tests, can be run with ?import networkx; networkx.test()? * and much more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.1 API Changes Returning dictionaries Several of the algorithms and the degree() method now return dictionaries keyed by node instead of lists. In some cases there was a with_labels keyword which is no longer necessary. For example, >>> G=nx.Graph() >>> G.add_edge('a','b') >>> G.degree() # returns dictionary of degree keyed by node {'a': 1, 'b': 1} Asking for the degree of a single node still returns a single number >>> G.degree('a') 1 The following now return dictionaries by default (instead of lists) and the with_labels keyword has been removed: * Graph.degree(), MultiGraph.degree(), DiGraph.degree(), DiGraph.in_degree(), DiGraph.out_degree(), MultiDiGraph.degree(), MultiDiGraph.in_degree(), MultiDiGraph.out_degree(). * clustering(), triangles() * node_clique_number(), number_of_cliques(), cliques_containing_node() * eccentricity() The following now return dictionaries by default (instead of lists) * pagerank() * hits() Adding nodes add_nodes_from now accepts (node,attrdict) two-tuples >>> G=nx.Graph() >>> G.add_nodes_from([(1,{'color':'red'})]) Examples * Mayvi2 drawing * Blockmodel * Sampson?s monastery * Ego graph Bug fixes * Support graph attributes with union, intersection, and other graph operations * Improve subgraph speed (and related algorithms such as connected_components_subgraphs()) * Handle multigraphs in more operators (e.g. union) * Handle double-quoted labels with pydot * Normalize betweeness_centrality for undirected graphs correctly * Normalize eigenvector_centrality by l2 norm * read_gml() now returns multigraphs
2010-08-27 05:09:18 +02:00
${PYSITELIB}/networkx/linalg/tests/test_spectrum.py
${PYSITELIB}/networkx/linalg/tests/test_spectrum.pyc
${PYSITELIB}/networkx/linalg/tests/test_spectrum.pyo
Add math/py-networkx package.
2008-08-27 20:53:42 +02:00
${PYSITELIB}/networkx/readwrite/__init__.py
${PYSITELIB}/networkx/readwrite/__init__.pyc
${PYSITELIB}/networkx/readwrite/__init__.pyo
${PYSITELIB}/networkx/readwrite/adjlist.py
${PYSITELIB}/networkx/readwrite/adjlist.pyc
${PYSITELIB}/networkx/readwrite/adjlist.pyo
${PYSITELIB}/networkx/readwrite/edgelist.py
${PYSITELIB}/networkx/readwrite/edgelist.pyc
${PYSITELIB}/networkx/readwrite/edgelist.pyo
${PYSITELIB}/networkx/readwrite/gml.py
${PYSITELIB}/networkx/readwrite/gml.pyc
${PYSITELIB}/networkx/readwrite/gml.pyo
${PYSITELIB}/networkx/readwrite/gpickle.py
${PYSITELIB}/networkx/readwrite/gpickle.pyc
${PYSITELIB}/networkx/readwrite/gpickle.pyo
${PYSITELIB}/networkx/readwrite/graphml.py
${PYSITELIB}/networkx/readwrite/graphml.pyc
${PYSITELIB}/networkx/readwrite/graphml.pyo
${PYSITELIB}/networkx/readwrite/leda.py
${PYSITELIB}/networkx/readwrite/leda.pyc
${PYSITELIB}/networkx/readwrite/leda.pyo
${PYSITELIB}/networkx/readwrite/nx_yaml.py
${PYSITELIB}/networkx/readwrite/nx_yaml.pyc
${PYSITELIB}/networkx/readwrite/nx_yaml.pyo
${PYSITELIB}/networkx/readwrite/p2g.py
${PYSITELIB}/networkx/readwrite/p2g.pyc
${PYSITELIB}/networkx/readwrite/p2g.pyo
${PYSITELIB}/networkx/readwrite/pajek.py
${PYSITELIB}/networkx/readwrite/pajek.pyc
${PYSITELIB}/networkx/readwrite/pajek.pyo
${PYSITELIB}/networkx/readwrite/sparsegraph6.py
${PYSITELIB}/networkx/readwrite/sparsegraph6.pyc
${PYSITELIB}/networkx/readwrite/sparsegraph6.pyo
Update math/py-networkx to 1.2. From PR pkg/43790 by Kamel Derouiche pkgsrc changes: - re-set LICENSE (modified-bsd). upstream changes: Networkx-1.2 Release date: 28 July 2010 See: https://networkx.lanl.gov/trac/timeline New features * Ford-Fulkerson max flow and min cut * Closness vitality * Eulerian circuits * Functions for isolates * Simpler s_max generator * Compatible with IronPython-2.6 * Improved testing functionality: import networkx; networkx.test() tests entire package and skips tests with missing optional packages * All tests work with Python-2.4 * and more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.2 Networkx-1.1 Release date: 21 April 2010 See: https://networkx.lanl.gov/trac/timeline New features * Algorithm for finding a basis for graph cycles * Blockmodeling * Assortativity and mixing matrices * in-degree and out-degree centrality * Attracting components and condensation. * Weakly connected components * Simpler interface to shortest path algorithms * Edgelist format to read and write data with attributes * Attribute matrices * GML reader for nested attributes * Current-flow (random walk) betweenness and closeness. * Directed configuration model, and directed random graph model. * Improved documentation of drawing, shortest paths, and other algorithms * Many more tests, can be run with ?import networkx; networkx.test()? * and much more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.1 API Changes Returning dictionaries Several of the algorithms and the degree() method now return dictionaries keyed by node instead of lists. In some cases there was a with_labels keyword which is no longer necessary. For example, >>> G=nx.Graph() >>> G.add_edge('a','b') >>> G.degree() # returns dictionary of degree keyed by node {'a': 1, 'b': 1} Asking for the degree of a single node still returns a single number >>> G.degree('a') 1 The following now return dictionaries by default (instead of lists) and the with_labels keyword has been removed: * Graph.degree(), MultiGraph.degree(), DiGraph.degree(), DiGraph.in_degree(), DiGraph.out_degree(), MultiDiGraph.degree(), MultiDiGraph.in_degree(), MultiDiGraph.out_degree(). * clustering(), triangles() * node_clique_number(), number_of_cliques(), cliques_containing_node() * eccentricity() The following now return dictionaries by default (instead of lists) * pagerank() * hits() Adding nodes add_nodes_from now accepts (node,attrdict) two-tuples >>> G=nx.Graph() >>> G.add_nodes_from([(1,{'color':'red'})]) Examples * Mayvi2 drawing * Blockmodel * Sampson?s monastery * Ego graph Bug fixes * Support graph attributes with union, intersection, and other graph operations * Improve subgraph speed (and related algorithms such as connected_components_subgraphs()) * Handle multigraphs in more operators (e.g. union) * Handle double-quoted labels with pydot * Normalize betweeness_centrality for undirected graphs correctly * Normalize eigenvector_centrality by l2 norm * read_gml() now returns multigraphs
2010-08-27 05:09:18 +02:00
${PYSITELIB}/networkx/readwrite/tests/test_adjlist.py
${PYSITELIB}/networkx/readwrite/tests/test_adjlist.pyc
${PYSITELIB}/networkx/readwrite/tests/test_adjlist.pyo
${PYSITELIB}/networkx/readwrite/tests/test_edgelist.py
${PYSITELIB}/networkx/readwrite/tests/test_edgelist.pyc
${PYSITELIB}/networkx/readwrite/tests/test_edgelist.pyo
${PYSITELIB}/networkx/readwrite/tests/test_gml.py
${PYSITELIB}/networkx/readwrite/tests/test_gml.pyc
${PYSITELIB}/networkx/readwrite/tests/test_gml.pyo
${PYSITELIB}/networkx/readwrite/tests/test_graphml.py
${PYSITELIB}/networkx/readwrite/tests/test_graphml.pyc
${PYSITELIB}/networkx/readwrite/tests/test_graphml.pyo
${PYSITELIB}/networkx/readwrite/tests/test_yaml.py
${PYSITELIB}/networkx/readwrite/tests/test_yaml.pyc
${PYSITELIB}/networkx/readwrite/tests/test_yaml.pyo
Add math/py-networkx package.
2008-08-27 20:53:42 +02:00
${PYSITELIB}/networkx/release.py
${PYSITELIB}/networkx/release.pyc
${PYSITELIB}/networkx/release.pyo
${PYSITELIB}/networkx/tests/__init__.py
${PYSITELIB}/networkx/tests/__init__.pyc
${PYSITELIB}/networkx/tests/__init__.pyo
${PYSITELIB}/networkx/tests/benchmark.py
${PYSITELIB}/networkx/tests/benchmark.pyc
${PYSITELIB}/networkx/tests/benchmark.pyo
${PYSITELIB}/networkx/tests/test.py
${PYSITELIB}/networkx/tests/test.pyc
${PYSITELIB}/networkx/tests/test.pyo
Update py-networkx to 1.0.1. Based on PR#42834 by Wen Heping. Update MASTER_SITES, set LICENSE=modified-bsd, 3-caulse BSD. ====================================================================== Networkx-1.0.1 Release date: 11 Jan 2010 See: https://networkx.lanl.gov/trac/timeline Bug fix release for missing setup.py in manifest. ====================================================================== Networkx-1.0 Release date: 8 Jan 2010 See: https://networkx.lanl.gov/trac/timeline New features This release has sigificant changes to parts of the graph API to allow graph, node, and edge attributes. See http://networkx.lanl.gov//reference/api_changes.html * Update Graph, DiGraph, and MultiGraph classes to allow attributes. * Default edge data is now an empty dictionary (was the integer 1) * Difference and intersection operators * Average shortest path * A* (A-Star) algorithm * PageRank, HITS, and eigenvector centrality * Read Pajek files * Line graphs * Minimum spanning tree (Kruskal¡Çs algorithm) * Dense and sparse Fruchterman-Reingold layout * Random clustered graph generator * Directed scale-free graph generator * Faster random regular graph generator * Improved edge color and label drawing with Matplotlib * and much more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.0 Examples * Update to work with networkx-1.0 API * Graph subclass example ====================================================================== Networkx-0.99 Release date: 18 November 2008 See: https://networkx.lanl.gov/trac/timeline New features¢ù This release has sigificant changes to parts of the graph API. See http://networkx.lanl.gov//reference/api_changes.html * Update Graph and DiGraph classes to use weighted graphs as default Change in API for performance and code simplicity. * New MultiGraph and MultiDiGraph classes (replace XGraph and XDiGraph) * Update to use Sphinx documentation system http://networkx.lanl.gov/ * Developer site at https://networkx.lanl.gov/trac/ * Experimental LabeledGraph and LabeledDiGraph * Moved package and file layout to subdirectories. Bug fixes * handle root= option to draw_graphviz correctly Examples * Update to work with networkx-0.99 API * Drawing examples now use matplotlib.pyplot interface * Improved drawings in many examples * New examples - see http://networkx.lanl.gov/examples/
2010-03-03 13:00:59 +01:00
${PYSITELIB}/networkx/tests/test_convert_numpy.py
${PYSITELIB}/networkx/tests/test_convert_numpy.pyc
${PYSITELIB}/networkx/tests/test_convert_numpy.pyo
${PYSITELIB}/networkx/tests/test_convert_scipy.py
${PYSITELIB}/networkx/tests/test_convert_scipy.pyc
${PYSITELIB}/networkx/tests/test_convert_scipy.pyo
Add math/py-networkx package.
2008-08-27 20:53:42 +02:00
${PYSITELIB}/networkx/utils.py
${PYSITELIB}/networkx/utils.pyc
${PYSITELIB}/networkx/utils.pyo
Update py-networkx to 1.0.1. Based on PR#42834 by Wen Heping. Update MASTER_SITES, set LICENSE=modified-bsd, 3-caulse BSD. ====================================================================== Networkx-1.0.1 Release date: 11 Jan 2010 See: https://networkx.lanl.gov/trac/timeline Bug fix release for missing setup.py in manifest. ====================================================================== Networkx-1.0 Release date: 8 Jan 2010 See: https://networkx.lanl.gov/trac/timeline New features This release has sigificant changes to parts of the graph API to allow graph, node, and edge attributes. See http://networkx.lanl.gov//reference/api_changes.html * Update Graph, DiGraph, and MultiGraph classes to allow attributes. * Default edge data is now an empty dictionary (was the integer 1) * Difference and intersection operators * Average shortest path * A* (A-Star) algorithm * PageRank, HITS, and eigenvector centrality * Read Pajek files * Line graphs * Minimum spanning tree (Kruskal¡Çs algorithm) * Dense and sparse Fruchterman-Reingold layout * Random clustered graph generator * Directed scale-free graph generator * Faster random regular graph generator * Improved edge color and label drawing with Matplotlib * and much more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.0 Examples * Update to work with networkx-1.0 API * Graph subclass example ====================================================================== Networkx-0.99 Release date: 18 November 2008 See: https://networkx.lanl.gov/trac/timeline New features¢ù This release has sigificant changes to parts of the graph API. See http://networkx.lanl.gov//reference/api_changes.html * Update Graph and DiGraph classes to use weighted graphs as default Change in API for performance and code simplicity. * New MultiGraph and MultiDiGraph classes (replace XGraph and XDiGraph) * Update to use Sphinx documentation system http://networkx.lanl.gov/ * Developer site at https://networkx.lanl.gov/trac/ * Experimental LabeledGraph and LabeledDiGraph * Moved package and file layout to subdirectories. Bug fixes * handle root= option to draw_graphviz correctly Examples * Update to work with networkx-0.99 API * Drawing examples now use matplotlib.pyplot interface * Improved drawings in many examples * New examples - see http://networkx.lanl.gov/examples/
2010-03-03 13:00:59 +01:00
${PYSITELIB}/networkx/version.py
${PYSITELIB}/networkx/version.pyc
${PYSITELIB}/networkx/version.pyo
share/doc/networkx-${PKGVERSION}/INSTALL.txt
share/doc/networkx-${PKGVERSION}/LICENSE.txt
share/doc/networkx-${PKGVERSION}/README.txt
share/doc/networkx-${PKGVERSION}/examples/advanced/eigenvalues.py
share/doc/networkx-${PKGVERSION}/examples/advanced/heavy_metal_umlaut.py
share/doc/networkx-${PKGVERSION}/examples/advanced/iterated_dynamical_systems.py
Update math/py-networkx to 1.2. From PR pkg/43790 by Kamel Derouiche pkgsrc changes: - re-set LICENSE (modified-bsd). upstream changes: Networkx-1.2 Release date: 28 July 2010 See: https://networkx.lanl.gov/trac/timeline New features * Ford-Fulkerson max flow and min cut * Closness vitality * Eulerian circuits * Functions for isolates * Simpler s_max generator * Compatible with IronPython-2.6 * Improved testing functionality: import networkx; networkx.test() tests entire package and skips tests with missing optional packages * All tests work with Python-2.4 * and more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.2 Networkx-1.1 Release date: 21 April 2010 See: https://networkx.lanl.gov/trac/timeline New features * Algorithm for finding a basis for graph cycles * Blockmodeling * Assortativity and mixing matrices * in-degree and out-degree centrality * Attracting components and condensation. * Weakly connected components * Simpler interface to shortest path algorithms * Edgelist format to read and write data with attributes * Attribute matrices * GML reader for nested attributes * Current-flow (random walk) betweenness and closeness. * Directed configuration model, and directed random graph model. * Improved documentation of drawing, shortest paths, and other algorithms * Many more tests, can be run with ?import networkx; networkx.test()? * and much more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.1 API Changes Returning dictionaries Several of the algorithms and the degree() method now return dictionaries keyed by node instead of lists. In some cases there was a with_labels keyword which is no longer necessary. For example, >>> G=nx.Graph() >>> G.add_edge('a','b') >>> G.degree() # returns dictionary of degree keyed by node {'a': 1, 'b': 1} Asking for the degree of a single node still returns a single number >>> G.degree('a') 1 The following now return dictionaries by default (instead of lists) and the with_labels keyword has been removed: * Graph.degree(), MultiGraph.degree(), DiGraph.degree(), DiGraph.in_degree(), DiGraph.out_degree(), MultiDiGraph.degree(), MultiDiGraph.in_degree(), MultiDiGraph.out_degree(). * clustering(), triangles() * node_clique_number(), number_of_cliques(), cliques_containing_node() * eccentricity() The following now return dictionaries by default (instead of lists) * pagerank() * hits() Adding nodes add_nodes_from now accepts (node,attrdict) two-tuples >>> G=nx.Graph() >>> G.add_nodes_from([(1,{'color':'red'})]) Examples * Mayvi2 drawing * Blockmodel * Sampson?s monastery * Ego graph Bug fixes * Support graph attributes with union, intersection, and other graph operations * Improve subgraph speed (and related algorithms such as connected_components_subgraphs()) * Handle multigraphs in more operators (e.g. union) * Handle double-quoted labels with pydot * Normalize betweeness_centrality for undirected graphs correctly * Normalize eigenvector_centrality by l2 norm * read_gml() now returns multigraphs
2010-08-27 05:09:18 +02:00
share/doc/networkx-${PKGVERSION}/examples/algorithms/blockmodel.py
Update py-networkx to 1.0.1. Based on PR#42834 by Wen Heping. Update MASTER_SITES, set LICENSE=modified-bsd, 3-caulse BSD. ====================================================================== Networkx-1.0.1 Release date: 11 Jan 2010 See: https://networkx.lanl.gov/trac/timeline Bug fix release for missing setup.py in manifest. ====================================================================== Networkx-1.0 Release date: 8 Jan 2010 See: https://networkx.lanl.gov/trac/timeline New features This release has sigificant changes to parts of the graph API to allow graph, node, and edge attributes. See http://networkx.lanl.gov//reference/api_changes.html * Update Graph, DiGraph, and MultiGraph classes to allow attributes. * Default edge data is now an empty dictionary (was the integer 1) * Difference and intersection operators * Average shortest path * A* (A-Star) algorithm * PageRank, HITS, and eigenvector centrality * Read Pajek files * Line graphs * Minimum spanning tree (Kruskal¡Çs algorithm) * Dense and sparse Fruchterman-Reingold layout * Random clustered graph generator * Directed scale-free graph generator * Faster random regular graph generator * Improved edge color and label drawing with Matplotlib * and much more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.0 Examples * Update to work with networkx-1.0 API * Graph subclass example ====================================================================== Networkx-0.99 Release date: 18 November 2008 See: https://networkx.lanl.gov/trac/timeline New features¢ù This release has sigificant changes to parts of the graph API. See http://networkx.lanl.gov//reference/api_changes.html * Update Graph and DiGraph classes to use weighted graphs as default Change in API for performance and code simplicity. * New MultiGraph and MultiDiGraph classes (replace XGraph and XDiGraph) * Update to use Sphinx documentation system http://networkx.lanl.gov/ * Developer site at https://networkx.lanl.gov/trac/ * Experimental LabeledGraph and LabeledDiGraph * Moved package and file layout to subdirectories. Bug fixes * handle root= option to draw_graphviz correctly Examples * Update to work with networkx-0.99 API * Drawing examples now use matplotlib.pyplot interface * Improved drawings in many examples * New examples - see http://networkx.lanl.gov/examples/
2010-03-03 13:00:59 +01:00
share/doc/networkx-${PKGVERSION}/examples/algorithms/davis_club.py
Update math/py-networkx to 1.2. From PR pkg/43790 by Kamel Derouiche pkgsrc changes: - re-set LICENSE (modified-bsd). upstream changes: Networkx-1.2 Release date: 28 July 2010 See: https://networkx.lanl.gov/trac/timeline New features * Ford-Fulkerson max flow and min cut * Closness vitality * Eulerian circuits * Functions for isolates * Simpler s_max generator * Compatible with IronPython-2.6 * Improved testing functionality: import networkx; networkx.test() tests entire package and skips tests with missing optional packages * All tests work with Python-2.4 * and more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.2 Networkx-1.1 Release date: 21 April 2010 See: https://networkx.lanl.gov/trac/timeline New features * Algorithm for finding a basis for graph cycles * Blockmodeling * Assortativity and mixing matrices * in-degree and out-degree centrality * Attracting components and condensation. * Weakly connected components * Simpler interface to shortest path algorithms * Edgelist format to read and write data with attributes * Attribute matrices * GML reader for nested attributes * Current-flow (random walk) betweenness and closeness. * Directed configuration model, and directed random graph model. * Improved documentation of drawing, shortest paths, and other algorithms * Many more tests, can be run with ?import networkx; networkx.test()? * and much more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.1 API Changes Returning dictionaries Several of the algorithms and the degree() method now return dictionaries keyed by node instead of lists. In some cases there was a with_labels keyword which is no longer necessary. For example, >>> G=nx.Graph() >>> G.add_edge('a','b') >>> G.degree() # returns dictionary of degree keyed by node {'a': 1, 'b': 1} Asking for the degree of a single node still returns a single number >>> G.degree('a') 1 The following now return dictionaries by default (instead of lists) and the with_labels keyword has been removed: * Graph.degree(), MultiGraph.degree(), DiGraph.degree(), DiGraph.in_degree(), DiGraph.out_degree(), MultiDiGraph.degree(), MultiDiGraph.in_degree(), MultiDiGraph.out_degree(). * clustering(), triangles() * node_clique_number(), number_of_cliques(), cliques_containing_node() * eccentricity() The following now return dictionaries by default (instead of lists) * pagerank() * hits() Adding nodes add_nodes_from now accepts (node,attrdict) two-tuples >>> G=nx.Graph() >>> G.add_nodes_from([(1,{'color':'red'})]) Examples * Mayvi2 drawing * Blockmodel * Sampson?s monastery * Ego graph Bug fixes * Support graph attributes with union, intersection, and other graph operations * Improve subgraph speed (and related algorithms such as connected_components_subgraphs()) * Handle multigraphs in more operators (e.g. union) * Handle double-quoted labels with pydot * Normalize betweeness_centrality for undirected graphs correctly * Normalize eigenvector_centrality by l2 norm * read_gml() now returns multigraphs
2010-08-27 05:09:18 +02:00
share/doc/networkx-${PKGVERSION}/examples/algorithms/hartford_drug.edgelist
Update py-networkx to 1.0.1. Based on PR#42834 by Wen Heping. Update MASTER_SITES, set LICENSE=modified-bsd, 3-caulse BSD. ====================================================================== Networkx-1.0.1 Release date: 11 Jan 2010 See: https://networkx.lanl.gov/trac/timeline Bug fix release for missing setup.py in manifest. ====================================================================== Networkx-1.0 Release date: 8 Jan 2010 See: https://networkx.lanl.gov/trac/timeline New features This release has sigificant changes to parts of the graph API to allow graph, node, and edge attributes. See http://networkx.lanl.gov//reference/api_changes.html * Update Graph, DiGraph, and MultiGraph classes to allow attributes. * Default edge data is now an empty dictionary (was the integer 1) * Difference and intersection operators * Average shortest path * A* (A-Star) algorithm * PageRank, HITS, and eigenvector centrality * Read Pajek files * Line graphs * Minimum spanning tree (Kruskal¡Çs algorithm) * Dense and sparse Fruchterman-Reingold layout * Random clustered graph generator * Directed scale-free graph generator * Faster random regular graph generator * Improved edge color and label drawing with Matplotlib * and much more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.0 Examples * Update to work with networkx-1.0 API * Graph subclass example ====================================================================== Networkx-0.99 Release date: 18 November 2008 See: https://networkx.lanl.gov/trac/timeline New features¢ù This release has sigificant changes to parts of the graph API. See http://networkx.lanl.gov//reference/api_changes.html * Update Graph and DiGraph classes to use weighted graphs as default Change in API for performance and code simplicity. * New MultiGraph and MultiDiGraph classes (replace XGraph and XDiGraph) * Update to use Sphinx documentation system http://networkx.lanl.gov/ * Developer site at https://networkx.lanl.gov/trac/ * Experimental LabeledGraph and LabeledDiGraph * Moved package and file layout to subdirectories. Bug fixes * handle root= option to draw_graphviz correctly Examples * Update to work with networkx-0.99 API * Drawing examples now use matplotlib.pyplot interface * Improved drawings in many examples * New examples - see http://networkx.lanl.gov/examples/
2010-03-03 13:00:59 +01:00
share/doc/networkx-${PKGVERSION}/examples/algorithms/krackhardt_centrality.py
share/doc/networkx-${PKGVERSION}/examples/basic/properties.py
share/doc/networkx-${PKGVERSION}/examples/basic/read_write.py
share/doc/networkx-${PKGVERSION}/examples/drawing/atlas.py
share/doc/networkx-${PKGVERSION}/examples/drawing/chess_masters.py
share/doc/networkx-${PKGVERSION}/examples/drawing/chess_masters_WCC.pgn.bz2
share/doc/networkx-${PKGVERSION}/examples/drawing/circular_tree.py
share/doc/networkx-${PKGVERSION}/examples/drawing/degree_histogram.py
share/doc/networkx-${PKGVERSION}/examples/drawing/edge_colormap.py
Update math/py-networkx to 1.2. From PR pkg/43790 by Kamel Derouiche pkgsrc changes: - re-set LICENSE (modified-bsd). upstream changes: Networkx-1.2 Release date: 28 July 2010 See: https://networkx.lanl.gov/trac/timeline New features * Ford-Fulkerson max flow and min cut * Closness vitality * Eulerian circuits * Functions for isolates * Simpler s_max generator * Compatible with IronPython-2.6 * Improved testing functionality: import networkx; networkx.test() tests entire package and skips tests with missing optional packages * All tests work with Python-2.4 * and more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.2 Networkx-1.1 Release date: 21 April 2010 See: https://networkx.lanl.gov/trac/timeline New features * Algorithm for finding a basis for graph cycles * Blockmodeling * Assortativity and mixing matrices * in-degree and out-degree centrality * Attracting components and condensation. * Weakly connected components * Simpler interface to shortest path algorithms * Edgelist format to read and write data with attributes * Attribute matrices * GML reader for nested attributes * Current-flow (random walk) betweenness and closeness. * Directed configuration model, and directed random graph model. * Improved documentation of drawing, shortest paths, and other algorithms * Many more tests, can be run with ?import networkx; networkx.test()? * and much more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.1 API Changes Returning dictionaries Several of the algorithms and the degree() method now return dictionaries keyed by node instead of lists. In some cases there was a with_labels keyword which is no longer necessary. For example, >>> G=nx.Graph() >>> G.add_edge('a','b') >>> G.degree() # returns dictionary of degree keyed by node {'a': 1, 'b': 1} Asking for the degree of a single node still returns a single number >>> G.degree('a') 1 The following now return dictionaries by default (instead of lists) and the with_labels keyword has been removed: * Graph.degree(), MultiGraph.degree(), DiGraph.degree(), DiGraph.in_degree(), DiGraph.out_degree(), MultiDiGraph.degree(), MultiDiGraph.in_degree(), MultiDiGraph.out_degree(). * clustering(), triangles() * node_clique_number(), number_of_cliques(), cliques_containing_node() * eccentricity() The following now return dictionaries by default (instead of lists) * pagerank() * hits() Adding nodes add_nodes_from now accepts (node,attrdict) two-tuples >>> G=nx.Graph() >>> G.add_nodes_from([(1,{'color':'red'})]) Examples * Mayvi2 drawing * Blockmodel * Sampson?s monastery * Ego graph Bug fixes * Support graph attributes with union, intersection, and other graph operations * Improve subgraph speed (and related algorithms such as connected_components_subgraphs()) * Handle multigraphs in more operators (e.g. union) * Handle double-quoted labels with pydot * Normalize betweeness_centrality for undirected graphs correctly * Normalize eigenvector_centrality by l2 norm * read_gml() now returns multigraphs
2010-08-27 05:09:18 +02:00
share/doc/networkx-${PKGVERSION}/examples/drawing/ego_graph.py
Update py-networkx to 1.0.1. Based on PR#42834 by Wen Heping. Update MASTER_SITES, set LICENSE=modified-bsd, 3-caulse BSD. ====================================================================== Networkx-1.0.1 Release date: 11 Jan 2010 See: https://networkx.lanl.gov/trac/timeline Bug fix release for missing setup.py in manifest. ====================================================================== Networkx-1.0 Release date: 8 Jan 2010 See: https://networkx.lanl.gov/trac/timeline New features This release has sigificant changes to parts of the graph API to allow graph, node, and edge attributes. See http://networkx.lanl.gov//reference/api_changes.html * Update Graph, DiGraph, and MultiGraph classes to allow attributes. * Default edge data is now an empty dictionary (was the integer 1) * Difference and intersection operators * Average shortest path * A* (A-Star) algorithm * PageRank, HITS, and eigenvector centrality * Read Pajek files * Line graphs * Minimum spanning tree (Kruskal¡Çs algorithm) * Dense and sparse Fruchterman-Reingold layout * Random clustered graph generator * Directed scale-free graph generator * Faster random regular graph generator * Improved edge color and label drawing with Matplotlib * and much more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.0 Examples * Update to work with networkx-1.0 API * Graph subclass example ====================================================================== Networkx-0.99 Release date: 18 November 2008 See: https://networkx.lanl.gov/trac/timeline New features¢ù This release has sigificant changes to parts of the graph API. See http://networkx.lanl.gov//reference/api_changes.html * Update Graph and DiGraph classes to use weighted graphs as default Change in API for performance and code simplicity. * New MultiGraph and MultiDiGraph classes (replace XGraph and XDiGraph) * Update to use Sphinx documentation system http://networkx.lanl.gov/ * Developer site at https://networkx.lanl.gov/trac/ * Experimental LabeledGraph and LabeledDiGraph * Moved package and file layout to subdirectories. Bug fixes * handle root= option to draw_graphviz correctly Examples * Update to work with networkx-0.99 API * Drawing examples now use matplotlib.pyplot interface * Improved drawings in many examples * New examples - see http://networkx.lanl.gov/examples/
2010-03-03 13:00:59 +01:00
share/doc/networkx-${PKGVERSION}/examples/drawing/four_grids.py
share/doc/networkx-${PKGVERSION}/examples/drawing/giant_component.py
share/doc/networkx-${PKGVERSION}/examples/drawing/house_with_colors.py
share/doc/networkx-${PKGVERSION}/examples/drawing/knuth_miles.py
share/doc/networkx-${PKGVERSION}/examples/drawing/knuth_miles.txt.gz
share/doc/networkx-${PKGVERSION}/examples/drawing/labels_and_colors.py
share/doc/networkx-${PKGVERSION}/examples/drawing/lanl_routes.edgelist
share/doc/networkx-${PKGVERSION}/examples/drawing/lanl_routes.py
Update math/py-networkx to 1.2. From PR pkg/43790 by Kamel Derouiche pkgsrc changes: - re-set LICENSE (modified-bsd). upstream changes: Networkx-1.2 Release date: 28 July 2010 See: https://networkx.lanl.gov/trac/timeline New features * Ford-Fulkerson max flow and min cut * Closness vitality * Eulerian circuits * Functions for isolates * Simpler s_max generator * Compatible with IronPython-2.6 * Improved testing functionality: import networkx; networkx.test() tests entire package and skips tests with missing optional packages * All tests work with Python-2.4 * and more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.2 Networkx-1.1 Release date: 21 April 2010 See: https://networkx.lanl.gov/trac/timeline New features * Algorithm for finding a basis for graph cycles * Blockmodeling * Assortativity and mixing matrices * in-degree and out-degree centrality * Attracting components and condensation. * Weakly connected components * Simpler interface to shortest path algorithms * Edgelist format to read and write data with attributes * Attribute matrices * GML reader for nested attributes * Current-flow (random walk) betweenness and closeness. * Directed configuration model, and directed random graph model. * Improved documentation of drawing, shortest paths, and other algorithms * Many more tests, can be run with ?import networkx; networkx.test()? * and much more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.1 API Changes Returning dictionaries Several of the algorithms and the degree() method now return dictionaries keyed by node instead of lists. In some cases there was a with_labels keyword which is no longer necessary. For example, >>> G=nx.Graph() >>> G.add_edge('a','b') >>> G.degree() # returns dictionary of degree keyed by node {'a': 1, 'b': 1} Asking for the degree of a single node still returns a single number >>> G.degree('a') 1 The following now return dictionaries by default (instead of lists) and the with_labels keyword has been removed: * Graph.degree(), MultiGraph.degree(), DiGraph.degree(), DiGraph.in_degree(), DiGraph.out_degree(), MultiDiGraph.degree(), MultiDiGraph.in_degree(), MultiDiGraph.out_degree(). * clustering(), triangles() * node_clique_number(), number_of_cliques(), cliques_containing_node() * eccentricity() The following now return dictionaries by default (instead of lists) * pagerank() * hits() Adding nodes add_nodes_from now accepts (node,attrdict) two-tuples >>> G=nx.Graph() >>> G.add_nodes_from([(1,{'color':'red'})]) Examples * Mayvi2 drawing * Blockmodel * Sampson?s monastery * Ego graph Bug fixes * Support graph attributes with union, intersection, and other graph operations * Improve subgraph speed (and related algorithms such as connected_components_subgraphs()) * Handle multigraphs in more operators (e.g. union) * Handle double-quoted labels with pydot * Normalize betweeness_centrality for undirected graphs correctly * Normalize eigenvector_centrality by l2 norm * read_gml() now returns multigraphs
2010-08-27 05:09:18 +02:00
share/doc/networkx-${PKGVERSION}/examples/drawing/mayavi2_spring.py
Update py-networkx to 1.0.1. Based on PR#42834 by Wen Heping. Update MASTER_SITES, set LICENSE=modified-bsd, 3-caulse BSD. ====================================================================== Networkx-1.0.1 Release date: 11 Jan 2010 See: https://networkx.lanl.gov/trac/timeline Bug fix release for missing setup.py in manifest. ====================================================================== Networkx-1.0 Release date: 8 Jan 2010 See: https://networkx.lanl.gov/trac/timeline New features This release has sigificant changes to parts of the graph API to allow graph, node, and edge attributes. See http://networkx.lanl.gov//reference/api_changes.html * Update Graph, DiGraph, and MultiGraph classes to allow attributes. * Default edge data is now an empty dictionary (was the integer 1) * Difference and intersection operators * Average shortest path * A* (A-Star) algorithm * PageRank, HITS, and eigenvector centrality * Read Pajek files * Line graphs * Minimum spanning tree (Kruskal¡Çs algorithm) * Dense and sparse Fruchterman-Reingold layout * Random clustered graph generator * Directed scale-free graph generator * Faster random regular graph generator * Improved edge color and label drawing with Matplotlib * and much more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.0 Examples * Update to work with networkx-1.0 API * Graph subclass example ====================================================================== Networkx-0.99 Release date: 18 November 2008 See: https://networkx.lanl.gov/trac/timeline New features¢ù This release has sigificant changes to parts of the graph API. See http://networkx.lanl.gov//reference/api_changes.html * Update Graph and DiGraph classes to use weighted graphs as default Change in API for performance and code simplicity. * New MultiGraph and MultiDiGraph classes (replace XGraph and XDiGraph) * Update to use Sphinx documentation system http://networkx.lanl.gov/ * Developer site at https://networkx.lanl.gov/trac/ * Experimental LabeledGraph and LabeledDiGraph * Moved package and file layout to subdirectories. Bug fixes * handle root= option to draw_graphviz correctly Examples * Update to work with networkx-0.99 API * Drawing examples now use matplotlib.pyplot interface * Improved drawings in many examples * New examples - see http://networkx.lanl.gov/examples/
2010-03-03 13:00:59 +01:00
share/doc/networkx-${PKGVERSION}/examples/drawing/node_colormap.py
share/doc/networkx-${PKGVERSION}/examples/drawing/random_geometric_graph.py
Update math/py-networkx to 1.2. From PR pkg/43790 by Kamel Derouiche pkgsrc changes: - re-set LICENSE (modified-bsd). upstream changes: Networkx-1.2 Release date: 28 July 2010 See: https://networkx.lanl.gov/trac/timeline New features * Ford-Fulkerson max flow and min cut * Closness vitality * Eulerian circuits * Functions for isolates * Simpler s_max generator * Compatible with IronPython-2.6 * Improved testing functionality: import networkx; networkx.test() tests entire package and skips tests with missing optional packages * All tests work with Python-2.4 * and more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.2 Networkx-1.1 Release date: 21 April 2010 See: https://networkx.lanl.gov/trac/timeline New features * Algorithm for finding a basis for graph cycles * Blockmodeling * Assortativity and mixing matrices * in-degree and out-degree centrality * Attracting components and condensation. * Weakly connected components * Simpler interface to shortest path algorithms * Edgelist format to read and write data with attributes * Attribute matrices * GML reader for nested attributes * Current-flow (random walk) betweenness and closeness. * Directed configuration model, and directed random graph model. * Improved documentation of drawing, shortest paths, and other algorithms * Many more tests, can be run with ?import networkx; networkx.test()? * and much more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.1 API Changes Returning dictionaries Several of the algorithms and the degree() method now return dictionaries keyed by node instead of lists. In some cases there was a with_labels keyword which is no longer necessary. For example, >>> G=nx.Graph() >>> G.add_edge('a','b') >>> G.degree() # returns dictionary of degree keyed by node {'a': 1, 'b': 1} Asking for the degree of a single node still returns a single number >>> G.degree('a') 1 The following now return dictionaries by default (instead of lists) and the with_labels keyword has been removed: * Graph.degree(), MultiGraph.degree(), DiGraph.degree(), DiGraph.in_degree(), DiGraph.out_degree(), MultiDiGraph.degree(), MultiDiGraph.in_degree(), MultiDiGraph.out_degree(). * clustering(), triangles() * node_clique_number(), number_of_cliques(), cliques_containing_node() * eccentricity() The following now return dictionaries by default (instead of lists) * pagerank() * hits() Adding nodes add_nodes_from now accepts (node,attrdict) two-tuples >>> G=nx.Graph() >>> G.add_nodes_from([(1,{'color':'red'})]) Examples * Mayvi2 drawing * Blockmodel * Sampson?s monastery * Ego graph Bug fixes * Support graph attributes with union, intersection, and other graph operations * Improve subgraph speed (and related algorithms such as connected_components_subgraphs()) * Handle multigraphs in more operators (e.g. union) * Handle double-quoted labels with pydot * Normalize betweeness_centrality for undirected graphs correctly * Normalize eigenvector_centrality by l2 norm * read_gml() now returns multigraphs
2010-08-27 05:09:18 +02:00
share/doc/networkx-${PKGVERSION}/examples/drawing/sampson.py
Update py-networkx to 1.0.1. Based on PR#42834 by Wen Heping. Update MASTER_SITES, set LICENSE=modified-bsd, 3-caulse BSD. ====================================================================== Networkx-1.0.1 Release date: 11 Jan 2010 See: https://networkx.lanl.gov/trac/timeline Bug fix release for missing setup.py in manifest. ====================================================================== Networkx-1.0 Release date: 8 Jan 2010 See: https://networkx.lanl.gov/trac/timeline New features This release has sigificant changes to parts of the graph API to allow graph, node, and edge attributes. See http://networkx.lanl.gov//reference/api_changes.html * Update Graph, DiGraph, and MultiGraph classes to allow attributes. * Default edge data is now an empty dictionary (was the integer 1) * Difference and intersection operators * Average shortest path * A* (A-Star) algorithm * PageRank, HITS, and eigenvector centrality * Read Pajek files * Line graphs * Minimum spanning tree (Kruskal¡Çs algorithm) * Dense and sparse Fruchterman-Reingold layout * Random clustered graph generator * Directed scale-free graph generator * Faster random regular graph generator * Improved edge color and label drawing with Matplotlib * and much more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.0 Examples * Update to work with networkx-1.0 API * Graph subclass example ====================================================================== Networkx-0.99 Release date: 18 November 2008 See: https://networkx.lanl.gov/trac/timeline New features¢ù This release has sigificant changes to parts of the graph API. See http://networkx.lanl.gov//reference/api_changes.html * Update Graph and DiGraph classes to use weighted graphs as default Change in API for performance and code simplicity. * New MultiGraph and MultiDiGraph classes (replace XGraph and XDiGraph) * Update to use Sphinx documentation system http://networkx.lanl.gov/ * Developer site at https://networkx.lanl.gov/trac/ * Experimental LabeledGraph and LabeledDiGraph * Moved package and file layout to subdirectories. Bug fixes * handle root= option to draw_graphviz correctly Examples * Update to work with networkx-0.99 API * Drawing examples now use matplotlib.pyplot interface * Improved drawings in many examples * New examples - see http://networkx.lanl.gov/examples/
2010-03-03 13:00:59 +01:00
share/doc/networkx-${PKGVERSION}/examples/drawing/simple_path.py
share/doc/networkx-${PKGVERSION}/examples/drawing/unix_email.mbox
share/doc/networkx-${PKGVERSION}/examples/drawing/unix_email.py
share/doc/networkx-${PKGVERSION}/examples/drawing/weighted_graph.py
share/doc/networkx-${PKGVERSION}/examples/graph/atlas.py
share/doc/networkx-${PKGVERSION}/examples/graph/atlas2.py
share/doc/networkx-${PKGVERSION}/examples/graph/degree_sequence.py
share/doc/networkx-${PKGVERSION}/examples/graph/erdos_renyi.py
share/doc/networkx-${PKGVERSION}/examples/graph/expected_degree_sequence.py
share/doc/networkx-${PKGVERSION}/examples/graph/football.py
share/doc/networkx-${PKGVERSION}/examples/graph/karate_club.py
share/doc/networkx-${PKGVERSION}/examples/graph/knuth_miles.py
share/doc/networkx-${PKGVERSION}/examples/graph/knuth_miles.txt.gz
share/doc/networkx-${PKGVERSION}/examples/graph/napoleon_russian_campaign.py
share/doc/networkx-${PKGVERSION}/examples/graph/roget.py
share/doc/networkx-${PKGVERSION}/examples/graph/roget_dat.txt.gz
share/doc/networkx-${PKGVERSION}/examples/graph/unix_email.mbox
share/doc/networkx-${PKGVERSION}/examples/graph/unix_email.py
share/doc/networkx-${PKGVERSION}/examples/graph/words.py
share/doc/networkx-${PKGVERSION}/examples/graph/words_dat.txt.gz
share/doc/networkx-${PKGVERSION}/examples/multigraph/chess_masters.py
share/doc/networkx-${PKGVERSION}/examples/multigraph/chess_masters_WCC.pgn.bz2
share/doc/networkx-${PKGVERSION}/examples/pygraphviz/pygraphviz_attributes.py
share/doc/networkx-${PKGVERSION}/examples/pygraphviz/pygraphviz_draw.py
share/doc/networkx-${PKGVERSION}/examples/pygraphviz/pygraphviz_simple.py
share/doc/networkx-${PKGVERSION}/examples/pygraphviz/write_dotfile.py
@pkgdir share/doc/networkx-${PKGVERSION}/examples/readwrite
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