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**To**:**pkg-manager%netbsd.org@localhost,gnats-admin%netbsd.org@localhost,pkgsrc-bugs%netbsd.org@localhost,kamelderouiche%yahoo.com@localhost****Subject**:**PR/43790 CVS commit: pkgsrc/math/py-networkx****From**:**Guillaume Lasmayous <gls%netbsd.org@localhost>**- Date: Fri, 27 Aug 2010 03:10:12 +0000 (UTC)

The following reply was made to PR pkg/43790; it has been noted by GNATS. From: Guillaume Lasmayous <gls%netbsd.org@localhost> To: gnats-bugs%gnats.NetBSD.org@localhost Cc: Subject: PR/43790 CVS commit: pkgsrc/math/py-networkx Date: Fri, 27 Aug 2010 03:09:18 +0000 Module Name: pkgsrc Committed By: gls Date: Fri Aug 27 03:09:18 UTC 2010 Modified Files: pkgsrc/math/py-networkx: Makefile PLIST distinfo Log Message: 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 To generate a diff of this commit: cvs rdiff -u -r1.4 -r1.5 pkgsrc/math/py-networkx/Makefile cvs rdiff -u -r1.5 -r1.6 pkgsrc/math/py-networkx/PLIST cvs rdiff -u -r1.2 -r1.3 pkgsrc/math/py-networkx/distinfo Please note that diffs are not public domain; they are subject to the copyright notices on the relevant files.

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