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Revision **1.15** / (**download**) - annotate - [select for diffs], *Sat Apr 11 07:45:41 2020 UTC* (7 months, 2 weeks ago) by *adam*

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py-networkx: updated to 2.4 2.4: This release is the result of 6 months of work with over 200 commits by 67 contributors. Highlights include: - Remove deprecated code from 1.x - Support for Python 3.8 - Switched to pytest for testing - Last release to support Python 3.5 New Functions: - barycenter functions - Bethe Hessian matrix function - Eulerian Path methods - group centrality measures - subgraph monomorphisms - k-truss algorithms - onion decomposition - resistance distance - asteroidal triples - non-randomness measures - linear prufing - minimum weight bipartite matching - Incremental closeness centrality - ISMAGS subgraph isomorphism algorithm - create chordal graph of a graph New generators - Binomial tree generator - Directed joint degree generator - Random internet AS graph generator New for Layouts - spiral node layout routine - support for 3d layouts Improvements ------------ - allow average shortest path to use Floyd-Warshall method - improve read/write of GML, GEXF, GraphML - allow string or json object as input to jit_graph - attempt to allow numpy.array input in place of lists in more places - faster strongly connected components - faster Floyd-Warshall Optimization - faster global efficiency - faster transitive closure - fix unionfind; betweenness_subset; lexico-topo-sort; A*; inverse_line_graph; async label propagation; edgelist reading; Gomory-Hu flow method; label_propagation; partial_duplication; shell_layout with 1 node in shell; from_pandas_edgelist - Documentation improvement and fixes API Changes ----------- A utility function is_list_of_ints became is_bunch_of_ints and now tests int(item)==item instead of isinstance(_, int) This allows e.g. floats whose values are integer. Added utility make_list_of_ints to convert containers of integer values to lists of integers Deprecations ------------ Removed functions (marked as deprecated in NetworkX 2.1): - attracting_component_subgraphs - connected_component_subgraphs - weakly_connected_component_subgraphs - strongly_connected_component_subgraphs - biconnected_component_subgraphs - See docs for component functions for how to get subgraphs. Graph Object methods removed (marked as deprecated 2.1) - G.add_path - G.add_cycle - G.add_star - G.nodes_with_selfloops - G.number_of_selfloops - G.selfloop_edges - These are now NetworkX functions, e.g. nx.add_star(G, 5) - G.node --> use G.nodes - G.fresh_copy --> use G.__class__ Remove old names for graphview functions. - ReverseView - SubGraph - SubMultiGraph - SubMultiDiGraph - SubDiGraph - GraphView - DiGraphView - MultiGraphView - MultiDiGraphView - MultiReverseView - Use reverse_view, subgraph_view and generic_graph_view.

Revision **1.14** / (**download**) - annotate - [select for diffs], *Wed Sep 25 07:24:12 2019 UTC* (14 months ago) by *adam*

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py-networkx: fix building; Python 2.7 is not supported

Revision **1.13** / (**download**) - annotate - [select for diffs], *Mon Jun 17 14:58:26 2019 UTC* (17 months, 1 week ago) by *adam*

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py-networkx: updated to 2.3 Announcement: NetworkX 2.3 ========================== We're happy to announce the release of NetworkX 2.3! NetworkX is a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. For more information, please visit our website <http://networkx.github.io/>_ and our gallery of examples <https://networkx.github.io/documentation/latest/auto_examples/index.html>_. Please send comments and questions to the networkx-discuss mailing list <http://groups.google.com/group/networkx-discuss>_. Highlights ---------- This release is the result of 6 months of work with over 92 pull requests by 30 contributors. Highlights include: - Dropped support for Python 2. We are no longer supporting Python 2.7 and we will start changing code to take advantage of Python 3 features we couldn't before. - Added some Moral Graph analysis functions. - Enable matplotlib drawing using curved arrows via connectionstyle parameter. - Remove ticks and axes labels from matplotlib plots. - Two new generators of Harary Graphs. - Added Dual Barabasi-Albert model - Added VoteRank algorithm - Added Equitable coloring algorithms - Added planar layout algorithms - Les Miserables network example - Javascript example update Improvements ------------ - Change default colors to be color-blind friendly - Many bug fixes and documentation improvements - Speed up of simple_cycles - Improvements for reading various formats like GML, GEXF, Graphml - Allow subclassing to access node_attr_dict_factory API Changes ----------- - The G.fresh_copy() mechanism for creating an empty_graph of the same type (introduced in v2.0) does not playing nicely with pickle and others. So, we have removed the code that caused a need for that. Instead you should use the more natural G.__class__() syntax to get an empty_graph of the same type as G. Deprecations ------------ - The Graph.fresh_copy() method should now use Graph.__class__() - ReverseView class removed in favor of reverse_view() function.

Revision **1.12** / (**download**) - annotate - [select for diffs], *Fri Nov 30 10:37:07 2018 UTC* (23 months, 3 weeks ago) by *adam*

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py-networkx: updated to 2.2 2.2: This release is the result of 8 months of work with over 149 commits by 58 contributors. Highlights include: - Add support for Python 3.7. This is the last release to support Python 2. - Uniform random number generator (RNG) handling which defaults to global RNGs but allows specification of a single RNG for all random numbers in NX. - Improved GraphViews to ease subclassing and remove cyclic references which caused trouble with deepcopy and pickle. - New Graph method `G.update(H)`

Revision **1.11** / (**download**) - annotate - [select for diffs], *Thu Feb 1 21:00:25 2018 UTC* (2 years, 9 months ago) by *adam*

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py-networkx: updated to 2.1 NetworkX 2.1 Highlights This release is the result of four months of work with 75 pull requests by 37 contributors. Highlights include: - Arrows for drawing DiGraph edges are vastly improved! And an example to show them. - More than 12 new functions for graph generation, manipulation and/or new graph algorithms. - Add a large clique size heuristic function - Add rooted product function - Label Propagation Community Detection - Minimum cycle basis - Add Mycielski Operator - Adds prefix_tree, dag_to_branching, and example. - Add inverse_line_graph generator - Steiner tree and metric closure. - Add flow based node and edge disjoint paths. - Update geometric networks with new models - Graph edit distance - Added function for finding a k-edge-augmentation - G.name is no longer processed by graph operators. It remains as a property mechanism to access ``G.graph['name']`` but the user is in charge of updating or changing it for copies, subgraphs, unions and other graph operations. Improvements - Many bug fixes, documentation changes. - Speed improvements especially for subgraphs. - Changed input variable names for functions using ``**kwds`` to avoid name collisions -- especially ``add_node`` - New examples for arrows and spectral embedding of the grid graph.

Revision **1.10** / (**download**) - annotate - [select for diffs], *Wed Sep 27 13:25:54 2017 UTC* (3 years, 1 month ago) by *adam*

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py-networkx: update to 2.0 NetworkX 2.0 Support for Python 3.6 added, drop support for Python 3.3.

Revision **1.9** / (**download**) - annotate - [select for diffs], *Fri Aug 12 13:38:22 2016 UTC* (4 years, 3 months ago) by *wen*

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Update to 1.11 Update DEPENDS Based on PR/51271 from kamelderouiche@yahoo.com Upstream changes: 1.11 API changes [#1930] No longer import nx_agraph and nx_pydot into the top-level namespace. They can be accessed within networkx as e.g. nx.nx_agraph.write_dot or imported as from networkx.drawing.nx_agraph import write_dot. [#1750] Arguments center and scale are now available for all layout functions. The defaul values revert to the v1.9 values (center is the origin for circular layouts and domain is [0, scale) for others. [#1924] Replace pydot with pydotplus for drawing with the pydot interface. [#1888] Replace support for Python3.2 with support for Python 3.5. Miscellaneous changes [#1763] Set up appveyor to automatically test installation on Windows machines. Remove symbolic links in examples to help such istallation. Change many doc_string typos to allow sphinx to build the docs without errors or warnings. Enable the docs to be automatically built on readthedocs.org by changing requirements.txt

Revision **1.8** / (**download**) - annotate - [select for diffs], *Sun Nov 1 09:58:28 2015 UTC* (5 years ago) by *wiz*

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Changes since **1.7: +5 -4
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Update py-networkx to 1.10, based on PR 50383 by Derouiche. API changes [#1501] connected_components, weakly_connected_components, and strongly_connected_components return now a generator of sets of nodes. Previously the generator was of lists of nodes. This PR also refactored the connected_components and weakly_connected_components implementations making them faster, especially for large graphs. [#1547] The func_iter functions in Di/Multi/Graphs classes are slated for removal in NetworkX 2.0 release. func will behave like func_iter and return an iterator instead of list. These functions are deprecated in NetworkX 1.10 release. New functionalities [#823] A enumerate_all_cliques function is added in the clique package (networkx.algorithms.clique) for enumerating all cliques (including nonmaximal ones) of undirected graphs. [#1105] A coloring package (networkx.algorithms.coloring) is created for graph coloring algorithms. Initially, a greedy_color function is provided for coloring graphs using various greedy heuristics. [#1193] A new generator edge_dfs, added to networkx.algorithms.traversal, implements a depth-first traversal of the edges in a graph. This complements functionality provided by a depth-first traversal of the nodes in a graph. For multigraphs, it allows the user to know precisely which edges were followed in a traversal. All NetworkX graph types are supported. A traversal can also reverse edge orientations or ignore them. [#1194] A find_cycle function is added to the networkx.algorithms.cycles package to find a cycle in a graph. Edge orientations can be optionally reversed or ignored. [#1210] Add a random generator for the duplication-divergence model. [#1241] A new networkx.algorithms.dominance package is added for dominance/dominator algorithms on directed graphs. It contains a immediate_dominators function for computing immediate dominators/dominator trees and a dominance_frontiers function for computing dominance frontiers. [#1269] The GML reader/parser and writer/generator are rewritten to remove the dependence on pyparsing and enable handling of arbitrary graph data. [#1280] The network simplex method in the networkx.algorithms.flow package is rewritten to improve its performance and support multi- and disconnected networks. For some cases, the new implementation is two or three orders of magnitude faster than the old implementation. [#1286] Added the MargulisãàÅ¨abberãàÅ¨alil graph to networkx.generators. [#1306] Added the chordal p-cycle graph, a mildly explicit algebraic construction of a family of 3-regular expander graphs. Also, moves both the existing expander graph generator function (for the Margulis-Gabber-Galil expander) and the new chordal cycle graph function to a new module, networkx.generators.expanders. [#1314] Allow overwriting of base class dict with dict-like: OrderedGraph, ThinGraph, LogGraph, etc. [#1321] Added to_pandas_dataframe and from_pandas_dataframe. [#1322] Added the HopcroftãàÅ¬arp algorithm for finding a maximum cardinality matching in bipartite graphs. [#1336] Expanded data keyword in G.edges and added default keyword. [#1338] Added support for finding optimum branchings and arborescences. [#1340] Added a from_pandas_dataframe function that accepts Pandas DataFrames and returns a new graph object. At a minimum, the DataFrame must have two columns, which define the nodes that make up an edge. However, the function can also process an arbitrary number of additional columns as edge attributes, such as ãàÏØeightãà [#1354] Expanded layout functions to add flexibility for drawing subsets of nodes with distinct layouts and for centering each layout around given coordinates. [#1356] Added ordered variants of default graph class. [#1360] Added harmonic centrality to network.algorithms.centrality. [#1390] The generators.bipartite have been moved to algorithms.bipartite.generators. The functions are not imported in the main namespace, so to use it, the bipartite package has to be imported. [#1391] Added KanevskyãàÑÔ algorithm for finding all minimum-size separating node sets in an undirected graph. It is implemented as a generator of node cut sets. [#1399] Added power function for simple graphs [#1405] Added fast approximation for node connectivity based on White and NewmanãàÑÔ approximation algorithm for finding node independent paths between two nodes. [#1413] Added transitive closure and antichains function for directed acyclic graphs in algorithms.dag. The antichains function was contributed by Peter Jipsen and Franco Saliola and originally developed for the SAGE project. [#1425] Added generator function for the complete multipartite graph. [#1427] Added nonisomorphic trees generator. [#1436] Added a generator function for circulant graphs to the networkx.generators.classic module. [#1437] Added function for computing quotient graphs; also created a new module, networkx.algorithms.minors. [#1438] Added longest_path and longest_path_length for DAG. [#1439] Added node and edge contraction functions to networkx.algorithms.minors. [#1445] Added a new modularity matrix module to networkx.linalg, and associated spectrum functions to the networkx.linalg.spectrum module. [#1447] Added function to generate all simple paths starting with the shortest ones based on YenãàÑÔ algorithm for finding k shortest paths at algorithms.simple_paths. [#1455] Added the directed modularity matrix to the networkx.linalg.modularity_matrix module. [#1474] Adds triadic_census function; also creates a new module, networkx.algorithms.triads. [#1476] Adds functions for testing if a graph has weighted or negatively weighted edges. Also adds a function for testing if a graph is empty. These are is_weighted, is_negatively_weighted, and is_empty. [#1481] Added JohnsonãàÑÔ algorithm; one more algorithm for shortest paths. It solves all pairs shortest path problem. This is johnson at algorithms.shortest_paths [#1414] Added Moody and White algorithm for identifying k_components in a graph, which is based on KanevskyãàÑÔ algorithm for finding all minimum-size node cut-sets (implemented in all_node_cuts #1391). [#1415] Added fast approximation for k_components to the networkx.approximation package. This is based on White and Newman approximation algorithm for finding node independent paths between two nodes (see #1405). Removed functionalities [#1236] The legacy ford_fulkerson maximum flow function is removed. Use edmonds_karp instead. Miscellaneous changes [#1192] Support for Python 2.6 is dropped.

Revision **1.7** / (**download**) - annotate - [select for diffs], *Mon Jul 28 12:16:23 2014 UTC* (6 years, 3 months ago) by *wen*

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Update to 1.9 Add missing DEPENDS Upstream changes: NetworkX 1.9 Release date: 21 June 2014 Support for Python 3.1 is dropped in this release. Highlights Completely rewritten maximum flow and flow-based connectivity algorithms with backwards incompatible interfaces Community graph generators Stoer-Wagner minimum cut algorithm Linear-time Eulerian circuit algorithm Linear algebra package changed to use SciPy sparse matrices Algebraic connectivity, Fiedler vector, spectral ordering algorithms Link prediction algorithms Goldberg-Radzik shortest path algorithm Semiconnected graph and tree recognition algorithms

Revision **1.6** / (**download**) - annotate - [select for diffs], *Tue Jun 10 12:04:58 2014 UTC* (6 years, 5 months ago) by *wen*

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Update to 1.8.1 Upstream changes: Networkx-1.8.1 Release date: 4 August 2013 Bugfix release for missing files in source packaging Networkx-1.8 Release date: 28 July 2013 Highlights Faster (linear-time) graphicality tests and Havel-Hakimi graph generators Directed Laplacian matrix generator Katz centrality algorithm Functions to generate all simple paths Improved shapefile reader More flexible weighted projection of bipartite graphs Faster topological sort, decendents and ancestors of DAGs Scaling parameter for force-directed layout Bug Fixes Error with average weighted connectivity for digraphs, correct normalized laplacian with self-loops, load betweenness for single node graphs, isolated nodes missing from dfs/bfs trees, normalize HITS using l1, handle density of graphs with self loops Cleaner handling of current figure status with Matplotlib, Pajek files now don't write troublesome header line, default alpha value for GEXF files, read curved edges from yEd GraphML

Revision **1.5** / (**download**) - annotate - [select for diffs], *Fri Jul 13 14:00:32 2012 UTC* (8 years, 4 months ago) by *wen*

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Update to 1.7 Release Log Networkx-1.7 Release date: 4 July 2012 Highlights New functions for k-clique community finding, flow hierarchy, union, disjoint union, compose, and intersection operators that work on lists of graphs, and creating the biadjacency matrix of a bipartite graph. New approximation algorithms for dominating set, edge dominating set, independent set, max clique, and min-weighted vertex cover. Many bug fixes and other improvements. For full details of the tickets closed for this release (added features and bug fixes) see: https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.7 API Changes See Version 1.7 notes and API changes

Revision **1.4** / (**download**) - annotate - [select for diffs], *Sat Jun 2 13:19:17 2012 UTC* (8 years, 5 months ago) by *obache*

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Update py-networkx to 1.6. Based on PR 46506 by Wen Heping. * let to register egg-info. * marked as incompatible with python 2.5, as new features in 1.3. but not marked as compatible with 3.x, one file will not be compiled well both 3.1 and 3.2. Lease Log: Networkx-1.6 Release date: 20 November 2011 Highlights New functions for finding articulation points, generating random bipartite graphs, constructing adjacency matrix representations, forming graph products, computing assortativity coefficients, measuring subgraph centrality and communicability, finding k-clique communities, and writing JSON format output. New examples for drawing with D3 Javascript library, and ordering matrices with the Cuthill-McKee algorithm. More memory efficient implementation of current-flow betweenness and new approximation algorithms for current-flow betweenness and shortest-path betweenness. Simplified handling of "weight" attributes for algorithms that use weights/costs/values. See Version 1.6 notes and API changes. Updated all code to work with the PyPy Python implementation http://pypy.org which produces faster performance on many algorithms. For full details of the tickets closed for this release (added features and bug fixes) see: https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.6 API Changes See Version 1.6 notes and API changes: http://networkx.lanl.gov/reference/api_1.6.html Networkx-1.5 Release date: 4 June 2011 For full details of the tickets closed for this release see: https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.5 Highlights New features * Algorithms for generating and analyzing bipartite graphs * Maximal independent set algorithm * Erd?s-Gallai graphical degree sequence test * Negative edge cycle test * More memory efficient Dijkstra path length with cutoff parameter * Weighted clustering coefficient * Read and write version 1.2 of GEXF reader format * Neighbor degree correlation that handle subsets of nodes * In-place node relabeling * Many `weighted' graph algorithms now take optional parameter to use specified edge attribute (default=`weight') (ticket 509) * Test for distance regular graphs * Fast directed Erd?s-Renyi graph generator * Fast expected degree graph generator * Navigable small world generator * Waxman model generator * Geographical threshold graph generator * Karate Club, Florentine Families, and Davis' Women's Club graphs API Changes See Version 1.5 notes and API changes http://networkx.lanl.gov/reference/api_1.5.html Bug fixes * Fix edge handling for multigraphs in networkx/graphviz interface (ticket 507) * Update networkx/pydot interface for new versions of pydot (ticket 506), (ticket 535) * Fix negative cycle handling in Bellman-Ford (ticket 502) * Write more attributes with GraphML and GML formats (ticket 480) * Handle white space better in read_edgelist (ticket 513) * Better parsing of Pajek format files (ticket 524) (ticket 542) * Isolates functions work with directed graphs (ticket 526) * Faster conversion to numpy matrices (ticket 529) * Add graph[`name'] and use properties to access Graph.name (ticket 544) * Topological sort confused None and 0 (ticket 546) * GEXF writer mishandled weight=0 (ticket 550) * Speedup in SciPy version of PageRank (ticket 554) * Numpy PageRank node order incorrect + speedups (ticket 555) Networkx-1.4 Release date: 23 January 2011 New features * k-shell,k-crust,k-corona * read GraphML files from yEd * read/write GEXF format files * find cycles in a directed graph * DFS and BFS algorithms * chordal graph functions * Prim's algorithm for minimum spanning tree * r-ary tree generator * rich club coefficient * NumPy matrix version of Floyd's algorithm for all-pairs shortest path * read GIS shapefiles * functions to get and set node and edge attributes * and more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.4 API Changes * gnp_random_graph() now takes a directed=True|False keyword instead of create_using * gnm_random_graph() now takes a directed=True|False keyword instead of create_using Bug fixes * see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.4 Networkx-1.3 Release date: 28 August 2010 See: https://networkx.lanl.gov/trac/timeline New features * Works with Python versions 2.6, 2.7, 3.1, and 3.2 (but not 2.4 and 2.5). * Minimum cost flow algorithms * Bellman-Ford shortest paths * GraphML reader and writer * More exception/error types * Updated many tests to unittest style. Run with: "import networkx; networkx.test()" (requires nose testing package) * and more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.3 API Changes * minimum_spanning_tree() now returns a NetworkX Graph (a tree or forest) Bug fixes * see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.3

Revision **1.3** / (**download**) - annotate - [select for diffs], *Fri Aug 27 03:09:18 2010 UTC* (10 years, 3 months ago) by *gls*

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pkgsrc-2010Q4,
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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

Revision **1.2** / (**download**) - annotate - [select for diffs], *Wed Mar 3 12:00:59 2010 UTC* (10 years, 8 months ago) by *obache*

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Diff to previous 1.1 (colored)

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 (KruskalÂ¡s 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 featuresÂ¢Ã¹ 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/

Revision **1.1** / (**download**) - annotate - [select for diffs], *Wed Aug 27 18:53:42 2008 UTC* (12 years, 3 months ago) by *apb*

Branch: **MAIN
**

CVS Tags: **pkgsrc-2009Q4-base,
pkgsrc-2009Q4,
pkgsrc-2009Q3-base,
pkgsrc-2009Q3,
pkgsrc-2009Q2-base,
pkgsrc-2009Q2,
pkgsrc-2009Q1-base,
pkgsrc-2009Q1,
pkgsrc-2008Q4-base,
pkgsrc-2008Q4,
pkgsrc-2008Q3-base,
pkgsrc-2008Q3,
cube-native-xorg-base,
cube-native-xorg
**

Add math/py-networkx package.

CVSweb <webmaster@jp.NetBSD.org>