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pkgsrc/math/py-networkx/PLIST
obache 8039ec81d4 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
2012-06-02 13:19:17 +00:00

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@comment $NetBSD: PLIST,v 1.7 2012/06/02 13:19:17 obache Exp $
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${PYSITELIB}/networkx/readwrite/json_graph/serialize.py
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${PYSITELIB}/networkx/readwrite/json_graph/serialize.pyo
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${PYSITELIB}/networkx/readwrite/json_graph/tests/test_adjacency.pyo
${PYSITELIB}/networkx/readwrite/json_graph/tests/test_node_link.py
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${PYSITELIB}/networkx/readwrite/json_graph/tests/test_serialize.py
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${PYSITELIB}/networkx/readwrite/json_graph/tests/test_serialize.pyo
${PYSITELIB}/networkx/readwrite/json_graph/tests/test_tree.py
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${PYSITELIB}/networkx/readwrite/json_graph/tests/test_tree.pyo
${PYSITELIB}/networkx/readwrite/json_graph/tree.py
${PYSITELIB}/networkx/readwrite/json_graph/tree.pyc
${PYSITELIB}/networkx/readwrite/json_graph/tree.pyo
${PYSITELIB}/networkx/readwrite/leda.py
${PYSITELIB}/networkx/readwrite/leda.pyc
${PYSITELIB}/networkx/readwrite/leda.pyo
${PYSITELIB}/networkx/readwrite/multiline_adjlist.py
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${PYSITELIB}/networkx/readwrite/nx_shp.py
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${PYSITELIB}/networkx/readwrite/nx_shp.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
${PYSITELIB}/networkx/readwrite/pajek.pyc
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${PYSITELIB}/networkx/readwrite/sparsegraph6.py
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${PYSITELIB}/networkx/readwrite/sparsegraph6.pyo
${PYSITELIB}/networkx/readwrite/tests/test_adjlist.py
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${PYSITELIB}/networkx/readwrite/tests/test_gml.py
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${PYSITELIB}/networkx/readwrite/tests/test_gml.pyo
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${PYSITELIB}/networkx/readwrite/tests/test_graphml.py
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${PYSITELIB}/networkx/readwrite/tests/test_p2g.py
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${PYSITELIB}/networkx/readwrite/tests/test_sparsegraph6.py
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${PYSITELIB}/networkx/readwrite/tests/test_yaml.pyo
${PYSITELIB}/networkx/relabel.py
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${PYSITELIB}/networkx/release.py
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${PYSITELIB}/networkx/tests/__init__.py
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${PYSITELIB}/networkx/tests/test_convert.py
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${PYSITELIB}/networkx/tests/test_convert_scipy.py
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${PYSITELIB}/networkx/tests/test_exceptions.py
${PYSITELIB}/networkx/tests/test_exceptions.pyc
${PYSITELIB}/networkx/tests/test_exceptions.pyo
${PYSITELIB}/networkx/tests/test_relabel.py
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${PYSITELIB}/networkx/utils/__init__.py
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${PYSITELIB}/networkx/utils/__init__.pyo
${PYSITELIB}/networkx/utils/decorators.py
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${PYSITELIB}/networkx/utils/misc.py
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${PYSITELIB}/networkx/utils/misc.pyo
${PYSITELIB}/networkx/utils/random_sequence.py
${PYSITELIB}/networkx/utils/random_sequence.pyc
${PYSITELIB}/networkx/utils/random_sequence.pyo
${PYSITELIB}/networkx/utils/rcm.py
${PYSITELIB}/networkx/utils/rcm.pyc
${PYSITELIB}/networkx/utils/rcm.pyo
${PYSITELIB}/networkx/utils/tests/test_decorators.py
${PYSITELIB}/networkx/utils/tests/test_decorators.pyc
${PYSITELIB}/networkx/utils/tests/test_decorators.pyo
${PYSITELIB}/networkx/utils/tests/test_misc.py
${PYSITELIB}/networkx/utils/tests/test_misc.pyc
${PYSITELIB}/networkx/utils/tests/test_misc.pyo
${PYSITELIB}/networkx/utils/tests/test_random_sequence.py
${PYSITELIB}/networkx/utils/tests/test_random_sequence.pyc
${PYSITELIB}/networkx/utils/tests/test_random_sequence.pyo
${PYSITELIB}/networkx/utils/tests/test_rcm.py
${PYSITELIB}/networkx/utils/tests/test_rcm.pyc
${PYSITELIB}/networkx/utils/tests/test_rcm.pyo
${PYSITELIB}/networkx/utils/union_find.py
${PYSITELIB}/networkx/utils/union_find.pyc
${PYSITELIB}/networkx/utils/union_find.pyo
${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-${PKGVERSION}/examples/3d_drawing/mayavi2_spring.py
share/doc/networkx-${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
share/doc/networkx-${PKGVERSION}/examples/algorithms/blockmodel.py
share/doc/networkx-${PKGVERSION}/examples/algorithms/davis_club.py
share/doc/networkx-${PKGVERSION}/examples/algorithms/hartford_drug.edgelist
share/doc/networkx-${PKGVERSION}/examples/algorithms/krackhardt_centrality.py
share/doc/networkx-${PKGVERSION}/examples/algorithms/rcm.py
share/doc/networkx-${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-${PKGVERSION}/examples/drawing/edge_colormap.py
share/doc/networkx-${PKGVERSION}/examples/drawing/ego_graph.py
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
share/doc/networkx-${PKGVERSION}/examples/drawing/node_colormap.py
share/doc/networkx-${PKGVERSION}/examples/drawing/random_geometric_graph.py
share/doc/networkx-${PKGVERSION}/examples/drawing/sampson.py
share/doc/networkx-${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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