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Accepting request 330047 from devel:languages:python

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- update to 1.10:
  * 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.
  * 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.
  * A enumerate_all_cliques function is added in the clique package
    (networkx.algorithms.clique) for enumerating all cliques
    (including nonmaximal ones) of undirected graphs.
  * 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.
  * 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.
  * 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.
  * Add a random generator for the duplication-divergence model.
  * 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 (forwarded request 330044 from tbechtold)

OBS-URL: https://build.opensuse.org/request/show/330047
OBS-URL: https://build.opensuse.org/package/show/openSUSE:Factory/python-networkx?expand=0&rev=8
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Dominique Leuenberger 2015-09-11 07:03:58 +00:00 committed by Git OBS Bridge
parent 36bf48451a
commit ba1c08de49
4 changed files with 112 additions and 4 deletions
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networkx-1.10.tar.gz Normal file
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python-networkx.changes
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-------------------------------------------------------------------
Wed Sep 9 12:32:21 UTC 2015 - tbechtold@suse.com
- update to 1.10:
* 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.
* 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.
* A enumerate_all_cliques function is added in the clique package
(networkx.algorithms.clique) for enumerating all cliques
(including nonmaximal ones) of undirected graphs.
* 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.
* 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.
* 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.
* Add a random generator for the duplication-divergence model.
* 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.
* The GML reader/parser and writer/generator are rewritten to remove
the dependence on pyparsing and enable handling of arbitrary graph data.
* 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.
* Added the Margulis--Gabber--Galil graph to networkx.generators.
* 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.
* Allow overwriting of base class dict with dict-like: OrderedGraph, ThinGraph,
LogGraph, etc.
* Added to_pandas_dataframe and from_pandas_dataframe.
* Added the Hopcroft--Karp algorithm for finding a maximum cardinality
matching in bipartite graphs.
* Expanded data keyword in G.edges and added default keyword.
* Added support for finding optimum branchings and arborescences.
* 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 'weight'.
* Expanded layout functions to add flexibility for drawing subsets of nodes
with distinct layouts and for centering each layout around given coordinates.
* Added ordered variants of default graph class.
* Added harmonic centrality to network.algorithms.centrality.
* 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.
* Added Kanevsky's algorithm for finding all minimum-size separating node
sets in an undirected graph. It is implemented as a generator of node
cut sets.
* Added power function for simple graphs
* Added fast approximation for node connectivity based on White and Newman's
approximation algorithm for finding node independent paths between two nodes.
* 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.
* Added generator function for the complete multipartite graph.
* Added nonisomorphic trees generator.
* Added a generator function for circulant graphs to the
networkx.generators.classic module.
* Added function for computing quotient graphs; also created a new module,
networkx.algorithms.minors.
* Added longest_path and longest_path_length for DAG.
* Added node and edge contraction functions to networkx.algorithms.minors.
* Added a new modularity matrix module to networkx.linalg, and associated
spectrum functions to the networkx.linalg.spectrum module.
* Added function to generate all simple paths starting with the shortest ones
based on Yen's algorithm for finding k shortest paths at
algorithms.simple_paths.
* Added the directed modularity matrix to the
networkx.linalg.modularity_matrix module.
* Adds triadic_census function; also creates a new module,
networkx.algorithms.triads.
* 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.
* Added Johnson's algorithm; one more algorithm for shortest paths. It solves
all pairs shortest path problem. This is johnson at
algorithms.shortest_paths
* Added Moody and White algorithm for identifying k_components in a graph,
which is based on Kanevsky's algorithm for finding all minimum-size node
cut-sets (implemented in all_node_cuts #1391).
* 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).
* The legacy ford_fulkerson maximum flow function is removed.
Use edmonds_karp instead.
* Support for Python 2.6 is dropped.
-------------------------------------------------------------------
Sat Jul 25 12:36:58 UTC 2015 - seife+obs@b1-systems.com

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python-networkx.spec
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Name: python-networkx
Version: 1.9.1
Version: 1.10
Release: 0
Summary: Python package for the creation, manipulation,
License: BSD-3-Clause