Hello community, here is the log from the commit of package python-networkx for openSUSE:Factory checked in at 2015-09-11 09:03:58 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ Comparing /work/SRC/openSUSE:Factory/python-networkx (Old) and /work/SRC/openSUSE:Factory/.python-networkx.new (New) ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Package is "python-networkx" Changes: -------- --- /work/SRC/openSUSE:Factory/python-networkx/python-networkx.changes 2015-08-01 11:36:58.000000000 +0200 +++ /work/SRC/openSUSE:Factory/.python-networkx.new/python-networkx.changes 2015-09-11 09:04:19.000000000 +0200 @@ -1,0 +2,108 @@ +Wed Sep 9 12:32:21 UTC 2015 - [email protected] + +- 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. + +------------------------------------------------------------------- Old: ---- networkx-1.9.1.tar.gz New: ---- networkx-1.10.tar.gz ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ Other differences: ------------------ ++++++ python-networkx.spec ++++++ --- /var/tmp/diff_new_pack.iJCuGi/_old 2015-09-11 09:04:20.000000000 +0200 +++ /var/tmp/diff_new_pack.iJCuGi/_new 2015-09-11 09:04:20.000000000 +0200 @@ -17,7 +17,7 @@ Name: python-networkx -Version: 1.9.1 +Version: 1.10 Release: 0 Summary: Python package for the creation, manipulation, License: BSD-3-Clause ++++++ networkx-1.9.1.tar.gz -> networkx-1.10.tar.gz ++++++ ++++ 39876 lines of diff (skipped)
