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| Name: python-networkx-doc | Distribution: SUSE Linux Enterprise 15 |
| Version: 2.0 | Vendor: SUSE LLC <https://www.suse.com/> |
| Release: 3.2.8 | Build date: Wed May 29 16:32:06 2019 |
| Group: Documentation/Other | Build host: sheep18 |
| Size: 278545 | Source RPM: python-networkx-2.0-3.2.8.src.rpm |
| Packager: https://www.suse.com/ | |
| Url: http://networkx.lanl.gov | |
| Summary: Documentation for python-networkx | |
Documentation and examples for python-networkx.
BSD-3-Clause
* Tue Oct 31 2017 arun@gmx.de
- specfile:
* changes from tar.gz to zip
* updated sed
* INSTALL doesn't seem to be packaged anymore, deleted "rm" command
- update to version 2.0:
* Highlights
+ This release is the result of over two years of work with 1212
commits and 193 merges by 86 contributors. Highlights include:
+ We have made major changes to the methods in the Multi/Di/Graph
classes. There is a migration guide for people moving from 1.X
to 2.0.
+ We updated the documentation system.
* full release notes at
https://networkx.github.io/documentation/stable/release/release_2.0.html
* Sun Aug 06 2017 toddrme2178@gmail.com
- Fix shebangs
* Thu May 11 2017 toddrme2178@gmail.com
- Implement single-spec version.
- Fix source URL.
* Wed Aug 17 2016 tbechtold@suse.com
update to version networkx-1.11
* Update release and news info for v1.10.1
* Use utils.testing to handle testing edge and node equality
* Update news to include 1.10 release highlights
* Remove spurious line due to typo.
* Fix algebraicconnectivity float conversion
* Fix python3 numpy wont read in {}.values to array.
* update requirements.txt on v1.11 branch
* update doc/requirements.txt to point Sphinx-origin_stable
* Update license, readme, and release.py for networkx-1.11
* adjust tutorial to mention import write_dot
* Revert some API changes in layout.py due to bugs.
* Update news and api for v1.11
* Update authors, copyrights and EOL space
* Add release date in news
* Add tests, convert center to np.array, fix domain_size
* Put graphviz install outside check for python2.7
* Activate Appveyor-CI
* Add layout tests and minor docs
* networkx-1.11rc2 label
* Remove all the symbolic links from the 'examples/' directory
* v1.11 Add utils functions to flow variable __all__
* Fix Sphinx for v1.11
* Prepare release number and news.rst for v1.11
* simplify pydot imports, use testing.utils routines
* Get the month right.
* update release docs files for v1.11
* Use pydotplus for all supported python versions
* Add note about pyggraphviz and pydotplus import changes
* Modified release.py
* change copyright year in doc build
* For v1.11 drop support for python3.2 and add 3.5
* Update news.rst for v1.11
* Examples and doc changes
* Re-add scaling inside fruchterman_reingold
* Update conf.py to point to make_examples_rst.py
* Reinstate v1.10 layout except center. Fix bugs
* Adjust imports in drawing layouts with graphviz
* Doc tweak on edges for v1.11
* Sun Mar 13 2016 dmueller@suse.com
- add license/readme
* Wed Sep 09 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 2015 seife+obs@b1-systems.com
- fix rhel build by conditionalizing "Recommends:" tags
- do not hardcode /usr/share/doc/packages but use %_docdir
* Wed Apr 29 2015 tbechtold@suse.com
- Don't BuildRequires python-pygraphviz. It's not needed.
* Thu Oct 30 2014 tbechtold@suse.com
- update to version 1.9.1:
* Bugfix release for minor installation and documentation issues
- Don't BuildRequire/Recommend matplotlib and scipy on SLE11
and SLE12. Both are not available there.
* Fri Oct 24 2014 toddrme2178@gmail.com
- Add python-decorator in requires to buildrequires
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