Release date: 23 January 2011
- k-shell,k-crust,k-coronoa
- 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
- 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
Release date: 28 August 2010
See: https://networkx.lanl.gov/trac/timeline
- 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
Release date: 28 July 2010
See: https://networkx.lanl.gov/trac/timeline
- 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
Release date: 21 April 2010
See: https://networkx.lanl.gov/trac/timeline
- 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
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()
add_nodes_from now accepts (node,attrdict) two-tuples
>>> G=nx.Graph()
>>> G.add_nodes_from([(1,{'color':'red'})])
- 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
Release date: 11 Jan 2010
See: https://networkx.lanl.gov/trac/timeline
Bug fix release for missing setup.py in manifest.
Release date: 8 Jan 2010
See: https://networkx.lanl.gov/trac/timeline
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 (Kruskal’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
- Update to work with networkx-1.0 API
- Graph subclass example
Release date: 18 November 2008
See: https://networkx.lanl.gov/trac/timeline
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.
- handle root= option to draw_graphviz correctly
- 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/
Release date: 17 August 2008
See: https://networkx.lanl.gov/trac/timeline
NetworkX now requires Python 2.4 or later for full functionality.
- Edge coloring and node line widths with Matplotlib drawings
- Update pydot functions to work with pydot-1.0.2
- Maximum-weight matching algorithm
- Ubigraph interface for 3D OpenGL layout and drawing
- Pajek graph file format reader and writer
- p2g graph file format reader and writer
- Secondary sort in topological sort
- Better edge data handling with GML writer
- Edge betweenness fix for XGraph with default data of None
- Handle Matplotlib version strings (allow “pre”)
- Interface to PyGraphviz (to_agraph()) now handles parallel edges
- Fix bug in copy from XGraph to XGraph with multiedges
- Use SciPy sparse lil matrix format instead of coo format
- Clear up ambiguous cases for Barabasi-Albert model
- Better care of color maps with Matplotlib when drawing colored nodes and edges
- Fix error handling in layout.py
- Ubigraph examples showing 3D drawing
Release date: 13 January 2008
See: https://networkx.lanl.gov/trac/timeline
- GML format graph reader, tests, and example (football.py)
- edge_betweenness() and load_betweenness()
- remove obsolete parts of pygraphviz interface
- improve handling of Matplotlib version strings
- write_dot() now writes parallel edges and self loops
- is_bipartite() and bipartite_color() fixes
- configuration model speedup using random.shuffle()
- convert with specified nodelist now works correctly
- vf2 isomorphism checker updates
Release date: 27 July 2007
See: https://networkx.lanl.gov/trac/timeline
Small update to fix import readwrite problem and maintain Python2.3 compatibility.
Release date: 22 July 2007
See: https://networkx.lanl.gov/trac/timeline
- algorithms for strongly connected components.
- Brandes betweenness centrality algorithm (weighted and unweighted versions)
- closeness centrality for weighted graphs
- dfs_preorder, dfs_postorder, dfs_tree, dfs_successor, dfs_predecessor
- readers for GraphML, LEDA, sparse6, and graph6 formats.
- allow arguments in graphviz_layout to be passed directly to graphviz
- more detailed installation instructions
- replaced dfs_preorder,dfs_postorder (see search.py)
- allow initial node positions in spectral_layout
- report no error on attempting to draw empty graph
- report errors correctly when using tuples as nodes #114
- handle conversions from incomplete dict-of-dict data
Release date: 12 April 2007
See: https://networkx.lanl.gov/trac/timeline
- benchmarks for graph classes
- Brandes betweenness centrality algorithm
- Dijkstra predecessor and distance algorithm
- xslt to convert DIA graphs to NetworkX
- number_of_edges(u,v) counts edges between nodes u and v
- run tests with python setup_egg.py test (needs setuptools) else use python -c “import networkx; networkx.test()”
- is_isomorphic() that uses vf2 algorithm
- speedups of neighbors()
- simplified Dijkstra’s algorithm code
- better exception handling for shortest paths
- get_edge(u,v) returns None (instead of exception) if no edge u-v
- floyd_warshall_array fixes for negative weights
- bad G467, docs, and unittest fixes for graph atlas
- don’t put nans in numpy or scipy sparse adjacency matrix
- handle get_edge() exception (return None if no edge)
- remove extra kwds arguments in many places
- no multi counting edges in conversion to dict of lists for multigraphs
- allow passing tuple to get_edge()
- bad parameter order in node/edge betweenness
- edge betweenness doesn’t fail with XGraph
- don’t throw exceptions for nodes not in graph (silently ignore instead) in edges_* and degree_*
Release date: 27 November 2006
See: https://networkx.lanl.gov/trac/timeline
draw edges with specified colormap
more efficient version of Floyd’s algorithm for all pairs shortest path
use numpy only, Numeric is deprecated
include tests in source package (networkx/tests)
include documentation in source package (doc)
- tests can now be run with
- read_gpickle now works correctly with Windows
- refactored large modules into smaller code files
- degree(nbunch) now returns degrees in same order as nbunch
- degree() now works for multiedges=True
- update node_boundary and edge_boundary for efficiency
- edited documentation for graph classes, now mostly in info.py
- Draw edges with colormap
Release date: 29 September 2006
See: https://networkx.lanl.gov/trac/timeline
- Update to work with numpy-1.0x
- Make egg usage optional: use python setup_egg.py bdist_egg to build egg
- Generators and functions for bipartite graphs
- Experimental classes for trees and forests
- Support for new pygraphviz update (in nx_agraph.py) , see http://networkx.lanl.gov/pygraphviz/ for pygraphviz details
- Handle special cases correctly in triangles function
- Typos in documentation
- Handle special cases in shortest_path and shortest_path_length, allow cutoff parameter for maximum depth to search
- Update examples: erdos_renyi.py, miles.py, roget,py, eigenvalues.py
- Expected degree sequence
- New pygraphviz interface
Release date: 20 July 2006
See: https://networkx.lanl.gov/trac/timeline
- arbitrary node relabeling (use relabel_nodes)
- conversion of NetworkX graphs to/from Python dict/list types, numpy matrix or array types, and scipy_sparse_matrix types
- generator for random graphs with given expected degree sequence
- Allow drawing graphs with no edges using pylab
- Use faster heapq in dijkstra
- Don’t complain if X windows is not available
- update drawing examples
Release date: 23 June 2006
See: https://networkx.lanl.gov/trac/timeline
- update to work with Python 2.5
- bidirectional version of shortest_path and Dijkstra
- single_source_shortest_path and all_pairs_shortest_path
- s-metric and experimental code to generate maximal s-metric graph
- double_edge_swap and connected_double_edge_swap
- Floyd’s algorithm for all pairs shortest path
- read and write unicode graph data to text files
- read and write YAML format text files, http://yaml.org
- speed improvements (faster version of subgraph, is_connected)
- added cumulative distribution and modified discrete distribution utilities
- report error if DiGraphs are sent to connected_components routines
- removed with_labels keywords for many functions where it was causing confusion
- function name changes in shortest_path routines
- saner internal handling of nbunch (node bunches), raise an exception if an nbunch isn’t a node or iterable
- better keyword handling in io.py allows reading multiple graphs
- don’t mix Numeric and numpy arrays in graph layouts and drawing
- avoid automatically rescaling matplotlib axes when redrawing graph layout
- unicode node labels
Release date: 28 April 2006
See: https://networkx.lanl.gov/trac/timeline
- Algorithms for betweeenness, eigenvalues, eigenvectors, and spectral projection for threshold graphs
- Use numpy when available
- dense_gnm_random_graph generator
- Generators for some directed graphs: GN, GNR, and GNC by Krapivsky and Redner
- Grid graph generators now label by index tuples. Helper functions for manipulating labels.
- relabel_nodes_with_function
- Betweenness centrality now correctly uses Brandes definition and has normalization option outside main loop
- Empty graph now labled as empty_graph(n)
- shortest_path_length used python2.4 generator feature
- degree_sequence_tree off by one error caused nonconsecutive labeling
- periodic_grid_2d_graph removed in favor of grid_2d_graph with periodic=True
Release date: 13 March 2006
See: https://networkx.lanl.gov/trac/timeline
- Option to construct Laplacian with rows and columns in specified order
- Option in convert_node_labels_to_integers to use sorted order
- predecessor(G,n) function that returns dictionary of nodes with predecessors from breadth-first search of G starting at node n. https://networkx.lanl.gov/trac/ticket/26
- Formation of giant component in binomial_graph:
- Chess masters matches:
- Gallery https://networkx.lanl.gov/gallery.html
- Adjusted names for random graphs.
- erdos_renyi_graph=binomial_graph=gnp_graph: n nodes with edge probability p
- gnm_graph: n nodes and m edges
- fast_gnp_random_graph: gnp for sparse graphs (small p)
Documentation contains correct spelling of Barabási, Bollobás, Erdős, and Rényi in UTF-8 encoding
Increased speed of connected_components and related functions by using faster BFS algorithm in networkx.paths https://networkx.lanl.gov/trac/ticket/27
XGraph and XDiGraph with multiedges=True produced error on delete_edge
Cleaned up docstring errors
Normalize names of some graphs to produce strings that represent calling sequence
Release date: 5 February 2006
See: https://networkx.lanl.gov/trac/timeline
- sparse_binomial_graph: faster graph generator for sparse random graphs
- read/write routines in io.py now handle XGraph() type and gzip and bzip2 files
- optional mapping of type for read/write routine to allow on-the-fly conversion of node and edge datatype on read
- Substantial changes related to digraphs and definitions of neighbors() and edges(). For digraphs edges=out_edges. Neighbors now returns a list of neighboring nodes with possible duplicates for graphs with parallel edges See https://networkx.lanl.gov/trac/ticket/24
- Addition of out_edges, in_edges and corresponding out_neighbors and in_neighbors for digraphs. For digraphs edges=out_edges.
- Minard’s data for Napoleon’s Russian campaign
- XGraph(multiedges=True) returns a copy of the list of edges for get_edge()
Release date: 6 January 2006
- Simpler interface to drawing with pylab
- G.info(node=None) function returns short information about graph or node
- adj_matrix now takes optional nodelist to force ordering of rows/columns in matrix
- optional pygraphviz and pydot interface to graphviz is now callable as “graphviz” with pygraphviz preferred. Use draw_graphviz(G).
- Several new examples showing how draw to graphs with various properties of nodes, edges, and labels
- Default data type for all graphs is now None (was the integer 1)
- add_nodes_from now won’t delete edges if nodes added already exist
- Added missing names to generated graphs
- Indexes for nodes in graphs start at zero by default (was 1)
Release date: 5 December 2005
- Uses setuptools for installation http://peak.telecommunity.com/DevCenter/setuptools
- Improved testing infrastructure, can now run python setup.py test
- Added interface to draw graphs with pygraphviz https://networkx.lanl.gov/pygraphviz/
- is_directed() function call
- Email example shows how to use XDiGraph with Python objects as edge data
- Reformat menu, minor changes to Readme, better stylesheet
- use create_using= instead of result= keywords for graph types in all cases
- missing weights for degree 0 and 1 nodes in clustering
- configuration model now uses XGraph, returns graph with identical degree sequence as input sequence
- fixed dijstra priority queue
- fixed non-recursive toposort and is_directed_acyclic graph
Release date: 20 August 2005
- Update of dijstra algorithm code
- dfs_successor now calls proper search method
- Changed to list compehension in DiGraph.reverse() for python2.3 compatibility
- Barabasi-Albert graph generator fixed
- Attempt to add self loop should add node even if parallel edges not allowed
Release date: 14 July 2005
The NetworkX web locations have changed:
http://networkx.lanl.gov/ - main documentation site http://networkx.lanl.gov/svn/ - subversion source code repository https://networkx.lanl.gov/trac/ - bug tracking and info
The naming conventions in NetworkX have changed. The package name “NX” is now “networkx”.
The suggested ways to import the NetworkX package are
- import networkx
- import networkx as NX
- from networkx import *
DiGraph reverse
- Graph generators
- watts_strogatz_graph now does rewiring method
- old watts_strogatz_graph->newman_watts_strogatz_graph
- Changed to reflect NX-networkx change
- main site is now https://networkx.lanl.gov/
- Fixed logic in io.py for reading DiGraphs.
- Path based centrality measures (betweenness, closeness) modified so they work on graphs that are not connected and produce the same result as if each connected component were considered separately.
Release date: 17 June 2005
Topological sort, testing for directed acyclic graphs (DAGs)
Dikjstra’s algorithm for shortest paths in weighted graphs
Multidimensional layout with dim=n for drawing
3d rendering demonstration with vtk
- Graph generators
- random_powerlaw_tree
- dorogovtsev_goltsev_mendes_graph
- Kevin Bacon movie actor graph: Examples/kevin_bacon.py
- Compute eigenvalues of graph Laplacian: Examples/eigenvalues.py
- Atlas of small graphs: Examples/atlas.py
- Rewrite of setup scripts to install documentation and tests in documentation directory specified
- Handle calls to edges() with non-node, non-iterable items.
- truncated_tetrahedral_graph was just plain wrong
- Speedup of betweenness_centrality code
- bfs_path_length now returns correct lengths
- Catch error if target of search not in connected component of source
- Code cleanup to label internal functions with _name
- Changed import statement lines to always use “import NX” to protect name-spaces
- Other minor bug-fixes and testing added