This documents an unmaintained version of NetworkX. Please upgrade to a maintained version and see the current NetworkX documentation.
Version 1.6 notes and API changes¶
This page reflects API changes from networkx-1.5 to networkx-1.6.
Please send comments and questions to the networkx-discuss mailing list: http://groups.google.com/group/networkx-discuss .
The degree* methods in the graph classes (Graph, DiGraph, MultiGraph, MultiDiGraph) now take an optional weight= keyword that allows computing weighted degree with arbitrary (numerical) edge attributes. Setting weight=None is equivalent to the previous weighted=False.
Weighted graph algorithms¶
Many ‘weighted’ graph algorithms now take optional parameter to
specifiy which edge attribute should be used for the weight
In some cases the parameter name was changed from weighted, to weight. Here is how to specify which edge attribute will be used in the algorithms:
- Use weight=None to consider all weights equally (unweighted case)
- Use weight=’weight’ to use the ‘weight’ edge atribute
- Use weight=’other’ to use the ‘other’ edge attribute
Algorithms affected are:
to_scipy_sparse_matrix, clustering, average_clustering, bipartite.degree, spectral_layout, neighbor_degree, is_isomorphic, betweenness_centrality, betweenness_centrality_subset, vitality, load_centrality, mincost, shortest_path, shortest_path_length, average_shortest_path_length
Node and edge attributes are now more easily incorporated into isomorphism checks via the ‘node_match’ and ‘edge_match’ parameters. As part of this change, the following classes were removed:
WeightedGraphMatcher WeightedDiGraphMatcher WeightedMultiGraphMatcher WeightedMultiDiGraphMatcher
The function signature for ‘is_isomorphic’ is now simply:
is_isomorphic(g1, g2, node_match=None, edge_match=None)
See its docstring for more details. To aid in the creation of ‘node_match’ and ‘edge_match’ functions, users are encouraged to work with:
categorical_node_match categorical_edge_match categroical_multiedge_match numerical_node_match numerical_edge_match numerical_multiedge_match generic_node_match generic_edge_match generic_multiedge_match
These functions construct functions which can be passed to ‘is_isomorphic’. Finally, note that the above functions are not imported into the top-level namespace and should be accessed from ‘networkx.algorithms.isomorphism’. A useful import statement that will be repeated throughout documentation is:
import networkx.algorithms.isomorphism as iso
A list of lists is returned instead of a list of tuples.
The condensation algorithm now takes a second argument (scc) and returns a graph with nodes labeled as integers instead of node tuples.
average_in_degree_connectivity and average_out_degree_connectivity have have been replaced with
average_degree_connectivity(G, source=’in’, target=’in’)
average_degree_connectivity(G, source=’out’, target=’out’)
average_neighbor_in_degree and average_neighbor_out_degreey have have been replaced with
average_neighbor_degree(G, source=’in’, target=’in’)
average_neighbor_degree(G, source=’out’, target=’out’)