Source Code for Package networkx

  1  """ 
  2  NetworkX 
  3  ======== 
  4   
  5     NetworkX (NX) is a Python package for the creation, manipulation, and 
  6     study of the structure, dynamics, and functions of complex networks.   
  7   
  8     https://networkx.lanl.gov/ 
  9   
 10  Using  
 11  ----- 
 12   
 13     Just write in Python 
 14   
 15     >>> import networkx as NX 
 16     >>> G=NX.Graph() 
 17     >>> G.add_edge(1,2) 
 18     >>> G.add_node("spam") 
 19     >>> print G.nodes() 
 20     [1, 2, 'spam'] 
 21     >>> print G.edges() 
 22     [(1, 2)] 
 23  """ 
 24  #    Copyright (C) 2004-2006 by  
 25  #    Aric Hagberg <hagberg@lanl.gov> 
 26  #    Dan Schult <dschult@colgate.edu> 
 27  #    Pieter Swart <swart@lanl.gov> 
 28  #    Distributed under the terms of the GNU Lesser General Public License 
 29  #    http://www.gnu.org/copyleft/lesser.html 
 30  # 
 31  # Add platform dependent shared library path to sys.path 
 32  # 
 33  import sys 
 34  if sys.version_info[:2] < (2, 3): 
 35      print "Python version 2.3 or later is required for NetworkX (%d.%d detected)." %  sys.version_info[:2] 
 36      sys.exit(-1) 
 37  del sys 
 38  # Release data 
 39  import release  
 40  __version__  = release.version 
 41  __date__     = release.date 
 42  __author__   = '%s <%s>\n%s <%s>\n%s <%s>' % \ 
 43                ( release.authors['Hagberg'] + release.authors['Schult'] + \ 
 44                  release.authors['Swart'] ) 
 45  __license__  = release.license 
 46   
 47  import info 
 48  __doc__+=info.__doc__ 
 49   
 50  # 
 51  # NetworkX package modules 
 52  # 
 53  from exception import  NetworkXException, NetworkXError 
 54  from graph import Graph 
 55  from digraph import DiGraph 
 56  from function import  nodes, edges, degree, degree_histogram, neighbors,\ 
 57                   number_of_nodes, number_of_edges, density,\ 
 58                   nodes_iter, edges_iter, is_directed 
 59  from xgraph import XGraph 
 60  from xdigraph import XDiGraph 
 61  from distance import eccentricity, diameter, radius, periphery, center 
 62  from path import  \ 
 63       shortest_path, shortest_path_length,bidirectional_shortest_path,\ 
 64       single_source_shortest_path, single_source_shortest_path_length,\ 
 65       all_pairs_shortest_path, all_pairs_shortest_path_length,\ 
 66       dijkstra_path, dijkstra_path_length, bidirectional_dijkstra,\ 
 67       single_source_dijkstra_path, single_source_dijkstra_path_length,\ 
 68       single_source_dijkstra,\ 
 69       dijkstra_predecessor_and_distance, predecessor, floyd_warshall 
 70  from dag import \ 
 71       topological_sort, topological_sort_recursive,\ 
 72       is_directed_acyclic_graph 
 73  from component import \ 
 74       number_connected_components, connected_components,\ 
 75       is_connected, connected_component_subgraphs,\ 
 76       node_connected_component,\ 
 77       number_strongly_connected_components, strongly_connected_components,\ 
 78       is_strongly_connected, strongly_connected_component_subgraphs,\ 
 79       strongly_connected_components_recursive,\ 
 80       kosaraju_strongly_connected_components 
 81   
 82  from search import dfs_preorder, dfs_postorder, dfs_predecessor,\ 
 83              dfs_successor, dfs_tree 
 84  from cluster import triangles, average_clustering, clustering, transitivity 
 85  from operators import union, cartesian_product, compose, complement,\ 
 86                        disjoint_union, create_empty_copy,\ 
 87                        subgraph, convert_to_undirected, convert_to_directed,\ 
 88                        convert_node_labels_to_integers, relabel_nodes 
 89  from centrality import betweenness_centrality, \ 
 90                         betweenness_centrality_source, \ 
 91                         load_centrality,\ 
 92                         newman_betweenness_centrality,\ 
 93                         brandes_betweenness_centrality,\ 
 94                         edge_betweenness,\ 
 95                         edge_load,\ 
 96                         degree_centrality, \ 
 97                         closeness_centrality 
 98  from hybrid import kl_connected_subgraph, is_kl_connected 
 99  from cliques import find_cliques, make_max_clique_graph,\ 
100                      make_clique_bipartite,graph_clique_number,\ 
101                      graph_number_of_cliques,node_clique_number,\ 
102                      number_of_cliques,cliques_containing_node 
103  from isomorph import is_isomorphic 
104                       
105  # need numpy for spectrum 
106  try: 
107      from spectrum import \ 
108           adj_matrix, laplacian, generalized_laplacian,\ 
109           laplacian_spectrum, adjacency_spectrum 
110  except ImportError: 
111      pass 
112   
113  from utils import is_string_like, iterable,\ 
114                    pareto_sequence, powerlaw_sequence, uniform_sequence,\ 
115                    cumulative_distribution, discrete_sequence,_get_fh 
116   
117   
118  from convert import from_whatever,\ 
119       from_dict_of_dicts, to_dict_of_dicts,\ 
120       from_dict_of_lists, to_dict_of_lists,\ 
121       from_numpy_matrix, to_numpy_matrix,\ 
122       from_scipy_sparse_matrix, to_scipy_sparse_matrix 
123   
124  # import some useful graphs - we always use these... 
125  from generators.classic import * 
126  from generators.small import * 
127  from generators.random_graphs import * 
128  from generators.degree_seq import * 
129  from generators.directed import * 
130  # drawing 
131  from drawing import * 
132  # read/write graphs in various formats 
133  from readwrite import * 
134   
135  from tests import run as test 
136