annotate env/lib/python3.9/site-packages/networkx/classes/graph.py @ 0:4f3585e2f14b draft default tip

"planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
author shellac
date Mon, 22 Mar 2021 18:12:50 +0000
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1 """Base class for undirected graphs.
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2
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3 The Graph class allows any hashable object as a node
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4 and can associate key/value attribute pairs with each undirected edge.
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5
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6 Self-loops are allowed but multiple edges are not (see MultiGraph).
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7
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8 For directed graphs see DiGraph and MultiDiGraph.
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9 """
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10 from copy import deepcopy
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11
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12 import networkx as nx
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13 from networkx.classes.coreviews import AdjacencyView
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14 from networkx.classes.reportviews import NodeView, EdgeView, DegreeView
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15 from networkx.exception import NetworkXError
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16 import networkx.convert as convert
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17
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18
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19 class Graph:
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20 """
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21 Base class for undirected graphs.
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22
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23 A Graph stores nodes and edges with optional data, or attributes.
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24
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25 Graphs hold undirected edges. Self loops are allowed but multiple
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26 (parallel) edges are not.
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27
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28 Nodes can be arbitrary (hashable) Python objects with optional
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29 key/value attributes. By convention `None` is not used as a node.
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30
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31 Edges are represented as links between nodes with optional
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32 key/value attributes.
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33
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34 Parameters
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35 ----------
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36 incoming_graph_data : input graph (optional, default: None)
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37 Data to initialize graph. If None (default) an empty
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38 graph is created. The data can be any format that is supported
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39 by the to_networkx_graph() function, currently including edge list,
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40 dict of dicts, dict of lists, NetworkX graph, NumPy matrix
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41 or 2d ndarray, SciPy sparse matrix, or PyGraphviz graph.
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42
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43 attr : keyword arguments, optional (default= no attributes)
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44 Attributes to add to graph as key=value pairs.
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45
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46 See Also
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47 --------
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48 DiGraph
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49 MultiGraph
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50 MultiDiGraph
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51 OrderedGraph
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52
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53 Examples
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54 --------
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55 Create an empty graph structure (a "null graph") with no nodes and
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56 no edges.
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57
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58 >>> G = nx.Graph()
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59
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60 G can be grown in several ways.
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61
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62 **Nodes:**
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63
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64 Add one node at a time:
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65
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66 >>> G.add_node(1)
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67
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68 Add the nodes from any container (a list, dict, set or
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69 even the lines from a file or the nodes from another graph).
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70
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71 >>> G.add_nodes_from([2, 3])
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72 >>> G.add_nodes_from(range(100, 110))
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73 >>> H = nx.path_graph(10)
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74 >>> G.add_nodes_from(H)
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75
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76 In addition to strings and integers any hashable Python object
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77 (except None) can represent a node, e.g. a customized node object,
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78 or even another Graph.
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79
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80 >>> G.add_node(H)
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81
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82 **Edges:**
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83
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84 G can also be grown by adding edges.
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85
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86 Add one edge,
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87
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88 >>> G.add_edge(1, 2)
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89
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90 a list of edges,
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91
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92 >>> G.add_edges_from([(1, 2), (1, 3)])
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93
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94 or a collection of edges,
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95
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96 >>> G.add_edges_from(H.edges)
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97
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98 If some edges connect nodes not yet in the graph, the nodes
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99 are added automatically. There are no errors when adding
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100 nodes or edges that already exist.
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101
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102 **Attributes:**
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103
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104 Each graph, node, and edge can hold key/value attribute pairs
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105 in an associated attribute dictionary (the keys must be hashable).
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106 By default these are empty, but can be added or changed using
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107 add_edge, add_node or direct manipulation of the attribute
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108 dictionaries named graph, node and edge respectively.
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109
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110 >>> G = nx.Graph(day="Friday")
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111 >>> G.graph
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112 {'day': 'Friday'}
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113
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114 Add node attributes using add_node(), add_nodes_from() or G.nodes
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115
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116 >>> G.add_node(1, time="5pm")
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117 >>> G.add_nodes_from([3], time="2pm")
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118 >>> G.nodes[1]
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119 {'time': '5pm'}
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120 >>> G.nodes[1]["room"] = 714 # node must exist already to use G.nodes
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121 >>> del G.nodes[1]["room"] # remove attribute
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122 >>> list(G.nodes(data=True))
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123 [(1, {'time': '5pm'}), (3, {'time': '2pm'})]
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124
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125 Add edge attributes using add_edge(), add_edges_from(), subscript
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126 notation, or G.edges.
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127
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128 >>> G.add_edge(1, 2, weight=4.7)
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129 >>> G.add_edges_from([(3, 4), (4, 5)], color="red")
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130 >>> G.add_edges_from([(1, 2, {"color": "blue"}), (2, 3, {"weight": 8})])
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131 >>> G[1][2]["weight"] = 4.7
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132 >>> G.edges[1, 2]["weight"] = 4
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133
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134 Warning: we protect the graph data structure by making `G.edges` a
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135 read-only dict-like structure. However, you can assign to attributes
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136 in e.g. `G.edges[1, 2]`. Thus, use 2 sets of brackets to add/change
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137 data attributes: `G.edges[1, 2]['weight'] = 4`
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138 (For multigraphs: `MG.edges[u, v, key][name] = value`).
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139
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140 **Shortcuts:**
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141
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142 Many common graph features allow python syntax to speed reporting.
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143
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144 >>> 1 in G # check if node in graph
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145 True
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146 >>> [n for n in G if n < 3] # iterate through nodes
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147 [1, 2]
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148 >>> len(G) # number of nodes in graph
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149 5
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150
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151 Often the best way to traverse all edges of a graph is via the neighbors.
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152 The neighbors are reported as an adjacency-dict `G.adj` or `G.adjacency()`
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153
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154 >>> for n, nbrsdict in G.adjacency():
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155 ... for nbr, eattr in nbrsdict.items():
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156 ... if "weight" in eattr:
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157 ... # Do something useful with the edges
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158 ... pass
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159
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160 But the edges() method is often more convenient:
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161
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162 >>> for u, v, weight in G.edges.data("weight"):
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163 ... if weight is not None:
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164 ... # Do something useful with the edges
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165 ... pass
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166
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167 **Reporting:**
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168
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169 Simple graph information is obtained using object-attributes and methods.
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170 Reporting typically provides views instead of containers to reduce memory
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171 usage. The views update as the graph is updated similarly to dict-views.
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172 The objects `nodes`, `edges` and `adj` provide access to data attributes
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173 via lookup (e.g. `nodes[n]`, `edges[u, v]`, `adj[u][v]`) and iteration
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174 (e.g. `nodes.items()`, `nodes.data('color')`,
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175 `nodes.data('color', default='blue')` and similarly for `edges`)
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176 Views exist for `nodes`, `edges`, `neighbors()`/`adj` and `degree`.
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177
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178 For details on these and other miscellaneous methods, see below.
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179
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180 **Subclasses (Advanced):**
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181
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182 The Graph class uses a dict-of-dict-of-dict data structure.
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183 The outer dict (node_dict) holds adjacency information keyed by node.
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184 The next dict (adjlist_dict) represents the adjacency information and holds
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185 edge data keyed by neighbor. The inner dict (edge_attr_dict) represents
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186 the edge data and holds edge attribute values keyed by attribute names.
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187
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188 Each of these three dicts can be replaced in a subclass by a user defined
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189 dict-like object. In general, the dict-like features should be
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190 maintained but extra features can be added. To replace one of the
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191 dicts create a new graph class by changing the class(!) variable
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192 holding the factory for that dict-like structure. The variable names are
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193 node_dict_factory, node_attr_dict_factory, adjlist_inner_dict_factory,
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194 adjlist_outer_dict_factory, edge_attr_dict_factory and graph_attr_dict_factory.
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195
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196 node_dict_factory : function, (default: dict)
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197 Factory function to be used to create the dict containing node
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198 attributes, keyed by node id.
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199 It should require no arguments and return a dict-like object
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200
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201 node_attr_dict_factory: function, (default: dict)
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202 Factory function to be used to create the node attribute
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203 dict which holds attribute values keyed by attribute name.
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204 It should require no arguments and return a dict-like object
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205
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206 adjlist_outer_dict_factory : function, (default: dict)
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207 Factory function to be used to create the outer-most dict
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208 in the data structure that holds adjacency info keyed by node.
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209 It should require no arguments and return a dict-like object.
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210
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211 adjlist_inner_dict_factory : function, (default: dict)
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212 Factory function to be used to create the adjacency list
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213 dict which holds edge data keyed by neighbor.
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214 It should require no arguments and return a dict-like object
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215
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216 edge_attr_dict_factory : function, (default: dict)
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217 Factory function to be used to create the edge attribute
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218 dict which holds attribute values keyed by attribute name.
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219 It should require no arguments and return a dict-like object.
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220
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221 graph_attr_dict_factory : function, (default: dict)
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222 Factory function to be used to create the graph attribute
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223 dict which holds attribute values keyed by attribute name.
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224 It should require no arguments and return a dict-like object.
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225
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226 Typically, if your extension doesn't impact the data structure all
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227 methods will inherit without issue except: `to_directed/to_undirected`.
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228 By default these methods create a DiGraph/Graph class and you probably
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229 want them to create your extension of a DiGraph/Graph. To facilitate
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230 this we define two class variables that you can set in your subclass.
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231
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232 to_directed_class : callable, (default: DiGraph or MultiDiGraph)
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233 Class to create a new graph structure in the `to_directed` method.
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234 If `None`, a NetworkX class (DiGraph or MultiDiGraph) is used.
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235
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236 to_undirected_class : callable, (default: Graph or MultiGraph)
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237 Class to create a new graph structure in the `to_undirected` method.
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238 If `None`, a NetworkX class (Graph or MultiGraph) is used.
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239
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240 Examples
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241 --------
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242
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243 Create a low memory graph class that effectively disallows edge
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244 attributes by using a single attribute dict for all edges.
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245 This reduces the memory used, but you lose edge attributes.
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246
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247 >>> class ThinGraph(nx.Graph):
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248 ... all_edge_dict = {"weight": 1}
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249 ...
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250 ... def single_edge_dict(self):
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251 ... return self.all_edge_dict
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252 ...
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253 ... edge_attr_dict_factory = single_edge_dict
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254 >>> G = ThinGraph()
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255 >>> G.add_edge(2, 1)
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256 >>> G[2][1]
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257 {'weight': 1}
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258 >>> G.add_edge(2, 2)
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259 >>> G[2][1] is G[2][2]
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260 True
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261
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262 Please see :mod:`~networkx.classes.ordered` for more examples of
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263 creating graph subclasses by overwriting the base class `dict` with
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264 a dictionary-like object.
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265 """
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266
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267 node_dict_factory = dict
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268 node_attr_dict_factory = dict
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269 adjlist_outer_dict_factory = dict
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270 adjlist_inner_dict_factory = dict
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271 edge_attr_dict_factory = dict
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272 graph_attr_dict_factory = dict
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273
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274 def to_directed_class(self):
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275 """Returns the class to use for empty directed copies.
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276
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277 If you subclass the base classes, use this to designate
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278 what directed class to use for `to_directed()` copies.
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279 """
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280 return nx.DiGraph
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281
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282 def to_undirected_class(self):
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283 """Returns the class to use for empty undirected copies.
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284
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285 If you subclass the base classes, use this to designate
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286 what directed class to use for `to_directed()` copies.
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287 """
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288 return Graph
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289
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290 def __init__(self, incoming_graph_data=None, **attr):
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291 """Initialize a graph with edges, name, or graph attributes.
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292
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293 Parameters
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294 ----------
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295 incoming_graph_data : input graph (optional, default: None)
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296 Data to initialize graph. If None (default) an empty
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297 graph is created. The data can be an edge list, or any
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298 NetworkX graph object. If the corresponding optional Python
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299 packages are installed the data can also be a NumPy matrix
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300 or 2d ndarray, a SciPy sparse matrix, or a PyGraphviz graph.
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301
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302 attr : keyword arguments, optional (default= no attributes)
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303 Attributes to add to graph as key=value pairs.
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304
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305 See Also
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306 --------
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307 convert
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308
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309 Examples
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310 --------
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311 >>> G = nx.Graph() # or DiGraph, MultiGraph, MultiDiGraph, etc
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312 >>> G = nx.Graph(name="my graph")
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313 >>> e = [(1, 2), (2, 3), (3, 4)] # list of edges
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314 >>> G = nx.Graph(e)
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315
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316 Arbitrary graph attribute pairs (key=value) may be assigned
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317
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318 >>> G = nx.Graph(e, day="Friday")
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319 >>> G.graph
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320 {'day': 'Friday'}
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321
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322 """
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323 self.graph_attr_dict_factory = self.graph_attr_dict_factory
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324 self.node_dict_factory = self.node_dict_factory
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325 self.node_attr_dict_factory = self.node_attr_dict_factory
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326 self.adjlist_outer_dict_factory = self.adjlist_outer_dict_factory
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327 self.adjlist_inner_dict_factory = self.adjlist_inner_dict_factory
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328 self.edge_attr_dict_factory = self.edge_attr_dict_factory
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329
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330 self.graph = self.graph_attr_dict_factory() # dictionary for graph attributes
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331 self._node = self.node_dict_factory() # empty node attribute dict
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332 self._adj = self.adjlist_outer_dict_factory() # empty adjacency dict
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333 # attempt to load graph with data
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334 if incoming_graph_data is not None:
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335 convert.to_networkx_graph(incoming_graph_data, create_using=self)
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336 # load graph attributes (must be after convert)
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337 self.graph.update(attr)
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338
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339 @property
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340 def adj(self):
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341 """Graph adjacency object holding the neighbors of each node.
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342
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343 This object is a read-only dict-like structure with node keys
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344 and neighbor-dict values. The neighbor-dict is keyed by neighbor
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345 to the edge-data-dict. So `G.adj[3][2]['color'] = 'blue'` sets
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346 the color of the edge `(3, 2)` to `"blue"`.
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347
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348 Iterating over G.adj behaves like a dict. Useful idioms include
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349 `for nbr, datadict in G.adj[n].items():`.
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350
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351 The neighbor information is also provided by subscripting the graph.
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352 So `for nbr, foovalue in G[node].data('foo', default=1):` works.
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353
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354 For directed graphs, `G.adj` holds outgoing (successor) info.
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355 """
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356 return AdjacencyView(self._adj)
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357
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358 @property
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359 def name(self):
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360 """String identifier of the graph.
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361
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362 This graph attribute appears in the attribute dict G.graph
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363 keyed by the string `"name"`. as well as an attribute (technically
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364 a property) `G.name`. This is entirely user controlled.
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365 """
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366 return self.graph.get("name", "")
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367
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368 @name.setter
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369 def name(self, s):
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370 self.graph["name"] = s
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371
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372 def __str__(self):
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373 """Returns the graph name.
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374
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375 Returns
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376 -------
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377 name : string
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378 The name of the graph.
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379
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380 Examples
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381 --------
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382 >>> G = nx.Graph(name="foo")
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383 >>> str(G)
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384 'foo'
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385 """
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386 return self.name
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387
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388 def __iter__(self):
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389 """Iterate over the nodes. Use: 'for n in G'.
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390
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391 Returns
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392 -------
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393 niter : iterator
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394 An iterator over all nodes in the graph.
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395
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396 Examples
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397 --------
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398 >>> G = nx.path_graph(4) # or DiGraph, MultiGraph, MultiDiGraph, etc
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399 >>> [n for n in G]
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400 [0, 1, 2, 3]
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401 >>> list(G)
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402 [0, 1, 2, 3]
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403 """
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404 return iter(self._node)
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405
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406 def __contains__(self, n):
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407 """Returns True if n is a node, False otherwise. Use: 'n in G'.
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408
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409 Examples
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410 --------
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411 >>> G = nx.path_graph(4) # or DiGraph, MultiGraph, MultiDiGraph, etc
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412 >>> 1 in G
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413 True
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414 """
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415 try:
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416 return n in self._node
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417 except TypeError:
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418 return False
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419
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420 def __len__(self):
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421 """Returns the number of nodes in the graph. Use: 'len(G)'.
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422
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423 Returns
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424 -------
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425 nnodes : int
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426 The number of nodes in the graph.
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427
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428 See Also
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429 --------
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430 number_of_nodes, order which are identical
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431
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432 Examples
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433 --------
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434 >>> G = nx.path_graph(4) # or DiGraph, MultiGraph, MultiDiGraph, etc
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435 >>> len(G)
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436 4
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437
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438 """
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439 return len(self._node)
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440
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441 def __getitem__(self, n):
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442 """Returns a dict of neighbors of node n. Use: 'G[n]'.
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443
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444 Parameters
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445 ----------
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446 n : node
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447 A node in the graph.
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448
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449 Returns
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450 -------
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451 adj_dict : dictionary
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452 The adjacency dictionary for nodes connected to n.
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453
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454 Notes
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455 -----
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456 G[n] is the same as G.adj[n] and similar to G.neighbors(n)
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457 (which is an iterator over G.adj[n])
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458
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459 Examples
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460 --------
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461 >>> G = nx.path_graph(4) # or DiGraph, MultiGraph, MultiDiGraph, etc
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462 >>> G[0]
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463 AtlasView({1: {}})
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464 """
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465 return self.adj[n]
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466
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467 def add_node(self, node_for_adding, **attr):
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468 """Add a single node `node_for_adding` and update node attributes.
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469
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470 Parameters
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471 ----------
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472 node_for_adding : node
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473 A node can be any hashable Python object except None.
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474 attr : keyword arguments, optional
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475 Set or change node attributes using key=value.
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476
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477 See Also
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478 --------
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479 add_nodes_from
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480
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481 Examples
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482 --------
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483 >>> G = nx.Graph() # or DiGraph, MultiGraph, MultiDiGraph, etc
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484 >>> G.add_node(1)
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485 >>> G.add_node("Hello")
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486 >>> K3 = nx.Graph([(0, 1), (1, 2), (2, 0)])
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487 >>> G.add_node(K3)
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488 >>> G.number_of_nodes()
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489 3
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490
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491 Use keywords set/change node attributes:
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492
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493 >>> G.add_node(1, size=10)
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494 >>> G.add_node(3, weight=0.4, UTM=("13S", 382871, 3972649))
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495
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496 Notes
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497 -----
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498 A hashable object is one that can be used as a key in a Python
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499 dictionary. This includes strings, numbers, tuples of strings
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500 and numbers, etc.
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501
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502 On many platforms hashable items also include mutables such as
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503 NetworkX Graphs, though one should be careful that the hash
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504 doesn't change on mutables.
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505 """
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506 if node_for_adding not in self._node:
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507 self._adj[node_for_adding] = self.adjlist_inner_dict_factory()
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508 attr_dict = self._node[node_for_adding] = self.node_attr_dict_factory()
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509 attr_dict.update(attr)
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510 else: # update attr even if node already exists
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511 self._node[node_for_adding].update(attr)
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512
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513 def add_nodes_from(self, nodes_for_adding, **attr):
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514 """Add multiple nodes.
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515
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516 Parameters
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517 ----------
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518 nodes_for_adding : iterable container
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519 A container of nodes (list, dict, set, etc.).
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520 OR
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521 A container of (node, attribute dict) tuples.
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522 Node attributes are updated using the attribute dict.
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523 attr : keyword arguments, optional (default= no attributes)
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524 Update attributes for all nodes in nodes.
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525 Node attributes specified in nodes as a tuple take
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526 precedence over attributes specified via keyword arguments.
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527
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528 See Also
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529 --------
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530 add_node
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531
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532 Examples
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533 --------
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534 >>> G = nx.Graph() # or DiGraph, MultiGraph, MultiDiGraph, etc
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535 >>> G.add_nodes_from("Hello")
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536 >>> K3 = nx.Graph([(0, 1), (1, 2), (2, 0)])
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537 >>> G.add_nodes_from(K3)
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538 >>> sorted(G.nodes(), key=str)
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539 [0, 1, 2, 'H', 'e', 'l', 'o']
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540
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541 Use keywords to update specific node attributes for every node.
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542
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543 >>> G.add_nodes_from([1, 2], size=10)
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544 >>> G.add_nodes_from([3, 4], weight=0.4)
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545
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546 Use (node, attrdict) tuples to update attributes for specific nodes.
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547
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548 >>> G.add_nodes_from([(1, dict(size=11)), (2, {"color": "blue"})])
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549 >>> G.nodes[1]["size"]
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550 11
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551 >>> H = nx.Graph()
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552 >>> H.add_nodes_from(G.nodes(data=True))
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553 >>> H.nodes[1]["size"]
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554 11
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555
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556 """
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557 for n in nodes_for_adding:
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558 # keep all this inside try/except because
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559 # CPython throws TypeError on n not in self._node,
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560 # while pre-2.7.5 ironpython throws on self._adj[n]
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561 try:
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562 if n not in self._node:
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563 self._adj[n] = self.adjlist_inner_dict_factory()
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564 attr_dict = self._node[n] = self.node_attr_dict_factory()
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565 attr_dict.update(attr)
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566 else:
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567 self._node[n].update(attr)
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568 except TypeError:
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569 nn, ndict = n
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570 if nn not in self._node:
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571 self._adj[nn] = self.adjlist_inner_dict_factory()
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572 newdict = attr.copy()
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573 newdict.update(ndict)
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574 attr_dict = self._node[nn] = self.node_attr_dict_factory()
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575 attr_dict.update(newdict)
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576 else:
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577 olddict = self._node[nn]
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578 olddict.update(attr)
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579 olddict.update(ndict)
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580
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581 def remove_node(self, n):
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582 """Remove node n.
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583
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584 Removes the node n and all adjacent edges.
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585 Attempting to remove a non-existent node will raise an exception.
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586
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587 Parameters
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588 ----------
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589 n : node
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590 A node in the graph
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591
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592 Raises
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593 -------
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594 NetworkXError
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595 If n is not in the graph.
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596
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597 See Also
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598 --------
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599 remove_nodes_from
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600
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601 Examples
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602 --------
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603 >>> G = nx.path_graph(3) # or DiGraph, MultiGraph, MultiDiGraph, etc
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604 >>> list(G.edges)
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605 [(0, 1), (1, 2)]
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606 >>> G.remove_node(1)
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607 >>> list(G.edges)
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608 []
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609
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610 """
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611 adj = self._adj
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612 try:
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613 nbrs = list(adj[n]) # list handles self-loops (allows mutation)
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614 del self._node[n]
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615 except KeyError as e: # NetworkXError if n not in self
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616 raise NetworkXError(f"The node {n} is not in the graph.") from e
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617 for u in nbrs:
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618 del adj[u][n] # remove all edges n-u in graph
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619 del adj[n] # now remove node
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620
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621 def remove_nodes_from(self, nodes):
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622 """Remove multiple nodes.
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623
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624 Parameters
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625 ----------
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626 nodes : iterable container
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627 A container of nodes (list, dict, set, etc.). If a node
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628 in the container is not in the graph it is silently
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629 ignored.
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630
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631 See Also
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632 --------
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633 remove_node
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634
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635 Examples
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636 --------
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637 >>> G = nx.path_graph(3) # or DiGraph, MultiGraph, MultiDiGraph, etc
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638 >>> e = list(G.nodes)
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639 >>> e
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640 [0, 1, 2]
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diff changeset
641 >>> G.remove_nodes_from(e)
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parents:
diff changeset
642 >>> list(G.nodes)
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diff changeset
643 []
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644
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645 """
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diff changeset
646 adj = self._adj
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diff changeset
647 for n in nodes:
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diff changeset
648 try:
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649 del self._node[n]
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diff changeset
650 for u in list(adj[n]): # list handles self-loops
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diff changeset
651 del adj[u][n] # (allows mutation of dict in loop)
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parents:
diff changeset
652 del adj[n]
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parents:
diff changeset
653 except KeyError:
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parents:
diff changeset
654 pass
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655
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656 @property
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657 def nodes(self):
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658 """A NodeView of the Graph as G.nodes or G.nodes().
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659
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660 Can be used as `G.nodes` for data lookup and for set-like operations.
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661 Can also be used as `G.nodes(data='color', default=None)` to return a
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662 NodeDataView which reports specific node data but no set operations.
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diff changeset
663 It presents a dict-like interface as well with `G.nodes.items()`
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parents:
diff changeset
664 iterating over `(node, nodedata)` 2-tuples and `G.nodes[3]['foo']`
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665 providing the value of the `foo` attribute for node `3`. In addition,
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diff changeset
666 a view `G.nodes.data('foo')` provides a dict-like interface to the
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diff changeset
667 `foo` attribute of each node. `G.nodes.data('foo', default=1)`
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parents:
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668 provides a default for nodes that do not have attribute `foo`.
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669
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670 Parameters
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671 ----------
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672 data : string or bool, optional (default=False)
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673 The node attribute returned in 2-tuple (n, ddict[data]).
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674 If True, return entire node attribute dict as (n, ddict).
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675 If False, return just the nodes n.
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parents:
diff changeset
676
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diff changeset
677 default : value, optional (default=None)
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parents:
diff changeset
678 Value used for nodes that don't have the requested attribute.
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parents:
diff changeset
679 Only relevant if data is not True or False.
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680
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diff changeset
681 Returns
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682 -------
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parents:
diff changeset
683 NodeView
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diff changeset
684 Allows set-like operations over the nodes as well as node
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diff changeset
685 attribute dict lookup and calling to get a NodeDataView.
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diff changeset
686 A NodeDataView iterates over `(n, data)` and has no set operations.
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parents:
diff changeset
687 A NodeView iterates over `n` and includes set operations.
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parents:
diff changeset
688
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diff changeset
689 When called, if data is False, an iterator over nodes.
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parents:
diff changeset
690 Otherwise an iterator of 2-tuples (node, attribute value)
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parents:
diff changeset
691 where the attribute is specified in `data`.
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parents:
diff changeset
692 If data is True then the attribute becomes the
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diff changeset
693 entire data dictionary.
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694
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parents:
diff changeset
695 Notes
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diff changeset
696 -----
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diff changeset
697 If your node data is not needed, it is simpler and equivalent
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diff changeset
698 to use the expression ``for n in G``, or ``list(G)``.
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parents:
diff changeset
699
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diff changeset
700 Examples
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701 --------
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parents:
diff changeset
702 There are two simple ways of getting a list of all nodes in the graph:
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diff changeset
703
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diff changeset
704 >>> G = nx.path_graph(3)
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parents:
diff changeset
705 >>> list(G.nodes)
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parents:
diff changeset
706 [0, 1, 2]
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parents:
diff changeset
707 >>> list(G)
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parents:
diff changeset
708 [0, 1, 2]
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parents:
diff changeset
709
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parents:
diff changeset
710 To get the node data along with the nodes:
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parents:
diff changeset
711
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parents:
diff changeset
712 >>> G.add_node(1, time="5pm")
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parents:
diff changeset
713 >>> G.nodes[0]["foo"] = "bar"
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parents:
diff changeset
714 >>> list(G.nodes(data=True))
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parents:
diff changeset
715 [(0, {'foo': 'bar'}), (1, {'time': '5pm'}), (2, {})]
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parents:
diff changeset
716 >>> list(G.nodes.data())
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parents:
diff changeset
717 [(0, {'foo': 'bar'}), (1, {'time': '5pm'}), (2, {})]
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parents:
diff changeset
718
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parents:
diff changeset
719 >>> list(G.nodes(data="foo"))
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parents:
diff changeset
720 [(0, 'bar'), (1, None), (2, None)]
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parents:
diff changeset
721 >>> list(G.nodes.data("foo"))
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parents:
diff changeset
722 [(0, 'bar'), (1, None), (2, None)]
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parents:
diff changeset
723
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parents:
diff changeset
724 >>> list(G.nodes(data="time"))
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parents:
diff changeset
725 [(0, None), (1, '5pm'), (2, None)]
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parents:
diff changeset
726 >>> list(G.nodes.data("time"))
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parents:
diff changeset
727 [(0, None), (1, '5pm'), (2, None)]
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parents:
diff changeset
728
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parents:
diff changeset
729 >>> list(G.nodes(data="time", default="Not Available"))
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parents:
diff changeset
730 [(0, 'Not Available'), (1, '5pm'), (2, 'Not Available')]
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parents:
diff changeset
731 >>> list(G.nodes.data("time", default="Not Available"))
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parents:
diff changeset
732 [(0, 'Not Available'), (1, '5pm'), (2, 'Not Available')]
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parents:
diff changeset
733
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parents:
diff changeset
734 If some of your nodes have an attribute and the rest are assumed
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shellac
parents:
diff changeset
735 to have a default attribute value you can create a dictionary
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
736 from node/attribute pairs using the `default` keyword argument
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parents:
diff changeset
737 to guarantee the value is never None::
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parents:
diff changeset
738
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parents:
diff changeset
739 >>> G = nx.Graph()
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parents:
diff changeset
740 >>> G.add_node(0)
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parents:
diff changeset
741 >>> G.add_node(1, weight=2)
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shellac
parents:
diff changeset
742 >>> G.add_node(2, weight=3)
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parents:
diff changeset
743 >>> dict(G.nodes(data="weight", default=1))
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parents:
diff changeset
744 {0: 1, 1: 2, 2: 3}
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parents:
diff changeset
745
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parents:
diff changeset
746 """
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parents:
diff changeset
747 nodes = NodeView(self)
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parents:
diff changeset
748 # Lazy View creation: overload the (class) property on the instance
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parents:
diff changeset
749 # Then future G.nodes use the existing View
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parents:
diff changeset
750 # setattr doesn't work because attribute already exists
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parents:
diff changeset
751 self.__dict__["nodes"] = nodes
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parents:
diff changeset
752 return nodes
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parents:
diff changeset
753
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parents:
diff changeset
754 def number_of_nodes(self):
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parents:
diff changeset
755 """Returns the number of nodes in the graph.
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parents:
diff changeset
756
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parents:
diff changeset
757 Returns
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parents:
diff changeset
758 -------
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parents:
diff changeset
759 nnodes : int
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parents:
diff changeset
760 The number of nodes in the graph.
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parents:
diff changeset
761
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parents:
diff changeset
762 See Also
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parents:
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763 --------
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parents:
diff changeset
764 order, __len__ which are identical
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parents:
diff changeset
765
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766 Examples
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767 --------
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768 >>> G = nx.path_graph(3) # or DiGraph, MultiGraph, MultiDiGraph, etc
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diff changeset
769 >>> G.number_of_nodes()
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770 3
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771 """
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772 return len(self._node)
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773
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774 def order(self):
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775 """Returns the number of nodes in the graph.
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776
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777 Returns
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778 -------
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779 nnodes : int
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diff changeset
780 The number of nodes in the graph.
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781
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782 See Also
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783 --------
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784 number_of_nodes, __len__ which are identical
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785
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786 Examples
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787 --------
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788 >>> G = nx.path_graph(3) # or DiGraph, MultiGraph, MultiDiGraph, etc
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789 >>> G.order()
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790 3
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791 """
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792 return len(self._node)
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793
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794 def has_node(self, n):
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795 """Returns True if the graph contains the node n.
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796
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797 Identical to `n in G`
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798
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799 Parameters
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800 ----------
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801 n : node
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802
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803 Examples
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804 --------
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805 >>> G = nx.path_graph(3) # or DiGraph, MultiGraph, MultiDiGraph, etc
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806 >>> G.has_node(0)
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807 True
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808
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809 It is more readable and simpler to use
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810
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811 >>> 0 in G
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812 True
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813
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814 """
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815 try:
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816 return n in self._node
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817 except TypeError:
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818 return False
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819
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820 def add_edge(self, u_of_edge, v_of_edge, **attr):
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821 """Add an edge between u and v.
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822
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823 The nodes u and v will be automatically added if they are
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824 not already in the graph.
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825
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826 Edge attributes can be specified with keywords or by directly
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827 accessing the edge's attribute dictionary. See examples below.
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828
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829 Parameters
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830 ----------
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831 u, v : nodes
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832 Nodes can be, for example, strings or numbers.
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833 Nodes must be hashable (and not None) Python objects.
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834 attr : keyword arguments, optional
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835 Edge data (or labels or objects) can be assigned using
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836 keyword arguments.
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837
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838 See Also
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839 --------
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840 add_edges_from : add a collection of edges
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841
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842 Notes
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843 -----
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844 Adding an edge that already exists updates the edge data.
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845
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846 Many NetworkX algorithms designed for weighted graphs use
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847 an edge attribute (by default `weight`) to hold a numerical value.
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848
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849 Examples
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850 --------
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851 The following all add the edge e=(1, 2) to graph G:
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852
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853 >>> G = nx.Graph() # or DiGraph, MultiGraph, MultiDiGraph, etc
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854 >>> e = (1, 2)
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855 >>> G.add_edge(1, 2) # explicit two-node form
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856 >>> G.add_edge(*e) # single edge as tuple of two nodes
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857 >>> G.add_edges_from([(1, 2)]) # add edges from iterable container
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858
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859 Associate data to edges using keywords:
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860
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861 >>> G.add_edge(1, 2, weight=3)
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862 >>> G.add_edge(1, 3, weight=7, capacity=15, length=342.7)
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863
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864 For non-string attribute keys, use subscript notation.
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865
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866 >>> G.add_edge(1, 2)
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867 >>> G[1][2].update({0: 5})
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868 >>> G.edges[1, 2].update({0: 5})
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869 """
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870 u, v = u_of_edge, v_of_edge
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871 # add nodes
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872 if u not in self._node:
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873 self._adj[u] = self.adjlist_inner_dict_factory()
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874 self._node[u] = self.node_attr_dict_factory()
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875 if v not in self._node:
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876 self._adj[v] = self.adjlist_inner_dict_factory()
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877 self._node[v] = self.node_attr_dict_factory()
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878 # add the edge
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879 datadict = self._adj[u].get(v, self.edge_attr_dict_factory())
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880 datadict.update(attr)
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881 self._adj[u][v] = datadict
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882 self._adj[v][u] = datadict
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883
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884 def add_edges_from(self, ebunch_to_add, **attr):
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885 """Add all the edges in ebunch_to_add.
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886
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887 Parameters
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888 ----------
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889 ebunch_to_add : container of edges
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890 Each edge given in the container will be added to the
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891 graph. The edges must be given as as 2-tuples (u, v) or
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892 3-tuples (u, v, d) where d is a dictionary containing edge data.
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893 attr : keyword arguments, optional
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894 Edge data (or labels or objects) can be assigned using
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parents:
diff changeset
895 keyword arguments.
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parents:
diff changeset
896
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parents:
diff changeset
897 See Also
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parents:
diff changeset
898 --------
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parents:
diff changeset
899 add_edge : add a single edge
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shellac
parents:
diff changeset
900 add_weighted_edges_from : convenient way to add weighted edges
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parents:
diff changeset
901
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parents:
diff changeset
902 Notes
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parents:
diff changeset
903 -----
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parents:
diff changeset
904 Adding the same edge twice has no effect but any edge data
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parents:
diff changeset
905 will be updated when each duplicate edge is added.
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parents:
diff changeset
906
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parents:
diff changeset
907 Edge attributes specified in an ebunch take precedence over
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parents:
diff changeset
908 attributes specified via keyword arguments.
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parents:
diff changeset
909
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parents:
diff changeset
910 Examples
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parents:
diff changeset
911 --------
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parents:
diff changeset
912 >>> G = nx.Graph() # or DiGraph, MultiGraph, MultiDiGraph, etc
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parents:
diff changeset
913 >>> G.add_edges_from([(0, 1), (1, 2)]) # using a list of edge tuples
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parents:
diff changeset
914 >>> e = zip(range(0, 3), range(1, 4))
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parents:
diff changeset
915 >>> G.add_edges_from(e) # Add the path graph 0-1-2-3
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diff changeset
916
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parents:
diff changeset
917 Associate data to edges
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diff changeset
918
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parents:
diff changeset
919 >>> G.add_edges_from([(1, 2), (2, 3)], weight=3)
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parents:
diff changeset
920 >>> G.add_edges_from([(3, 4), (1, 4)], label="WN2898")
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diff changeset
921 """
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diff changeset
922 for e in ebunch_to_add:
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parents:
diff changeset
923 ne = len(e)
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diff changeset
924 if ne == 3:
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diff changeset
925 u, v, dd = e
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diff changeset
926 elif ne == 2:
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parents:
diff changeset
927 u, v = e
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diff changeset
928 dd = {} # doesn't need edge_attr_dict_factory
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parents:
diff changeset
929 else:
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diff changeset
930 raise NetworkXError(f"Edge tuple {e} must be a 2-tuple or 3-tuple.")
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parents:
diff changeset
931 if u not in self._node:
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parents:
diff changeset
932 self._adj[u] = self.adjlist_inner_dict_factory()
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parents:
diff changeset
933 self._node[u] = self.node_attr_dict_factory()
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shellac
parents:
diff changeset
934 if v not in self._node:
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shellac
parents:
diff changeset
935 self._adj[v] = self.adjlist_inner_dict_factory()
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parents:
diff changeset
936 self._node[v] = self.node_attr_dict_factory()
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parents:
diff changeset
937 datadict = self._adj[u].get(v, self.edge_attr_dict_factory())
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parents:
diff changeset
938 datadict.update(attr)
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parents:
diff changeset
939 datadict.update(dd)
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parents:
diff changeset
940 self._adj[u][v] = datadict
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parents:
diff changeset
941 self._adj[v][u] = datadict
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diff changeset
942
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diff changeset
943 def add_weighted_edges_from(self, ebunch_to_add, weight="weight", **attr):
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parents:
diff changeset
944 """Add weighted edges in `ebunch_to_add` with specified weight attr
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parents:
diff changeset
945
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diff changeset
946 Parameters
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parents:
diff changeset
947 ----------
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diff changeset
948 ebunch_to_add : container of edges
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parents:
diff changeset
949 Each edge given in the list or container will be added
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parents:
diff changeset
950 to the graph. The edges must be given as 3-tuples (u, v, w)
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parents:
diff changeset
951 where w is a number.
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diff changeset
952 weight : string, optional (default= 'weight')
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diff changeset
953 The attribute name for the edge weights to be added.
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parents:
diff changeset
954 attr : keyword arguments, optional (default= no attributes)
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diff changeset
955 Edge attributes to add/update for all edges.
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diff changeset
956
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957 See Also
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958 --------
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parents:
diff changeset
959 add_edge : add a single edge
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diff changeset
960 add_edges_from : add multiple edges
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diff changeset
961
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diff changeset
962 Notes
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diff changeset
963 -----
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diff changeset
964 Adding the same edge twice for Graph/DiGraph simply updates
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diff changeset
965 the edge data. For MultiGraph/MultiDiGraph, duplicate edges
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shellac
parents:
diff changeset
966 are stored.
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parents:
diff changeset
967
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parents:
diff changeset
968 Examples
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diff changeset
969 --------
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diff changeset
970 >>> G = nx.Graph() # or DiGraph, MultiGraph, MultiDiGraph, etc
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parents:
diff changeset
971 >>> G.add_weighted_edges_from([(0, 1, 3.0), (1, 2, 7.5)])
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diff changeset
972 """
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diff changeset
973 self.add_edges_from(((u, v, {weight: d}) for u, v, d in ebunch_to_add), **attr)
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diff changeset
974
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diff changeset
975 def remove_edge(self, u, v):
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parents:
diff changeset
976 """Remove the edge between u and v.
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parents:
diff changeset
977
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parents:
diff changeset
978 Parameters
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parents:
diff changeset
979 ----------
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parents:
diff changeset
980 u, v : nodes
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shellac
parents:
diff changeset
981 Remove the edge between nodes u and v.
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shellac
parents:
diff changeset
982
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parents:
diff changeset
983 Raises
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diff changeset
984 ------
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parents:
diff changeset
985 NetworkXError
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diff changeset
986 If there is not an edge between u and v.
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parents:
diff changeset
987
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parents:
diff changeset
988 See Also
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parents:
diff changeset
989 --------
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diff changeset
990 remove_edges_from : remove a collection of edges
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shellac
parents:
diff changeset
991
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parents:
diff changeset
992 Examples
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diff changeset
993 --------
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parents:
diff changeset
994 >>> G = nx.path_graph(4) # or DiGraph, etc
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shellac
parents:
diff changeset
995 >>> G.remove_edge(0, 1)
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parents:
diff changeset
996 >>> e = (1, 2)
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parents:
diff changeset
997 >>> G.remove_edge(*e) # unpacks e from an edge tuple
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parents:
diff changeset
998 >>> e = (2, 3, {"weight": 7}) # an edge with attribute data
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shellac
parents:
diff changeset
999 >>> G.remove_edge(*e[:2]) # select first part of edge tuple
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shellac
parents:
diff changeset
1000 """
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parents:
diff changeset
1001 try:
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diff changeset
1002 del self._adj[u][v]
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diff changeset
1003 if u != v: # self-loop needs only one entry removed
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parents:
diff changeset
1004 del self._adj[v][u]
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parents:
diff changeset
1005 except KeyError as e:
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diff changeset
1006 raise NetworkXError(f"The edge {u}-{v} is not in the graph") from e
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parents:
diff changeset
1007
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parents:
diff changeset
1008 def remove_edges_from(self, ebunch):
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diff changeset
1009 """Remove all edges specified in ebunch.
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parents:
diff changeset
1010
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diff changeset
1011 Parameters
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parents:
diff changeset
1012 ----------
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diff changeset
1013 ebunch: list or container of edge tuples
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diff changeset
1014 Each edge given in the list or container will be removed
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shellac
parents:
diff changeset
1015 from the graph. The edges can be:
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parents:
diff changeset
1016
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diff changeset
1017 - 2-tuples (u, v) edge between u and v.
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diff changeset
1018 - 3-tuples (u, v, k) where k is ignored.
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shellac
parents:
diff changeset
1019
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1020 See Also
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1021 --------
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1022 remove_edge : remove a single edge
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1023
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1024 Notes
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1025 -----
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1026 Will fail silently if an edge in ebunch is not in the graph.
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1027
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1028 Examples
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1029 --------
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1030 >>> G = nx.path_graph(4) # or DiGraph, MultiGraph, MultiDiGraph, etc
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1031 >>> ebunch = [(1, 2), (2, 3)]
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1032 >>> G.remove_edges_from(ebunch)
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1033 """
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1034 adj = self._adj
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1035 for e in ebunch:
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1036 u, v = e[:2] # ignore edge data if present
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1037 if u in adj and v in adj[u]:
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1038 del adj[u][v]
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1039 if u != v: # self loop needs only one entry removed
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1040 del adj[v][u]
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1041
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1042 def update(self, edges=None, nodes=None):
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1043 """Update the graph using nodes/edges/graphs as input.
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1044
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1045 Like dict.update, this method takes a graph as input, adding the
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1046 graph's nodes and edges to this graph. It can also take two inputs:
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1047 edges and nodes. Finally it can take either edges or nodes.
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1048 To specify only nodes the keyword `nodes` must be used.
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1049
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1050 The collections of edges and nodes are treated similarly to
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1051 the add_edges_from/add_nodes_from methods. When iterated, they
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1052 should yield 2-tuples (u, v) or 3-tuples (u, v, datadict).
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1053
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1054 Parameters
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1055 ----------
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1056 edges : Graph object, collection of edges, or None
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1057 The first parameter can be a graph or some edges. If it has
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1058 attributes `nodes` and `edges`, then it is taken to be a
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1059 Graph-like object and those attributes are used as collections
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1060 of nodes and edges to be added to the graph.
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1061 If the first parameter does not have those attributes, it is
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1062 treated as a collection of edges and added to the graph.
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1063 If the first argument is None, no edges are added.
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1064 nodes : collection of nodes, or None
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1065 The second parameter is treated as a collection of nodes
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1066 to be added to the graph unless it is None.
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1067 If `edges is None` and `nodes is None` an exception is raised.
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1068 If the first parameter is a Graph, then `nodes` is ignored.
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1069
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1070 Examples
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1071 --------
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1072 >>> G = nx.path_graph(5)
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1073 >>> G.update(nx.complete_graph(range(4, 10)))
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1074 >>> from itertools import combinations
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1075 >>> edges = (
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1076 ... (u, v, {"power": u * v})
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1077 ... for u, v in combinations(range(10, 20), 2)
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1078 ... if u * v < 225
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1079 ... )
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1080 >>> nodes = [1000] # for singleton, use a container
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1081 >>> G.update(edges, nodes)
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1082
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1083 Notes
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1084 -----
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1085 It you want to update the graph using an adjacency structure
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1086 it is straightforward to obtain the edges/nodes from adjacency.
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1087 The following examples provide common cases, your adjacency may
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1088 be slightly different and require tweaks of these examples.
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1089
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1090 >>> # dict-of-set/list/tuple
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1091 >>> adj = {1: {2, 3}, 2: {1, 3}, 3: {1, 2}}
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1092 >>> e = [(u, v) for u, nbrs in adj.items() for v in nbrs]
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1093 >>> G.update(edges=e, nodes=adj)
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1094
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1095 >>> DG = nx.DiGraph()
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1096 >>> # dict-of-dict-of-attribute
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1097 >>> adj = {1: {2: 1.3, 3: 0.7}, 2: {1: 1.4}, 3: {1: 0.7}}
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1098 >>> e = [
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1099 ... (u, v, {"weight": d})
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1100 ... for u, nbrs in adj.items()
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1101 ... for v, d in nbrs.items()
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1102 ... ]
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1103 >>> DG.update(edges=e, nodes=adj)
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1104
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1105 >>> # dict-of-dict-of-dict
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1106 >>> adj = {1: {2: {"weight": 1.3}, 3: {"color": 0.7, "weight": 1.2}}}
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1107 >>> e = [
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1108 ... (u, v, {"weight": d})
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1109 ... for u, nbrs in adj.items()
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1110 ... for v, d in nbrs.items()
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1111 ... ]
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1112 >>> DG.update(edges=e, nodes=adj)
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1113
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1114 >>> # predecessor adjacency (dict-of-set)
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1115 >>> pred = {1: {2, 3}, 2: {3}, 3: {3}}
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1116 >>> e = [(v, u) for u, nbrs in pred.items() for v in nbrs]
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1117
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1118 >>> # MultiGraph dict-of-dict-of-dict-of-attribute
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1119 >>> MDG = nx.MultiDiGraph()
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1120 >>> adj = {
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1121 ... 1: {2: {0: {"weight": 1.3}, 1: {"weight": 1.2}}},
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1122 ... 3: {2: {0: {"weight": 0.7}}},
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1123 ... }
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1124 >>> e = [
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1125 ... (u, v, ekey, d)
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1126 ... for u, nbrs in adj.items()
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1127 ... for v, keydict in nbrs.items()
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1128 ... for ekey, d in keydict.items()
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1129 ... ]
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1130 >>> MDG.update(edges=e)
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1131
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1132 See Also
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1133 --------
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1134 add_edges_from: add multiple edges to a graph
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1135 add_nodes_from: add multiple nodes to a graph
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1136 """
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1137 if edges is not None:
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1138 if nodes is not None:
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1139 self.add_nodes_from(nodes)
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1140 self.add_edges_from(edges)
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1141 else:
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1142 # check if edges is a Graph object
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diff changeset
1143 try:
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1144 graph_nodes = edges.nodes
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1145 graph_edges = edges.edges
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1146 except AttributeError:
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1147 # edge not Graph-like
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1148 self.add_edges_from(edges)
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1149 else: # edges is Graph-like
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1150 self.add_nodes_from(graph_nodes.data())
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1151 self.add_edges_from(graph_edges.data())
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1152 self.graph.update(edges.graph)
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1153 elif nodes is not None:
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1154 self.add_nodes_from(nodes)
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1155 else:
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1156 raise NetworkXError("update needs nodes or edges input")
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1157
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1158 def has_edge(self, u, v):
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1159 """Returns True if the edge (u, v) is in the graph.
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1160
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1161 This is the same as `v in G[u]` without KeyError exceptions.
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1162
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1163 Parameters
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1164 ----------
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1165 u, v : nodes
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1166 Nodes can be, for example, strings or numbers.
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1167 Nodes must be hashable (and not None) Python objects.
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1168
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1169 Returns
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1170 -------
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1171 edge_ind : bool
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1172 True if edge is in the graph, False otherwise.
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1173
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1174 Examples
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1175 --------
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1176 >>> G = nx.path_graph(4) # or DiGraph, MultiGraph, MultiDiGraph, etc
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1177 >>> G.has_edge(0, 1) # using two nodes
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1178 True
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1179 >>> e = (0, 1)
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1180 >>> G.has_edge(*e) # e is a 2-tuple (u, v)
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1181 True
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1182 >>> e = (0, 1, {"weight": 7})
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1183 >>> G.has_edge(*e[:2]) # e is a 3-tuple (u, v, data_dictionary)
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1184 True
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1185
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1186 The following syntax are equivalent:
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1187
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1188 >>> G.has_edge(0, 1)
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1189 True
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1190 >>> 1 in G[0] # though this gives KeyError if 0 not in G
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1191 True
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1192
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1193 """
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1194 try:
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1195 return v in self._adj[u]
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1196 except KeyError:
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1197 return False
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1198
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1199 def neighbors(self, n):
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1200 """Returns an iterator over all neighbors of node n.
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1201
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1202 This is identical to `iter(G[n])`
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1203
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1204 Parameters
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1205 ----------
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1206 n : node
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1207 A node in the graph
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1208
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1209 Returns
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1210 -------
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1211 neighbors : iterator
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1212 An iterator over all neighbors of node n
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1213
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1214 Raises
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1215 ------
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1216 NetworkXError
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1217 If the node n is not in the graph.
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1218
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1219 Examples
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1220 --------
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1221 >>> G = nx.path_graph(4) # or DiGraph, MultiGraph, MultiDiGraph, etc
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1222 >>> [n for n in G.neighbors(0)]
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1223 [1]
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1224
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1225 Notes
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1226 -----
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1227 Alternate ways to access the neighbors are ``G.adj[n]`` or ``G[n]``:
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1228
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1229 >>> G = nx.Graph() # or DiGraph, MultiGraph, MultiDiGraph, etc
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1230 >>> G.add_edge("a", "b", weight=7)
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1231 >>> G["a"]
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1232 AtlasView({'b': {'weight': 7}})
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1233 >>> G = nx.path_graph(4)
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1234 >>> [n for n in G[0]]
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1235 [1]
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1236 """
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1237 try:
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1238 return iter(self._adj[n])
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1239 except KeyError as e:
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1240 raise NetworkXError(f"The node {n} is not in the graph.") from e
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1241
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1242 @property
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1243 def edges(self):
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1244 """An EdgeView of the Graph as G.edges or G.edges().
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1245
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1246 edges(self, nbunch=None, data=False, default=None)
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1247
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1248 The EdgeView provides set-like operations on the edge-tuples
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1249 as well as edge attribute lookup. When called, it also provides
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1250 an EdgeDataView object which allows control of access to edge
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1251 attributes (but does not provide set-like operations).
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1252 Hence, `G.edges[u, v]['color']` provides the value of the color
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1253 attribute for edge `(u, v)` while
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1254 `for (u, v, c) in G.edges.data('color', default='red'):`
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1255 iterates through all the edges yielding the color attribute
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1256 with default `'red'` if no color attribute exists.
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1257
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1258 Parameters
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1259 ----------
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1260 nbunch : single node, container, or all nodes (default= all nodes)
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1261 The view will only report edges incident to these nodes.
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1262 data : string or bool, optional (default=False)
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1263 The edge attribute returned in 3-tuple (u, v, ddict[data]).
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1264 If True, return edge attribute dict in 3-tuple (u, v, ddict).
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1265 If False, return 2-tuple (u, v).
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1266 default : value, optional (default=None)
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1267 Value used for edges that don't have the requested attribute.
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1268 Only relevant if data is not True or False.
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1269
4f3585e2f14b "planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
shellac
parents:
diff changeset
1270 Returns
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1271 -------
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1272 edges : EdgeView
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1273 A view of edge attributes, usually it iterates over (u, v)
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1274 or (u, v, d) tuples of edges, but can also be used for
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1275 attribute lookup as `edges[u, v]['foo']`.
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1276
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diff changeset
1277 Notes
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1278 -----
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1279 Nodes in nbunch that are not in the graph will be (quietly) ignored.
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1280 For directed graphs this returns the out-edges.
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1281
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1282 Examples
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1283 --------
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1284 >>> G = nx.path_graph(3) # or MultiGraph, etc
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1285 >>> G.add_edge(2, 3, weight=5)
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1286 >>> [e for e in G.edges]
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1287 [(0, 1), (1, 2), (2, 3)]
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1288 >>> G.edges.data() # default data is {} (empty dict)
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1289 EdgeDataView([(0, 1, {}), (1, 2, {}), (2, 3, {'weight': 5})])
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1290 >>> G.edges.data("weight", default=1)
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1291 EdgeDataView([(0, 1, 1), (1, 2, 1), (2, 3, 5)])
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1292 >>> G.edges([0, 3]) # only edges incident to these nodes
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1293 EdgeDataView([(0, 1), (3, 2)])
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1294 >>> G.edges(0) # only edges incident to a single node (use G.adj[0]?)
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1295 EdgeDataView([(0, 1)])
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1296 """
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1297 return EdgeView(self)
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1298
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1299 def get_edge_data(self, u, v, default=None):
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1300 """Returns the attribute dictionary associated with edge (u, v).
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1301
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1302 This is identical to `G[u][v]` except the default is returned
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1303 instead of an exception if the edge doesn't exist.
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1304
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1305 Parameters
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1306 ----------
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1307 u, v : nodes
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1308 default: any Python object (default=None)
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1309 Value to return if the edge (u, v) is not found.
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1310
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1311 Returns
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1312 -------
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1313 edge_dict : dictionary
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1314 The edge attribute dictionary.
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1315
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1316 Examples
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1317 --------
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1318 >>> G = nx.path_graph(4) # or DiGraph, MultiGraph, MultiDiGraph, etc
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1319 >>> G[0][1]
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1320 {}
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1321
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1322 Warning: Assigning to `G[u][v]` is not permitted.
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1323 But it is safe to assign attributes `G[u][v]['foo']`
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1324
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1325 >>> G[0][1]["weight"] = 7
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1326 >>> G[0][1]["weight"]
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1327 7
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1328 >>> G[1][0]["weight"]
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1329 7
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1330
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1331 >>> G = nx.path_graph(4) # or DiGraph, MultiGraph, MultiDiGraph, etc
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1332 >>> G.get_edge_data(0, 1) # default edge data is {}
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1333 {}
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1334 >>> e = (0, 1)
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1335 >>> G.get_edge_data(*e) # tuple form
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1336 {}
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1337 >>> G.get_edge_data("a", "b", default=0) # edge not in graph, return 0
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1338 0
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1339 """
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1340 try:
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1341 return self._adj[u][v]
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1342 except KeyError:
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1343 return default
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1344
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1345 def adjacency(self):
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1346 """Returns an iterator over (node, adjacency dict) tuples for all nodes.
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1347
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1348 For directed graphs, only outgoing neighbors/adjacencies are included.
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1349
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1350 Returns
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1351 -------
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1352 adj_iter : iterator
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1353 An iterator over (node, adjacency dictionary) for all nodes in
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1354 the graph.
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1355
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1356 Examples
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1357 --------
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1358 >>> G = nx.path_graph(4) # or DiGraph, MultiGraph, MultiDiGraph, etc
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1359 >>> [(n, nbrdict) for n, nbrdict in G.adjacency()]
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1360 [(0, {1: {}}), (1, {0: {}, 2: {}}), (2, {1: {}, 3: {}}), (3, {2: {}})]
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1361
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1362 """
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1363 return iter(self._adj.items())
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1364
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1365 @property
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1366 def degree(self):
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1367 """A DegreeView for the Graph as G.degree or G.degree().
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1368
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1369 The node degree is the number of edges adjacent to the node.
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1370 The weighted node degree is the sum of the edge weights for
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1371 edges incident to that node.
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1372
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1373 This object provides an iterator for (node, degree) as well as
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1374 lookup for the degree for a single node.
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1375
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1376 Parameters
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1377 ----------
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1378 nbunch : single node, container, or all nodes (default= all nodes)
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1379 The view will only report edges incident to these nodes.
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1380
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1381 weight : string or None, optional (default=None)
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1382 The name of an edge attribute that holds the numerical value used
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1383 as a weight. If None, then each edge has weight 1.
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1384 The degree is the sum of the edge weights adjacent to the node.
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1385
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1386 Returns
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1387 -------
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1388 If a single node is requested
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1389 deg : int
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1390 Degree of the node
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1391
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1392 OR if multiple nodes are requested
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1393 nd_view : A DegreeView object capable of iterating (node, degree) pairs
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1394
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1395 Examples
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1396 --------
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1397 >>> G = nx.path_graph(4) # or DiGraph, MultiGraph, MultiDiGraph, etc
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1398 >>> G.degree[0] # node 0 has degree 1
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1399 1
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1400 >>> list(G.degree([0, 1, 2]))
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1401 [(0, 1), (1, 2), (2, 2)]
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1402 """
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1403 return DegreeView(self)
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1404
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1405 def clear(self):
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1406 """Remove all nodes and edges from the graph.
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1407
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1408 This also removes the name, and all graph, node, and edge attributes.
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1409
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1410 Examples
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1411 --------
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1412 >>> G = nx.path_graph(4) # or DiGraph, MultiGraph, MultiDiGraph, etc
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1413 >>> G.clear()
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1414 >>> list(G.nodes)
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1415 []
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1416 >>> list(G.edges)
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1417 []
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