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<h1>Source code for networkx.generators.ego</h1><div class="highlight"><pre>
<span class="sd">"""</span>
<span class="sd">Ego graph.</span>
<span class="sd">"""</span>
<span class="c"># Copyright (C) 2010 by </span>
<span class="c"># Aric Hagberg <hagberg@lanl.gov></span>
<span class="c"># Dan Schult <dschult@colgate.edu></span>
<span class="c"># Pieter Swart <swart@lanl.gov></span>
<span class="c"># All rights reserved.</span>
<span class="c"># BSD license.</span>
<span class="n">__author__</span> <span class="o">=</span> <span class="s">"""</span><span class="se">\n</span><span class="s">"""</span><span class="o">.</span><span class="n">join</span><span class="p">([</span><span class="s">'Drew Conway <drew.conway@nyu.edu>'</span><span class="p">,</span>
<span class="s">'Aric Hagberg <hagberg@lanl.gov>'</span><span class="p">])</span>
<span class="n">__all__</span> <span class="o">=</span> <span class="p">[</span><span class="s">'ego_graph'</span><span class="p">]</span>
<span class="kn">import</span> <span class="nn">networkx</span> <span class="kn">as</span> <span class="nn">nx</span>
<div class="viewcode-block" id="ego_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.ego.ego_graph.html#networkx.generators.ego.ego_graph">[docs]</a><span class="k">def</span> <span class="nf">ego_graph</span><span class="p">(</span><span class="n">G</span><span class="p">,</span><span class="n">n</span><span class="p">,</span><span class="n">radius</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span><span class="n">center</span><span class="o">=</span><span class="bp">True</span><span class="p">,</span><span class="n">undirected</span><span class="o">=</span><span class="bp">False</span><span class="p">,</span><span class="n">distance</span><span class="o">=</span><span class="bp">None</span><span class="p">):</span>
<span class="sd">"""Returns induced subgraph of neighbors centered at node n within</span>
<span class="sd"> a given radius.</span>
<span class="sd"> </span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> G : graph</span>
<span class="sd"> A NetworkX Graph or DiGraph</span>
<span class="sd"> n : node </span>
<span class="sd"> A single node </span>
<span class="sd"> radius : number, optional</span>
<span class="sd"> Include all neighbors of distance<=radius from n.</span>
<span class="sd"> </span>
<span class="sd"> center : bool, optional</span>
<span class="sd"> If False, do not include center node in graph </span>
<span class="sd"> undirected : bool, optional </span>
<span class="sd"> If True use both in- and out-neighbors of directed graphs.</span>
<span class="sd"> distance : key, optional </span>
<span class="sd"> Use specified edge data key as distance. For example, setting</span>
<span class="sd"> distance='weight' will use the edge weight to measure the</span>
<span class="sd"> distance from the node n.</span>
<span class="sd"> Notes</span>
<span class="sd"> -----</span>
<span class="sd"> For directed graphs D this produces the "out" neighborhood</span>
<span class="sd"> or successors. If you want the neighborhood of predecessors</span>
<span class="sd"> first reverse the graph with D.reverse(). If you want both</span>
<span class="sd"> directions use the keyword argument undirected=True.</span>
<span class="sd"> Node, edge, and graph attributes are copied to the returned subgraph.</span>
<span class="sd"> """</span>
<span class="k">if</span> <span class="n">undirected</span><span class="p">:</span>
<span class="k">if</span> <span class="n">distance</span> <span class="ow">is</span> <span class="ow">not</span> <span class="bp">None</span><span class="p">:</span>
<span class="n">sp</span><span class="p">,</span><span class="n">_</span><span class="o">=</span><span class="n">nx</span><span class="o">.</span><span class="n">single_source_dijkstra</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">to_undirected</span><span class="p">(),</span>
<span class="n">n</span><span class="p">,</span><span class="n">cutoff</span><span class="o">=</span><span class="n">radius</span><span class="p">,</span>
<span class="n">weight</span><span class="o">=</span><span class="n">distance</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">sp</span><span class="o">=</span><span class="n">nx</span><span class="o">.</span><span class="n">single_source_shortest_path_length</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">to_undirected</span><span class="p">(),</span>
<span class="n">n</span><span class="p">,</span><span class="n">cutoff</span><span class="o">=</span><span class="n">radius</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">if</span> <span class="n">distance</span> <span class="ow">is</span> <span class="ow">not</span> <span class="bp">None</span><span class="p">:</span>
<span class="n">sp</span><span class="p">,</span><span class="n">_</span><span class="o">=</span><span class="n">nx</span><span class="o">.</span><span class="n">single_source_dijkstra</span><span class="p">(</span><span class="n">G</span><span class="p">,</span>
<span class="n">n</span><span class="p">,</span><span class="n">cutoff</span><span class="o">=</span><span class="n">radius</span><span class="p">,</span>
<span class="n">weight</span><span class="o">=</span><span class="n">distance</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">sp</span><span class="o">=</span><span class="n">nx</span><span class="o">.</span><span class="n">single_source_shortest_path_length</span><span class="p">(</span><span class="n">G</span><span class="p">,</span><span class="n">n</span><span class="p">,</span><span class="n">cutoff</span><span class="o">=</span><span class="n">radius</span><span class="p">)</span>
<span class="n">H</span><span class="o">=</span><span class="n">G</span><span class="o">.</span><span class="n">subgraph</span><span class="p">(</span><span class="n">sp</span><span class="p">)</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>
<span class="k">if</span> <span class="ow">not</span> <span class="n">center</span><span class="p">:</span>
<span class="n">H</span><span class="o">.</span><span class="n">remove_node</span><span class="p">(</span><span class="n">n</span><span class="p">)</span>
<span class="k">return</span> <span class="n">H</span></div>
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