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<div class="section" id="module-altgraph.GraphUtil">
<span id="altgraph-graphutil-utility-functions"></span><h1><a class="reference internal" href="#module-altgraph.GraphUtil" title="altgraph.GraphUtil: Utility functions"><tt class="xref py py-mod docutils literal"><span class="pre">altgraph.GraphUtil</span></tt></a> — Utility functions<a class="headerlink" href="#module-altgraph.GraphUtil" title="Permalink to this headline">¶</a></h1>
<p>The module <a class="reference internal" href="#module-altgraph.GraphUtil" title="altgraph.GraphUtil: Utility functions"><tt class="xref py py-mod docutils literal"><span class="pre">altgraph.GraphUtil</span></tt></a> performs a number of more
or less useful utility functions.</p>
<dl class="function">
<dt id="altgraph.GraphUtil.generate_random_graph">
<tt class="descclassname">altgraph.GraphUtil.</tt><tt class="descname">generate_random_graph</tt><big>(</big><em>node_num, edge_num[, self_loops[, multi_edges]</em><big>)</big><a class="headerlink" href="#altgraph.GraphUtil.generate_random_graph" title="Permalink to this definition">¶</a></dt>
<dd><p>Generates and returns a <a class="reference internal" href="graph.html#altgraph.Graph.Graph" title="altgraph.Graph.Graph"><tt class="xref py py-class docutils literal"><span class="pre">Graph</span></tt></a> instance
with <em>node_num</em> nodes randomly connected by <em>edge_num</em> edges.</p>
<p>When <em>self_loops</em> is present and True there can be edges that point from
a node to itself.</p>
<p>When <em>multi_edge</em> is present and True there can be duplicate edges.</p>
<p>This method raises <tt class="xref py py-class docutils literal"><span class="pre">GraphError</span> <span class="pre"><altgraph.GraphError</span></tt> when
a graph with the requested configuration cannot be created.</p>
</dd></dl>
<dl class="function">
<dt id="altgraph.GraphUtil.generate_scale_free_graph">
<tt class="descclassname">altgraph.GraphUtil.</tt><tt class="descname">generate_scale_free_graph</tt><big>(</big><em>steps</em>, <em>growth_num</em><span class="optional">[</span>, <em>self_loops</em><span class="optional">[</span>, <em>multi_edges</em><span class="optional">]</span><span class="optional">]</span><big>)</big><a class="headerlink" href="#altgraph.GraphUtil.generate_scale_free_graph" title="Permalink to this definition">¶</a></dt>
<dd><p>Generates and returns a <a class="reference internal" href="graph.html#altgraph.Graph.Graph" title="altgraph.Graph.Graph"><tt class="xref py py-class docutils literal"><span class="pre">Graph</span></tt></a> instance that
will have <em>steps*growth_n um</em> nodes and a scale free (powerlaw)
connectivity.</p>
<p>Starting with a fully connected graph with <em>growth_num</em> nodes
at every step <em>growth_num</em> nodes are added to the graph and are connected
to existing nodes with a probability proportional to the degree of these
existing nodes.</p>
<div class="admonition warning">
<p class="first admonition-title">Warning</p>
<p class="last">The current implementation is basically untested, although
code inspection seems to indicate an implementation that is consistent
with the description at
<a class="reference external" href="http://mathworld.wolfram.com/Scale-FreeNetwork.html">Wolfram MathWorld</a></p>
</div>
</dd></dl>
<dl class="function">
<dt id="altgraph.GraphUtil.filter_stack">
<tt class="descclassname">altgraph.GraphUtil.</tt><tt class="descname">filter_stack</tt><big>(</big><em>graph</em>, <em>head</em>, <em>filters</em><big>)</big><a class="headerlink" href="#altgraph.GraphUtil.filter_stack" title="Permalink to this definition">¶</a></dt>
<dd><p>Perform a depth-first oder walk of the graph starting at <em>head</em> and
apply all filter functions in <em>filters</em> on the node data of the nodes
found.</p>
<p>Returns (<em>visited</em>, <em>removes</em>, <em>orphans</em>), where</p>
<ul class="simple">
<li><em>visited</em>: the set of visited nodes</li>
<li><em>removes</em>: the list of nodes where the node data doesn’t match
all <em>filters</em>.</li>
<li><em>orphans</em>: list of tuples (<em>last_good</em>, <em>node</em>), where
node is not in <em>removes</em> and one of the nodes that is connected
by an incoming edge is in <em>removes</em>. <em>Last_good</em> is the
closest upstream node that is not in <em>removes</em>.</li>
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