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<h1>Source code for networkx.drawing.nx_pylab</h1><div class="highlight"><pre>
<span class="sd">"""</span>
<span class="sd">**********</span>
<span class="sd">Matplotlib</span>
<span class="sd">**********</span>
<span class="sd">Draw networks with matplotlib.</span>
<span class="sd">See Also</span>
<span class="sd">--------</span>
<span class="sd">matplotlib: http://matplotlib.sourceforge.net/</span>
<span class="sd">pygraphviz: http://networkx.lanl.gov/pygraphviz/</span>
<span class="sd">"""</span>
<span class="c"># Copyright (C) 2004-2012 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="kn">import</span> <span class="nn">networkx</span> <span class="kn">as</span> <span class="nn">nx</span>
<span class="kn">from</span> <span class="nn">networkx.drawing.layout</span> <span class="kn">import</span> <span class="n">shell_layout</span><span class="p">,</span>\
<span class="n">circular_layout</span><span class="p">,</span><span class="n">spectral_layout</span><span class="p">,</span><span class="n">spring_layout</span><span class="p">,</span><span class="n">random_layout</span>
<span class="n">__author__</span> <span class="o">=</span> <span class="s">"""Aric Hagberg (hagberg@lanl.gov)"""</span>
<span class="n">__all__</span> <span class="o">=</span> <span class="p">[</span><span class="s">'draw'</span><span class="p">,</span>
<span class="s">'draw_networkx'</span><span class="p">,</span>
<span class="s">'draw_networkx_nodes'</span><span class="p">,</span>
<span class="s">'draw_networkx_edges'</span><span class="p">,</span>
<span class="s">'draw_networkx_labels'</span><span class="p">,</span>
<span class="s">'draw_networkx_edge_labels'</span><span class="p">,</span>
<span class="s">'draw_circular'</span><span class="p">,</span>
<span class="s">'draw_random'</span><span class="p">,</span>
<span class="s">'draw_spectral'</span><span class="p">,</span>
<span class="s">'draw_spring'</span><span class="p">,</span>
<span class="s">'draw_shell'</span><span class="p">,</span>
<span class="s">'draw_graphviz'</span><span class="p">]</span>
<div class="viewcode-block" id="draw"><a class="viewcode-back" href="../../../reference/generated/networkx.drawing.nx_pylab.draw.html#networkx.drawing.nx_pylab.draw">[docs]</a><span class="k">def</span> <span class="nf">draw</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">pos</span><span class="o">=</span><span class="bp">None</span><span class="p">,</span> <span class="n">ax</span><span class="o">=</span><span class="bp">None</span><span class="p">,</span> <span class="n">hold</span><span class="o">=</span><span class="bp">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwds</span><span class="p">):</span>
<span class="sd">"""Draw the graph G with Matplotlib.</span>
<span class="sd"> Draw the graph as a simple representation with no node</span>
<span class="sd"> labels or edge labels and using the full Matplotlib figure area</span>
<span class="sd"> and no axis labels by default. See draw_networkx() for more</span>
<span class="sd"> full-featured drawing that allows title, axis labels etc.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> G : graph</span>
<span class="sd"> A networkx graph</span>
<span class="sd"> pos : dictionary, optional</span>
<span class="sd"> A dictionary with nodes as keys and positions as values.</span>
<span class="sd"> If not specified a spring layout positioning will be computed.</span>
<span class="sd"> See networkx.layout for functions that compute node positions.</span>
<span class="sd"> ax : Matplotlib Axes object, optional</span>
<span class="sd"> Draw the graph in specified Matplotlib axes.</span>
<span class="sd"> hold : bool, optional</span>
<span class="sd"> Set the Matplotlib hold state. If True subsequent draw</span>
<span class="sd"> commands will be added to the current axes.</span>
<span class="sd"> **kwds : optional keywords</span>
<span class="sd"> See networkx.draw_networkx() for a description of optional keywords.</span>
<span class="sd"> Examples</span>
<span class="sd"> --------</span>
<span class="sd"> >>> G=nx.dodecahedral_graph()</span>
<span class="sd"> >>> nx.draw(G)</span>
<span class="sd"> >>> nx.draw(G,pos=nx.spring_layout(G)) # use spring layout</span>
<span class="sd"> See Also</span>
<span class="sd"> --------</span>
<span class="sd"> draw_networkx()</span>
<span class="sd"> draw_networkx_nodes()</span>
<span class="sd"> draw_networkx_edges()</span>
<span class="sd"> draw_networkx_labels()</span>
<span class="sd"> draw_networkx_edge_labels()</span>
<span class="sd"> Notes</span>
<span class="sd"> -----</span>
<span class="sd"> This function has the same name as pylab.draw and pyplot.draw</span>
<span class="sd"> so beware when using</span>
<span class="sd"> >>> from networkx import *</span>
<span class="sd"> since you might overwrite the pylab.draw function.</span>
<span class="sd"> With pyplot use</span>
<span class="sd"> >>> import matplotlib.pyplot as plt</span>
<span class="sd"> >>> import networkx as nx</span>
<span class="sd"> >>> G=nx.dodecahedral_graph()</span>
<span class="sd"> >>> nx.draw(G) # networkx draw()</span>
<span class="sd"> >>> plt.draw() # pyplot draw()</span>
<span class="sd"> Also see the NetworkX drawing examples at</span>
<span class="sd"> http://networkx.lanl.gov/gallery.html</span>
<span class="sd"> """</span>
<span class="k">try</span><span class="p">:</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="kn">as</span> <span class="nn">plt</span>
<span class="k">except</span> <span class="ne">ImportError</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">ImportError</span><span class="p">(</span><span class="s">"Matplotlib required for draw()"</span><span class="p">)</span>
<span class="k">except</span> <span class="ne">RuntimeError</span><span class="p">:</span>
<span class="k">print</span><span class="p">(</span><span class="s">"Matplotlib unable to open display"</span><span class="p">)</span>
<span class="k">raise</span>
<span class="k">if</span> <span class="n">ax</span> <span class="ow">is</span> <span class="bp">None</span><span class="p">:</span>
<span class="n">cf</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">gcf</span><span class="p">()</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">cf</span> <span class="o">=</span> <span class="n">ax</span><span class="o">.</span><span class="n">get_figure</span><span class="p">()</span>
<span class="n">cf</span><span class="o">.</span><span class="n">set_facecolor</span><span class="p">(</span><span class="s">'w'</span><span class="p">)</span>
<span class="k">if</span> <span class="n">ax</span> <span class="ow">is</span> <span class="bp">None</span><span class="p">:</span>
<span class="k">if</span> <span class="n">cf</span><span class="o">.</span><span class="n">_axstack</span><span class="p">()</span> <span class="ow">is</span> <span class="bp">None</span><span class="p">:</span>
<span class="n">ax</span><span class="o">=</span><span class="n">cf</span><span class="o">.</span><span class="n">add_axes</span><span class="p">((</span><span class="mi">0</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">))</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">ax</span><span class="o">=</span><span class="n">cf</span><span class="o">.</span><span class="n">gca</span><span class="p">()</span>
<span class="c"># allow callers to override the hold state by passing hold=True|False</span>
<span class="n">b</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">ishold</span><span class="p">()</span>
<span class="n">h</span> <span class="o">=</span> <span class="n">kwds</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s">'hold'</span><span class="p">,</span> <span class="bp">None</span><span class="p">)</span>
<span class="k">if</span> <span class="n">h</span> <span class="ow">is</span> <span class="ow">not</span> <span class="bp">None</span><span class="p">:</span>
<span class="n">plt</span><span class="o">.</span><span class="n">hold</span><span class="p">(</span><span class="n">h</span><span class="p">)</span>
<span class="k">try</span><span class="p">:</span>
<span class="n">draw_networkx</span><span class="p">(</span><span class="n">G</span><span class="p">,</span><span class="n">pos</span><span class="o">=</span><span class="n">pos</span><span class="p">,</span><span class="n">ax</span><span class="o">=</span><span class="n">ax</span><span class="p">,</span><span class="o">**</span><span class="n">kwds</span><span class="p">)</span>
<span class="n">ax</span><span class="o">.</span><span class="n">set_axis_off</span><span class="p">()</span>
<span class="n">plt</span><span class="o">.</span><span class="n">draw_if_interactive</span><span class="p">()</span>
<span class="k">except</span><span class="p">:</span>
<span class="n">plt</span><span class="o">.</span><span class="n">hold</span><span class="p">(</span><span class="n">b</span><span class="p">)</span>
<span class="k">raise</span>
<span class="n">plt</span><span class="o">.</span><span class="n">hold</span><span class="p">(</span><span class="n">b</span><span class="p">)</span>
<span class="k">return</span>
</div>
<div class="viewcode-block" id="draw_networkx"><a class="viewcode-back" href="../../../reference/generated/networkx.drawing.nx_pylab.draw_networkx.html#networkx.drawing.nx_pylab.draw_networkx">[docs]</a><span class="k">def</span> <span class="nf">draw_networkx</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">pos</span><span class="o">=</span><span class="bp">None</span><span class="p">,</span> <span class="n">with_labels</span><span class="o">=</span><span class="bp">True</span><span class="p">,</span> <span class="o">**</span><span class="n">kwds</span><span class="p">):</span>
<span class="sd">"""Draw the graph G using Matplotlib.</span>
<span class="sd"> Draw the graph with Matplotlib with options for node positions,</span>
<span class="sd"> labeling, titles, and many other drawing features.</span>
<span class="sd"> See draw() for simple drawing without labels or axes.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> G : graph</span>
<span class="sd"> A networkx graph</span>
<span class="sd"> pos : dictionary, optional</span>
<span class="sd"> A dictionary with nodes as keys and positions as values.</span>
<span class="sd"> If not specified a spring layout positioning will be computed.</span>
<span class="sd"> See networkx.layout for functions that compute node positions.</span>
<span class="sd"> with_labels : bool, optional (default=True)</span>
<span class="sd"> Set to True to draw labels on the nodes.</span>
<span class="sd"> ax : Matplotlib Axes object, optional</span>
<span class="sd"> Draw the graph in the specified Matplotlib axes.</span>
<span class="sd"> nodelist : list, optional (default G.nodes())</span>
<span class="sd"> Draw only specified nodes</span>
<span class="sd"> edgelist : list, optional (default=G.edges())</span>
<span class="sd"> Draw only specified edges</span>
<span class="sd"> node_size : scalar or array, optional (default=300)</span>
<span class="sd"> Size of nodes. If an array is specified it must be the</span>
<span class="sd"> same length as nodelist.</span>
<span class="sd"> node_color : color string, or array of floats, (default='r')</span>
<span class="sd"> Node color. Can be a single color format string,</span>
<span class="sd"> or a sequence of colors with the same length as nodelist.</span>
<span class="sd"> If numeric values are specified they will be mapped to</span>
<span class="sd"> colors using the cmap and vmin,vmax parameters. See</span>
<span class="sd"> matplotlib.scatter for more details.</span>
<span class="sd"> node_shape : string, optional (default='o')</span>
<span class="sd"> The shape of the node. Specification is as matplotlib.scatter</span>
<span class="sd"> marker, one of 'so^>v<dph8'.</span>
<span class="sd"> alpha : float, optional (default=1.0)</span>
<span class="sd"> The node transparency</span>
<span class="sd"> cmap : Matplotlib colormap, optional (default=None)</span>
<span class="sd"> Colormap for mapping intensities of nodes</span>
<span class="sd"> vmin,vmax : float, optional (default=None)</span>
<span class="sd"> Minimum and maximum for node colormap scaling</span>
<span class="sd"> linewidths : [None | scalar | sequence]</span>
<span class="sd"> Line width of symbol border (default =1.0)</span>
<span class="sd"> width : float, optional (default=1.0)</span>
<span class="sd"> Line width of edges</span>
<span class="sd"> edge_color : color string, or array of floats (default='r')</span>
<span class="sd"> Edge color. Can be a single color format string,</span>
<span class="sd"> or a sequence of colors with the same length as edgelist.</span>
<span class="sd"> If numeric values are specified they will be mapped to</span>
<span class="sd"> colors using the edge_cmap and edge_vmin,edge_vmax parameters.</span>
<span class="sd"> edge_ cmap : Matplotlib colormap, optional (default=None)</span>
<span class="sd"> Colormap for mapping intensities of edges</span>
<span class="sd"> edge_vmin,edge_vmax : floats, optional (default=None)</span>
<span class="sd"> Minimum and maximum for edge colormap scaling</span>
<span class="sd"> style : string, optional (default='solid')</span>
<span class="sd"> Edge line style (solid|dashed|dotted,dashdot)</span>
<span class="sd"> labels : dictionary, optional (default=None)</span>
<span class="sd"> Node labels in a dictionary keyed by node of text labels</span>
<span class="sd"> font_size : int, optional (default=12)</span>
<span class="sd"> Font size for text labels</span>
<span class="sd"> font_color : string, optional (default='k' black)</span>
<span class="sd"> Font color string</span>
<span class="sd"> font_weight : string, optional (default='normal')</span>
<span class="sd"> Font weight</span>
<span class="sd"> font_family : string, optional (default='sans-serif')</span>
<span class="sd"> Font family</span>
<span class="sd"> label : string, optional</span>
<span class="sd"> Label for graph legend</span>
<span class="sd"> Examples</span>
<span class="sd"> --------</span>
<span class="sd"> >>> G=nx.dodecahedral_graph()</span>
<span class="sd"> >>> nx.draw(G)</span>
<span class="sd"> >>> nx.draw(G,pos=nx.spring_layout(G)) # use spring layout</span>
<span class="sd"> >>> import matplotlib.pyplot as plt</span>
<span class="sd"> >>> limits=plt.axis('off') # turn of axis</span>
<span class="sd"> Also see the NetworkX drawing examples at</span>
<span class="sd"> http://networkx.lanl.gov/gallery.html</span>
<span class="sd"> See Also</span>
<span class="sd"> --------</span>
<span class="sd"> draw()</span>
<span class="sd"> draw_networkx_nodes()</span>
<span class="sd"> draw_networkx_edges()</span>
<span class="sd"> draw_networkx_labels()</span>
<span class="sd"> draw_networkx_edge_labels()</span>
<span class="sd"> """</span>
<span class="k">try</span><span class="p">:</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="kn">as</span> <span class="nn">plt</span>
<span class="k">except</span> <span class="ne">ImportError</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">ImportError</span><span class="p">(</span><span class="s">"Matplotlib required for draw()"</span><span class="p">)</span>
<span class="k">except</span> <span class="ne">RuntimeError</span><span class="p">:</span>
<span class="k">print</span><span class="p">(</span><span class="s">"Matplotlib unable to open display"</span><span class="p">)</span>
<span class="k">raise</span>
<span class="k">if</span> <span class="n">pos</span> <span class="ow">is</span> <span class="bp">None</span><span class="p">:</span>
<span class="n">pos</span><span class="o">=</span><span class="n">nx</span><span class="o">.</span><span class="n">drawing</span><span class="o">.</span><span class="n">spring_layout</span><span class="p">(</span><span class="n">G</span><span class="p">)</span> <span class="c"># default to spring layout</span>
<span class="n">node_collection</span><span class="o">=</span><span class="n">draw_networkx_nodes</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">pos</span><span class="p">,</span> <span class="o">**</span><span class="n">kwds</span><span class="p">)</span>
<span class="n">edge_collection</span><span class="o">=</span><span class="n">draw_networkx_edges</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">pos</span><span class="p">,</span> <span class="o">**</span><span class="n">kwds</span><span class="p">)</span>
<span class="k">if</span> <span class="n">with_labels</span><span class="p">:</span>
<span class="n">draw_networkx_labels</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">pos</span><span class="p">,</span> <span class="o">**</span><span class="n">kwds</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">draw_if_interactive</span><span class="p">()</span>
</div>
<div class="viewcode-block" id="draw_networkx_nodes"><a class="viewcode-back" href="../../../reference/generated/networkx.drawing.nx_pylab.draw_networkx_nodes.html#networkx.drawing.nx_pylab.draw_networkx_nodes">[docs]</a><span class="k">def</span> <span class="nf">draw_networkx_nodes</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">pos</span><span class="p">,</span>
<span class="n">nodelist</span><span class="o">=</span><span class="bp">None</span><span class="p">,</span>
<span class="n">node_size</span><span class="o">=</span><span class="mi">300</span><span class="p">,</span>
<span class="n">node_color</span><span class="o">=</span><span class="s">'r'</span><span class="p">,</span>
<span class="n">node_shape</span><span class="o">=</span><span class="s">'o'</span><span class="p">,</span>
<span class="n">alpha</span><span class="o">=</span><span class="mf">1.0</span><span class="p">,</span>
<span class="n">cmap</span><span class="o">=</span><span class="bp">None</span><span class="p">,</span>
<span class="n">vmin</span><span class="o">=</span><span class="bp">None</span><span class="p">,</span>
<span class="n">vmax</span><span class="o">=</span><span class="bp">None</span><span class="p">,</span>
<span class="n">ax</span><span class="o">=</span><span class="bp">None</span><span class="p">,</span>
<span class="n">linewidths</span><span class="o">=</span><span class="bp">None</span><span class="p">,</span>
<span class="n">label</span> <span class="o">=</span> <span class="bp">None</span><span class="p">,</span>
<span class="o">**</span><span class="n">kwds</span><span class="p">):</span>
<span class="sd">"""Draw the nodes of the graph G.</span>
<span class="sd"> This draws only the nodes of the graph G.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> G : graph</span>
<span class="sd"> A networkx graph</span>
<span class="sd"> pos : dictionary</span>
<span class="sd"> A dictionary with nodes as keys and positions as values.</span>
<span class="sd"> If not specified a spring layout positioning will be computed.</span>
<span class="sd"> See networkx.layout for functions that compute node positions.</span>
<span class="sd"> ax : Matplotlib Axes object, optional</span>
<span class="sd"> Draw the graph in the specified Matplotlib axes.</span>
<span class="sd"> nodelist : list, optional</span>
<span class="sd"> Draw only specified nodes (default G.nodes())</span>
<span class="sd"> node_size : scalar or array</span>
<span class="sd"> Size of nodes (default=300). If an array is specified it must be the</span>
<span class="sd"> same length as nodelist.</span>
<span class="sd"> node_color : color string, or array of floats</span>
<span class="sd"> Node color. Can be a single color format string (default='r'),</span>
<span class="sd"> or a sequence of colors with the same length as nodelist.</span>
<span class="sd"> If numeric values are specified they will be mapped to</span>
<span class="sd"> colors using the cmap and vmin,vmax parameters. See</span>
<span class="sd"> matplotlib.scatter for more details.</span>
<span class="sd"> node_shape : string</span>
<span class="sd"> The shape of the node. Specification is as matplotlib.scatter</span>
<span class="sd"> marker, one of 'so^>v<dph8' (default='o').</span>
<span class="sd"> alpha : float</span>
<span class="sd"> The node transparency (default=1.0)</span>
<span class="sd"> cmap : Matplotlib colormap</span>
<span class="sd"> Colormap for mapping intensities of nodes (default=None)</span>
<span class="sd"> vmin,vmax : floats</span>
<span class="sd"> Minimum and maximum for node colormap scaling (default=None)</span>
<span class="sd"> linewidths : [None | scalar | sequence]</span>
<span class="sd"> Line width of symbol border (default =1.0)</span>
<span class="sd"> label : [None| string]</span>
<span class="sd"> Label for legend</span>
<span class="sd"> Examples</span>
<span class="sd"> --------</span>
<span class="sd"> >>> G=nx.dodecahedral_graph()</span>
<span class="sd"> >>> nodes=nx.draw_networkx_nodes(G,pos=nx.spring_layout(G))</span>
<span class="sd"> Also see the NetworkX drawing examples at</span>
<span class="sd"> http://networkx.lanl.gov/gallery.html</span>
<span class="sd"> See Also</span>
<span class="sd"> --------</span>
<span class="sd"> draw()</span>
<span class="sd"> draw_networkx()</span>
<span class="sd"> draw_networkx_edges()</span>
<span class="sd"> draw_networkx_labels()</span>
<span class="sd"> draw_networkx_edge_labels()</span>
<span class="sd"> """</span>
<span class="k">try</span><span class="p">:</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="kn">as</span> <span class="nn">plt</span>
<span class="kn">import</span> <span class="nn">numpy</span>
<span class="k">except</span> <span class="ne">ImportError</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">ImportError</span><span class="p">(</span><span class="s">"Matplotlib required for draw()"</span><span class="p">)</span>
<span class="k">except</span> <span class="ne">RuntimeError</span><span class="p">:</span>
<span class="k">print</span><span class="p">(</span><span class="s">"Matplotlib unable to open display"</span><span class="p">)</span>
<span class="k">raise</span>
<span class="k">if</span> <span class="n">ax</span> <span class="ow">is</span> <span class="bp">None</span><span class="p">:</span>
<span class="n">ax</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">gca</span><span class="p">()</span>
<span class="k">if</span> <span class="n">nodelist</span> <span class="ow">is</span> <span class="bp">None</span><span class="p">:</span>
<span class="n">nodelist</span><span class="o">=</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">()</span>
<span class="k">if</span> <span class="ow">not</span> <span class="n">nodelist</span> <span class="ow">or</span> <span class="nb">len</span><span class="p">(</span><span class="n">nodelist</span><span class="p">)</span><span class="o">==</span><span class="mi">0</span><span class="p">:</span> <span class="c"># empty nodelist, no drawing</span>
<span class="k">return</span> <span class="bp">None</span>
<span class="k">try</span><span class="p">:</span>
<span class="n">xy</span><span class="o">=</span><span class="n">numpy</span><span class="o">.</span><span class="n">asarray</span><span class="p">([</span><span class="n">pos</span><span class="p">[</span><span class="n">v</span><span class="p">]</span> <span class="k">for</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">nodelist</span><span class="p">])</span>
<span class="k">except</span> <span class="ne">KeyError</span> <span class="k">as</span> <span class="n">e</span><span class="p">:</span>
<span class="k">raise</span> <span class="n">nx</span><span class="o">.</span><span class="n">NetworkXError</span><span class="p">(</span><span class="s">'Node </span><span class="si">%s</span><span class="s"> has no position.'</span><span class="o">%</span><span class="n">e</span><span class="p">)</span>
<span class="k">except</span> <span class="ne">ValueError</span><span class="p">:</span>
<span class="k">raise</span> <span class="n">nx</span><span class="o">.</span><span class="n">NetworkXError</span><span class="p">(</span><span class="s">'Bad value in node positions.'</span><span class="p">)</span>
<span class="n">node_collection</span><span class="o">=</span><span class="n">ax</span><span class="o">.</span><span class="n">scatter</span><span class="p">(</span><span class="n">xy</span><span class="p">[:,</span><span class="mi">0</span><span class="p">],</span> <span class="n">xy</span><span class="p">[:,</span><span class="mi">1</span><span class="p">],</span>
<span class="n">s</span><span class="o">=</span><span class="n">node_size</span><span class="p">,</span>
<span class="n">c</span><span class="o">=</span><span class="n">node_color</span><span class="p">,</span>
<span class="n">marker</span><span class="o">=</span><span class="n">node_shape</span><span class="p">,</span>
<span class="n">cmap</span><span class="o">=</span><span class="n">cmap</span><span class="p">,</span>
<span class="n">vmin</span><span class="o">=</span><span class="n">vmin</span><span class="p">,</span>
<span class="n">vmax</span><span class="o">=</span><span class="n">vmax</span><span class="p">,</span>
<span class="n">alpha</span><span class="o">=</span><span class="n">alpha</span><span class="p">,</span>
<span class="n">linewidths</span><span class="o">=</span><span class="n">linewidths</span><span class="p">,</span>
<span class="n">label</span><span class="o">=</span><span class="n">label</span><span class="p">)</span>
<span class="n">node_collection</span><span class="o">.</span><span class="n">set_zorder</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span>
<span class="k">return</span> <span class="n">node_collection</span>
</div>
<div class="viewcode-block" id="draw_networkx_edges"><a class="viewcode-back" href="../../../reference/generated/networkx.drawing.nx_pylab.draw_networkx_edges.html#networkx.drawing.nx_pylab.draw_networkx_edges">[docs]</a><span class="k">def</span> <span class="nf">draw_networkx_edges</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">pos</span><span class="p">,</span>
<span class="n">edgelist</span><span class="o">=</span><span class="bp">None</span><span class="p">,</span>
<span class="n">width</span><span class="o">=</span><span class="mf">1.0</span><span class="p">,</span>
<span class="n">edge_color</span><span class="o">=</span><span class="s">'k'</span><span class="p">,</span>
<span class="n">style</span><span class="o">=</span><span class="s">'solid'</span><span class="p">,</span>
<span class="n">alpha</span><span class="o">=</span><span class="bp">None</span><span class="p">,</span>
<span class="n">edge_cmap</span><span class="o">=</span><span class="bp">None</span><span class="p">,</span>
<span class="n">edge_vmin</span><span class="o">=</span><span class="bp">None</span><span class="p">,</span>
<span class="n">edge_vmax</span><span class="o">=</span><span class="bp">None</span><span class="p">,</span>
<span class="n">ax</span><span class="o">=</span><span class="bp">None</span><span class="p">,</span>
<span class="n">arrows</span><span class="o">=</span><span class="bp">True</span><span class="p">,</span>
<span class="n">label</span><span class="o">=</span><span class="bp">None</span><span class="p">,</span>
<span class="o">**</span><span class="n">kwds</span><span class="p">):</span>
<span class="sd">"""Draw the edges of the graph G.</span>
<span class="sd"> This draws only the edges of the graph G.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> G : graph</span>
<span class="sd"> A networkx graph</span>
<span class="sd"> pos : dictionary</span>
<span class="sd"> A dictionary with nodes as keys and positions as values.</span>
<span class="sd"> If not specified a spring layout positioning will be computed.</span>
<span class="sd"> See networkx.layout for functions that compute node positions.</span>
<span class="sd"> edgelist : collection of edge tuples</span>
<span class="sd"> Draw only specified edges(default=G.edges())</span>
<span class="sd"> width : float</span>
<span class="sd"> Line width of edges (default =1.0)</span>
<span class="sd"> edge_color : color string, or array of floats</span>
<span class="sd"> Edge color. Can be a single color format string (default='r'),</span>
<span class="sd"> or a sequence of colors with the same length as edgelist.</span>
<span class="sd"> If numeric values are specified they will be mapped to</span>
<span class="sd"> colors using the edge_cmap and edge_vmin,edge_vmax parameters.</span>
<span class="sd"> style : string</span>
<span class="sd"> Edge line style (default='solid') (solid|dashed|dotted,dashdot)</span>
<span class="sd"> alpha : float</span>
<span class="sd"> The edge transparency (default=1.0)</span>
<span class="sd"> edge_ cmap : Matplotlib colormap</span>
<span class="sd"> Colormap for mapping intensities of edges (default=None)</span>
<span class="sd"> edge_vmin,edge_vmax : floats</span>
<span class="sd"> Minimum and maximum for edge colormap scaling (default=None)</span>
<span class="sd"> ax : Matplotlib Axes object, optional</span>
<span class="sd"> Draw the graph in the specified Matplotlib axes.</span>
<span class="sd"> arrows : bool, optional (default=True)</span>
<span class="sd"> For directed graphs, if True draw arrowheads.</span>
<span class="sd"> label : [None| string]</span>
<span class="sd"> Label for legend</span>
<span class="sd"> Notes</span>
<span class="sd"> -----</span>
<span class="sd"> For directed graphs, "arrows" (actually just thicker stubs) are drawn</span>
<span class="sd"> at the head end. Arrows can be turned off with keyword arrows=False.</span>
<span class="sd"> Yes, it is ugly but drawing proper arrows with Matplotlib this</span>
<span class="sd"> way is tricky.</span>
<span class="sd"> Examples</span>
<span class="sd"> --------</span>
<span class="sd"> >>> G=nx.dodecahedral_graph()</span>
<span class="sd"> >>> edges=nx.draw_networkx_edges(G,pos=nx.spring_layout(G))</span>
<span class="sd"> Also see the NetworkX drawing examples at</span>
<span class="sd"> http://networkx.lanl.gov/gallery.html</span>
<span class="sd"> See Also</span>
<span class="sd"> --------</span>
<span class="sd"> draw()</span>
<span class="sd"> draw_networkx()</span>
<span class="sd"> draw_networkx_nodes()</span>
<span class="sd"> draw_networkx_labels()</span>
<span class="sd"> draw_networkx_edge_labels()</span>
<span class="sd"> """</span>
<span class="k">try</span><span class="p">:</span>
<span class="kn">import</span> <span class="nn">matplotlib</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="kn">as</span> <span class="nn">plt</span>
<span class="kn">import</span> <span class="nn">matplotlib.cbook</span> <span class="kn">as</span> <span class="nn">cb</span>
<span class="kn">from</span> <span class="nn">matplotlib.colors</span> <span class="kn">import</span> <span class="n">colorConverter</span><span class="p">,</span><span class="n">Colormap</span>
<span class="kn">from</span> <span class="nn">matplotlib.collections</span> <span class="kn">import</span> <span class="n">LineCollection</span>
<span class="kn">import</span> <span class="nn">numpy</span>
<span class="k">except</span> <span class="ne">ImportError</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">ImportError</span><span class="p">(</span><span class="s">"Matplotlib required for draw()"</span><span class="p">)</span>
<span class="k">except</span> <span class="ne">RuntimeError</span><span class="p">:</span>
<span class="k">print</span><span class="p">(</span><span class="s">"Matplotlib unable to open display"</span><span class="p">)</span>
<span class="k">raise</span>
<span class="k">if</span> <span class="n">ax</span> <span class="ow">is</span> <span class="bp">None</span><span class="p">:</span>
<span class="n">ax</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">gca</span><span class="p">()</span>
<span class="k">if</span> <span class="n">edgelist</span> <span class="ow">is</span> <span class="bp">None</span><span class="p">:</span>
<span class="n">edgelist</span><span class="o">=</span><span class="n">G</span><span class="o">.</span><span class="n">edges</span><span class="p">()</span>
<span class="k">if</span> <span class="ow">not</span> <span class="n">edgelist</span> <span class="ow">or</span> <span class="nb">len</span><span class="p">(</span><span class="n">edgelist</span><span class="p">)</span><span class="o">==</span><span class="mi">0</span><span class="p">:</span> <span class="c"># no edges!</span>
<span class="k">return</span> <span class="bp">None</span>
<span class="c"># set edge positions</span>
<span class="n">edge_pos</span><span class="o">=</span><span class="n">numpy</span><span class="o">.</span><span class="n">asarray</span><span class="p">([(</span><span class="n">pos</span><span class="p">[</span><span class="n">e</span><span class="p">[</span><span class="mi">0</span><span class="p">]],</span><span class="n">pos</span><span class="p">[</span><span class="n">e</span><span class="p">[</span><span class="mi">1</span><span class="p">]])</span> <span class="k">for</span> <span class="n">e</span> <span class="ow">in</span> <span class="n">edgelist</span><span class="p">])</span>
<span class="k">if</span> <span class="ow">not</span> <span class="n">cb</span><span class="o">.</span><span class="n">iterable</span><span class="p">(</span><span class="n">width</span><span class="p">):</span>
<span class="n">lw</span> <span class="o">=</span> <span class="p">(</span><span class="n">width</span><span class="p">,)</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">lw</span> <span class="o">=</span> <span class="n">width</span>
<span class="k">if</span> <span class="ow">not</span> <span class="n">cb</span><span class="o">.</span><span class="n">is_string_like</span><span class="p">(</span><span class="n">edge_color</span><span class="p">)</span> \
<span class="ow">and</span> <span class="n">cb</span><span class="o">.</span><span class="n">iterable</span><span class="p">(</span><span class="n">edge_color</span><span class="p">)</span> \
<span class="ow">and</span> <span class="nb">len</span><span class="p">(</span><span class="n">edge_color</span><span class="p">)</span><span class="o">==</span><span class="nb">len</span><span class="p">(</span><span class="n">edge_pos</span><span class="p">):</span>
<span class="k">if</span> <span class="n">numpy</span><span class="o">.</span><span class="n">alltrue</span><span class="p">([</span><span class="n">cb</span><span class="o">.</span><span class="n">is_string_like</span><span class="p">(</span><span class="n">c</span><span class="p">)</span>
<span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="n">edge_color</span><span class="p">]):</span>
<span class="c"># (should check ALL elements)</span>
<span class="c"># list of color letters such as ['k','r','k',...]</span>
<span class="n">edge_colors</span> <span class="o">=</span> <span class="nb">tuple</span><span class="p">([</span><span class="n">colorConverter</span><span class="o">.</span><span class="n">to_rgba</span><span class="p">(</span><span class="n">c</span><span class="p">,</span><span class="n">alpha</span><span class="p">)</span>
<span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="n">edge_color</span><span class="p">])</span>
<span class="k">elif</span> <span class="n">numpy</span><span class="o">.</span><span class="n">alltrue</span><span class="p">([</span><span class="ow">not</span> <span class="n">cb</span><span class="o">.</span><span class="n">is_string_like</span><span class="p">(</span><span class="n">c</span><span class="p">)</span>
<span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="n">edge_color</span><span class="p">]):</span>
<span class="c"># If color specs are given as (rgb) or (rgba) tuples, we're OK</span>
<span class="k">if</span> <span class="n">numpy</span><span class="o">.</span><span class="n">alltrue</span><span class="p">([</span><span class="n">cb</span><span class="o">.</span><span class="n">iterable</span><span class="p">(</span><span class="n">c</span><span class="p">)</span> <span class="ow">and</span> <span class="nb">len</span><span class="p">(</span><span class="n">c</span><span class="p">)</span> <span class="ow">in</span> <span class="p">(</span><span class="mi">3</span><span class="p">,</span><span class="mi">4</span><span class="p">)</span>
<span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="n">edge_color</span><span class="p">]):</span>
<span class="n">edge_colors</span> <span class="o">=</span> <span class="nb">tuple</span><span class="p">(</span><span class="n">edge_color</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="c"># numbers (which are going to be mapped with a colormap)</span>
<span class="n">edge_colors</span> <span class="o">=</span> <span class="bp">None</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s">'edge_color must consist of either color names or numbers'</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">if</span> <span class="n">cb</span><span class="o">.</span><span class="n">is_string_like</span><span class="p">(</span><span class="n">edge_color</span><span class="p">)</span> <span class="ow">or</span> <span class="nb">len</span><span class="p">(</span><span class="n">edge_color</span><span class="p">)</span><span class="o">==</span><span class="mi">1</span><span class="p">:</span>
<span class="n">edge_colors</span> <span class="o">=</span> <span class="p">(</span> <span class="n">colorConverter</span><span class="o">.</span><span class="n">to_rgba</span><span class="p">(</span><span class="n">edge_color</span><span class="p">,</span> <span class="n">alpha</span><span class="p">),</span> <span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s">'edge_color must be a single color or list of exactly m colors where m is the number or edges'</span><span class="p">)</span>
<span class="n">edge_collection</span> <span class="o">=</span> <span class="n">LineCollection</span><span class="p">(</span><span class="n">edge_pos</span><span class="p">,</span>
<span class="n">colors</span> <span class="o">=</span> <span class="n">edge_colors</span><span class="p">,</span>
<span class="n">linewidths</span> <span class="o">=</span> <span class="n">lw</span><span class="p">,</span>
<span class="n">antialiaseds</span> <span class="o">=</span> <span class="p">(</span><span class="mi">1</span><span class="p">,),</span>
<span class="n">linestyle</span> <span class="o">=</span> <span class="n">style</span><span class="p">,</span>
<span class="n">transOffset</span> <span class="o">=</span> <span class="n">ax</span><span class="o">.</span><span class="n">transData</span><span class="p">,</span>
<span class="p">)</span>
<span class="n">edge_collection</span><span class="o">.</span><span class="n">set_zorder</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span> <span class="c"># edges go behind nodes</span>
<span class="n">edge_collection</span><span class="o">.</span><span class="n">set_label</span><span class="p">(</span><span class="n">label</span><span class="p">)</span>
<span class="n">ax</span><span class="o">.</span><span class="n">add_collection</span><span class="p">(</span><span class="n">edge_collection</span><span class="p">)</span>
<span class="c"># Note: there was a bug in mpl regarding the handling of alpha values for</span>
<span class="c"># each line in a LineCollection. It was fixed in matplotlib in r7184 and</span>
<span class="c"># r7189 (June 6 2009). We should then not set the alpha value globally,</span>
<span class="c"># since the user can instead provide per-edge alphas now. Only set it</span>
<span class="c"># globally if provided as a scalar.</span>
<span class="k">if</span> <span class="n">cb</span><span class="o">.</span><span class="n">is_numlike</span><span class="p">(</span><span class="n">alpha</span><span class="p">):</span>
<span class="n">edge_collection</span><span class="o">.</span><span class="n">set_alpha</span><span class="p">(</span><span class="n">alpha</span><span class="p">)</span>
<span class="k">if</span> <span class="n">edge_colors</span> <span class="ow">is</span> <span class="bp">None</span><span class="p">:</span>
<span class="k">if</span> <span class="n">edge_cmap</span> <span class="ow">is</span> <span class="ow">not</span> <span class="bp">None</span><span class="p">:</span>
<span class="k">assert</span><span class="p">(</span><span class="nb">isinstance</span><span class="p">(</span><span class="n">edge_cmap</span><span class="p">,</span> <span class="n">Colormap</span><span class="p">))</span>
<span class="n">edge_collection</span><span class="o">.</span><span class="n">set_array</span><span class="p">(</span><span class="n">numpy</span><span class="o">.</span><span class="n">asarray</span><span class="p">(</span><span class="n">edge_color</span><span class="p">))</span>
<span class="n">edge_collection</span><span class="o">.</span><span class="n">set_cmap</span><span class="p">(</span><span class="n">edge_cmap</span><span class="p">)</span>
<span class="k">if</span> <span class="n">edge_vmin</span> <span class="ow">is</span> <span class="ow">not</span> <span class="bp">None</span> <span class="ow">or</span> <span class="n">edge_vmax</span> <span class="ow">is</span> <span class="ow">not</span> <span class="bp">None</span><span class="p">:</span>
<span class="n">edge_collection</span><span class="o">.</span><span class="n">set_clim</span><span class="p">(</span><span class="n">edge_vmin</span><span class="p">,</span> <span class="n">edge_vmax</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">edge_collection</span><span class="o">.</span><span class="n">autoscale</span><span class="p">()</span>
<span class="n">arrow_collection</span><span class="o">=</span><span class="bp">None</span>
<span class="k">if</span> <span class="n">G</span><span class="o">.</span><span class="n">is_directed</span><span class="p">()</span> <span class="ow">and</span> <span class="n">arrows</span><span class="p">:</span>
<span class="c"># a directed graph hack</span>
<span class="c"># draw thick line segments at head end of edge</span>
<span class="c"># waiting for someone else to implement arrows that will work</span>
<span class="n">arrow_colors</span> <span class="o">=</span> <span class="n">edge_colors</span>
<span class="n">a_pos</span><span class="o">=</span><span class="p">[]</span>
<span class="n">p</span><span class="o">=</span><span class="mf">1.0</span><span class="o">-</span><span class="mf">0.25</span> <span class="c"># make head segment 25 percent of edge length</span>
<span class="k">for</span> <span class="n">src</span><span class="p">,</span><span class="n">dst</span> <span class="ow">in</span> <span class="n">edge_pos</span><span class="p">:</span>
<span class="n">x1</span><span class="p">,</span><span class="n">y1</span><span class="o">=</span><span class="n">src</span>
<span class="n">x2</span><span class="p">,</span><span class="n">y2</span><span class="o">=</span><span class="n">dst</span>
<span class="n">dx</span><span class="o">=</span><span class="n">x2</span><span class="o">-</span><span class="n">x1</span> <span class="c"># x offset</span>
<span class="n">dy</span><span class="o">=</span><span class="n">y2</span><span class="o">-</span><span class="n">y1</span> <span class="c"># y offset</span>
<span class="n">d</span><span class="o">=</span><span class="n">numpy</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="nb">float</span><span class="p">(</span><span class="n">dx</span><span class="o">**</span><span class="mi">2</span><span class="o">+</span><span class="n">dy</span><span class="o">**</span><span class="mi">2</span><span class="p">))</span> <span class="c"># length of edge</span>
<span class="k">if</span> <span class="n">d</span><span class="o">==</span><span class="mi">0</span><span class="p">:</span> <span class="c"># source and target at same position</span>
<span class="k">continue</span>
<span class="k">if</span> <span class="n">dx</span><span class="o">==</span><span class="mi">0</span><span class="p">:</span> <span class="c"># vertical edge</span>
<span class="n">xa</span><span class="o">=</span><span class="n">x2</span>
<span class="n">ya</span><span class="o">=</span><span class="n">dy</span><span class="o">*</span><span class="n">p</span><span class="o">+</span><span class="n">y1</span>
<span class="k">if</span> <span class="n">dy</span><span class="o">==</span><span class="mi">0</span><span class="p">:</span> <span class="c"># horizontal edge</span>
<span class="n">ya</span><span class="o">=</span><span class="n">y2</span>
<span class="n">xa</span><span class="o">=</span><span class="n">dx</span><span class="o">*</span><span class="n">p</span><span class="o">+</span><span class="n">x1</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">theta</span><span class="o">=</span><span class="n">numpy</span><span class="o">.</span><span class="n">arctan2</span><span class="p">(</span><span class="n">dy</span><span class="p">,</span><span class="n">dx</span><span class="p">)</span>
<span class="n">xa</span><span class="o">=</span><span class="n">p</span><span class="o">*</span><span class="n">d</span><span class="o">*</span><span class="n">numpy</span><span class="o">.</span><span class="n">cos</span><span class="p">(</span><span class="n">theta</span><span class="p">)</span><span class="o">+</span><span class="n">x1</span>
<span class="n">ya</span><span class="o">=</span><span class="n">p</span><span class="o">*</span><span class="n">d</span><span class="o">*</span><span class="n">numpy</span><span class="o">.</span><span class="n">sin</span><span class="p">(</span><span class="n">theta</span><span class="p">)</span><span class="o">+</span><span class="n">y1</span>
<span class="n">a_pos</span><span class="o">.</span><span class="n">append</span><span class="p">(((</span><span class="n">xa</span><span class="p">,</span><span class="n">ya</span><span class="p">),(</span><span class="n">x2</span><span class="p">,</span><span class="n">y2</span><span class="p">)))</span>
<span class="n">arrow_collection</span> <span class="o">=</span> <span class="n">LineCollection</span><span class="p">(</span><span class="n">a_pos</span><span class="p">,</span>
<span class="n">colors</span> <span class="o">=</span> <span class="n">arrow_colors</span><span class="p">,</span>
<span class="n">linewidths</span> <span class="o">=</span> <span class="p">[</span><span class="mi">4</span><span class="o">*</span><span class="n">ww</span> <span class="k">for</span> <span class="n">ww</span> <span class="ow">in</span> <span class="n">lw</span><span class="p">],</span>
<span class="n">antialiaseds</span> <span class="o">=</span> <span class="p">(</span><span class="mi">1</span><span class="p">,),</span>
<span class="n">transOffset</span> <span class="o">=</span> <span class="n">ax</span><span class="o">.</span><span class="n">transData</span><span class="p">,</span>
<span class="p">)</span>
<span class="n">arrow_collection</span><span class="o">.</span><span class="n">set_zorder</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span> <span class="c"># edges go behind nodes</span>
<span class="n">arrow_collection</span><span class="o">.</span><span class="n">set_label</span><span class="p">(</span><span class="n">label</span><span class="p">)</span>
<span class="n">ax</span><span class="o">.</span><span class="n">add_collection</span><span class="p">(</span><span class="n">arrow_collection</span><span class="p">)</span>
<span class="c"># update view</span>
<span class="n">minx</span> <span class="o">=</span> <span class="n">numpy</span><span class="o">.</span><span class="n">amin</span><span class="p">(</span><span class="n">numpy</span><span class="o">.</span><span class="n">ravel</span><span class="p">(</span><span class="n">edge_pos</span><span class="p">[:,:,</span><span class="mi">0</span><span class="p">]))</span>
<span class="n">maxx</span> <span class="o">=</span> <span class="n">numpy</span><span class="o">.</span><span class="n">amax</span><span class="p">(</span><span class="n">numpy</span><span class="o">.</span><span class="n">ravel</span><span class="p">(</span><span class="n">edge_pos</span><span class="p">[:,:,</span><span class="mi">0</span><span class="p">]))</span>
<span class="n">miny</span> <span class="o">=</span> <span class="n">numpy</span><span class="o">.</span><span class="n">amin</span><span class="p">(</span><span class="n">numpy</span><span class="o">.</span><span class="n">ravel</span><span class="p">(</span><span class="n">edge_pos</span><span class="p">[:,:,</span><span class="mi">1</span><span class="p">]))</span>
<span class="n">maxy</span> <span class="o">=</span> <span class="n">numpy</span><span class="o">.</span><span class="n">amax</span><span class="p">(</span><span class="n">numpy</span><span class="o">.</span><span class="n">ravel</span><span class="p">(</span><span class="n">edge_pos</span><span class="p">[:,:,</span><span class="mi">1</span><span class="p">]))</span>
<span class="n">w</span> <span class="o">=</span> <span class="n">maxx</span><span class="o">-</span><span class="n">minx</span>
<span class="n">h</span> <span class="o">=</span> <span class="n">maxy</span><span class="o">-</span><span class="n">miny</span>
<span class="n">padx</span><span class="p">,</span> <span class="n">pady</span> <span class="o">=</span> <span class="mf">0.05</span><span class="o">*</span><span class="n">w</span><span class="p">,</span> <span class="mf">0.05</span><span class="o">*</span><span class="n">h</span>
<span class="n">corners</span> <span class="o">=</span> <span class="p">(</span><span class="n">minx</span><span class="o">-</span><span class="n">padx</span><span class="p">,</span> <span class="n">miny</span><span class="o">-</span><span class="n">pady</span><span class="p">),</span> <span class="p">(</span><span class="n">maxx</span><span class="o">+</span><span class="n">padx</span><span class="p">,</span> <span class="n">maxy</span><span class="o">+</span><span class="n">pady</span><span class="p">)</span>
<span class="n">ax</span><span class="o">.</span><span class="n">update_datalim</span><span class="p">(</span> <span class="n">corners</span><span class="p">)</span>
<span class="n">ax</span><span class="o">.</span><span class="n">autoscale_view</span><span class="p">()</span>
<span class="c"># if arrow_collection:</span>
<span class="k">return</span> <span class="n">edge_collection</span>
</div>
<div class="viewcode-block" id="draw_networkx_labels"><a class="viewcode-back" href="../../../reference/generated/networkx.drawing.nx_pylab.draw_networkx_labels.html#networkx.drawing.nx_pylab.draw_networkx_labels">[docs]</a><span class="k">def</span> <span class="nf">draw_networkx_labels</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">pos</span><span class="p">,</span>
<span class="n">labels</span><span class="o">=</span><span class="bp">None</span><span class="p">,</span>
<span class="n">font_size</span><span class="o">=</span><span class="mi">12</span><span class="p">,</span>
<span class="n">font_color</span><span class="o">=</span><span class="s">'k'</span><span class="p">,</span>
<span class="n">font_family</span><span class="o">=</span><span class="s">'sans-serif'</span><span class="p">,</span>
<span class="n">font_weight</span><span class="o">=</span><span class="s">'normal'</span><span class="p">,</span>
<span class="n">alpha</span><span class="o">=</span><span class="mf">1.0</span><span class="p">,</span>
<span class="n">ax</span><span class="o">=</span><span class="bp">None</span><span class="p">,</span>
<span class="o">**</span><span class="n">kwds</span><span class="p">):</span>
<span class="sd">"""Draw node labels on the graph G.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> G : graph</span>
<span class="sd"> A networkx graph</span>
<span class="sd"> pos : dictionary, optional</span>
<span class="sd"> A dictionary with nodes as keys and positions as values.</span>
<span class="sd"> If not specified a spring layout positioning will be computed.</span>
<span class="sd"> See networkx.layout for functions that compute node positions.</span>
<span class="sd"> labels : dictionary, optional (default=None)</span>
<span class="sd"> Node labels in a dictionary keyed by node of text labels</span>
<span class="sd"> font_size : int</span>
<span class="sd"> Font size for text labels (default=12)</span>
<span class="sd"> font_color : string</span>
<span class="sd"> Font color string (default='k' black)</span>
<span class="sd"> font_family : string</span>
<span class="sd"> Font family (default='sans-serif')</span>
<span class="sd"> font_weight : string</span>
<span class="sd"> Font weight (default='normal')</span>
<span class="sd"> alpha : float</span>
<span class="sd"> The text transparency (default=1.0)</span>
<span class="sd"> ax : Matplotlib Axes object, optional</span>
<span class="sd"> Draw the graph in the specified Matplotlib axes.</span>
<span class="sd"> Examples</span>
<span class="sd"> --------</span>
<span class="sd"> >>> G=nx.dodecahedral_graph()</span>
<span class="sd"> >>> labels=nx.draw_networkx_labels(G,pos=nx.spring_layout(G))</span>
<span class="sd"> Also see the NetworkX drawing examples at</span>
<span class="sd"> http://networkx.lanl.gov/gallery.html</span>
<span class="sd"> See Also</span>
<span class="sd"> --------</span>
<span class="sd"> draw()</span>
<span class="sd"> draw_networkx()</span>
<span class="sd"> draw_networkx_nodes()</span>
<span class="sd"> draw_networkx_edges()</span>
<span class="sd"> draw_networkx_edge_labels()</span>
<span class="sd"> """</span>
<span class="k">try</span><span class="p">:</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="kn">as</span> <span class="nn">plt</span>
<span class="kn">import</span> <span class="nn">matplotlib.cbook</span> <span class="kn">as</span> <span class="nn">cb</span>
<span class="k">except</span> <span class="ne">ImportError</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">ImportError</span><span class="p">(</span><span class="s">"Matplotlib required for draw()"</span><span class="p">)</span>
<span class="k">except</span> <span class="ne">RuntimeError</span><span class="p">:</span>
<span class="k">print</span><span class="p">(</span><span class="s">"Matplotlib unable to open display"</span><span class="p">)</span>
<span class="k">raise</span>
<span class="k">if</span> <span class="n">ax</span> <span class="ow">is</span> <span class="bp">None</span><span class="p">:</span>
<span class="n">ax</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">gca</span><span class="p">()</span>
<span class="k">if</span> <span class="n">labels</span> <span class="ow">is</span> <span class="bp">None</span><span class="p">:</span>
<span class="n">labels</span><span class="o">=</span><span class="nb">dict</span><span class="p">(</span> <span class="p">(</span><span class="n">n</span><span class="p">,</span><span class="n">n</span><span class="p">)</span> <span class="k">for</span> <span class="n">n</span> <span class="ow">in</span> <span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">())</span>
<span class="c"># set optional alignment</span>
<span class="n">horizontalalignment</span><span class="o">=</span><span class="n">kwds</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s">'horizontalalignment'</span><span class="p">,</span><span class="s">'center'</span><span class="p">)</span>
<span class="n">verticalalignment</span><span class="o">=</span><span class="n">kwds</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s">'verticalalignment'</span><span class="p">,</span><span class="s">'center'</span><span class="p">)</span>
<span class="n">text_items</span><span class="o">=</span><span class="p">{}</span> <span class="c"># there is no text collection so we'll fake one</span>
<span class="k">for</span> <span class="n">n</span><span class="p">,</span> <span class="n">label</span> <span class="ow">in</span> <span class="n">labels</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
<span class="p">(</span><span class="n">x</span><span class="p">,</span><span class="n">y</span><span class="p">)</span><span class="o">=</span><span class="n">pos</span><span class="p">[</span><span class="n">n</span><span class="p">]</span>
<span class="k">if</span> <span class="ow">not</span> <span class="n">cb</span><span class="o">.</span><span class="n">is_string_like</span><span class="p">(</span><span class="n">label</span><span class="p">):</span>
<span class="n">label</span><span class="o">=</span><span class="nb">str</span><span class="p">(</span><span class="n">label</span><span class="p">)</span> <span class="c"># this will cause "1" and 1 to be labeled the same</span>
<span class="n">t</span><span class="o">=</span><span class="n">ax</span><span class="o">.</span><span class="n">text</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span>
<span class="n">label</span><span class="p">,</span>
<span class="n">size</span><span class="o">=</span><span class="n">font_size</span><span class="p">,</span>
<span class="n">color</span><span class="o">=</span><span class="n">font_color</span><span class="p">,</span>
<span class="n">family</span><span class="o">=</span><span class="n">font_family</span><span class="p">,</span>
<span class="n">weight</span><span class="o">=</span><span class="n">font_weight</span><span class="p">,</span>
<span class="n">horizontalalignment</span><span class="o">=</span><span class="n">horizontalalignment</span><span class="p">,</span>
<span class="n">verticalalignment</span><span class="o">=</span><span class="n">verticalalignment</span><span class="p">,</span>
<span class="n">transform</span> <span class="o">=</span> <span class="n">ax</span><span class="o">.</span><span class="n">transData</span><span class="p">,</span>
<span class="n">clip_on</span><span class="o">=</span><span class="bp">True</span><span class="p">,</span>
<span class="p">)</span>
<span class="n">text_items</span><span class="p">[</span><span class="n">n</span><span class="p">]</span><span class="o">=</span><span class="n">t</span>
<span class="k">return</span> <span class="n">text_items</span>
</div>
<div class="viewcode-block" id="draw_networkx_edge_labels"><a class="viewcode-back" href="../../../reference/generated/networkx.drawing.nx_pylab.draw_networkx_edge_labels.html#networkx.drawing.nx_pylab.draw_networkx_edge_labels">[docs]</a><span class="k">def</span> <span class="nf">draw_networkx_edge_labels</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">pos</span><span class="p">,</span>
<span class="n">edge_labels</span><span class="o">=</span><span class="bp">None</span><span class="p">,</span>
<span class="n">label_pos</span><span class="o">=</span><span class="mf">0.5</span><span class="p">,</span>
<span class="n">font_size</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span>
<span class="n">font_color</span><span class="o">=</span><span class="s">'k'</span><span class="p">,</span>
<span class="n">font_family</span><span class="o">=</span><span class="s">'sans-serif'</span><span class="p">,</span>
<span class="n">font_weight</span><span class="o">=</span><span class="s">'normal'</span><span class="p">,</span>
<span class="n">alpha</span><span class="o">=</span><span class="mf">1.0</span><span class="p">,</span>
<span class="n">bbox</span><span class="o">=</span><span class="bp">None</span><span class="p">,</span>
<span class="n">ax</span><span class="o">=</span><span class="bp">None</span><span class="p">,</span>
<span class="n">rotate</span><span class="o">=</span><span class="bp">True</span><span class="p">,</span>
<span class="o">**</span><span class="n">kwds</span><span class="p">):</span>
<span class="sd">"""Draw edge labels.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> G : graph</span>
<span class="sd"> A networkx graph</span>
<span class="sd"> pos : dictionary, optional</span>
<span class="sd"> A dictionary with nodes as keys and positions as values.</span>
<span class="sd"> If not specified a spring layout positioning will be computed.</span>
<span class="sd"> See networkx.layout for functions that compute node positions.</span>
<span class="sd"> ax : Matplotlib Axes object, optional</span>
<span class="sd"> Draw the graph in the specified Matplotlib axes.</span>
<span class="sd"> alpha : float</span>
<span class="sd"> The text transparency (default=1.0)</span>
<span class="sd"> edge_labels : dictionary</span>
<span class="sd"> Edge labels in a dictionary keyed by edge two-tuple of text</span>
<span class="sd"> labels (default=None). Only labels for the keys in the dictionary</span>
<span class="sd"> are drawn.</span>
<span class="sd"> label_pos : float</span>
<span class="sd"> Position of edge label along edge (0=head, 0.5=center, 1=tail)</span>
<span class="sd"> font_size : int</span>
<span class="sd"> Font size for text labels (default=12)</span>
<span class="sd"> font_color : string</span>
<span class="sd"> Font color string (default='k' black)</span>
<span class="sd"> font_weight : string</span>
<span class="sd"> Font weight (default='normal')</span>
<span class="sd"> font_family : string</span>
<span class="sd"> Font family (default='sans-serif')</span>
<span class="sd"> bbox : Matplotlib bbox</span>
<span class="sd"> Specify text box shape and colors.</span>
<span class="sd"> clip_on : bool</span>
<span class="sd"> Turn on clipping at axis boundaries (default=True)</span>
<span class="sd"> Examples</span>
<span class="sd"> --------</span>
<span class="sd"> >>> G=nx.dodecahedral_graph()</span>
<span class="sd"> >>> edge_labels=nx.draw_networkx_edge_labels(G,pos=nx.spring_layout(G))</span>
<span class="sd"> Also see the NetworkX drawing examples at</span>
<span class="sd"> http://networkx.lanl.gov/gallery.html</span>
<span class="sd"> See Also</span>
<span class="sd"> --------</span>
<span class="sd"> draw()</span>
<span class="sd"> draw_networkx()</span>
<span class="sd"> draw_networkx_nodes()</span>
<span class="sd"> draw_networkx_edges()</span>
<span class="sd"> draw_networkx_labels()</span>
<span class="sd"> """</span>
<span class="k">try</span><span class="p">:</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="kn">as</span> <span class="nn">plt</span>
<span class="kn">import</span> <span class="nn">matplotlib.cbook</span> <span class="kn">as</span> <span class="nn">cb</span>
<span class="kn">import</span> <span class="nn">numpy</span>
<span class="k">except</span> <span class="ne">ImportError</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">ImportError</span><span class="p">(</span><span class="s">"Matplotlib required for draw()"</span><span class="p">)</span>
<span class="k">except</span> <span class="ne">RuntimeError</span><span class="p">:</span>
<span class="k">print</span><span class="p">(</span><span class="s">"Matplotlib unable to open display"</span><span class="p">)</span>
<span class="k">raise</span>
<span class="k">if</span> <span class="n">ax</span> <span class="ow">is</span> <span class="bp">None</span><span class="p">:</span>
<span class="n">ax</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">gca</span><span class="p">()</span>
<span class="k">if</span> <span class="n">edge_labels</span> <span class="ow">is</span> <span class="bp">None</span><span class="p">:</span>
<span class="n">labels</span><span class="o">=</span><span class="nb">dict</span><span class="p">(</span> <span class="p">((</span><span class="n">u</span><span class="p">,</span><span class="n">v</span><span class="p">),</span> <span class="n">d</span><span class="p">)</span> <span class="k">for</span> <span class="n">u</span><span class="p">,</span><span class="n">v</span><span class="p">,</span><span class="n">d</span> <span class="ow">in</span> <span class="n">G</span><span class="o">.</span><span class="n">edges</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="bp">True</span><span class="p">)</span> <span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">labels</span> <span class="o">=</span> <span class="n">edge_labels</span>
<span class="n">text_items</span><span class="o">=</span><span class="p">{}</span>
<span class="k">for</span> <span class="p">(</span><span class="n">n1</span><span class="p">,</span><span class="n">n2</span><span class="p">),</span> <span class="n">label</span> <span class="ow">in</span> <span class="n">labels</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
<span class="p">(</span><span class="n">x1</span><span class="p">,</span><span class="n">y1</span><span class="p">)</span><span class="o">=</span><span class="n">pos</span><span class="p">[</span><span class="n">n1</span><span class="p">]</span>
<span class="p">(</span><span class="n">x2</span><span class="p">,</span><span class="n">y2</span><span class="p">)</span><span class="o">=</span><span class="n">pos</span><span class="p">[</span><span class="n">n2</span><span class="p">]</span>
<span class="p">(</span><span class="n">x</span><span class="p">,</span><span class="n">y</span><span class="p">)</span> <span class="o">=</span> <span class="p">(</span><span class="n">x1</span> <span class="o">*</span> <span class="n">label_pos</span> <span class="o">+</span> <span class="n">x2</span> <span class="o">*</span> <span class="p">(</span><span class="mf">1.0</span> <span class="o">-</span> <span class="n">label_pos</span><span class="p">),</span>
<span class="n">y1</span> <span class="o">*</span> <span class="n">label_pos</span> <span class="o">+</span> <span class="n">y2</span> <span class="o">*</span> <span class="p">(</span><span class="mf">1.0</span> <span class="o">-</span> <span class="n">label_pos</span><span class="p">))</span>
<span class="k">if</span> <span class="n">rotate</span><span class="p">:</span>
<span class="n">angle</span><span class="o">=</span><span class="n">numpy</span><span class="o">.</span><span class="n">arctan2</span><span class="p">(</span><span class="n">y2</span><span class="o">-</span><span class="n">y1</span><span class="p">,</span><span class="n">x2</span><span class="o">-</span><span class="n">x1</span><span class="p">)</span><span class="o">/</span><span class="p">(</span><span class="mf">2.0</span><span class="o">*</span><span class="n">numpy</span><span class="o">.</span><span class="n">pi</span><span class="p">)</span><span class="o">*</span><span class="mi">360</span> <span class="c"># degrees</span>
<span class="c"># make label orientation "right-side-up"</span>
<span class="k">if</span> <span class="n">angle</span> <span class="o">></span> <span class="mi">90</span><span class="p">:</span>
<span class="n">angle</span><span class="o">-=</span><span class="mi">180</span>
<span class="k">if</span> <span class="n">angle</span> <span class="o"><</span> <span class="o">-</span> <span class="mi">90</span><span class="p">:</span>
<span class="n">angle</span><span class="o">+=</span><span class="mi">180</span>
<span class="c"># transform data coordinate angle to screen coordinate angle</span>
<span class="n">xy</span><span class="o">=</span><span class="n">numpy</span><span class="o">.</span><span class="n">array</span><span class="p">((</span><span class="n">x</span><span class="p">,</span><span class="n">y</span><span class="p">))</span>
<span class="n">trans_angle</span><span class="o">=</span><span class="n">ax</span><span class="o">.</span><span class="n">transData</span><span class="o">.</span><span class="n">transform_angles</span><span class="p">(</span><span class="n">numpy</span><span class="o">.</span><span class="n">array</span><span class="p">((</span><span class="n">angle</span><span class="p">,)),</span>
<span class="n">xy</span><span class="o">.</span><span class="n">reshape</span><span class="p">((</span><span class="mi">1</span><span class="p">,</span><span class="mi">2</span><span class="p">)))[</span><span class="mi">0</span><span class="p">]</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">trans_angle</span><span class="o">=</span><span class="mf">0.0</span>
<span class="c"># use default box of white with white border</span>
<span class="k">if</span> <span class="n">bbox</span> <span class="ow">is</span> <span class="bp">None</span><span class="p">:</span>
<span class="n">bbox</span> <span class="o">=</span> <span class="nb">dict</span><span class="p">(</span><span class="n">boxstyle</span><span class="o">=</span><span class="s">'round'</span><span class="p">,</span>
<span class="n">ec</span><span class="o">=</span><span class="p">(</span><span class="mf">1.0</span><span class="p">,</span> <span class="mf">1.0</span><span class="p">,</span> <span class="mf">1.0</span><span class="p">),</span>
<span class="n">fc</span><span class="o">=</span><span class="p">(</span><span class="mf">1.0</span><span class="p">,</span> <span class="mf">1.0</span><span class="p">,</span> <span class="mf">1.0</span><span class="p">),</span>
<span class="p">)</span>
<span class="k">if</span> <span class="ow">not</span> <span class="n">cb</span><span class="o">.</span><span class="n">is_string_like</span><span class="p">(</span><span class="n">label</span><span class="p">):</span>
<span class="n">label</span><span class="o">=</span><span class="nb">str</span><span class="p">(</span><span class="n">label</span><span class="p">)</span> <span class="c"># this will cause "1" and 1 to be labeled the same</span>
<span class="c"># set optional alignment</span>
<span class="n">horizontalalignment</span><span class="o">=</span><span class="n">kwds</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s">'horizontalalignment'</span><span class="p">,</span><span class="s">'center'</span><span class="p">)</span>
<span class="n">verticalalignment</span><span class="o">=</span><span class="n">kwds</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s">'verticalalignment'</span><span class="p">,</span><span class="s">'center'</span><span class="p">)</span>
<span class="n">t</span><span class="o">=</span><span class="n">ax</span><span class="o">.</span><span class="n">text</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span>
<span class="n">label</span><span class="p">,</span>
<span class="n">size</span><span class="o">=</span><span class="n">font_size</span><span class="p">,</span>
<span class="n">color</span><span class="o">=</span><span class="n">font_color</span><span class="p">,</span>
<span class="n">family</span><span class="o">=</span><span class="n">font_family</span><span class="p">,</span>
<span class="n">weight</span><span class="o">=</span><span class="n">font_weight</span><span class="p">,</span>
<span class="n">horizontalalignment</span><span class="o">=</span><span class="n">horizontalalignment</span><span class="p">,</span>
<span class="n">verticalalignment</span><span class="o">=</span><span class="n">verticalalignment</span><span class="p">,</span>
<span class="n">rotation</span><span class="o">=</span><span class="n">trans_angle</span><span class="p">,</span>
<span class="n">transform</span> <span class="o">=</span> <span class="n">ax</span><span class="o">.</span><span class="n">transData</span><span class="p">,</span>
<span class="n">bbox</span> <span class="o">=</span> <span class="n">bbox</span><span class="p">,</span>
<span class="n">zorder</span> <span class="o">=</span> <span class="mi">1</span><span class="p">,</span>
<span class="n">clip_on</span><span class="o">=</span><span class="bp">True</span><span class="p">,</span>
<span class="p">)</span>
<span class="n">text_items</span><span class="p">[(</span><span class="n">n1</span><span class="p">,</span><span class="n">n2</span><span class="p">)]</span><span class="o">=</span><span class="n">t</span>
<span class="k">return</span> <span class="n">text_items</span>
</div>
<div class="viewcode-block" id="draw_circular"><a class="viewcode-back" href="../../../reference/generated/networkx.drawing.nx_pylab.draw_circular.html#networkx.drawing.nx_pylab.draw_circular">[docs]</a><span class="k">def</span> <span class="nf">draw_circular</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">"""Draw the graph G with a circular layout."""</span>
<span class="n">draw</span><span class="p">(</span><span class="n">G</span><span class="p">,</span><span class="n">circular_layout</span><span class="p">(</span><span class="n">G</span><span class="p">),</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
</div>
<div class="viewcode-block" id="draw_random"><a class="viewcode-back" href="../../../reference/generated/networkx.drawing.nx_pylab.draw_random.html#networkx.drawing.nx_pylab.draw_random">[docs]</a><span class="k">def</span> <span class="nf">draw_random</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">"""Draw the graph G with a random layout."""</span>
<span class="n">draw</span><span class="p">(</span><span class="n">G</span><span class="p">,</span><span class="n">random_layout</span><span class="p">(</span><span class="n">G</span><span class="p">),</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
</div>
<div class="viewcode-block" id="draw_spectral"><a class="viewcode-back" href="../../../reference/generated/networkx.drawing.nx_pylab.draw_spectral.html#networkx.drawing.nx_pylab.draw_spectral">[docs]</a><span class="k">def</span> <span class="nf">draw_spectral</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">"""Draw the graph G with a spectral layout."""</span>
<span class="n">draw</span><span class="p">(</span><span class="n">G</span><span class="p">,</span><span class="n">spectral_layout</span><span class="p">(</span><span class="n">G</span><span class="p">),</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
</div>
<div class="viewcode-block" id="draw_spring"><a class="viewcode-back" href="../../../reference/generated/networkx.drawing.nx_pylab.draw_spring.html#networkx.drawing.nx_pylab.draw_spring">[docs]</a><span class="k">def</span> <span class="nf">draw_spring</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">"""Draw the graph G with a spring layout."""</span>
<span class="n">draw</span><span class="p">(</span><span class="n">G</span><span class="p">,</span><span class="n">spring_layout</span><span class="p">(</span><span class="n">G</span><span class="p">),</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
</div>
<div class="viewcode-block" id="draw_shell"><a class="viewcode-back" href="../../../reference/generated/networkx.drawing.nx_pylab.draw_shell.html#networkx.drawing.nx_pylab.draw_shell">[docs]</a><span class="k">def</span> <span class="nf">draw_shell</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">"""Draw networkx graph with shell layout."""</span>
<span class="n">nlist</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s">'nlist'</span><span class="p">,</span> <span class="bp">None</span><span class="p">)</span>
<span class="k">if</span> <span class="n">nlist</span> <span class="o">!=</span> <span class="bp">None</span><span class="p">:</span>
<span class="k">del</span><span class="p">(</span><span class="n">kwargs</span><span class="p">[</span><span class="s">'nlist'</span><span class="p">])</span>
<span class="n">draw</span><span class="p">(</span><span class="n">G</span><span class="p">,</span><span class="n">shell_layout</span><span class="p">(</span><span class="n">G</span><span class="p">,</span><span class="n">nlist</span><span class="o">=</span><span class="n">nlist</span><span class="p">),</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
</div>
<div class="viewcode-block" id="draw_graphviz"><a class="viewcode-back" href="../../../reference/generated/networkx.drawing.nx_pylab.draw_graphviz.html#networkx.drawing.nx_pylab.draw_graphviz">[docs]</a><span class="k">def</span> <span class="nf">draw_graphviz</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">prog</span><span class="o">=</span><span class="s">"neato"</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">"""Draw networkx graph with graphviz layout."""</span>
<span class="n">pos</span><span class="o">=</span><span class="n">nx</span><span class="o">.</span><span class="n">drawing</span><span class="o">.</span><span class="n">graphviz_layout</span><span class="p">(</span><span class="n">G</span><span class="p">,</span><span class="n">prog</span><span class="p">)</span>
<span class="n">draw</span><span class="p">(</span><span class="n">G</span><span class="p">,</span><span class="n">pos</span><span class="p">,</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
</div>
<span class="k">def</span> <span class="nf">draw_nx</span><span class="p">(</span><span class="n">G</span><span class="p">,</span><span class="n">pos</span><span class="p">,</span><span class="o">**</span><span class="n">kwds</span><span class="p">):</span>
<span class="sd">"""For backward compatibility; use draw or draw_networkx."""</span>
<span class="n">draw</span><span class="p">(</span><span class="n">G</span><span class="p">,</span><span class="n">pos</span><span class="p">,</span><span class="o">**</span><span class="n">kwds</span><span class="p">)</span>
<span class="c"># fixture for nose tests</span>
<span class="k">def</span> <span class="nf">setup_module</span><span class="p">(</span><span class="n">module</span><span class="p">):</span>
<span class="kn">from</span> <span class="nn">nose</span> <span class="kn">import</span> <span class="n">SkipTest</span>
<span class="k">try</span><span class="p">:</span>
<span class="kn">import</span> <span class="nn">matplotlib</span> <span class="kn">as</span> <span class="nn">mpl</span>
<span class="n">mpl</span><span class="o">.</span><span class="n">use</span><span class="p">(</span><span class="s">'PS'</span><span class="p">,</span><span class="n">warn</span><span class="o">=</span><span class="bp">False</span><span class="p">)</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="kn">as</span> <span class="nn">plt</span>
<span class="k">except</span><span class="p">:</span>
<span class="k">raise</span> <span class="n">SkipTest</span><span class="p">(</span><span class="s">"matplotlib not available"</span><span class="p">)</span>
</pre></div>
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