kvadrat
вот это http://networkx.lanl.gov/ сделано по средствам использования чего? слева я вижу питоновский код
fata1ex, вас никто не заставляет отвечать мне. если мои посты вызывают в вас раздражение, или какие-то другие не комфортные ощущения, просто не отвечайте
Где тут код питона?
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NetworkX
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<pre>easy_install networkx</pre>
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<h2>High productivity software for complex networks</a></h2>
<blockquote>
<p>NetworkX is a Python language software package for the creation, manipulation, and
study of the structure, dynamics, and functions of complex networks.</p>
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<h2>Quick Example</h2>
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<div class="highlight-python"><div class="highlight"><pre><span class="gp">>>> </span><span class="k">import</span> <span class="nn">networkx</span> <span class="k">as</span> <span class="nn">nx</span>
<span class="gp">>>> </span><span class="n">G</span><span class="o">=</span><span class="n">nx</span><span class="o">.</span><span class="n">Graph</span><span class="p">()</span>
<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">add_node</span><span class="p">(</span><span class="s">"spam"</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">add_edge</span><span class="p">(</span><span class="mf">1</span><span class="p">,</span><span class="mf">2</span><span class="p">)</span>
<span class="gp">>>> </span><span class="k">print</span><span class="p">(</span class="p"><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">())</span>
<span class="go">[1, 2, 'spam']</span>
<span class="gp">>>> </span><span class="k">print</span><span class="p">(</span class="p"><span class="n">G</span><span class="o">.</span><span class="n">edges</span><span class="p">())</span>
<span class="go">[(1, 2)]</span>
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<h2>Features</h2>
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<li> Python language data structures for graphs, digraphs, and multigraphs.
<li> Nodes can be "anything" (e.g. text, images, XML records)</li>
<li> Edges can hold arbitrary data (e.g. weights, time-series)
<li> Generators for classic graphs, random graphs, and synthetic networks</li>
<li> Standard graph algorithms</li>
<li> Network structure and analysis measures</li>
<li> Basic graph drawing</li>
<li> Open source <a href="reference/legal.html">BSD license</a> </li>
<li> Well tested: more than 1500 unit tests</li>
<li> Additional benefits from Python: fast prototyping, easy to teach, multi-platform</li>
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