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  <title>shortest_avg_max_hist(1) - Compute the distance between one node and all the other nodes of a graph</title>
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    <a href="#NAME">NAME</a>
    <a href="#SYNOPSIS">SYNOPSIS</a>
    <a href="#DESCRIPTION">DESCRIPTION</a>
    <a href="#PARAMETERS">PARAMETERS</a>
    <a href="#OUTPUT">OUTPUT</a>
    <a href="#EXAMPLES">EXAMPLES</a>
    <a href="#SEE-ALSO">SEE ALSO</a>
    <a href="#REFERENCES">REFERENCES</a>
    <a href="#AUTHORS">AUTHORS</a>
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  <ol class='man-decor man-head man head'>
    <li class='tl'>shortest_avg_max_hist(1)</li>
    <li class='tc'>www.complex-networks.net</li>
    <li class='tr'>shortest_avg_max_hist(1)</li>
  </ol>

  <h2 id="NAME">NAME</h2>
<p class="man-name">
  <code>shortest_avg_max_hist</code> - <span class="man-whatis">Compute the distance between one node and all the other nodes of a graph</span>
</p>

<h2 id="SYNOPSIS">SYNOPSIS</h2>

<p><code>shortest_avg_max_hist</code> <var>graph_in</var> <var>node</var></p>

<h2 id="DESCRIPTION">DESCRIPTION</h2>

<p><code>shortest_avg_max_hist</code> computes the distance (and the shortest paths)
between a given node and all the other nodes of an undirected graph
provided as input. The program implements the Breadth-First Search
algorithm, and works almost exactly as <a href="shortest.1.html">shortest(1)</a>, except for the
output.</p>

<h2 id="PARAMETERS">PARAMETERS</h2>

<dl>
<dt><var>graph_in</var></dt><dd><p>  input graph (edge list) if equal to <code>-</code> (dash), read the edge list
  from STDIN.</p></dd>
<dt class="flush"><var>node</var></dt><dd><p>  The label of the node from which distances are to be computed</p></dd>
</dl>


<h2 id="OUTPUT">OUTPUT</h2>

<p>The output</p>

<h2 id="EXAMPLES">EXAMPLES</h2>

<p>The following command:</p>

<pre><code>      $ shortest_avg_max_hist er_1000_5000.net 25 
      3.2002 4 11 111 544 333
      $
</code></pre>

<p>is showing the average distance between node <code>25</code> and all the other
nodes in the graph (<code>3.2002</code>), the eccentricity of node <code>25</code> (equal to
<code>4</code>), and the number of nodes at distance <code>1</code> (11), <code>2</code> (111), <code>3</code>
(544) and <code>4</code> (333) from node <code>25</code>.</p>

<h2 id="SEE-ALSO">SEE ALSO</h2>

<p><a class="man-ref" href="shortest.1.html">shortest<span class="s">(1)</span></a>, <a class="man-ref" href="betweenness.1.html">betweenness<span class="s">(1)</span></a>, <a class="man-ref" href="bet_dependency.1.html">bet_dependency<span class="s">(1)</span></a></p>

<h2 id="REFERENCES">REFERENCES</h2>

<ul>
<li><p>V. Latora, V. Nicosia, G. Russo, "Complex Networks: Principles,
Methods and Applications", Chapter 3, Cambridge University Press
(2017)</p></li>
<li><p>V. Latora, V. Nicosia, G. Russo, "Complex Networks: Principles,
Methods and Applications", Appendix 6, Cambridge University Press
(2017)</p></li>
</ul>


<h2 id="AUTHORS">AUTHORS</h2>

<p>(c) Vincenzo 'KatolaZ' Nicosia 2009-2017 <code>&lt;v.nicosia@qmul.ac.uk&gt;</code>.</p>


  <ol class='man-decor man-foot man foot'>
    <li class='tl'>www.complex-networks.net</li>
    <li class='tc'>September 2017</li>
    <li class='tr'>shortest_avg_max_hist(1)</li>
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