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<h5 class="subsubsectionHead"><a
id="x44-430002.1.1"></a><span
class="cmtt-10x-x-109">model</span><span
class="cmtt-10x-x-109">_MDM.py</span></h5>
<!--l. 3--><p class="noindent" ><span
class="cmbx-10x-x-109">NAME</span>
<!--l. 3--><p class="indent" > <span
class="cmbx-10x-x-109">model</span><span
class="cmbx-10x-x-109">_MDM.py </span>- Multi-activity Deterministic Model.
<!--l. 3--><p class="noindent" ><span
class="cmbx-10x-x-109">SYNOPSYS</span>
<!--l. 3--><p class="indent" > <span
class="cmbx-10x-x-109">model</span><span
class="cmbx-10x-x-109">_MDM.py </span><span
class="cmmi-10x-x-109"><</span><span
class="cmitt-10x-x-109">Bi</span><span
class="cmitt-10x-x-109">_file</span><span
class="cmmi-10x-x-109">> <</span><span
class="cmitt-10x-x-109">M</span><span
class="cmmi-10x-x-109">></span>
<!--l. 23--><p class="noindent" ><span
class="cmbx-10x-x-109">DESCRIPTION</span>
<!--l. 23--><p class="indent" > This is the Multi-activity Deterministic Model (MDM). In this model each
node <span
class="cmmi-10x-x-109">i </span>is considered active if it was active in the reference multiplex, maintains
the same value of node activity <span
class="cmmi-10x-x-109">B</span><sub><span
class="cmmi-8">i</span></sub> (i.e., the number of layers in which it was
active) and is associated an activity vector sampled uniformly at random from
the <span
class="cmex-10x-x-109">(</span><span
class="cmmi-8">M</span>
<span
class="cmmi-8">B</span><sub><span
class="cmmi-6">i</span></sub><span
class="cmex-10x-x-109">)</span>
possible activity vectors with <span
class="cmmi-10x-x-109">B</span><sub><span
class="cmmi-8">i</span></sub> non-null entries.
<!--l. 23--><p class="indent" > The file <span
class="cmti-10x-x-109">Bi</span><span
class="cmti-10x-x-109">_file </span>is in the format:
<!--l. 23--><p class="indent" >   <span
class="cmti-10x-x-109">Bi N(Bi)</span>
<!--l. 23--><p class="indent" > where <span
class="cmti-10x-x-109">Bi </span>is a value of node activity and <span
class="cmti-10x-x-109">N(Bi) </span>is the number of nodes which
had node activity equaly to <span
class="cmti-10x-x-109">Bi </span>in the reference multiplex.
<!--l. 23--><p class="indent" > The parameter <span
class="cmti-10x-x-109">M </span>is the number of layers in the multiplex.
<!--l. 34--><p class="noindent" ><span
class="cmbx-10x-x-109">OUTPUT</span>
<!--l. 34--><p class="indent" > The program prints on <span
class="cmtt-10x-x-109">stdout </span>a distribution of bit-strings, in the
format:
<!--l. 34--><p class="indent" >   <span
class="cmti-10x-x-109">Bi bitstring count</span>
<!--l. 34--><p class="indent" > where <span
class="cmti-10x-x-109">bitstring </span>is the activity bitstring, <span
class="cmti-10x-x-109">Bi </span>is the number of non-zero entries
of <span
class="cmti-10x-x-109">bitstring </span>and <span
class="cmti-10x-x-109">count </span>is the number of times that <span
class="cmti-10x-x-109">bitstrings </span>appear in the null
model.
<!--l. 37--><p class="noindent" ><span
class="cmbx-10x-x-109">REFERENCE</span>
<!--l. 37--><p class="indent" > V. Nicosia, V. Latora, “Measuring and modeling correlations in multiplex
networks”, <span
class="cmti-10x-x-109">Phys. Rev. E </span><span
class="cmbx-10x-x-109">92</span>, 032805 (2015).
<!--l. 37--><p class="indent" > Link to paper: <a
href="http://journals.aps.org/pre/abstract/10.1103/PhysRevE.92.032805" class="url" ><span
class="cmtt-10x-x-109">http://journals.aps.org/pre/abstract/10.1103/PhysRevE.92.032805</span></a>
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