Difference between revisions of "Template:LMU-TUM Munich ModelCode2"

 
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<div class="cell border-box-sizing code_cell rendered">
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<div class="prompt input_prompt">In&nbsp;[153]:</div>
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<div class=" highlight hl-ipython2"><pre><span></span><span class="n">_</span><span class="o">=</span><span class="n">random_graph</span><span class="p">(</span><span class="n">cell_graph</span><span class="p">,</span> <span class="mi">30</span><span class="p">,</span> <span class="mi">120</span><span class="p">,</span> <span class="n">n_cell_binding</span><span class="o">=</span><span class="mi">400</span><span class="p">,</span> <span class="n">n_protein_binding</span><span class="o">=</span><span class="mi">4</span><span class="p">,</span>
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              <span class="n">concentration</span><span class="o">=</span><span class="mf">0.02</span><span class="p">,</span> <span class="n">reactivity</span><span class="o">=</span><span class="mf">0.1</span><span class="p">,</span> <span class="n">mobility</span><span class="o">=</span><span class="mf">0.05</span><span class="p">,</span> <span class="n">max_time</span><span class="o">=</span><span class="mf">5.0</span><span class="p">)</span>
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</pre></div>
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</div>
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 +
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
 +
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 +
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 +
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 +
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gg==
 +
"
 +
>
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<div class="inner_cell">
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 +
<p>Hmmm somehow there are many individual clusters... Maybe we can increase the number of networking proteins</p>
 +
 +
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Line 9,300: Line 15,588:
 
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<div class="prompt input_prompt">In&nbsp;[155]:</div>
 
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    <div class="input_area">
 
<div class=" highlight hl-ipython2"><pre><span></span><span class="n">_</span><span class="o">=</span><span class="n">random_graph</span><span class="p">(</span><span class="n">cell_graph</span><span class="p">,</span> <span class="mi">30</span><span class="p">,</span> <span class="mi">200</span><span class="p">,</span> <span class="n">n_cell_binding</span><span class="o">=</span><span class="mi">400</span><span class="p">,</span> <span class="n">n_protein_binding</span><span class="o">=</span><span class="mi">4</span><span class="p">,</span>
 
              <span class="n">concentration</span><span class="o">=</span><span class="mf">0.02</span><span class="p">,</span> <span class="n">reactivity</span><span class="o">=</span><span class="mf">0.1</span><span class="p">,</span> <span class="n">mobility</span><span class="o">=</span><span class="mf">0.05</span><span class="p">,</span> <span class="n">max_time</span><span class="o">=</span><span class="mf">10.0</span><span class="p">)</span>
 
</pre></div>
 
 
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AAAAAAAAAADAWe69h35jh6PVAAAAAElFTkSuQmCC
 
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<p>Great! Now everything is connected!</p>
 
 
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<h3 id="Lots-of-eperiments">Lots of eperiments<a class="anchor-link" href="#Lots-of-eperiments">&#182;</a></h3>
 
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<p>But maybe we need the reaction to happen fast. So lets put the simulated time back to 5 and try out a lot of different NP concentrations.</p>
 
<p>And using graph theoretical metrics we can maybe find a sweet spot with the perfect amount of protein for a certain amount of cells.</p>
 
<p>But first let's turn of the drawing</p>
 
 
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<div class="prompt input_prompt">In&nbsp;[156]:</div>
 
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<div class=" highlight hl-ipython2"><pre><span></span><span class="n">draw</span> <span class="o">=</span> <span class="bp">False</span>
 
</pre></div>
 
 
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<div class="prompt input_prompt">In&nbsp;[169]:</div>
 
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<div class=" highlight hl-ipython2"><pre><span></span><span class="n">results</span><span class="o">=</span><span class="p">[]</span>
 
<span class="n">draw</span><span class="o">=</span><span class="bp">False</span>
 
<span class="n">n_cells</span><span class="o">=</span><span class="mi">30</span>
 
<span class="k">for</span> <span class="n">n_proteins</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="o">-</span><span class="mf">1.5</span><span class="p">,</span><span class="mf">4.0</span><span class="p">,</span><span class="mf">0.1</span><span class="p">):</span>
 
    <span class="n">n_proteins</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="n">n_cells</span><span class="o">*</span><span class="mi">10</span><span class="o">**</span><span class="n">n_proteins</span><span class="p">)</span>
 
    <span class="n">g</span><span class="p">,</span><span class="n">cells</span><span class="p">,</span><span class="n">proteins</span> <span class="o">=</span> <span class="n">random_graph</span><span class="p">(</span><span class="n">cell_graph</span><span class="p">,</span> <span class="n">n_cells</span><span class="p">,</span> <span class="n">n_proteins</span><span class="p">,</span> <span class="n">n_cell_binding</span><span class="o">=</span><span class="mi">400</span><span class="p">,</span> <span class="n">n_protein_binding</span><span class="o">=</span><span class="mi">4</span><span class="p">,</span>
 
                                    <span class="n">concentration</span><span class="o">=</span><span class="mf">0.02</span><span class="p">,</span> <span class="n">reactivity</span><span class="o">=</span><span class="mf">0.1</span><span class="p">,</span> <span class="n">mobility</span><span class="o">=</span><span class="mf">0.05</span><span class="p">,</span> <span class="n">max_time</span><span class="o">=</span><span class="mf">1.0</span><span class="p">)</span>
 
   
 
    <span class="n">global_clustering</span> <span class="o">=</span> <span class="n">clustering</span><span class="o">.</span><span class="n">global_clustering</span><span class="p">(</span><span class="n">g</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span>
 
   
 
    <span class="n">tmp</span><span class="o">=</span><span class="n">graph_tool</span><span class="o">.</span><span class="n">topology</span><span class="o">.</span><span class="n">max_cardinality_matching</span><span class="p">(</span><span class="n">g</span><span class="p">)</span>
 
    <span class="n">n_max_matching</span> <span class="o">=</span> <span class="n">tmp</span><span class="o">.</span><span class="n">count</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span>
 
   
 
    <span class="n">max_shortest_path</span> <span class="o">=</span> <span class="n">graph_tool</span><span class="o">.</span><span class="n">topology</span><span class="o">.</span><span class="n">pseudo_diameter</span><span class="p">(</span><span class="n">g</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span>
 
   
 
    <span class="n">tmp</span><span class="o">=</span><span class="n">graph_tool</span><span class="o">.</span><span class="n">topology</span><span class="o">.</span><span class="n">label_largest_component</span><span class="p">(</span><span class="n">g</span><span class="p">)</span>
 
    <span class="n">biggest_cluster</span> <span class="o">=</span> <span class="n">tmp</span><span class="o">.</span><span class="n">get_array</span><span class="p">()</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
 
   
 
    <span class="n">tmp</span> <span class="o">=</span> <span class="n">graph_tool</span><span class="o">.</span><span class="n">topology</span><span class="o">.</span><span class="n">label_components</span><span class="p">(</span><span class="n">g</span><span class="p">)[</span><span class="mi">1</span><span class="p">]</span>
 
    <span class="n">tmp</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sort</span><span class="p">(</span><span class="n">tmp</span><span class="p">)[::</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span>
 
    <span class="n">n_clusters</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span>
 
    <span class="n">biggest_cluster</span> <span class="o">=</span> <span class="n">tmp</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
 
    <span class="n">mean_cluster</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span>
 
   
 
   
 
    <span class="n">n_free_protein_bindings</span> <span class="o">=</span> <span class="mi">0</span>
 
    <span class="n">n_free_proteins</span> <span class="o">=</span> <span class="mi">0</span>
 
    <span class="k">for</span> <span class="n">p</span> <span class="ow">in</span> <span class="n">proteins</span><span class="p">:</span>
 
        <span class="n">p_free</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="n">p</span><span class="o">.</span><span class="n">free_bindings</span><span class="p">))</span>
 
        <span class="n">n_free_protein_bindings</span> <span class="o">+=</span> <span class="n">p_free</span>
 
       
 
        <span class="k">if</span> <span class="n">p_free</span> <span class="o">==</span> <span class="nb">len</span><span class="p">(</span><span class="n">p</span><span class="o">.</span><span class="n">bindings</span><span class="p">):</span>
 
            <span class="n">n_free_proteins</span> <span class="o">+=</span> <span class="mi">1</span>
 
   
 
    <span class="n">n_free_cell_bindings</span> <span class="o">=</span> <span class="mi">0</span>
 
    <span class="n">n_free_cells</span> <span class="o">=</span> <span class="mi">0</span>
 
    <span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="n">cells</span><span class="p">:</span>
 
        <span class="n">c_free</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="n">c</span><span class="o">.</span><span class="n">free_bindings</span><span class="p">))</span>
 
        <span class="n">n_free_cell_bindings</span> <span class="o">+=</span> <span class="n">c_free</span>
 
        <span class="k">if</span> <span class="n">c_free</span> <span class="o">==</span> <span class="nb">len</span><span class="p">(</span><span class="n">c</span><span class="o">.</span><span class="n">bindings</span><span class="p">):</span>
 
            <span class="n">n_free_cells</span> <span class="o">+=</span> <span class="mi">1</span>
 
   
 
    <span class="n">results</span><span class="o">.</span><span class="n">append</span><span class="p">([</span><span class="n">n_proteins</span><span class="p">,</span> <span class="n">n_free_cells</span><span class="p">,</span> <span class="n">n_free_cell_bindings</span><span class="p">,</span> <span class="n">n_free_proteins</span><span class="p">,</span> <span class="n">n_free_protein_bindings</span><span class="p">,</span>
 
                    <span class="n">n_clusters</span><span class="p">,</span> <span class="n">mean_cluster</span><span class="p">,</span> <span class="n">biggest_cluster</span><span class="p">,</span> <span class="n">global_clustering</span><span class="p">,</span> <span class="n">max_shortest_path</span><span class="p">])</span>
 
    <span class="k">print</span> <span class="n">results</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span>
 
   
 
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<pre>[0, 30, 12000, 0, 0, 30, 1.0, 1, nan, 0]
 
[1, 29, 11996, 0, 0, 30, 1.0, 1, nan, 0]
 
[1, 29, 11996, 0, 0, 30, 1.0, 1, nan, 0]
 
[1, 29, 11996, 0, 0, 30, 1.0, 1, nan, 0]
 
[2, 27, 11992, 0, 0, 29, 1.0344827586206897, 2, 0.0, 1.0]
 
[3, 25, 11988, 0, 0, 28, 1.0714285714285714, 2, 0.0, 1.0]
 
[3, 26, 11988, 0, 0, 29, 1.0344827586206897, 2, 0.0, 0]
 
[4, 25, 11984, 0, 0, 29, 1.0344827586206897, 2, 0.0, 0]
 
[5, 24, 11980, 0, 0, 29, 1.0344827586206897, 2, 0.0, 0]
 
[7, 22, 11972, 0, 0, 29, 1.0344827586206897, 2, 0.0, 0]
 
[9, 21, 11964, 0, 0, 30, 1.0, 1, nan, 0]
 
[11, 13, 11956, 0, 0, 24, 1.25, 2, 0.0, 0]
 
[15, 14, 11940, 0, 0, 27, 1.1111111111111112, 3, 0.0, 0]
 
[18, 6, 11928, 0, 0, 20, 1.5, 3, 0.0, 0]
 
[23, 10, 11908, 0, 0, 26, 1.1538461538461537, 3, 0.0, 0]
 
[30, 3, 11880, 0, 0, 18, 1.6666666666666667, 4, 0.0, 0]
 
[37, 4, 11852, 0, 0, 20, 1.5, 3, 0.0, 0]
 
[47, 1, 11812, 0, 0, 13, 2.3076923076923075, 5, 0.0, 0]
 
[59, 0, 11770, 0, 6, 13, 2.3076923076923075, 7, 0.0, 1.0]
 
[75, 0, 11707, 0, 7, 19, 1.5789473684210527, 6, 0.17687074829931973, 1.0]
 
[94, 0, 11628, 0, 4, 10, 3.0, 9, 0.1424802110817942, 0]
 
[119, 1, 11530, 0, 6, 8, 3.75, 10, 0.1257189811010682, 3.0]
 
[150, 0, 11405, 0, 5, 5, 6.0, 21, 0.22478527607361964, 15.0]
 
[189, 0, 11263, 0, 19, 2, 15.0, 29, 0.15215517241379312, 17.0]
 
[238, 0, 11069, 0, 21, 3, 10.0, 22, 0.19888170156781054, 2.0]
 
[300, 0, 10823, 0, 23, 3, 10.0, 23, 0.37664686127615604, 2.0]
 
[377, 0, 10521, 0, 29, 1, 30.0, 30, 0.2738212366608643, 15.0]
 
[475, 0, 10142, 0, 42, 1, 30.0, 30, 0.3499592003263974, 11.0]
 
[598, 0, 9670, 0, 62, 1, 30.0, 30, 0.33487031700288183, 10.0]
 
[753, 0, 9069, 0, 81, 1, 30.0, 30, 0.46846999792503724, 10.0]
 
[948, 0, 8298, 0, 90, 1, 30.0, 30, 0.5131035980597988, 9.0]
 
[1194, 0, 7337, 0, 113, 1, 30.0, 30, 0.5400158292155982, 8.0]
 
[1503, 0, 6122, 0, 134, 1, 30.0, 30, 0.5746343396101824, 8.0]
 
[1892, 0, 4618, 0, 186, 1, 30.0, 30, 0.6053303642623806, 9.0]
 
[2382, 0, 2722, 0, 250, 1, 30.0, 30, 0.6215079423127517, 9.0]
 
[3000, 0, 608, 0, 608, 1, 30.0, 30, 0.6223426197506082, 7.0]
 
[3776, 0, 290, 0, 3394, 1, 30.0, 30, 0.45031431967170227, 13.0]
 
[4754, 0, 212, 27, 7228, 1, 30.0, 30, 0.3959936635621117, 16.0]
 
[5985, 0, 212, 156, 12152, 1, 30.0, 30, 0.32378448294141343, 17.0]
 
[7535, 0, 70, 660, 18210, 1, 30.0, 30, 0.19459141681363903, 18.0]
 
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<div class="output_area"><div class="prompt"></div>
 
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<pre>
 
<span class="ansired">---------------------------------------------------------------------------</span>
 
<span class="ansired">KeyboardInterrupt</span>                        Traceback (most recent call last)
 
<span class="ansigreen">&lt;ipython-input-169-31496c86d87d&gt;</span> in <span class="ansicyan">&lt;module&gt;</span><span class="ansiblue">()</span>
 
<span class="ansigreen">      5</span>    n_proteins <span class="ansiyellow">=</span> int<span class="ansiyellow">(</span>n_cells<span class="ansiyellow">*</span><span class="ansicyan">10</span><span class="ansiyellow">**</span>n_proteins<span class="ansiyellow">)</span><span class="ansiyellow"></span>
 
<span class="ansigreen">      6</span>    g,cells,proteins = random_graph(cell_graph, n_cells, n_proteins, n_cell_binding=400, n_protein_binding=4,
 
<span class="ansigreen">----&gt; 7</span><span class="ansiyellow">                                    concentration=0.02, reactivity=0.1, mobility=0.05, max_time=1.0)
 
</span><span class="ansigreen">      8</span> <span class="ansiyellow"></span>
 
<span class="ansigreen">      9</span>    global_clustering <span class="ansiyellow">=</span> clustering<span class="ansiyellow">.</span>global_clustering<span class="ansiyellow">(</span>g<span class="ansiyellow">)</span><span class="ansiyellow">[</span><span class="ansicyan">0</span><span class="ansiyellow">]</span><span class="ansiyellow"></span>
 
 
<span class="ansigreen">&lt;ipython-input-144-8d61d150c73b&gt;</span> in <span class="ansicyan">random_graph</span><span class="ansiblue">(graph_method, n_cells, n_proteins, n_cell_binding, n_protein_binding, concentration, reactivity, mobility, max_time)</span>
 
<span class="ansigreen">      3</span> <span class="ansired">#    polymerize(cells,proteins)</span><span class="ansiyellow"></span><span class="ansiyellow"></span>
 
<span class="ansigreen">      4</span>    cells<span class="ansiyellow">,</span>proteins<span class="ansiyellow">=</span>init_monomers<span class="ansiyellow">(</span>n_cells<span class="ansiyellow">,</span> n_proteins<span class="ansiyellow">,</span> n_cell_binding <span class="ansiyellow">=</span> n_cell_binding<span class="ansiyellow">,</span> n_protein_binding <span class="ansiyellow">=</span> n_protein_binding<span class="ansiyellow">)</span><span class="ansiyellow"></span>
 
<span class="ansigreen">----&gt; 5</span><span class="ansiyellow">    </span>polymerize_spacial<span class="ansiyellow">(</span>cells<span class="ansiyellow">,</span> proteins<span class="ansiyellow">,</span> n_protein_binding<span class="ansiyellow">=</span>n_protein_binding<span class="ansiyellow">,</span> concentration<span class="ansiyellow">=</span>concentration<span class="ansiyellow">,</span> reactivity<span class="ansiyellow">=</span>reactivity<span class="ansiyellow">,</span> mobility<span class="ansiyellow">=</span>mobility<span class="ansiyellow">,</span> max_time<span class="ansiyellow">=</span>max_time<span class="ansiyellow">)</span><span class="ansiyellow"></span>
 
<span class="ansigreen">      6</span>    <span class="ansigreen">return</span> graph_method<span class="ansiyellow">(</span>cells<span class="ansiyellow">,</span>proteins<span class="ansiyellow">,</span>draw<span class="ansiyellow">)</span><span class="ansiyellow">,</span>cells<span class="ansiyellow">,</span>proteins<span class="ansiyellow"></span>
 
 
<span class="ansigreen">&lt;ipython-input-49-bba830e73fd1&gt;</span> in <span class="ansicyan">polymerize_spacial</span><span class="ansiblue">(cells, proteins, n_protein_binding, concentration, reactivity, mobility, max_time)</span>
 
<span class="ansigreen">    39</span>            cell <span class="ansiyellow">=</span> np<span class="ansiyellow">.</span>random<span class="ansiyellow">.</span>choice<span class="ansiyellow">(</span>candidate_cells<span class="ansiyellow">,</span> p<span class="ansiyellow">=</span>probabilities<span class="ansiyellow">)</span><span class="ansiyellow"></span>
 
<span class="ansigreen">    40</span>            <span class="ansigreen">try</span><span class="ansiyellow">:</span><span class="ansiyellow"></span>
 
<span class="ansigreen">---&gt; 41</span><span class="ansiyellow">                </span>cell<span class="ansiyellow">.</span>free_bindings<span class="ansiyellow">.</span>next<span class="ansiyellow">(</span><span class="ansiyellow">)</span><span class="ansiyellow"></span>
 
<span class="ansigreen">    42</span>            <span class="ansigreen">except</span> StopIteration<span class="ansiyellow">:</span><span class="ansiyellow"></span>
 
<span class="ansigreen">    43</span>                <span class="ansired"># no free bindings left in this cell</span><span class="ansiyellow"></span><span class="ansiyellow"></span>
 
 
<span class="ansigreen">/home/moses/ownCloud/Projekte/iGEM/modelling/monomers.pyc</span> in <span class="ansicyan">&lt;genexpr&gt;</span><span class="ansiblue">((b,))</span>
 
<span class="ansigreen">    15</span>    <span class="ansiyellow">@</span>property<span class="ansiyellow"></span>
 
<span class="ansigreen">    16</span>    <span class="ansigreen">def</span> free_bindings<span class="ansiyellow">(</span>self<span class="ansiyellow">)</span><span class="ansiyellow">:</span><span class="ansiyellow"></span>
 
<span class="ansigreen">---&gt; 17</span><span class="ansiyellow">        </span><span class="ansigreen">return</span> <span class="ansiyellow">(</span>b <span class="ansigreen">for</span> b <span class="ansigreen">in</span> self<span class="ansiyellow">.</span>bindings <span class="ansigreen">if</span> b<span class="ansiyellow">.</span>partner <span class="ansigreen">is</span> None<span class="ansiyellow">)</span><span class="ansiyellow"></span>
 
<span class="ansigreen">    18</span>        <span class="ansired">#return filter(lambda b: b.partner is None, self.bindings)</span><span class="ansiyellow"></span><span class="ansiyellow"></span>
 
<span class="ansigreen">    19</span> <span class="ansiyellow"></span>
 
 
<span class="ansired">KeyboardInterrupt</span>: </pre>
 
</div>
 
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</div>
 
 
</div>
 
<div class="cell border-box-sizing code_cell rendered">
 
<div class="input">
 
<div class="prompt input_prompt">In&nbsp;[170]:</div>
 
<div class="inner_cell">
 
    <div class="input_area">
 
<div class=" highlight hl-ipython2"><pre><span></span><span class="n">results</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">asarray</span><span class="p">(</span><span class="n">results</span><span class="p">)</span><span class="o">.</span><span class="n">T</span>
 
<span class="n">n_proteins</span><span class="o">=</span><span class="n">results</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
 
<span class="n">results</span><span class="o">=</span><span class="n">results</span><span class="p">[</span><span class="mi">1</span><span class="p">:]</span>
 
</pre></div>
 
 
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<div class="prompt input_prompt">In&nbsp;[177]:</div>
 
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    <div class="input_area">
 
<div class=" highlight hl-ipython2"><pre><span></span><span class="n">titles</span><span class="o">=</span><span class="p">[</span><span class="s2">&quot;Cells with some free binding sites left&quot;</span><span class="p">,</span>
 
        <span class="s2">&quot;Free cell binding sites left&quot;</span><span class="p">,</span>
 
        <span class="s2">&quot;NP with some free binding sites left&quot;</span><span class="p">,</span>
 
        <span class="s2">&quot;Free NPBS left&quot;</span><span class="p">,</span>
 
        <span class="s2">&quot;Number of clusters without outward connections&quot;</span><span class="p">,</span>
 
        <span class="s2">&quot;Mean size of all clusters&quot;</span><span class="p">,</span>
 
        <span class="s2">&quot;Size of biggest cluster&quot;</span><span class="p">,</span>
 
        <span class="s2">&quot;</span><span class="se">\&quot;</span><span class="s2">Global Clustering</span><span class="se">\&quot;</span><span class="s2"> Metric&quot;</span><span class="p">,</span>
 
        <span class="s2">&quot;Length of the shortest path between the two cells furthest apart&quot;</span><span class="p">]</span>
 
<span class="n">f</span><span class="p">,</span> <span class="n">axes</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">titles</span><span class="p">)</span><span class="o">/</span><span class="mi">2</span><span class="o">+</span><span class="mi">1</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span> <span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">16</span><span class="p">,</span><span class="mi">8</span><span class="o">*</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">titles</span><span class="p">)</span><span class="o">/</span><span class="mi">2</span><span class="o">+</span><span class="mi">1</span><span class="p">)))</span>
 
<span class="k">for</span> <span class="n">i</span><span class="p">,</span><span class="n">result</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">results</span><span class="p">):</span>
 
    <span class="n">ax</span> <span class="o">=</span> <span class="n">axes</span><span class="p">[</span><span class="n">i</span><span class="o">/</span><span class="mi">2</span><span class="p">,</span><span class="n">i</span><span class="o">%</span><span class="k">2</span>]
 
    <span class="n">ax</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="n">titles</span><span class="p">[</span><span class="n">i</span><span class="p">])</span>
 
    <span class="n">ax</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="n">n_proteins</span><span class="o">/</span><span class="n">n_cells</span><span class="p">)</span><span class="o">/</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mi">10</span><span class="p">),</span> <span class="n">result</span><span class="o">.</span><span class="n">T</span><span class="p">,</span><span class="s2">&quot;-x&quot;</span><span class="p">)</span>
 
    <span class="c1">#ax.set_xscale(&quot;log&quot;)</span>
 
    <span class="n">ax</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="s2">&quot;10^n_proteins per cell&quot;</span><span class="p">)</span>
 
   
 
</pre></div>
 
 
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<div class="output_area"><div class="prompt"></div>
 
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<pre>/usr/local/lib/python2.7/dist-packages/ipykernel/__main__.py:14: RuntimeWarning: divide by zero encountered in log
 
</pre>
 
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"
 
>
 
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<div class="prompt input_prompt">In&nbsp;[37]:</div>
 
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<div class=" highlight hl-ipython2"><pre><span></span><span class="n">stats</span><span class="o">.</span><span class="n">distance_histogram</span><span class="p">(</span><span class="n">g</span><span class="p">)</span>
 
</pre></div>
 
 
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<div class="output_area"><div class="prompt output_prompt">Out[37]:</div>
 
 
 
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<pre>[array([    0.,  4534.,  5366.]), array([0, 1, 2, 3], dtype=uint64)]</pre>
 
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<div class="prompt input_prompt">In&nbsp;[46]:</div>
 
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<div class=" highlight hl-ipython2"><pre><span></span><span class="n">tmp</span><span class="o">=</span><span class="n">graph_tool</span><span class="o">.</span><span class="n">topology</span><span class="o">.</span><span class="n">max_cardinality_matching</span><span class="p">(</span><span class="n">g</span><span class="p">)</span>
 
<span class="n">tmp</span><span class="o">.</span><span class="n">count</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span>
 
</pre></div>
 
 
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<div class="output_area"><div class="prompt output_prompt">Out[46]:</div>
 
 
 
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<pre>0</pre>
 
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<h3 id="Cells-and-Protein-bindings-vertices">Cells and Protein bindings vertices<a class="anchor-link" href="#Cells-and-Protein-bindings-vertices">&#182;</a></h3>
 
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<div class="prompt input_prompt">In&nbsp;[&nbsp;]:</div>
 
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    <div class="input_area">
 
<div class=" highlight hl-ipython2"><pre><span></span><span class="n">g</span> <span class="o">=</span> <span class="n">Graph</span><span class="p">(</span><span class="n">directed</span><span class="o">=</span><span class="bp">False</span><span class="p">)</span>
 
 
<span class="n">v_size</span> <span class="o">=</span> <span class="n">g</span><span class="o">.</span><span class="n">new_vertex_property</span><span class="p">(</span><span class="s2">&quot;int&quot;</span><span class="p">,</span><span class="n">val</span><span class="o">=</span><span class="mi">20</span><span class="p">)</span>
 
<span class="n">v_group</span> <span class="o">=</span> <span class="n">g</span><span class="o">.</span><span class="n">new_vertex_property</span><span class="p">(</span><span class="s2">&quot;int32_t&quot;</span><span class="p">)</span>
 
 
<span class="c1">#v_color = vprop_vint = g.new_vertex_property(&quot;vector&lt;int&gt;&quot;, vals=[])</span>
 
 
<span class="c1">#cell_vertices = list(g.add_vertex(n_cells))</span>
 
<span class="k">for</span> <span class="n">cell</span> <span class="ow">in</span> <span class="n">cells</span><span class="p">:</span>
 
    <span class="n">cell</span><span class="o">.</span><span class="n">vertex</span> <span class="o">=</span> <span class="n">g</span><span class="o">.</span><span class="n">add_vertex</span><span class="p">()</span>
 
    <span class="n">v_size</span><span class="p">[</span><span class="n">cell</span><span class="o">.</span><span class="n">vertex</span><span class="p">]</span> <span class="o">=</span> <span class="mi">100</span>
 
 
<span class="k">for</span> <span class="n">p</span> <span class="ow">in</span> <span class="n">proteins</span><span class="p">:</span>
 
    <span class="n">last_vertex</span> <span class="o">=</span> <span class="bp">None</span>
 
    <span class="k">for</span> <span class="n">b</span> <span class="ow">in</span> <span class="n">p</span><span class="o">.</span><span class="n">bindings</span><span class="p">:</span>
 
        <span class="n">b</span><span class="o">.</span><span class="n">vertex</span><span class="o">=</span><span class="n">g</span><span class="o">.</span><span class="n">add_vertex</span><span class="p">()</span>
 
        <span class="n">v_size</span><span class="p">[</span><span class="n">b</span><span class="o">.</span><span class="n">vertex</span><span class="p">]</span> <span class="o">=</span> <span class="mi">10</span>
 
        <span class="n">v_group</span><span class="p">[</span><span class="n">cell</span><span class="o">.</span><span class="n">vertex</span><span class="p">]</span> <span class="o">=</span> <span class="n">p</span><span class="o">.</span><span class="n">id</span>
 
 
        <span class="c1">#intraprotein connections</span>
 
        <span class="k">if</span> <span class="n">last_vertex</span> <span class="ow">is</span> <span class="ow">not</span> <span class="bp">None</span><span class="p">:</span>
 
            <span class="n">g</span><span class="o">.</span><span class="n">add_edge</span><span class="p">(</span><span class="n">b</span><span class="o">.</span><span class="n">vertex</span><span class="p">,</span><span class="n">last_vertex</span><span class="p">)</span>
 
        <span class="n">last_vertex</span><span class="o">=</span><span class="n">b</span><span class="o">.</span><span class="n">vertex</span>
 
        <span class="c1">#cell connections</span>
 
        <span class="k">if</span> <span class="n">b</span><span class="o">.</span><span class="n">partner</span> <span class="ow">is</span> <span class="ow">not</span> <span class="bp">None</span><span class="p">:</span>
 
            <span class="n">cell_vertex</span> <span class="o">=</span> <span class="n">b</span><span class="o">.</span><span class="n">partner</span><span class="o">.</span><span class="n">parent</span><span class="o">.</span><span class="n">vertex</span>
 
            <span class="n">g</span><span class="o">.</span><span class="n">add_edge</span><span class="p">(</span><span class="n">b</span><span class="o">.</span><span class="n">vertex</span><span class="p">,</span><span class="n">cell_vertex</span><span class="p">)</span>
 
           
 
       
 
<span class="n">pos</span><span class="o">=</span><span class="n">sfdp_layout</span><span class="p">(</span><span class="n">g</span><span class="p">,</span><span class="n">groups</span><span class="o">=</span><span class="n">v_group</span><span class="p">)</span>
 
<span class="c1">#graph_draw(g, vertex_text=g.vertex_index, vertex_font_size=18, output=&quot;/tmp/graph.png&quot;,</span>
 
<span class="c1">#            output_size=(2000, 2000))</span>
 
<span class="n">graph_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="n">pos</span><span class="p">,</span><span class="n">edge_pen_width</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">vertex_text</span><span class="o">=</span><span class="n">g</span><span class="o">.</span><span class="n">vertex_index</span><span class="p">,</span> <span class="n">vertex_size</span><span class="o">=</span><span class="n">v_size</span><span class="p">,</span> <span class="n">vertex_font_size</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">output_size</span><span class="o">=</span><span class="p">(</span><span class="mi">2000</span><span class="p">,</span> <span class="mi">2000</span><span class="p">))</span>
 
<span class="c1">#graphviz_draw(g, elen=100, vsize=v_size, size=(2000, 2000))</span>
 
</pre></div>
 
 
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Latest revision as of 03:53, 20 October 2016


In [153]:
<span></span><span class="n">_</span><span class="o">=</span><span class="n">random_graph</span><span class="p">(</span><span class="n">cell_graph</span><span class="p">,</span> <span class="mi">30</span><span class="p">,</span> <span class="mi">120</span><span class="p">,</span> <span class="n">n_cell_binding</span><span class="o">=</span><span class="mi">400</span><span class="p">,</span> <span class="n">n_protein_binding</span><span class="o">=</span><span class="mi">4</span><span class="p">,</span> 
               <span class="n">concentration</span><span class="o">=</span><span class="mf">0.02</span><span class="p">,</span> <span class="n">reactivity</span><span class="o">=</span><span class="mf">0.1</span><span class="p">,</span> <span class="n">mobility</span><span class="o">=</span><span class="mf">0.05</span><span class="p">,</span> <span class="n">max_time</span><span class="o">=</span><span class="mf">5.0</span><span class="p">)</span>



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AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAHB9+T8e7GNX+OElFAAAAABJRU5ErkJg gg== " >

Hmmm somehow there are many individual clusters... Maybe we can increase the number of networking proteins

In [154]:
<span></span><span class="n">_</span><span class="o">=</span><span class="n">random_graph</span><span class="p">(</span><span class="n">cell_graph</span><span class="p">,</span> <span class="mi">30</span><span class="p">,</span> <span class="mi">200</span><span class="p">,</span> <span class="n">n_cell_binding</span><span class="o">=</span><span class="mi">400</span><span class="p">,</span> <span class="n">n_protein_binding</span><span class="o">=</span><span class="mi">4</span><span class="p">,</span> 
               <span class="n">concentration</span><span class="o">=</span><span class="mf">0.02</span><span class="p">,</span> <span class="n">reactivity</span><span class="o">=</span><span class="mf">0.1</span><span class="p">,</span> <span class="n">mobility</span><span class="o">=</span><span class="mf">0.05</span><span class="p">,</span> <span class="n">max_time</span><span class="o">=</span><span class="mf">5.0</span><span class="p">)</span>



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Ok, that ooks a bit better already. What if we give it a bit more time to react?