diff --git a/doc/KADMOS.html b/doc/KADMOS.html
index eb1515300bcfed1c875b9b53b79416cbeb11e6db..3eafebfd27c31e42fa5fd385d0e396f5fbd6e40e 100644
--- a/doc/KADMOS.html
+++ b/doc/KADMOS.html
@@ -106,10 +106,16 @@
<span class="gp">>>> </span><span class="n">add_contact</span><span class="p">(</span><span class="s1">'Maaike de Wit'</span><span class="p">,</span> <span class="s1">'M.D.deWit@student.tudelft.nl'</span><span class="p">,</span> <span class="s1">'mddewit'</span><span class="p">,</span> <span class="n">company</span><span class="o">=</span><span class="s1">'TU Delft'</span><span class="p">,</span> <span class="n">roles</span><span class="o">=</span><span class="n">roles</span><span class="p">)</span>
</pre></div>
</div>
-<p>In case the contact uid already exists the old contact attributes are conserved and only new roles are added to
-the roles already present for that contact. To change old contact information, this has to be adjusted in the
-XML-file from which the old contact information is loaded.</p>
-<p>To add (more) roles to the existing contact, it is recommended to use the method: add_contact_roles()</p>
+<div class="admonition note">
+<p class="first admonition-title">Note</p>
+<p class="last">In case the contact uid already exists the old contact attributes are conserved and only new roles
+are added to the roles already present for that contact. To change old contact information, this has to be
+adjusted in the XML-file from which the old contact information is loaded.</p>
+</div>
+<div class="admonition hint">
+<p class="first admonition-title">Hint</p>
+<p class="last">To add (more) roles to the existing contact, it is recommended to use the method: add_contact_roles()</p>
+</div>
</dd></dl>
<dl class="method">
@@ -145,7 +151,10 @@ XML-file from which the old contact information is loaded.</p>
<span class="gp">>>> </span><span class="n">add_contact</span><span class="p">(</span><span class="s1">'mddewit'</span><span class="p">,</span> <span class="n">company</span><span class="o">=</span><span class="s1">'TU Delft'</span><span class="p">,</span> <span class="n">roles</span><span class="o">=</span><span class="n">roles</span><span class="p">)</span>
</pre></div>
</div>
-<p>This method only works for existing contacts. To add a contact use the method: add_contact()</p>
+<div class="admonition hint">
+<p class="first admonition-title">Hint</p>
+<p class="last">This method only works for existing contacts. To add a contact use the method: add_contact()</p>
+</div>
</dd></dl>
<dl class="method">
@@ -204,7 +213,7 @@ XML-file from which the old contact information is loaded.</p>
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
<li><strong>dc_uid</strong> (<em>str</em>) – uid of the design competence</li>
-<li><strong>single_or_multi_execution</strong> (<em>'single'</em><em> or </em><em>'multiple'</em>) – execution type</li>
+<li><strong>single_or_multi_execution</strong> (<em>str</em>) – execution type. Choose from ‘single’ or ‘multiple’.</li>
<li><strong>job_name</strong> (<em>str</em>) – job name of the design competence</li>
<li><strong>remote_engineer</strong> (<em>str</em>) – contact uid of remote engineering of the design competence</li>
<li><strong>notification_message</strong> (<em>str</em>) – message to notify remote_engineer</li>
@@ -216,8 +225,9 @@ XML-file from which the old contact information is loaded.</p>
</table>
<p>Example use:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">single_or_multi</span> <span class="o">=</span> <span class="s2">"single"</span>
-<span class="gp">>>> </span><span class="n">job_name</span> <span class="o">=</span> <span class="s1">'job_</span><span class="si">{}</span><span class="s1">'</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">fpg</span><span class="o">.</span><span class="n">node</span><span class="p">[</span><span class="n">node</span><span class="p">][</span><span class="s1">'label'</span><span class="p">]</span><span class="o">.</span><span class="n">replace</span><span class="p">(</span><span class="s1">' '</span><span class="p">,</span> <span class="s1">''</span><span class="p">))</span>
-<span class="gp">>>> </span><span class="n">notification_message</span> <span class="o">=</span> <span class="s1">'Hi, could you please run this tool </span><span class="si">{}</span><span class="s1"> for me for my </span><span class="si">{}</span><span class="s1"> AGILE workflow '</span> <span class="s1">'execution. Thanks.'</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">fpg</span><span class="o">.</span><span class="n">node</span><span class="p">[</span><span class="n">node</span><span class="p">][</span><span class="s1">'label'</span><span class="p">]</span><span class="o">.</span><span class="n">replace</span><span class="p">(</span><span class="s1">' '</span><span class="p">,</span> <span class="s1">''</span><span class="p">),</span> <span class="n">architecture</span><span class="p">)</span>
+<span class="gp">>>> </span><span class="n">job_name</span> <span class="o">=</span> <span class="s1">'job_</span><span class="si">{}</span><span class="s1">'</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">fpg</span><span class="o">.</span><span class="n">nodes</span><span class="p">[</span><span class="n">node</span><span class="p">][</span><span class="s1">'label'</span><span class="p">]</span><span class="o">.</span><span class="n">replace</span><span class="p">(</span><span class="s1">' '</span><span class="p">,</span> <span class="s1">''</span><span class="p">))</span>
+<span class="gp">>>> </span><span class="n">notification_message</span> <span class="o">=</span> <span class="s1">'Hi, could you please run this tool </span><span class="si">{}</span><span class="s1"> for me for my </span><span class="si">{}</span><span class="s1"> AGILE workflow '</span>
+<span class="gp">>>> </span> <span class="s1">'execution. Thanks.'</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">fpg</span><span class="o">.</span><span class="n">nodes</span><span class="p">[</span><span class="n">node</span><span class="p">][</span><span class="s1">'label'</span><span class="p">]</span><span class="o">.</span><span class="n">replace</span><span class="p">(</span><span class="s1">' '</span><span class="p">,</span> <span class="s1">''</span><span class="p">),</span> <span class="n">architecture</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">fpg</span><span class="o">.</span><span class="n">add_dc_remote_component_info</span><span class="p">(</span><span class="n">node</span><span class="p">,</span> <span class="n">single_or_multi</span><span class="p">,</span> <span class="n">job_name</span><span class="p">,</span> <span class="s1">'ivangent'</span><span class="p">,</span> <span class="n">notification_message</span><span class="p">,</span>
<span class="gp">>>> </span> <span class="n">data_exchange_dict</span><span class="o">=</span><span class="p">{</span><span class="s1">'urlsite'</span><span class="p">:</span> <span class="s1">'some_url'</span><span class="p">,</span>
<span class="gp">>>> </span> <span class="s1">'folder'</span><span class="p">:</span> <span class="s1">'some_folder'</span><span class="p">})</span>
@@ -261,22 +271,24 @@ XML-file from which the old contact information is loaded.</p>
<dt id="kadmos.graph.graph_kadmos.KadmosGraph.add_edge">
<code class="descname">add_edge</code><span class="sig-paren">(</span><em>u</em>, <em>v</em>, <em>attr_dict=None</em>, <em>**attr</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.add_edge" title="Permalink to this definition">¶</a></dt>
<dd><p>Add an edge between u and v.</p>
-<p>The nodes u and v will be automatically added if they are not already in the graph.</p>
-<p>Adding an existing edge results in an update of the edge data.</p>
-<p>Edge attributes can be specified with keywords or by directly accessing the edge’s attribute dictionary.
-See examples below.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
-<li><strong>v</strong> (<em>u</em><em>,</em>) – nodes</li>
-<li><strong>attr</strong> (<em>Edge data</em><em> (or </em><em>labels</em><em> or </em><em>objects</em><em>) </em><em>can be assigned using keyword arguments.</em>) – keyword arguments, optional</li>
+<li><strong>u</strong> (<em>can be</em><em>, </em><em>for example</em><em>, </em><em>strings</em><em> or </em><em>numbers. Nodes must be hashable</em><em> (</em><em>and not None</em><em>) </em><em>Python objects.</em>) – node</li>
+<li><strong>v</strong> (<em>see u</em>) – node</li>
+<li><strong>attr_dict</strong> (<em>str</em>) – keyword arguments</li>
+<li><strong>attr</strong> (<em>str</em>) – edge data (or labels or objects) can be assigned using keyword arguments.</li>
</ul>
</td>
</tr>
</tbody>
</table>
+<p>The nodes u and v will be automatically added if they are not already in the graph.</p>
+<p>Adding an existing edge results in an update of the edge data.</p>
+<p>Edge attributes can be specified with keywords or by directly accessing the edge’s attribute dictionary.
+See examples below.</p>
<p>The following examples both add the edge e=(1,2) to graph G:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></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="c1"># or DiGraph, MultiGraph, MultiDiGraph, etc</span>
<span class="gp">>>> </span><span class="n">e</span> <span class="o">=</span> <span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">)</span>
@@ -298,101 +310,6 @@ numerical value. Associate date to edge using keywords:</p>
</div>
</dd></dl>
-<dl class="method">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.add_edges_from">
-<code class="descname">add_edges_from</code><span class="sig-paren">(</span><em>ebunch_to_add</em>, <em>**attr</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.add_edges_from" title="Permalink to this definition">¶</a></dt>
-<dd><p>Add all the edges in ebunch_to_add.</p>
-<dl class="docutils">
-<dt>ebunch_to_add <span class="classifier-delimiter">:</span> <span class="classifier">container of edges</span></dt>
-<dd>Each edge given in the container will be added to the
-graph. The edges must be given as 2-tuples (u, v) or
-3-tuples (u, v, d) where d is a dictionary containing edge data.</dd>
-<dt>attr <span class="classifier-delimiter">:</span> <span class="classifier">keyword arguments, optional</span></dt>
-<dd>Edge data (or labels or objects) can be assigned using
-keyword arguments.</dd>
-</dl>
-<p>add_edge : add a single edge
-add_weighted_edges_from : convenient way to add weighted edges</p>
-<p>Adding the same edge twice has no effect but any edge data
-will be updated when each duplicate edge is added.</p>
-<p>Edge attributes specified in an ebunch take precedence over
-attributes specified via keyword arguments.</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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="c1"># or DiGraph, MultiGraph, MultiDiGraph, etc</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">add_edges_from</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="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">)])</span> <span class="c1"># using a list of edge tuples</span>
-<span class="gp">>>> </span><span class="n">e</span> <span class="o">=</span> <span class="nb">zip</span><span class="p">(</span><span class="nb">range</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">3</span><span class="p">),</span> <span class="nb">range</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">4</span><span class="p">))</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">add_edges_from</span><span class="p">(</span><span class="n">e</span><span class="p">)</span> <span class="c1"># Add the path graph 0-1-2-3</span>
-</pre></div>
-</div>
-<p>Associate data to edges</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">add_edges_from</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="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">)],</span> <span class="n">weight</span><span class="o">=</span><span class="mi">3</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">add_edges_from</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="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">4</span><span class="p">)],</span> <span class="n">label</span><span class="o">=</span><span class="s1">'WN2898'</span><span class="p">)</span>
-</pre></div>
-</div>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.add_equation">
-<code class="descname">add_equation</code><span class="sig-paren">(</span><em>edge_or_node</em>, <em>equation</em>, <em>language='Python'</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.add_equation" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to add an equation to an output edge.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
-<li><strong>edge_or_node</strong> (<em>list</em><em>, </em><em>str</em>) – graph edge or node under consideration.</li>
-<li><strong>equation</strong> (<em>str</em>) – equation to be added</li>
-<li><strong>language</strong> (<em>str</em>) – equation language used for the equation</li>
-</ul>
-</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.add_equation_label">
-<code class="descname">add_equation_label</code><span class="sig-paren">(</span><em>edge</em>, <em>labeling_method='node_label'</em>, <em>language='Python'</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.add_equation_label" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to add an equation label to a edge that can (safely) be used as reference in an equation.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
-<li><strong>edge</strong> (<em>str</em>) – graph edge under consideration</li>
-<li><strong>labeling_method</strong> (<em>str</em>) – select method for automatic label string determination (node_id or node_label)</li>
-<li><strong>language</strong> (<em>str</em>) – equation language used for the equation label</li>
-</ul>
-</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">label</p>
-</td>
-</tr>
-<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last">str</p>
-</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.add_equation_labels">
-<code class="descname">add_equation_labels</code><span class="sig-paren">(</span><em>nodes</em>, <em>language='Python'</em>, <em>labeling_method='node_id'</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.add_equation_labels" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to add equation labels automatically to all input edges connected to the specified list of nodes</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
-<li><strong>nodes</strong> (<em>list</em>) – list of nodes</li>
-<li><strong>language</strong> (<em>str</em>) – equation language used for the equation label</li>
-<li><strong>labeling_method</strong> (<em>str</em>) – select method for automatic label string determination (node_id or node_label)</li>
-</ul>
-</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
<dl class="method">
<dt id="kadmos.graph.graph_kadmos.KadmosGraph.add_instance">
<code class="descname">add_instance</code><span class="sig-paren">(</span><em>node</em>, <em>instance=None</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.add_instance" title="Permalink to this definition">¶</a></dt>
@@ -412,26 +329,6 @@ attributes specified via keyword arguments.</p>
<p>In case the default is used the instance added is the highest current instance + 1.</p>
</dd></dl>
-<dl class="method">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.add_mathematical_function">
-<code class="descname">add_mathematical_function</code><span class="sig-paren">(</span><em>input_nodes</em>, <em>function_node</em>, <em>output_nodes</em>, <em>function_type='regular'</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.add_mathematical_function" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to add mathematical function to graph</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
-<li><strong>input_nodes</strong> (<em>str</em><em>, </em><em>list</em>) – input nodes of the mathematical function</li>
-<li><strong>function_node</strong> (<em>str</em>) – function node of the mathematical function</li>
-<li><strong>output_nodes</strong> (<em>str</em><em>, </em><em>list</em>) – output nodes of the mathematical function</li>
-<li><strong>function_type</strong> (<em>'regular'</em><em> or </em><em>'consistency'</em>) – type of function, optional (default=’regular’)</li>
-</ul>
-</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
<dl class="method">
<dt id="kadmos.graph.graph_kadmos.KadmosGraph.add_node">
<code class="descname">add_node</code><span class="sig-paren">(</span><em>n</em>, <em>attr_dict=None</em>, <em>**attr</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.add_node" title="Permalink to this definition">¶</a></dt>
@@ -443,7 +340,7 @@ attributes specified via keyword arguments.</p>
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
<li><strong>n</strong> (<em>A node can be any hashable Python object except None.</em>) – node</li>
<li><strong>attr_dict</strong> (<em>dict</em>) – dictionary of attribute keyword arguments.</li>
-<li><strong>attr</strong> (<em>Set</em><em> or </em><em>change node attributes using attr_dict.</em>) – keyword arguments, optional</li>
+<li><strong>attr</strong> (<em>str</em><em>, </em><em>dict</em>) – Set or change node attributes using attr_dict.</li>
</ul>
</td>
</tr>
@@ -463,53 +360,17 @@ attributes specified via keyword arguments.</p>
<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="mi">3</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="mf">0.4</span><span class="p">,</span> <span class="n">UTM</span><span class="o">=</span><span class="p">(</span><span class="s1">'13S'</span><span class="p">,</span> <span class="mi">382871</span><span class="p">,</span> <span class="mi">3972649</span><span class="p">))</span>
</pre></div>
</div>
-<p>Notes:</p>
-<p>A hashable object is one that can be used as a key in a Python
+<div class="admonition note">
+<p class="first admonition-title">Note</p>
+<p class="last">A hashable object is one that can be used as a key in a Python
dictionary. This includes strings, numbers, tuples of strings
and numbers, etc.</p>
-<p>On many platforms hashable items also include mutables such as
+</div>
+<div class="admonition note">
+<p class="first admonition-title">Note</p>
+<p class="last">On many platforms hashable items also include mutables such as
NetworkX Graphs, though one should be careful that the hash
doesn’t change on mutables.</p>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.add_nodes_from">
-<code class="descname">add_nodes_from</code><span class="sig-paren">(</span><em>nodes_for_adding</em>, <em>**attr</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.add_nodes_from" title="Permalink to this definition">¶</a></dt>
-<dd><p>Add multiple nodes.</p>
-<dl class="docutils">
-<dt>nodes_for_adding <span class="classifier-delimiter">:</span> <span class="classifier">iterable container</span></dt>
-<dd>A container of nodes (list, dict, set, etc.).
-OR
-A container of (node, attribute dict) tuples.
-Node attributes are updated using the attribute dict.</dd>
-<dt>attr <span class="classifier-delimiter">:</span> <span class="classifier">keyword arguments, optional (default= no attributes)</span></dt>
-<dd>Update attributes for all nodes in nodes.
-Node attributes specified in nodes as a tuple take
-precedence over attributes specified via keyword arguments.</dd>
-</dl>
-<p>add_node</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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="c1"># or DiGraph, MultiGraph, MultiDiGraph, etc</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">add_nodes_from</span><span class="p">(</span><span class="s1">'Hello'</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="n">K3</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="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">),</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="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="mi">0</span><span class="p">)])</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">add_nodes_from</span><span class="p">(</span><span class="n">K3</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="nb">sorted</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">(),</span> <span class="n">key</span><span class="o">=</span><span class="nb">str</span><span class="p">)</span>
-<span class="go">[0, 1, 2, 'H', 'e', 'l', 'o']</span>
-</pre></div>
-</div>
-<p>Use keywords to update specific node attributes for every node.</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">add_nodes_from</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="n">size</span><span class="o">=</span><span class="mi">10</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">add_nodes_from</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="n">weight</span><span class="o">=</span><span class="mf">0.4</span><span class="p">)</span>
-</pre></div>
-</div>
-<p>Use (node, attrdict) tuples to update attributes for specific nodes.</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">add_nodes_from</span><span class="p">([(</span><span class="mi">1</span><span class="p">,</span> <span class="nb">dict</span><span class="p">(</span><span class="n">size</span><span class="o">=</span><span class="mi">11</span><span class="p">)),</span> <span class="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="p">{</span><span class="s1">'color'</span><span class="p">:</span><span class="s1">'blue'</span><span class="p">})])</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">[</span><span class="mi">1</span><span class="p">][</span><span class="s1">'size'</span><span class="p">]</span>
-<span class="go">11</span>
-<span class="gp">>>> </span><span class="n">H</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">H</span><span class="o">.</span><span class="n">add_nodes_from</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="kc">True</span><span class="p">))</span>
-<span class="gp">>>> </span><span class="n">H</span><span class="o">.</span><span class="n">nodes</span><span class="p">[</span><span class="mi">1</span><span class="p">][</span><span class="s1">'size'</span><span class="p">]</span>
-<span class="go">11</span>
-</pre></div>
</div>
</dd></dl>
@@ -517,22 +378,6 @@ precedence over attributes specified via keyword arguments.</dd>
<dt id="kadmos.graph.graph_kadmos.KadmosGraph.add_objective_function_by_nodes">
<code class="descname">add_objective_function_by_nodes</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.add_objective_function_by_nodes" title="Permalink to this definition">¶</a></dt>
<dd><p>This function adds objective functions to the graph using lists of variable nodes.</p>
-<p>Each list produces a separate objective function node in the graph. If the list if passed as a keyword argument,
-the keyword is taken as the name of the objective function node. Otherwise, a standard name will be given to the
-node. Each objective function node has one output variable, and takes the nodes given in the argument list as
-input nodes.</p>
-<p>If the provided nodes do not exist in the graph, a warning is given to the user on whether to continue the
-addition of the objective function to the graph using valid nodes.</p>
-<p>Example:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">unnamed_function</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="o">>></span><span class="nb">list</span> <span class="n">of</span> <span class="n">graph</span> <span class="n">nodes</span><span class="o"><<</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="n">named_obj_fcn</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="o">>></span><span class="nb">list</span> <span class="n">of</span> <span class="n">graph</span> <span class="n">nodes</span><span class="o"><<</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="n">MyGraph</span><span class="o">.</span><span class="n">add_objective_function_by_nodes</span><span class="p">(</span><span class="n">unnamed_function</span><span class="p">,</span> <span class="n">My_obj_fcn_name</span> <span class="o">=</span> <span class="n">named_obj_fcn</span><span class="p">)</span>
-</pre></div>
-</div>
-<p>The added objective function nodes can be queried by the attribute:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">Graph</span><span class="o">.</span><span class="n">node</span><span class="p">[</span><span class="n">node</span><span class="p">][</span><span class="s2">"name"</span><span class="p">]</span> <span class="o">==</span> <span class="s2">"Objective"</span>
-</pre></div>
-</div>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
@@ -551,91 +396,44 @@ addition of the objective function to the graph using valid nodes.</p>
</tr>
</tbody>
</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.add_weighted_edges_from">
-<code class="descname">add_weighted_edges_from</code><span class="sig-paren">(</span><em>ebunch_to_add</em>, <em>weight='weight'</em>, <em>**attr</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.add_weighted_edges_from" title="Permalink to this definition">¶</a></dt>
-<dd><p>Add weighted edges in <cite>ebunch_to_add</cite> with specified weight attr</p>
-<dl class="docutils">
-<dt>ebunch_to_add <span class="classifier-delimiter">:</span> <span class="classifier">container of edges</span></dt>
-<dd>Each edge given in the list or container will be added
-to the graph. The edges must be given as 3-tuples (u, v, w)
-where w is a number.</dd>
-<dt>weight <span class="classifier-delimiter">:</span> <span class="classifier">string, optional (default= ‘weight’)</span></dt>
-<dd>The attribute name for the edge weights to be added.</dd>
-<dt>attr <span class="classifier-delimiter">:</span> <span class="classifier">keyword arguments, optional (default= no attributes)</span></dt>
-<dd>Edge attributes to add/update for all edges.</dd>
-</dl>
-<p>add_edge : add a single edge
-add_edges_from : add multiple edges</p>
-<p>Adding the same edge twice for Graph/DiGraph simply updates
-the edge data. For MultiGraph/MultiDiGraph, duplicate edges
-are stored.</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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="c1"># or DiGraph, MultiGraph, MultiDiGraph, etc</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">add_weighted_edges_from</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="mf">3.0</span><span class="p">),</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="mf">7.5</span><span class="p">)])</span>
+<p>Each list produces a separate objective function node in the graph. If the list if passed as a keyword argument,
+the keyword is taken as the name of the objective function node. Otherwise, a standard name will be given to the
+node. Each objective function node has one output variable, and takes the nodes given in the argument list as
+input nodes.</p>
+<p>If the provided nodes do not exist in the graph, a warning is given to the user on whether to continue the
+addition of the objective function to the graph using valid nodes.</p>
+<p>Example:</p>
+<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">unnamed_function</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="o">>></span><span class="nb">list</span> <span class="n">of</span> <span class="n">graph</span> <span class="n">nodes</span><span class="o"><<</span><span class="p">)</span>
+<span class="gp">>>> </span><span class="n">named_obj_fcn</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="o">>></span><span class="nb">list</span> <span class="n">of</span> <span class="n">graph</span> <span class="n">nodes</span><span class="o"><<</span><span class="p">)</span>
+<span class="gp">>>> </span><span class="n">MyGraph</span><span class="o">.</span><span class="n">add_objective_function_by_nodes</span><span class="p">(</span><span class="n">unnamed_function</span><span class="p">,</span> <span class="n">My_obj_fcn_name</span> <span class="o">=</span> <span class="n">named_obj_fcn</span><span class="p">)</span>
</pre></div>
</div>
-</dd></dl>
-
-<dl class="attribute">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.adj">
-<code class="descname">adj</code><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.adj" title="Permalink to this definition">¶</a></dt>
-<dd><p>Graph adjacency object holding the neighbors of each node.</p>
-<p>This object is a read-only dict-like structure with node keys
-and neighbor-dict values. The neighbor-dict is keyed by neighbor
-to the edge-data-dict. So <cite>G.adj[3][2][‘color’] = ‘blue’</cite> sets
-the color of the edge <cite>(3, 2)</cite> to <cite>“blueâ€</cite>.</p>
-<p>Iterating over G.adj behaves like a dict. Useful idioms include
-<cite>for nbr, datadict in G.adj[n].items():</cite>.</p>
-<p>The neighbor information is also provided by subscripting the graph.
-So <cite>for nbr, foovalue in G[node].data(‘foo’, default=1):</cite> works.</p>
-<p>For directed graphs, <cite>G.adj</cite> holds outgoing (successor) info.</p>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.adjacency">
-<code class="descname">adjacency</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.adjacency" title="Permalink to this definition">¶</a></dt>
-<dd><p>Return an iterator over (node, adjacency dict) tuples for all nodes.</p>
-<p>For directed graphs, only outgoing neighbors/adjacencies are included.</p>
-<dl class="docutils">
-<dt>adj_iter <span class="classifier-delimiter">:</span> <span class="classifier">iterator</span></dt>
-<dd>An iterator over (node, adjacency dictionary) for all nodes in
-the graph.</dd>
-</dl>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">path_graph</span><span class="p">(</span><span class="mi">4</span><span class="p">)</span> <span class="c1"># or DiGraph, MultiGraph, MultiDiGraph, etc</span>
-<span class="gp">>>> </span><span class="p">[(</span><span class="n">n</span><span class="p">,</span> <span class="n">nbrdict</span><span class="p">)</span> <span class="k">for</span> <span class="n">n</span><span class="p">,</span> <span class="n">nbrdict</span> <span class="ow">in</span> <span class="n">G</span><span class="o">.</span><span class="n">adjacency</span><span class="p">()]</span>
-<span class="go">[(0, {1: {}}), (1, {0: {}, 2: {}}), (2, {1: {}, 3: {}}), (3, {2: {}})]</span>
+<p>The added objective function nodes can be queried by the attribute:</p>
+<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">Graph</span><span class="o">.</span><span class="n">nodes</span><span class="p">[</span><span class="n">node</span><span class="p">][</span><span class="s2">"name"</span><span class="p">]</span> <span class="o">==</span> <span class="s2">"Objective"</span>
</pre></div>
</div>
</dd></dl>
-<dl class="attribute">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.adjlist_inner_dict_factory">
-<code class="descname">adjlist_inner_dict_factory</code><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.adjlist_inner_dict_factory" title="Permalink to this definition">¶</a></dt>
-<dd><p>alias of <code class="xref py py-class docutils literal notranslate"><span class="pre">__builtin__.dict</span></code></p>
-</dd></dl>
-
-<dl class="attribute">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.adjlist_outer_dict_factory">
-<code class="descname">adjlist_outer_dict_factory</code><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.adjlist_outer_dict_factory" title="Permalink to this definition">¶</a></dt>
-<dd><p>alias of <code class="xref py py-class docutils literal notranslate"><span class="pre">__builtin__.dict</span></code></p>
-</dd></dl>
-
<dl class="method">
<dt id="kadmos.graph.graph_kadmos.KadmosGraph.change_graph_class">
<code class="descname">change_graph_class</code><span class="sig-paren">(</span><em>graph_class</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.change_graph_class" title="Permalink to this definition">¶</a></dt>
<dd><p>Method to adjust the class of a graph.</p>
+<table class="docutils field-list" frame="void" rules="none">
+<col class="field-name" />
+<col class="field-body" />
+<tbody valign="top">
+<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">newly classed graph.</td>
+</tr>
+<tr class="field-even field"><th class="field-name">Return type:</th><td class="field-body">graph_class</td>
+</tr>
+</tbody>
+</table>
</dd></dl>
<dl class="method">
<dt id="kadmos.graph.graph_kadmos.KadmosGraph.check">
<code class="descname">check</code><span class="sig-paren">(</span><em>raise_error=False</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.check" title="Permalink to this definition">¶</a></dt>
<dd><p>Method to check the graph for validity and completeness.</p>
-<p>Several checks are performed. However the method does not guarantee the validity of the graph.</p>
-<p>The checks are split into several categories and the methods _check_category_a, _check_category_b and
-_check_category_c are used to determine the overall validity and completeness. These sub methods are generally
-defined below and are then further refined in child classes.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
@@ -648,15 +446,19 @@ defined below and are then further refined in child classes.</p>
</tr>
</tbody>
</table>
+<div class="admonition note">
+<p class="first admonition-title">Note</p>
+<p class="last">Several checks are performed. However the method does not guarantee the validity of the graph.</p>
+</div>
+<p>The checks are split into several categories and the methods _check_category_a, _check_category_b and
+_check_category_c are used to determine the overall validity and completeness. These sub methods are generally
+defined below and are then further refined in child classes.</p>
</dd></dl>
<dl class="method">
<dt id="kadmos.graph.graph_kadmos.KadmosGraph.check_cmdows_integrity">
<code class="descname">check_cmdows_integrity</code><span class="sig-paren">(</span><em>convention=True</em>, <em>mpg=None</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.check_cmdows_integrity" title="Permalink to this definition">¶</a></dt>
<dd><p>Method to check the integrity of the CMDOWS file that can be created with the save method.</p>
-<p>The integrity check is graph specific and thus needs to be executed for every graph before saving as CMDOWS if
-one wants to be sure that the CMDOWS file is integer. Due to its relative long runtime this check is however not
-performed automatically when using the save method.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
@@ -675,13 +477,15 @@ performed automatically when using the save method.</p>
</tr>
</tbody>
</table>
+<p>The integrity check is graph specific and thus needs to be executed for every graph before saving as CMDOWS if
+one wants to be sure that the CMDOWS file is integer. Due to its relative long runtime this check is however not
+performed automatically when using the save method.</p>
</dd></dl>
<dl class="method">
<dt id="kadmos.graph.graph_kadmos.KadmosGraph.check_for_coupling">
<code class="descname">check_for_coupling</code><span class="sig-paren">(</span><em>function_order</em>, <em>only_feedback=False</em>, <em>raise_error_if_true=False</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.check_for_coupling" title="Permalink to this definition">¶</a></dt>
<dd><p>Function to check for the presence of coupling in a graph for a list of analyses in a given analysis order.</p>
-<p>Note that only the functions in the function_order list are checked for feedback.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
@@ -701,85 +505,9 @@ performed automatically when using the save method.</p>
</tr>
</tbody>
</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.clear">
-<code class="descname">clear</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.clear" title="Permalink to this definition">¶</a></dt>
-<dd><p>Remove all nodes and edges from the graph.</p>
-<p>This also removes the name, and all graph, node, and edge attributes.</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">path_graph</span><span class="p">(</span><span class="mi">4</span><span class="p">)</span> <span class="c1"># or DiGraph, MultiGraph, MultiDiGraph, etc</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">clear</span><span class="p">()</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">)</span>
-<span class="go">[]</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">edges</span><span class="p">)</span>
-<span class="go">[]</span>
-</pre></div>
-</div>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.copy">
-<code class="descname">copy</code><span class="sig-paren">(</span><em>as_view=False</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.copy" title="Permalink to this definition">¶</a></dt>
-<dd><p>Return a copy of the graph.</p>
-<p>The copy method by default returns a shallow copy of the graph
-and attributes. That is, if an attribute is a container, that
-container is shared by the original an the copy.
-Use Python’s <cite>copy.deepcopy</cite> for new containers.</p>
-<p>If <cite>as_view</cite> is True then a view is returned instead of a copy.</p>
-<p>All copies reproduce the graph structure, but data attributes
-may be handled in different ways. There are four types of copies
-of a graph that people might want.</p>
-<p>Deepcopy – The default behavior is a “deepcopy†where the graph
-structure as well as all data attributes and any objects they might
-contain are copied. The entire graph object is new so that changes
-in the copy do not affect the original object. (see Python’s
-copy.deepcopy)</p>
-<p>Data Reference (Shallow) – For a shallow copy the graph structure
-is copied but the edge, node and graph attribute dicts are
-references to those in the original graph. This saves
-time and memory but could cause confusion if you change an attribute
-in one graph and it changes the attribute in the other.
-NetworkX does not provide this level of shallow copy.</p>
-<p>Independent Shallow – This copy creates new independent attribute
-dicts and then does a shallow copy of the attributes. That is, any
-attributes that are containers are shared between the new graph
-and the original. This is exactly what <cite>dict.copy()</cite> provides.
-You can obtain this style copy using:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">path_graph</span><span class="p">(</span><span class="mi">5</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="n">H</span> <span class="o">=</span> <span class="n">G</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>
-<span class="gp">>>> </span><span class="n">H</span> <span class="o">=</span> <span class="n">G</span><span class="o">.</span><span class="n">copy</span><span class="p">(</span><span class="n">as_view</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="n">H</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="n">G</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="n">H</span> <span class="o">=</span> <span class="n">G</span><span class="o">.</span><span class="n">fresh_copy</span><span class="p">()</span><span class="o">.</span><span class="vm">__class__</span><span class="p">(</span><span class="n">G</span><span class="p">)</span>
-</pre></div>
-</div>
-<p>Fresh Data – For fresh data, the graph structure is copied while
-new empty data attribute dicts are created. The resulting graph
-is independent of the original and it has no edge, node or graph
-attributes. Fresh copies are not enabled. Instead use:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">H</span> <span class="o">=</span> <span class="n">G</span><span class="o">.</span><span class="n">fresh_copy</span><span class="p">()</span>
-<span class="gp">>>> </span><span class="n">H</span><span class="o">.</span><span class="n">add_nodes_from</span><span class="p">(</span><span class="n">G</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="n">H</span><span class="o">.</span><span class="n">add_edges_from</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">edges</span><span class="p">)</span>
-</pre></div>
-</div>
-<p>View – Inspired by dict-views, graph-views act like read-only
-versions of the original graph, providing a copy of the original
-structure without requiring any memory for copying the information.</p>
-<p>See the Python copy module for more information on shallow
-and deep copies, <a class="reference external" href="https://docs.python.org/2/library/copy.html">https://docs.python.org/2/library/copy.html</a>.</p>
-<dl class="docutils">
-<dt>as_view <span class="classifier-delimiter">:</span> <span class="classifier">bool, optional (default=False)</span></dt>
-<dd>If True, the returned graph-view provides a read-only view
-of the original graph without actually copying any data.</dd>
-</dl>
-<dl class="docutils">
-<dt>G <span class="classifier-delimiter">:</span> <span class="classifier">Graph</span></dt>
-<dd>A copy of the graph.</dd>
-</dl>
-<p>to_directed: return a directed copy of the graph.</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">path_graph</span><span class="p">(</span><span class="mi">4</span><span class="p">)</span> <span class="c1"># or DiGraph, MultiGraph, MultiDiGraph, etc</span>
-<span class="gp">>>> </span><span class="n">H</span> <span class="o">=</span> <span class="n">G</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>
-</pre></div>
+<div class="admonition note">
+<p class="first admonition-title">Note</p>
+<p class="last">only the functions in the function_order list are checked for feedback.</p>
</div>
</dd></dl>
@@ -835,7 +563,7 @@ of the original graph without actually copying any data.</dd>
<li><strong>node</strong> (<em>str</em>) – node to be copied</li>
<li><strong>suffix</strong> (<em>str</em>) – suffix to be added to the node ID</li>
<li><strong>label_extension</strong> (<em>str</em>) – extension for labels</li>
-<li><strong>kwargs</strong> (<em>dict</em>) – keyword arguments will be added as node attributes</li>
+<li><strong>kwargs</strong> (<em>dict</em><em>, </em><em>int</em>) – keyword arguments will be added as node attributes</li>
</ul>
</td>
</tr>
@@ -924,48 +652,10 @@ of the original graph without actually copying any data.</dd>
</table>
</dd></dl>
-<dl class="attribute">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.degree">
-<code class="descname">degree</code><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.degree" title="Permalink to this definition">¶</a></dt>
-<dd><p>A DegreeView for the Graph as G.degree or G.degree().</p>
-<p>The node degree is the number of edges adjacent to the node.
-The weighted node degree is the sum of the edge weights for
-edges incident to that node.</p>
-<p>This object provides an iterator for (node, degree) as well as
-lookup for the degree for a single node.</p>
-<dl class="docutils">
-<dt>nbunch <span class="classifier-delimiter">:</span> <span class="classifier">single node, container, or all nodes (default= all nodes)</span></dt>
-<dd>The view will only report edges incident to these nodes.</dd>
-<dt>weight <span class="classifier-delimiter">:</span> <span class="classifier">string or None, optional (default=None)</span></dt>
-<dd>The name of an edge attribute that holds the numerical value used
-as a weight. If None, then each edge has weight 1.
-The degree is the sum of the edge weights adjacent to the node.</dd>
-</dl>
-<p>If a single node is requested
-deg : int</p>
-<blockquote>
-<div>Degree of the node</div></blockquote>
-<p>OR if multiple nodes are requested
-nd_iter : iterator</p>
-<blockquote>
-<div>The iterator returns two-tuples of (node, degree).</div></blockquote>
-<p>in_degree, out_degree</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">DiGraph</span><span class="p">()</span> <span class="c1"># or MultiDiGraph</span>
-<span class="gp">>>> </span><span class="n">nx</span><span class="o">.</span><span class="n">add_path</span><span class="p">(</span><span class="n">G</span><span class="p">,</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">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">])</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">degree</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span> <span class="c1"># node 0 with degree 1</span>
-<span class="go">1</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">degree</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">2</span><span class="p">]))</span>
-<span class="go">[(0, 1), (1, 2), (2, 2)]</span>
-</pre></div>
-</div>
-</dd></dl>
-
<dl class="method">
<dt id="kadmos.graph.graph_kadmos.KadmosGraph.disconnect_problematic_variables_from">
<code class="descname">disconnect_problematic_variables_from</code><span class="sig-paren">(</span><em>function</em>, <em>disconnect_collided_targets=True</em>, <em>disconnect_shared_sources=True</em>, <em>ignore_list=[]</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.disconnect_problematic_variables_from" title="Permalink to this definition">¶</a></dt>
<dd><p>Method to automatically disconnect certain problematic variables with respect to a given function.</p>
-<p>If given as setting (disconnect_collided_targets=True) then the collided targets will be disconnected from this
-function. Also, if given as setting (disconnect_shared_sources=True), shared sources are also disconnected.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
@@ -973,103 +663,15 @@ function. Also, if given as setting (disconnect_shared_sources=True), shared sou
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
<li><strong>function</strong> (<em>basestring</em>) – function around which problematic variables are disconnected</li>
<li><strong>disconnect_collided_targets</strong> (<em>bool</em>) – setting to disconnect collided targets</li>
-<li><strong>disconnect_shared_sources</strong> (<em>list</em>) – setting to disconnect shared sources</li>
-<li><strong>disconnect_shared_sources</strong> – setting to ignore certain nodes</li>
+<li><strong>disconnect_shared_sources</strong> (<em>bool</em>) – setting to disconnect shared sources</li>
+<li><strong>ignore_list</strong> (<em>list</em>) – setting to ignore certain nodes</li>
</ul>
</td>
</tr>
</tbody>
</table>
-</dd></dl>
-
-<dl class="attribute">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.edge_attr_dict_factory">
-<code class="descname">edge_attr_dict_factory</code><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.edge_attr_dict_factory" title="Permalink to this definition">¶</a></dt>
-<dd><p>alias of <code class="xref py py-class docutils literal notranslate"><span class="pre">__builtin__.dict</span></code></p>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.edge_subgraph">
-<code class="descname">edge_subgraph</code><span class="sig-paren">(</span><em>edges</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.edge_subgraph" title="Permalink to this definition">¶</a></dt>
-<dd><p>Returns the subgraph induced by the specified edges.</p>
-<p>The induced subgraph contains each edge in <cite>edges</cite> and each
-node incident to any one of those edges.</p>
-<dl class="docutils">
-<dt>edges <span class="classifier-delimiter">:</span> <span class="classifier">iterable</span></dt>
-<dd>An iterable of edges in this graph.</dd>
-</dl>
-<dl class="docutils">
-<dt>G <span class="classifier-delimiter">:</span> <span class="classifier">Graph</span></dt>
-<dd>An edge-induced subgraph of this graph with the same edge
-attributes.</dd>
-</dl>
-<p>The graph, edge, and node attributes in the returned subgraph
-view are references to the corresponding attributes in the original
-graph. The view is read-only.</p>
-<p>To create a full graph version of the subgraph with its own copy
-of the edge or node attributes, use:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">edge_subgraph</span><span class="p">(</span><span class="n">edges</span><span class="p">)</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>
-</pre></div>
-</div>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">path_graph</span><span class="p">(</span><span class="mi">5</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="n">H</span> <span class="o">=</span> <span class="n">G</span><span class="o">.</span><span class="n">edge_subgraph</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="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">)])</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">H</span><span class="o">.</span><span class="n">nodes</span><span class="p">)</span>
-<span class="go">[0, 1, 3, 4]</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">H</span><span class="o">.</span><span class="n">edges</span><span class="p">)</span>
-<span class="go">[(0, 1), (3, 4)]</span>
-</pre></div>
-</div>
-</dd></dl>
-
-<dl class="attribute">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.edges">
-<code class="descname">edges</code><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.edges" title="Permalink to this definition">¶</a></dt>
-<dd><p>An OutEdgeView of the DiGraph as G.edges or G.edges().</p>
-<p>edges(self, nbunch=None, data=False, default=None)</p>
-<p>The OutEdgeView provides set-like operations on the edge-tuples
-as well as edge attribute lookup. When called, it also provides
-an EdgeDataView object which allows control of access to edge
-attributes (but does not provide set-like operations).
-Hence, <cite>G.edges[u, v][‘color’]</cite> provides the value of the color
-attribute for edge <cite>(u, v)</cite> while
-<cite>for (u, v, c) in G.edges.data(‘color’, default=’red’):</cite>
-iterates through all the edges yielding the color attribute
-with default <cite>‘red’</cite> if no color attribute exists.</p>
-<dl class="docutils">
-<dt>nbunch <span class="classifier-delimiter">:</span> <span class="classifier">single node, container, or all nodes (default= all nodes)</span></dt>
-<dd>The view will only report edges incident to these nodes.</dd>
-<dt>data <span class="classifier-delimiter">:</span> <span class="classifier">string or bool, optional (default=False)</span></dt>
-<dd>The edge attribute returned in 3-tuple (u, v, ddict[data]).
-If True, return edge attribute dict in 3-tuple (u, v, ddict).
-If False, return 2-tuple (u, v).</dd>
-<dt>default <span class="classifier-delimiter">:</span> <span class="classifier">value, optional (default=None)</span></dt>
-<dd>Value used for edges that dont have the requested attribute.
-Only relevant if data is not True or False.</dd>
-</dl>
-<dl class="docutils">
-<dt>edges <span class="classifier-delimiter">:</span> <span class="classifier">OutEdgeView</span></dt>
-<dd>A view of edge attributes, usually it iterates over (u, v)
-or (u, v, d) tuples of edges, but can also be used for
-attribute lookup as <cite>edges[u, v][‘foo’]</cite>.</dd>
-</dl>
-<p>in_edges, out_edges</p>
-<p>Nodes in nbunch that are not in the graph will be (quietly) ignored.
-For directed graphs this returns the out-edges.</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">DiGraph</span><span class="p">()</span> <span class="c1"># or MultiDiGraph, etc</span>
-<span class="gp">>>> </span><span class="n">nx</span><span class="o">.</span><span class="n">add_path</span><span class="p">(</span><span class="n">G</span><span class="p">,</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">2</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="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="mi">5</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="p">[</span><span class="n">e</span> <span class="k">for</span> <span class="n">e</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="go">[(0, 1), (1, 2), (2, 3)]</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">edges</span><span class="o">.</span><span class="n">data</span><span class="p">()</span> <span class="c1"># default data is {} (empty dict)</span>
-<span class="go">OutEdgeDataView([(0, 1, {}), (1, 2, {}), (2, 3, {'weight': 5})])</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">edges</span><span class="o">.</span><span class="n">data</span><span class="p">(</span><span class="s1">'weight'</span><span class="p">,</span> <span class="n">default</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
-<span class="go">OutEdgeDataView([(0, 1, 1), (1, 2, 1), (2, 3, 5)])</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">edges</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="mi">2</span><span class="p">])</span> <span class="c1"># only edges incident to these nodes</span>
-<span class="go">OutEdgeDataView([(0, 1), (2, 3)])</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">edges</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span> <span class="c1"># only edges incident to a single node (use G.adj[0]?)</span>
-<span class="go">OutEdgeDataView([(0, 1)])</span>
-</pre></div>
-</div>
+<p>If given as setting (disconnect_collided_targets=True) then the collided targets will be disconnected from this
+function. Also, if given as setting (disconnect_shared_sources=True), shared sources are also disconnected.</p>
</dd></dl>
<dl class="method">
@@ -1206,22 +808,12 @@ Just get all nodes of a graph in a list:</p>
</div>
<p>Get all nodes with any of the listed attribute values:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">all_nodes</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">find_all_nodes</span><span class="p">(</span><span class="n">category</span><span class="o">=</span><span class="s1">'all'</span><span class="p">,</span> <span class="n">subcategory</span><span class="o">=</span><span class="s1">'all'</span><span class="p">,</span>
-<span class="gp">>>> </span> <span class="n">attr_include</span><span class="o">=</span><span class="p">[[</span><span class="s1">'problem_role'</span><span class="p">,</span> <span class="p">[</span><span class="s1">'constraint'</span><span class="p">,</span> <span class="s1">'objective'</span><span class="p">]],</span> <span class="p">[</span><span class="s1">'instance'</span><span class="p">,</span> <span class="mi">1</span><span class="p">]])</span>
+<span class="gp">>>> </span> <span class="n">attr_include</span><span class="o">=</span><span class="p">[[</span><span class="s1">'problem_role'</span><span class="p">,</span> <span class="p">[</span><span class="s1">'constraint'</span><span class="p">,</span> <span class="s1">'objective'</span><span class="p">]],</span>
+<span class="gp">>>> </span> <span class="p">[</span><span class="s1">'instance'</span><span class="p">,</span> <span class="mi">1</span><span class="p">]])</span>
</pre></div>
</div>
</dd></dl>
-<dl class="method">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.fresh_copy">
-<code class="descname">fresh_copy</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.fresh_copy" title="Permalink to this definition">¶</a></dt>
-<dd><p>Return a fresh copy graph with the same data structure.</p>
-<p>A fresh copy has no nodes, edges or graph attributes. It is
-the same data structure as the current graph. This method is
-typically used to create an empty version of the graph.</p>
-<p>If you subclass the base class you should overwrite this method
-to return your class of graph.</p>
-</dd></dl>
-
<dl class="method">
<dt id="kadmos.graph.graph_kadmos.KadmosGraph.get_adjacency_matrix">
<code class="descname">get_adjacency_matrix</code><span class="sig-paren">(</span><em>print_in_log=True</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.get_adjacency_matrix" title="Permalink to this definition">¶</a></dt>
@@ -1310,16 +902,6 @@ to return your class of graph.</p>
<dt id="kadmos.graph.graph_kadmos.KadmosGraph.get_contracted_graph">
<code class="descname">get_contracted_graph</code><span class="sig-paren">(</span><em>contraction_level</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.get_contracted_graph" title="Permalink to this definition">¶</a></dt>
<dd><p>This function contracts the nodes of a graph to the provided contraction level.</p>
-<p>The contraction level refers to the xpath-level, which represents the position of the descendant with respect
-to its predecessors. The example below represents a level 3 node, with “cpacs†being at level zero.</p>
-<p>/cpacs/aircraft/wings/wing</p>
-<p>–cpacs</p>
-<p>—-aircraft</p>
-<p>——–wings</p>
-<p>————wing</p>
-<p>All nodes above the contraction level are removed from the graph and replaced by a “variable group†node, which
-groups the removed nodes in a node at contraction level. This allows for a “de-cluttering†of the graph, with
-the graph connections still being represented.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
@@ -1330,23 +912,25 @@ the graph connections still being represented.</p>
</tr>
</tbody>
</table>
+<p>The contraction level refers to the xpath-level, which represents the position of the descendant with respect
+to its predecessors. The example below represents a level 3 node, with “cpacs†being at level zero.</p>
+<p>/cpacs/aircraft/wings/wing</p>
+<p>–cpacs</p>
+<p>—-aircraft</p>
+<p>——–wings</p>
+<p>————wing</p>
+<div class="admonition note">
+<p class="first admonition-title">Note</p>
+<p class="last">All nodes above the contraction level are removed from the graph and replaced by a “variable group†node, which
+groups the removed nodes in a node at contraction level. This allows for a “de-cluttering†of the graph, with
+the graph connections still being represented.</p>
+</div>
</dd></dl>
<dl class="method">
<dt id="kadmos.graph.graph_kadmos.KadmosGraph.get_direct_coupling_nodes">
<code class="descname">get_direct_coupling_nodes</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.get_direct_coupling_nodes" title="Permalink to this definition">¶</a></dt>
<dd><p>This method returns the direct couplings between two nodes in a graph.</p>
-<p>This method is specifically written (and tested) with function nodes in mind. Direct coupling is defined as
-coupling with between two nodes through a third node.</p>
-<p>In this function, each combination between the provided arguments is tested for couplings (in pairs). First,
-the two nodes in each pair are checked for common neighbors. If they do, the edges of the common neighbors are
-iterated to determine whether the node-pair is connected to each other, or only the neighbor. The direction of
-the coupling is also checked.</p>
-<p>Example:</p>
-<p>The connection:</p>
-<p>F1 => N1 => F2</p>
-<p>leads to:</p>
-<p>[(F1, F2, N1)]</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
@@ -1366,46 +950,17 @@ the coupling is also checked.</p>
</tr>
</tbody>
</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.get_edge_data">
-<code class="descname">get_edge_data</code><span class="sig-paren">(</span><em>u</em>, <em>v</em>, <em>default=None</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.get_edge_data" title="Permalink to this definition">¶</a></dt>
-<dd><p>Return the attribute dictionary associated with edge (u, v).</p>
-<p>This is identical to <cite>G[u][v]</cite> except the default is returned
-instead of an exception is the edge doesn’t exist.</p>
-<p>u, v : nodes
-default: any Python object (default=None)</p>
-<blockquote>
-<div>Value to return if the edge (u, v) is not found.</div></blockquote>
-<dl class="docutils">
-<dt>edge_dict <span class="classifier-delimiter">:</span> <span class="classifier">dictionary</span></dt>
-<dd>The edge attribute dictionary.</dd>
-</dl>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">path_graph</span><span class="p">(</span><span class="mi">4</span><span class="p">)</span> <span class="c1"># or DiGraph, MultiGraph, MultiDiGraph, etc</span>
-<span class="gp">>>> </span><span class="n">G</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="go">{}</span>
-</pre></div>
-</div>
-<p>Warning: Assigning to <cite>G[u][v]</cite> is not permitted.
-But it is safe to assign attributes <cite>G[u][v][‘foo’]</cite></p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">G</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="s1">'weight'</span><span class="p">]</span> <span class="o">=</span> <span class="mi">7</span>
-<span class="gp">>>> </span><span class="n">G</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="s1">'weight'</span><span class="p">]</span>
-<span class="go">7</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="p">[</span><span class="mi">1</span><span class="p">][</span><span class="mi">0</span><span class="p">][</span><span class="s1">'weight'</span><span class="p">]</span>
-<span class="go">7</span>
-</pre></div>
-</div>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">path_graph</span><span class="p">(</span><span class="mi">4</span><span class="p">)</span> <span class="c1"># or DiGraph, MultiGraph, MultiDiGraph, etc</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">get_edge_data</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="c1"># default edge data is {}</span>
-<span class="go">{}</span>
-<span class="gp">>>> </span><span class="n">e</span> <span class="o">=</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="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">get_edge_data</span><span class="p">(</span><span class="o">*</span><span class="n">e</span><span class="p">)</span> <span class="c1"># tuple form</span>
-<span class="go">{}</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">get_edge_data</span><span class="p">(</span><span class="s1">'a'</span><span class="p">,</span> <span class="s1">'b'</span><span class="p">,</span> <span class="n">default</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span> <span class="c1"># edge not in graph, return 0</span>
-<span class="go">0</span>
-</pre></div>
-</div>
+<p>This method is specifically written (and tested) with function nodes in mind. Direct coupling is defined as
+coupling with between two nodes through a third node.</p>
+<p>In this function, each combination between the provided arguments is tested for couplings (in pairs). First,
+the two nodes in each pair are checked for common neighbors. If they do, the edges of the common neighbors are
+iterated to determine whether the node-pair is connected to each other, or only the neighbor. The direction of
+the coupling is also checked.</p>
+<p>Example:</p>
+<ul class="simple">
+<li>The connection: F1 => N1 => F2</li>
+<li>Leads to: [(F1, F2, N1)]</li>
+</ul>
</dd></dl>
<dl class="method">
@@ -1430,12 +985,6 @@ But it is safe to assign attributes <cite>G[u][v][‘foo’]</cite></p>
<dt id="kadmos.graph.graph_kadmos.KadmosGraph.get_function_graph">
<code class="descname">get_function_graph</code><span class="sig-paren">(</span><em>keep_objective_variables=False</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.get_function_graph" title="Permalink to this definition">¶</a></dt>
<dd><p>Method for replacing variable nodes by function connections.</p>
-<p>This function removes all variable nodes from the graph and replaces the variable connections of each function
-with function connections, such that:</p>
-<p>F(1) => N(1) => F(2) => N(2) => F(3)</p>
-<p>becomes:</p>
-<p>F(1) => F(2) => F(3)</p>
-<p>Note: N(i) is a variable node, and F(i) a function node.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
@@ -1448,6 +997,13 @@ with function connections, such that:</p>
</tr>
</tbody>
</table>
+<div class="admonition note">
+<p class="first admonition-title">Note</p>
+<p>This function removes all variable nodes from the graph and replaces the variable connections of each function
+with function connections, such that if N(i) is a variable node, and F(i) a function node:</p>
+<p>F(1) => N(1) => F(2) => N(2) => F(3)</p>
+<p class="last">becomes: F(1) => F(2) => F(3)</p>
+</div>
</dd></dl>
<dl class="method">
@@ -1478,8 +1034,6 @@ with function connections, such that:</p>
<dt id="kadmos.graph.graph_kadmos.KadmosGraph.get_graph_properties">
<code class="descname">get_graph_properties</code><span class="sig-paren">(</span><em>*args</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.get_graph_properties" title="Permalink to this definition">¶</a></dt>
<dd><p>This function retrieves the properties of a graph.</p>
-<p>If no argument is given, the standard list of properties GRAPH_PROPERTIES is analyzed and their values are
-returned in a dict. If arguments are given, only this list will be used as standard list of properties.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
@@ -1492,6 +1046,8 @@ returned in a dict. If arguments are given, only this list will be used as stand
</tr>
</tbody>
</table>
+<p>If no argument is given, the standard list of properties GRAPH_PROPERTIES is analyzed and their values are
+returned in a dict. If arguments are given, only this list will be used as standard list of properties.</p>
</dd></dl>
<dl class="method">
@@ -1523,6 +1079,18 @@ returned in a dict. If arguments are given, only this list will be used as stand
<dt id="kadmos.graph.graph_kadmos.KadmosGraph.get_node_subcategory">
<code class="descname">get_node_subcategory</code><span class="sig-paren">(</span><em>node</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.get_node_subcategory" title="Permalink to this definition">¶</a></dt>
<dd><p>Method to analyse a node and to update the subcategory attribute of the node.</p>
+<table class="docutils field-list" frame="void" rules="none">
+<col class="field-name" />
+<col class="field-body" />
+<tbody valign="top">
+<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>node</strong> (<em>basestring</em>) – node in the graph</td>
+</tr>
+<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">subcategory of the node</td>
+</tr>
+<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body">basestring</td>
+</tr>
+</tbody>
+</table>
<p>The following table illustrates how the subcategory is determined based on the category, indegree and outdegree:</p>
<table border="1" class="docutils">
<colgroup>
@@ -1603,26 +1171,12 @@ collided shared circular coupling</td>
</tr>
</tbody>
</table>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>node</strong> (<em>basestring</em>) – node in the graph</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">subcategory of the node</td>
-</tr>
-<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body">basestring</td>
-</tr>
-</tbody>
-</table>
</dd></dl>
<dl class="method">
<dt id="kadmos.graph.graph_kadmos.KadmosGraph.get_nodes_based_on_strings">
<code class="descname">get_nodes_based_on_strings</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.get_nodes_based_on_strings" title="Permalink to this definition">¶</a></dt>
<dd><p>This function enables the user to search graph nodes for specific strings.</p>
-<p>Each provided string will be searched for, and if multiple node are found for each string, the user will be able
-to select the ones desired. The other matched nodes are disregarded.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
@@ -1638,6 +1192,8 @@ to select the ones desired. The other matched nodes are disregarded.</p>
</tr>
</tbody>
</table>
+<p>Each provided string will be searched for, and if multiple node are found for each string, the user will be able
+to select the ones desired. The other matched nodes are disregarded.</p>
</dd></dl>
<dl class="method">
@@ -1690,7 +1246,7 @@ to select the ones desired. The other matched nodes are disregarded.</p>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">number of couplings for the input node</td>
</tr>
-<tr class="field-odd field"><th class="field-name">Type:</th><td class="field-body">int</td>
+<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body">int</td>
</tr>
</tbody>
</table>
@@ -1742,7 +1298,6 @@ to select the ones desired. The other matched nodes are disregarded.</p>
<dt id="kadmos.graph.graph_kadmos.KadmosGraph.get_subgraph_by_function_nodes">
<code class="descname">get_subgraph_by_function_nodes</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.get_subgraph_by_function_nodes" title="Permalink to this definition">¶</a></dt>
<dd><p>This function retrieves a subgraph from the original graph only containing the argument nodes.</p>
-<p>All arguments must be found in the graph.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
@@ -1758,25 +1313,38 @@ to select the ones desired. The other matched nodes are disregarded.</p>
</tr>
</tbody>
</table>
+<div class="admonition note">
+<p class="first admonition-title">Note</p>
+<p class="last">All arguments must be found in the graph.</p>
+</div>
</dd></dl>
<dl class="method">
<dt id="kadmos.graph.graph_kadmos.KadmosGraph.get_system_inputs">
<code class="descname">get_system_inputs</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.get_system_inputs" title="Permalink to this definition">¶</a></dt>
<dd><p>This method checks whether there are system inputs in the graph using the function nodes provided.</p>
-<p>The function nodes should be provided in the args. If system inputs exist they are returned.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>args</strong> – function nodes</td>
+<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
+<li><strong>args</strong> – function nodes</li>
+<li><strong>kwargs</strong> – </li>
+</ul>
+</td>
</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">system input nodes dictionary</td>
+<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">system input nodes dictionary</p>
+</td>
</tr>
-<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body">dict</td>
+<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last">dict</p>
+</td>
</tr>
</tbody>
</table>
+<div class="admonition note">
+<p class="first admonition-title">Note</p>
+<p class="last">The function nodes should be provided in the args. If system inputs exist they are returned.</p>
+</div>
</dd></dl>
<dl class="method">
@@ -1815,58 +1383,6 @@ to select the ones desired. The other matched nodes are disregarded.</p>
</table>
</dd></dl>
-<dl class="method">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.has_edge">
-<code class="descname">has_edge</code><span class="sig-paren">(</span><em>u</em>, <em>v</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.has_edge" title="Permalink to this definition">¶</a></dt>
-<dd><p>Return True if the edge (u, v) is in the graph.</p>
-<p>This is the same as <cite>v in G[u]</cite> without KeyError exceptions.</p>
-<dl class="docutils">
-<dt>u, v <span class="classifier-delimiter">:</span> <span class="classifier">nodes</span></dt>
-<dd>Nodes can be, for example, strings or numbers.
-Nodes must be hashable (and not None) Python objects.</dd>
-</dl>
-<dl class="docutils">
-<dt>edge_ind <span class="classifier-delimiter">:</span> <span class="classifier">bool</span></dt>
-<dd>True if edge is in the graph, False otherwise.</dd>
-</dl>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">path_graph</span><span class="p">(</span><span class="mi">4</span><span class="p">)</span> <span class="c1"># or DiGraph, MultiGraph, MultiDiGraph, etc</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">has_edge</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="c1"># using two nodes</span>
-<span class="go">True</span>
-<span class="gp">>>> </span><span class="n">e</span> <span class="o">=</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="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">has_edge</span><span class="p">(</span><span class="o">*</span><span class="n">e</span><span class="p">)</span> <span class="c1"># e is a 2-tuple (u, v)</span>
-<span class="go">True</span>
-<span class="gp">>>> </span><span class="n">e</span> <span class="o">=</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="p">{</span><span class="s1">'weight'</span><span class="p">:</span><span class="mi">7</span><span class="p">})</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">has_edge</span><span class="p">(</span><span class="o">*</span><span class="n">e</span><span class="p">[:</span><span class="mi">2</span><span class="p">])</span> <span class="c1"># e is a 3-tuple (u, v, data_dictionary)</span>
-<span class="go">True</span>
-</pre></div>
-</div>
-<p>The following syntax are equivalent:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">has_edge</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="go">True</span>
-<span class="gp">>>> </span><span class="mi">1</span> <span class="ow">in</span> <span class="n">G</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="c1"># though this gives KeyError if 0 not in G</span>
-<span class="go">True</span>
-</pre></div>
-</div>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.has_node">
-<code class="descname">has_node</code><span class="sig-paren">(</span><em>n</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.has_node" title="Permalink to this definition">¶</a></dt>
-<dd><p>Return True if the graph contains the node n.</p>
-<p>Identical to <cite>n in G</cite></p>
-<p>n : node</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">path_graph</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span> <span class="c1"># or DiGraph, MultiGraph, MultiDiGraph, etc</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">has_node</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
-<span class="go">True</span>
-</pre></div>
-</div>
-<p>It is more readable and simpler to use</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="mi">0</span> <span class="ow">in</span> <span class="n">G</span>
-<span class="go">True</span>
-</pre></div>
-</div>
-</dd></dl>
-
<dl class="method">
<dt id="kadmos.graph.graph_kadmos.KadmosGraph.has_nodes">
<code class="descname">has_nodes</code><span class="sig-paren">(</span><em>nodes</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.has_nodes" title="Permalink to this definition">¶</a></dt>
@@ -1885,85 +1401,20 @@ Nodes must be hashable (and not None) Python objects.</dd>
</table>
</dd></dl>
-<dl class="method">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.has_predecessor">
-<code class="descname">has_predecessor</code><span class="sig-paren">(</span><em>u</em>, <em>v</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.has_predecessor" title="Permalink to this definition">¶</a></dt>
-<dd><p>Return True if node u has predecessor v.</p>
-<p>This is true if graph has the edge u<-v.</p>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.has_successor">
-<code class="descname">has_successor</code><span class="sig-paren">(</span><em>u</em>, <em>v</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.has_successor" title="Permalink to this definition">¶</a></dt>
-<dd><p>Return True if node u has successor v.</p>
-<p>This is true if graph has the edge u->v.</p>
-</dd></dl>
-
-<dl class="attribute">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.in_degree">
-<code class="descname">in_degree</code><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.in_degree" title="Permalink to this definition">¶</a></dt>
-<dd><p>An InDegreeView for (node, in_degree) or in_degree for single node.</p>
-<p>The node in_degree is the number of edges pointing to the node.
-The weighted node degree is the sum of the edge weights for
-edges incident to that node.</p>
-<p>This object provides an iteration over (node, in_degree) as well as
-lookup for the degree for a single node.</p>
-<dl class="docutils">
-<dt>nbunch <span class="classifier-delimiter">:</span> <span class="classifier">single node, container, or all nodes (default= all nodes)</span></dt>
-<dd>The view will only report edges incident to these nodes.</dd>
-<dt>weight <span class="classifier-delimiter">:</span> <span class="classifier">string or None, optional (default=None)</span></dt>
-<dd>The name of an edge attribute that holds the numerical value used
-as a weight. If None, then each edge has weight 1.
-The degree is the sum of the edge weights adjacent to the node.</dd>
-</dl>
-<p>If a single node is requested
-deg : int</p>
-<blockquote>
-<div>In-degree of the node</div></blockquote>
-<p>OR if multiple nodes are requested
-nd_iter : iterator</p>
-<blockquote>
-<div>The iterator returns two-tuples of (node, in-degree).</div></blockquote>
-<p>degree, out_degree</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">DiGraph</span><span class="p">()</span>
-<span class="gp">>>> </span><span class="n">nx</span><span class="o">.</span><span class="n">add_path</span><span class="p">(</span><span class="n">G</span><span class="p">,</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">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">])</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">in_degree</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span> <span class="c1"># node 0 with degree 0</span>
-<span class="go">0</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">in_degree</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">2</span><span class="p">]))</span>
-<span class="go">[(0, 0), (1, 1), (2, 1)]</span>
-</pre></div>
-</div>
-</dd></dl>
-
-<dl class="attribute">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.in_edges">
-<code class="descname">in_edges</code><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.in_edges" title="Permalink to this definition">¶</a></dt>
-<dd><p>An InEdgeView of the Graph as G.in_edges or G.in_edges().</p>
-<p>in_edges(self, nbunch=None, data=False, default=None):</p>
-<dl class="docutils">
-<dt>nbunch <span class="classifier-delimiter">:</span> <span class="classifier">single node, container, or all nodes (default= all nodes)</span></dt>
-<dd>The view will only report edges incident to these nodes.</dd>
-<dt>data <span class="classifier-delimiter">:</span> <span class="classifier">string or bool, optional (default=False)</span></dt>
-<dd>The edge attribute returned in 3-tuple (u, v, ddict[data]).
-If True, return edge attribute dict in 3-tuple (u, v, ddict).
-If False, return 2-tuple (u, v).</dd>
-<dt>default <span class="classifier-delimiter">:</span> <span class="classifier">value, optional (default=None)</span></dt>
-<dd>Value used for edges that dont have the requested attribute.
-Only relevant if data is not True or False.</dd>
-</dl>
-<dl class="docutils">
-<dt>in_edges <span class="classifier-delimiter">:</span> <span class="classifier">InEdgeView</span></dt>
-<dd>A view of edge attributes, usually it iterates over (u, v)
-or (u, v, d) tuples of edges, but can also be used for
-attribute lookup as <cite>edges[u, v][‘foo’]</cite>.</dd>
-</dl>
-<p>edges</p>
-</dd></dl>
-
<dl class="method">
<dt id="kadmos.graph.graph_kadmos.KadmosGraph.inspect">
<code class="descname">inspect</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.inspect" title="Permalink to this definition">¶</a></dt>
<dd><p>Method to print an overview of the graph.</p>
+<table class="docutils field-list" frame="void" rules="none">
+<col class="field-name" />
+<col class="field-body" />
+<tbody valign="top">
+<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">printed overview of the graph</td>
+</tr>
+<tr class="field-even field"><th class="field-name">Return type:</th><td class="field-body">str</td>
+</tr>
+</tbody>
+</table>
</dd></dl>
<dl class="method">
@@ -1976,6 +1427,10 @@ attribute lookup as <cite>edges[u, v][‘foo’]</cite>.</dd>
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>node</strong> (<em>str</em>) – node</td>
</tr>
+<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">printed node details</td>
+</tr>
+<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body">str</td>
+</tr>
</tbody>
</table>
</dd></dl>
@@ -1990,22 +1445,14 @@ attribute lookup as <cite>edges[u, v][‘foo’]</cite>.</dd>
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>list_of_nodes</strong> (<em>list</em>) – node list</td>
</tr>
+<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">printed details of nodes</td>
+</tr>
+<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body">str</td>
+</tr>
</tbody>
</table>
</dd></dl>
-<dl class="method">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.is_directed">
-<code class="descname">is_directed</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.is_directed" title="Permalink to this definition">¶</a></dt>
-<dd><p>Return True if graph is directed, False otherwise.</p>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.is_multigraph">
-<code class="descname">is_multigraph</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.is_multigraph" title="Permalink to this definition">¶</a></dt>
-<dd><p>Return True if graph is a multigraph, False otherwise.</p>
-</dd></dl>
-
<dl class="method">
<dt id="kadmos.graph.graph_kadmos.KadmosGraph.load_cmdows">
<code class="descname">load_cmdows</code><span class="sig-paren">(</span><em>cmdows</em>, <em>check_list</em>, <em>ignore_modes=False</em>, <em>keep_running=False</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.load_cmdows" title="Permalink to this definition">¶</a></dt>
@@ -2030,12 +1477,15 @@ attribute lookup as <cite>edges[u, v][‘foo’]</cite>.</dd>
</tr>
</tbody>
</table>
-<p>Check_list options:</p>
-<ul class="simple">
+<div class="admonition note">
+<p class="first admonition-title">Note</p>
+<p>check_list options:</p>
+<ul class="last simple">
<li>‘consistent_root’: check if all in-/output files have the same root element</li>
<li>‘invalid_leaf_elements’: check for leaf elements that still have child elements in other in-/output files</li>
<li>‘schemas’: check if the in-/output files are consistent with the schema.</li>
</ul>
+</div>
<p>To perform all of the checks without stopping if an error is found by the checks:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">check_list</span> <span class="o">=</span> <span class="p">[</span><span class="s1">'consistent_root'</span><span class="p">,</span> <span class="s1">'invalid_leaf_elements'</span><span class="p">,</span> <span class="s1">'schemas'</span><span class="p">]</span>
<span class="gp">>>> </span><span class="n">graph</span><span class="o">.</span><span class="n">load_cmdows</span><span class="p">(</span><span class="n">cmdows</span><span class="p">,</span> <span class="n">check_list</span><span class="p">,</span> <span class="n">keep_running</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
@@ -2047,6 +1497,14 @@ attribute lookup as <cite>edges[u, v][‘foo’]</cite>.</dd>
<dt id="kadmos.graph.graph_kadmos.KadmosGraph.make_all_variables_valid">
<code class="descname">make_all_variables_valid</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.make_all_variables_valid" title="Permalink to this definition">¶</a></dt>
<dd><p>Method to analyze all variables in a graph and make any problematic variables valid.</p>
+<table class="docutils field-list" frame="void" rules="none">
+<col class="field-name" />
+<col class="field-body" />
+<tbody valign="top">
+<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">graph with problematic variables removed.</td>
+</tr>
+</tbody>
+</table>
<p>Problematic variable are holes and splittables. Splittable variables are split and holes will simply be removed.</p>
</dd></dl>
@@ -2078,8 +1536,6 @@ attribute lookup as <cite>edges[u, v][‘foo’]</cite>.</dd>
<dt id="kadmos.graph.graph_kadmos.KadmosGraph.merge_function_nodes_based_on_modes">
<code class="descname">merge_function_nodes_based_on_modes</code><span class="sig-paren">(</span><em>merge_funcs=None</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.merge_function_nodes_based_on_modes" title="Permalink to this definition">¶</a></dt>
<dd><p>This class method merges all execution modes of the same function into a single node.</p>
-<p>Mainly used for illustration purposes since information on the execution modes gets lost. Functions must be
-present in graph.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
@@ -2090,6 +1546,8 @@ present in graph.</p>
</tr>
</tbody>
</table>
+<p>Mainly used for illustration purposes since information on the execution modes gets lost. Functions must be
+present in graph.</p>
</dd></dl>
<dl class="method">
@@ -2100,12 +1558,18 @@ present in graph.</p>
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
+<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>args</strong> (<em>node_ids</em>) – functions to be merged</li>
<li><strong>kwargs</strong> (<em>dict</em>) – new_label to specify new node label manually (optional)</li>
</ul>
</td>
</tr>
+<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">graph with merged function</p>
+</td>
+</tr>
+<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last"><a class="reference internal" href="#kadmos.graph.graph_kadmos.KadmosGraph" title="kadmos.graph.graph_kadmos.KadmosGraph">KadmosGraph</a></p>
+</td>
+</tr>
</tbody>
</table>
</dd></dl>
@@ -2118,12 +1582,18 @@ present in graph.</p>
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
+<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>args</strong> (<em>node_ids</em>) – functions to be merged</li>
<li><strong>kwargs</strong> (<em>dict</em>) – new_label to specify new node label manually (optional)</li>
</ul>
</td>
</tr>
+<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">graph with merged functions</p>
+</td>
+</tr>
+<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last"><a class="reference internal" href="#kadmos.graph.graph_kadmos.KadmosGraph" title="kadmos.graph.graph_kadmos.KadmosGraph">KadmosGraph</a></p>
+</td>
+</tr>
</tbody>
</table>
</dd></dl>
@@ -2132,161 +1602,31 @@ present in graph.</p>
<dt id="kadmos.graph.graph_kadmos.KadmosGraph.merge_sequential_functions">
<code class="descname">merge_sequential_functions</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.merge_sequential_functions" title="Permalink to this definition">¶</a></dt>
<dd><p>Function to merge a collection of functions.</p>
-<p>It is assumed that the merged functions are actually executed in the sequence in which they are given to this
-function.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
+<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>args</strong> (<em>node_ids</em>) – functions to be merged in the given sequence</li>
<li><strong>kwargs</strong> (<em>str</em>) – new_label to specify new node label manually (optional)</li>
</ul>
</td>
</tr>
+<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">graph with merged functions</p>
+</td>
+</tr>
+<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last"><a class="reference internal" href="#kadmos.graph.graph_kadmos.KadmosGraph" title="kadmos.graph.graph_kadmos.KadmosGraph">KadmosGraph</a></p>
+</td>
+</tr>
</tbody>
</table>
-</dd></dl>
-
-<dl class="attribute">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.name">
-<code class="descname">name</code><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.name" title="Permalink to this definition">¶</a></dt>
-<dd><p>String identifier of the graph.</p>
-<p>This graph attribute appears in the attribute dict G.graph
-keyed by the string <cite>“nameâ€</cite>. as well as an attribute (technically
-a property) <cite>G.name</cite>. This is entirely user controlled.</p>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.nbunch_iter">
-<code class="descname">nbunch_iter</code><span class="sig-paren">(</span><em>nbunch=None</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.nbunch_iter" title="Permalink to this definition">¶</a></dt>
-<dd><p>Return an iterator over nodes contained in nbunch that are
-also in the graph.</p>
-<p>The nodes in nbunch are checked for membership in the graph
-and if not are silently ignored.</p>
-<dl class="docutils">
-<dt>nbunch <span class="classifier-delimiter">:</span> <span class="classifier">single node, container, or all nodes (default= all nodes)</span></dt>
-<dd>The view will only report edges incident to these nodes.</dd>
-</dl>
-<dl class="docutils">
-<dt>niter <span class="classifier-delimiter">:</span> <span class="classifier">iterator</span></dt>
-<dd>An iterator over nodes in nbunch that are also in the graph.
-If nbunch is None, iterate over all nodes in the graph.</dd>
-</dl>
-<dl class="docutils">
-<dt>NetworkXError</dt>
-<dd>If nbunch is not a node or or sequence of nodes.
-If a node in nbunch is not hashable.</dd>
-</dl>
-<p>Graph.__iter__</p>
-<p>When nbunch is an iterator, the returned iterator yields values
-directly from nbunch, becoming exhausted when nbunch is exhausted.</p>
-<p>To test whether nbunch is a single node, one can use
-“if nbunch in self:â€, even after processing with this routine.</p>
-<p>If nbunch is not a node or a (possibly empty) sequence/iterator
-or None, a <code class="xref py py-exc docutils literal notranslate"><span class="pre">NetworkXError</span></code> is raised. Also, if any object in
-nbunch is not hashable, a <code class="xref py py-exc docutils literal notranslate"><span class="pre">NetworkXError</span></code> is raised.</p>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.neighbors">
-<code class="descname">neighbors</code><span class="sig-paren">(</span><em>n</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.neighbors" title="Permalink to this definition">¶</a></dt>
-<dd><p>Return an iterator over successor nodes of n.</p>
-<p>neighbors() and successors() are the same.</p>
-</dd></dl>
-
-<dl class="attribute">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.node">
-<code class="descname">node</code><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.node" title="Permalink to this definition">¶</a></dt>
-<dd><p>A NodeView of the Graph as G.nodes or G.nodes().</p>
-<p>Can be used as <cite>G.nodes</cite> for data lookup and for set-like operations.
-Can also be used as <cite>G.nodes(data=’color’, default=None)</cite> to return a
-NodeDataView which reports specific node data but no set operations.
-It presents a dict-like interface as well with <cite>G.nodes.items()</cite>
-iterating over <cite>(node, nodedata)</cite> 2-tuples and <cite>G.nodes[3][‘foo’]</cite>
-providing the value of the <cite>foo</cite> attribute for node <cite>3</cite>. In addition,
-a view <cite>G.nodes.data(‘foo’)</cite> provides a dict-like interface to the
-<cite>foo</cite> attribute of each node. <cite>G.nodes.data(‘foo’, default=1)</cite>
-provides a default for nodes that do not have attribute <cite>foo</cite>.</p>
-<dl class="docutils">
-<dt>data <span class="classifier-delimiter">:</span> <span class="classifier">string or bool, optional (default=False)</span></dt>
-<dd>The node attribute returned in 2-tuple (n, ddict[data]).
-If True, return entire node attribute dict as (n, ddict).
-If False, return just the nodes n.</dd>
-<dt>default <span class="classifier-delimiter">:</span> <span class="classifier">value, optional (default=None)</span></dt>
-<dd>Value used for nodes that dont have the requested attribute.
-Only relevant if data is not True or False.</dd>
-</dl>
-<dl class="docutils">
-<dt>NodeView</dt>
-<dd><p class="first">Allows set-like operations over the nodes as well as node
-attribute dict lookup and calling to get a NodeDataView.
-A NodeDataView iterates over <cite>(n, data)</cite> and has no set operations.
-A NodeView iterates over <cite>n</cite> and includes set operations.</p>
-<p class="last">When called, if data is False, an iterator over nodes.
-Otherwise an iterator of 2-tuples (node, attribute value)
-where the attribute is specified in <cite>data</cite>.
-If data is True then the attribute becomes the
-entire data dictionary.</p>
-</dd>
-</dl>
-<p>If your node data is not needed, it is simpler and equivalent
-to use the expression <code class="docutils literal notranslate"><span class="pre">for</span> <span class="pre">n</span> <span class="pre">in</span> <span class="pre">G</span></code>, or <code class="docutils literal notranslate"><span class="pre">list(G)</span></code>.</p>
-<p>There are two simple ways of getting a list of all nodes in the graph:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">path_graph</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">)</span>
-<span class="go">[0, 1, 2]</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="p">)</span>
-<span class="go">[0, 1, 2]</span>
-</pre></div>
-</div>
-<p>To get the node data along with the nodes:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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="mi">1</span><span class="p">,</span> <span class="n">time</span><span class="o">=</span><span class="s1">'5pm'</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">[</span><span class="mi">0</span><span class="p">][</span><span class="s1">'foo'</span><span class="p">]</span> <span class="o">=</span> <span class="s1">'bar'</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="kc">True</span><span class="p">))</span>
-<span class="go">[(0, {'foo': 'bar'}), (1, {'time': '5pm'}), (2, {})]</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="o">.</span><span class="n">data</span><span class="p">())</span>
-<span class="go">[(0, {'foo': 'bar'}), (1, {'time': '5pm'}), (2, {})]</span>
-</pre></div>
-</div>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="s1">'foo'</span><span class="p">))</span>
-<span class="go">[(0, 'bar'), (1, None), (2, None)]</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="o">.</span><span class="n">data</span><span class="p">(</span><span class="s1">'foo'</span><span class="p">))</span>
-<span class="go">[(0, 'bar'), (1, None), (2, None)]</span>
-</pre></div>
-</div>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="s1">'time'</span><span class="p">))</span>
-<span class="go">[(0, None), (1, '5pm'), (2, None)]</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="o">.</span><span class="n">data</span><span class="p">(</span><span class="s1">'time'</span><span class="p">))</span>
-<span class="go">[(0, None), (1, '5pm'), (2, None)]</span>
-</pre></div>
-</div>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="s1">'time'</span><span class="p">,</span> <span class="n">default</span><span class="o">=</span><span class="s1">'Not Available'</span><span class="p">))</span>
-<span class="go">[(0, 'Not Available'), (1, '5pm'), (2, 'Not Available')]</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="o">.</span><span class="n">data</span><span class="p">(</span><span class="s1">'time'</span><span class="p">,</span> <span class="n">default</span><span class="o">=</span><span class="s1">'Not Available'</span><span class="p">))</span>
-<span class="go">[(0, 'Not Available'), (1, '5pm'), (2, 'Not Available')]</span>
-</pre></div>
-</div>
-<p>If some of your nodes have an attribute and the rest are assumed
-to have a default attribute value you can create a dictionary
-from node/attribute pairs using the <cite>default</cite> keyword argument
-to guarantee the value is never None:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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="mi">0</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="mi">1</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="mi">2</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="mi">2</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="mi">3</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="nb">dict</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="s1">'weight'</span><span class="p">,</span> <span class="n">default</span><span class="o">=</span><span class="mi">1</span><span class="p">))</span>
-<span class="go">{0: 1, 1: 2, 2: 3}</span>
-</pre></div>
+<div class="admonition attention">
+<p class="first admonition-title">Attention</p>
+<p class="last">It is assumed that the merged functions are actually executed in the sequence in which they are
+given to this function.</p>
</div>
</dd></dl>
-<dl class="attribute">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.node_dict_factory">
-<code class="descname">node_dict_factory</code><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.node_dict_factory" title="Permalink to this definition">¶</a></dt>
-<dd><p>alias of <code class="xref py py-class docutils literal notranslate"><span class="pre">__builtin__.dict</span></code></p>
-</dd></dl>
-
<dl class="method">
<dt id="kadmos.graph.graph_kadmos.KadmosGraph.node_is_function">
<code class="descname">node_is_function</code><span class="sig-paren">(</span><em>node</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.node_is_function" title="Permalink to this definition">¶</a></dt>
@@ -2327,17 +1667,6 @@ to guarantee the value is never None:</p>
<dt id="kadmos.graph.graph_kadmos.KadmosGraph.node_is_objective_function">
<code class="descname">node_is_objective_function</code><span class="sig-paren">(</span><em>node</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.node_is_objective_function" title="Permalink to this definition">¶</a></dt>
<dd><p>This function checks whether the provided node is a objective function.</p>
-<dl class="docutils">
-<dt>This function checks whether the provided node:</dt>
-<dd><ol class="first last arabic simple">
-<li>exists in graph</li>
-<li>has name-attribute “Objectiveâ€</li>
-<li>has an out-degree of 1</li>
-<li>has an outgoing node with an out-degree of zero # TODO: THIS IS WRONG!</li>
-</ol>
-</dd>
-</dl>
-<p>Only if all checks are satisfied, is the node a valid objective function node.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
@@ -2350,6 +1679,20 @@ to guarantee the value is never None:</p>
</tr>
</tbody>
</table>
+<dl class="docutils">
+<dt>This function checks whether the provided node:</dt>
+<dd><ol class="first last arabic simple">
+<li>exists in graph</li>
+<li>has name-attribute “Objectiveâ€</li>
+<li>has an out-degree of 1</li>
+<li>has an outgoing node with an out-degree of zero</li>
+</ol>
+</dd>
+</dl>
+<div class="admonition note">
+<p class="first admonition-title">Note</p>
+<p class="last">Only if all checks are satisfied, is the node a valid objective function node.</p>
+</div>
</dd></dl>
<dl class="method">
@@ -2388,284 +1731,41 @@ to guarantee the value is never None:</p>
</table>
</dd></dl>
-<dl class="attribute">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.nodes">
-<code class="descname">nodes</code><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.nodes" title="Permalink to this definition">¶</a></dt>
-<dd><p>A NodeView of the Graph as G.nodes or G.nodes().</p>
-<p>Can be used as <cite>G.nodes</cite> for data lookup and for set-like operations.
-Can also be used as <cite>G.nodes(data=’color’, default=None)</cite> to return a
-NodeDataView which reports specific node data but no set operations.
-It presents a dict-like interface as well with <cite>G.nodes.items()</cite>
-iterating over <cite>(node, nodedata)</cite> 2-tuples and <cite>G.nodes[3][‘foo’]</cite>
-providing the value of the <cite>foo</cite> attribute for node <cite>3</cite>. In addition,
-a view <cite>G.nodes.data(‘foo’)</cite> provides a dict-like interface to the
-<cite>foo</cite> attribute of each node. <cite>G.nodes.data(‘foo’, default=1)</cite>
-provides a default for nodes that do not have attribute <cite>foo</cite>.</p>
-<dl class="docutils">
-<dt>data <span class="classifier-delimiter">:</span> <span class="classifier">string or bool, optional (default=False)</span></dt>
-<dd>The node attribute returned in 2-tuple (n, ddict[data]).
-If True, return entire node attribute dict as (n, ddict).
-If False, return just the nodes n.</dd>
-<dt>default <span class="classifier-delimiter">:</span> <span class="classifier">value, optional (default=None)</span></dt>
-<dd>Value used for nodes that dont have the requested attribute.
-Only relevant if data is not True or False.</dd>
-</dl>
-<dl class="docutils">
-<dt>NodeView</dt>
-<dd><p class="first">Allows set-like operations over the nodes as well as node
-attribute dict lookup and calling to get a NodeDataView.
-A NodeDataView iterates over <cite>(n, data)</cite> and has no set operations.
-A NodeView iterates over <cite>n</cite> and includes set operations.</p>
-<p class="last">When called, if data is False, an iterator over nodes.
-Otherwise an iterator of 2-tuples (node, attribute value)
-where the attribute is specified in <cite>data</cite>.
-If data is True then the attribute becomes the
-entire data dictionary.</p>
-</dd>
-</dl>
-<p>If your node data is not needed, it is simpler and equivalent
-to use the expression <code class="docutils literal notranslate"><span class="pre">for</span> <span class="pre">n</span> <span class="pre">in</span> <span class="pre">G</span></code>, or <code class="docutils literal notranslate"><span class="pre">list(G)</span></code>.</p>
-<p>There are two simple ways of getting a list of all nodes in the graph:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">path_graph</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">)</span>
-<span class="go">[0, 1, 2]</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="p">)</span>
-<span class="go">[0, 1, 2]</span>
-</pre></div>
-</div>
-<p>To get the node data along with the nodes:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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="mi">1</span><span class="p">,</span> <span class="n">time</span><span class="o">=</span><span class="s1">'5pm'</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">[</span><span class="mi">0</span><span class="p">][</span><span class="s1">'foo'</span><span class="p">]</span> <span class="o">=</span> <span class="s1">'bar'</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="kc">True</span><span class="p">))</span>
-<span class="go">[(0, {'foo': 'bar'}), (1, {'time': '5pm'}), (2, {})]</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="o">.</span><span class="n">data</span><span class="p">())</span>
-<span class="go">[(0, {'foo': 'bar'}), (1, {'time': '5pm'}), (2, {})]</span>
-</pre></div>
-</div>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="s1">'foo'</span><span class="p">))</span>
-<span class="go">[(0, 'bar'), (1, None), (2, None)]</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="o">.</span><span class="n">data</span><span class="p">(</span><span class="s1">'foo'</span><span class="p">))</span>
-<span class="go">[(0, 'bar'), (1, None), (2, None)]</span>
-</pre></div>
-</div>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="s1">'time'</span><span class="p">))</span>
-<span class="go">[(0, None), (1, '5pm'), (2, None)]</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="o">.</span><span class="n">data</span><span class="p">(</span><span class="s1">'time'</span><span class="p">))</span>
-<span class="go">[(0, None), (1, '5pm'), (2, None)]</span>
-</pre></div>
-</div>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="s1">'time'</span><span class="p">,</span> <span class="n">default</span><span class="o">=</span><span class="s1">'Not Available'</span><span class="p">))</span>
-<span class="go">[(0, 'Not Available'), (1, '5pm'), (2, 'Not Available')]</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="o">.</span><span class="n">data</span><span class="p">(</span><span class="s1">'time'</span><span class="p">,</span> <span class="n">default</span><span class="o">=</span><span class="s1">'Not Available'</span><span class="p">))</span>
-<span class="go">[(0, 'Not Available'), (1, '5pm'), (2, 'Not Available')]</span>
-</pre></div>
-</div>
-<p>If some of your nodes have an attribute and the rest are assumed
-to have a default attribute value you can create a dictionary
-from node/attribute pairs using the <cite>default</cite> keyword argument
-to guarantee the value is never None:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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="mi">0</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="mi">1</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="mi">2</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="mi">2</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="mi">3</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="nb">dict</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="s1">'weight'</span><span class="p">,</span> <span class="n">default</span><span class="o">=</span><span class="mi">1</span><span class="p">))</span>
-<span class="go">{0: 1, 1: 2, 2: 3}</span>
-</pre></div>
-</div>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.number_of_edges">
-<code class="descname">number_of_edges</code><span class="sig-paren">(</span><em>u=None</em>, <em>v=None</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.number_of_edges" title="Permalink to this definition">¶</a></dt>
-<dd><p>Return the number of edges between two nodes.</p>
-<dl class="docutils">
-<dt>u, v <span class="classifier-delimiter">:</span> <span class="classifier">nodes, optional (default=all edges)</span></dt>
-<dd>If u and v are specified, return the number of edges between
-u and v. Otherwise return the total number of all edges.</dd>
-</dl>
-<dl class="docutils">
-<dt>nedges <span class="classifier-delimiter">:</span> <span class="classifier">int</span></dt>
-<dd>The number of edges in the graph. If nodes <cite>u</cite> and <cite>v</cite> are
-specified return the number of edges between those nodes. If
-the graph is directed, this only returns the number of edges
-from <cite>u</cite> to <cite>v</cite>.</dd>
-</dl>
-<p>size</p>
-<p>For undirected graphs, this method counts the total number of
-edges in the graph:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">path_graph</span><span class="p">(</span><span class="mi">4</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">number_of_edges</span><span class="p">()</span>
-<span class="go">3</span>
-</pre></div>
-</div>
-<p>If you specify two nodes, this counts the total number of edges
-joining the two nodes:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">number_of_edges</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="go">1</span>
-</pre></div>
-</div>
-<p>For directed graphs, this method can count the total number of
-directed edges from <cite>u</cite> to <cite>v</cite>:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">DiGraph</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="mi">0</span><span class="p">,</span> <span class="mi">1</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="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">number_of_edges</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="go">1</span>
-</pre></div>
-</div>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.number_of_nodes">
-<code class="descname">number_of_nodes</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.number_of_nodes" title="Permalink to this definition">¶</a></dt>
-<dd><p>Return the number of nodes in the graph.</p>
-<dl class="docutils">
-<dt>nnodes <span class="classifier-delimiter">:</span> <span class="classifier">int</span></dt>
-<dd>The number of nodes in the graph.</dd>
-</dl>
-<p>order, __len__ which are identical</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">path_graph</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span> <span class="c1"># or DiGraph, MultiGraph, MultiDiGraph, etc</span>
-<span class="gp">>>> </span><span class="nb">len</span><span class="p">(</span><span class="n">G</span><span class="p">)</span>
-<span class="go">3</span>
-</pre></div>
-</div>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.order">
-<code class="descname">order</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.order" title="Permalink to this definition">¶</a></dt>
-<dd><p>Return the number of nodes in the graph.</p>
-<dl class="docutils">
-<dt>nnodes <span class="classifier-delimiter">:</span> <span class="classifier">int</span></dt>
-<dd>The number of nodes in the graph.</dd>
-</dl>
-<p>number_of_nodes, __len__ which are identical</p>
-</dd></dl>
-
-<dl class="attribute">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.out_degree">
-<code class="descname">out_degree</code><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.out_degree" title="Permalink to this definition">¶</a></dt>
-<dd><p>An OutDegreeView for (node, out_degree)</p>
-<p>The node out_degree is the number of edges pointing out of the node.
-The weighted node degree is the sum of the edge weights for
-edges incident to that node.</p>
-<p>This object provides an iterator over (node, out_degree) as well as
-lookup for the degree for a single node.</p>
-<dl class="docutils">
-<dt>nbunch <span class="classifier-delimiter">:</span> <span class="classifier">single node, container, or all nodes (default= all nodes)</span></dt>
-<dd>The view will only report edges incident to these nodes.</dd>
-<dt>weight <span class="classifier-delimiter">:</span> <span class="classifier">string or None, optional (default=None)</span></dt>
-<dd>The name of an edge attribute that holds the numerical value used
-as a weight. If None, then each edge has weight 1.
-The degree is the sum of the edge weights adjacent to the node.</dd>
-</dl>
-<p>If a single node is requested
-deg : int</p>
-<blockquote>
-<div>Out-degree of the node</div></blockquote>
-<p>OR if multiple nodes are requested
-nd_iter : iterator</p>
-<blockquote>
-<div>The iterator returns two-tuples of (node, out-degree).</div></blockquote>
-<p>degree, in_degree</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">DiGraph</span><span class="p">()</span>
-<span class="gp">>>> </span><span class="n">nx</span><span class="o">.</span><span class="n">add_path</span><span class="p">(</span><span class="n">G</span><span class="p">,</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">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">])</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">out_degree</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span> <span class="c1"># node 0 with degree 1</span>
-<span class="go">1</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">out_degree</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">2</span><span class="p">]))</span>
-<span class="go">[(0, 1), (1, 1), (2, 1)]</span>
-</pre></div>
-</div>
-</dd></dl>
-
-<dl class="attribute">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.out_edges">
-<code class="descname">out_edges</code><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.out_edges" title="Permalink to this definition">¶</a></dt>
-<dd><p>An OutEdgeView of the DiGraph as G.edges or G.edges().</p>
-<p>edges(self, nbunch=None, data=False, default=None)</p>
-<p>The OutEdgeView provides set-like operations on the edge-tuples
-as well as edge attribute lookup. When called, it also provides
-an EdgeDataView object which allows control of access to edge
-attributes (but does not provide set-like operations).
-Hence, <cite>G.edges[u, v][‘color’]</cite> provides the value of the color
-attribute for edge <cite>(u, v)</cite> while
-<cite>for (u, v, c) in G.edges.data(‘color’, default=’red’):</cite>
-iterates through all the edges yielding the color attribute
-with default <cite>‘red’</cite> if no color attribute exists.</p>
-<dl class="docutils">
-<dt>nbunch <span class="classifier-delimiter">:</span> <span class="classifier">single node, container, or all nodes (default= all nodes)</span></dt>
-<dd>The view will only report edges incident to these nodes.</dd>
-<dt>data <span class="classifier-delimiter">:</span> <span class="classifier">string or bool, optional (default=False)</span></dt>
-<dd>The edge attribute returned in 3-tuple (u, v, ddict[data]).
-If True, return edge attribute dict in 3-tuple (u, v, ddict).
-If False, return 2-tuple (u, v).</dd>
-<dt>default <span class="classifier-delimiter">:</span> <span class="classifier">value, optional (default=None)</span></dt>
-<dd>Value used for edges that dont have the requested attribute.
-Only relevant if data is not True or False.</dd>
-</dl>
-<dl class="docutils">
-<dt>edges <span class="classifier-delimiter">:</span> <span class="classifier">OutEdgeView</span></dt>
-<dd>A view of edge attributes, usually it iterates over (u, v)
-or (u, v, d) tuples of edges, but can also be used for
-attribute lookup as <cite>edges[u, v][‘foo’]</cite>.</dd>
-</dl>
-<p>in_edges, out_edges</p>
-<p>Nodes in nbunch that are not in the graph will be (quietly) ignored.
-For directed graphs this returns the out-edges.</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">DiGraph</span><span class="p">()</span> <span class="c1"># or MultiDiGraph, etc</span>
-<span class="gp">>>> </span><span class="n">nx</span><span class="o">.</span><span class="n">add_path</span><span class="p">(</span><span class="n">G</span><span class="p">,</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">2</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="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="mi">5</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="p">[</span><span class="n">e</span> <span class="k">for</span> <span class="n">e</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="go">[(0, 1), (1, 2), (2, 3)]</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">edges</span><span class="o">.</span><span class="n">data</span><span class="p">()</span> <span class="c1"># default data is {} (empty dict)</span>
-<span class="go">OutEdgeDataView([(0, 1, {}), (1, 2, {}), (2, 3, {'weight': 5})])</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">edges</span><span class="o">.</span><span class="n">data</span><span class="p">(</span><span class="s1">'weight'</span><span class="p">,</span> <span class="n">default</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
-<span class="go">OutEdgeDataView([(0, 1, 1), (1, 2, 1), (2, 3, 5)])</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">edges</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="mi">2</span><span class="p">])</span> <span class="c1"># only edges incident to these nodes</span>
-<span class="go">OutEdgeDataView([(0, 1), (2, 3)])</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">edges</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span> <span class="c1"># only edges incident to a single node (use G.adj[0]?)</span>
-<span class="go">OutEdgeDataView([(0, 1)])</span>
-</pre></div>
-</div>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.plot_adjacency_matrix">
-<code class="descname">plot_adjacency_matrix</code><span class="sig-paren">(</span><em>fig_num=1</em>, <em>fig_size=(7</em>, <em>7)</em>, <em>show_now=True</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.plot_adjacency_matrix" title="Permalink to this definition">¶</a></dt>
-<dd><p>Draw the adjacency matrix in a plot window.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
-<li><strong>fig_num</strong> – figure number</li>
-<li><strong>fig_size</strong> – figure size</li>
-<li><strong>show_now</strong> – Boolean whether to plot directly (pausing the execution until the plot is closed), or not.</li>
-</ul>
-</td>
-</tr>
-</tbody>
-</table>
+<dl class="method">
+<dt id="kadmos.graph.graph_kadmos.KadmosGraph.plot_adjacency_matrix">
+<code class="descname">plot_adjacency_matrix</code><span class="sig-paren">(</span><em>fig_num=1</em>, <em>fig_size=(7</em>, <em>7)</em>, <em>show_now=True</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.plot_adjacency_matrix" title="Permalink to this definition">¶</a></dt>
+<dd><p>Draw the adjacency matrix in a plot window.</p>
+<table class="docutils field-list" frame="void" rules="none">
+<col class="field-name" />
+<col class="field-body" />
+<tbody valign="top">
+<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
+<li><strong>fig_num</strong> – figure number</li>
+<li><strong>fig_size</strong> – figure size</li>
+<li><strong>show_now</strong> – Boolean whether to plot directly (pausing the execution until the plot is closed), or not.</li>
+</ul>
+</td>
+</tr>
+</tbody>
+</table>
</dd></dl>
<dl class="method">
<dt id="kadmos.graph.graph_kadmos.KadmosGraph.plot_graph">
<code class="descname">plot_graph</code><span class="sig-paren">(</span><em>fig_num=1</em>, <em>color_setting='default'</em>, <em>positioning='circular'</em>, <em>save_as=None</em>, <em>show_now=True</em>, <em>title=None</em>, <em>edge_label=False</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.plot_graph" title="Permalink to this definition">¶</a></dt>
<dd><p>Function to plot a graph.</p>
-<p>Note that you need to add matplotlib.pyplot.show() at the end of your code to see the plot window.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
-<li><strong>fig_num</strong> – figure number</li>
-<li><strong>fig_size</strong> – size of figure window</li>
-<li><strong>color_setting</strong> – choose from ‘default’, ‘sinks’, ‘categories’, ‘partitions’</li>
-<li><strong>positioning</strong> – choose from ‘circular’, ‘spring’</li>
-<li><strong>save_as</strong> – save plot as figure file</li>
-<li><strong>show_now</strong> – Boolean whether to plot directly (pausing the execution until the plot is closed), or not.</li>
-<li><strong>title</strong> – title string of the graph</li>
-<li><strong>edge_label</strong> – edge attribute that will be shown for each edge in graph</li>
+<li><strong>fig_num</strong> (<em>int</em>) – figure number</li>
+<li><strong>color_setting</strong> (<em>str</em>) – choose from ‘default’, ‘sinks’, ‘categories’, ‘partitions’</li>
+<li><strong>positioning</strong> (<em>str</em>) – choose from ‘circular’, ‘spring’</li>
+<li><strong>save_as</strong> (<em>bool</em>) – save plot as figure file</li>
+<li><strong>show_now</strong> (<em>bool</em>) – Boolean whether to plot directly (pausing the execution until the plot is closed), or not.</li>
+<li><strong>title</strong> (<em>str</em>) – title of the graph</li>
+<li><strong>edge_label</strong> (<em>str</em>) – edge attribute that will be shown for each edge in graph</li>
</ul>
</td>
</tr>
@@ -2674,26 +1774,10 @@ For directed graphs this returns the out-edges.</p>
</tr>
</tbody>
</table>
-</dd></dl>
-
-<dl class="attribute">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.pred">
-<code class="descname">pred</code><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.pred" title="Permalink to this definition">¶</a></dt>
-<dd><p>Graph adjacency object holding the predecessors of each node.</p>
-<p>This object is a read-only dict-like structure with node keys
-and neighbor-dict values. The neighbor-dict is keyed by neighbor
-to the edge-data-dict. So <cite>G.pred[2][3][‘color’] = ‘blue’</cite> sets
-the color of the edge <cite>(3, 2)</cite> to <cite>“blueâ€</cite>.</p>
-<p>Iterating over G.pred behaves like a dict. Useful idioms include
-<cite>for nbr, datadict in G.pred[n].items():</cite>. A data-view not provided
-by dicts also exists: <cite>for nbr, foovalue in G.pred[node].data(‘foo’):</cite>
-A default can be set via a <cite>default</cite> argument to the <cite>data</cite> method.</p>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.predecessors">
-<code class="descname">predecessors</code><span class="sig-paren">(</span><em>n</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.predecessors" title="Permalink to this definition">¶</a></dt>
-<dd><p>Return an iterator over predecessor nodes of n.</p>
+<div class="admonition hint">
+<p class="first admonition-title">Hint</p>
+<p class="last">if the plot window is not showing, you need to add matplotlib.pyplot.show() at the end of your code</p>
+</div>
</dd></dl>
<dl class="method">
@@ -2718,7 +1802,9 @@ A default can be set via a <cite>default</cite> argument to the <cite>data</cite
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>mapping</strong> (<em>None</em><em>, </em><em>True</em>) – application of mapping required, optional (default=None)</td>
+<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>mapping</strong> (<em>None</em><em>, </em><em>bool</em>) – application of mapping required, optional (default=None)</td>
+</tr>
+<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">relabeled graph</td>
</tr>
</tbody>
</table>
@@ -2727,164 +1813,59 @@ A default can be set via a <cite>default</cite> argument to the <cite>data</cite
<li>Minimum information: ID</li>
<li>Maximum information: ID[modeID][instanceID][version]</li>
</ul>
-<p>Note: modeID, instanceID and version are only provided if there is a function with the same ID that requires
+<div class="admonition note">
+<p class="first admonition-title">Note</p>
+<p class="last">modeID, instanceID and version are only provided if there is a function with the same ID that requires
this specification to differentiate between the functions.</p>
+</div>
<p>Example:</p>
<p>Design competences (full information):</p>
-<ul class="simple">
+<ol class="arabic simple">
<li>Aerodynamics[A][1][v1]</li>
<li>Aerodynamics[A][2][v1]</li>
<li>Aerodynamics[B][1][v1]</li>
<li>Structures[A][1][v1]</li>
<li>Structures[A}[1][v2]</li>
<li>Propulsion[A][1][v2]</li>
-</ul>
+</ol>
<p>Design competences relabeled:</p>
-<ul class="simple">
+<ol class="arabic simple">
<li>Aerodynamics[A][1]</li>
<li>Aerodynamics[A][2]</li>
<li>Aerodynamics[B][1]</li>
<li>Structure[v1]</li>
<li>Structure[v2]</li>
<li>Propulsion</li>
-</ul>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.remove_edge">
-<code class="descname">remove_edge</code><span class="sig-paren">(</span><em>u</em>, <em>v</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.remove_edge" title="Permalink to this definition">¶</a></dt>
-<dd><p>Remove the edge between u and v.</p>
-<dl class="docutils">
-<dt>u, v <span class="classifier-delimiter">:</span> <span class="classifier">nodes</span></dt>
-<dd>Remove the edge between nodes u and v.</dd>
-</dl>
-<dl class="docutils">
-<dt>NetworkXError</dt>
-<dd>If there is not an edge between u and v.</dd>
-</dl>
-<p>remove_edges_from : remove a collection of edges</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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="c1"># or DiGraph, etc</span>
-<span class="gp">>>> </span><span class="n">nx</span><span class="o">.</span><span class="n">add_path</span><span class="p">(</span><span class="n">G</span><span class="p">,</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">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">])</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">remove_edge</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="gp">>>> </span><span class="n">e</span> <span class="o">=</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="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">remove_edge</span><span class="p">(</span><span class="o">*</span><span class="n">e</span><span class="p">)</span> <span class="c1"># unpacks e from an edge tuple</span>
-<span class="gp">>>> </span><span class="n">e</span> <span class="o">=</span> <span class="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="p">{</span><span class="s1">'weight'</span><span class="p">:</span><span class="mi">7</span><span class="p">})</span> <span class="c1"># an edge with attribute data</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">remove_edge</span><span class="p">(</span><span class="o">*</span><span class="n">e</span><span class="p">[:</span><span class="mi">2</span><span class="p">])</span> <span class="c1"># select first part of edge tuple</span>
-</pre></div>
-</div>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.remove_edges_from">
-<code class="descname">remove_edges_from</code><span class="sig-paren">(</span><em>ebunch</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.remove_edges_from" title="Permalink to this definition">¶</a></dt>
-<dd><p>Remove all edges specified in ebunch.</p>
-<dl class="docutils">
-<dt>ebunch: list or container of edge tuples</dt>
-<dd><p class="first">Each edge given in the list or container will be removed
-from the graph. The edges can be:</p>
-<blockquote class="last">
-<div><ul class="simple">
-<li>2-tuples (u, v) edge between u and v.</li>
-<li>3-tuples (u, v, k) where k is ignored.</li>
-</ul>
-</div></blockquote>
-</dd>
-</dl>
-<p>remove_edge : remove a single edge</p>
-<p>Will fail silently if an edge in ebunch is not in the graph.</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">path_graph</span><span class="p">(</span><span class="mi">4</span><span class="p">)</span> <span class="c1"># or DiGraph, MultiGraph, MultiDiGraph, etc</span>
-<span class="gp">>>> </span><span class="n">ebunch</span> <span class="o">=</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="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">)]</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">remove_edges_from</span><span class="p">(</span><span class="n">ebunch</span><span class="p">)</span>
-</pre></div>
-</div>
+</ol>
</dd></dl>
<dl class="method">
<dt id="kadmos.graph.graph_kadmos.KadmosGraph.remove_function_nodes">
<code class="descname">remove_function_nodes</code><span class="sig-paren">(</span><em>*args</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.remove_function_nodes" title="Permalink to this definition">¶</a></dt>
<dd><p>Function that removes a function node</p>
-<p>Also the input and output variables that only have links to this specific function node are deleted. A simple
-remove_node of a function node might lead to unconnected variables in the graph.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>args</strong> (<em>str</em><em> or </em><em>list</em>) – function node id(s)</td>
+<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>args</strong> (<em>str</em><em>, </em><em>list</em>) – function node id(s)</td>
+</tr>
+<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">graph with nodes removed</td>
+</tr>
+<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><a class="reference internal" href="#kadmos.graph.graph_kadmos.KadmosGraph" title="kadmos.graph.graph_kadmos.KadmosGraph">KadmosGraph</a></td>
</tr>
</tbody>
</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.remove_node">
-<code class="descname">remove_node</code><span class="sig-paren">(</span><em>n</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.remove_node" title="Permalink to this definition">¶</a></dt>
-<dd><p>Remove node n.</p>
-<p>Removes the node n and all adjacent edges.
-Attempting to remove a non-existent node will raise an exception.</p>
-<dl class="docutils">
-<dt>n <span class="classifier-delimiter">:</span> <span class="classifier">node</span></dt>
-<dd>A node in the graph</dd>
-</dl>
-<dl class="docutils">
-<dt>NetworkXError</dt>
-<dd>If n is not in the graph.</dd>
-</dl>
-<p>remove_nodes_from</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">path_graph</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span> <span class="c1"># or DiGraph, MultiGraph, MultiDiGraph, etc</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">edges</span><span class="p">)</span>
-<span class="go">[(0, 1), (1, 2)]</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">remove_node</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">edges</span><span class="p">)</span>
-<span class="go">[]</span>
-</pre></div>
-</div>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.remove_nodes_from">
-<code class="descname">remove_nodes_from</code><span class="sig-paren">(</span><em>nodes</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.remove_nodes_from" title="Permalink to this definition">¶</a></dt>
-<dd><p>Remove multiple nodes.</p>
-<dl class="docutils">
-<dt>nodes <span class="classifier-delimiter">:</span> <span class="classifier">iterable container</span></dt>
-<dd>A container of nodes (list, dict, set, etc.). If a node
-in the container is not in the graph it is silently ignored.</dd>
-</dl>
-<p>remove_node</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">path_graph</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span> <span class="c1"># or DiGraph, MultiGraph, MultiDiGraph, etc</span>
-<span class="gp">>>> </span><span class="n">e</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="n">e</span>
-<span class="go">[0, 1, 2]</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">remove_nodes_from</span><span class="p">(</span><span class="n">e</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">)</span>
-<span class="go">[]</span>
-</pre></div>
+<div class="admonition attention">
+<p class="first admonition-title">Attention</p>
+<p class="last">Also the input and output variables that only have links to this specific function node are
+deleted. A simple remove_node of a function node might lead to unconnected variables in the graph.</p>
</div>
</dd></dl>
-<dl class="method">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.reverse">
-<code class="descname">reverse</code><span class="sig-paren">(</span><em>copy=True</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.reverse" title="Permalink to this definition">¶</a></dt>
-<dd><p>Return the reverse of the graph.</p>
-<p>The reverse is a graph with the same nodes and edges
-but with the directions of the edges reversed.</p>
-<dl class="docutils">
-<dt>copy <span class="classifier-delimiter">:</span> <span class="classifier">bool optional (default=True)</span></dt>
-<dd>If True, return a new DiGraph holding the reversed edges.
-If False, the reverse graph is created using a view of
-the original graph.</dd>
-</dl>
-</dd></dl>
-
<dl class="method">
<dt id="kadmos.graph.graph_kadmos.KadmosGraph.save">
-<code class="descname">save</code><span class="sig-paren">(</span><em>file_name</em>, <em>file_type='kdms'</em>, <em>graph_check_critical=True</em>, <em>destination_folder=None</em>, <em>mpg=None</em>, <em>description=''</em>, <em>creator=''</em>, <em>version='1.0'</em>, <em>timestamp=datetime.datetime(2018</em>, <em>3</em>, <em>31</em>, <em>17</em>, <em>25</em>, <em>15</em>, <em>655000)</em>, <em>keep_empty_elements=False</em>, <em>pretty_print=False</em>, <em>convention=True</em>, <em>integrity=False</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.save" title="Permalink to this definition">¶</a></dt>
+<code class="descname">save</code><span class="sig-paren">(</span><em>file_name</em>, <em>file_type='kdms'</em>, <em>graph_check_critical=True</em>, <em>destination_folder=None</em>, <em>mpg=None</em>, <em>description=''</em>, <em>creator=''</em>, <em>version='1.0'</em>, <em>timestamp=datetime.datetime(2018</em>, <em>4</em>, <em>6</em>, <em>17</em>, <em>45</em>, <em>52</em>, <em>369000)</em>, <em>keep_empty_elements=False</em>, <em>pretty_print=False</em>, <em>convention=True</em>, <em>integrity=False</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.save" title="Permalink to this definition">¶</a></dt>
<dd><p>Method to save the graph.</p>
-<p>Different output file types are implemented for saving graphs. They are listed below:</p>
-<ul class="simple">
-<li>kdms: the most simple file type which makes use of pickling</li>
-<li>cmdows: the most versatile file type especially suited for file exchange with other tools</li>
-<li>graphml: another file type especially suited for file exchange with other tools based on graphs</li>
-</ul>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
@@ -2897,7 +1878,7 @@ the original graph.</dd>
<li><strong>mpg</strong> (<a class="reference internal" href="#kadmos.graph.graph_process.MdaoProcessGraph" title="kadmos.graph.graph_process.MdaoProcessGraph"><em>MdaoProcessGraph</em></a>) – optional MPG graph to be saved with MDG</li>
<li><strong>description</strong> (<em>str</em>) – description of the file (only applicable for the cmdows file type)</li>
<li><strong>creator</strong> (<em>str</em>) – name of the creator of the file (only applicable for the cmdows file type)</li>
-<li><strong>version</strong> (<em>str | float | int</em>) – version of the file (only applicable for the cmdows file type)</li>
+<li><strong>version</strong> (<em>str</em><em>, </em><em>float</em><em>, </em><em>int</em>) – version of the file (only applicable for the cmdows file type)</li>
<li><strong>timestamp</strong> (<em>datetime</em>) – timestamp to be saved in the file (only applicable for the cmdows file type)</li>
<li><strong>keep_empty_elements</strong> (<em>bool</em>) – option for keeping empty XML elements (only applicable for the cmdows file type)</li>
<li><strong>pretty_print</strong> (<em>bool</em>) – option for pretty XML printing (only applicable for the cmdows file type)</li>
@@ -2908,57 +1889,37 @@ the original graph.</dd>
</tr>
</tbody>
</table>
+<div class="admonition note">
+<p class="first admonition-title">Note</p>
+<p>Different output file types are implemented for saving graphs. They are listed below:</p>
+<ul class="last simple">
+<li>kdms: the most simple file type which makes use of pickling</li>
+<li>cmdows: the most versatile file type especially suited for file exchange with other tools</li>
+<li>graphml: another file type especially suited for file exchange with other tools based on graphs</li>
+</ul>
+</div>
</dd></dl>
<dl class="method">
<dt id="kadmos.graph.graph_kadmos.KadmosGraph.select_objectives_from_graph">
<code class="descname">select_objectives_from_graph</code><span class="sig-paren">(</span><em>*args</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.select_objectives_from_graph" title="Permalink to this definition">¶</a></dt>
<dd><p>This functions lets the user select one or more objective functions from the graph.</p>
-<p>Only functions can be selected as objectives. If no arguments are provided, user is prompted to select an
-objective from all functions in graph.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Param:</th><td class="field-body">args: objective functions to choose from</td>
+<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>args</strong> (<em>str</em>) – objective functions to choose from</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">list of objective functions</td>
</tr>
+<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body">list</td>
+</tr>
</tbody>
</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.size">
-<code class="descname">size</code><span class="sig-paren">(</span><em>weight=None</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.size" title="Permalink to this definition">¶</a></dt>
-<dd><p>Return the number of edges or total of all edge weights.</p>
-<dl class="docutils">
-<dt>weight <span class="classifier-delimiter">:</span> <span class="classifier">string or None, optional (default=None)</span></dt>
-<dd>The edge attribute that holds the numerical value used
-as a weight. If None, then each edge has weight 1.</dd>
-</dl>
-<dl class="docutils">
-<dt>size <span class="classifier-delimiter">:</span> <span class="classifier">numeric</span></dt>
-<dd><p class="first">The number of edges or
-(if weight keyword is provided) the total weight sum.</p>
-<p class="last">If weight is None, returns an int. Otherwise a float
-(or more general numeric if the weights are more general).</p>
-</dd>
-</dl>
-<p>number_of_edges</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">path_graph</span><span class="p">(</span><span class="mi">4</span><span class="p">)</span> <span class="c1"># or DiGraph, MultiGraph, MultiDiGraph, etc</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">size</span><span class="p">()</span>
-<span class="go">3</span>
-</pre></div>
-</div>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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="c1"># or DiGraph, MultiGraph, MultiDiGraph, etc</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="s1">'a'</span><span class="p">,</span> <span class="s1">'b'</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="mi">2</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="s1">'b'</span><span class="p">,</span> <span class="s1">'c'</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="mi">4</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">size</span><span class="p">()</span>
-<span class="go">2</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">size</span><span class="p">(</span><span class="n">weight</span><span class="o">=</span><span class="s1">'weight'</span><span class="p">)</span>
-<span class="go">6.0</span>
-</pre></div>
+<div class="admonition note">
+<p class="first admonition-title">Note</p>
+<p class="last">Only functions can be selected as objectives. If no arguments are provided, user is prompted to select
+an objective from all functions in graph.</p>
</div>
</dd></dl>
@@ -2966,28 +1927,35 @@ as a weight. If None, then each edge has weight 1.</dd>
<dt id="kadmos.graph.graph_kadmos.KadmosGraph.split_variables">
<code class="descname">split_variables</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.split_variables" title="Permalink to this definition">¶</a></dt>
<dd><p>Method to split a problematic variable node into multiple separate valid nodes.</p>
+<table class="docutils field-list" frame="void" rules="none">
+<col class="field-name" />
+<col class="field-body" />
+<tbody valign="top">
+<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
+<li><strong>args</strong> (<em>basestring</em><em>, </em><em>list</em>) – problematic node in the graph</li>
+<li><strong>kwargs</strong> – </li>
+</ul>
+</td>
+</tr>
+<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">graph with split variables</p>
+</td>
+</tr>
+<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last"><a class="reference internal" href="#kadmos.graph.graph_kadmos.KadmosGraph" title="kadmos.graph.graph_kadmos.KadmosGraph">KadmosGraph</a></p>
+</td>
+</tr>
+</tbody>
+</table>
<p>The following variables are considered problematic and will be handled by this function:</p>
-<blockquote>
-<div><ul>
-<li><p class="first">pure circular coupling</p>
-</li>
-<li><p class="first">shared circular coupling</p>
-</li>
-<li><p class="first">collided coupling</p>
-</li>
-<li><p class="first">collision</p>
-</li>
-<li><p class="first">collided circular coupling</p>
-</li>
-<li><p class="first">collided shared coupling</p>
-</li>
-<li><p class="first">collided shared circular coupling</p>
-<blockquote>
-<div><p>The following table shows an example situation for each of the different problematic variables:</p>
-</div></blockquote>
-</li>
+<ul class="simple">
+<li>pure circular coupling</li>
+<li>shared circular coupling</li>
+<li>collided coupling</li>
+<li>collision</li>
+<li>collided circular coupling</li>
+<li>collided shared coupling</li>
+<li>collided shared circular coupling</li>
</ul>
-</div></blockquote>
+<p>The following table shows an example situation for each of the different problematic variables:</p>
<table border="1" class="docutils">
<colgroup>
<col width="22%" />
@@ -3062,524 +2030,197 @@ F5, F6</td>
</tr>
</tbody>
</table>
+</dd></dl>
+
+</dd></dl>
+
+</div>
+<div class="section" id="datagraph">
+<h3>DataGraph<a class="headerlink" href="#datagraph" title="Permalink to this headline">¶</a></h3>
+<dl class="class">
+<dt id="kadmos.graph.graph_data.DataGraph">
+<em class="property">class </em><code class="descclassname">kadmos.graph.graph_data.</code><code class="descname">DataGraph</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph" title="Permalink to this definition">¶</a></dt>
+<dd><dl class="method">
+<dt id="kadmos.graph.graph_data.DataGraph.get_coupling_dictionary">
+<code class="descname">get_coupling_dictionary</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.get_coupling_dictionary" title="Permalink to this definition">¶</a></dt>
+<dd><p>Function to get a coupling dictionary.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>args</strong> (<em>basestring</em><em>, </em><em>list</em>) – problematic node in the graph</td>
+<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">coupling dictionary</td>
+</tr>
+<tr class="field-even field"><th class="field-name">Return type:</th><td class="field-body">dict</td>
</tr>
</tbody>
</table>
+<p>For each function node, the dictionary indicates from which function
+nodes it gets its input and the number of variables it gets.</p>
+<ul class="simple">
+<li>F2 ==> x1, x2 ==> F1</li>
+<li>F3 ==> x3 ==> F1</li>
+</ul>
+<p>Will give: {F1: {F2: 2, F3: 1}}</p>
</dd></dl>
<dl class="method">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.subgraph">
-<code class="descname">subgraph</code><span class="sig-paren">(</span><em>nodes</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.subgraph" title="Permalink to this definition">¶</a></dt>
-<dd><p>Return a SubGraph view of the subgraph induced on <cite>nodes</cite>.</p>
-<p>The induced subgraph of the graph contains the nodes in <cite>nodes</cite>
-and the edges between those nodes.</p>
-<dl class="docutils">
-<dt>nodes <span class="classifier-delimiter">:</span> <span class="classifier">list, iterable</span></dt>
-<dd>A container of nodes which will be iterated through once.</dd>
-</dl>
-<dl class="docutils">
-<dt>G <span class="classifier-delimiter">:</span> <span class="classifier">SubGraph View</span></dt>
-<dd>A subgraph view of the graph. The graph structure cannot be
-changed but node/edge attributes can and are shared with the
-original graph.</dd>
-</dl>
-<p>The graph, edge and node attributes are shared with the original graph.
-Changes to the graph structure is ruled out by the view, but changes
-to attributes are reflected in the original graph.</p>
-<p>To create a subgraph with its own copy of the edge/node attributes use:
-G.subgraph(nodes).copy()</p>
-<p>For an inplace reduction of a graph to a subgraph you can remove nodes:
-G.remove_nodes_from([n for n in G if n not in set(nodes)])</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">path_graph</span><span class="p">(</span><span class="mi">4</span><span class="p">)</span> <span class="c1"># or DiGraph, MultiGraph, MultiDiGraph, etc</span>
-<span class="gp">>>> </span><span class="n">H</span> <span class="o">=</span> <span class="n">G</span><span class="o">.</span><span class="n">subgraph</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">2</span><span class="p">])</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">H</span><span class="o">.</span><span class="n">edges</span><span class="p">)</span>
-<span class="go">[(0, 1), (1, 2)]</span>
-</pre></div>
-</div>
-</dd></dl>
-
-<dl class="attribute">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.succ">
-<code class="descname">succ</code><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.succ" title="Permalink to this definition">¶</a></dt>
-<dd><p>Graph adjacency object holding the successors of each node.</p>
-<p>This object is a read-only dict-like structure with node keys
-and neighbor-dict values. The neighbor-dict is keyed by neighbor
-to the edge-data-dict. So <cite>G.succ[3][2][‘color’] = ‘blue’</cite> sets
-the color of the edge <cite>(3, 2)</cite> to <cite>“blueâ€</cite>.</p>
-<p>Iterating over G.succ behaves like a dict. Useful idioms include
-<cite>for nbr, datadict in G.succ[n].items():</cite>. A data-view not provided
-by dicts also exists: <cite>for nbr, foovalue in G.succ[node].data(‘foo’):</cite>
-and a default can be set via a <cite>default</cite> argument to the <cite>data</cite> method.</p>
-<p>The neighbor information is also provided by subscripting the graph.
-So <cite>for nbr, foovalue in G[node].data(‘foo’, default=1):</cite> works.</p>
-<p>For directed graphs, <cite>G.adj</cite> is identical to <cite>G.succ</cite>.</p>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.successors">
-<code class="descname">successors</code><span class="sig-paren">(</span><em>n</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.successors" title="Permalink to this definition">¶</a></dt>
-<dd><p>Return an iterator over successor nodes of n.</p>
-<p>neighbors() and successors() are the same.</p>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.to_directed">
-<code class="descname">to_directed</code><span class="sig-paren">(</span><em>as_view=False</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.to_directed" title="Permalink to this definition">¶</a></dt>
-<dd><p>Return a directed representation of the graph.</p>
-<dl class="docutils">
-<dt>G <span class="classifier-delimiter">:</span> <span class="classifier">DiGraph</span></dt>
-<dd>A directed graph with the same name, same nodes, and with
-each edge (u, v, data) replaced by two directed edges
-(u, v, data) and (v, u, data).</dd>
-</dl>
-<p>This returns a “deepcopy†of the edge, node, and
-graph attributes which attempts to completely copy
-all of the data and references.</p>
-<p>This is in contrast to the similar D=DiGraph(G) which returns a
-shallow copy of the data.</p>
-<p>See the Python copy module for more information on shallow
-and deep copies, <a class="reference external" href="https://docs.python.org/2/library/copy.html">https://docs.python.org/2/library/copy.html</a>.</p>
-<p>Warning: If you have subclassed Graph to use dict-like objects
-in the data structure, those changes do not transfer to the
-DiGraph created by this method.</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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="c1"># or MultiGraph, etc</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="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="n">H</span> <span class="o">=</span> <span class="n">G</span><span class="o">.</span><span class="n">to_directed</span><span class="p">()</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">H</span><span class="o">.</span><span class="n">edges</span><span class="p">)</span>
-<span class="go">[(0, 1), (1, 0)]</span>
-</pre></div>
-</div>
-<p>If already directed, return a (deep) copy</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">DiGraph</span><span class="p">()</span> <span class="c1"># or MultiDiGraph, etc</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="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="n">H</span> <span class="o">=</span> <span class="n">G</span><span class="o">.</span><span class="n">to_directed</span><span class="p">()</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">H</span><span class="o">.</span><span class="n">edges</span><span class="p">)</span>
-<span class="go">[(0, 1)]</span>
-</pre></div>
-</div>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.to_undirected">
-<code class="descname">to_undirected</code><span class="sig-paren">(</span><em>reciprocal=False</em>, <em>as_view=False</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.to_undirected" title="Permalink to this definition">¶</a></dt>
-<dd><p>Return an undirected representation of the digraph.</p>
-<dl class="docutils">
-<dt>reciprocal <span class="classifier-delimiter">:</span> <span class="classifier">bool (optional)</span></dt>
-<dd>If True only keep edges that appear in both directions
-in the original digraph.</dd>
-<dt>as_view <span class="classifier-delimiter">:</span> <span class="classifier">bool (optional, default=False)</span></dt>
-<dd>If True return an undirected view of the original directed graph.</dd>
-</dl>
-<dl class="docutils">
-<dt>G <span class="classifier-delimiter">:</span> <span class="classifier">Graph</span></dt>
-<dd>An undirected graph with the same name and nodes and
-with edge (u, v, data) if either (u, v, data) or (v, u, data)
-is in the digraph. If both edges exist in digraph and
-their edge data is different, only one edge is created
-with an arbitrary choice of which edge data to use.
-You must check and correct for this manually if desired.</dd>
-</dl>
-<p>Graph, copy, add_edge, add_edges_from</p>
-<p>If edges in both directions (u, v) and (v, u) exist in the
-graph, attributes for the new undirected edge will be a combination of
-the attributes of the directed edges. The edge data is updated
-in the (arbitrary) order that the edges are encountered. For
-more customized control of the edge attributes use add_edge().</p>
-<p>This returns a “deepcopy†of the edge, node, and
-graph attributes which attempts to completely copy
-all of the data and references.</p>
-<p>This is in contrast to the similar G=DiGraph(D) which returns a
-shallow copy of the data.</p>
-<p>See the Python copy module for more information on shallow
-and deep copies, <a class="reference external" href="https://docs.python.org/2/library/copy.html">https://docs.python.org/2/library/copy.html</a>.</p>
-<p>Warning: If you have subclassed DiGraph to use dict-like objects
-in the data structure, those changes do not transfer to the
-Graph created by this method.</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">path_graph</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span> <span class="c1"># or MultiGraph, etc</span>
-<span class="gp">>>> </span><span class="n">H</span> <span class="o">=</span> <span class="n">G</span><span class="o">.</span><span class="n">to_directed</span><span class="p">()</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">H</span><span class="o">.</span><span class="n">edges</span><span class="p">)</span>
-<span class="go">[(0, 1), (1, 0)]</span>
-<span class="gp">>>> </span><span class="n">G2</span> <span class="o">=</span> <span class="n">H</span><span class="o">.</span><span class="n">to_undirected</span><span class="p">()</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G2</span><span class="o">.</span><span class="n">edges</span><span class="p">)</span>
-<span class="go">[(0, 1)]</span>
-</pre></div>
-</div>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.vistoms_add">
-<code class="descname">vistoms_add</code><span class="sig-paren">(</span><em>vistoms_dir</em>, <em>mpg=None</em>, <em>function_order=None</em>, <em>reference_file=None</em>, <em>compress=False</em>, <em>remove_after_compress=True</em>, <em>graph_id=None</em>, <em>replacement_id=None</em>, <em>xml_file=None</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.vistoms_add" title="Permalink to this definition">¶</a></dt>
-<dd><p>Function to add a graph to a existing VISTOMS instance.</p>
-<p>In one VISTOMS instance different graphs can be shown. For example it is possible to include different
-architectures for the same problem in one VISTOMS instance.</p>
+<dt id="kadmos.graph.graph_data.DataGraph.get_coupling_matrix">
+<code class="descname">get_coupling_matrix</code><span class="sig-paren">(</span><em>function_order_method='manual'</em>, <em>node_selection=None</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.get_coupling_matrix" title="Permalink to this definition">¶</a></dt>
+<dd><p>Function to determine the role of the different functions in the FPG.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
-<li><strong>vistoms_dir</strong> (<em>str</em>) – directory of the VISTOMS directory to be used for addition</li>
-<li><strong>mpg</strong> (<a class="reference internal" href="#kadmos.graph.graph_process.MdaoProcessGraph" title="kadmos.graph.graph_process.MdaoProcessGraph"><em>MdaoProcessGraph</em></a>) – optional MPG graph to be saved with MDG as XDSM (if None a DSM is created)</li>
-<li><strong>function_order</strong> (<em>list</em>) – optional function order for the diagonal of the graph (only applicable for DSMs)</li>
-<li><strong>reference_file</strong> (<em>str</em>) – file from which reference values are extracted (either full path or file in same folder)</li>
-<li><strong>compress</strong> (<em>bool</em>) – setting whether to compress the final VISTOMS instance folder to a zip file</li>
-<li><strong>remove_after_compress</strong> (<em>bool</em>) – setting whether to remove the original folder after compression</li>
-<li><strong>replacement_id</strong> (<em>basestr</em>) – indentifier of the graph to be replaced</li>
-<li><strong>xml_file</strong> (<em>file</em>) – Name of the CMDOWS xml-file</li>
+<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
+<li><strong>function_order_method</strong> (<em>basestring</em>) – algorithm to be used for the order in which the functions are executed.</li>
+<li><strong>node_selection</strong> (<em>list</em>) – selection of nodes for which the coupling matrix will be calculated only</li>
</ul>
</td>
</tr>
+<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">graph with enriched function node attributes and function problem role dictionary</p>
+</td>
+</tr>
+<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last"><a class="reference internal" href="#kadmos.graph.graph_data.FundamentalProblemGraph" title="kadmos.graph.graph_data.FundamentalProblemGraph">FundamentalProblemGraph</a></p>
+</td>
+</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
-<dt id="kadmos.graph.graph_kadmos.KadmosGraph.vistoms_create">
-<code class="descname">vistoms_create</code><span class="sig-paren">(</span><em>vistoms_dir</em>, <em>vistoms_version=None</em>, <em>mpg=None</em>, <em>function_order=None</em>, <em>reference_file=None</em>, <em>compress=False</em>, <em>remove_after_compress=True</em>, <em>graph_id=None</em>, <em>use_png_figs=False</em>, <em>file_refs=None</em>, <em>xml_file=None</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_kadmos.KadmosGraph.vistoms_create" title="Permalink to this definition">¶</a></dt>
-<dd><p>Function to create a new VISTOMS instance from a graph.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
-<li><strong>vistoms_dir</strong> (<em>str</em>) – directory of the VISTOMS directory to be created</li>
-<li><strong>vistoms_version</strong> – version of the VISTOMS instance to be used (as stored in the package itself)</li>
-<li><strong>vispack_version</strong> – str</li>
-<li><strong>mpg</strong> (<a class="reference internal" href="#kadmos.graph.graph_process.MdaoProcessGraph" title="kadmos.graph.graph_process.MdaoProcessGraph"><em>MdaoProcessGraph</em></a>) – optional MPG graph to be saved with MDG as XDSM (if None a DSM is created)</li>
-<li><strong>function_order</strong> (<em>list</em>) – optional function order for the diagonal of the graph (only applicable for DSMs)</li>
-<li><strong>reference_file</strong> (<em>str</em>) – file from which reference values are extracted (either full path or file in same folder)</li>
-<li><strong>compress</strong> (<em>bool</em>) – setting whether to compress the final VISTOMS instance folder to a zip file</li>
-<li><strong>remove_after_compress</strong> (<em>bool</em>) – setting whether to remove the original folder after compression</li>
-<li><strong>graph_id</strong> (<em>basestring</em>) – identifier of the new graph</li>
-<li><strong>use_png_figs</strong> (<em>bool</em>) – setting whether to use the PNG figures instead of the SVG figures for local execution</li>
-<li><strong>file_refs</strong> (<em>dict</em>) – setting to provide file references manually (to use VISTOMS on a server)</li>
-<li><strong>xml_file</strong> (<em>file</em>) – Name of the CMDOWS xml file</li>
-</ul>
-</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-</dd></dl>
-
-</div>
-<div class="section" id="datagraph">
-<h3>DataGraph<a class="headerlink" href="#datagraph" title="Permalink to this headline">¶</a></h3>
-<dl class="class">
-<dt id="kadmos.graph.graph_data.DataGraph">
-<em class="property">class </em><code class="descclassname">kadmos.graph.graph_data.</code><code class="descname">DataGraph</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph" title="Permalink to this definition">¶</a></dt>
-<dd><dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.add_contact">
-<code class="descname">add_contact</code><span class="sig-paren">(</span><em>name</em>, <em>email</em>, <em>uid</em>, <em>company=None</em>, <em>department=None</em>, <em>function=None</em>, <em>address=None</em>, <em>telephone=None</em>, <em>country=None</em>, <em>roles=None</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.add_contact" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to add a contact to the graph organization.</p>
+<dt id="kadmos.graph.graph_data.DataGraph.get_feedback_info">
+<code class="descname">get_feedback_info</code><span class="sig-paren">(</span><em>function_order</em>, <em>coupling_dict</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.get_feedback_info" title="Permalink to this definition">¶</a></dt>
+<dd><p>Function to determine the number of feedback loops for a given function order</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
-<li><strong>name</strong> (<em>str</em>) – name of the contact</li>
-<li><strong>email</strong> (<em>str</em>) – email adress of the contact</li>
-<li><strong>uid</strong> (<em>str</em>) – uid of the contact</li>
-<li><strong>company</strong> (<em>str</em>) – company of which the contact is an employee, optional</li>
-<li><strong>department</strong> (<em>str</em>) – department of company that the contact works at, optional</li>
-<li><strong>function</strong> (<em>str</em>) – the function of the contact, optional</li>
-<li><strong>address</strong> (<em>str</em>) – company address, optional</li>
-<li><strong>telephone</strong> (<em>int</em>) – telephone number of the contact, optional</li>
-<li><strong>country</strong> (<em>str</em>) – country of company, optional</li>
-<li><strong>roles</strong> – organizational role(s) of contact within the project, optional</li>
+<li><strong>function_order</strong> (<em>list</em>) – function order of the nodes</li>
+<li><strong>coupling_dict</strong> (<em>dict</em>) – function couplings</li>
</ul>
</td>
</tr>
-<tr class="field-even field"><th class="field-name">Type:</th><td class="field-body"><p class="first last">str, list</p>
+<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">number of feedback loops</p>
</td>
</tr>
-</tbody>
-</table>
-<p>Optional organizational contact roles:</p>
-<ul class="simple">
-<li>‘architect’</li>
-<li>‘integrator’</li>
-<li>‘collaborativeEngineer’</li>
-<li>‘toolSpecialist’</li>
-<li>‘customer’</li>
-</ul>
-<p>Adding a contact with one organizational role:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">add_contact</span><span class="p">(</span><span class="s1">'Maaike de Wit'</span><span class="p">,</span> <span class="s1">'M.D.deWit@student.tudelft.nl'</span><span class="p">,</span> <span class="s1">'mddewit'</span><span class="p">,</span> <span class="n">company</span><span class="o">=</span><span class="s1">'TU Delft'</span><span class="p">,</span>
-<span class="gp">>>> </span> <span class="n">roles</span><span class="o">=</span><span class="s1">'integrator'</span><span class="p">)</span>
-</pre></div>
-</div>
-<p>Adding a contact with two (or more) organizational roles:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">roles</span> <span class="o">=</span> <span class="p">[</span><span class="s1">'integrator'</span><span class="p">,</span> <span class="s1">'architect'</span><span class="p">]</span>
-<span class="gp">>>> </span><span class="n">add_contact</span><span class="p">(</span><span class="s1">'Maaike de Wit'</span><span class="p">,</span> <span class="s1">'M.D.deWit@student.tudelft.nl'</span><span class="p">,</span> <span class="s1">'mddewit'</span><span class="p">,</span> <span class="n">company</span><span class="o">=</span><span class="s1">'TU Delft'</span><span class="p">,</span> <span class="n">roles</span><span class="o">=</span><span class="n">roles</span><span class="p">)</span>
-</pre></div>
-</div>
-<p>In case the contact uid already exists the old contact attributes are conserved and only new roles are added to
-the roles already present for that contact. To change old contact information, this has to be adjusted in the
-XML-file from which the old contact information is loaded.</p>
-<p>To add (more) roles to the existing contact, it is recommended to use the method: add_contact_roles()</p>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.add_contact_roles">
-<code class="descname">add_contact_roles</code><span class="sig-paren">(</span><em>uid</em>, <em>roles</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.add_contact_roles" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to add roles to existing contacts</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
-<li><strong>uid</strong> (<em>str</em>) – uid of the contact</li>
-<li><strong>roles</strong> (<em>str</em><em>, </em><em>list</em>) – organizational role(s) to be added to the existing contact</li>
-</ul>
+<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last">int</p>
</td>
</tr>
</tbody>
</table>
-<p>Optional organizational contact roles:</p>
-<ul class="simple">
-<li>‘architect’</li>
-<li>‘integrator’</li>
-<li>‘collaborativeEngineer’</li>
-<li>‘toolSpecialist’</li>
-<li>‘customer’</li>
-</ul>
-<p>Adding an organizational role to an existing contact:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">add_contact</span><span class="p">(</span><span class="s1">'mddewit'</span><span class="p">,</span> <span class="n">roles</span><span class="o">=</span><span class="s1">'integrator'</span><span class="p">)</span>
-</pre></div>
-</div>
-<p>Adding two (or more) organizational roles to an existing contact:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">roles</span> <span class="o">=</span> <span class="p">[</span><span class="s1">'integrator'</span><span class="p">,</span> <span class="s1">'architect'</span><span class="p">]</span>
-<span class="gp">>>> </span><span class="n">add_contact</span><span class="p">(</span><span class="s1">'mddewit'</span><span class="p">,</span> <span class="n">company</span><span class="o">=</span><span class="s1">'TU Delft'</span><span class="p">,</span> <span class="n">roles</span><span class="o">=</span><span class="n">roles</span><span class="p">)</span>
-</pre></div>
-</div>
-<p>This method only works for existing contacts. To add a contact use the method: add_contact()</p>
</dd></dl>
<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.add_dc_general_info">
-<code class="descname">add_dc_general_info</code><span class="sig-paren">(</span><em>dc_uid</em>, <em>description</em>, <em>status=None</em>, <em>creation_date=None</em>, <em>owner_uid=None</em>, <em>creator_uid=None</em>, <em>operator_uid=None</em>, <em>model_definition=None</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.add_dc_general_info" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to add general info to a design competence</p>
+<dt id="kadmos.graph.graph_data.DataGraph.get_highest_instance">
+<code class="descname">get_highest_instance</code><span class="sig-paren">(</span><em>node</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.get_highest_instance" title="Permalink to this definition">¶</a></dt>
+<dd><p>Method to get the highest instance of a node.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
-<li><strong>dc_uid</strong> (<em>str</em>) – uid of the design competence</li>
-<li><strong>description</strong> (<em>str</em>) – description of the design competence</li>
-<li><strong>status</strong> (<em>str</em>) – status of the design competence, optional</li>
-<li><strong>creation_date</strong> (<em>date</em>) – creation date of the design competence, optional</li>
-<li><strong>owner_uid</strong> (<em>str</em>) – uid of the owner of the design competence, optional</li>
-<li><strong>creator_uid</strong> (<em>str</em>) – uid of the creator of the design competence, optional</li>
-<li><strong>operator_uid</strong> (<em>str</em>) – uid of the operator of the design competence, optional</li>
-<li><strong>model_definition</strong> (<em>str</em>) – model definition of the design competence, optional</li>
-</ul>
-</td>
+<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>node</strong> (<em>str</em>) – node</td>
</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.add_dc_performance_info">
-<code class="descname">add_dc_performance_info</code><span class="sig-paren">(</span><em>dc_uid</em>, <em>precision=None</em>, <em>fidelity_level=None</em>, <em>run_time=None</em>, <em>verification=None</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.add_dc_performance_info" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to add performance information to a design competence</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
-<li><strong>dc_uid</strong> (<em>str</em>) – uid of the design competence</li>
-<li><strong>precision</strong> (<em>float</em>) – precision of the design competence, optional</li>
-<li><strong>fidelity_level</strong> (<em>int</em>) – the level of fidelity of the design competence, optional</li>
-<li><strong>run_time</strong> (<em>float</em>) – the run time of the design competence, optional</li>
-<li><strong>verification</strong> (<em>str</em>) – verification method of the design competence, optional</li>
-</ul>
-</td>
+<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">highest instance of the node</td>
+</tr>
+<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body">int</td>
</tr>
</tbody>
</table>
-<p>At least one of the optional elements for the performance information has to be defined.</p>
</dd></dl>
<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.add_dc_remote_component_info">
-<code class="descname">add_dc_remote_component_info</code><span class="sig-paren">(</span><em>dc_uid</em>, <em>single_or_multi_execution</em>, <em>job_name</em>, <em>remote_engineer</em>, <em>notification_message</em>, <em>data_exchange_dict=None</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.add_dc_remote_component_info" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to add execution information to a design competence</p>
+<dt id="kadmos.graph.graph_data.DataGraph.get_possible_function_order">
+<code class="descname">get_possible_function_order</code><span class="sig-paren">(</span><em>method</em>, <em>multi_start=None</em>, <em>check_graph=False</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.get_possible_function_order" title="Permalink to this definition">¶</a></dt>
+<dd><p>Method to find a possible function order, in the order: pre-coupled, coupled, post-coupled functions</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
-<li><strong>dc_uid</strong> (<em>str</em>) – uid of the design competence</li>
-<li><strong>single_or_multi_execution</strong> (<em>'single'</em><em> or </em><em>'multiple'</em>) – execution type</li>
-<li><strong>job_name</strong> (<em>str</em>) – job name of the design competence</li>
-<li><strong>remote_engineer</strong> (<em>str</em>) – contact uid of remote engineering of the design competence</li>
-<li><strong>notification_message</strong> (<em>str</em>) – message to notify remote_engineer</li>
-<li><strong>data_exchange_dict</strong> (<em>str</em>) – data exchange settings of the design competence</li>
+<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
+<li><strong>method</strong> (<em>str</em>) – algorithm which will be used to minimize the feedback loops</li>
+<li><strong>multi_start</strong> (<em>int</em>) – start the algorithm from multiple starting points</li>
+<li><strong>check_graph</strong> (<em>bool</em>) – check whether graph has problematic variables</li>
</ul>
</td>
</tr>
-</tbody>
-</table>
-<p>Example use:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">single_or_multi</span> <span class="o">=</span> <span class="s2">"single"</span>
-<span class="gp">>>> </span><span class="n">job_name</span> <span class="o">=</span> <span class="s1">'job_</span><span class="si">{}</span><span class="s1">'</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">fpg</span><span class="o">.</span><span class="n">node</span><span class="p">[</span><span class="n">node</span><span class="p">][</span><span class="s1">'label'</span><span class="p">]</span><span class="o">.</span><span class="n">replace</span><span class="p">(</span><span class="s1">' '</span><span class="p">,</span> <span class="s1">''</span><span class="p">))</span>
-<span class="gp">>>> </span><span class="n">notification_message</span> <span class="o">=</span> <span class="s1">'Hi, could you please run this tool </span><span class="si">{}</span><span class="s1"> for me for my </span><span class="si">{}</span><span class="s1"> AGILE workflow '</span> <span class="s1">'execution. Thanks.'</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">fpg</span><span class="o">.</span><span class="n">node</span><span class="p">[</span><span class="n">node</span><span class="p">][</span><span class="s1">'label'</span><span class="p">]</span><span class="o">.</span><span class="n">replace</span><span class="p">(</span><span class="s1">' '</span><span class="p">,</span> <span class="s1">''</span><span class="p">),</span> <span class="n">architecture</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="n">fpg</span><span class="o">.</span><span class="n">add_dc_remote_component_info</span><span class="p">(</span><span class="n">node</span><span class="p">,</span> <span class="n">single_or_multi</span><span class="p">,</span> <span class="n">job_name</span><span class="p">,</span> <span class="s1">'ivangent'</span><span class="p">,</span> <span class="n">notification_message</span><span class="p">,</span>
-<span class="gp">>>> </span> <span class="n">data_exchange_dict</span><span class="o">=</span><span class="p">{</span><span class="s1">'urlsite'</span><span class="p">:</span> <span class="s1">'some_url'</span><span class="p">,</span>
-<span class="gp">>>> </span> <span class="s1">'folder'</span><span class="p">:</span> <span class="s1">'some_folder'</span><span class="p">})</span>
-</pre></div>
-</div>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.add_default_description">
-<code class="descname">add_default_description</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.add_default_description" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to add a default description attribute to a graph</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">graph with default attribute description</td>
+<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">Possible function order</p>
+</td>
</tr>
-<tr class="field-even field"><th class="field-name">Return type:</th><td class="field-body"><a class="reference internal" href="#kadmos.graph.graph_kadmos.KadmosGraph" title="kadmos.graph.graph_kadmos.KadmosGraph">KadmosGraph</a></td>
+<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last">list</p>
+</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.add_default_name">
-<code class="descname">add_default_name</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.add_default_name" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to add a default name attribute to a graph</p>
+<dt id="kadmos.graph.graph_data.DataGraph.mark_as_constraint">
+<code class="descname">mark_as_constraint</code><span class="sig-paren">(</span><em>node</em>, <em>operator</em>, <em>reference_value</em>, <em>remove_unused_outputs=False</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.mark_as_constraint" title="Permalink to this definition">¶</a></dt>
+<dd><p>Method to mark a node as a constraint.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">graph with default attribute name</td>
+<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
+<li><strong>node</strong> (<em>str</em>) – node to be marked (on the left side of the operator</li>
+<li><strong>operator</strong> (<em>str</em><em> or </em><em>string list</em>) – constraint operator or list of constraint operators</li>
+<li><strong>reference_value</strong> (<em>numbers.Number</em><em> or </em><em>list</em>) – value on the right side of the operator or list of values corresponding to the list of
+operators</li>
+<li><strong>remove_unused_outputs</strong> (<em>bool</em>) – option to remove unused outputs</li>
+</ul>
+</td>
</tr>
-<tr class="field-even field"><th class="field-name">Return type:</th><td class="field-body"><a class="reference internal" href="#kadmos.graph.graph_kadmos.KadmosGraph" title="kadmos.graph.graph_kadmos.KadmosGraph">KadmosGraph</a></td>
+<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">graph with enriched constraint node</p>
+</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.add_edge">
-<code class="descname">add_edge</code><span class="sig-paren">(</span><em>u</em>, <em>v</em>, <em>attr_dict=None</em>, <em>**attr</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.add_edge" title="Permalink to this definition">¶</a></dt>
-<dd><p>Add an edge between u and v.</p>
-<p>The nodes u and v will be automatically added if they are not already in the graph.</p>
-<p>Adding an existing edge results in an update of the edge data.</p>
-<p>Edge attributes can be specified with keywords or by directly accessing the edge’s attribute dictionary.
-See examples below.</p>
+<dt id="kadmos.graph.graph_data.DataGraph.mark_as_constraints">
+<code class="descname">mark_as_constraints</code><span class="sig-paren">(</span><em>nodes</em>, <em>operators</em>, <em>reference_values</em>, <em>remove_unused_outputs=False</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.mark_as_constraints" title="Permalink to this definition">¶</a></dt>
+<dd><p>Method to mark multiple nodes as constraints.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
-<li><strong>v</strong> (<em>u</em><em>,</em>) – nodes</li>
-<li><strong>attr</strong> (<em>Edge data</em><em> (or </em><em>labels</em><em> or </em><em>objects</em><em>) </em><em>can be assigned using keyword arguments.</em>) – keyword arguments, optional</li>
+<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
+<li><strong>nodes</strong> (<em>list</em>) – nodes to be marked.</li>
+<li><strong>operators</strong> (<em>str</em><em>, </em><em>list</em>) – operators to be implemented (as list per node or as single operator for all)</li>
+<li><strong>reference_values</strong> (<em>float</em><em>, </em><em>list</em>) – reference values to be used (as list of values per node or as single value for all)</li>
+<li><strong>remove_unused_outputs</strong> (<em>bool</em>) – option to remove unused outputs</li>
</ul>
</td>
</tr>
-</tbody>
-</table>
-<p>The following examples both add the edge e=(1,2) to graph G:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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="c1"># or DiGraph, MultiGraph, MultiDiGraph, etc</span>
-<span class="gp">>>> </span><span class="n">e</span> <span class="o">=</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="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">add_edge</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="c1"># explicit two-node form</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="o">*</span><span class="n">e</span><span class="p">)</span> <span class="c1"># single edge as tuple of two nodes</span>
-</pre></div>
-</div>
-<p>Many NetworkX algorithms designed for weighted graphs use an edge attribute (by default ‘weight’) to hold a
-numerical value. Associate date to edge using keywords:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="mi">3</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="mi">1</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="mi">7</span><span class="p">,</span> <span class="n">capacity</span><span class="o">=</span><span class="mi">15</span><span class="p">,</span> <span class="n">length</span><span class="o">=</span><span class="mf">342.7</span><span class="p">)</span>
-</pre></div>
-</div>
-<p>For non-string attribute keys, use subscript notation.</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="n">G</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="o">.</span><span class="n">update</span><span class="p">({</span><span class="mi">0</span><span class="p">:</span> <span class="mi">5</span><span class="p">})</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">edges</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="o">.</span><span class="n">update</span><span class="p">({</span><span class="mi">0</span><span class="p">:</span> <span class="mi">5</span><span class="p">})</span>
-</pre></div>
-</div>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.add_edges_from">
-<code class="descname">add_edges_from</code><span class="sig-paren">(</span><em>ebunch_to_add</em>, <em>**attr</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.add_edges_from" title="Permalink to this definition">¶</a></dt>
-<dd><p>Add all the edges in ebunch_to_add.</p>
-<dl class="docutils">
-<dt>ebunch_to_add <span class="classifier-delimiter">:</span> <span class="classifier">container of edges</span></dt>
-<dd>Each edge given in the container will be added to the
-graph. The edges must be given as 2-tuples (u, v) or
-3-tuples (u, v, d) where d is a dictionary containing edge data.</dd>
-<dt>attr <span class="classifier-delimiter">:</span> <span class="classifier">keyword arguments, optional</span></dt>
-<dd>Edge data (or labels or objects) can be assigned using
-keyword arguments.</dd>
-</dl>
-<p>add_edge : add a single edge
-add_weighted_edges_from : convenient way to add weighted edges</p>
-<p>Adding the same edge twice has no effect but any edge data
-will be updated when each duplicate edge is added.</p>
-<p>Edge attributes specified in an ebunch take precedence over
-attributes specified via keyword arguments.</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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="c1"># or DiGraph, MultiGraph, MultiDiGraph, etc</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">add_edges_from</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="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">)])</span> <span class="c1"># using a list of edge tuples</span>
-<span class="gp">>>> </span><span class="n">e</span> <span class="o">=</span> <span class="nb">zip</span><span class="p">(</span><span class="nb">range</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">3</span><span class="p">),</span> <span class="nb">range</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">4</span><span class="p">))</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">add_edges_from</span><span class="p">(</span><span class="n">e</span><span class="p">)</span> <span class="c1"># Add the path graph 0-1-2-3</span>
-</pre></div>
-</div>
-<p>Associate data to edges</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">add_edges_from</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="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">)],</span> <span class="n">weight</span><span class="o">=</span><span class="mi">3</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">add_edges_from</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="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">4</span><span class="p">)],</span> <span class="n">label</span><span class="o">=</span><span class="s1">'WN2898'</span><span class="p">)</span>
-</pre></div>
-</div>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.add_equation">
-<code class="descname">add_equation</code><span class="sig-paren">(</span><em>edge_or_node</em>, <em>equation</em>, <em>language='Python'</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.add_equation" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to add an equation to an output edge.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
-<li><strong>edge_or_node</strong> (<em>list</em><em>, </em><em>str</em>) – graph edge or node under consideration.</li>
-<li><strong>equation</strong> (<em>str</em>) – equation to be added</li>
-<li><strong>language</strong> (<em>str</em>) – equation language used for the equation</li>
-</ul>
+<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">graph with enriched constraint nodes</p>
</td>
</tr>
</tbody>
</table>
+<p>Operators: ‘==’, ‘>’, ‘<’, ‘>=’ and ‘<=’</p>
</dd></dl>
<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.add_equation_label">
-<code class="descname">add_equation_label</code><span class="sig-paren">(</span><em>edge</em>, <em>labeling_method='node_label'</em>, <em>language='Python'</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.add_equation_label" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to add an equation label to a edge that can (safely) be used as reference in an equation.</p>
+<dt id="kadmos.graph.graph_data.DataGraph.mark_as_design_variable">
+<code class="descname">mark_as_design_variable</code><span class="sig-paren">(</span><em>node</em>, <em>lower_bound=None</em>, <em>upper_bound=None</em>, <em>samples=None</em>, <em>nominal_value=0.0</em>, <em>ignore_outdegree=False</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.mark_as_design_variable" title="Permalink to this definition">¶</a></dt>
+<dd><p>Method to mark a single node as a design variable and add the required metadata for its definition.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
-<li><strong>edge</strong> (<em>str</em>) – graph edge under consideration</li>
-<li><strong>labeling_method</strong> (<em>str</em>) – select method for automatic label string determination (node_id or node_label)</li>
-<li><strong>language</strong> (<em>str</em>) – equation language used for the equation label</li>
+<li><strong>node</strong> (<em>str</em>) – node</li>
+<li><strong>lower_bound</strong> (<em>float</em>) – lower bound of design variable</li>
+<li><strong>upper_bound</strong> (<em>float</em>) – upper bound of design variable</li>
+<li><strong>samples</strong> (<em>list</em>) – samples of design variable</li>
+<li><strong>nominal_value</strong> (<em>float</em>) – nominal value of design variable</li>
+<li><strong>ignore_outdegree</strong> (<em>bool</em>) – option to ignore the outdegree required</li>
</ul>
</td>
</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">label</p>
-</td>
-</tr>
-<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last">str</p>
+<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">graph with enriched design variable node</p>
</td>
</tr>
</tbody>
@@ -3587,3144 +2228,146 @@ attributes specified via keyword arguments.</p>
</dd></dl>
<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.add_equation_labels">
-<code class="descname">add_equation_labels</code><span class="sig-paren">(</span><em>nodes</em>, <em>language='Python'</em>, <em>labeling_method='node_id'</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.add_equation_labels" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to add equation labels automatically to all input edges connected to the specified list of nodes</p>
+<dt id="kadmos.graph.graph_data.DataGraph.mark_as_design_variables">
+<code class="descname">mark_as_design_variables</code><span class="sig-paren">(</span><em>nodes</em>, <em>lower_bounds=None</em>, <em>upper_bounds=None</em>, <em>samples=None</em>, <em>nominal_values=None</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.mark_as_design_variables" title="Permalink to this definition">¶</a></dt>
+<dd><p>Method to mark a list of nodes as design variable and add metadata.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
-<li><strong>nodes</strong> (<em>list</em>) – list of nodes</li>
-<li><strong>language</strong> (<em>str</em>) – equation language used for the equation label</li>
-<li><strong>labeling_method</strong> (<em>str</em>) – select method for automatic label string determination (node_id or node_label)</li>
+<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
+<li><strong>nodes</strong> (<em>list</em><em> or </em><em>str</em>) – list of nodes present in the graph</li>
+<li><strong>lower_bounds</strong> (<em>list</em><em>, </em><em>numbers.Number</em>) – list of lower bound values</li>
+<li><strong>upper_bounds</strong> (<em>list</em><em>, </em><em>numbers.Number</em>) – list of upper bounds</li>
+<li><strong>samples</strong> (<em>list</em>) – nested list of kadmos values</li>
+<li><strong>nominal_values</strong> (<em>list</em><em>, </em><em>numbers.Number</em>) – list of nominal values</li>
</ul>
</td>
</tr>
+<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">graph with enriched design variable nodes</p>
+</td>
+</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.add_instance">
-<code class="descname">add_instance</code><span class="sig-paren">(</span><em>node</em>, <em>instance=None</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.add_instance" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to change the instance of a node</p>
+<dt id="kadmos.graph.graph_data.DataGraph.mark_as_objective">
+<code class="descname">mark_as_objective</code><span class="sig-paren">(</span><em>node</em>, <em>remove_unused_outputs=False</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.mark_as_objective" title="Permalink to this definition">¶</a></dt>
+<dd><p>Method to mark a single node as objective.</p>
<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
-<li><strong>node</strong> (<em>str</em>) – node to change the instance of</li>
-<li><strong>instance</strong> (<em>int</em>) – new instance, optional (default=None)</li>
-</ul>
-</td>
-</tr>
-</tbody>
-</table>
-<p>In case the default is used the instance added is the highest current instance + 1.</p>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.add_mathematical_function">
-<code class="descname">add_mathematical_function</code><span class="sig-paren">(</span><em>input_nodes</em>, <em>function_node</em>, <em>output_nodes</em>, <em>function_type='regular'</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.add_mathematical_function" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to add mathematical function to graph</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
-<li><strong>input_nodes</strong> (<em>str</em><em>, </em><em>list</em>) – input nodes of the mathematical function</li>
-<li><strong>function_node</strong> (<em>str</em>) – function node of the mathematical function</li>
-<li><strong>output_nodes</strong> (<em>str</em><em>, </em><em>list</em>) – output nodes of the mathematical function</li>
-<li><strong>function_type</strong> (<em>'regular'</em><em> or </em><em>'consistency'</em>) – type of function, optional (default=’regular’)</li>
-</ul>
-</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.add_node">
-<code class="descname">add_node</code><span class="sig-paren">(</span><em>n</em>, <em>attr_dict=None</em>, <em>**attr</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.add_node" title="Permalink to this definition">¶</a></dt>
-<dd><p>Add a single node and update node attributes.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
-<li><strong>n</strong> (<em>A node can be any hashable Python object except None.</em>) – node</li>
-<li><strong>attr_dict</strong> (<em>dict</em>) – dictionary of attribute keyword arguments.</li>
-<li><strong>attr</strong> (<em>Set</em><em> or </em><em>change node attributes using attr_dict.</em>) – keyword arguments, optional</li>
-</ul>
-</td>
-</tr>
-</tbody>
-</table>
-<p>Examples:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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="c1"># or DiGraph, MultiGraph, MultiDiGraph, etc</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="mi">1</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="s1">'Hello'</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="n">K3</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="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">),</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="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="mi">0</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="n">K3</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">number_of_nodes</span><span class="p">()</span>
-</pre></div>
-</div>
-<p>Use keywords set/change node attributes:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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="mi">1</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="mi">10</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="mi">3</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="mf">0.4</span><span class="p">,</span> <span class="n">UTM</span><span class="o">=</span><span class="p">(</span><span class="s1">'13S'</span><span class="p">,</span> <span class="mi">382871</span><span class="p">,</span> <span class="mi">3972649</span><span class="p">))</span>
-</pre></div>
-</div>
-<p>Notes:</p>
-<p>A hashable object is one that can be used as a key in a Python
-dictionary. This includes strings, numbers, tuples of strings
-and numbers, etc.</p>
-<p>On many platforms hashable items also include mutables such as
-NetworkX Graphs, though one should be careful that the hash
-doesn’t change on mutables.</p>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.add_nodes_from">
-<code class="descname">add_nodes_from</code><span class="sig-paren">(</span><em>nodes_for_adding</em>, <em>**attr</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.add_nodes_from" title="Permalink to this definition">¶</a></dt>
-<dd><p>Add multiple nodes.</p>
-<dl class="docutils">
-<dt>nodes_for_adding <span class="classifier-delimiter">:</span> <span class="classifier">iterable container</span></dt>
-<dd>A container of nodes (list, dict, set, etc.).
-OR
-A container of (node, attribute dict) tuples.
-Node attributes are updated using the attribute dict.</dd>
-<dt>attr <span class="classifier-delimiter">:</span> <span class="classifier">keyword arguments, optional (default= no attributes)</span></dt>
-<dd>Update attributes for all nodes in nodes.
-Node attributes specified in nodes as a tuple take
-precedence over attributes specified via keyword arguments.</dd>
-</dl>
-<p>add_node</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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="c1"># or DiGraph, MultiGraph, MultiDiGraph, etc</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">add_nodes_from</span><span class="p">(</span><span class="s1">'Hello'</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="n">K3</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="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">),</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="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="mi">0</span><span class="p">)])</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">add_nodes_from</span><span class="p">(</span><span class="n">K3</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="nb">sorted</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">(),</span> <span class="n">key</span><span class="o">=</span><span class="nb">str</span><span class="p">)</span>
-<span class="go">[0, 1, 2, 'H', 'e', 'l', 'o']</span>
-</pre></div>
-</div>
-<p>Use keywords to update specific node attributes for every node.</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">add_nodes_from</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="n">size</span><span class="o">=</span><span class="mi">10</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">add_nodes_from</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="n">weight</span><span class="o">=</span><span class="mf">0.4</span><span class="p">)</span>
-</pre></div>
-</div>
-<p>Use (node, attrdict) tuples to update attributes for specific nodes.</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">add_nodes_from</span><span class="p">([(</span><span class="mi">1</span><span class="p">,</span> <span class="nb">dict</span><span class="p">(</span><span class="n">size</span><span class="o">=</span><span class="mi">11</span><span class="p">)),</span> <span class="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="p">{</span><span class="s1">'color'</span><span class="p">:</span><span class="s1">'blue'</span><span class="p">})])</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">[</span><span class="mi">1</span><span class="p">][</span><span class="s1">'size'</span><span class="p">]</span>
-<span class="go">11</span>
-<span class="gp">>>> </span><span class="n">H</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">H</span><span class="o">.</span><span class="n">add_nodes_from</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="kc">True</span><span class="p">))</span>
-<span class="gp">>>> </span><span class="n">H</span><span class="o">.</span><span class="n">nodes</span><span class="p">[</span><span class="mi">1</span><span class="p">][</span><span class="s1">'size'</span><span class="p">]</span>
-<span class="go">11</span>
-</pre></div>
-</div>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.add_objective_function_by_nodes">
-<code class="descname">add_objective_function_by_nodes</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.add_objective_function_by_nodes" title="Permalink to this definition">¶</a></dt>
-<dd><p>This function adds objective functions to the graph using lists of variable nodes.</p>
-<p>Each list produces a separate objective function node in the graph. If the list if passed as a keyword argument,
-the keyword is taken as the name of the objective function node. Otherwise, a standard name will be given to the
-node. Each objective function node has one output variable, and takes the nodes given in the argument list as
-input nodes.</p>
-<p>If the provided nodes do not exist in the graph, a warning is given to the user on whether to continue the
-addition of the objective function to the graph using valid nodes.</p>
-<p>Example:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">unnamed_function</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="o">>></span><span class="nb">list</span> <span class="n">of</span> <span class="n">graph</span> <span class="n">nodes</span><span class="o"><<</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="n">named_obj_fcn</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="o">>></span><span class="nb">list</span> <span class="n">of</span> <span class="n">graph</span> <span class="n">nodes</span><span class="o"><<</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="n">MyGraph</span><span class="o">.</span><span class="n">add_objective_function_by_nodes</span><span class="p">(</span><span class="n">unnamed_function</span><span class="p">,</span> <span class="n">My_obj_fcn_name</span> <span class="o">=</span> <span class="n">named_obj_fcn</span><span class="p">)</span>
-</pre></div>
-</div>
-<p>The added objective function nodes can be queried by the attribute:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">Graph</span><span class="o">.</span><span class="n">node</span><span class="p">[</span><span class="n">node</span><span class="p">][</span><span class="s2">"name"</span><span class="p">]</span> <span class="o">==</span> <span class="s2">"Objective"</span>
-</pre></div>
-</div>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
-<li><strong>args</strong> (<em>list</em>) – list of nodes (list elements must be strings)</li>
-<li><strong>kwargs</strong> (<em>list</em>) – list of nodes (list elements must be strings)</li>
-</ul>
-</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">list of Objective Functions added to Graph</p>
-</td>
-</tr>
-<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last">list</p>
-</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.add_weighted_edges_from">
-<code class="descname">add_weighted_edges_from</code><span class="sig-paren">(</span><em>ebunch_to_add</em>, <em>weight='weight'</em>, <em>**attr</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.add_weighted_edges_from" title="Permalink to this definition">¶</a></dt>
-<dd><p>Add weighted edges in <cite>ebunch_to_add</cite> with specified weight attr</p>
-<dl class="docutils">
-<dt>ebunch_to_add <span class="classifier-delimiter">:</span> <span class="classifier">container of edges</span></dt>
-<dd>Each edge given in the list or container will be added
-to the graph. The edges must be given as 3-tuples (u, v, w)
-where w is a number.</dd>
-<dt>weight <span class="classifier-delimiter">:</span> <span class="classifier">string, optional (default= ‘weight’)</span></dt>
-<dd>The attribute name for the edge weights to be added.</dd>
-<dt>attr <span class="classifier-delimiter">:</span> <span class="classifier">keyword arguments, optional (default= no attributes)</span></dt>
-<dd>Edge attributes to add/update for all edges.</dd>
-</dl>
-<p>add_edge : add a single edge
-add_edges_from : add multiple edges</p>
-<p>Adding the same edge twice for Graph/DiGraph simply updates
-the edge data. For MultiGraph/MultiDiGraph, duplicate edges
-are stored.</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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="c1"># or DiGraph, MultiGraph, MultiDiGraph, etc</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">add_weighted_edges_from</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="mf">3.0</span><span class="p">),</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="mf">7.5</span><span class="p">)])</span>
-</pre></div>
-</div>
-</dd></dl>
-
-<dl class="attribute">
-<dt id="kadmos.graph.graph_data.DataGraph.adj">
-<code class="descname">adj</code><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.adj" title="Permalink to this definition">¶</a></dt>
-<dd><p>Graph adjacency object holding the neighbors of each node.</p>
-<p>This object is a read-only dict-like structure with node keys
-and neighbor-dict values. The neighbor-dict is keyed by neighbor
-to the edge-data-dict. So <cite>G.adj[3][2][‘color’] = ‘blue’</cite> sets
-the color of the edge <cite>(3, 2)</cite> to <cite>“blueâ€</cite>.</p>
-<p>Iterating over G.adj behaves like a dict. Useful idioms include
-<cite>for nbr, datadict in G.adj[n].items():</cite>.</p>
-<p>The neighbor information is also provided by subscripting the graph.
-So <cite>for nbr, foovalue in G[node].data(‘foo’, default=1):</cite> works.</p>
-<p>For directed graphs, <cite>G.adj</cite> holds outgoing (successor) info.</p>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.adjacency">
-<code class="descname">adjacency</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.adjacency" title="Permalink to this definition">¶</a></dt>
-<dd><p>Return an iterator over (node, adjacency dict) tuples for all nodes.</p>
-<p>For directed graphs, only outgoing neighbors/adjacencies are included.</p>
-<dl class="docutils">
-<dt>adj_iter <span class="classifier-delimiter">:</span> <span class="classifier">iterator</span></dt>
-<dd>An iterator over (node, adjacency dictionary) for all nodes in
-the graph.</dd>
-</dl>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">path_graph</span><span class="p">(</span><span class="mi">4</span><span class="p">)</span> <span class="c1"># or DiGraph, MultiGraph, MultiDiGraph, etc</span>
-<span class="gp">>>> </span><span class="p">[(</span><span class="n">n</span><span class="p">,</span> <span class="n">nbrdict</span><span class="p">)</span> <span class="k">for</span> <span class="n">n</span><span class="p">,</span> <span class="n">nbrdict</span> <span class="ow">in</span> <span class="n">G</span><span class="o">.</span><span class="n">adjacency</span><span class="p">()]</span>
-<span class="go">[(0, {1: {}}), (1, {0: {}, 2: {}}), (2, {1: {}, 3: {}}), (3, {2: {}})]</span>
-</pre></div>
-</div>
-</dd></dl>
-
-<dl class="attribute">
-<dt id="kadmos.graph.graph_data.DataGraph.adjlist_inner_dict_factory">
-<code class="descname">adjlist_inner_dict_factory</code><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.adjlist_inner_dict_factory" title="Permalink to this definition">¶</a></dt>
-<dd><p>alias of <code class="xref py py-class docutils literal notranslate"><span class="pre">__builtin__.dict</span></code></p>
-</dd></dl>
-
-<dl class="attribute">
-<dt id="kadmos.graph.graph_data.DataGraph.adjlist_outer_dict_factory">
-<code class="descname">adjlist_outer_dict_factory</code><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.adjlist_outer_dict_factory" title="Permalink to this definition">¶</a></dt>
-<dd><p>alias of <code class="xref py py-class docutils literal notranslate"><span class="pre">__builtin__.dict</span></code></p>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.change_graph_class">
-<code class="descname">change_graph_class</code><span class="sig-paren">(</span><em>graph_class</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.change_graph_class" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to adjust the class of a graph.</p>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.check">
-<code class="descname">check</code><span class="sig-paren">(</span><em>raise_error=False</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.check" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to check the graph for validity and completeness.</p>
-<p>Several checks are performed. However the method does not guarantee the validity of the graph.</p>
-<p>The checks are split into several categories and the methods _check_category_a, _check_category_b and
-_check_category_c are used to determine the overall validity and completeness. These sub methods are generally
-defined below and are then further refined in child classes.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>raise_error</strong> (<em>bool</em>) – determines if an error should be raised in case of an invalid graph</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">result of the check</td>
-</tr>
-<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body">bool</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.check_cmdows_integrity">
-<code class="descname">check_cmdows_integrity</code><span class="sig-paren">(</span><em>convention=True</em>, <em>mpg=None</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.check_cmdows_integrity" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to check the integrity of the CMDOWS file that can be created with the save method.</p>
-<p>The integrity check is graph specific and thus needs to be executed for every graph before saving as CMDOWS if
-one wants to be sure that the CMDOWS file is integer. Due to its relative long runtime this check is however not
-performed automatically when using the save method.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
-<li><strong>convention</strong> (<em>bool</em>) – option for applying a UID convention</li>
-<li><strong>mpg</strong> (<a class="reference internal" href="#kadmos.graph.graph_process.MdaoProcessGraph" title="kadmos.graph.graph_process.MdaoProcessGraph"><em>MdaoProcessGraph</em></a>) – MPG to be saved together with graph</li>
-</ul>
-</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">check result</p>
-</td>
-</tr>
-<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last">bool</p>
-</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.check_for_coupling">
-<code class="descname">check_for_coupling</code><span class="sig-paren">(</span><em>function_order</em>, <em>only_feedback=False</em>, <em>raise_error_if_true=False</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.check_for_coupling" title="Permalink to this definition">¶</a></dt>
-<dd><p>Function to check for the presence of coupling in a graph for a list of analyses in a given analysis order.</p>
-<p>Note that only the functions in the function_order list are checked for feedback.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
-<li><strong>function_order</strong> (<em>list</em>) – list with node names of functions</li>
-<li><strong>only_feedback</strong> (<em>bool</em>) – Boolean on whether to check for feedback coupling only (this is useful for Gauss-Seidel)</li>
-<li><strong>raise_error_if_true</strong> (<em>bool</em>) – Boolean on whether to raise an error if coupling exists</li>
-</ul>
-</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">Boolean value on whether coupling exists</p>
-</td>
-</tr>
-<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last">bool</p>
-</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.clear">
-<code class="descname">clear</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.clear" title="Permalink to this definition">¶</a></dt>
-<dd><p>Remove all nodes and edges from the graph.</p>
-<p>This also removes the name, and all graph, node, and edge attributes.</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">path_graph</span><span class="p">(</span><span class="mi">4</span><span class="p">)</span> <span class="c1"># or DiGraph, MultiGraph, MultiDiGraph, etc</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">clear</span><span class="p">()</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">)</span>
-<span class="go">[]</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">edges</span><span class="p">)</span>
-<span class="go">[]</span>
-</pre></div>
-</div>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.copy">
-<code class="descname">copy</code><span class="sig-paren">(</span><em>as_view=False</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.copy" title="Permalink to this definition">¶</a></dt>
-<dd><p>Return a copy of the graph.</p>
-<p>The copy method by default returns a shallow copy of the graph
-and attributes. That is, if an attribute is a container, that
-container is shared by the original an the copy.
-Use Python’s <cite>copy.deepcopy</cite> for new containers.</p>
-<p>If <cite>as_view</cite> is True then a view is returned instead of a copy.</p>
-<p>All copies reproduce the graph structure, but data attributes
-may be handled in different ways. There are four types of copies
-of a graph that people might want.</p>
-<p>Deepcopy – The default behavior is a “deepcopy†where the graph
-structure as well as all data attributes and any objects they might
-contain are copied. The entire graph object is new so that changes
-in the copy do not affect the original object. (see Python’s
-copy.deepcopy)</p>
-<p>Data Reference (Shallow) – For a shallow copy the graph structure
-is copied but the edge, node and graph attribute dicts are
-references to those in the original graph. This saves
-time and memory but could cause confusion if you change an attribute
-in one graph and it changes the attribute in the other.
-NetworkX does not provide this level of shallow copy.</p>
-<p>Independent Shallow – This copy creates new independent attribute
-dicts and then does a shallow copy of the attributes. That is, any
-attributes that are containers are shared between the new graph
-and the original. This is exactly what <cite>dict.copy()</cite> provides.
-You can obtain this style copy using:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">path_graph</span><span class="p">(</span><span class="mi">5</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="n">H</span> <span class="o">=</span> <span class="n">G</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>
-<span class="gp">>>> </span><span class="n">H</span> <span class="o">=</span> <span class="n">G</span><span class="o">.</span><span class="n">copy</span><span class="p">(</span><span class="n">as_view</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="n">H</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="n">G</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="n">H</span> <span class="o">=</span> <span class="n">G</span><span class="o">.</span><span class="n">fresh_copy</span><span class="p">()</span><span class="o">.</span><span class="vm">__class__</span><span class="p">(</span><span class="n">G</span><span class="p">)</span>
-</pre></div>
-</div>
-<p>Fresh Data – For fresh data, the graph structure is copied while
-new empty data attribute dicts are created. The resulting graph
-is independent of the original and it has no edge, node or graph
-attributes. Fresh copies are not enabled. Instead use:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">H</span> <span class="o">=</span> <span class="n">G</span><span class="o">.</span><span class="n">fresh_copy</span><span class="p">()</span>
-<span class="gp">>>> </span><span class="n">H</span><span class="o">.</span><span class="n">add_nodes_from</span><span class="p">(</span><span class="n">G</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="n">H</span><span class="o">.</span><span class="n">add_edges_from</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">edges</span><span class="p">)</span>
-</pre></div>
-</div>
-<p>View – Inspired by dict-views, graph-views act like read-only
-versions of the original graph, providing a copy of the original
-structure without requiring any memory for copying the information.</p>
-<p>See the Python copy module for more information on shallow
-and deep copies, <a class="reference external" href="https://docs.python.org/2/library/copy.html">https://docs.python.org/2/library/copy.html</a>.</p>
-<dl class="docutils">
-<dt>as_view <span class="classifier-delimiter">:</span> <span class="classifier">bool, optional (default=False)</span></dt>
-<dd>If True, the returned graph-view provides a read-only view
-of the original graph without actually copying any data.</dd>
-</dl>
-<dl class="docutils">
-<dt>G <span class="classifier-delimiter">:</span> <span class="classifier">Graph</span></dt>
-<dd>A copy of the graph.</dd>
-</dl>
-<p>to_directed: return a directed copy of the graph.</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">path_graph</span><span class="p">(</span><span class="mi">4</span><span class="p">)</span> <span class="c1"># or DiGraph, MultiGraph, MultiDiGraph, etc</span>
-<span class="gp">>>> </span><span class="n">H</span> <span class="o">=</span> <span class="n">G</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>
-</pre></div>
-</div>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.copy_as">
-<code class="descname">copy_as</code><span class="sig-paren">(</span><em>graph_class</em>, <em>as_view=False</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.copy_as" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to make a copy of a graph and make it into another KADMOS graph class.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">copy of the graph</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Return type:</th><td class="field-body"><a class="reference internal" href="#kadmos.graph.graph_kadmos.KadmosGraph" title="kadmos.graph.graph_kadmos.KadmosGraph">KadmosGraph</a></td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.copy_edge">
-<code class="descname">copy_edge</code><span class="sig-paren">(</span><em>old_edge</em>, <em>new_edge</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.copy_edge" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to copy an edge so that attributes of the old edge are maintained.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
-<li><strong>old_edge</strong> (<em>tuple</em>) – edge to be copied</li>
-<li><strong>new_edge</strong> (<em>tuple</em>) – edge to be created</li>
-</ul>
-</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">created edge</p>
-</td>
-</tr>
-<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last">tuple</p>
-</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.copy_node_with_suffix">
-<code class="descname">copy_node_with_suffix</code><span class="sig-paren">(</span><em>node</em>, <em>suffix</em>, <em>label_extension</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.copy_node_with_suffix" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to simply copy a node and its attributes by creating a new node with a suffix.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
-<li><strong>node</strong> (<em>str</em>) – node to be copied</li>
-<li><strong>suffix</strong> (<em>str</em>) – suffix to be added to the node ID</li>
-<li><strong>label_extension</strong> (<em>str</em>) – extension for labels</li>
-<li><strong>kwargs</strong> (<em>dict</em>) – keyword arguments will be added as node attributes</li>
-</ul>
-</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">new node name and enriched graph</p>
-</td>
-</tr>
-<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last">str</p>
-</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.count_function_nodes">
-<code class="descname">count_function_nodes</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.count_function_nodes" title="Permalink to this definition">¶</a></dt>
-<dd><p>This function counts the amount function nodes that are present in the graph.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">amount of function nodes counted in graph</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Return type:</th><td class="field-body">int</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.create_dsm">
-<code class="descname">create_dsm</code><span class="sig-paren">(</span><em>file_name</em>, <em>destination_folder=None</em>, <em>open_pdf=False</em>, <em>mpg=None</em>, <em>include_system_vars=True</em>, <em>summarize_vars=False</em>, <em>function_order=None</em>, <em>keep_tex_file=False</em>, <em>abbreviate_keywords=False</em>, <em>compile_pdf=True</em>, <em>colors_based_on='problem_roles'</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.create_dsm" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to create a (X)DSM PDF file</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
-<li><strong>file_name</strong> (<em>str</em>) – name of the file to be saved</li>
-<li><strong>destination_folder</strong> (<em>str</em>) – destination folder for the file to be saved</li>
-<li><strong>open_pdf</strong> (<em>bool</em>) – option for opening the created file directly</li>
-<li><strong>mpg</strong> (<a class="reference internal" href="#kadmos.graph.graph_process.MdaoProcessGraph" title="kadmos.graph.graph_process.MdaoProcessGraph"><em>MdaoProcessGraph</em></a>) – optional MPG graph to be saved with MDG as XDSM (if None a DSM is created)</li>
-<li><strong>include_system_vars</strong> (<em>bool</em>) – option for including system variables (only applicable for DSMs)</li>
-<li><strong>summarize_vars</strong> (<em>bool</em>) – option for summarizing label</li>
-<li><strong>function_order</strong> (<em>list</em>) – optional function order for the diagonal of the graph (only applicable for DSMs)</li>
-<li><strong>keep_tex_file</strong> (<em>bool</em>) – optional argument to keep the tex file of the PDF</li>
-<li><strong>abbreviate_keywords</strong> (<em>bool</em>) – optional argument to keep make keywords shorter (input -> inp., output -> outp.)</li>
-<li><strong>compile_pdf</strong> (<em>bool</em>) – optional argument to compile the PDF</li>
-<li><strong>colors_based_on</strong> (<em>str</em>) – option to base the colors either on the problem role or the partitions</li>
-</ul>
-</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.deepcopy">
-<code class="descname">deepcopy</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.deepcopy" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to make a deep copy of a graph.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">deepcopy of the graph</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Return type:</th><td class="field-body"><a class="reference internal" href="#kadmos.graph.graph_kadmos.KadmosGraph" title="kadmos.graph.graph_kadmos.KadmosGraph">KadmosGraph</a></td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.deepcopy_as">
-<code class="descname">deepcopy_as</code><span class="sig-paren">(</span><em>graph_class</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.deepcopy_as" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to make a deep copy of a graph and make it into another KADMOS graph class.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">deepcopy of the graph</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Return type:</th><td class="field-body"><a class="reference internal" href="#kadmos.graph.graph_kadmos.KadmosGraph" title="kadmos.graph.graph_kadmos.KadmosGraph">KadmosGraph</a></td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="attribute">
-<dt id="kadmos.graph.graph_data.DataGraph.degree">
-<code class="descname">degree</code><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.degree" title="Permalink to this definition">¶</a></dt>
-<dd><p>A DegreeView for the Graph as G.degree or G.degree().</p>
-<p>The node degree is the number of edges adjacent to the node.
-The weighted node degree is the sum of the edge weights for
-edges incident to that node.</p>
-<p>This object provides an iterator for (node, degree) as well as
-lookup for the degree for a single node.</p>
-<dl class="docutils">
-<dt>nbunch <span class="classifier-delimiter">:</span> <span class="classifier">single node, container, or all nodes (default= all nodes)</span></dt>
-<dd>The view will only report edges incident to these nodes.</dd>
-<dt>weight <span class="classifier-delimiter">:</span> <span class="classifier">string or None, optional (default=None)</span></dt>
-<dd>The name of an edge attribute that holds the numerical value used
-as a weight. If None, then each edge has weight 1.
-The degree is the sum of the edge weights adjacent to the node.</dd>
-</dl>
-<p>If a single node is requested
-deg : int</p>
-<blockquote>
-<div>Degree of the node</div></blockquote>
-<p>OR if multiple nodes are requested
-nd_iter : iterator</p>
-<blockquote>
-<div>The iterator returns two-tuples of (node, degree).</div></blockquote>
-<p>in_degree, out_degree</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">DiGraph</span><span class="p">()</span> <span class="c1"># or MultiDiGraph</span>
-<span class="gp">>>> </span><span class="n">nx</span><span class="o">.</span><span class="n">add_path</span><span class="p">(</span><span class="n">G</span><span class="p">,</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">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">])</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">degree</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span> <span class="c1"># node 0 with degree 1</span>
-<span class="go">1</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">degree</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">2</span><span class="p">]))</span>
-<span class="go">[(0, 1), (1, 2), (2, 2)]</span>
-</pre></div>
-</div>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.disconnect_problematic_variables_from">
-<code class="descname">disconnect_problematic_variables_from</code><span class="sig-paren">(</span><em>function</em>, <em>disconnect_collided_targets=True</em>, <em>disconnect_shared_sources=True</em>, <em>ignore_list=[]</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.disconnect_problematic_variables_from" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to automatically disconnect certain problematic variables with respect to a given function.</p>
-<p>If given as setting (disconnect_collided_targets=True) then the collided targets will be disconnected from this
-function. Also, if given as setting (disconnect_shared_sources=True), shared sources are also disconnected.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
-<li><strong>function</strong> (<em>basestring</em>) – function around which problematic variables are disconnected</li>
-<li><strong>disconnect_collided_targets</strong> (<em>bool</em>) – setting to disconnect collided targets</li>
-<li><strong>disconnect_shared_sources</strong> (<em>list</em>) – setting to disconnect shared sources</li>
-<li><strong>disconnect_shared_sources</strong> – setting to ignore certain nodes</li>
-</ul>
-</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="attribute">
-<dt id="kadmos.graph.graph_data.DataGraph.edge_attr_dict_factory">
-<code class="descname">edge_attr_dict_factory</code><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.edge_attr_dict_factory" title="Permalink to this definition">¶</a></dt>
-<dd><p>alias of <code class="xref py py-class docutils literal notranslate"><span class="pre">__builtin__.dict</span></code></p>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.edge_subgraph">
-<code class="descname">edge_subgraph</code><span class="sig-paren">(</span><em>edges</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.edge_subgraph" title="Permalink to this definition">¶</a></dt>
-<dd><p>Returns the subgraph induced by the specified edges.</p>
-<p>The induced subgraph contains each edge in <cite>edges</cite> and each
-node incident to any one of those edges.</p>
-<dl class="docutils">
-<dt>edges <span class="classifier-delimiter">:</span> <span class="classifier">iterable</span></dt>
-<dd>An iterable of edges in this graph.</dd>
-</dl>
-<dl class="docutils">
-<dt>G <span class="classifier-delimiter">:</span> <span class="classifier">Graph</span></dt>
-<dd>An edge-induced subgraph of this graph with the same edge
-attributes.</dd>
-</dl>
-<p>The graph, edge, and node attributes in the returned subgraph
-view are references to the corresponding attributes in the original
-graph. The view is read-only.</p>
-<p>To create a full graph version of the subgraph with its own copy
-of the edge or node attributes, use:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">edge_subgraph</span><span class="p">(</span><span class="n">edges</span><span class="p">)</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>
-</pre></div>
-</div>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">path_graph</span><span class="p">(</span><span class="mi">5</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="n">H</span> <span class="o">=</span> <span class="n">G</span><span class="o">.</span><span class="n">edge_subgraph</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="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">)])</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">H</span><span class="o">.</span><span class="n">nodes</span><span class="p">)</span>
-<span class="go">[0, 1, 3, 4]</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">H</span><span class="o">.</span><span class="n">edges</span><span class="p">)</span>
-<span class="go">[(0, 1), (3, 4)]</span>
-</pre></div>
-</div>
-</dd></dl>
-
-<dl class="attribute">
-<dt id="kadmos.graph.graph_data.DataGraph.edges">
-<code class="descname">edges</code><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.edges" title="Permalink to this definition">¶</a></dt>
-<dd><p>An OutEdgeView of the DiGraph as G.edges or G.edges().</p>
-<p>edges(self, nbunch=None, data=False, default=None)</p>
-<p>The OutEdgeView provides set-like operations on the edge-tuples
-as well as edge attribute lookup. When called, it also provides
-an EdgeDataView object which allows control of access to edge
-attributes (but does not provide set-like operations).
-Hence, <cite>G.edges[u, v][‘color’]</cite> provides the value of the color
-attribute for edge <cite>(u, v)</cite> while
-<cite>for (u, v, c) in G.edges.data(‘color’, default=’red’):</cite>
-iterates through all the edges yielding the color attribute
-with default <cite>‘red’</cite> if no color attribute exists.</p>
-<dl class="docutils">
-<dt>nbunch <span class="classifier-delimiter">:</span> <span class="classifier">single node, container, or all nodes (default= all nodes)</span></dt>
-<dd>The view will only report edges incident to these nodes.</dd>
-<dt>data <span class="classifier-delimiter">:</span> <span class="classifier">string or bool, optional (default=False)</span></dt>
-<dd>The edge attribute returned in 3-tuple (u, v, ddict[data]).
-If True, return edge attribute dict in 3-tuple (u, v, ddict).
-If False, return 2-tuple (u, v).</dd>
-<dt>default <span class="classifier-delimiter">:</span> <span class="classifier">value, optional (default=None)</span></dt>
-<dd>Value used for edges that dont have the requested attribute.
-Only relevant if data is not True or False.</dd>
-</dl>
-<dl class="docutils">
-<dt>edges <span class="classifier-delimiter">:</span> <span class="classifier">OutEdgeView</span></dt>
-<dd>A view of edge attributes, usually it iterates over (u, v)
-or (u, v, d) tuples of edges, but can also be used for
-attribute lookup as <cite>edges[u, v][‘foo’]</cite>.</dd>
-</dl>
-<p>in_edges, out_edges</p>
-<p>Nodes in nbunch that are not in the graph will be (quietly) ignored.
-For directed graphs this returns the out-edges.</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">DiGraph</span><span class="p">()</span> <span class="c1"># or MultiDiGraph, etc</span>
-<span class="gp">>>> </span><span class="n">nx</span><span class="o">.</span><span class="n">add_path</span><span class="p">(</span><span class="n">G</span><span class="p">,</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">2</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="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="mi">5</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="p">[</span><span class="n">e</span> <span class="k">for</span> <span class="n">e</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="go">[(0, 1), (1, 2), (2, 3)]</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">edges</span><span class="o">.</span><span class="n">data</span><span class="p">()</span> <span class="c1"># default data is {} (empty dict)</span>
-<span class="go">OutEdgeDataView([(0, 1, {}), (1, 2, {}), (2, 3, {'weight': 5})])</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">edges</span><span class="o">.</span><span class="n">data</span><span class="p">(</span><span class="s1">'weight'</span><span class="p">,</span> <span class="n">default</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
-<span class="go">OutEdgeDataView([(0, 1, 1), (1, 2, 1), (2, 3, 5)])</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">edges</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="mi">2</span><span class="p">])</span> <span class="c1"># only edges incident to these nodes</span>
-<span class="go">OutEdgeDataView([(0, 1), (2, 3)])</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">edges</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span> <span class="c1"># only edges incident to a single node (use G.adj[0]?)</span>
-<span class="go">OutEdgeDataView([(0, 1)])</span>
-</pre></div>
-</div>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.find_all_nodes">
-<code class="descname">find_all_nodes</code><span class="sig-paren">(</span><em>category='all'</em>, <em>subcategory='all'</em>, <em>attr_cond=None</em>, <em>attr_include=None</em>, <em>attr_exclude=None</em>, <em>xpath_include=None</em>, <em>xpath_exclude=None</em>, <em>print_in_log=False</em>, <em>print_attributes='all'</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.find_all_nodes" title="Permalink to this definition">¶</a></dt>
-<dd><p>Advanced search function to get nodes and their properties.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
-<li><strong>category</strong> (<em>str</em>) – category of the node (you can specify multiple in a list), see note for allowed values.</li>
-<li><strong>subcategory</strong> (<em>str</em>) – subcategory of the node (you can specify multiple in a list), see note for allowed values.</li>
-<li><strong>attr_cond</strong> (<em>list</em>) – conditional on the node attribute value (e.g. [‘execution time’,’>’,200])</li>
-<li><strong>attr_include</strong> (<em>list</em>) – attributes to exclusively include in search</li>
-<li><strong>attr_exclude</strong> (<em>list</em>) – attributes to exclude from search</li>
-<li><strong>xpath_include</strong> (<em>list</em>) – xpaths to exclusively include in search</li>
-<li><strong>xpath_exclude</strong> (<em>list</em>) – xpaths to exclude from search</li>
-<li><strong>print_in_log</strong> (<em>bool</em>) – parameter to set printing in log on or off</li>
-<li><strong>print_attributes</strong> (<em>str</em><em> or </em><em>list</em>) – attributes that should be printed in the log</li>
-</ul>
-</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">list of all nodes that meet the search criteria</p>
-</td>
-</tr>
-<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last">list</p>
-</td>
-</tr>
-</tbody>
-</table>
-<div class="admonition note">
-<p class="first admonition-title">Note</p>
-<p>The following categories are allowed:</p>
-<ul class="last simple">
-<li>all</li>
-<li>variable</li>
-<li>variable group</li>
-<li>function</li>
-<li>architecture element</li>
-<li>RCE component</li>
-</ul>
-</div>
-<div class="admonition note">
-<p class="first admonition-title">Note</p>
-<p>The following subcategories are allowed:</p>
-<p>GROUPS:</p>
-<ul class="simple">
-<li>all</li>
-<li>all variables</li>
-<li>all inputs</li>
-<li>all outputs</li>
-<li>all couplings</li>
-<li>all circular variables</li>
-<li>all PSG blocks</li>
-<li>all iterative blocks</li>
-<li>all design variables</li>
-</ul>
-<p>VARIABLES:</p>
-<ul class="simple">
-<li>hole</li>
-<li>supplied input</li>
-<li>supplied shared input</li>
-<li>output</li>
-<li>collision</li>
-<li>coupling</li>
-<li>pure circular coupling</li>
-<li>shared coupling</li>
-<li>shared circular coupling</li>
-<li>collided coupling</li>
-<li>collided circular coupling</li>
-<li>collided shared coupling</li>
-<li>collided shared circular coupling</li>
-</ul>
-<p>VARIABLE GROUPS:</p>
-<ul class="simple">
-<li>hole group</li>
-<li>supplied input group</li>
-<li>supplied shared input group</li>
-<li>output group</li>
-<li>coupling group</li>
-<li>shared coupling group</li>
-</ul>
-<p>FUNCTIONS:</p>
-<ul class="simple">
-<li>hole</li>
-<li>inputless</li>
-<li>outputless</li>
-<li>complete</li>
-</ul>
-<p>ARCHITECTURE ELEMENTS:</p>
-<p>Action blocks:</p>
-<ul class="simple">
-<li>optimizer</li>
-<li>MDA</li>
-<li>optimizer function</li>
-<li>MDA analysis</li>
-<li>independent output function</li>
-</ul>
-<p>Parameters:</p>
-<ul class="simple">
-<li>initial guess design variable</li>
-<li>final design variable</li>
-<li>final output variable</li>
-<li>MDA coupling variable</li>
-<li>initial guess MDA coupling variable</li>
-<li>final MDA coupling variable</li>
-<li>consistency constraint variable</li>
-</ul>
-<p>RCE COMPONENTS:</p>
-<ul class="last simple">
-<li>Input Provider</li>
-<li>XML Merger</li>
-<li>XML PyMerger</li>
-<li>CPACS Tool</li>
-<li>Converger</li>
-<li>Optimizer</li>
-<li>Consistency constraint function</li>
-</ul>
-</div>
-<p>Example usage:
-Just get all nodes of a graph in a list:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">all_nodes</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">find_all_nodes</span><span class="p">()</span>
-</pre></div>
-</div>
-<p>Get all input nodes in a list and print them in the log as well:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">all_nodes</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">find_all_nodes</span><span class="p">(</span><span class="n">category</span><span class="o">=</span><span class="s1">'all'</span><span class="p">,</span> <span class="n">subcategory</span><span class="o">=</span><span class="s1">'all inputs'</span><span class="p">,</span> <span class="n">print_in_log</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
-</pre></div>
-</div>
-<p>Get all input nodes with a certain attribute value:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">all_nodes</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">find_all_nodes</span><span class="p">(</span><span class="n">category</span><span class="o">=</span><span class="s1">'all'</span><span class="p">,</span> <span class="n">subcategory</span><span class="o">=</span><span class="s1">'all inputs'</span><span class="p">,</span>
-<span class="gp">>>> </span> <span class="n">attr_cond</span><span class="o">=</span><span class="p">[</span><span class="s1">'execution time'</span><span class="p">,</span> <span class="s1">'>'</span><span class="p">,</span> <span class="mi">5</span><span class="p">],</span> <span class="n">print_in_log</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
-</pre></div>
-</div>
-<p>Get all nodes with any of the listed attribute values:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">all_nodes</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">find_all_nodes</span><span class="p">(</span><span class="n">category</span><span class="o">=</span><span class="s1">'all'</span><span class="p">,</span> <span class="n">subcategory</span><span class="o">=</span><span class="s1">'all'</span><span class="p">,</span>
-<span class="gp">>>> </span> <span class="n">attr_include</span><span class="o">=</span><span class="p">[[</span><span class="s1">'problem_role'</span><span class="p">,</span> <span class="p">[</span><span class="s1">'constraint'</span><span class="p">,</span> <span class="s1">'objective'</span><span class="p">]],</span> <span class="p">[</span><span class="s1">'instance'</span><span class="p">,</span> <span class="mi">1</span><span class="p">]])</span>
-</pre></div>
-</div>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.fresh_copy">
-<code class="descname">fresh_copy</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.fresh_copy" title="Permalink to this definition">¶</a></dt>
-<dd><p>Return a fresh copy graph with the same data structure.</p>
-<p>A fresh copy has no nodes, edges or graph attributes. It is
-the same data structure as the current graph. This method is
-typically used to create an empty version of the graph.</p>
-<p>If you subclass the base class you should overwrite this method
-to return your class of graph.</p>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.get_adjacency_matrix">
-<code class="descname">get_adjacency_matrix</code><span class="sig-paren">(</span><em>print_in_log=True</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.get_adjacency_matrix" title="Permalink to this definition">¶</a></dt>
-<dd><p>Function to determine the adjacency matrix of a graph.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>print_in_log</strong> (<em>bool</em>) – option for printing the results</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">different methods of storing the same adjacency matrix in one dictionary</td>
-</tr>
-<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body">dict</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.get_architecture_node_ids">
-<code class="descname">get_architecture_node_ids</code><span class="sig-paren">(</span><em>mdao_architecture</em>, <em>number_of_groups=None</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.get_architecture_node_ids" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to get the IDs of architecture nodes specific for a certain MDAO architecture.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
-<li><strong>mdao_architecture</strong> (<em>basestring</em>) – specified architecture (CO, BLISS-2000, etc)</li>
-<li><strong>number_of_groups</strong> (<em>int</em><em>, </em><em>None</em>) – number of subgroups in distributed architectures</li>
-</ul>
-</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">node IDs</p>
-</td>
-</tr>
-<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last">tuple</p>
-</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.get_architecture_node_labels">
-<code class="descname">get_architecture_node_labels</code><span class="sig-paren">(</span><em>mdao_architecture</em>, <em>number_of_groups=None</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.get_architecture_node_labels" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to get the labels of architecture nodes specific for a certain MDAO architecture.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
-<li><strong>mdao_architecture</strong> (<em>basestring</em>) – specified architecture (CO, BLISS-2000, etc)</li>
-<li><strong>number_of_groups</strong> (<em>int</em><em>, </em><em>None</em>) – number of subgroups in distributed architectures</li>
-</ul>
-</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">node labels</p>
-</td>
-</tr>
-<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last">tuple</p>
-</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.get_categorized_nodes">
-<code class="descname">get_categorized_nodes</code><span class="sig-paren">(</span><em>print_in_log=False</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.get_categorized_nodes" title="Permalink to this definition">¶</a></dt>
-<dd><p>Function that returns a dictionary with graph nodes grouped according to category and subcategory.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>print_in_log</strong> (<em>bool</em>) – option for printing the categories</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">dictionary with analysis results</td>
-</tr>
-<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body">dict</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.get_contracted_graph">
-<code class="descname">get_contracted_graph</code><span class="sig-paren">(</span><em>contraction_level</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.get_contracted_graph" title="Permalink to this definition">¶</a></dt>
-<dd><p>This function contracts the nodes of a graph to the provided contraction level.</p>
-<p>The contraction level refers to the xpath-level, which represents the position of the descendant with respect
-to its predecessors. The example below represents a level 3 node, with “cpacs†being at level zero.</p>
-<p>/cpacs/aircraft/wings/wing</p>
-<p>–cpacs</p>
-<p>—-aircraft</p>
-<p>——–wings</p>
-<p>————wing</p>
-<p>All nodes above the contraction level are removed from the graph and replaced by a “variable group†node, which
-groups the removed nodes in a node at contraction level. This allows for a “de-cluttering†of the graph, with
-the graph connections still being represented.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>contraction_level</strong> (<em>int</em>) – from 0 (highest level) to X (lowest level existing in XML schema)</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">contracted_graph: graph with contracted nodes</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.get_coupling_matrix">
-<code class="descname">get_coupling_matrix</code><span class="sig-paren">(</span><em>function_order_method='manual'</em>, <em>node_selection=None</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.get_coupling_matrix" title="Permalink to this definition">¶</a></dt>
-<dd><p>Function to determine the role of the different functions in the FPG.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
-<li><strong>function_order_method</strong> (<em>basestring</em>) – algorithm to be used for the order in which the functions are executed.</li>
-<li><strong>node_selection</strong> (<em>list</em>) – selection of nodes for which the coupling matrix will be calculated only</li>
-</ul>
-</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">graph with enriched function node attributes and function problem role dictionary</p>
-</td>
-</tr>
-<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last"><a class="reference internal" href="#kadmos.graph.graph_data.FundamentalProblemGraph" title="kadmos.graph.graph_data.FundamentalProblemGraph">FundamentalProblemGraph</a></p>
-</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.get_direct_coupling_nodes">
-<code class="descname">get_direct_coupling_nodes</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.get_direct_coupling_nodes" title="Permalink to this definition">¶</a></dt>
-<dd><p>This method returns the direct couplings between two nodes in a graph.</p>
-<p>This method is specifically written (and tested) with function nodes in mind. Direct coupling is defined as
-coupling with between two nodes through a third node.</p>
-<p>In this function, each combination between the provided arguments is tested for couplings (in pairs). First,
-the two nodes in each pair are checked for common neighbors. If they do, the edges of the common neighbors are
-iterated to determine whether the node-pair is connected to each other, or only the neighbor. The direction of
-the coupling is also checked.</p>
-<p>Example:</p>
-<p>The connection:</p>
-<p>F1 => N1 => F2</p>
-<p>leads to:</p>
-<p>[(F1, F2, N1)]</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
-<li><strong>args</strong> (<em>str</em><em>, </em><em>list</em>) – nodes to be checked for couplings; at least two must be provided</li>
-<li><strong>kwargs</strong> (<em>direction: str</em>) – print_couplings: option for printing all couplings with coupling direction and node (optional)</li>
-<li><strong>kwargs</strong> – direction: set only coupling in certain direction (optional)</li>
-</ul>
-</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">couplings: list of tuples containing the coupled nodes and the coupling node</p>
-</td>
-</tr>
-<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last">list</p>
-</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.get_edge_data">
-<code class="descname">get_edge_data</code><span class="sig-paren">(</span><em>u</em>, <em>v</em>, <em>default=None</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.get_edge_data" title="Permalink to this definition">¶</a></dt>
-<dd><p>Return the attribute dictionary associated with edge (u, v).</p>
-<p>This is identical to <cite>G[u][v]</cite> except the default is returned
-instead of an exception is the edge doesn’t exist.</p>
-<p>u, v : nodes
-default: any Python object (default=None)</p>
-<blockquote>
-<div>Value to return if the edge (u, v) is not found.</div></blockquote>
-<dl class="docutils">
-<dt>edge_dict <span class="classifier-delimiter">:</span> <span class="classifier">dictionary</span></dt>
-<dd>The edge attribute dictionary.</dd>
-</dl>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">path_graph</span><span class="p">(</span><span class="mi">4</span><span class="p">)</span> <span class="c1"># or DiGraph, MultiGraph, MultiDiGraph, etc</span>
-<span class="gp">>>> </span><span class="n">G</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="go">{}</span>
-</pre></div>
-</div>
-<p>Warning: Assigning to <cite>G[u][v]</cite> is not permitted.
-But it is safe to assign attributes <cite>G[u][v][‘foo’]</cite></p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">G</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="s1">'weight'</span><span class="p">]</span> <span class="o">=</span> <span class="mi">7</span>
-<span class="gp">>>> </span><span class="n">G</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="s1">'weight'</span><span class="p">]</span>
-<span class="go">7</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="p">[</span><span class="mi">1</span><span class="p">][</span><span class="mi">0</span><span class="p">][</span><span class="s1">'weight'</span><span class="p">]</span>
-<span class="go">7</span>
-</pre></div>
-</div>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">path_graph</span><span class="p">(</span><span class="mi">4</span><span class="p">)</span> <span class="c1"># or DiGraph, MultiGraph, MultiDiGraph, etc</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">get_edge_data</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="c1"># default edge data is {}</span>
-<span class="go">{}</span>
-<span class="gp">>>> </span><span class="n">e</span> <span class="o">=</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="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">get_edge_data</span><span class="p">(</span><span class="o">*</span><span class="n">e</span><span class="p">)</span> <span class="c1"># tuple form</span>
-<span class="go">{}</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">get_edge_data</span><span class="p">(</span><span class="s1">'a'</span><span class="p">,</span> <span class="s1">'b'</span><span class="p">,</span> <span class="n">default</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span> <span class="c1"># edge not in graph, return 0</span>
-<span class="go">0</span>
-</pre></div>
-</div>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.get_feedback_info">
-<code class="descname">get_feedback_info</code><span class="sig-paren">(</span><em>function_order</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.get_feedback_info" title="Permalink to this definition">¶</a></dt>
-<dd><p>Function to determine the number of feedback loops for a given function order</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>function_order</strong> (<em>list</em>) – function order of the nodes</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">number of feedback loops</td>
-</tr>
-<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body">int</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.get_first_node_instance">
-<code class="descname">get_first_node_instance</code><span class="sig-paren">(</span><em>node</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.get_first_node_instance" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to obtain the first instance of a node</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>node</strong> (<em>str</em>) – node to find first instance of</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">node of first instance</td>
-</tr>
-<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body">str</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.get_function_graph">
-<code class="descname">get_function_graph</code><span class="sig-paren">(</span><em>keep_objective_variables=False</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.get_function_graph" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method for replacing variable nodes by function connections.</p>
-<p>This function removes all variable nodes from the graph and replaces the variable connections of each function
-with function connections, such that:</p>
-<p>F(1) => N(1) => F(2) => N(2) => F(3)</p>
-<p>becomes:</p>
-<p>F(1) => F(2) => F(3)</p>
-<p>Note: N(i) is a variable node, and F(i) a function node.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Param:</th><td class="field-body">keep_objective_variables: if given the objective variables will remain in graph</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Type:</th><td class="field-body">keep_objective_variables: bool</td>
-</tr>
-<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">new graph without variable nodes</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.get_function_metadata">
-<code class="descname">get_function_metadata</code><span class="sig-paren">(</span><em>node</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.get_function_metadata" title="Permalink to this definition">¶</a></dt>
-<dd><p>Function to get the node metadata in a list (used in the dynamic visualization package).</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>node</strong> (<em>basestring</em>) – function node to collect the metadata for.</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">list with metadata</td>
-</tr>
-<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body">list</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.get_function_nodes">
-<code class="descname">get_function_nodes</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.get_function_nodes" title="Permalink to this definition">¶</a></dt>
-<dd><p>This function returns a list of all function nodes in the graph.</p>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.get_graph_properties">
-<code class="descname">get_graph_properties</code><span class="sig-paren">(</span><em>*args</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.get_graph_properties" title="Permalink to this definition">¶</a></dt>
-<dd><p>This function retrieves the properties of a graph.</p>
-<p>If no argument is given, the standard list of properties GRAPH_PROPERTIES is analyzed and their values are
-returned in a dict. If arguments are given, only this list will be used as standard list of properties.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Param:</th><td class="field-body">args: specific properties to be retrieved (optional)</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">dictionary containing the properties of the graph</td>
-</tr>
-<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body">dict</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.get_node_attributes">
-<code class="descname">get_node_attributes</code><span class="sig-paren">(</span><em>node</em>, <em>attr_list</em>, <em>print_in_log=False</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.get_node_attributes" title="Permalink to this definition">¶</a></dt>
-<dd><p>Function to get and print certain attributes of a node from the graph.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
-<li><strong>node</strong> (<em>str</em>) – node name</li>
-<li><strong>attr_list</strong> (<em>list</em>) – list with attributes to be pulled</li>
-<li><strong>print_in_log</strong> (<em>bool</em>) – option for printing to log</li>
-</ul>
-</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">dictionary with node attributes</p>
-</td>
-</tr>
-<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last">dict</p>
-</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.get_node_subcategory">
-<code class="descname">get_node_subcategory</code><span class="sig-paren">(</span><em>node</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.get_node_subcategory" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to analyse a node and to update the subcategory attribute of the node.</p>
-<p>The following table illustrates how the subcategory is determined based on the category, indegree and outdegree:</p>
-<table border="1" class="docutils">
-<colgroup>
-<col width="25%" />
-<col width="47%" />
-<col width="13%" />
-<col width="15%" />
-</colgroup>
-<thead valign="bottom">
-<tr class="row-odd"><th class="head">NODE CATEGORY</th>
-<th class="head">SUBCATEGORY</th>
-<th class="head">INDEGREE</th>
-<th class="head">OUTDEGREE</th>
-</tr>
-</thead>
-<tbody valign="top">
-<tr class="row-even"><td rowspan="9">variable</td>
-<td>hole</td>
-<td>0</td>
-<td>0</td>
-</tr>
-<tr class="row-odd"><td>supplied input</td>
-<td>0</td>
-<td>1</td>
-</tr>
-<tr class="row-even"><td>supplied shared input</td>
-<td>0</td>
-<td>>1</td>
-</tr>
-<tr class="row-odd"><td>output</td>
-<td>1</td>
-<td>0</td>
-</tr>
-<tr class="row-even"><td>collision</td>
-<td>>1</td>
-<td>0</td>
-</tr>
-<tr class="row-odd"><td>coupling
-or
-pure circular coupling</td>
-<td>1</td>
-<td>1</td>
-</tr>
-<tr class="row-even"><td>shared coupling
-or
-shared circular coupling</td>
-<td>1</td>
-<td>>1</td>
-</tr>
-<tr class="row-odd"><td>collided coupling
-or
-collided circular coupling</td>
-<td>>1</td>
-<td>1</td>
-</tr>
-<tr class="row-even"><td>collided shared coupling
-or
-collided shared circular coupling</td>
-<td>>1</td>
-<td>>1</td>
-</tr>
-<tr class="row-odd"><td rowspan="4">function</td>
-<td>hole</td>
-<td>0</td>
-<td>0</td>
-</tr>
-<tr class="row-even"><td>inputless</td>
-<td>0</td>
-<td>>0</td>
-</tr>
-<tr class="row-odd"><td>outputless</td>
-<td>>0</td>
-<td>0</td>
-</tr>
-<tr class="row-even"><td>complete</td>
-<td>>0</td>
-<td>>0</td>
-</tr>
-</tbody>
-</table>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>node</strong> (<em>basestring</em>) – node in the graph</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">subcategory of the node</td>
-</tr>
-<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body">basestring</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.get_nodes_based_on_strings">
-<code class="descname">get_nodes_based_on_strings</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.get_nodes_based_on_strings" title="Permalink to this definition">¶</a></dt>
-<dd><p>This function enables the user to search graph nodes for specific strings.</p>
-<p>Each provided string will be searched for, and if multiple node are found for each string, the user will be able
-to select the ones desired. The other matched nodes are disregarded.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
-<li><strong>args</strong> (<em>str</em>) – strings that graph nodes being searched for</li>
-<li><strong>kwargs</strong> (<em>include_all: bool</em>) – include_all: If include_all is set to True, all matching nodes are added to returned list</li>
-</ul>
-</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">matching nodes that user selected (all if include_all is True)</p>
-</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.get_nodes_indegree">
-<code class="descname">get_nodes_indegree</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.get_nodes_indegree" title="Permalink to this definition">¶</a></dt>
-<dd><p>Function to get the indegree of all the graph nodes and store them in a dictionary.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">dictionary with node name key and indegree integer value.</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Return type:</th><td class="field-body">dict</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.get_nodes_outdegree">
-<code class="descname">get_nodes_outdegree</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.get_nodes_outdegree" title="Permalink to this definition">¶</a></dt>
-<dd><p>Function to get the outdegree of all the graph nodes and store them in a dictionary.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">dictionary with node name key and outdegree integer value.</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Return type:</th><td class="field-body">dict</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.get_nodes_subcategory">
-<code class="descname">get_nodes_subcategory</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.get_nodes_subcategory" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to analyse all nodes and to update the subcategory attributes of the nodes.</p>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.get_number_of_couplings">
-<code class="descname">get_number_of_couplings</code><span class="sig-paren">(</span><em>node</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.get_number_of_couplings" title="Permalink to this definition">¶</a></dt>
-<dd><p>This function returns the number of couplings of a node in the graph.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>node</strong> – input node</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">number of couplings for the input node</td>
-</tr>
-<tr class="field-odd field"><th class="field-name">Type:</th><td class="field-body">int</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.get_possible_function_order">
-<code class="descname">get_possible_function_order</code><span class="sig-paren">(</span><em>method</em>, <em>multi_start=None</em>, <em>check_graph=False</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.get_possible_function_order" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to find a possible function order, in the order: pre-coupled, coupled, post-coupled functions</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
-<li><strong>method</strong> (<em>str</em>) – algorithm which will be used to minimize the feedback loops</li>
-<li><strong>multi_start</strong> (<em>int</em>) – start the algorithm from multiple starting points</li>
-<li><strong>check_graph</strong> (<em>bool</em>) – check whether graph has problematic variables</li>
-</ul>
-</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">Possible function order</p>
-</td>
-</tr>
-<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last">list</p>
-</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.get_same_graph_class">
-<code class="descname">get_same_graph_class</code><span class="sig-paren">(</span><em>graph</em>, <em>copy_type='deep'</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.get_same_graph_class" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to reinstantiate a given graph according to the same graph class as the self.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
-<li><strong>graph</strong> (<em>DiGraph</em>) – graph object to be reinstantiated</li>
-<li><strong>copy_type</strong> (<em>basestring</em>) – setting to have a deep or shallow copy of the graph</li>
-</ul>
-</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">reinstantiated graph</p>
-</td>
-</tr>
-<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last"><a class="reference internal" href="#kadmos.graph.graph_kadmos.KadmosGraph" title="kadmos.graph.graph_kadmos.KadmosGraph">KadmosGraph</a></p>
-</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.get_sources">
-<code class="descname">get_sources</code><span class="sig-paren">(</span><em>node</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.get_sources" title="Permalink to this definition">¶</a></dt>
-<dd><p>Function to determine the sources of a given node.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>node</strong> (<em>basestring</em>) – node for which sources should be found</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">list with sources</td>
-</tr>
-<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body">list</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.get_subgraph_by_function_nodes">
-<code class="descname">get_subgraph_by_function_nodes</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.get_subgraph_by_function_nodes" title="Permalink to this definition">¶</a></dt>
-<dd><p>This function retrieves a subgraph from the original graph only containing the argument nodes.</p>
-<p>All arguments must be found in the graph.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
-<li><strong>args</strong> (<em>list</em><em>, </em><em>str</em>) – arbitrary amount of graph nodes</li>
-<li><strong>kwargs</strong> (<em>copy_type: str</em>) – copy_type: type of copy (clean or deep)</li>
-</ul>
-</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">sub-graph only containing nodes provided as arguments, and their edges</p>
-</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.get_system_inputs">
-<code class="descname">get_system_inputs</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.get_system_inputs" title="Permalink to this definition">¶</a></dt>
-<dd><p>This method checks whether there are system inputs in the graph using the function nodes provided.</p>
-<p>The function nodes should be provided in the args. If system inputs exist they are returned.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>args</strong> – function nodes</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">system input nodes dictionary</td>
-</tr>
-<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body">dict</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.get_targets">
-<code class="descname">get_targets</code><span class="sig-paren">(</span><em>node</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.get_targets" title="Permalink to this definition">¶</a></dt>
-<dd><p>Function to determine the targets of a given node.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>node</strong> (<em>basestring</em>) – node for which targets should be found</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">list with targets</td>
-</tr>
-<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body">list</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.graph_has_nested_attributes">
-<code class="descname">graph_has_nested_attributes</code><span class="sig-paren">(</span><em>*attrbs</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.graph_has_nested_attributes" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to test if graph has nested attributes</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>attrbs</strong> (<em>str</em>) – attributes to check for nesting in graph</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">presence of nested attribute</td>
-</tr>
-<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body">bool</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.has_edge">
-<code class="descname">has_edge</code><span class="sig-paren">(</span><em>u</em>, <em>v</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.has_edge" title="Permalink to this definition">¶</a></dt>
-<dd><p>Return True if the edge (u, v) is in the graph.</p>
-<p>This is the same as <cite>v in G[u]</cite> without KeyError exceptions.</p>
-<dl class="docutils">
-<dt>u, v <span class="classifier-delimiter">:</span> <span class="classifier">nodes</span></dt>
-<dd>Nodes can be, for example, strings or numbers.
-Nodes must be hashable (and not None) Python objects.</dd>
-</dl>
-<dl class="docutils">
-<dt>edge_ind <span class="classifier-delimiter">:</span> <span class="classifier">bool</span></dt>
-<dd>True if edge is in the graph, False otherwise.</dd>
-</dl>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">path_graph</span><span class="p">(</span><span class="mi">4</span><span class="p">)</span> <span class="c1"># or DiGraph, MultiGraph, MultiDiGraph, etc</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">has_edge</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="c1"># using two nodes</span>
-<span class="go">True</span>
-<span class="gp">>>> </span><span class="n">e</span> <span class="o">=</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="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">has_edge</span><span class="p">(</span><span class="o">*</span><span class="n">e</span><span class="p">)</span> <span class="c1"># e is a 2-tuple (u, v)</span>
-<span class="go">True</span>
-<span class="gp">>>> </span><span class="n">e</span> <span class="o">=</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="p">{</span><span class="s1">'weight'</span><span class="p">:</span><span class="mi">7</span><span class="p">})</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">has_edge</span><span class="p">(</span><span class="o">*</span><span class="n">e</span><span class="p">[:</span><span class="mi">2</span><span class="p">])</span> <span class="c1"># e is a 3-tuple (u, v, data_dictionary)</span>
-<span class="go">True</span>
-</pre></div>
-</div>
-<p>The following syntax are equivalent:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">has_edge</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="go">True</span>
-<span class="gp">>>> </span><span class="mi">1</span> <span class="ow">in</span> <span class="n">G</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="c1"># though this gives KeyError if 0 not in G</span>
-<span class="go">True</span>
-</pre></div>
-</div>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.has_node">
-<code class="descname">has_node</code><span class="sig-paren">(</span><em>n</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.has_node" title="Permalink to this definition">¶</a></dt>
-<dd><p>Return True if the graph contains the node n.</p>
-<p>Identical to <cite>n in G</cite></p>
-<p>n : node</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">path_graph</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span> <span class="c1"># or DiGraph, MultiGraph, MultiDiGraph, etc</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">has_node</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
-<span class="go">True</span>
-</pre></div>
-</div>
-<p>It is more readable and simpler to use</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="mi">0</span> <span class="ow">in</span> <span class="n">G</span>
-<span class="go">True</span>
-</pre></div>
-</div>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.has_nodes">
-<code class="descname">has_nodes</code><span class="sig-paren">(</span><em>nodes</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.has_nodes" title="Permalink to this definition">¶</a></dt>
-<dd><p>Function that checks whether all nodes given in a list are present in the graph.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>nodes</strong> (<em>list</em>) – list of nodes to be checked</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">boolean whether all nodes have been found</td>
-</tr>
-<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body">bool</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.has_predecessor">
-<code class="descname">has_predecessor</code><span class="sig-paren">(</span><em>u</em>, <em>v</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.has_predecessor" title="Permalink to this definition">¶</a></dt>
-<dd><p>Return True if node u has predecessor v.</p>
-<p>This is true if graph has the edge u<-v.</p>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.has_successor">
-<code class="descname">has_successor</code><span class="sig-paren">(</span><em>u</em>, <em>v</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.has_successor" title="Permalink to this definition">¶</a></dt>
-<dd><p>Return True if node u has successor v.</p>
-<p>This is true if graph has the edge u->v.</p>
-</dd></dl>
-
-<dl class="attribute">
-<dt id="kadmos.graph.graph_data.DataGraph.in_degree">
-<code class="descname">in_degree</code><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.in_degree" title="Permalink to this definition">¶</a></dt>
-<dd><p>An InDegreeView for (node, in_degree) or in_degree for single node.</p>
-<p>The node in_degree is the number of edges pointing to the node.
-The weighted node degree is the sum of the edge weights for
-edges incident to that node.</p>
-<p>This object provides an iteration over (node, in_degree) as well as
-lookup for the degree for a single node.</p>
-<dl class="docutils">
-<dt>nbunch <span class="classifier-delimiter">:</span> <span class="classifier">single node, container, or all nodes (default= all nodes)</span></dt>
-<dd>The view will only report edges incident to these nodes.</dd>
-<dt>weight <span class="classifier-delimiter">:</span> <span class="classifier">string or None, optional (default=None)</span></dt>
-<dd>The name of an edge attribute that holds the numerical value used
-as a weight. If None, then each edge has weight 1.
-The degree is the sum of the edge weights adjacent to the node.</dd>
-</dl>
-<p>If a single node is requested
-deg : int</p>
-<blockquote>
-<div>In-degree of the node</div></blockquote>
-<p>OR if multiple nodes are requested
-nd_iter : iterator</p>
-<blockquote>
-<div>The iterator returns two-tuples of (node, in-degree).</div></blockquote>
-<p>degree, out_degree</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">DiGraph</span><span class="p">()</span>
-<span class="gp">>>> </span><span class="n">nx</span><span class="o">.</span><span class="n">add_path</span><span class="p">(</span><span class="n">G</span><span class="p">,</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">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">])</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">in_degree</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span> <span class="c1"># node 0 with degree 0</span>
-<span class="go">0</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">in_degree</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">2</span><span class="p">]))</span>
-<span class="go">[(0, 0), (1, 1), (2, 1)]</span>
-</pre></div>
-</div>
-</dd></dl>
-
-<dl class="attribute">
-<dt id="kadmos.graph.graph_data.DataGraph.in_edges">
-<code class="descname">in_edges</code><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.in_edges" title="Permalink to this definition">¶</a></dt>
-<dd><p>An InEdgeView of the Graph as G.in_edges or G.in_edges().</p>
-<p>in_edges(self, nbunch=None, data=False, default=None):</p>
-<dl class="docutils">
-<dt>nbunch <span class="classifier-delimiter">:</span> <span class="classifier">single node, container, or all nodes (default= all nodes)</span></dt>
-<dd>The view will only report edges incident to these nodes.</dd>
-<dt>data <span class="classifier-delimiter">:</span> <span class="classifier">string or bool, optional (default=False)</span></dt>
-<dd>The edge attribute returned in 3-tuple (u, v, ddict[data]).
-If True, return edge attribute dict in 3-tuple (u, v, ddict).
-If False, return 2-tuple (u, v).</dd>
-<dt>default <span class="classifier-delimiter">:</span> <span class="classifier">value, optional (default=None)</span></dt>
-<dd>Value used for edges that dont have the requested attribute.
-Only relevant if data is not True or False.</dd>
-</dl>
-<dl class="docutils">
-<dt>in_edges <span class="classifier-delimiter">:</span> <span class="classifier">InEdgeView</span></dt>
-<dd>A view of edge attributes, usually it iterates over (u, v)
-or (u, v, d) tuples of edges, but can also be used for
-attribute lookup as <cite>edges[u, v][‘foo’]</cite>.</dd>
-</dl>
-<p>edges</p>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.inspect">
-<code class="descname">inspect</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.inspect" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to print an overview of the graph.</p>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.inspect_node">
-<code class="descname">inspect_node</code><span class="sig-paren">(</span><em>node</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.inspect_node" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to print a node with details.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>node</strong> (<em>str</em>) – node</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.inspect_nodes">
-<code class="descname">inspect_nodes</code><span class="sig-paren">(</span><em>list_of_nodes</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.inspect_nodes" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to inspect/print a list of nodes with details.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>list_of_nodes</strong> (<em>list</em>) – node list</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.is_directed">
-<code class="descname">is_directed</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.is_directed" title="Permalink to this definition">¶</a></dt>
-<dd><p>Return True if graph is directed, False otherwise.</p>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.is_multigraph">
-<code class="descname">is_multigraph</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.is_multigraph" title="Permalink to this definition">¶</a></dt>
-<dd><p>Return True if graph is a multigraph, False otherwise.</p>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.load_cmdows">
-<code class="descname">load_cmdows</code><span class="sig-paren">(</span><em>cmdows</em>, <em>check_list</em>, <em>ignore_modes=False</em>, <em>keep_running=False</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.load_cmdows" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to load the graph from a CMDOWS file</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
-<li><strong>cmdows</strong> (<em>str</em>) – CMDOWS file path</li>
-<li><strong>check_list</strong> (<em>list</em>) – checks to be performed. See below.</li>
-<li><strong>ignore_modes</strong> (<em>bool</em>) – for determining if modes are taken into account</li>
-<li><strong>keep_running</strong> (<em>bool</em>) – for determining if errors should be raised</li>
-</ul>
-</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">mpg</p>
-</td>
-</tr>
-<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last"><a class="reference internal" href="#kadmos.graph.graph_process.MdaoProcessGraph" title="kadmos.graph.graph_process.MdaoProcessGraph">MdaoProcessGraph</a></p>
-</td>
-</tr>
-</tbody>
-</table>
-<p>Check_list options:</p>
-<ul class="simple">
-<li>‘consistent_root’: check if all in-/output files have the same root element</li>
-<li>‘invalid_leaf_elements’: check for leaf elements that still have child elements in other in-/output files</li>
-<li>‘schemas’: check if the in-/output files are consistent with the schema.</li>
-</ul>
-<p>To perform all of the checks without stopping if an error is found by the checks:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">check_list</span> <span class="o">=</span> <span class="p">[</span><span class="s1">'consistent_root'</span><span class="p">,</span> <span class="s1">'invalid_leaf_elements'</span><span class="p">,</span> <span class="s1">'schemas'</span><span class="p">]</span>
-<span class="gp">>>> </span><span class="n">graph</span><span class="o">.</span><span class="n">load_cmdows</span><span class="p">(</span><span class="n">cmdows</span><span class="p">,</span> <span class="n">check_list</span><span class="p">,</span> <span class="n">keep_running</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
-</pre></div>
-</div>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.make_all_variables_valid">
-<code class="descname">make_all_variables_valid</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.make_all_variables_valid" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to analyze all variables in a graph and make any problematic variables valid.</p>
-<p>Problematic variable are holes and splittables. Splittable variables are split and holes will simply be removed.</p>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.mark_as_constraint">
-<code class="descname">mark_as_constraint</code><span class="sig-paren">(</span><em>node</em>, <em>operator</em>, <em>reference_value</em>, <em>remove_unused_outputs=False</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.mark_as_constraint" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to mark a node as a constraint.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
-<li><strong>node</strong> – node to be marked (on the left side of the operator</li>
-<li><strong>operator</strong> (<em>str</em>) – constraint operator</li>
-<li><strong>reference_value</strong> (<em>numbers.Number</em>) – value on the right side of the operator</li>
-</ul>
-</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.mark_as_constraints">
-<code class="descname">mark_as_constraints</code><span class="sig-paren">(</span><em>nodes</em>, <em>operators</em>, <em>reference_values</em>, <em>remove_unused_outputs=False</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.mark_as_constraints" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to mark multiple nodes as constraints.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
-<li><strong>nodes</strong> – list of nodes to be marked.</li>
-<li><strong>operators</strong> – operators to be implemented (as list per node or as single operator for all)</li>
-<li><strong>reference_values</strong> – reference values to be used (as list of values per node or as single value for all)</li>
-</ul>
-</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">graph with enriched constraint nodes</p>
-</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.mark_as_design_variable">
-<code class="descname">mark_as_design_variable</code><span class="sig-paren">(</span><em>node</em>, <em>lower_bound=None</em>, <em>upper_bound=None</em>, <em>samples=None</em>, <em>nominal_value=0.0</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.mark_as_design_variable" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to mark a single node as a design variable and add the required metadata for its definition.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
-<li><strong>node</strong> – </li>
-<li><strong>lower_bound</strong> – </li>
-<li><strong>upper_bound</strong> – </li>
-<li><strong>samples</strong> – </li>
-</ul>
-</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last"></p>
-</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.mark_as_design_variables">
-<code class="descname">mark_as_design_variables</code><span class="sig-paren">(</span><em>nodes</em>, <em>lower_bounds=None</em>, <em>upper_bounds=None</em>, <em>samples=None</em>, <em>nominal_values=None</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.mark_as_design_variables" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to mark a list of nodes as design variable and add metadata.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
-<li><strong>nodes</strong> (<em>list</em><em> or </em><em>str</em>) – list of nodes present in the graph</li>
-<li><strong>lower_bounds</strong> (<em>list</em><em> or </em><em>numbers.Number</em>) – list of lower bound values</li>
-<li><strong>upper_bounds</strong> (<em>list</em><em> or </em><em>numbers.Number</em>) – list of upper bounds</li>
-<li><strong>samples</strong> (<em>list</em>) – nested list of kadmos values</li>
-<li><strong>nominal_values</strong> (<em>list</em><em> or </em><em>numbers.Number</em>) – list of nominal values</li>
-</ul>
-</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.mark_as_objective">
-<code class="descname">mark_as_objective</code><span class="sig-paren">(</span><em>node</em>, <em>remove_unused_outputs=False</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.mark_as_objective" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to mark a single node as objective.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>node</strong> (<em>basestring</em>) – variable node</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.mark_as_qois">
-<code class="descname">mark_as_qois</code><span class="sig-paren">(</span><em>nodes</em>, <em>remove_unused_outputs=False</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.mark_as_qois" title="Permalink to this definition">¶</a></dt>
-<dd><p>Function to mark a list of nodes as quantity of interest.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>nodes</strong> (<em>list</em>) – list of nodes present in the graph</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.merge_function_modes">
-<code class="descname">merge_function_modes</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.merge_function_modes" title="Permalink to this definition">¶</a></dt>
-<dd><p>Function to contract certain modes of the same function.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
-<li><strong>args</strong> (<em>str</em>) – function (first arg) and then followed by modes to be contracted.</li>
-<li><strong>kwargs</strong> (<em>dict</em><em> or </em><em>str</em>) – new_label to specify new node label manually (optional)</li>
-</ul>
-</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">contracted graph</p>
-</td>
-</tr>
-<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last"><a class="reference internal" href="#kadmos.graph.graph_kadmos.KadmosGraph" title="kadmos.graph.graph_kadmos.KadmosGraph">KadmosGraph</a></p>
-</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.merge_function_nodes_based_on_modes">
-<code class="descname">merge_function_nodes_based_on_modes</code><span class="sig-paren">(</span><em>merge_funcs=None</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.merge_function_nodes_based_on_modes" title="Permalink to this definition">¶</a></dt>
-<dd><p>This class method merges all execution modes of the same function into a single node.</p>
-<p>Mainly used for illustration purposes since information on the execution modes gets lost. Functions must be
-present in graph.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>merge_funcs</strong> (<em>list</em><em>, </em><em>tuple</em>) – List of tuple of functions to merge. If empty (default), all functions are merged.</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">merged graph</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.merge_functions">
-<code class="descname">merge_functions</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.merge_functions" title="Permalink to this definition">¶</a></dt>
-<dd><p>Function to merge a collection of functions.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
-<li><strong>args</strong> (<em>node_ids</em>) – functions to be merged</li>
-<li><strong>kwargs</strong> (<em>dict</em>) – new_label to specify new node label manually (optional)</li>
-</ul>
-</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.merge_parallel_functions">
-<code class="descname">merge_parallel_functions</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.merge_parallel_functions" title="Permalink to this definition">¶</a></dt>
-<dd><p>Function to merge a list of functions</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
-<li><strong>args</strong> (<em>node_ids</em>) – functions to be merged</li>
-<li><strong>kwargs</strong> (<em>dict</em>) – new_label to specify new node label manually (optional)</li>
-</ul>
-</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.merge_sequential_functions">
-<code class="descname">merge_sequential_functions</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.merge_sequential_functions" title="Permalink to this definition">¶</a></dt>
-<dd><p>Function to merge a collection of functions.</p>
-<p>It is assumed that the merged functions are actually executed in the sequence in which they are given to this
-function.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
-<li><strong>args</strong> (<em>node_ids</em>) – functions to be merged in the given sequence</li>
-<li><strong>kwargs</strong> (<em>str</em>) – new_label to specify new node label manually (optional)</li>
-</ul>
-</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.minimize_feedback">
-<code class="descname">minimize_feedback</code><span class="sig-paren">(</span><em>nodes</em>, <em>method</em>, <em>multi_start=None</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.minimize_feedback" title="Permalink to this definition">¶</a></dt>
-<dd><p>Function to find the function order with minimum feedback</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
-<li><strong>nodes</strong> (<em>list</em>) – nodes for which the feedback needs to be minimized</li>
-<li><strong>method</strong> (<em>str</em>) – algorithm used to find optimal function order</li>
-<li><strong>multi_start</strong> (<em>int</em>) – start the algorithm from multiple starting points</li>
-</ul>
-</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">function order</p>
-</td>
-</tr>
-<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last">list</p>
-</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="attribute">
-<dt id="kadmos.graph.graph_data.DataGraph.name">
-<code class="descname">name</code><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.name" title="Permalink to this definition">¶</a></dt>
-<dd><p>String identifier of the graph.</p>
-<p>This graph attribute appears in the attribute dict G.graph
-keyed by the string <cite>“nameâ€</cite>. as well as an attribute (technically
-a property) <cite>G.name</cite>. This is entirely user controlled.</p>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.nbunch_iter">
-<code class="descname">nbunch_iter</code><span class="sig-paren">(</span><em>nbunch=None</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.nbunch_iter" title="Permalink to this definition">¶</a></dt>
-<dd><p>Return an iterator over nodes contained in nbunch that are
-also in the graph.</p>
-<p>The nodes in nbunch are checked for membership in the graph
-and if not are silently ignored.</p>
-<dl class="docutils">
-<dt>nbunch <span class="classifier-delimiter">:</span> <span class="classifier">single node, container, or all nodes (default= all nodes)</span></dt>
-<dd>The view will only report edges incident to these nodes.</dd>
-</dl>
-<dl class="docutils">
-<dt>niter <span class="classifier-delimiter">:</span> <span class="classifier">iterator</span></dt>
-<dd>An iterator over nodes in nbunch that are also in the graph.
-If nbunch is None, iterate over all nodes in the graph.</dd>
-</dl>
-<dl class="docutils">
-<dt>NetworkXError</dt>
-<dd>If nbunch is not a node or or sequence of nodes.
-If a node in nbunch is not hashable.</dd>
-</dl>
-<p>Graph.__iter__</p>
-<p>When nbunch is an iterator, the returned iterator yields values
-directly from nbunch, becoming exhausted when nbunch is exhausted.</p>
-<p>To test whether nbunch is a single node, one can use
-“if nbunch in self:â€, even after processing with this routine.</p>
-<p>If nbunch is not a node or a (possibly empty) sequence/iterator
-or None, a <code class="xref py py-exc docutils literal notranslate"><span class="pre">NetworkXError</span></code> is raised. Also, if any object in
-nbunch is not hashable, a <code class="xref py py-exc docutils literal notranslate"><span class="pre">NetworkXError</span></code> is raised.</p>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.neighbors">
-<code class="descname">neighbors</code><span class="sig-paren">(</span><em>n</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.neighbors" title="Permalink to this definition">¶</a></dt>
-<dd><p>Return an iterator over successor nodes of n.</p>
-<p>neighbors() and successors() are the same.</p>
-</dd></dl>
-
-<dl class="attribute">
-<dt id="kadmos.graph.graph_data.DataGraph.node">
-<code class="descname">node</code><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.node" title="Permalink to this definition">¶</a></dt>
-<dd><p>A NodeView of the Graph as G.nodes or G.nodes().</p>
-<p>Can be used as <cite>G.nodes</cite> for data lookup and for set-like operations.
-Can also be used as <cite>G.nodes(data=’color’, default=None)</cite> to return a
-NodeDataView which reports specific node data but no set operations.
-It presents a dict-like interface as well with <cite>G.nodes.items()</cite>
-iterating over <cite>(node, nodedata)</cite> 2-tuples and <cite>G.nodes[3][‘foo’]</cite>
-providing the value of the <cite>foo</cite> attribute for node <cite>3</cite>. In addition,
-a view <cite>G.nodes.data(‘foo’)</cite> provides a dict-like interface to the
-<cite>foo</cite> attribute of each node. <cite>G.nodes.data(‘foo’, default=1)</cite>
-provides a default for nodes that do not have attribute <cite>foo</cite>.</p>
-<dl class="docutils">
-<dt>data <span class="classifier-delimiter">:</span> <span class="classifier">string or bool, optional (default=False)</span></dt>
-<dd>The node attribute returned in 2-tuple (n, ddict[data]).
-If True, return entire node attribute dict as (n, ddict).
-If False, return just the nodes n.</dd>
-<dt>default <span class="classifier-delimiter">:</span> <span class="classifier">value, optional (default=None)</span></dt>
-<dd>Value used for nodes that dont have the requested attribute.
-Only relevant if data is not True or False.</dd>
-</dl>
-<dl class="docutils">
-<dt>NodeView</dt>
-<dd><p class="first">Allows set-like operations over the nodes as well as node
-attribute dict lookup and calling to get a NodeDataView.
-A NodeDataView iterates over <cite>(n, data)</cite> and has no set operations.
-A NodeView iterates over <cite>n</cite> and includes set operations.</p>
-<p class="last">When called, if data is False, an iterator over nodes.
-Otherwise an iterator of 2-tuples (node, attribute value)
-where the attribute is specified in <cite>data</cite>.
-If data is True then the attribute becomes the
-entire data dictionary.</p>
-</dd>
-</dl>
-<p>If your node data is not needed, it is simpler and equivalent
-to use the expression <code class="docutils literal notranslate"><span class="pre">for</span> <span class="pre">n</span> <span class="pre">in</span> <span class="pre">G</span></code>, or <code class="docutils literal notranslate"><span class="pre">list(G)</span></code>.</p>
-<p>There are two simple ways of getting a list of all nodes in the graph:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">path_graph</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">)</span>
-<span class="go">[0, 1, 2]</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="p">)</span>
-<span class="go">[0, 1, 2]</span>
-</pre></div>
-</div>
-<p>To get the node data along with the nodes:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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="mi">1</span><span class="p">,</span> <span class="n">time</span><span class="o">=</span><span class="s1">'5pm'</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">[</span><span class="mi">0</span><span class="p">][</span><span class="s1">'foo'</span><span class="p">]</span> <span class="o">=</span> <span class="s1">'bar'</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="kc">True</span><span class="p">))</span>
-<span class="go">[(0, {'foo': 'bar'}), (1, {'time': '5pm'}), (2, {})]</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="o">.</span><span class="n">data</span><span class="p">())</span>
-<span class="go">[(0, {'foo': 'bar'}), (1, {'time': '5pm'}), (2, {})]</span>
-</pre></div>
-</div>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="s1">'foo'</span><span class="p">))</span>
-<span class="go">[(0, 'bar'), (1, None), (2, None)]</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="o">.</span><span class="n">data</span><span class="p">(</span><span class="s1">'foo'</span><span class="p">))</span>
-<span class="go">[(0, 'bar'), (1, None), (2, None)]</span>
-</pre></div>
-</div>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="s1">'time'</span><span class="p">))</span>
-<span class="go">[(0, None), (1, '5pm'), (2, None)]</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="o">.</span><span class="n">data</span><span class="p">(</span><span class="s1">'time'</span><span class="p">))</span>
-<span class="go">[(0, None), (1, '5pm'), (2, None)]</span>
-</pre></div>
-</div>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="s1">'time'</span><span class="p">,</span> <span class="n">default</span><span class="o">=</span><span class="s1">'Not Available'</span><span class="p">))</span>
-<span class="go">[(0, 'Not Available'), (1, '5pm'), (2, 'Not Available')]</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="o">.</span><span class="n">data</span><span class="p">(</span><span class="s1">'time'</span><span class="p">,</span> <span class="n">default</span><span class="o">=</span><span class="s1">'Not Available'</span><span class="p">))</span>
-<span class="go">[(0, 'Not Available'), (1, '5pm'), (2, 'Not Available')]</span>
-</pre></div>
-</div>
-<p>If some of your nodes have an attribute and the rest are assumed
-to have a default attribute value you can create a dictionary
-from node/attribute pairs using the <cite>default</cite> keyword argument
-to guarantee the value is never None:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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="mi">0</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="mi">1</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="mi">2</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="mi">2</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="mi">3</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="nb">dict</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="s1">'weight'</span><span class="p">,</span> <span class="n">default</span><span class="o">=</span><span class="mi">1</span><span class="p">))</span>
-<span class="go">{0: 1, 1: 2, 2: 3}</span>
-</pre></div>
-</div>
-</dd></dl>
-
-<dl class="attribute">
-<dt id="kadmos.graph.graph_data.DataGraph.node_dict_factory">
-<code class="descname">node_dict_factory</code><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.node_dict_factory" title="Permalink to this definition">¶</a></dt>
-<dd><p>alias of <code class="xref py py-class docutils literal notranslate"><span class="pre">__builtin__.dict</span></code></p>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.node_is_function">
-<code class="descname">node_is_function</code><span class="sig-paren">(</span><em>node</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.node_is_function" title="Permalink to this definition">¶</a></dt>
-<dd><p>Function that checks whether a node is a function node or not.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>node</strong> (<em>str</em>) – node in graph</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">check result</td>
-</tr>
-<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body">bool</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.node_is_hole">
-<code class="descname">node_is_hole</code><span class="sig-paren">(</span><em>node</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.node_is_hole" title="Permalink to this definition">¶</a></dt>
-<dd><p>Function that checks whether a node is a hole (unconnected).</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>node</strong> (<em>str</em>) – node in graph</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">check result</td>
-</tr>
-<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body">bool</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.node_is_objective_function">
-<code class="descname">node_is_objective_function</code><span class="sig-paren">(</span><em>node</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.node_is_objective_function" title="Permalink to this definition">¶</a></dt>
-<dd><p>This function checks whether the provided node is a objective function.</p>
-<dl class="docutils">
-<dt>This function checks whether the provided node:</dt>
-<dd><ol class="first last arabic simple">
-<li>exists in graph</li>
-<li>has name-attribute “Objectiveâ€</li>
-<li>has an out-degree of 1</li>
-<li>has an outgoing node with an out-degree of zero # TODO: THIS IS WRONG!</li>
-</ol>
-</dd>
-</dl>
-<p>Only if all checks are satisfied, is the node a valid objective function node.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>node</strong> (<em>str</em>) – graph node to be tested</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">check result</td>
-</tr>
-<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body">bool</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.node_is_output">
-<code class="descname">node_is_output</code><span class="sig-paren">(</span><em>node</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.node_is_output" title="Permalink to this definition">¶</a></dt>
-<dd><p>Function that checks whether a node is a system output.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>node</strong> (<em>str</em>) – node in graph</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">check result</td>
-</tr>
-<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body">bool</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.node_is_variable">
-<code class="descname">node_is_variable</code><span class="sig-paren">(</span><em>node</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.node_is_variable" title="Permalink to this definition">¶</a></dt>
-<dd><p>Function that checks whether a node is a variable node or not.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>node</strong> (<em>str</em>) – node in graph</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">check result</td>
-</tr>
-<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body">bool</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="attribute">
-<dt id="kadmos.graph.graph_data.DataGraph.nodes">
-<code class="descname">nodes</code><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.nodes" title="Permalink to this definition">¶</a></dt>
-<dd><p>A NodeView of the Graph as G.nodes or G.nodes().</p>
-<p>Can be used as <cite>G.nodes</cite> for data lookup and for set-like operations.
-Can also be used as <cite>G.nodes(data=’color’, default=None)</cite> to return a
-NodeDataView which reports specific node data but no set operations.
-It presents a dict-like interface as well with <cite>G.nodes.items()</cite>
-iterating over <cite>(node, nodedata)</cite> 2-tuples and <cite>G.nodes[3][‘foo’]</cite>
-providing the value of the <cite>foo</cite> attribute for node <cite>3</cite>. In addition,
-a view <cite>G.nodes.data(‘foo’)</cite> provides a dict-like interface to the
-<cite>foo</cite> attribute of each node. <cite>G.nodes.data(‘foo’, default=1)</cite>
-provides a default for nodes that do not have attribute <cite>foo</cite>.</p>
-<dl class="docutils">
-<dt>data <span class="classifier-delimiter">:</span> <span class="classifier">string or bool, optional (default=False)</span></dt>
-<dd>The node attribute returned in 2-tuple (n, ddict[data]).
-If True, return entire node attribute dict as (n, ddict).
-If False, return just the nodes n.</dd>
-<dt>default <span class="classifier-delimiter">:</span> <span class="classifier">value, optional (default=None)</span></dt>
-<dd>Value used for nodes that dont have the requested attribute.
-Only relevant if data is not True or False.</dd>
-</dl>
-<dl class="docutils">
-<dt>NodeView</dt>
-<dd><p class="first">Allows set-like operations over the nodes as well as node
-attribute dict lookup and calling to get a NodeDataView.
-A NodeDataView iterates over <cite>(n, data)</cite> and has no set operations.
-A NodeView iterates over <cite>n</cite> and includes set operations.</p>
-<p class="last">When called, if data is False, an iterator over nodes.
-Otherwise an iterator of 2-tuples (node, attribute value)
-where the attribute is specified in <cite>data</cite>.
-If data is True then the attribute becomes the
-entire data dictionary.</p>
-</dd>
-</dl>
-<p>If your node data is not needed, it is simpler and equivalent
-to use the expression <code class="docutils literal notranslate"><span class="pre">for</span> <span class="pre">n</span> <span class="pre">in</span> <span class="pre">G</span></code>, or <code class="docutils literal notranslate"><span class="pre">list(G)</span></code>.</p>
-<p>There are two simple ways of getting a list of all nodes in the graph:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">path_graph</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">)</span>
-<span class="go">[0, 1, 2]</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="p">)</span>
-<span class="go">[0, 1, 2]</span>
-</pre></div>
-</div>
-<p>To get the node data along with the nodes:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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="mi">1</span><span class="p">,</span> <span class="n">time</span><span class="o">=</span><span class="s1">'5pm'</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">[</span><span class="mi">0</span><span class="p">][</span><span class="s1">'foo'</span><span class="p">]</span> <span class="o">=</span> <span class="s1">'bar'</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="kc">True</span><span class="p">))</span>
-<span class="go">[(0, {'foo': 'bar'}), (1, {'time': '5pm'}), (2, {})]</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="o">.</span><span class="n">data</span><span class="p">())</span>
-<span class="go">[(0, {'foo': 'bar'}), (1, {'time': '5pm'}), (2, {})]</span>
-</pre></div>
-</div>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="s1">'foo'</span><span class="p">))</span>
-<span class="go">[(0, 'bar'), (1, None), (2, None)]</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="o">.</span><span class="n">data</span><span class="p">(</span><span class="s1">'foo'</span><span class="p">))</span>
-<span class="go">[(0, 'bar'), (1, None), (2, None)]</span>
-</pre></div>
-</div>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="s1">'time'</span><span class="p">))</span>
-<span class="go">[(0, None), (1, '5pm'), (2, None)]</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="o">.</span><span class="n">data</span><span class="p">(</span><span class="s1">'time'</span><span class="p">))</span>
-<span class="go">[(0, None), (1, '5pm'), (2, None)]</span>
-</pre></div>
-</div>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="s1">'time'</span><span class="p">,</span> <span class="n">default</span><span class="o">=</span><span class="s1">'Not Available'</span><span class="p">))</span>
-<span class="go">[(0, 'Not Available'), (1, '5pm'), (2, 'Not Available')]</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="o">.</span><span class="n">data</span><span class="p">(</span><span class="s1">'time'</span><span class="p">,</span> <span class="n">default</span><span class="o">=</span><span class="s1">'Not Available'</span><span class="p">))</span>
-<span class="go">[(0, 'Not Available'), (1, '5pm'), (2, 'Not Available')]</span>
-</pre></div>
-</div>
-<p>If some of your nodes have an attribute and the rest are assumed
-to have a default attribute value you can create a dictionary
-from node/attribute pairs using the <cite>default</cite> keyword argument
-to guarantee the value is never None:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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="mi">0</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="mi">1</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="mi">2</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="mi">2</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="mi">3</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="nb">dict</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="s1">'weight'</span><span class="p">,</span> <span class="n">default</span><span class="o">=</span><span class="mi">1</span><span class="p">))</span>
-<span class="go">{0: 1, 1: 2, 2: 3}</span>
-</pre></div>
-</div>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.number_of_edges">
-<code class="descname">number_of_edges</code><span class="sig-paren">(</span><em>u=None</em>, <em>v=None</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.number_of_edges" title="Permalink to this definition">¶</a></dt>
-<dd><p>Return the number of edges between two nodes.</p>
-<dl class="docutils">
-<dt>u, v <span class="classifier-delimiter">:</span> <span class="classifier">nodes, optional (default=all edges)</span></dt>
-<dd>If u and v are specified, return the number of edges between
-u and v. Otherwise return the total number of all edges.</dd>
-</dl>
-<dl class="docutils">
-<dt>nedges <span class="classifier-delimiter">:</span> <span class="classifier">int</span></dt>
-<dd>The number of edges in the graph. If nodes <cite>u</cite> and <cite>v</cite> are
-specified return the number of edges between those nodes. If
-the graph is directed, this only returns the number of edges
-from <cite>u</cite> to <cite>v</cite>.</dd>
-</dl>
-<p>size</p>
-<p>For undirected graphs, this method counts the total number of
-edges in the graph:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">path_graph</span><span class="p">(</span><span class="mi">4</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">number_of_edges</span><span class="p">()</span>
-<span class="go">3</span>
-</pre></div>
-</div>
-<p>If you specify two nodes, this counts the total number of edges
-joining the two nodes:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">number_of_edges</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="go">1</span>
-</pre></div>
-</div>
-<p>For directed graphs, this method can count the total number of
-directed edges from <cite>u</cite> to <cite>v</cite>:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">DiGraph</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="mi">0</span><span class="p">,</span> <span class="mi">1</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="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">number_of_edges</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="go">1</span>
-</pre></div>
-</div>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.number_of_nodes">
-<code class="descname">number_of_nodes</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.number_of_nodes" title="Permalink to this definition">¶</a></dt>
-<dd><p>Return the number of nodes in the graph.</p>
-<dl class="docutils">
-<dt>nnodes <span class="classifier-delimiter">:</span> <span class="classifier">int</span></dt>
-<dd>The number of nodes in the graph.</dd>
-</dl>
-<p>order, __len__ which are identical</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">path_graph</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span> <span class="c1"># or DiGraph, MultiGraph, MultiDiGraph, etc</span>
-<span class="gp">>>> </span><span class="nb">len</span><span class="p">(</span><span class="n">G</span><span class="p">)</span>
-<span class="go">3</span>
-</pre></div>
-</div>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.order">
-<code class="descname">order</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.order" title="Permalink to this definition">¶</a></dt>
-<dd><p>Return the number of nodes in the graph.</p>
-<dl class="docutils">
-<dt>nnodes <span class="classifier-delimiter">:</span> <span class="classifier">int</span></dt>
-<dd>The number of nodes in the graph.</dd>
-</dl>
-<p>number_of_nodes, __len__ which are identical</p>
-</dd></dl>
-
-<dl class="attribute">
-<dt id="kadmos.graph.graph_data.DataGraph.out_degree">
-<code class="descname">out_degree</code><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.out_degree" title="Permalink to this definition">¶</a></dt>
-<dd><p>An OutDegreeView for (node, out_degree)</p>
-<p>The node out_degree is the number of edges pointing out of the node.
-The weighted node degree is the sum of the edge weights for
-edges incident to that node.</p>
-<p>This object provides an iterator over (node, out_degree) as well as
-lookup for the degree for a single node.</p>
-<dl class="docutils">
-<dt>nbunch <span class="classifier-delimiter">:</span> <span class="classifier">single node, container, or all nodes (default= all nodes)</span></dt>
-<dd>The view will only report edges incident to these nodes.</dd>
-<dt>weight <span class="classifier-delimiter">:</span> <span class="classifier">string or None, optional (default=None)</span></dt>
-<dd>The name of an edge attribute that holds the numerical value used
-as a weight. If None, then each edge has weight 1.
-The degree is the sum of the edge weights adjacent to the node.</dd>
-</dl>
-<p>If a single node is requested
-deg : int</p>
-<blockquote>
-<div>Out-degree of the node</div></blockquote>
-<p>OR if multiple nodes are requested
-nd_iter : iterator</p>
-<blockquote>
-<div>The iterator returns two-tuples of (node, out-degree).</div></blockquote>
-<p>degree, in_degree</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">DiGraph</span><span class="p">()</span>
-<span class="gp">>>> </span><span class="n">nx</span><span class="o">.</span><span class="n">add_path</span><span class="p">(</span><span class="n">G</span><span class="p">,</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">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">])</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">out_degree</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span> <span class="c1"># node 0 with degree 1</span>
-<span class="go">1</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">out_degree</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">2</span><span class="p">]))</span>
-<span class="go">[(0, 1), (1, 1), (2, 1)]</span>
-</pre></div>
-</div>
-</dd></dl>
-
-<dl class="attribute">
-<dt id="kadmos.graph.graph_data.DataGraph.out_edges">
-<code class="descname">out_edges</code><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.out_edges" title="Permalink to this definition">¶</a></dt>
-<dd><p>An OutEdgeView of the DiGraph as G.edges or G.edges().</p>
-<p>edges(self, nbunch=None, data=False, default=None)</p>
-<p>The OutEdgeView provides set-like operations on the edge-tuples
-as well as edge attribute lookup. When called, it also provides
-an EdgeDataView object which allows control of access to edge
-attributes (but does not provide set-like operations).
-Hence, <cite>G.edges[u, v][‘color’]</cite> provides the value of the color
-attribute for edge <cite>(u, v)</cite> while
-<cite>for (u, v, c) in G.edges.data(‘color’, default=’red’):</cite>
-iterates through all the edges yielding the color attribute
-with default <cite>‘red’</cite> if no color attribute exists.</p>
-<dl class="docutils">
-<dt>nbunch <span class="classifier-delimiter">:</span> <span class="classifier">single node, container, or all nodes (default= all nodes)</span></dt>
-<dd>The view will only report edges incident to these nodes.</dd>
-<dt>data <span class="classifier-delimiter">:</span> <span class="classifier">string or bool, optional (default=False)</span></dt>
-<dd>The edge attribute returned in 3-tuple (u, v, ddict[data]).
-If True, return edge attribute dict in 3-tuple (u, v, ddict).
-If False, return 2-tuple (u, v).</dd>
-<dt>default <span class="classifier-delimiter">:</span> <span class="classifier">value, optional (default=None)</span></dt>
-<dd>Value used for edges that dont have the requested attribute.
-Only relevant if data is not True or False.</dd>
-</dl>
-<dl class="docutils">
-<dt>edges <span class="classifier-delimiter">:</span> <span class="classifier">OutEdgeView</span></dt>
-<dd>A view of edge attributes, usually it iterates over (u, v)
-or (u, v, d) tuples of edges, but can also be used for
-attribute lookup as <cite>edges[u, v][‘foo’]</cite>.</dd>
-</dl>
-<p>in_edges, out_edges</p>
-<p>Nodes in nbunch that are not in the graph will be (quietly) ignored.
-For directed graphs this returns the out-edges.</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">DiGraph</span><span class="p">()</span> <span class="c1"># or MultiDiGraph, etc</span>
-<span class="gp">>>> </span><span class="n">nx</span><span class="o">.</span><span class="n">add_path</span><span class="p">(</span><span class="n">G</span><span class="p">,</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">2</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="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="mi">5</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="p">[</span><span class="n">e</span> <span class="k">for</span> <span class="n">e</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="go">[(0, 1), (1, 2), (2, 3)]</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">edges</span><span class="o">.</span><span class="n">data</span><span class="p">()</span> <span class="c1"># default data is {} (empty dict)</span>
-<span class="go">OutEdgeDataView([(0, 1, {}), (1, 2, {}), (2, 3, {'weight': 5})])</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">edges</span><span class="o">.</span><span class="n">data</span><span class="p">(</span><span class="s1">'weight'</span><span class="p">,</span> <span class="n">default</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
-<span class="go">OutEdgeDataView([(0, 1, 1), (1, 2, 1), (2, 3, 5)])</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">edges</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="mi">2</span><span class="p">])</span> <span class="c1"># only edges incident to these nodes</span>
-<span class="go">OutEdgeDataView([(0, 1), (2, 3)])</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">edges</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span> <span class="c1"># only edges incident to a single node (use G.adj[0]?)</span>
-<span class="go">OutEdgeDataView([(0, 1)])</span>
-</pre></div>
-</div>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.plot_adjacency_matrix">
-<code class="descname">plot_adjacency_matrix</code><span class="sig-paren">(</span><em>fig_num=1</em>, <em>fig_size=(7</em>, <em>7)</em>, <em>show_now=True</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.plot_adjacency_matrix" title="Permalink to this definition">¶</a></dt>
-<dd><p>Draw the adjacency matrix in a plot window.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
-<li><strong>fig_num</strong> – figure number</li>
-<li><strong>fig_size</strong> – figure size</li>
-<li><strong>show_now</strong> – Boolean whether to plot directly (pausing the execution until the plot is closed), or not.</li>
-</ul>
-</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.plot_graph">
-<code class="descname">plot_graph</code><span class="sig-paren">(</span><em>fig_num=1</em>, <em>color_setting='default'</em>, <em>positioning='circular'</em>, <em>save_as=None</em>, <em>show_now=True</em>, <em>title=None</em>, <em>edge_label=False</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.plot_graph" title="Permalink to this definition">¶</a></dt>
-<dd><p>Function to plot a graph.</p>
-<p>Note that you need to add matplotlib.pyplot.show() at the end of your code to see the plot window.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
-<li><strong>fig_num</strong> – figure number</li>
-<li><strong>fig_size</strong> – size of figure window</li>
-<li><strong>color_setting</strong> – choose from ‘default’, ‘sinks’, ‘categories’, ‘partitions’</li>
-<li><strong>positioning</strong> – choose from ‘circular’, ‘spring’</li>
-<li><strong>save_as</strong> – save plot as figure file</li>
-<li><strong>show_now</strong> – Boolean whether to plot directly (pausing the execution until the plot is closed), or not.</li>
-<li><strong>title</strong> – title string of the graph</li>
-<li><strong>edge_label</strong> – edge attribute that will be shown for each edge in graph</li>
-</ul>
-</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">window with plot</p>
-</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="attribute">
-<dt id="kadmos.graph.graph_data.DataGraph.pred">
-<code class="descname">pred</code><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.pred" title="Permalink to this definition">¶</a></dt>
-<dd><p>Graph adjacency object holding the predecessors of each node.</p>
-<p>This object is a read-only dict-like structure with node keys
-and neighbor-dict values. The neighbor-dict is keyed by neighbor
-to the edge-data-dict. So <cite>G.pred[2][3][‘color’] = ‘blue’</cite> sets
-the color of the edge <cite>(3, 2)</cite> to <cite>“blueâ€</cite>.</p>
-<p>Iterating over G.pred behaves like a dict. Useful idioms include
-<cite>for nbr, datadict in G.pred[n].items():</cite>. A data-view not provided
-by dicts also exists: <cite>for nbr, foovalue in G.pred[node].data(‘foo’):</cite>
-A default can be set via a <cite>default</cite> argument to the <cite>data</cite> method.</p>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.predecessors">
-<code class="descname">predecessors</code><span class="sig-paren">(</span><em>n</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.predecessors" title="Permalink to this definition">¶</a></dt>
-<dd><p>Return an iterator over predecessor nodes of n.</p>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.print_graph">
-<code class="descname">print_graph</code><span class="sig-paren">(</span><em>use_pretty_print=False</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.print_graph" title="Permalink to this definition">¶</a></dt>
-<dd><p>Function to print the full graph.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>use_pretty_print</strong> (<em>bool</em>) – Boolean on whether to use pretty print for node and edge attributes</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.relabel_function_nodes">
-<code class="descname">relabel_function_nodes</code><span class="sig-paren">(</span><em>mapping=None</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.relabel_function_nodes" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to relabel all function nodes so that they meet the minimum CMDOWS convention</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>mapping</strong> (<em>None</em><em>, </em><em>True</em>) – application of mapping required, optional (default=None)</td>
-</tr>
-</tbody>
-</table>
-<p>CMDOWS convention:</p>
-<ul class="simple">
-<li>Minimum information: ID</li>
-<li>Maximum information: ID[modeID][instanceID][version]</li>
-</ul>
-<p>Note: modeID, instanceID and version are only provided if there is a function with the same ID that requires
-this specification to differentiate between the functions.</p>
-<p>Example:</p>
-<p>Design competences (full information):</p>
-<ul class="simple">
-<li>Aerodynamics[A][1][v1]</li>
-<li>Aerodynamics[A][2][v1]</li>
-<li>Aerodynamics[B][1][v1]</li>
-<li>Structures[A][1][v1]</li>
-<li>Structures[A}[1][v2]</li>
-<li>Propulsion[A][1][v2]</li>
-</ul>
-<p>Design competences relabeled:</p>
-<ul class="simple">
-<li>Aerodynamics[A][1]</li>
-<li>Aerodynamics[A][2]</li>
-<li>Aerodynamics[B][1]</li>
-<li>Structure[v1]</li>
-<li>Structure[v2]</li>
-<li>Propulsion</li>
-</ul>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.remove_edge">
-<code class="descname">remove_edge</code><span class="sig-paren">(</span><em>u</em>, <em>v</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.remove_edge" title="Permalink to this definition">¶</a></dt>
-<dd><p>Remove the edge between u and v.</p>
-<dl class="docutils">
-<dt>u, v <span class="classifier-delimiter">:</span> <span class="classifier">nodes</span></dt>
-<dd>Remove the edge between nodes u and v.</dd>
-</dl>
-<dl class="docutils">
-<dt>NetworkXError</dt>
-<dd>If there is not an edge between u and v.</dd>
-</dl>
-<p>remove_edges_from : remove a collection of edges</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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="c1"># or DiGraph, etc</span>
-<span class="gp">>>> </span><span class="n">nx</span><span class="o">.</span><span class="n">add_path</span><span class="p">(</span><span class="n">G</span><span class="p">,</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">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">])</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">remove_edge</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="gp">>>> </span><span class="n">e</span> <span class="o">=</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="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">remove_edge</span><span class="p">(</span><span class="o">*</span><span class="n">e</span><span class="p">)</span> <span class="c1"># unpacks e from an edge tuple</span>
-<span class="gp">>>> </span><span class="n">e</span> <span class="o">=</span> <span class="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="p">{</span><span class="s1">'weight'</span><span class="p">:</span><span class="mi">7</span><span class="p">})</span> <span class="c1"># an edge with attribute data</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">remove_edge</span><span class="p">(</span><span class="o">*</span><span class="n">e</span><span class="p">[:</span><span class="mi">2</span><span class="p">])</span> <span class="c1"># select first part of edge tuple</span>
-</pre></div>
-</div>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.remove_edges_from">
-<code class="descname">remove_edges_from</code><span class="sig-paren">(</span><em>ebunch</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.remove_edges_from" title="Permalink to this definition">¶</a></dt>
-<dd><p>Remove all edges specified in ebunch.</p>
-<dl class="docutils">
-<dt>ebunch: list or container of edge tuples</dt>
-<dd><p class="first">Each edge given in the list or container will be removed
-from the graph. The edges can be:</p>
-<blockquote class="last">
-<div><ul class="simple">
-<li>2-tuples (u, v) edge between u and v.</li>
-<li>3-tuples (u, v, k) where k is ignored.</li>
-</ul>
-</div></blockquote>
-</dd>
-</dl>
-<p>remove_edge : remove a single edge</p>
-<p>Will fail silently if an edge in ebunch is not in the graph.</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">path_graph</span><span class="p">(</span><span class="mi">4</span><span class="p">)</span> <span class="c1"># or DiGraph, MultiGraph, MultiDiGraph, etc</span>
-<span class="gp">>>> </span><span class="n">ebunch</span> <span class="o">=</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="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">)]</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">remove_edges_from</span><span class="p">(</span><span class="n">ebunch</span><span class="p">)</span>
-</pre></div>
-</div>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.remove_function_nodes">
-<code class="descname">remove_function_nodes</code><span class="sig-paren">(</span><em>*args</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.remove_function_nodes" title="Permalink to this definition">¶</a></dt>
-<dd><p>Function that removes a function node</p>
-<p>Also the input and output variables that only have links to this specific function node are deleted. A simple
-remove_node of a function node might lead to unconnected variables in the graph.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>args</strong> (<em>str</em><em> or </em><em>list</em>) – function node id(s)</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.remove_node">
-<code class="descname">remove_node</code><span class="sig-paren">(</span><em>n</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.remove_node" title="Permalink to this definition">¶</a></dt>
-<dd><p>Remove node n.</p>
-<p>Removes the node n and all adjacent edges.
-Attempting to remove a non-existent node will raise an exception.</p>
-<dl class="docutils">
-<dt>n <span class="classifier-delimiter">:</span> <span class="classifier">node</span></dt>
-<dd>A node in the graph</dd>
-</dl>
-<dl class="docutils">
-<dt>NetworkXError</dt>
-<dd>If n is not in the graph.</dd>
-</dl>
-<p>remove_nodes_from</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">path_graph</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span> <span class="c1"># or DiGraph, MultiGraph, MultiDiGraph, etc</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">edges</span><span class="p">)</span>
-<span class="go">[(0, 1), (1, 2)]</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">remove_node</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">edges</span><span class="p">)</span>
-<span class="go">[]</span>
-</pre></div>
-</div>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.remove_nodes_from">
-<code class="descname">remove_nodes_from</code><span class="sig-paren">(</span><em>nodes</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.remove_nodes_from" title="Permalink to this definition">¶</a></dt>
-<dd><p>Remove multiple nodes.</p>
-<dl class="docutils">
-<dt>nodes <span class="classifier-delimiter">:</span> <span class="classifier">iterable container</span></dt>
-<dd>A container of nodes (list, dict, set, etc.). If a node
-in the container is not in the graph it is silently ignored.</dd>
-</dl>
-<p>remove_node</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">path_graph</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span> <span class="c1"># or DiGraph, MultiGraph, MultiDiGraph, etc</span>
-<span class="gp">>>> </span><span class="n">e</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="n">e</span>
-<span class="go">[0, 1, 2]</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">remove_nodes_from</span><span class="p">(</span><span class="n">e</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">)</span>
-<span class="go">[]</span>
-</pre></div>
-</div>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.remove_unused_outputs">
-<code class="descname">remove_unused_outputs</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.remove_unused_outputs" title="Permalink to this definition">¶</a></dt>
-<dd><p>Function to remove output nodes from an FPG which do not have a problem role.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">the nodes that were removed</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Return type:</th><td class="field-body">list</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.reverse">
-<code class="descname">reverse</code><span class="sig-paren">(</span><em>copy=True</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.reverse" title="Permalink to this definition">¶</a></dt>
-<dd><p>Return the reverse of the graph.</p>
-<p>The reverse is a graph with the same nodes and edges
-but with the directions of the edges reversed.</p>
-<dl class="docutils">
-<dt>copy <span class="classifier-delimiter">:</span> <span class="classifier">bool optional (default=True)</span></dt>
-<dd>If True, return a new DiGraph holding the reversed edges.
-If False, the reverse graph is created using a view of
-the original graph.</dd>
-</dl>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.save">
-<code class="descname">save</code><span class="sig-paren">(</span><em>file_name</em>, <em>file_type='kdms'</em>, <em>graph_check_critical=True</em>, <em>destination_folder=None</em>, <em>mpg=None</em>, <em>description=''</em>, <em>creator=''</em>, <em>version='1.0'</em>, <em>timestamp=datetime.datetime(2018</em>, <em>3</em>, <em>31</em>, <em>17</em>, <em>25</em>, <em>15</em>, <em>655000)</em>, <em>keep_empty_elements=False</em>, <em>pretty_print=False</em>, <em>convention=True</em>, <em>integrity=False</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.save" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to save the graph.</p>
-<p>Different output file types are implemented for saving graphs. They are listed below:</p>
-<ul class="simple">
-<li>kdms: the most simple file type which makes use of pickling</li>
-<li>cmdows: the most versatile file type especially suited for file exchange with other tools</li>
-<li>graphml: another file type especially suited for file exchange with other tools based on graphs</li>
-</ul>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
-<li><strong>file_name</strong> (<em>str</em>) – name of the file to be saved</li>
-<li><strong>file_type</strong> (<em>str</em>) – file_type</li>
-<li><strong>graph_check_critical</strong> (<em>bool</em>) – option for raising errors in case of an invalid graph</li>
-<li><strong>destination_folder</strong> (<em>str</em>) – destination folder for the file to be saved</li>
-<li><strong>mpg</strong> (<a class="reference internal" href="#kadmos.graph.graph_process.MdaoProcessGraph" title="kadmos.graph.graph_process.MdaoProcessGraph"><em>MdaoProcessGraph</em></a>) – optional MPG graph to be saved with MDG</li>
-<li><strong>description</strong> (<em>str</em>) – description of the file (only applicable for the cmdows file type)</li>
-<li><strong>creator</strong> (<em>str</em>) – name of the creator of the file (only applicable for the cmdows file type)</li>
-<li><strong>version</strong> (<em>str | float | int</em>) – version of the file (only applicable for the cmdows file type)</li>
-<li><strong>timestamp</strong> (<em>datetime</em>) – timestamp to be saved in the file (only applicable for the cmdows file type)</li>
-<li><strong>keep_empty_elements</strong> (<em>bool</em>) – option for keeping empty XML elements (only applicable for the cmdows file type)</li>
-<li><strong>pretty_print</strong> (<em>bool</em>) – option for pretty XML printing (only applicable for the cmdows file type)</li>
-<li><strong>convention</strong> (<em>bool</em>) – option for appyling a UID convention (only applicable for the cmdows file type)</li>
-<li><strong>integrity</strong> (<em>bool</em>) – option for doing an integrity file check (only applicable for the cmdows file type)</li>
-</ul>
-</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.select_objectives_from_graph">
-<code class="descname">select_objectives_from_graph</code><span class="sig-paren">(</span><em>*args</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.select_objectives_from_graph" title="Permalink to this definition">¶</a></dt>
-<dd><p>This functions lets the user select one or more objective functions from the graph.</p>
-<p>Only functions can be selected as objectives. If no arguments are provided, user is prompted to select an
-objective from all functions in graph.</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Param:</th><td class="field-body">args: objective functions to choose from</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">list of objective functions</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.size">
-<code class="descname">size</code><span class="sig-paren">(</span><em>weight=None</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.size" title="Permalink to this definition">¶</a></dt>
-<dd><p>Return the number of edges or total of all edge weights.</p>
-<dl class="docutils">
-<dt>weight <span class="classifier-delimiter">:</span> <span class="classifier">string or None, optional (default=None)</span></dt>
-<dd>The edge attribute that holds the numerical value used
-as a weight. If None, then each edge has weight 1.</dd>
-</dl>
-<dl class="docutils">
-<dt>size <span class="classifier-delimiter">:</span> <span class="classifier">numeric</span></dt>
-<dd><p class="first">The number of edges or
-(if weight keyword is provided) the total weight sum.</p>
-<p class="last">If weight is None, returns an int. Otherwise a float
-(or more general numeric if the weights are more general).</p>
-</dd>
-</dl>
-<p>number_of_edges</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">path_graph</span><span class="p">(</span><span class="mi">4</span><span class="p">)</span> <span class="c1"># or DiGraph, MultiGraph, MultiDiGraph, etc</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">size</span><span class="p">()</span>
-<span class="go">3</span>
-</pre></div>
-</div>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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="c1"># or DiGraph, MultiGraph, MultiDiGraph, etc</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="s1">'a'</span><span class="p">,</span> <span class="s1">'b'</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="mi">2</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="s1">'b'</span><span class="p">,</span> <span class="s1">'c'</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="mi">4</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">size</span><span class="p">()</span>
-<span class="go">2</span>
-<span class="gp">>>> </span><span class="n">G</span><span class="o">.</span><span class="n">size</span><span class="p">(</span><span class="n">weight</span><span class="o">=</span><span class="s1">'weight'</span><span class="p">)</span>
-<span class="go">6.0</span>
-</pre></div>
-</div>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.sort_non_coupled_nodes">
-<code class="descname">sort_non_coupled_nodes</code><span class="sig-paren">(</span><em>nodes</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.sort_non_coupled_nodes" title="Permalink to this definition">¶</a></dt>
-<dd><p>Function to sort the pre and post coupling nodes</p>
-<table class="docutils field-list" frame="void" rules="none">
-<col class="field-name" />
-<col class="field-body" />
-<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>nodes</strong> (<em>list</em>) – nodes that need to be sorted</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">nodes in sorted order</td>
-</tr>
-<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body">list</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.split_variables">
-<code class="descname">split_variables</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.split_variables" title="Permalink to this definition">¶</a></dt>
-<dd><p>Method to split a problematic variable node into multiple separate valid nodes.</p>
-<p>The following variables are considered problematic and will be handled by this function:</p>
-<blockquote>
-<div><ul>
-<li><p class="first">pure circular coupling</p>
-</li>
-<li><p class="first">shared circular coupling</p>
-</li>
-<li><p class="first">collided coupling</p>
-</li>
-<li><p class="first">collision</p>
-</li>
-<li><p class="first">collided circular coupling</p>
-</li>
-<li><p class="first">collided shared coupling</p>
-</li>
-<li><p class="first">collided shared circular coupling</p>
-<blockquote>
-<div><p>The following table shows an example situation for each of the different problematic variables:</p>
-</div></blockquote>
-</li>
-</ul>
-</div></blockquote>
-<table border="1" class="docutils">
-<colgroup>
-<col width="22%" />
-<col width="24%" />
-<col width="16%" />
-<col width="39%" />
-</colgroup>
-<thead valign="bottom">
-<tr class="row-odd"><th class="head">PROBLEMATIC VARIABLE</th>
-<th class="head">SITUATION</th>
-<th class="head">FUNCTION ORDER</th>
-<th class="head">RESOLVED AS</th>
-</tr>
-</thead>
-<tbody valign="top">
-<tr class="row-even"><td>pure circular
-coupling</td>
-<td>x1 <=> F1</td>
-<td>n.a.</td>
-<td>x1/variableInstance1 => F1 =>
-x1/variableInstance2</td>
-</tr>
-<tr class="row-odd"><td>shared circular
-coupling</td>
-<td>F1 <=> x1 => F2, F3</td>
-<td>n.a.</td>
-<td><dl class="first last docutils">
-<dt>x1/variableInstance1 => F1 =></dt>
-<dd>x1/variableInstance2 => F2, F3, etc.</dd>
-</dl>
-</td>
-</tr>
-<tr class="row-even"><td rowspan="2">collided (shared)
-coupling</td>
-<td rowspan="2">F1, F3 => x1 => F2, F4</td>
-<td rowspan="2">F1, F2, F3, F4</td>
-<td>F1 => x1/variableInstance1 => F2</td>
-</tr>
-<tr class="row-odd"><td>F3 => x1/variableInstance2 => F4</td>
-</tr>
-<tr class="row-even"><td rowspan="2">collision</td>
-<td rowspan="2">F1, F2 => x1</td>
-<td rowspan="2">F1, F2</td>
-<td>F1 => x1/variableInstance1</td>
-</tr>
-<tr class="row-odd"><td>F2 => x1/variableInstance2</td>
-</tr>
-<tr class="row-even"><td rowspan="3">collided circular
-coupling</td>
-<td rowspan="3">F1 <=> x1 <= F2, F3</td>
-<td rowspan="3">n.a.</td>
-<td>x1/variableInstance1 => F1 =>
-x1/variableInstance2</td>
-</tr>
-<tr class="row-odd"><td>F2 => x1/variableInstance3</td>
-</tr>
-<tr class="row-even"><td>F3 => x1/variableInstance4</td>
-</tr>
-<tr class="row-odd"><td rowspan="4">collided shared
-circular coupling</td>
-<td rowspan="4">F3, F5 <=> x1 <= F2
-x1 => F1, F4, F6</td>
-<td rowspan="4">F1, F2, F3, F4,
-F5, F6</td>
-<td>x1/variableInstance1 => F2 => (..)</td>
-</tr>
-<tr class="row-even"><td>x1/variableInstance2 => F1, F3 => (..)</td>
-</tr>
-<tr class="row-odd"><td>x1/variableInstance3 => F4, F5 => (..)</td>
+<col class="field-name" />
+<col class="field-body" />
+<tbody valign="top">
+<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
+<li><strong>node</strong> (<em>basestring</em>) – variable node</li>
+<li><strong>remove_unused_outputs</strong> (<em>bool</em>) – option to remove unused outputs</li>
+</ul>
+</td>
</tr>
-<tr class="row-even"><td>x1/variableInstance4 => F6</td>
+<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">graph enriched with objective node</p>
+</td>
</tr>
</tbody>
</table>
+</dd></dl>
+
+<dl class="method">
+<dt id="kadmos.graph.graph_data.DataGraph.mark_as_qois">
+<code class="descname">mark_as_qois</code><span class="sig-paren">(</span><em>nodes</em>, <em>remove_unused_outputs=False</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.mark_as_qois" title="Permalink to this definition">¶</a></dt>
+<dd><p>Function to mark a list of nodes as quantity of interest.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>args</strong> (<em>basestring</em><em>, </em><em>list</em>) – problematic node in the graph</td>
+<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
+<li><strong>nodes</strong> (<em>list</em>) – list of nodes present in the graph</li>
+<li><strong>remove_unused_outputs</strong> (<em>bool</em>) – option to remove unused outputs</li>
+</ul>
+</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.subgraph">
-<code class="descname">subgraph</code><span class="sig-paren">(</span><em>nodes</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.subgraph" title="Permalink to this definition">¶</a></dt>
-<dd><p>Return a SubGraph view of the subgraph induced on <cite>nodes</cite>.</p>
-<p>The induced subgraph of the graph contains the nodes in <cite>nodes</cite>
-and the edges between those nodes.</p>
-<dl class="docutils">
-<dt>nodes <span class="classifier-delimiter">:</span> <span class="classifier">list, iterable</span></dt>
-<dd>A container of nodes which will be iterated through once.</dd>
-</dl>
-<dl class="docutils">
-<dt>G <span class="classifier-delimiter">:</span> <span class="classifier">SubGraph View</span></dt>
-<dd>A subgraph view of the graph. The graph structure cannot be
-changed but node/edge attributes can and are shared with the
-original graph.</dd>
-</dl>
-<p>The graph, edge and node attributes are shared with the original graph.
-Changes to the graph structure is ruled out by the view, but changes
-to attributes are reflected in the original graph.</p>
-<p>To create a subgraph with its own copy of the edge/node attributes use:
-G.subgraph(nodes).copy()</p>
-<p>For an inplace reduction of a graph to a subgraph you can remove nodes:
-G.remove_nodes_from([n for n in G if n not in set(nodes)])</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">path_graph</span><span class="p">(</span><span class="mi">4</span><span class="p">)</span> <span class="c1"># or DiGraph, MultiGraph, MultiDiGraph, etc</span>
-<span class="gp">>>> </span><span class="n">H</span> <span class="o">=</span> <span class="n">G</span><span class="o">.</span><span class="n">subgraph</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">2</span><span class="p">])</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">H</span><span class="o">.</span><span class="n">edges</span><span class="p">)</span>
-<span class="go">[(0, 1), (1, 2)]</span>
-</pre></div>
-</div>
-</dd></dl>
-
-<dl class="attribute">
-<dt id="kadmos.graph.graph_data.DataGraph.succ">
-<code class="descname">succ</code><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.succ" title="Permalink to this definition">¶</a></dt>
-<dd><p>Graph adjacency object holding the successors of each node.</p>
-<p>This object is a read-only dict-like structure with node keys
-and neighbor-dict values. The neighbor-dict is keyed by neighbor
-to the edge-data-dict. So <cite>G.succ[3][2][‘color’] = ‘blue’</cite> sets
-the color of the edge <cite>(3, 2)</cite> to <cite>“blueâ€</cite>.</p>
-<p>Iterating over G.succ behaves like a dict. Useful idioms include
-<cite>for nbr, datadict in G.succ[n].items():</cite>. A data-view not provided
-by dicts also exists: <cite>for nbr, foovalue in G.succ[node].data(‘foo’):</cite>
-and a default can be set via a <cite>default</cite> argument to the <cite>data</cite> method.</p>
-<p>The neighbor information is also provided by subscripting the graph.
-So <cite>for nbr, foovalue in G[node].data(‘foo’, default=1):</cite> works.</p>
-<p>For directed graphs, <cite>G.adj</cite> is identical to <cite>G.succ</cite>.</p>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.successors">
-<code class="descname">successors</code><span class="sig-paren">(</span><em>n</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.successors" title="Permalink to this definition">¶</a></dt>
-<dd><p>Return an iterator over successor nodes of n.</p>
-<p>neighbors() and successors() are the same.</p>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.to_directed">
-<code class="descname">to_directed</code><span class="sig-paren">(</span><em>as_view=False</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.to_directed" title="Permalink to this definition">¶</a></dt>
-<dd><p>Return a directed representation of the graph.</p>
-<dl class="docutils">
-<dt>G <span class="classifier-delimiter">:</span> <span class="classifier">DiGraph</span></dt>
-<dd>A directed graph with the same name, same nodes, and with
-each edge (u, v, data) replaced by two directed edges
-(u, v, data) and (v, u, data).</dd>
-</dl>
-<p>This returns a “deepcopy†of the edge, node, and
-graph attributes which attempts to completely copy
-all of the data and references.</p>
-<p>This is in contrast to the similar D=DiGraph(G) which returns a
-shallow copy of the data.</p>
-<p>See the Python copy module for more information on shallow
-and deep copies, <a class="reference external" href="https://docs.python.org/2/library/copy.html">https://docs.python.org/2/library/copy.html</a>.</p>
-<p>Warning: If you have subclassed Graph to use dict-like objects
-in the data structure, those changes do not transfer to the
-DiGraph created by this method.</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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="c1"># or MultiGraph, etc</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="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="n">H</span> <span class="o">=</span> <span class="n">G</span><span class="o">.</span><span class="n">to_directed</span><span class="p">()</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">H</span><span class="o">.</span><span class="n">edges</span><span class="p">)</span>
-<span class="go">[(0, 1), (1, 0)]</span>
-</pre></div>
-</div>
-<p>If already directed, return a (deep) copy</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">DiGraph</span><span class="p">()</span> <span class="c1"># or MultiDiGraph, etc</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="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="n">H</span> <span class="o">=</span> <span class="n">G</span><span class="o">.</span><span class="n">to_directed</span><span class="p">()</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">H</span><span class="o">.</span><span class="n">edges</span><span class="p">)</span>
-<span class="go">[(0, 1)]</span>
-</pre></div>
-</div>
-</dd></dl>
-
-<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.to_undirected">
-<code class="descname">to_undirected</code><span class="sig-paren">(</span><em>reciprocal=False</em>, <em>as_view=False</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.to_undirected" title="Permalink to this definition">¶</a></dt>
-<dd><p>Return an undirected representation of the digraph.</p>
-<dl class="docutils">
-<dt>reciprocal <span class="classifier-delimiter">:</span> <span class="classifier">bool (optional)</span></dt>
-<dd>If True only keep edges that appear in both directions
-in the original digraph.</dd>
-<dt>as_view <span class="classifier-delimiter">:</span> <span class="classifier">bool (optional, default=False)</span></dt>
-<dd>If True return an undirected view of the original directed graph.</dd>
-</dl>
-<dl class="docutils">
-<dt>G <span class="classifier-delimiter">:</span> <span class="classifier">Graph</span></dt>
-<dd>An undirected graph with the same name and nodes and
-with edge (u, v, data) if either (u, v, data) or (v, u, data)
-is in the digraph. If both edges exist in digraph and
-their edge data is different, only one edge is created
-with an arbitrary choice of which edge data to use.
-You must check and correct for this manually if desired.</dd>
-</dl>
-<p>Graph, copy, add_edge, add_edges_from</p>
-<p>If edges in both directions (u, v) and (v, u) exist in the
-graph, attributes for the new undirected edge will be a combination of
-the attributes of the directed edges. The edge data is updated
-in the (arbitrary) order that the edges are encountered. For
-more customized control of the edge attributes use add_edge().</p>
-<p>This returns a “deepcopy†of the edge, node, and
-graph attributes which attempts to completely copy
-all of the data and references.</p>
-<p>This is in contrast to the similar G=DiGraph(D) which returns a
-shallow copy of the data.</p>
-<p>See the Python copy module for more information on shallow
-and deep copies, <a class="reference external" href="https://docs.python.org/2/library/copy.html">https://docs.python.org/2/library/copy.html</a>.</p>
-<p>Warning: If you have subclassed DiGraph to use dict-like objects
-in the data structure, those changes do not transfer to the
-Graph created by this method.</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></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">path_graph</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span> <span class="c1"># or MultiGraph, etc</span>
-<span class="gp">>>> </span><span class="n">H</span> <span class="o">=</span> <span class="n">G</span><span class="o">.</span><span class="n">to_directed</span><span class="p">()</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">H</span><span class="o">.</span><span class="n">edges</span><span class="p">)</span>
-<span class="go">[(0, 1), (1, 0)]</span>
-<span class="gp">>>> </span><span class="n">G2</span> <span class="o">=</span> <span class="n">H</span><span class="o">.</span><span class="n">to_undirected</span><span class="p">()</span>
-<span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">G2</span><span class="o">.</span><span class="n">edges</span><span class="p">)</span>
-<span class="go">[(0, 1)]</span>
-</pre></div>
-</div>
+<dt id="kadmos.graph.graph_data.DataGraph.minimize_feedback">
+<code class="descname">minimize_feedback</code><span class="sig-paren">(</span><em>nodes</em>, <em>method</em>, <em>multi_start=None</em>, <em>get_evaluations=False</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.minimize_feedback" title="Permalink to this definition">¶</a></dt>
+<dd><p>Function to find the function order with minimum feedback</p>
+<table class="docutils field-list" frame="void" rules="none">
+<col class="field-name" />
+<col class="field-body" />
+<tbody valign="top">
+<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
+<li><strong>nodes</strong> (<em>list</em>) – nodes for which the feedback needs to be minimized</li>
+<li><strong>method</strong> (<em>str</em>) – algorithm used to find optimal function order</li>
+<li><strong>multi_start</strong> (<em>int</em>) – start the algorithm from multiple starting points</li>
+<li><strong>get_evaluations</strong> (<em>bool</em>) – option to give the number of evaluations as output</li>
+</ul>
+</td>
+</tr>
+<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">function order</p>
+</td>
+</tr>
+<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first">list</p>
+</td>
+</tr>
+<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">number of evaluations</p>
+</td>
+</tr>
+<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last">list</p>
+</td>
+</tr>
+</tbody>
+</table>
</dd></dl>
<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.unmark_variable">
-<code class="descname">unmark_variable</code><span class="sig-paren">(</span><em>node</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.unmark_variable" title="Permalink to this definition">¶</a></dt>
-<dd><p>Function to unmark any marked variable.</p>
+<dt id="kadmos.graph.graph_data.DataGraph.remove_unused_outputs">
+<code class="descname">remove_unused_outputs</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.remove_unused_outputs" title="Permalink to this definition">¶</a></dt>
+<dd><p>Function to remove output nodes from an FPG which do not have a problem role.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>node</strong> (<em>basestring</em>) – variable node to be unmarked</td>
+<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">the nodes that were removed</td>
+</tr>
+<tr class="field-even field"><th class="field-name">Return type:</th><td class="field-body">list</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.vistoms_add">
-<code class="descname">vistoms_add</code><span class="sig-paren">(</span><em>vistoms_dir</em>, <em>mpg=None</em>, <em>function_order=None</em>, <em>reference_file=None</em>, <em>compress=False</em>, <em>remove_after_compress=True</em>, <em>graph_id=None</em>, <em>replacement_id=None</em>, <em>xml_file=None</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.vistoms_add" title="Permalink to this definition">¶</a></dt>
-<dd><p>Function to add a graph to a existing VISTOMS instance.</p>
-<p>In one VISTOMS instance different graphs can be shown. For example it is possible to include different
-architectures for the same problem in one VISTOMS instance.</p>
+<dt id="kadmos.graph.graph_data.DataGraph.sort_nodes_for_process">
+<code class="descname">sort_nodes_for_process</code><span class="sig-paren">(</span><em>nodes</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.sort_nodes_for_process" title="Permalink to this definition">¶</a></dt>
+<dd><p>Method to sort function nodes such that the process order is optimized, while not increasing the number of
+feedback loops</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
-<li><strong>vistoms_dir</strong> (<em>str</em>) – directory of the VISTOMS directory to be used for addition</li>
-<li><strong>mpg</strong> (<a class="reference internal" href="#kadmos.graph.graph_process.MdaoProcessGraph" title="kadmos.graph.graph_process.MdaoProcessGraph"><em>MdaoProcessGraph</em></a>) – optional MPG graph to be saved with MDG as XDSM (if None a DSM is created)</li>
-<li><strong>function_order</strong> (<em>list</em>) – optional function order for the diagonal of the graph (only applicable for DSMs)</li>
-<li><strong>reference_file</strong> (<em>str</em>) – file from which reference values are extracted (either full path or file in same folder)</li>
-<li><strong>compress</strong> (<em>bool</em>) – setting whether to compress the final VISTOMS instance folder to a zip file</li>
-<li><strong>remove_after_compress</strong> (<em>bool</em>) – setting whether to remove the original folder after compression</li>
-<li><strong>replacement_id</strong> (<em>basestr</em>) – indentifier of the graph to be replaced</li>
-<li><strong>xml_file</strong> (<em>file</em>) – Name of the CMDOWS xml-file</li>
-</ul>
-</td>
+<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>nodes</strong> (<em>list</em>) – function nodes to sort</td>
+</tr>
+<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">nodes in sorted order</td>
+</tr>
+<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body">list</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
-<dt id="kadmos.graph.graph_data.DataGraph.vistoms_create">
-<code class="descname">vistoms_create</code><span class="sig-paren">(</span><em>vistoms_dir</em>, <em>vistoms_version=None</em>, <em>mpg=None</em>, <em>function_order=None</em>, <em>reference_file=None</em>, <em>compress=False</em>, <em>remove_after_compress=True</em>, <em>graph_id=None</em>, <em>use_png_figs=False</em>, <em>file_refs=None</em>, <em>xml_file=None</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.vistoms_create" title="Permalink to this definition">¶</a></dt>
-<dd><p>Function to create a new VISTOMS instance from a graph.</p>
+<dt id="kadmos.graph.graph_data.DataGraph.unmark_variable">
+<code class="descname">unmark_variable</code><span class="sig-paren">(</span><em>node</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.DataGraph.unmark_variable" title="Permalink to this definition">¶</a></dt>
+<dd><p>Function to unmark any marked variable.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
-<li><strong>vistoms_dir</strong> (<em>str</em>) – directory of the VISTOMS directory to be created</li>
-<li><strong>vistoms_version</strong> – version of the VISTOMS instance to be used (as stored in the package itself)</li>
-<li><strong>vispack_version</strong> – str</li>
-<li><strong>mpg</strong> (<a class="reference internal" href="#kadmos.graph.graph_process.MdaoProcessGraph" title="kadmos.graph.graph_process.MdaoProcessGraph"><em>MdaoProcessGraph</em></a>) – optional MPG graph to be saved with MDG as XDSM (if None a DSM is created)</li>
-<li><strong>function_order</strong> (<em>list</em>) – optional function order for the diagonal of the graph (only applicable for DSMs)</li>
-<li><strong>reference_file</strong> (<em>str</em>) – file from which reference values are extracted (either full path or file in same folder)</li>
-<li><strong>compress</strong> (<em>bool</em>) – setting whether to compress the final VISTOMS instance folder to a zip file</li>
-<li><strong>remove_after_compress</strong> (<em>bool</em>) – setting whether to remove the original folder after compression</li>
-<li><strong>graph_id</strong> (<em>basestring</em>) – identifier of the new graph</li>
-<li><strong>use_png_figs</strong> (<em>bool</em>) – setting whether to use the PNG figures instead of the SVG figures for local execution</li>
-<li><strong>file_refs</strong> (<em>dict</em>) – setting to provide file references manually (to use VISTOMS on a server)</li>
-<li><strong>xml_file</strong> (<em>file</em>) – Name of the CMDOWS xml file</li>
-</ul>
-</td>
+<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>node</strong> (<em>basestring</em>) – variable node to be unmarked</td>
+</tr>
+<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">graph with unmarked node</td>
</tr>
</tbody>
</table>
@@ -6749,13 +2392,13 @@ Complexity Problem’, Mathematical Problems in Engineering, 2017.</p>
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
-<li><strong>n_disciplines</strong> – Number of disciplines</li>
-<li><strong>coupling_strength</strong> – percentage of couplings, 0 no couplings, 1 all possible couplings</li>
-<li><strong>n_global_var</strong> – Number of global design variables</li>
-<li><strong>n_local_var</strong> – Number of local design variables for each discipline</li>
-<li><strong>n_coupling_var</strong> – Number of output variables for each discipline</li>
-<li><strong>n_local_constraints</strong> – Number of local constraints</li>
-<li><strong>n_global_constraints</strong> – Number of global constraints</li>
+<li><strong>n_disciplines</strong> (<em>int</em>) – Number of disciplines</li>
+<li><strong>coupling_strength</strong> (<em>int</em>) – percentage of couplings, 0 no couplings, 1 all possible couplings</li>
+<li><strong>n_global_var</strong> (<em>int</em>) – Number of global design variables</li>
+<li><strong>n_local_var</strong> (<em>int</em>) – Number of local design variables for each discipline</li>
+<li><strong>n_coupling_var</strong> (<em>int</em>) – Number of output variables for each discipline</li>
+<li><strong>n_local_constraints</strong> (<em>int</em>) – Number of local constraints</li>
+<li><strong>n_global_constraints</strong> (<em>int</em>) – Number of global constraints</li>
<li><strong>B</strong> – relation between the coupling variables</li>
<li><strong>C</strong> – relation between the global design variables and coupling variables</li>
<li><strong>D</strong> – relation between the local design variables and coupling variables</li>
@@ -6765,9 +2408,9 @@ Complexity Problem’, Mathematical Problems in Engineering, 2017.</p>
<li><strong>H</strong> – relation between the global design variables and global constraints</li>
<li><strong>I</strong> – relation between the local design variables and global constraints</li>
<li><strong>J</strong> – relation between the coupling variables and global constraints</li>
-<li><strong>r</strong> – positive scalars to be used for the local constraints</li>
-<li><strong>s</strong> – positive scalars to be used for the global constraints</li>
-<li><strong>write_problem_to_textfile</strong> – option to write generated problem to a textfile</li>
+<li><strong>r</strong> (<em>float</em>) – positive scalars to be used for the local constraints</li>
+<li><strong>s</strong> (<em>float</em>) – positive scalars to be used for the global constraints</li>
+<li><strong>write_problem_to_textfile</strong> (<em>bool</em>) – option to write generated problem to a textfile</li>
</ul>
</td>
</tr>
@@ -6855,9 +2498,11 @@ Complexity Problem’, Mathematical Problems in Engineering, 2017.</p>
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">new fpg graph</td>
+<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>args</strong> (<em>list</em><em>, </em><em>str</em>) – arbitrary amount of graph nodes</td>
</tr>
-<tr class="field-even field"><th class="field-name">Return type:</th><td class="field-body"><a class="reference internal" href="#kadmos.graph.graph_data.FundamentalProblemGraph" title="kadmos.graph.graph_data.FundamentalProblemGraph">FundamentalProblemGraph</a></td>
+<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">new fpg graph</td>
+</tr>
+<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><a class="reference internal" href="#kadmos.graph.graph_data.FundamentalProblemGraph" title="kadmos.graph.graph_data.FundamentalProblemGraph">FundamentalProblemGraph</a></td>
</tr>
</tbody>
</table>
@@ -6868,22 +2513,13 @@ Complexity Problem’, Mathematical Problems in Engineering, 2017.</p>
<code class="descname">get_function_paths_by_objective</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.RepositoryConnectivityGraph.get_function_paths_by_objective" title="Permalink to this definition">¶</a></dt>
<dd><p>This function takes an arbitrary amount of objective nodes as graph sinks and returns all path combinations
of tools.</p>
-<p>If no arguments are given, user is prompted to select objectives from the graph.</p>
-<p>The tool combinations are found using the function itertools.product() and can lead to significant computation
-times for large graphs. If this is the case, the user is prompted whether to continue or not.</p>
-<p>A variety of filters can be applied to the search of possible tools combinations, some of which reduce the
-computation time.</p>
-<p>kwargs:
-obj_vars_covered - ensures that all objective variables are used in tool configurations
-ignore_funcs - ignores functions for the config
-source - source node; if provided, must be in config</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
-<li><strong>args</strong> – arbitrary amount of objective nodes</li>
-<li><strong>kwargs</strong> – filter options to limit possible path combinations</li>
+<li><strong>args</strong> (<em>list</em><em>, </em><em>str</em>) – arbitrary amount of objective nodes</li>
+<li><strong>kwargs</strong> (<em>bool</em><em>, </em><em>str</em>) – filter options to limit possible path combinations</li>
</ul>
</td>
</tr>
@@ -6892,38 +2528,92 @@ source - source node; if provided, must be in config</p>
</tr>
</tbody>
</table>
+<p>If no arguments are given, user is prompted to select objectives from the graph.</p>
+<div class="admonition hint">
+<p class="first admonition-title">Hint</p>
+<p class="last">The tool combinations are found using the function itertools.product() and can lead to significant
+computation times for large graphs. If this is the case, the user is prompted whether to continue or not.</p>
+</div>
+<p>A variety of filters can be applied to the search of possible tools combinations, some of which reduce the
+computation time.</p>
+<p>kwargs:</p>
+<ul class="simple">
+<li>obj_vars_covered - ensures that all objective variables are used in tool configurations</li>
+<li>ignore_funcs - ignores functions for the config</li>
+<li>source - source node; if provided, must be in config</li>
+</ul>
</dd></dl>
<dl class="method">
<dt id="kadmos.graph.graph_data.RepositoryConnectivityGraph.get_path_combinations">
<code class="descname">get_path_combinations</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.RepositoryConnectivityGraph.get_path_combinations" title="Permalink to this definition">¶</a></dt>
<dd><p>This function takes lists of subsets and generates all possible combinations between them.</p>
-<p>This is done by using the itertools.product() function. If the amount of expected evaluations exceeds a pre-set
-minimum, the user will be asked if to continue or not; because the process can take a long time and use up many
-resources.</p>
-<p>Optional arguments:
-min_func: minimum amount of functions in each configuration
-max_func: maximum amount of functions in each configuration</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>args</strong> (<em>list</em>) – lists of subsets that will be used to find configurations</td>
+<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
+<li><strong>args</strong> (<em>list</em>) – lists of subsets that will be used to find configurations</li>
+<li><strong>kwargs</strong> (<em>int</em>) – see optional arguments</li>
+</ul>
+</td>
</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">set of all unique path combinations</td>
+<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">set of all unique path combinations</p>
+</td>
</tr>
</tbody>
</table>
+<p>This is done by using the itertools.product() function. If the amount of expected evaluations exceeds a pre-set
+minimum, the user will be asked if to continue or not; because the process can take a long time and use up many
+resources.</p>
+<div class="admonition note">
+<p class="first admonition-title">Note</p>
+<p>Optional arguments:</p>
+<ul class="last simple">
+<li>min_func: minimum amount of functions in each configuration</li>
+<li>max_func: maximum amount of functions in each configuration</li>
+</ul>
+</div>
</dd></dl>
<dl class="method">
<dt id="kadmos.graph.graph_data.RepositoryConnectivityGraph.select_function_combination_from">
<code class="descname">select_function_combination_from</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.RepositoryConnectivityGraph.select_function_combination_from" title="Permalink to this definition">¶</a></dt>
<dd><p>This function takes all provided workflow configurations and lists them according to their characteristics.</p>
-<p>The user can then choose the workflow configuration from the list.
-A warning is given to the user if the amount of total configurations exceeds n = 1e4.
-Print limit is set to [0-20] by default.
-sort_by must be one of [“couplingsâ€, “system_inputsâ€, “edgesâ€, “nodesâ€].</p>
+<table class="docutils field-list" frame="void" rules="none">
+<col class="field-name" />
+<col class="field-body" />
+<tbody valign="top">
+<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
+<li><strong>args</strong> (<em>list</em>) – workflow configurations</li>
+<li><strong>kwargs</strong> (<em>bool</em><em>, </em><em>str</em><em>, </em><em>int</em>) – see optional arguments</li>
+</ul>
+</td>
+</tr>
+<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">sorted list of workflow configurations</p>
+</td>
+</tr>
+<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last">list</p>
+</td>
+</tr>
+</tbody>
+</table>
+<div class="admonition note">
+<p class="first admonition-title">Note</p>
+<p class="last">Optional arguments:
+* ‘print_combos’ - option to print the combinations in a table
+* ‘n_limit’ - amount of combinations that will be printed in the table
+* ‘sort_by’ - characteristic to sort workflow configurations by
+* ‘sort_by ascending’ - option to sort workflow configurations by ascension
+* ‘plot_combos’ - option to plot the combinations in a graph</p>
+</div>
+<p>The user can choose the workflow configuration from the list.</p>
+<p>A warning is given to the user if the amount of total configurations exceeds n = 1e4.
+Print limit is set to [0-20] by default.</p>
+<div class="admonition note">
+<p class="first admonition-title">Note</p>
+<p class="last">sort_by must be one of [“couplingsâ€, “system_inputsâ€, “edgesâ€, “nodesâ€].</p>
+</div>
</dd></dl>
</dd></dl>
@@ -6996,6 +2686,59 @@ sort_by must be one of [“couplingsâ€, “system_inputsâ€, “edgesâ€, “no
</table>
</dd></dl>
+<dl class="method">
+<dt id="kadmos.graph.graph_data.FundamentalProblemGraph.determine_scope_constraint_functions">
+<code class="descname">determine_scope_constraint_functions</code><span class="sig-paren">(</span><em>cnstrnt_vars=None</em>, <em>coupled_functions_groups=None</em>, <em>post_coupling_functions=None</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.FundamentalProblemGraph.determine_scope_constraint_functions" title="Permalink to this definition">¶</a></dt>
+<dd><p>Method to determine the scope (global, local) of the constraint functions based on the constraint variables
+and to determine on which coupled function groups the constraint function depends.</p>
+<table class="docutils field-list" frame="void" rules="none">
+<col class="field-name" />
+<col class="field-body" />
+<tbody valign="top">
+<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
+<li><strong>cnstrnt_vars</strong> (<em>list</em>) – (optional) constraint variables to be determined</li>
+<li><strong>coupled_functions_groups</strong> (<em>list</em>) – (optional) list of lists with coupled functions groups</li>
+<li><strong>post_coupling_functions</strong> (<em>list</em>) – (optional) list with post-coupling functions</li>
+</ul>
+</td>
+</tr>
+<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">global constraint variables and functions, local constraint variables and functions, groups indices
+per constraint function</p>
+</td>
+</tr>
+<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last">tuple</p>
+</td>
+</tr>
+</tbody>
+</table>
+</dd></dl>
+
+<dl class="method">
+<dt id="kadmos.graph.graph_data.FundamentalProblemGraph.determine_scope_design_variables">
+<code class="descname">determine_scope_design_variables</code><span class="sig-paren">(</span><em>des_vars=None</em>, <em>coupled_functions_groups=None</em>, <em>pre_coupling_functions=None</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.FundamentalProblemGraph.determine_scope_design_variables" title="Permalink to this definition">¶</a></dt>
+<dd><p>Method to determine the scope (global, local) of the design variables and to determine to which coupled function
+groups the design variable belongs.</p>
+<table class="docutils field-list" frame="void" rules="none">
+<col class="field-name" />
+<col class="field-body" />
+<tbody valign="top">
+<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
+<li><strong>des_vars</strong> (<em>list</em>) – list of design variables (if not given, it is taken from the graph)</li>
+<li><strong>coupled_functions_groups</strong> (<em>list</em>) – list with list of coupled function groups</li>
+<li><strong>pre_coupling_functions</strong> (<em>list</em>) – list with list of pre-coupled function groups</li>
+</ul>
+</td>
+</tr>
+<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">list of global design variables, list of local design variables, dictionary with dependencies</p>
+</td>
+</tr>
+<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last">tuple</p>
+</td>
+</tr>
+</tbody>
+</table>
+</dd></dl>
+
<dl class="method">
<dt id="kadmos.graph.graph_data.FundamentalProblemGraph.get_mdg">
<code class="descname">get_mdg</code><span class="sig-paren">(</span><em>name='MDG'</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.FundamentalProblemGraph.get_mdg" title="Permalink to this definition">¶</a></dt>
@@ -7033,23 +2776,46 @@ have to be divided in two parts: the first part does not use the design variabl
</dd></dl>
<dl class="method">
-<dt id="kadmos.graph.graph_data.FundamentalProblemGraph.get_mpg">
-<code class="descname">get_mpg</code><span class="sig-paren">(</span><em>name='MPG'</em>, <em>mdg=None</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.FundamentalProblemGraph.get_mpg" title="Permalink to this definition">¶</a></dt>
-<dd><p>Create the MDAO process graph for a given FPG.</p>
+<dt id="kadmos.graph.graph_data.FundamentalProblemGraph.get_objective_node">
+<code class="descname">get_objective_node</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.FundamentalProblemGraph.get_objective_node" title="Permalink to this definition">¶</a></dt>
+<dd><p>Method to get the single (or non-existent) objective node from a graph.</p>
+<table class="docutils field-list" frame="void" rules="none">
+<col class="field-name" />
+<col class="field-body" />
+<tbody valign="top">
+<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">objective node or None if no objective node is present</td>
+</tr>
+<tr class="field-even field"><th class="field-name">Return type:</th><td class="field-body">str, None</td>
+</tr>
+</tbody>
+</table>
+</dd></dl>
+
+<dl class="method">
+<dt id="kadmos.graph.graph_data.FundamentalProblemGraph.get_partition_info">
+<code class="descname">get_partition_info</code><span class="sig-paren">(</span><em>partitions</em>, <em>include_run_time=False</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.FundamentalProblemGraph.get_partition_info" title="Permalink to this definition">¶</a></dt>
+<dd><p>Function to get the number of feedback variables in the partitions and the number system variables (feedback
+and feedforward variables between partitions)</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
-<li><strong>name</strong> (<em>basestring</em>) – name of the new graph</li>
-<li><strong>mdg</strong> (<em>MdaoDataGraph</em>) – data graph to be used for process optimization</li>
+<li><strong>partitions</strong> (<em>dict</em>) – dictionary which indicates which nodes are in which partition</li>
+<li><strong>include_run_time</strong> (<em>bool</em>) – </li>
</ul>
</td>
</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">MDAO process graph</p>
+<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">partition_variables:</p>
</td>
</tr>
-<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last"><a class="reference internal" href="#kadmos.graph.graph_process.MdaoProcessGraph" title="kadmos.graph.graph_process.MdaoProcessGraph">MdaoProcessGraph</a></p>
+<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first">partition_variables: list of sets</p>
+</td>
+</tr>
+<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">system_variables:</p>
+</td>
+</tr>
+<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last">system_variables: set</p>
</td>
</tr>
</tbody>
@@ -7072,6 +2838,65 @@ have to be divided in two parts: the first part does not use the design variabl
</table>
</dd></dl>
+<dl class="method">
+<dt id="kadmos.graph.graph_data.FundamentalProblemGraph.partition_graph">
+<code class="descname">partition_graph</code><span class="sig-paren">(</span><em>n_parts</em>, <em>include_run_time=False</em>, <em>tpwgts=None</em>, <em>recursive=True</em>, <em>contig=False</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.FundamentalProblemGraph.partition_graph" title="Permalink to this definition">¶</a></dt>
+<dd><p>Partition a graph using the Metis algorithm (<a class="reference external" href="http://glaros.dtc.umn.edu/gkhome/metis/metis/overview">http://glaros.dtc.umn.edu/gkhome/metis/metis/overview</a>).</p>
+<p>Note that partitioning can only be performed on undirected graphs. Therefore every graph input is translated
+into an undirected graph.</p>
+<table class="docutils field-list" frame="void" rules="none">
+<col class="field-name" />
+<col class="field-body" />
+<tbody valign="top">
+<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
+<li><strong>n_parts</strong> (<em>int</em>) – number of partitions requested (algorithm might provide less)</li>
+<li><strong>include_run_time</strong> (<em>bool</em>) – </li>
+<li><strong>tpwgts</strong> (<em>list</em>) – list of target partition weights</li>
+<li><strong>recursive</strong> (<em>bool</em>) – option to use the recursive bisection or k-way partitioning algorithm</li>
+<li><strong>contig</strong> (<em>bool</em>) – Metis option</li>
+</ul>
+</td>
+</tr>
+</tbody>
+</table>
+</dd></dl>
+
+<dl class="method">
+<dt id="kadmos.graph.graph_data.FundamentalProblemGraph.select_distributed_architecture">
+<code class="descname">select_distributed_architecture</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.FundamentalProblemGraph.select_distributed_architecture" title="Permalink to this definition">¶</a></dt>
+<dd><p>Function for easy selection of a distributed architecture for a partitioned graph.</p>
+<table class="docutils field-list" frame="void" rules="none">
+<col class="field-name" />
+<col class="field-body" />
+<tbody valign="top">
+<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">Extended problem formulation</td>
+</tr>
+</tbody>
+</table>
+</dd></dl>
+
+<dl class="method">
+<dt id="kadmos.graph.graph_data.FundamentalProblemGraph.select_number_of_partitions">
+<code class="descname">select_number_of_partitions</code><span class="sig-paren">(</span><em>partition_range</em>, <em>include_run_time=False</em>, <em>plot_pareto_front=False</em><span class="sig-paren">)</span><a class="headerlink" href="#kadmos.graph.graph_data.FundamentalProblemGraph.select_number_of_partitions" title="Permalink to this definition">¶</a></dt>
+<dd><p>Function to evaluate the properties of different number of partitions and to select the best one.</p>
+<table class="docutils field-list" frame="void" rules="none">
+<col class="field-name" />
+<col class="field-body" />
+<tbody valign="top">
+<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
+<li><strong>partition_range</strong> (<em>list</em>) – range of number of partitions that need to be evaluated</li>
+<li><strong>include_run_time</strong> – </li>
+<li><strong>plot_pareto_front</strong> (<em>bool</em>) – Option to plot the characteristics of different number of partitions</li>
+</ul>
+</td>
+</tr>
+<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last"></p>
+</td>
+</tr>
+</tbody>
+</table>
+</dd></dl>
+
</dd></dl>
</div>
@@ -8463,7 +4288,7 @@ items that are not present in the given dictionary. All keys of the dictionary s
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
<li><strong>print_container</strong> (<em>iterable</em>) – container for iterables –> [[row1], [row2], …]</li>
-<li><strong>kwargs</strong> (<em>str</em>) – keyword arguments for printing</li>
+<li><strong>kwargs</strong> (<em>str</em><em>, </em><em>bool</em>) – keyword arguments for printing</li>
</ul>
</td>
</tr>
diff --git a/doc/_sources/KADMOS.rst.txt b/doc/_sources/KADMOS.rst.txt
index 0d6721f5080856020c770ae466f0043a774b101d..8edad5a3c1f972ef3cec887b87410a852b323222 100644
--- a/doc/_sources/KADMOS.rst.txt
+++ b/doc/_sources/KADMOS.rst.txt
@@ -38,13 +38,11 @@ KadmosGraph
~~~~~~~~~~~
.. autoclass:: kadmos.graph.graph_kadmos.KadmosGraph
:members:
- :inherited-members:
DataGraph
~~~~~~~~~
.. autoclass:: kadmos.graph.graph_data.DataGraph
:members:
- :inherited-members:
RepositoryConnectivityGraph
~~~~~~~~~~~~~~~~~~~~~~~~~~~
diff --git a/doc/genindex.html b/doc/genindex.html
index d52b6a1aed848a08685ee8796c48f2d0b86a5e00..36f5b85e0b8dfbf8864d17429253911e431d0703 100644
--- a/doc/genindex.html
+++ b/doc/genindex.html
@@ -70,24 +70,16 @@
<li><a href="KADMOS.html#kadmos.cmdows.cmdows.CMDOWS.add_contact">add_contact() (kadmos.cmdows.cmdows.CMDOWS method)</a>
<ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.add_contact">(kadmos.graph.graph_data.DataGraph method)</a>
-</li>
<li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.add_contact">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
</ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.add_contact_roles">add_contact_roles() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.add_contact_roles">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.add_contact_roles">add_contact_roles() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
<li><a href="KADMOS.html#kadmos.cmdows.cmdows.CMDOWS.add_dc">add_dc() (kadmos.cmdows.cmdows.CMDOWS method)</a>
</li>
<li><a href="KADMOS.html#kadmos.cmdows.cmdows.CMDOWS.add_dc_general_info">add_dc_general_info() (kadmos.cmdows.cmdows.CMDOWS method)</a>
<ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.add_dc_general_info">(kadmos.graph.graph_data.DataGraph method)</a>
-</li>
<li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.add_dc_general_info">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
</ul></li>
@@ -98,147 +90,53 @@
<li><a href="KADMOS.html#kadmos.cmdows.cmdows.CMDOWS.add_dc_performance_info">add_dc_performance_info() (kadmos.cmdows.cmdows.CMDOWS method)</a>
<ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.add_dc_performance_info">(kadmos.graph.graph_data.DataGraph method)</a>
-</li>
<li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.add_dc_performance_info">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
</ul></li>
<li><a href="KADMOS.html#kadmos.cmdows.cmdows.CMDOWS.add_dc_remote_component_info">add_dc_remote_component_info() (kadmos.cmdows.cmdows.CMDOWS method)</a>
<ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.add_dc_remote_component_info">(kadmos.graph.graph_data.DataGraph method)</a>
-</li>
<li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.add_dc_remote_component_info">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
</ul></li>
<li><a href="KADMOS.html#kadmos.cmdows.cmdows.CMDOWS.add_dc_verification">add_dc_verification() (kadmos.cmdows.cmdows.CMDOWS method)</a>
</li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.add_default_description">add_default_description() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.add_default_description">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.add_default_description">add_default_description() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.add_default_name">add_default_name() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.add_default_name">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.add_default_name">add_default_name() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.add_edge">add_edge() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.add_edge">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
-</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.add_edges_from">add_edges_from() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.add_edges_from">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ </ul></td>
+ <td style="width: 33%; vertical-align: top;"><ul>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.add_edge">add_edge() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
<li><a href="KADMOS.html#kadmos.cmdows.cmdows.CMDOWS.add_element_to_element_of_uid">add_element_to_element_of_uid() (kadmos.cmdows.cmdows.CMDOWS method)</a>
</li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.add_equation">add_equation() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.add_equation">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.mixin_equation.EquationMixin.add_equation">add_equation() (kadmos.graph.mixin_equation.EquationMixin method)</a>
</li>
- <li><a href="KADMOS.html#kadmos.graph.mixin_equation.EquationMixin.add_equation">(kadmos.graph.mixin_equation.EquationMixin method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.mixin_equation.EquationMixin.add_equation_label">add_equation_label() (kadmos.graph.mixin_equation.EquationMixin method)</a>
</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.add_equation_label">add_equation_label() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.add_equation_label">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
-</li>
- <li><a href="KADMOS.html#kadmos.graph.mixin_equation.EquationMixin.add_equation_label">(kadmos.graph.mixin_equation.EquationMixin method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.mixin_equation.EquationMixin.add_equation_labels">add_equation_labels() (kadmos.graph.mixin_equation.EquationMixin method)</a>
</li>
- </ul></li>
- </ul></td>
- <td style="width: 33%; vertical-align: top;"><ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.add_equation_labels">add_equation_labels() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.add_equation_labels">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
-</li>
- <li><a href="KADMOS.html#kadmos.graph.mixin_equation.EquationMixin.add_equation_labels">(kadmos.graph.mixin_equation.EquationMixin method)</a>
-</li>
- </ul></li>
<li><a href="KADMOS.html#kadmos.graph.graph_data.FundamentalProblemGraph.add_function_problem_roles">add_function_problem_roles() (kadmos.graph.graph_data.FundamentalProblemGraph method)</a>
</li>
<li><a href="KADMOS.html#kadmos.cmdows.cmdows.CMDOWS.add_header">add_header() (kadmos.cmdows.cmdows.CMDOWS method)</a>
</li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.add_instance">add_instance() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.add_instance">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.add_instance">add_instance() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.add_mathematical_function">add_mathematical_function() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.add_mathematical_function">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
-</li>
- <li><a href="KADMOS.html#kadmos.graph.mixin_equation.EquationMixin.add_mathematical_function">(kadmos.graph.mixin_equation.EquationMixin method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.mixin_equation.EquationMixin.add_mathematical_function">add_mathematical_function() (kadmos.graph.mixin_equation.EquationMixin method)</a>
</li>
- </ul></li>
<li><a href="KADMOS.html#kadmos.cmdows.cmdows.CMDOWS.add_new_parameters_from_element">add_new_parameters_from_element() (kadmos.cmdows.cmdows.CMDOWS method)</a>
</li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.add_node">add_node() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.add_node">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.add_node">add_node() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.add_nodes_from">add_nodes_from() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.add_nodes_from">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
-</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.add_objective_function_by_nodes">add_objective_function_by_nodes() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.add_objective_function_by_nodes">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.add_objective_function_by_nodes">add_objective_function_by_nodes() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
<li><a href="KADMOS.html#kadmos.graph.graph_process.MdaoProcessGraph.add_process">add_process() (kadmos.graph.graph_process.MdaoProcessGraph method)</a>
</li>
<li><a href="KADMOS.html#kadmos.utilities.xml.ExtendedElement.add_process_hierarchy">add_process_hierarchy() (kadmos.utilities.xml.ExtendedElement method)</a>
</li>
<li><a href="KADMOS.html#kadmos.graph.graph_process.MdaoProcessGraph.add_process_partitions">add_process_partitions() (kadmos.graph.graph_process.MdaoProcessGraph method)</a>
</li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.add_weighted_edges_from">add_weighted_edges_from() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.add_weighted_edges_from">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
-</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.adj">adj (kadmos.graph.graph_data.DataGraph attribute)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.adj">(kadmos.graph.graph_kadmos.KadmosGraph attribute)</a>
-</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.adjacency">adjacency() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.adjacency">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
-</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.adjlist_inner_dict_factory">adjlist_inner_dict_factory (kadmos.graph.graph_data.DataGraph attribute)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.adjlist_inner_dict_factory">(kadmos.graph.graph_kadmos.KadmosGraph attribute)</a>
-</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.adjlist_outer_dict_factory">adjlist_outer_dict_factory (kadmos.graph.graph_data.DataGraph attribute)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.adjlist_outer_dict_factory">(kadmos.graph.graph_kadmos.KadmosGraph attribute)</a>
-</li>
- </ul></li>
<li><a href="KADMOS.html#kadmos.utilities.general.assert_dict_keys">assert_dict_keys() (in module kadmos.utilities.general)</a>
</li>
<li><a href="KADMOS.html#kadmos.cmdows.cmdows.CMDOWS.assert_element_tag">assert_element_tag() (kadmos.cmdows.cmdows.CMDOWS method)</a>
@@ -249,32 +147,18 @@
<h2 id="C">C</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
<td style="width: 33%; vertical-align: top;"><ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.change_graph_class">change_graph_class() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.change_graph_class">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.change_graph_class">change_graph_class() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
<li><a href="KADMOS.html#kadmos.cmdows.cmdows.CMDOWS.check">check() (kadmos.cmdows.cmdows.CMDOWS method)</a>
<ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.check">(kadmos.graph.graph_data.DataGraph method)</a>
-</li>
<li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.check">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
</ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.check_cmdows_integrity">check_cmdows_integrity() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.check_cmdows_integrity">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.check_cmdows_integrity">check_cmdows_integrity() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.check_for_coupling">check_for_coupling() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.check_for_coupling">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.check_for_coupling">check_for_coupling() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
<li><a href="KADMOS.html#kadmos.cmdows.cmdows.CMDOWS.check_references">check_references() (kadmos.cmdows.cmdows.CMDOWS method)</a>
</li>
<li><a href="KADMOS.html#kadmos.cmdows.cmdows.CMDOWS.check_schema">check_schema() (kadmos.cmdows.cmdows.CMDOWS method)</a>
@@ -283,58 +167,26 @@
</li>
<li><a href="KADMOS.html#kadmos.utilities.xml.ExtendedElement.clean">clean() (kadmos.utilities.xml.ExtendedElement method)</a>
</li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.clear">clear() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.clear">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
-</li>
- </ul></li>
<li><a href="KADMOS.html#kadmos.cmdows.cmdows.CMDOWS">CMDOWS (class in kadmos.cmdows.cmdows)</a>
-</li>
- <li><a href="KADMOS.html#kadmos.utilities.general.color_list">color_list() (in module kadmos.utilities.general)</a>
</li>
</ul></td>
<td style="width: 33%; vertical-align: top;"><ul>
+ <li><a href="KADMOS.html#kadmos.utilities.general.color_list">color_list() (in module kadmos.utilities.general)</a>
+</li>
<li><a href="KADMOS.html#kadmos.graph.graph_process.MdaoProcessGraph.connect_nested_iterators">connect_nested_iterators() (kadmos.graph.graph_process.MdaoProcessGraph method)</a>
</li>
<li><a href="KADMOS.html#kadmos.utilities.general.convert_bytes">convert_bytes() (in module kadmos.utilities.general)</a>
</li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.copy">copy() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.copy">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
-</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.copy_as">copy_as() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.copy_as">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.copy_as">copy_as() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.copy_edge">copy_edge() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.copy_edge">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.copy_edge">copy_edge() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.copy_node_with_suffix">copy_node_with_suffix() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.copy_node_with_suffix">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.copy_node_with_suffix">copy_node_with_suffix() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.count_function_nodes">count_function_nodes() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.count_function_nodes">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.count_function_nodes">count_function_nodes() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.create_dsm">create_dsm() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.create_dsm">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.create_dsm">create_dsm() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
<li><a href="KADMOS.html#kadmos.graph.graph_data.RepositoryConnectivityGraph.create_mathematical_problem">create_mathematical_problem() (kadmos.graph.graph_data.RepositoryConnectivityGraph method)</a>
</li>
<li><a href="KADMOS.html#kadmos.graph.graph_data.FundamentalProblemGraph.create_mdg">create_mdg() (kadmos.graph.graph_data.FundamentalProblemGraph method)</a>
@@ -349,64 +201,32 @@
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph">DataGraph (class in kadmos.graph.graph_data)</a>
</li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.deepcopy">deepcopy() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.deepcopy">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.deepcopy">deepcopy() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.deepcopy_as">deepcopy_as() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.deepcopy_as">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.deepcopy_as">deepcopy_as() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
</ul></td>
<td style="width: 33%; vertical-align: top;"><ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.degree">degree (kadmos.graph.graph_data.DataGraph attribute)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.degree">(kadmos.graph.graph_kadmos.KadmosGraph attribute)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_data.FundamentalProblemGraph.determine_scope_constraint_functions">determine_scope_constraint_functions() (kadmos.graph.graph_data.FundamentalProblemGraph method)</a>
+</li>
+ <li><a href="KADMOS.html#kadmos.graph.graph_data.FundamentalProblemGraph.determine_scope_design_variables">determine_scope_design_variables() (kadmos.graph.graph_data.FundamentalProblemGraph method)</a>
</li>
- </ul></li>
<li><a href="KADMOS.html#kadmos.utilities.general.dict_to_ord_dict">dict_to_ord_dict() (in module kadmos.utilities.general)</a>
</li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.disconnect_problematic_variables_from">disconnect_problematic_variables_from() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.disconnect_problematic_variables_from">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.disconnect_problematic_variables_from">disconnect_problematic_variables_from() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
</ul></td>
</tr></table>
<h2 id="E">E</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
- <td style="width: 33%; vertical-align: top;"><ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.edge_attr_dict_factory">edge_attr_dict_factory (kadmos.graph.graph_data.DataGraph attribute)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.edge_attr_dict_factory">(kadmos.graph.graph_kadmos.KadmosGraph attribute)</a>
-</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.edge_subgraph">edge_subgraph() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.edge_subgraph">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
-</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.edges">edges (kadmos.graph.graph_data.DataGraph attribute)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.edges">(kadmos.graph.graph_kadmos.KadmosGraph attribute)</a>
-</li>
- </ul></li>
- </ul></td>
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="KADMOS.html#kadmos.cmdows.cmdows.CMDOWS.ensure_abs_xpath">ensure_abs_xpath() (kadmos.cmdows.cmdows.CMDOWS method)</a>
</li>
<li><a href="KADMOS.html#kadmos.graph.mixin_equation.EquationMixin">EquationMixin (class in kadmos.graph.mixin_equation)</a>
</li>
+ </ul></td>
+ <td style="width: 33%; vertical-align: top;"><ul>
<li><a href="KADMOS.html#kadmos.utilities.general.export_as_json">export_as_json() (in module kadmos.utilities.general)</a>
</li>
<li><a href="KADMOS.html#kadmos.utilities.xml.ExtendedElement">ExtendedElement (class in kadmos.utilities.xml)</a>
@@ -423,28 +243,18 @@
</li>
<li><a href="KADMOS.html#kadmos.utilities.general.filter_group_vars">filter_group_vars() (in module kadmos.utilities.general)</a>
</li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.find_all_nodes">find_all_nodes() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.find_all_nodes">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
-</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.utilities.xml.ExtendedElement.findasttext">findasttext() (kadmos.utilities.xml.ExtendedElement method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.find_all_nodes">find_all_nodes() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
</ul></td>
<td style="width: 33%; vertical-align: top;"><ul>
+ <li><a href="KADMOS.html#kadmos.utilities.xml.ExtendedElement.findasttext">findasttext() (kadmos.utilities.xml.ExtendedElement method)</a>
+</li>
<li><a href="KADMOS.html#kadmos.utilities.xml.ExtendedElement.finddict">finddict() (kadmos.utilities.xml.ExtendedElement method)</a>
</li>
<li><a href="KADMOS.html#kadmos.utilities.general.format_string_for_latex">format_string_for_latex() (in module kadmos.utilities.general)</a>
</li>
<li><a href="KADMOS.html#kadmos.utilities.general.format_string_for_vistoms">format_string_for_vistoms() (in module kadmos.utilities.general)</a>
</li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.fresh_copy">fresh_copy() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.fresh_copy">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
-</li>
- </ul></li>
<li><a href="KADMOS.html#kadmos.graph.graph_data.FundamentalProblemGraph">FundamentalProblemGraph (class in kadmos.graph.graph_data)</a>
</li>
</ul></td>
@@ -453,52 +263,24 @@
<h2 id="G">G</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
<td style="width: 33%; vertical-align: top;"><ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.get_adjacency_matrix">get_adjacency_matrix() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_adjacency_matrix">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_adjacency_matrix">get_adjacency_matrix() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.get_architecture_node_ids">get_architecture_node_ids() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_architecture_node_ids">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_architecture_node_ids">get_architecture_node_ids() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.get_architecture_node_labels">get_architecture_node_labels() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_architecture_node_labels">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_architecture_node_labels">get_architecture_node_labels() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.get_categorized_nodes">get_categorized_nodes() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_categorized_nodes">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_categorized_nodes">get_categorized_nodes() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.get_contracted_graph">get_contracted_graph() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_contracted_graph">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_contracted_graph">get_contracted_graph() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+</li>
+ <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.get_coupling_dictionary">get_coupling_dictionary() (kadmos.graph.graph_data.DataGraph method)</a>
</li>
- </ul></li>
<li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.get_coupling_matrix">get_coupling_matrix() (kadmos.graph.graph_data.DataGraph method)</a>
</li>
<li><a href="KADMOS.html#kadmos.cmdows.cmdows.CMDOWS.get_design_competences_uids">get_design_competences_uids() (kadmos.cmdows.cmdows.CMDOWS method)</a>
</li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.get_direct_coupling_nodes">get_direct_coupling_nodes() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_direct_coupling_nodes">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
-</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.get_edge_data">get_edge_data() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_edge_data">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_direct_coupling_nodes">get_direct_coupling_nodes() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
<li><a href="KADMOS.html#kadmos.utilities.xml.get_element_details">get_element_details() (in module kadmos.utilities.xml)</a>
</li>
<li><a href="KADMOS.html#kadmos.utilities.general.get_element_dict">get_element_dict() (in module kadmos.utilities.general)</a>
@@ -509,12 +291,8 @@
</li>
<li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.get_feedback_info">get_feedback_info() (kadmos.graph.graph_data.DataGraph method)</a>
</li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.get_first_node_instance">get_first_node_instance() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_first_node_instance">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_first_node_instance">get_first_node_instance() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
<li><a href="KADMOS.html#kadmos.graph.graph_data.RepositoryConnectivityGraph.get_fpg_based_on_function_nodes">get_fpg_based_on_function_nodes() (kadmos.graph.graph_data.RepositoryConnectivityGraph method)</a>
</li>
<li><a href="KADMOS.html#kadmos.graph.graph_data.RepositoryConnectivityGraph.get_fpg_based_on_list_functions">get_fpg_based_on_list_functions() (kadmos.graph.graph_data.RepositoryConnectivityGraph method)</a>
@@ -527,35 +305,23 @@
</li>
<li><a href="KADMOS.html#kadmos.knowledgebase.knowledgebase.KnowledgeBase.get_function_dependencies">get_function_dependencies() (kadmos.knowledgebase.knowledgebase.KnowledgeBase method)</a>
</li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.get_function_graph">get_function_graph() (kadmos.graph.graph_data.DataGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_function_graph">get_function_graph() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
<ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_function_graph">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
-</li>
<li><a href="KADMOS.html#kadmos.knowledgebase.knowledgebase.KnowledgeBase.get_function_graph">(kadmos.knowledgebase.knowledgebase.KnowledgeBase method)</a>
</li>
</ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.get_function_metadata">get_function_metadata() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_function_metadata">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_function_metadata">get_function_metadata() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.get_function_nodes">get_function_nodes() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_function_nodes">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_function_nodes">get_function_nodes() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
<li><a href="KADMOS.html#kadmos.graph.graph_data.RepositoryConnectivityGraph.get_function_paths_by_objective">get_function_paths_by_objective() (kadmos.graph.graph_data.RepositoryConnectivityGraph method)</a>
</li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.get_graph_properties">get_graph_properties() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_graph_properties">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_graph_properties">get_graph_properties() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
<li><a href="KADMOS.html#kadmos.utilities.general.get_group_vars">get_group_vars() (in module kadmos.utilities.general)</a>
+</li>
+ <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.get_highest_instance">get_highest_instance() (kadmos.graph.graph_data.DataGraph method)</a>
</li>
<li><a href="KADMOS.html#kadmos.cmdows.cmdows.CMDOWS.get_inputs_uids">get_inputs_uids() (kadmos.cmdows.cmdows.CMDOWS method)</a>
</li>
@@ -575,57 +341,31 @@
</li>
<li><a href="KADMOS.html#kadmos.graph.graph_data.FundamentalProblemGraph.get_mg_function_ordering">get_mg_function_ordering() (kadmos.graph.graph_data.FundamentalProblemGraph method)</a>
</li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.FundamentalProblemGraph.get_mpg">get_mpg() (kadmos.graph.graph_data.FundamentalProblemGraph method)</a>
-</li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.get_node_attributes">get_node_attributes() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_node_attributes">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_node_attributes">get_node_attributes() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.get_node_subcategory">get_node_subcategory() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_node_subcategory">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_node_subcategory">get_node_subcategory() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
<li><a href="KADMOS.html#kadmos.graph.graph_process.MdaoProcessGraph.get_node_text">get_node_text() (kadmos.graph.graph_process.MdaoProcessGraph method)</a>
</li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.get_nodes_based_on_strings">get_nodes_based_on_strings() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_nodes_based_on_strings">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_nodes_based_on_strings">get_nodes_based_on_strings() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.get_nodes_indegree">get_nodes_indegree() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_nodes_indegree">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_nodes_indegree">get_nodes_indegree() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.get_nodes_outdegree">get_nodes_outdegree() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_nodes_outdegree">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_nodes_outdegree">get_nodes_outdegree() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.get_nodes_subcategory">get_nodes_subcategory() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_nodes_subcategory">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_nodes_subcategory">get_nodes_subcategory() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.get_number_of_couplings">get_number_of_couplings() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_number_of_couplings">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_number_of_couplings">get_number_of_couplings() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+</li>
+ <li><a href="KADMOS.html#kadmos.graph.graph_data.FundamentalProblemGraph.get_objective_node">get_objective_node() (kadmos.graph.graph_data.FundamentalProblemGraph method)</a>
</li>
- </ul></li>
<li><a href="KADMOS.html#kadmos.graph.graph_process.MdaoProcessGraph.get_ordered_cycles">get_ordered_cycles() (kadmos.graph.graph_process.MdaoProcessGraph method)</a>
</li>
<li><a href="KADMOS.html#kadmos.cmdows.cmdows.CMDOWS.get_outputs_uids">get_outputs_uids() (kadmos.cmdows.cmdows.CMDOWS method)</a>
</li>
<li><a href="KADMOS.html#kadmos.cmdows.cmdows.CMDOWS.get_parameters_uids">get_parameters_uids() (kadmos.cmdows.cmdows.CMDOWS method)</a>
+</li>
+ <li><a href="KADMOS.html#kadmos.graph.graph_data.FundamentalProblemGraph.get_partition_info">get_partition_info() (kadmos.graph.graph_data.FundamentalProblemGraph method)</a>
</li>
<li><a href="KADMOS.html#kadmos.graph.graph_data.RepositoryConnectivityGraph.get_path_combinations">get_path_combinations() (kadmos.graph.graph_data.RepositoryConnectivityGraph method)</a>
</li>
@@ -637,36 +377,16 @@
</li>
<li><a href="KADMOS.html#kadmos.knowledgebase.knowledgebase.KnowledgeBase.get_rcg">get_rcg() (kadmos.knowledgebase.knowledgebase.KnowledgeBase method)</a>
</li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.get_same_graph_class">get_same_graph_class() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_same_graph_class">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_same_graph_class">get_same_graph_class() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.get_sources">get_sources() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_sources">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_sources">get_sources() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.get_subgraph_by_function_nodes">get_subgraph_by_function_nodes() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_subgraph_by_function_nodes">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_subgraph_by_function_nodes">get_subgraph_by_function_nodes() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.get_system_inputs">get_system_inputs() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_system_inputs">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_system_inputs">get_system_inputs() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.get_targets">get_targets() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_targets">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.get_targets">get_targets() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
<li><a href="KADMOS.html#kadmos.utilities.general.get_uid">get_uid() (in module kadmos.utilities.general)</a>
</li>
<li><a href="KADMOS.html#kadmos.utilities.xml.get_uid_search_xpath">get_uid_search_xpath() (in module kadmos.utilities.xml)</a>
@@ -677,50 +397,18 @@
</li>
<li><a href="KADMOS.html#kadmos.cmdows.cmdows.CMDOWS.get_xpath_of_uid">get_xpath_of_uid() (kadmos.cmdows.cmdows.CMDOWS method)</a>
</li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.graph_has_nested_attributes">graph_has_nested_attributes() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.graph_has_nested_attributes">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.graph_has_nested_attributes">graph_has_nested_attributes() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
</ul></td>
</tr></table>
<h2 id="H">H</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
<td style="width: 33%; vertical-align: top;"><ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.has_edge">has_edge() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.has_edge">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.has_nodes">has_nodes() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.has_node">has_node() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.has_node">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
-</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.has_nodes">has_nodes() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.has_nodes">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
-</li>
- </ul></li>
</ul></td>
<td style="width: 33%; vertical-align: top;"><ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.has_predecessor">has_predecessor() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.has_predecessor">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
-</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.has_successor">has_successor() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.has_successor">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
-</li>
- </ul></li>
<li><a href="KADMOS.html#kadmos.utilities.general.hex_to_rgb">hex_to_rgb() (in module kadmos.utilities.general)</a>
</li>
</ul></td>
@@ -731,54 +419,18 @@
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="KADMOS.html#kadmos.graph.graph_data.FundamentalProblemGraph.impose_mdao_architecture">impose_mdao_architecture() (kadmos.graph.graph_data.FundamentalProblemGraph method)</a>
</li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.in_degree">in_degree (kadmos.graph.graph_data.DataGraph attribute)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.in_degree">(kadmos.graph.graph_kadmos.KadmosGraph attribute)</a>
-</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.in_edges">in_edges (kadmos.graph.graph_data.DataGraph attribute)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.in_edges">(kadmos.graph.graph_kadmos.KadmosGraph attribute)</a>
-</li>
- </ul></li>
<li><a href="KADMOS.html#kadmos.graph.mixin_mdao.MdaoMixin.insert_node_on_diagonal">insert_node_on_diagonal() (kadmos.graph.mixin_mdao.MdaoMixin method)</a>
</li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.inspect">inspect() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.inspect">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.inspect">inspect() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
</ul></td>
<td style="width: 33%; vertical-align: top;"><ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.inspect_node">inspect_node() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.inspect_node">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.inspect_node">inspect_node() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.inspect_nodes">inspect_nodes() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.inspect_nodes">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.inspect_nodes">inspect_nodes() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
<li><a href="KADMOS.html#kadmos.graph.graph_process.MdaoProcessGraph.inspect_process">inspect_process() (kadmos.graph.graph_process.MdaoProcessGraph method)</a>
</li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.is_directed">is_directed() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.is_directed">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
-</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.is_multigraph">is_multigraph() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.is_multigraph">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
-</li>
- </ul></li>
</ul></td>
</tr></table>
@@ -807,24 +459,16 @@
<h2 id="L">L</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
<td style="width: 33%; vertical-align: top;"><ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.load_cmdows">load_cmdows() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.load_cmdows">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.load_cmdows">load_cmdows() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
</ul></td>
</tr></table>
<h2 id="M">M</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
<td style="width: 33%; vertical-align: top;"><ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.make_all_variables_valid">make_all_variables_valid() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.make_all_variables_valid">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.make_all_variables_valid">make_all_variables_valid() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
<li><a href="KADMOS.html#kadmos.utilities.general.make_camel_case">make_camel_case() (in module kadmos.utilities.general)</a>
</li>
<li><a href="KADMOS.html#kadmos.utilities.general.make_plural">make_plural() (in module kadmos.utilities.general)</a>
@@ -841,46 +485,26 @@
</li>
<li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.mark_as_objective">mark_as_objective() (kadmos.graph.graph_data.DataGraph method)</a>
</li>
+ </ul></td>
+ <td style="width: 33%; vertical-align: top;"><ul>
<li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.mark_as_qois">mark_as_qois() (kadmos.graph.graph_data.DataGraph method)</a>
</li>
<li><a href="KADMOS.html#kadmos.graph.mixin_mdao.MdaoMixin">MdaoMixin (class in kadmos.graph.mixin_mdao)</a>
</li>
- </ul></td>
- <td style="width: 33%; vertical-align: top;"><ul>
<li><a href="KADMOS.html#kadmos.graph.graph_process.MdaoProcessGraph">MdaoProcessGraph (class in kadmos.graph.graph_process)</a>
</li>
<li><a href="KADMOS.html#kadmos.utilities.xml.merge">merge() (in module kadmos.utilities.xml)</a>
</li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.merge_function_modes">merge_function_modes() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.merge_function_modes">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.merge_function_modes">merge_function_modes() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.merge_function_nodes_based_on_modes">merge_function_nodes_based_on_modes() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.merge_function_nodes_based_on_modes">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.merge_function_nodes_based_on_modes">merge_function_nodes_based_on_modes() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.merge_functions">merge_functions() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.merge_functions">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.merge_functions">merge_functions() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.merge_parallel_functions">merge_parallel_functions() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.merge_parallel_functions">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.merge_parallel_functions">merge_parallel_functions() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.merge_sequential_functions">merge_sequential_functions() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.merge_sequential_functions">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.merge_sequential_functions">merge_sequential_functions() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
<li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.minimize_feedback">minimize_feedback() (kadmos.graph.graph_data.DataGraph method)</a>
</li>
</ul></td>
@@ -889,86 +513,18 @@
<h2 id="N">N</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
<td style="width: 33%; vertical-align: top;"><ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.name">name (kadmos.graph.graph_data.DataGraph attribute)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.name">(kadmos.graph.graph_kadmos.KadmosGraph attribute)</a>
-</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.nbunch_iter">nbunch_iter() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.nbunch_iter">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
-</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.neighbors">neighbors() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.neighbors">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
-</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.node">node (kadmos.graph.graph_data.DataGraph attribute)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.node">(kadmos.graph.graph_kadmos.KadmosGraph attribute)</a>
-</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.node_dict_factory">node_dict_factory (kadmos.graph.graph_data.DataGraph attribute)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.node_dict_factory">(kadmos.graph.graph_kadmos.KadmosGraph attribute)</a>
-</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.node_is_function">node_is_function() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.node_is_function">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.node_is_function">node_is_function() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.node_is_hole">node_is_hole() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.node_is_hole">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.node_is_hole">node_is_hole() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
</ul></td>
<td style="width: 33%; vertical-align: top;"><ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.node_is_objective_function">node_is_objective_function() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.node_is_objective_function">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.node_is_objective_function">node_is_objective_function() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.node_is_output">node_is_output() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.node_is_output">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
-</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.node_is_variable">node_is_variable() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.node_is_variable">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.node_is_output">node_is_output() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.nodes">nodes (kadmos.graph.graph_data.DataGraph attribute)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.nodes">(kadmos.graph.graph_kadmos.KadmosGraph attribute)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.node_is_variable">node_is_variable() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.number_of_edges">number_of_edges() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.number_of_edges">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
-</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.number_of_nodes">number_of_nodes() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.number_of_nodes">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
-</li>
- </ul></li>
</ul></td>
</tr></table>
@@ -977,66 +533,24 @@
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="KADMOS.html#kadmos.utilities.general.open_file">open_file() (in module kadmos.utilities.general)</a>
</li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.order">order() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.order">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
-</li>
- </ul></li>
- </ul></td>
- <td style="width: 33%; vertical-align: top;"><ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.out_degree">out_degree (kadmos.graph.graph_data.DataGraph attribute)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.out_degree">(kadmos.graph.graph_kadmos.KadmosGraph attribute)</a>
-</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.out_edges">out_edges (kadmos.graph.graph_data.DataGraph attribute)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.out_edges">(kadmos.graph.graph_kadmos.KadmosGraph attribute)</a>
-</li>
- </ul></li>
</ul></td>
</tr></table>
<h2 id="P">P</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
<td style="width: 33%; vertical-align: top;"><ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.plot_adjacency_matrix">plot_adjacency_matrix() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.plot_adjacency_matrix">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_data.FundamentalProblemGraph.partition_graph">partition_graph() (kadmos.graph.graph_data.FundamentalProblemGraph method)</a>
</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.plot_graph">plot_graph() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.plot_graph">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.plot_adjacency_matrix">plot_adjacency_matrix() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.pred">pred (kadmos.graph.graph_data.DataGraph attribute)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.pred">(kadmos.graph.graph_kadmos.KadmosGraph attribute)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.plot_graph">plot_graph() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.predecessors">predecessors() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.predecessors">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.knowledgebase.knowledgebase.KnowledgeBase.print_circular_connections_in_log">print_circular_connections_in_log() (kadmos.knowledgebase.knowledgebase.KnowledgeBase method)</a>
</li>
- </ul></li>
</ul></td>
<td style="width: 33%; vertical-align: top;"><ul>
- <li><a href="KADMOS.html#kadmos.knowledgebase.knowledgebase.KnowledgeBase.print_circular_connections_in_log">print_circular_connections_in_log() (kadmos.knowledgebase.knowledgebase.KnowledgeBase method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.print_graph">print_graph() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.print_graph">print_graph() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.print_graph">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
-</li>
- </ul></li>
<li><a href="KADMOS.html#kadmos.utilities.printing.print_in_table">print_in_table() (in module kadmos.utilities.printing)</a>
</li>
<li><a href="KADMOS.html#kadmos.utilities.printing.print_indexed_list">print_indexed_list() (in module kadmos.utilities.printing)</a>
@@ -1055,12 +569,8 @@
</li>
<li><a href="KADMOS.html#kadmos.utilities.xml.recursively_unique_attribute">recursively_unique_attribute() (in module kadmos.utilities.xml)</a>
</li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.relabel_function_nodes">relabel_function_nodes() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.relabel_function_nodes">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.relabel_function_nodes">relabel_function_nodes() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
<li><a href="KADMOS.html#kadmos.cmdows.cmdows.CMDOWS.remove_children_of_uid">remove_children_of_uid() (kadmos.cmdows.cmdows.CMDOWS method)</a>
</li>
<li><a href="KADMOS.html#kadmos.cmdows.cmdows.CMDOWS.remove_children_of_xpath">remove_children_of_xpath() (kadmos.cmdows.cmdows.CMDOWS method)</a>
@@ -1069,28 +579,12 @@
</li>
<li><a href="KADMOS.html#kadmos.cmdows.cmdows.CMDOWS.remove_data_graph_element">remove_data_graph_element() (kadmos.cmdows.cmdows.CMDOWS method)</a>
</li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.remove_edge">remove_edge() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.remove_edge">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
-</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.remove_edges_from">remove_edges_from() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.remove_edges_from">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
-</li>
- </ul></li>
<li><a href="KADMOS.html#kadmos.cmdows.cmdows.CMDOWS.remove_element_based_on_uid">remove_element_based_on_uid() (kadmos.cmdows.cmdows.CMDOWS method)</a>
</li>
<li><a href="KADMOS.html#kadmos.cmdows.cmdows.CMDOWS.remove_element_based_on_xpath">remove_element_based_on_xpath() (kadmos.cmdows.cmdows.CMDOWS method)</a>
</li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.remove_function_nodes">remove_function_nodes() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.remove_function_nodes">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.remove_function_nodes">remove_function_nodes() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
<li><a href="KADMOS.html#kadmos.utilities.general.remove_if_exists">remove_if_exists() (in module kadmos.utilities.general)</a>
</li>
</ul></td>
@@ -1099,20 +593,8 @@
</li>
<li><a href="KADMOS.html#kadmos.cmdows.cmdows.CMDOWS.remove_inputs">remove_inputs() (kadmos.cmdows.cmdows.CMDOWS method)</a>
</li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.remove_node">remove_node() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.remove_node">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
-</li>
- </ul></li>
<li><a href="KADMOS.html#kadmos.graph.mixin_mdao.MdaoMixin.remove_node_from_diagonal">remove_node_from_diagonal() (kadmos.graph.mixin_mdao.MdaoMixin method)</a>
</li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.remove_nodes_from">remove_nodes_from() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.remove_nodes_from">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
-</li>
- </ul></li>
<li><a href="KADMOS.html#kadmos.cmdows.cmdows.CMDOWS.remove_outputs">remove_outputs() (kadmos.cmdows.cmdows.CMDOWS method)</a>
</li>
<li><a href="KADMOS.html#kadmos.cmdows.cmdows.CMDOWS.remove_parameter">remove_parameter() (kadmos.cmdows.cmdows.CMDOWS method)</a>
@@ -1133,12 +615,6 @@
</li>
<li><a href="KADMOS.html#kadmos.cmdows.cmdows.CMDOWS.resolve_uids">resolve_uids() (kadmos.cmdows.cmdows.CMDOWS method)</a>
</li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.reverse">reverse() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.reverse">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
-</li>
- </ul></li>
</ul></td>
</tr></table>
@@ -1148,59 +624,29 @@
<li><a href="KADMOS.html#kadmos.cmdows.cmdows.CMDOWS.save">save() (kadmos.cmdows.cmdows.CMDOWS method)</a>
<ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.save">(kadmos.graph.graph_data.DataGraph method)</a>
-</li>
<li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.save">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
</ul></li>
<li><a href="KADMOS.html#kadmos.cmdows.cmdows.CMDOWS.schema">schema() (kadmos.cmdows.cmdows.CMDOWS method)</a>
</li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.RepositoryConnectivityGraph.select_function_combination_from">select_function_combination_from() (kadmos.graph.graph_data.RepositoryConnectivityGraph method)</a>
-</li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.select_objectives_from_graph">select_objectives_from_graph() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.select_objectives_from_graph">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
-</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.cmdows.cmdows.CMDOWS.simplify">simplify() (kadmos.cmdows.cmdows.CMDOWS method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_data.FundamentalProblemGraph.select_distributed_architecture">select_distributed_architecture() (kadmos.graph.graph_data.FundamentalProblemGraph method)</a>
</li>
- <li><a href="KADMOS.html#kadmos.cmdows.cmdows.CMDOWS.simplify_equations">simplify_equations() (kadmos.cmdows.cmdows.CMDOWS method)</a>
-</li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.size">size() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.size">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_data.RepositoryConnectivityGraph.select_function_combination_from">select_function_combination_from() (kadmos.graph.graph_data.RepositoryConnectivityGraph method)</a>
</li>
- </ul></li>
</ul></td>
<td style="width: 33%; vertical-align: top;"><ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.sort_non_coupled_nodes">sort_non_coupled_nodes() (kadmos.graph.graph_data.DataGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_data.FundamentalProblemGraph.select_number_of_partitions">select_number_of_partitions() (kadmos.graph.graph_data.FundamentalProblemGraph method)</a>
</li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.split_variables">split_variables() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.split_variables">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.select_objectives_from_graph">select_objectives_from_graph() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.subgraph">subgraph() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.subgraph">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.cmdows.cmdows.CMDOWS.simplify">simplify() (kadmos.cmdows.cmdows.CMDOWS method)</a>
</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.succ">succ (kadmos.graph.graph_data.DataGraph attribute)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.succ">(kadmos.graph.graph_kadmos.KadmosGraph attribute)</a>
+ <li><a href="KADMOS.html#kadmos.cmdows.cmdows.CMDOWS.simplify_equations">simplify_equations() (kadmos.cmdows.cmdows.CMDOWS method)</a>
</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.successors">successors() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.successors">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.sort_nodes_for_process">sort_nodes_for_process() (kadmos.graph.graph_data.DataGraph method)</a>
+</li>
+ <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.split_variables">split_variables() (kadmos.graph.graph_kadmos.KadmosGraph method)</a>
</li>
- </ul></li>
</ul></td>
</tr></table>
@@ -1209,22 +655,10 @@
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="KADMOS.html#kadmos.utilities.general.test_attr_cond">test_attr_cond() (in module kadmos.utilities.general)</a>
</li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.to_directed">to_directed() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.to_directed">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
-</li>
- </ul></li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.to_undirected">to_undirected() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.to_undirected">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
+ <li><a href="KADMOS.html#kadmos.utilities.general.transform_data_into_strings">transform_data_into_strings() (in module kadmos.utilities.general)</a>
</li>
- </ul></li>
</ul></td>
<td style="width: 33%; vertical-align: top;"><ul>
- <li><a href="KADMOS.html#kadmos.utilities.general.transform_data_into_strings">transform_data_into_strings() (in module kadmos.utilities.general)</a>
-</li>
<li><a href="KADMOS.html#kadmos.utilities.general.transform_string_into_format">transform_string_into_format() (in module kadmos.utilities.general)</a>
</li>
<li><a href="KADMOS.html#kadmos.utilities.general.translate_dict_keys">translate_dict_keys() (in module kadmos.utilities.general)</a>
@@ -1251,24 +685,12 @@
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="KADMOS.html#kadmos.cmdows.cmdows.CMDOWS.version">version() (kadmos.cmdows.cmdows.CMDOWS method)</a>
</li>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.vistoms_add">vistoms_add() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.vistoms_add">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
-</li>
- <li><a href="KADMOS.html#kadmos.graph.mixin_vistoms.VistomsMixin.vistoms_add">(kadmos.graph.mixin_vistoms.VistomsMixin method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.mixin_vistoms.VistomsMixin.vistoms_add">vistoms_add() (kadmos.graph.mixin_vistoms.VistomsMixin method)</a>
</li>
- </ul></li>
</ul></td>
<td style="width: 33%; vertical-align: top;"><ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_data.DataGraph.vistoms_create">vistoms_create() (kadmos.graph.graph_data.DataGraph method)</a>
-
- <ul>
- <li><a href="KADMOS.html#kadmos.graph.graph_kadmos.KadmosGraph.vistoms_create">(kadmos.graph.graph_kadmos.KadmosGraph method)</a>
-</li>
- <li><a href="KADMOS.html#kadmos.graph.mixin_vistoms.VistomsMixin.vistoms_create">(kadmos.graph.mixin_vistoms.VistomsMixin method)</a>
+ <li><a href="KADMOS.html#kadmos.graph.mixin_vistoms.VistomsMixin.vistoms_create">vistoms_create() (kadmos.graph.mixin_vistoms.VistomsMixin method)</a>
</li>
- </ul></li>
<li><a href="KADMOS.html#kadmos.graph.mixin_vistoms.VistomsMixin">VistomsMixin (class in kadmos.graph.mixin_vistoms)</a>
</li>
</ul></td>
diff --git a/doc/objects.inv b/doc/objects.inv
index 97a15969fe67392da5dc7cb310578a0741a766a2..904dd3aeee01270a796f64350b009006839b7cce 100644
Binary files a/doc/objects.inv and b/doc/objects.inv differ
diff --git a/doc/searchindex.js b/doc/searchindex.js
index 021b5a5a3303b2a751307cfaf0bfadf48511e02d..7b7fffda6a9f866a129812ed0276c81ed85285bc 100644
--- a/doc/searchindex.js
+++ b/doc/searchindex.js
@@ -1 +1 @@
-Search.setIndex({docnames:["KADMOS"],envversion:52,filenames:["KADMOS.rst"],objects:{"":{kadmos:[0,0,0,"-"]},"kadmos.cmdows.cmdows":{CMDOWS:[0,1,1,""]},"kadmos.cmdows.cmdows.CMDOWS":{add_actor:[0,2,1,""],add_contact:[0,2,1,""],add_dc:[0,2,1,""],add_dc_general_info:[0,2,1,""],add_dc_inputs_element:[0,2,1,""],add_dc_outputs_element:[0,2,1,""],add_dc_performance_info:[0,2,1,""],add_dc_remote_component_info:[0,2,1,""],add_dc_verification:[0,2,1,""],add_element_to_element_of_uid:[0,2,1,""],add_header:[0,2,1,""],add_new_parameters_from_element:[0,2,1,""],assert_element_tag:[0,2,1,""],check:[0,2,1,""],check_references:[0,2,1,""],check_schema:[0,2,1,""],check_uids:[0,2,1,""],ensure_abs_xpath:[0,2,1,""],get_design_competences_uids:[0,2,1,""],get_element_of_uid:[0,2,1,""],get_executable_blocks_uids:[0,2,1,""],get_inputs_uids:[0,2,1,""],get_mathematical_functions_uids:[0,2,1,""],get_outputs_uids:[0,2,1,""],get_parameters_uids:[0,2,1,""],get_used_parameter_uids:[0,2,1,""],get_xpath_of_uid:[0,2,1,""],remove_children_of_uid:[0,2,1,""],remove_children_of_xpath:[0,2,1,""],remove_contact:[0,2,1,""],remove_data_graph_element:[0,2,1,""],remove_element_based_on_uid:[0,2,1,""],remove_element_based_on_xpath:[0,2,1,""],remove_in_and_outputs:[0,2,1,""],remove_inputs:[0,2,1,""],remove_outputs:[0,2,1,""],remove_parameter:[0,2,1,""],remove_parameters:[0,2,1,""],remove_parameters_element:[0,2,1,""],remove_process_graph_element:[0,2,1,""],remove_unused_contacts:[0,2,1,""],remove_workflow_element:[0,2,1,""],resolve_uids:[0,2,1,""],save:[0,2,1,""],schema:[0,2,1,""],simplify:[0,2,1,""],simplify_equations:[0,2,1,""],version:[0,2,1,""]},"kadmos.graph.graph_data":{DataGraph:[0,1,1,""],FundamentalProblemGraph:[0,1,1,""],RepositoryConnectivityGraph:[0,1,1,""]},"kadmos.graph.graph_data.DataGraph":{add_contact:[0,2,1,""],add_contact_roles:[0,2,1,""],add_dc_general_info:[0,2,1,""],add_dc_performance_info:[0,2,1,""],add_dc_remote_component_info:[0,2,1,""],add_default_description:[0,2,1,""],add_default_name:[0,2,1,""],add_edge:[0,2,1,""],add_edges_from:[0,2,1,""],add_equation:[0,2,1,""],add_equation_label:[0,2,1,""],add_equation_labels:[0,2,1,""],add_instance:[0,2,1,""],add_mathematical_function:[0,2,1,""],add_node:[0,2,1,""],add_nodes_from:[0,2,1,""],add_objective_function_by_nodes:[0,2,1,""],add_weighted_edges_from:[0,2,1,""],adj:[0,3,1,""],adjacency:[0,2,1,""],adjlist_inner_dict_factory:[0,3,1,""],adjlist_outer_dict_factory:[0,3,1,""],change_graph_class:[0,2,1,""],check:[0,2,1,""],check_cmdows_integrity:[0,2,1,""],check_for_coupling:[0,2,1,""],clear:[0,2,1,""],copy:[0,2,1,""],copy_as:[0,2,1,""],copy_edge:[0,2,1,""],copy_node_with_suffix:[0,2,1,""],count_function_nodes:[0,2,1,""],create_dsm:[0,2,1,""],deepcopy:[0,2,1,""],deepcopy_as:[0,2,1,""],degree:[0,3,1,""],disconnect_problematic_variables_from:[0,2,1,""],edge_attr_dict_factory:[0,3,1,""],edge_subgraph:[0,2,1,""],edges:[0,3,1,""],find_all_nodes:[0,2,1,""],fresh_copy:[0,2,1,""],get_adjacency_matrix:[0,2,1,""],get_architecture_node_ids:[0,2,1,""],get_architecture_node_labels:[0,2,1,""],get_categorized_nodes:[0,2,1,""],get_contracted_graph:[0,2,1,""],get_coupling_matrix:[0,2,1,""],get_direct_coupling_nodes:[0,2,1,""],get_edge_data:[0,2,1,""],get_feedback_info:[0,2,1,""],get_first_node_instance:[0,2,1,""],get_function_graph:[0,2,1,""],get_function_metadata:[0,2,1,""],get_function_nodes:[0,2,1,""],get_graph_properties:[0,2,1,""],get_node_attributes:[0,2,1,""],get_node_subcategory:[0,2,1,""],get_nodes_based_on_strings:[0,2,1,""],get_nodes_indegree:[0,2,1,""],get_nodes_outdegree:[0,2,1,""],get_nodes_subcategory:[0,2,1,""],get_number_of_couplings:[0,2,1,""],get_possible_function_order:[0,2,1,""],get_same_graph_class:[0,2,1,""],get_sources:[0,2,1,""],get_subgraph_by_function_nodes:[0,2,1,""],get_system_inputs:[0,2,1,""],get_targets:[0,2,1,""],graph_has_nested_attributes:[0,2,1,""],has_edge:[0,2,1,""],has_node:[0,2,1,""],has_nodes:[0,2,1,""],has_predecessor:[0,2,1,""],has_successor:[0,2,1,""],in_degree:[0,3,1,""],in_edges:[0,3,1,""],inspect:[0,2,1,""],inspect_node:[0,2,1,""],inspect_nodes:[0,2,1,""],is_directed:[0,2,1,""],is_multigraph:[0,2,1,""],load_cmdows:[0,2,1,""],make_all_variables_valid:[0,2,1,""],mark_as_constraint:[0,2,1,""],mark_as_constraints:[0,2,1,""],mark_as_design_variable:[0,2,1,""],mark_as_design_variables:[0,2,1,""],mark_as_objective:[0,2,1,""],mark_as_qois:[0,2,1,""],merge_function_modes:[0,2,1,""],merge_function_nodes_based_on_modes:[0,2,1,""],merge_functions:[0,2,1,""],merge_parallel_functions:[0,2,1,""],merge_sequential_functions:[0,2,1,""],minimize_feedback:[0,2,1,""],name:[0,3,1,""],nbunch_iter:[0,2,1,""],neighbors:[0,2,1,""],node:[0,3,1,""],node_dict_factory:[0,3,1,""],node_is_function:[0,2,1,""],node_is_hole:[0,2,1,""],node_is_objective_function:[0,2,1,""],node_is_output:[0,2,1,""],node_is_variable:[0,2,1,""],nodes:[0,3,1,""],number_of_edges:[0,2,1,""],number_of_nodes:[0,2,1,""],order:[0,2,1,""],out_degree:[0,3,1,""],out_edges:[0,3,1,""],plot_adjacency_matrix:[0,2,1,""],plot_graph:[0,2,1,""],pred:[0,3,1,""],predecessors:[0,2,1,""],print_graph:[0,2,1,""],relabel_function_nodes:[0,2,1,""],remove_edge:[0,2,1,""],remove_edges_from:[0,2,1,""],remove_function_nodes:[0,2,1,""],remove_node:[0,2,1,""],remove_nodes_from:[0,2,1,""],remove_unused_outputs:[0,2,1,""],reverse:[0,2,1,""],save:[0,2,1,""],select_objectives_from_graph:[0,2,1,""],size:[0,2,1,""],sort_non_coupled_nodes:[0,2,1,""],split_variables:[0,2,1,""],subgraph:[0,2,1,""],succ:[0,3,1,""],successors:[0,2,1,""],to_directed:[0,2,1,""],to_undirected:[0,2,1,""],unmark_variable:[0,2,1,""],vistoms_add:[0,2,1,""],vistoms_create:[0,2,1,""]},"kadmos.graph.graph_data.FundamentalProblemGraph":{add_function_problem_roles:[0,2,1,""],create_mdg:[0,2,1,""],create_mpg:[0,2,1,""],get_mdg:[0,2,1,""],get_mg_function_ordering:[0,2,1,""],get_mpg:[0,2,1,""],impose_mdao_architecture:[0,2,1,""]},"kadmos.graph.graph_data.RepositoryConnectivityGraph":{create_mathematical_problem:[0,2,1,""],get_fpg_based_on_function_nodes:[0,2,1,""],get_fpg_based_on_list_functions:[0,2,1,""],get_fpg_based_on_sinks:[0,2,1,""],get_fpg_by_function_nodes:[0,2,1,""],get_function_paths_by_objective:[0,2,1,""],get_path_combinations:[0,2,1,""],select_function_combination_from:[0,2,1,""]},"kadmos.graph.graph_kadmos":{KadmosGraph:[0,1,1,""]},"kadmos.graph.graph_kadmos.KadmosGraph":{add_contact:[0,2,1,""],add_contact_roles:[0,2,1,""],add_dc_general_info:[0,2,1,""],add_dc_performance_info:[0,2,1,""],add_dc_remote_component_info:[0,2,1,""],add_default_description:[0,2,1,""],add_default_name:[0,2,1,""],add_edge:[0,2,1,""],add_edges_from:[0,2,1,""],add_equation:[0,2,1,""],add_equation_label:[0,2,1,""],add_equation_labels:[0,2,1,""],add_instance:[0,2,1,""],add_mathematical_function:[0,2,1,""],add_node:[0,2,1,""],add_nodes_from:[0,2,1,""],add_objective_function_by_nodes:[0,2,1,""],add_weighted_edges_from:[0,2,1,""],adj:[0,3,1,""],adjacency:[0,2,1,""],adjlist_inner_dict_factory:[0,3,1,""],adjlist_outer_dict_factory:[0,3,1,""],change_graph_class:[0,2,1,""],check:[0,2,1,""],check_cmdows_integrity:[0,2,1,""],check_for_coupling:[0,2,1,""],clear:[0,2,1,""],copy:[0,2,1,""],copy_as:[0,2,1,""],copy_edge:[0,2,1,""],copy_node_with_suffix:[0,2,1,""],count_function_nodes:[0,2,1,""],create_dsm:[0,2,1,""],deepcopy:[0,2,1,""],deepcopy_as:[0,2,1,""],degree:[0,3,1,""],disconnect_problematic_variables_from:[0,2,1,""],edge_attr_dict_factory:[0,3,1,""],edge_subgraph:[0,2,1,""],edges:[0,3,1,""],find_all_nodes:[0,2,1,""],fresh_copy:[0,2,1,""],get_adjacency_matrix:[0,2,1,""],get_architecture_node_ids:[0,2,1,""],get_architecture_node_labels:[0,2,1,""],get_categorized_nodes:[0,2,1,""],get_contracted_graph:[0,2,1,""],get_direct_coupling_nodes:[0,2,1,""],get_edge_data:[0,2,1,""],get_first_node_instance:[0,2,1,""],get_function_graph:[0,2,1,""],get_function_metadata:[0,2,1,""],get_function_nodes:[0,2,1,""],get_graph_properties:[0,2,1,""],get_node_attributes:[0,2,1,""],get_node_subcategory:[0,2,1,""],get_nodes_based_on_strings:[0,2,1,""],get_nodes_indegree:[0,2,1,""],get_nodes_outdegree:[0,2,1,""],get_nodes_subcategory:[0,2,1,""],get_number_of_couplings:[0,2,1,""],get_same_graph_class:[0,2,1,""],get_sources:[0,2,1,""],get_subgraph_by_function_nodes:[0,2,1,""],get_system_inputs:[0,2,1,""],get_targets:[0,2,1,""],graph_has_nested_attributes:[0,2,1,""],has_edge:[0,2,1,""],has_node:[0,2,1,""],has_nodes:[0,2,1,""],has_predecessor:[0,2,1,""],has_successor:[0,2,1,""],in_degree:[0,3,1,""],in_edges:[0,3,1,""],inspect:[0,2,1,""],inspect_node:[0,2,1,""],inspect_nodes:[0,2,1,""],is_directed:[0,2,1,""],is_multigraph:[0,2,1,""],load_cmdows:[0,2,1,""],make_all_variables_valid:[0,2,1,""],merge_function_modes:[0,2,1,""],merge_function_nodes_based_on_modes:[0,2,1,""],merge_functions:[0,2,1,""],merge_parallel_functions:[0,2,1,""],merge_sequential_functions:[0,2,1,""],name:[0,3,1,""],nbunch_iter:[0,2,1,""],neighbors:[0,2,1,""],node:[0,3,1,""],node_dict_factory:[0,3,1,""],node_is_function:[0,2,1,""],node_is_hole:[0,2,1,""],node_is_objective_function:[0,2,1,""],node_is_output:[0,2,1,""],node_is_variable:[0,2,1,""],nodes:[0,3,1,""],number_of_edges:[0,2,1,""],number_of_nodes:[0,2,1,""],order:[0,2,1,""],out_degree:[0,3,1,""],out_edges:[0,3,1,""],plot_adjacency_matrix:[0,2,1,""],plot_graph:[0,2,1,""],pred:[0,3,1,""],predecessors:[0,2,1,""],print_graph:[0,2,1,""],relabel_function_nodes:[0,2,1,""],remove_edge:[0,2,1,""],remove_edges_from:[0,2,1,""],remove_function_nodes:[0,2,1,""],remove_node:[0,2,1,""],remove_nodes_from:[0,2,1,""],reverse:[0,2,1,""],save:[0,2,1,""],select_objectives_from_graph:[0,2,1,""],size:[0,2,1,""],split_variables:[0,2,1,""],subgraph:[0,2,1,""],succ:[0,3,1,""],successors:[0,2,1,""],to_directed:[0,2,1,""],to_undirected:[0,2,1,""],vistoms_add:[0,2,1,""],vistoms_create:[0,2,1,""]},"kadmos.graph.graph_process":{MdaoProcessGraph:[0,1,1,""],ProcessGraph:[0,1,1,""]},"kadmos.graph.graph_process.MdaoProcessGraph":{add_process:[0,2,1,""],add_process_partitions:[0,2,1,""],connect_nested_iterators:[0,2,1,""],get_lowest_psn:[0,2,1,""],get_node_text:[0,2,1,""],get_ordered_cycles:[0,2,1,""],get_process_hierarchy:[0,2,1,""],get_process_list:[0,2,1,""],inspect_process:[0,2,1,""]},"kadmos.graph.mixin_equation":{EquationMixin:[0,1,1,""]},"kadmos.graph.mixin_equation.EquationMixin":{add_equation:[0,2,1,""],add_equation_label:[0,2,1,""],add_equation_labels:[0,2,1,""],add_mathematical_function:[0,2,1,""]},"kadmos.graph.mixin_mdao":{MdaoMixin:[0,1,1,""]},"kadmos.graph.mixin_mdao.MdaoMixin":{insert_node_on_diagonal:[0,2,1,""],remove_node_from_diagonal:[0,2,1,""]},"kadmos.graph.mixin_vistoms":{VistomsMixin:[0,1,1,""]},"kadmos.graph.mixin_vistoms.VistomsMixin":{vistoms_add:[0,2,1,""],vistoms_create:[0,2,1,""]},"kadmos.knowledgebase.knowledgebase":{KnowledgeBase:[0,1,1,""]},"kadmos.knowledgebase.knowledgebase.KnowledgeBase":{get_function_dependencies:[0,2,1,""],get_function_graph:[0,2,1,""],get_kb_graphs:[0,2,1,""],get_rcg:[0,2,1,""],print_circular_connections_in_log:[0,2,1,""]},"kadmos.utilities":{general:[0,0,0,"-"],printing:[0,0,0,"-"],strings:[0,0,0,"-"],xml:[0,0,0,"-"]},"kadmos.utilities.general":{assert_dict_keys:[0,4,1,""],color_list:[0,4,1,""],convert_bytes:[0,4,1,""],dict_to_ord_dict:[0,4,1,""],export_as_json:[0,4,1,""],file_size:[0,4,1,""],file_size_MB:[0,4,1,""],filter_group_vars:[0,4,1,""],format_string_for_latex:[0,4,1,""],format_string_for_vistoms:[0,4,1,""],get_element_dict:[0,4,1,""],get_friendly_id:[0,4,1,""],get_group_vars:[0,4,1,""],get_list_entries:[0,4,1,""],get_mdao_setup:[0,4,1,""],get_uid:[0,4,1,""],get_unique_friendly_id:[0,4,1,""],hex_to_rgb:[0,4,1,""],make_camel_case:[0,4,1,""],make_plural:[0,4,1,""],make_singular:[0,4,1,""],open_file:[0,4,1,""],remove_if_exists:[0,4,1,""],test_attr_cond:[0,4,1,""],transform_data_into_strings:[0,4,1,""],transform_string_into_format:[0,4,1,""],translate_dict_keys:[0,4,1,""],translate_list:[0,4,1,""],unmake_camel_case:[0,4,1,""]},"kadmos.utilities.printing":{print_in_table:[0,4,1,""],print_indexed_list:[0,4,1,""]},"kadmos.utilities.xml":{ExtendedElement:[0,1,1,""],get_element_details:[0,4,1,""],get_uid_search_xpath:[0,4,1,""],merge:[0,4,1,""],recursively_empty:[0,4,1,""],recursively_stringify:[0,4,1,""],recursively_unique_attribute:[0,4,1,""]},"kadmos.utilities.xml.ExtendedElement":{add:[0,2,1,""],add_process_hierarchy:[0,2,1,""],clean:[0,2,1,""],findasttext:[0,2,1,""],finddict:[0,2,1,""]}},objnames:{"0":["py","module","Python module"],"1":["py","class","Python class"],"2":["py","method","Python method"],"3":["py","attribute","Python attribute"],"4":["py","function","Python function"]},objtypes:{"0":"py:module","1":"py:class","2":"py:method","3":"py:attribute","4":"py:function"},terms:{"13S":0,"1e4":0,"5pm":0,"boolean":0,"byte":0,"case":0,"class":0,"default":0,"export":0,"final":0,"float":0,"function":0,"import":0,"int":0,"long":0,"new":0,"return":0,"super":0,"true":0,"try":0,"while":0,Adding:0,But:0,For:0,IDs:0,Not:0,That:0,The:0,There:0,These:0,Use:0,Useful:0,Will:0,__all__:0,__builtin__:0,__class__:0,__iter__:0,__len__:0,__none__:0,_check_category_a:0,_check_category_b:0,_check_category_c:0,abbreviate_keyword:0,abl:0,abov:0,absolut:0,access:0,accord:0,account:0,act:0,action:0,actual:0,add:0,add_actor:0,add_contact:0,add_contact_rol:0,add_dc:0,add_dc_general_info:0,add_dc_inputs_el:0,add_dc_outputs_el:0,add_dc_performance_info:0,add_dc_remote_component_info:0,add_dc_verif:0,add_default_descript:0,add_default_nam:0,add_edg:0,add_edges_from:0,add_element_to_element_of_uid:0,add_equ:0,add_equation_label:0,add_function_problem_rol:0,add_head:0,add_inst:0,add_mathematical_funct:0,add_new_parameters_from_el:0,add_nod:0,add_nodes_from:0,add_objective_function_by_nod:0,add_path:0,add_process:0,add_process_hierarchi:0,add_process_partit:0,add_weighted_edges_from:0,added:0,addit:0,address:0,adher:0,adj:0,adj_it:0,adjac:0,adjlist_inner_dict_factori:0,adjlist_outer_dict_factori:0,adjust:0,adress:0,advanc:0,aerodynam:0,aerospac:0,affect:0,after:0,agil:0,aircraft:0,algorithm:0,alia:0,all:0,all_keys_requir:0,all_nod:0,allow:0,allow_unconverged_coupl:0,along:0,alreadi:0,als:0,also:0,american:0,amount:0,analys:0,analysi:0,analyt:0,analyz:0,ani:0,anoth:0,appear:0,append:0,appli:0,applic:0,appyl:0,arbitrari:0,architect:0,architectur:0,archiv:0,arg:0,argument:0,around:0,as_view:0,ask:0,assert:0,assert_dict_kei:0,assert_element_tag:0,assess:0,assign:0,associ:0,assum:0,ast:0,attempt:0,attr:0,attr_cond:0,attr_dict:0,attr_exclud:0,attr_includ:0,attr_list:0,attr_valu:0,attrb:0,attrdict:0,attrib:0,attribut:0,automat:0,avail:0,back:0,bar:0,base:0,baselin:0,basestr:0,becaus:0,becom:0,been:0,befor:0,behav:0,behavior:0,being:0,belong:0,below:0,between:0,bliss:0,block:0,blue:0,bool:0,both:0,bound:0,box:0,bracket:0,branch:0,build:0,busi:0,calcul:0,call:0,camel:0,camel_case_convers:0,camelcas:0,can:0,cannot:0,capac:0,care:0,casi:0,categori:0,caus:0,certain:0,chang:0,change_graph_class:0,charact:0,characterist:0,check:0,check_cmdows_integr:0,check_for_coupl:0,check_graph:0,check_list:0,check_refer:0,check_schema:0,check_uid:0,child:0,children:0,children_to_keep:0,children_to_remov:0,choic:0,choos:0,circular:0,circularconnect:0,clariti:0,clean:0,clear:0,close:0,clutter:0,cmdowsvers:0,collaborativeengin:0,collect:0,collid:0,collis:0,color:0,color_list:0,color_set:0,colors_based_on:0,column:0,combin:0,common:0,compani:0,compar:0,comparison:0,compet:0,compil:0,compile_pdf:0,complet:0,complex:0,compon:0,compos:0,compress:0,comput:0,condit:0,config:0,configur:0,confus:0,connect:0,connect_nested_iter:0,conserv:0,consid:0,consider:0,consist:0,consistent_root:0,consol:0,constraint:0,contact:0,contact_uid:0,contain:0,content:0,continu:0,contract:0,contracted_graph:0,contraction_level:0,contrast:0,control:0,conv:0,conveni:0,convent:0,converg:0,convers:0,convert:0,convert_byt:0,coor:0,copi:0,copy_a:0,copy_edg:0,copy_node_with_suffix:0,copy_typ:0,correct:0,correspond:0,could:0,count:0,count_function_nod:0,countri:0,coupl:0,coupling_strength:0,cpac:0,creat:0,create_dsm:0,create_mathematical_problem:0,create_mdg:0,create_mpg:0,creation:0,creation_d:0,creator:0,creator_uid:0,criteria:0,cross:0,current:0,current_group_idx:0,custom:0,cwd:0,cycl:0,d3j:0,data:0,data_dictionari:0,data_exchange_dict:0,datadict:0,date:0,datetim:0,dc_uid:0,ddict:0,decrib:0,deep:0,deepcopi:0,deepcopy_a:0,defin:0,definit:0,deg:0,degre:0,degreeview:0,delet:0,delft:0,depart:0,depend:0,deprec:0,descend:0,describ:0,descript:0,design:0,designcompet:0,desir:0,destin:0,destination_fold:0,detail:0,determin:0,develop:0,dewit:0,diagon:0,diagonal_po:0,diagram:0,dic:0,dict:0,dict_to_ord_dict:0,dictionari:0,differ:0,differenti:0,digraph:0,dimens:0,direct:0,directli:0,directori:0,disciplin:0,disciplinari:0,disconnect:0,disconnect_collided_target:0,disconnect_problematic_variables_from:0,disconnect_shared_sourc:0,disregard:0,distinguis:0,distribut:0,divid:0,doc:0,doctest:0,doe:0,doesn:0,doing:0,done:0,dont:0,download:0,draw:0,dsm:0,dubreuil:0,due:0,duplic:0,dynam:0,each:0,ebunch:0,ebunch_to_add:0,edg:0,edge_attr_dict_factori:0,edge_dict:0,edge_ind:0,edge_label:0,edge_or_nod:0,edge_subgraph:0,edgedataview:0,effect:0,either:0,element:0,element_to_add:0,elementtre:0,email:0,employe:0,empti:0,enabl:0,encod:0,encount:0,end:0,end_in_iterative_nod:0,engin:0,enrich:0,ensur:0,ensure_abs_xpath:0,entir:0,entri:0,entries_to_remov:0,equat:0,equival:0,error:0,especi:0,etc:0,evalu:0,even:0,everi:0,everyth:0,exactli:0,exampl:0,exblock_uid:0,exce:0,except:0,exchang:0,exclud:0,exclus:0,execut:0,executableblock:0,exhaust:0,exist:0,expect:0,expected_amount:0,expected_kei:0,expected_tag:0,expected_tag_new_el:0,expected_tag_uid_el:0,expected_text:0,explicit:0,export_as_json:0,express:0,extend:0,extendedel:0,extens:0,extra:0,extract:0,fail:0,fals:0,feedback:0,fidel:0,fidelity_level:0,fig_num:0,fig_siz:0,figur:0,file:0,file_nam:0,file_path:0,file_ref:0,file_s:0,file_size_mb:0,file_typ:0,filenam:0,filevers:0,filter:0,filter_group_var:0,filter_set:0,find:0,find_all_nod:0,findasttext:0,finddict:0,findtext:0,first:0,folder:0,follow:0,foo:0,foovalu:0,form:0,format:0,format_string_for_latex:0,format_string_for_vistom:0,found:0,four:0,fpg:0,french:0,fresh:0,fresh_copi:0,from:0,front:0,full:0,funcnam:0,function_nod:0,function_ord:0,function_order_method:0,function_typ:0,functiongraph:0,fundament:0,further:0,futur:0,gauss:0,get:0,get_adjacency_matrix:0,get_architecture_node_id:0,get_architecture_node_label:0,get_categorized_nod:0,get_contracted_graph:0,get_coupling_matrix:0,get_design_competences_uid:0,get_direct_coupling_nod:0,get_edge_data:0,get_element_detail:0,get_element_dict:0,get_element_of_uid:0,get_executable_blocks_uid:0,get_feedback_info:0,get_first_node_inst:0,get_fpg_based_on_function_nod:0,get_fpg_based_on_list_funct:0,get_fpg_based_on_sink:0,get_fpg_by_function_nod:0,get_friendly_id:0,get_function_depend:0,get_function_graph:0,get_function_metadata:0,get_function_nod:0,get_function_paths_by_object:0,get_graph_properti:0,get_group_var:0,get_inputs_uid:0,get_kb_graph:0,get_list_entri:0,get_lowest_psn:0,get_mathematical_functions_uid:0,get_mdao_setup:0,get_mdg:0,get_mg_function_ord:0,get_mpg:0,get_node_attribut:0,get_node_subcategori:0,get_node_text:0,get_nodes_based_on_str:0,get_nodes_indegre:0,get_nodes_outdegre:0,get_nodes_subcategori:0,get_number_of_coupl:0,get_ordered_cycl:0,get_outputs_uid:0,get_parameters_uid:0,get_path_combin:0,get_possible_function_ord:0,get_process_hierarchi:0,get_process_list:0,get_rcg:0,get_same_graph_class:0,get_sourc:0,get_subgraph_by_function_nod:0,get_system_input:0,get_target:0,get_uid:0,get_uid_search_xpath:0,get_unique_friendly_id:0,get_used_parameter_uid:0,get_xpath_of_uid:0,give:0,given:0,global:0,gov:0,graph_check_crit:0,graph_class:0,graph_data:0,graph_has_nested_attribut:0,graph_id:0,graph_kadmo:0,graph_process:0,graph_properti:0,graphml:0,group:0,group_dict:0,group_idx:0,guarante:0,guess:0,handl:0,has:0,has_edg:0,has_nod:0,has_predecessor:0,has_successor:0,hash:0,hashabl:0,have:0,header:0,hello:0,henc:0,here:0,hex:0,hex_to_rgb:0,hierarchi:0,higher_level_remov:0,highest:0,hold:0,hole:0,how:0,howev:0,html:0,http:0,ident:0,identifi:0,idf:0,idiom:0,ids:0,ignor:0,ignore_func:0,ignore_list:0,ignore_mod:0,ignorefunct:0,illustr:0,implement:0,impose_mdao_architectur:0,in_degre:0,in_edg:0,incid:0,includ:0,include_al:0,include_reference_data:0,include_system_var:0,indec:0,indegre:0,indegreeview:0,indent:0,indentifi:0,independ:0,index:0,index_bracket:0,indic:0,induc:0,inedgeview:0,info:0,inform:0,initi:0,inout:0,inp:0,inplac:0,input:0,input_list:0,input_nod:0,inputless:0,inputs_el:0,insert:0,insert_node_on_diagon:0,insid:0,inspect:0,inspect_nod:0,inspect_process:0,inspir:0,instanc:0,instance_id:0,instanceid:0,instead:0,integ:0,integr:0,interest:0,interfac:0,invalid:0,invalid_leaf_el:0,is_direct:0,is_multigraph:0,italian:0,item:0,iter:0,itertool:0,its:0,itself:0,ivang:0,japanes:0,jet:0,job:0,job_:0,job_nam:0,join:0,json:0,just:0,kb_dir_path:0,kdm:0,keep:0,keep_empty_el:0,keep_objective_vari:0,keep_run:0,keep_tex_fil:0,kei:0,key_ord:0,keyerror:0,keys_to_be_remov:0,keyword:0,knowledg:0,knowledge_bas:0,kwarg:0,lab:0,label:0,label_extens:0,labeling_method:0,lafag:0,languag:0,larg:0,last:0,latex:0,lead:0,leaf:0,least:0,left:0,len:0,length:0,let:0,level:0,librari:0,like:0,limit:0,line:0,link:0,list:0,list_of_funct:0,list_of_nod:0,list_of_sink:0,list_of_tool:0,literatur:0,load:0,load_cmdow:0,local:0,log:0,lookup:0,loop:0,lost:0,lower:0,lower_bound:0,lower_cas:0,lowest:0,maaik:0,mai:0,mainli:0,maintain:0,make:0,make_all_variables_valid:0,make_camel_cas:0,make_plur:0,make_plural_opt:0,make_singular:0,mani:0,manipul:0,manual:0,map:0,mark:0,mark_as_constraint:0,mark_as_design_vari:0,mark_as_object:0,mark_as_qoi:0,master:0,match:0,mathemat:0,matplotlib:0,matrix:0,max_func:0,maxim:0,maximum:0,mda:0,mda_typ:0,mdao:0,mdao_architectur:0,mdao_setup:0,mdaodatagraph:0,mddewit:0,mdf:0,mdg:0,mdo:0,mdo_architectur:0,meet:0,membership:0,memori:0,merg:0,merge_func:0,merge_funct:0,merge_function_mod:0,merge_function_nodes_based_on_mod:0,merge_parallel_funct:0,merge_sequential_funct:0,merger:0,messag:0,metadata:0,method:0,mg_function_ord:0,might:0,min_func:0,mind:0,minim:0,minimize_feedback:0,minimum:0,mixin_equ:0,mixin_mdao:0,mixin_vistom:0,mode:0,mode_id:0,modeid:0,model:0,model_definit:0,modul:0,more:0,most:0,mpg:0,multi_start:0,multidigraph:0,multigraph:0,multipl:0,must:0,mutabl:0,my_obj_fcn_nam:0,mygraph:0,n_coupling_var:0,n_disciplin:0,n_global_constraint:0,n_global_var:0,n_local_constraint:0,n_local_var:0,name:0,named_obj_fcn:0,namespac:0,nasa:0,nativ:0,nbr:0,nbrdict:0,nbunch:0,nbunch_it:0,nd_iter:0,nedg:0,need:0,neighbor:0,nest:0,networkx:0,networkxerror:0,never:0,new_edg:0,new_label:0,next_sequ:0,niter:0,nnode:0,node:0,node_dict_factori:0,node_id:0,node_is_funct:0,node_is_hol:0,node_is_objective_funct:0,node_is_output:0,node_is_vari:0,node_label:0,node_select:0,nodedata:0,nodedataview:0,nodes_for_ad:0,nodeview:0,nomin:0,nominal_valu:0,non:0,none:0,nonetyp:0,notat:0,note:0,notifi:0,notification_messag:0,ntr:0,num:0,number:0,number_of_edg:0,number_of_group:0,number_of_nod:0,numer:0,obj_vars_cov:0,object:0,obtain:0,off:0,old:0,old_edg:0,onc:0,one:0,onera:0,ones:0,onli:0,only_add_if_valu:0,only_feedback:0,open:0,open_fil:0,open_pdf:0,openmdao:0,oper:0,operator_uid:0,opt:0,optim:0,option:0,order:0,ordereddict:0,org:0,organ:0,organiz:0,origin:0,other:0,otherwis:0,our:0,out:0,out_degre:0,out_edg:0,outdegre:0,outdegreeview:0,outedgedataview:0,outedgeview:0,outgo:0,outp:0,output:0,output_nod:0,outputless:0,outputs_el:0,over:0,overal:0,overview:0,overwrit:0,own:0,owner:0,owner_uid:0,packag:0,page:0,pair:0,parallel:0,param:0,param_uid:0,paramet:0,parameters_el:0,params_uid:0,part:0,partit:0,pass:0,pate:0,path:0,path_graph:0,path_or_el:0,paus:0,pdf:0,peopl:0,per:0,percentag:0,perform:0,permit:0,pickl:0,place:0,platform:0,pleas:0,plot:0,plot_adjacency_matrix:0,plot_graph:0,plural:0,png:0,point:0,posit:0,possibl:0,post:0,pre:0,preced:0,precis:0,pred:0,predecessor:0,prefer:0,prefix:0,presenc:0,present:0,pretti:0,pretty_print:0,previous_sequ:0,print_attribut:0,print_circular_connections_in_log:0,print_contain:0,print_coupl:0,print_graph:0,print_in_log:0,print_in_t:0,print_indec:0,print_indexed_list:0,problem:0,problem_rol:0,problemat:0,process:0,process_hierarchi:0,process_step:0,produc:0,product:0,project:0,prompt:0,properti:0,propuls:0,provid:0,psg:0,psn:0,pull:0,pure:0,purpos:0,pymerg:0,pyplot:0,python:0,quantiti:0,queri:0,quickli:0,quietli:0,quot:0,rais:0,raise_error:0,raise_error_if_tru:0,rang:0,rce:0,rcg:0,read:0,readabl:0,reciproc:0,recognis:0,recommend:0,recurs:0,recursively_empti:0,recursively_stringifi:0,recursively_unique_attribut:0,red:0,reduc:0,reduct:0,ref:0,refer:0,reference_fil:0,reference_valu:0,refin:0,reflect:0,regular:0,reinstanti:0,rel:0,relabel:0,relabel_function_nod:0,relat:0,relev:0,remain:0,remi:0,remot:0,remote_engin:0,remov:0,remove_after_compress:0,remove_children_of_uid:0,remove_children_of_xpath:0,remove_contact:0,remove_data_graph_el:0,remove_edg:0,remove_edges_from:0,remove_element_based_on_uid:0,remove_element_based_on_xpath:0,remove_function_nod:0,remove_if_exist:0,remove_in_and_output:0,remove_input:0,remove_nod:0,remove_node_from_diagon:0,remove_nodes_from:0,remove_output:0,remove_paramet:0,remove_parameters_el:0,remove_process_graph_el:0,remove_unused_contact:0,remove_unused_output:0,remove_workflow_el:0,renam:0,replac:0,replacement_id:0,report:0,repres:0,represent:0,reproduc:0,request:0,requir:0,resolv:0,resolve_uid:0,resourc:0,respect:0,rest:0,result:0,retriev:0,revers:0,rgb:0,right:0,role:0,root:0,round:0,routin:0,row1:0,row2:0,rule:0,run:0,run_tim:0,runtim:0,safe:0,same:0,sampl:0,sampledir:0,samplefil:0,satisfi:0,save:0,save_a:0,scalar:0,schema:0,script:0,search:0,second:0,see:0,seidel:0,select:0,select_function_combination_from:0,select_objectives_from_graph:0,self:0,sellar:0,separ:0,sequenc:0,server:0,set:0,sever:0,shallow:0,share:0,shorter:0,should:0,show:0,show_now:0,shown:0,side:0,sidebar:0,signific:0,silent:0,similar:0,simpl:0,simpler:0,simpli:0,simplifi:0,simplify_equ:0,sinc:0,singl:0,single_or_multi:0,single_or_multi_execut:0,singular:0,sink:0,situat:0,size:0,skip:0,slave:0,small:0,some:0,some_fold:0,some_url:0,song:0,sonic:0,sort:0,sort_bi:0,sort_kei:0,sort_non_coupled_nod:0,sourc:0,space:0,specif:0,specifi:0,split:0,split_vari:0,splittabl:0,spring:0,squar:0,standard:0,start:0,start_step:0,statement:0,statu:0,step:0,still:0,stop:0,store:0,str:0,stringifi:0,structur:0,student:0,style:0,sub:0,subcategori:0,subclass:0,subel:0,subgraph:0,subgroup:0,subscript:0,subset:0,succ:0,successor:0,suffix:0,suit:0,sum:0,summar:0,summarize_var:0,suppli:0,sure:0,svg:0,sylvain:0,symbol:0,syntax:0,system:0,system_input:0,tabl:0,tabul:0,tag:0,take:0,taken:0,target:0,technic:0,telephon:0,test:0,test_attr_cond:0,test_valu:0,tex:0,text:0,textfil:0,thank:0,thei:0,them:0,thi:0,think:0,third:0,those:0,though:0,through:0,thu:0,time:0,timestamp:0,titl:0,to_direct:0,to_undirect:0,todo:0,togeth:0,tool:0,toolspecialist:0,total:0,transfer:0,transform:0,transform_data_into_str:0,transform_string_into_format:0,translat:0,translate_dict_kei:0,translate_list:0,tree:0,tudelft:0,tupl:0,twice:0,two:0,type:0,typic:0,uid:0,uid_length:0,uml:0,unconnect:0,under:0,underscor:0,undirect:0,uniqu:0,unmake_camel_cas:0,unmark:0,unmark_vari:0,unnamed_funct:0,unpack:0,until:0,updat:0,upper:0,upper_bound:0,urlsit:0,usag:0,use:0,use_d3js_node_id:0,use_png_fig:0,use_pretty_print:0,used:0,used_id:0,useful:0,user:0,user_prompt_select_opt:0,using:0,usual:0,utf:0,utm:0,uxpath:0,valid:0,valu:0,var_dim:0,var_valu:0,variabl:0,variableinstance1:0,variableinstance2:0,variableinstance3:0,variableinstance4:0,varieti:0,variou:0,verif:0,verifi:0,versatil:0,version:0,via:0,view:0,vispack_vers:0,vistom:0,vistoms_add:0,vistoms_cr:0,vistoms_dir:0,vistoms_vers:0,visual:0,wai:0,wang:0,want:0,warn:0,weight:0,well:0,were:0,what:0,when:0,where:0,whether:0,which:0,window:0,wing:0,wit:0,within:0,without:0,wn2898:0,work:0,workflow:0,write:0,write_problem_to_textfil:0,written:0,wrong:0,xdsm:0,xml_declar:0,xml_file:0,xpath:0,xpath_exclud:0,xpath_includ:0,yet:0,yield:0,you:0,your:0,zero:0,zhang:0,zip:0},titles:["Welcome to KADMOS\u2019s documentation!"],titleterms:{cmdow:0,code:0,datagraph:0,document:0,equationmixin:0,fundamentalproblemgraph:0,gener:0,graph:0,kadmo:0,kadmosgraph:0,knowledgebas:0,mdaomixin:0,mdaoprocessgraph:0,print:0,processgraph:0,repositoryconnectivitygraph:0,string:0,util:0,vistomsmixin:0,welcom:0,xml:0}})
\ No newline at end of file
+Search.setIndex({docnames:["KADMOS"],envversion:52,filenames:["KADMOS.rst"],objects:{"":{kadmos:[0,0,0,"-"]},"kadmos.cmdows.cmdows":{CMDOWS:[0,1,1,""]},"kadmos.cmdows.cmdows.CMDOWS":{add_actor:[0,2,1,""],add_contact:[0,2,1,""],add_dc:[0,2,1,""],add_dc_general_info:[0,2,1,""],add_dc_inputs_element:[0,2,1,""],add_dc_outputs_element:[0,2,1,""],add_dc_performance_info:[0,2,1,""],add_dc_remote_component_info:[0,2,1,""],add_dc_verification:[0,2,1,""],add_element_to_element_of_uid:[0,2,1,""],add_header:[0,2,1,""],add_new_parameters_from_element:[0,2,1,""],assert_element_tag:[0,2,1,""],check:[0,2,1,""],check_references:[0,2,1,""],check_schema:[0,2,1,""],check_uids:[0,2,1,""],ensure_abs_xpath:[0,2,1,""],get_design_competences_uids:[0,2,1,""],get_element_of_uid:[0,2,1,""],get_executable_blocks_uids:[0,2,1,""],get_inputs_uids:[0,2,1,""],get_mathematical_functions_uids:[0,2,1,""],get_outputs_uids:[0,2,1,""],get_parameters_uids:[0,2,1,""],get_used_parameter_uids:[0,2,1,""],get_xpath_of_uid:[0,2,1,""],remove_children_of_uid:[0,2,1,""],remove_children_of_xpath:[0,2,1,""],remove_contact:[0,2,1,""],remove_data_graph_element:[0,2,1,""],remove_element_based_on_uid:[0,2,1,""],remove_element_based_on_xpath:[0,2,1,""],remove_in_and_outputs:[0,2,1,""],remove_inputs:[0,2,1,""],remove_outputs:[0,2,1,""],remove_parameter:[0,2,1,""],remove_parameters:[0,2,1,""],remove_parameters_element:[0,2,1,""],remove_process_graph_element:[0,2,1,""],remove_unused_contacts:[0,2,1,""],remove_workflow_element:[0,2,1,""],resolve_uids:[0,2,1,""],save:[0,2,1,""],schema:[0,2,1,""],simplify:[0,2,1,""],simplify_equations:[0,2,1,""],version:[0,2,1,""]},"kadmos.graph.graph_data":{DataGraph:[0,1,1,""],FundamentalProblemGraph:[0,1,1,""],RepositoryConnectivityGraph:[0,1,1,""]},"kadmos.graph.graph_data.DataGraph":{get_coupling_dictionary:[0,2,1,""],get_coupling_matrix:[0,2,1,""],get_feedback_info:[0,2,1,""],get_highest_instance:[0,2,1,""],get_possible_function_order:[0,2,1,""],mark_as_constraint:[0,2,1,""],mark_as_constraints:[0,2,1,""],mark_as_design_variable:[0,2,1,""],mark_as_design_variables:[0,2,1,""],mark_as_objective:[0,2,1,""],mark_as_qois:[0,2,1,""],minimize_feedback:[0,2,1,""],remove_unused_outputs:[0,2,1,""],sort_nodes_for_process:[0,2,1,""],unmark_variable:[0,2,1,""]},"kadmos.graph.graph_data.FundamentalProblemGraph":{add_function_problem_roles:[0,2,1,""],create_mdg:[0,2,1,""],create_mpg:[0,2,1,""],determine_scope_constraint_functions:[0,2,1,""],determine_scope_design_variables:[0,2,1,""],get_mdg:[0,2,1,""],get_mg_function_ordering:[0,2,1,""],get_objective_node:[0,2,1,""],get_partition_info:[0,2,1,""],impose_mdao_architecture:[0,2,1,""],partition_graph:[0,2,1,""],select_distributed_architecture:[0,2,1,""],select_number_of_partitions:[0,2,1,""]},"kadmos.graph.graph_data.RepositoryConnectivityGraph":{create_mathematical_problem:[0,2,1,""],get_fpg_based_on_function_nodes:[0,2,1,""],get_fpg_based_on_list_functions:[0,2,1,""],get_fpg_based_on_sinks:[0,2,1,""],get_fpg_by_function_nodes:[0,2,1,""],get_function_paths_by_objective:[0,2,1,""],get_path_combinations:[0,2,1,""],select_function_combination_from:[0,2,1,""]},"kadmos.graph.graph_kadmos":{KadmosGraph:[0,1,1,""]},"kadmos.graph.graph_kadmos.KadmosGraph":{add_contact:[0,2,1,""],add_contact_roles:[0,2,1,""],add_dc_general_info:[0,2,1,""],add_dc_performance_info:[0,2,1,""],add_dc_remote_component_info:[0,2,1,""],add_default_description:[0,2,1,""],add_default_name:[0,2,1,""],add_edge:[0,2,1,""],add_instance:[0,2,1,""],add_node:[0,2,1,""],add_objective_function_by_nodes:[0,2,1,""],change_graph_class:[0,2,1,""],check:[0,2,1,""],check_cmdows_integrity:[0,2,1,""],check_for_coupling:[0,2,1,""],copy_as:[0,2,1,""],copy_edge:[0,2,1,""],copy_node_with_suffix:[0,2,1,""],count_function_nodes:[0,2,1,""],create_dsm:[0,2,1,""],deepcopy:[0,2,1,""],deepcopy_as:[0,2,1,""],disconnect_problematic_variables_from:[0,2,1,""],find_all_nodes:[0,2,1,""],get_adjacency_matrix:[0,2,1,""],get_architecture_node_ids:[0,2,1,""],get_architecture_node_labels:[0,2,1,""],get_categorized_nodes:[0,2,1,""],get_contracted_graph:[0,2,1,""],get_direct_coupling_nodes:[0,2,1,""],get_first_node_instance:[0,2,1,""],get_function_graph:[0,2,1,""],get_function_metadata:[0,2,1,""],get_function_nodes:[0,2,1,""],get_graph_properties:[0,2,1,""],get_node_attributes:[0,2,1,""],get_node_subcategory:[0,2,1,""],get_nodes_based_on_strings:[0,2,1,""],get_nodes_indegree:[0,2,1,""],get_nodes_outdegree:[0,2,1,""],get_nodes_subcategory:[0,2,1,""],get_number_of_couplings:[0,2,1,""],get_same_graph_class:[0,2,1,""],get_sources:[0,2,1,""],get_subgraph_by_function_nodes:[0,2,1,""],get_system_inputs:[0,2,1,""],get_targets:[0,2,1,""],graph_has_nested_attributes:[0,2,1,""],has_nodes:[0,2,1,""],inspect:[0,2,1,""],inspect_node:[0,2,1,""],inspect_nodes:[0,2,1,""],load_cmdows:[0,2,1,""],make_all_variables_valid:[0,2,1,""],merge_function_modes:[0,2,1,""],merge_function_nodes_based_on_modes:[0,2,1,""],merge_functions:[0,2,1,""],merge_parallel_functions:[0,2,1,""],merge_sequential_functions:[0,2,1,""],node_is_function:[0,2,1,""],node_is_hole:[0,2,1,""],node_is_objective_function:[0,2,1,""],node_is_output:[0,2,1,""],node_is_variable:[0,2,1,""],plot_adjacency_matrix:[0,2,1,""],plot_graph:[0,2,1,""],print_graph:[0,2,1,""],relabel_function_nodes:[0,2,1,""],remove_function_nodes:[0,2,1,""],save:[0,2,1,""],select_objectives_from_graph:[0,2,1,""],split_variables:[0,2,1,""]},"kadmos.graph.graph_process":{MdaoProcessGraph:[0,1,1,""],ProcessGraph:[0,1,1,""]},"kadmos.graph.graph_process.MdaoProcessGraph":{add_process:[0,2,1,""],add_process_partitions:[0,2,1,""],connect_nested_iterators:[0,2,1,""],get_lowest_psn:[0,2,1,""],get_node_text:[0,2,1,""],get_ordered_cycles:[0,2,1,""],get_process_hierarchy:[0,2,1,""],get_process_list:[0,2,1,""],inspect_process:[0,2,1,""]},"kadmos.graph.mixin_equation":{EquationMixin:[0,1,1,""]},"kadmos.graph.mixin_equation.EquationMixin":{add_equation:[0,2,1,""],add_equation_label:[0,2,1,""],add_equation_labels:[0,2,1,""],add_mathematical_function:[0,2,1,""]},"kadmos.graph.mixin_mdao":{MdaoMixin:[0,1,1,""]},"kadmos.graph.mixin_mdao.MdaoMixin":{insert_node_on_diagonal:[0,2,1,""],remove_node_from_diagonal:[0,2,1,""]},"kadmos.graph.mixin_vistoms":{VistomsMixin:[0,1,1,""]},"kadmos.graph.mixin_vistoms.VistomsMixin":{vistoms_add:[0,2,1,""],vistoms_create:[0,2,1,""]},"kadmos.knowledgebase.knowledgebase":{KnowledgeBase:[0,1,1,""]},"kadmos.knowledgebase.knowledgebase.KnowledgeBase":{get_function_dependencies:[0,2,1,""],get_function_graph:[0,2,1,""],get_kb_graphs:[0,2,1,""],get_rcg:[0,2,1,""],print_circular_connections_in_log:[0,2,1,""]},"kadmos.utilities":{general:[0,0,0,"-"],printing:[0,0,0,"-"],strings:[0,0,0,"-"],xml:[0,0,0,"-"]},"kadmos.utilities.general":{assert_dict_keys:[0,3,1,""],color_list:[0,3,1,""],convert_bytes:[0,3,1,""],dict_to_ord_dict:[0,3,1,""],export_as_json:[0,3,1,""],file_size:[0,3,1,""],file_size_MB:[0,3,1,""],filter_group_vars:[0,3,1,""],format_string_for_latex:[0,3,1,""],format_string_for_vistoms:[0,3,1,""],get_element_dict:[0,3,1,""],get_friendly_id:[0,3,1,""],get_group_vars:[0,3,1,""],get_list_entries:[0,3,1,""],get_mdao_setup:[0,3,1,""],get_uid:[0,3,1,""],get_unique_friendly_id:[0,3,1,""],hex_to_rgb:[0,3,1,""],make_camel_case:[0,3,1,""],make_plural:[0,3,1,""],make_singular:[0,3,1,""],open_file:[0,3,1,""],remove_if_exists:[0,3,1,""],test_attr_cond:[0,3,1,""],transform_data_into_strings:[0,3,1,""],transform_string_into_format:[0,3,1,""],translate_dict_keys:[0,3,1,""],translate_list:[0,3,1,""],unmake_camel_case:[0,3,1,""]},"kadmos.utilities.printing":{print_in_table:[0,3,1,""],print_indexed_list:[0,3,1,""]},"kadmos.utilities.xml":{ExtendedElement:[0,1,1,""],get_element_details:[0,3,1,""],get_uid_search_xpath:[0,3,1,""],merge:[0,3,1,""],recursively_empty:[0,3,1,""],recursively_stringify:[0,3,1,""],recursively_unique_attribute:[0,3,1,""]},"kadmos.utilities.xml.ExtendedElement":{add:[0,2,1,""],add_process_hierarchy:[0,2,1,""],clean:[0,2,1,""],findasttext:[0,2,1,""],finddict:[0,2,1,""]}},objnames:{"0":["py","module","Python module"],"1":["py","class","Python class"],"2":["py","method","Python method"],"3":["py","function","Python function"]},objtypes:{"0":"py:module","1":"py:class","2":"py:method","3":"py:function"},terms:{"13S":0,"1e4":0,"boolean":0,"byte":0,"case":0,"class":0,"default":0,"export":0,"final":0,"float":0,"function":0,"import":0,"int":0,"long":0,"new":0,"return":0,"super":0,"true":0,"try":0,"while":0,Adding:0,For:0,IDs:0,The:0,These:0,Use:0,Will:0,__all__:0,__none__:0,_check_category_a:0,_check_category_b:0,_check_category_c:0,abbreviate_keyword:0,abl:0,abov:0,absolut:0,access:0,accord:0,account:0,action:0,actual:0,add:0,add_actor:0,add_contact:0,add_contact_rol:0,add_dc:0,add_dc_general_info:0,add_dc_inputs_el:0,add_dc_outputs_el:0,add_dc_performance_info:0,add_dc_remote_component_info:0,add_dc_verif:0,add_default_descript:0,add_default_nam:0,add_edg:0,add_element_to_element_of_uid:0,add_equ:0,add_equation_label:0,add_function_problem_rol:0,add_head:0,add_inst:0,add_mathematical_funct:0,add_new_parameters_from_el:0,add_nod:0,add_objective_function_by_nod:0,add_process:0,add_process_hierarchi:0,add_process_partit:0,added:0,addit:0,address:0,adher:0,adjac:0,adjust:0,adress:0,advanc:0,aerodynam:0,aerospac:0,after:0,agil:0,aircraft:0,algorithm:0,all:0,all_keys_requir:0,all_nod:0,allow:0,allow_unconverged_coupl:0,alreadi:0,als:0,also:0,american:0,amount:0,analys:0,analysi:0,analyt:0,analyz:0,ani:0,anoth:0,append:0,appli:0,applic:0,appyl:0,arbitrari:0,architect:0,architectur:0,archiv:0,arg:0,argument:0,around:0,as_view:0,ascend:0,ascens:0,ask:0,assert:0,assert_dict_kei:0,assert_element_tag:0,assess:0,assign:0,associ:0,assum:0,ast:0,attr:0,attr_cond:0,attr_dict:0,attr_exclud:0,attr_includ:0,attr_list:0,attr_valu:0,attrb:0,attrib:0,attribut:0,automat:0,avail:0,back:0,base:0,baselin:0,basestr:0,becaus:0,becom:0,been:0,befor:0,being:0,belong:0,below:0,best:0,between:0,bisect:0,bliss:0,block:0,bool:0,both:0,bound:0,box:0,bracket:0,branch:0,build:0,busi:0,calcul:0,camel:0,camel_case_convers:0,camelcas:0,can:0,capac:0,care:0,casi:0,categori:0,certain:0,chang:0,change_graph_class:0,charact:0,characterist:0,check:0,check_cmdows_integr:0,check_for_coupl:0,check_graph:0,check_list:0,check_refer:0,check_schema:0,check_uid:0,child:0,children:0,children_to_keep:0,children_to_remov:0,choos:0,circular:0,circularconnect:0,clariti:0,clean:0,close:0,clutter:0,cmdowsvers:0,cnstrnt_var:0,collaborativeengin:0,collect:0,collid:0,collis:0,color:0,color_list:0,color_set:0,colors_based_on:0,column:0,combin:0,common:0,compani:0,compar:0,comparison:0,compet:0,compil:0,compile_pdf:0,complet:0,complex:0,compon:0,compos:0,compress:0,comput:0,condit:0,config:0,configur:0,connect:0,connect_nested_iter:0,conserv:0,consid:0,consider:0,consist:0,consistent_root:0,consol:0,constraint:0,contact:0,contact_uid:0,contain:0,content:0,contig:0,continu:0,contract:0,contracted_graph:0,contraction_level:0,contraint:[],conv:0,convent:0,converg:0,convers:0,convert:0,convert_byt:0,coor:0,copi:0,copy_a:0,copy_edg:0,copy_node_with_suffix:0,copy_typ:0,correspond:0,could:0,count:0,count_function_nod:0,countri:0,coupl:0,coupled_functions_group:0,coupling_dict:0,coupling_strength:0,cpac:0,creat:0,create_dsm:0,create_mathematical_problem:0,create_mdg:0,create_mpg:0,creation:0,creation_d:0,creator:0,creator_uid:0,criteria:0,cross:0,current:0,current_group_idx:0,custom:0,cwd:0,cycl:0,d3j:0,data:0,data_exchange_dict:0,date:0,datetim:0,dc_uid:0,decrib:0,deep:0,deepcopi:0,deepcopy_a:0,defin:0,definit:0,degre:0,delet:0,delft:0,depart:0,depend:0,deprec:0,des_var:0,descend:0,describ:0,descript:0,design:0,designcompet:0,desir:0,destin:0,destination_fold:0,detail:0,determin:0,determine_scope_constraint_funct:0,determine_scope_design_vari:0,develop:0,dewit:0,diagon:0,diagonal_po:0,diagram:0,dic:0,dict:0,dict_to_ord_dict:0,dictionari:0,differ:0,differenti:0,digraph:0,dimens:0,direct:0,directli:0,directori:0,disciplin:0,disciplinari:0,disconnect:0,disconnect_collided_target:0,disconnect_problematic_variables_from:0,disconnect_shared_sourc:0,disregard:0,distinguis:0,distribut:0,divid:0,doc:[],doe:0,doesn:0,doing:0,done:0,download:0,draw:0,dsm:0,dtc:0,dubreuil:0,due:0,duplic:0,dynam:0,each:0,easi:0,edg:0,edge_label:0,edge_or_nod:0,edu:0,either:0,element:0,element_to_add:0,elementtre:0,email:0,employe:0,empti:0,enabl:0,encod:0,end:0,end_in_iterative_nod:0,engin:0,enrich:0,ensur:0,ensure_abs_xpath:0,entri:0,entries_to_remov:0,equat:0,error:0,especi:0,etc:0,evalu:0,everi:0,everyth:0,exampl:0,exblock_uid:0,exce:0,except:0,exchang:0,exclud:0,exclus:0,execut:0,executableblock:0,exist:0,expect:0,expected_amount:0,expected_kei:0,expected_tag:0,expected_tag_new_el:0,expected_tag_uid_el:0,expected_text:0,explicit:0,export_as_json:0,express:0,extend:0,extendedel:0,extens:0,extra:0,extract:0,fals:0,feedback:0,feedforward:0,fidel:0,fidelity_level:0,fig_num:0,fig_siz:0,figur:0,file:0,file_nam:0,file_path:0,file_ref:0,file_s:0,file_size_mb:0,file_typ:0,filenam:0,filevers:0,filter:0,filter_group_var:0,filter_set:0,find:0,find_all_nod:0,findasttext:0,finddict:0,findtext:0,first:0,folder:0,follow:0,form:0,format:0,format_string_for_latex:0,format_string_for_vistom:0,formul:0,found:0,fpg:0,french:0,from:0,front:0,full:0,funcnam:0,function_nod:0,function_ord:0,function_order_method:0,function_typ:0,functiongraph:0,functionss:[],fundament:0,further:0,futur:0,gauss:0,get:0,get_adjacency_matrix:0,get_architecture_node_id:0,get_architecture_node_label:0,get_categorized_nod:0,get_contracted_graph:0,get_coupling_dictionari:0,get_coupling_matrix:0,get_design_competences_uid:0,get_direct_coupling_nod:0,get_element_detail:0,get_element_dict:0,get_element_of_uid:0,get_evalu:0,get_executable_blocks_uid:0,get_feedback_info:0,get_first_node_inst:0,get_fpg_based_on_function_nod:0,get_fpg_based_on_list_funct:0,get_fpg_based_on_sink:0,get_fpg_by_function_nod:0,get_friendly_id:0,get_function_depend:0,get_function_graph:0,get_function_metadata:0,get_function_nod:0,get_function_paths_by_object:0,get_graph_properti:0,get_group_var:0,get_highest_inst:0,get_inputs_uid:0,get_kb_graph:0,get_list_entri:0,get_lowest_psn:0,get_mathematical_functions_uid:0,get_mdao_setup:0,get_mdg:0,get_mg_function_ord:0,get_node_attribut:0,get_node_subcategori:0,get_node_text:0,get_nodes_based_on_str:0,get_nodes_indegre:0,get_nodes_outdegre:0,get_nodes_subcategori:0,get_number_of_coupl:0,get_objective_nod:0,get_ordered_cycl:0,get_outputs_uid:0,get_parameters_uid:0,get_partition_info:0,get_path_combin:0,get_possible_function_ord:0,get_process_hierarchi:0,get_process_list:0,get_rcg:0,get_same_graph_class:0,get_sourc:0,get_subgraph_by_function_nod:0,get_system_input:0,get_target:0,get_uid:0,get_uid_search_xpath:0,get_unique_friendly_id:0,get_used_parameter_uid:0,get_xpath_of_uid:0,give:0,given:0,gkhome:0,glaro:0,global:0,gov:0,graph_check_crit:0,graph_class:0,graph_data:0,graph_has_nested_attribut:0,graph_id:0,graph_kadmo:0,graph_process:0,graph_properti:0,graphml:0,group:0,group_dict:0,group_idx:0,guarante:0,guess:0,handl:0,has:0,has_nod:0,hash:0,hashabl:0,have:0,header:0,hello:0,here:0,hex:0,hex_to_rgb:0,hierarchi:0,higher_level_remov:0,highest:0,hold:0,hole:0,how:0,howev:0,html:0,http:0,identifi:0,idf:0,ids:0,ignor:0,ignore_func:0,ignore_list:0,ignore_mod:0,ignore_outdegre:0,ignorefunct:0,illustr:0,imco:[],implement:0,impose_mdao_architectur:0,includ:0,include_al:0,include_reference_data:0,include_run_tim:0,include_system_var:0,increas:0,indec:0,indegre:0,indent:0,indentifi:0,independ:0,index:0,index_bracket:0,indic:0,info:0,inform:0,initi:0,inout:0,inp:0,input:0,input_list:0,input_nod:0,inputless:0,inputs_el:0,insert:0,insert_node_on_diagon:0,insid:0,inspect:0,inspect_nod:0,inspect_process:0,instanc:0,instance_id:0,instanceid:0,instead:0,integ:0,integr:0,interest:0,invalid:0,invalid_leaf_el:0,italian:0,item:0,iter:0,itertool:0,its:0,itself:0,ivang:0,japanes:0,jet:0,job:0,job_:0,job_nam:0,json:0,just:0,kb_dir_path:0,kdm:0,keep:0,keep_empty_el:0,keep_objective_vari:0,keep_run:0,keep_tex_fil:0,kei:0,key_ord:0,keys_to_be_remov:0,keyword:0,knowledg:0,knowledge_bas:0,kwarg:0,lab:0,label:0,label_extens:0,labeling_method:0,lafag:0,languag:0,larg:0,last:0,latex:0,lead:0,leaf:0,least:0,left:0,length:0,less:0,let:0,level:0,librari:0,limit:0,line:0,link:0,list:0,list_of_funct:0,list_of_nod:0,list_of_sink:0,list_of_tool:0,literatur:0,load:0,load_cmdow:0,local:0,log:0,loop:0,lost:0,lower:0,lower_bound:0,lower_cas:0,lowest:0,maaik:0,mainli:0,maintain:0,make:0,make_all_variables_valid:0,make_camel_cas:0,make_plur:0,make_plural_opt:0,make_singular:0,mani:0,manipul:0,manual:0,map:0,mark:0,mark_as_constraint:0,mark_as_design_vari:0,mark_as_object:0,mark_as_qoi:0,master:0,match:0,mathemat:0,matplotlib:0,matrix:0,max_func:0,maxim:0,maximum:0,mda:0,mda_typ:0,mdao:0,mdao_architectur:0,mdao_setup:0,mdaodatagraph:0,mddewit:0,mdf:0,mdg:0,mdo:0,mdo_architectur:0,meet:0,merg:0,merge_func:0,merge_funct:0,merge_function_mod:0,merge_function_nodes_based_on_mod:0,merge_parallel_funct:0,merge_sequential_funct:0,merger:0,messag:0,metadata:0,method:0,meti:0,mg_function_ord:0,might:0,min_func:0,mind:0,minim:0,minimize_feedback:0,minimum:0,mixin_equ:0,mixin_mdao:0,mixin_vistom:0,mode:0,mode_id:0,modeid:0,model:0,model_definit:0,modul:0,more:0,most:0,mpg:0,multi_start:0,multidigraph:0,multigraph:0,multipl:0,must:0,mutabl:0,my_obj_fcn_nam:0,mygraph:0,n_coupling_var:0,n_disciplin:0,n_global_constraint:0,n_global_var:0,n_limit:0,n_local_constraint:0,n_local_var:0,n_part:0,name:0,named_obj_fcn:0,namespac:0,nasa:0,nativ:0,need:0,neighbor:0,nest:0,networkx:0,new_edg:0,new_label:0,newli:0,next_sequ:0,node:0,node_id:0,node_is_funct:0,node_is_hol:0,node_is_objective_funct:0,node_is_output:0,node_is_vari:0,node_label:0,node_select:0,nomin:0,nominal_valu:0,non:0,none:0,nonetyp:0,notat:0,note:0,notifi:0,notification_messag:0,ntr:0,num:0,number:0,number_of_group:0,number_of_nod:0,numer:0,obj_vars_cov:0,object:0,obtain:0,off:0,old:0,old_edg:0,one:0,onera:0,ones:0,onli:0,only_add_if_valu:0,only_feedback:0,open:0,open_fil:0,open_pdf:0,openmdao:0,oper:0,operator_uid:0,opt:0,optim:0,option:0,order:0,ordereddict:0,organ:0,organiz:0,origin:0,other:0,otherwis:0,our:0,out:0,outdegre:0,outgo:0,outp:0,output:0,output_nod:0,outputless:0,outputs_el:0,overal:0,overview:0,owner:0,owner_uid:0,packag:0,page:0,pair:0,parallel:0,param:0,param_uid:0,paramet:0,parameters_el:0,params_uid:0,part:0,partit:0,partition_graph:0,partition_rang:0,partition_vari:0,pass:0,pate:0,path:0,path_or_el:0,paus:0,pdf:0,per:0,percentag:0,perform:0,pickl:0,place:0,platform:0,pleas:0,plot:0,plot_adjacency_matrix:0,plot_combo:0,plot_graph:0,plot_pareto_front:0,plural:0,png:0,point:0,posit:0,possibl:0,post:0,post_coupling_funct:0,pre:0,pre_coupling_funct:0,precis:0,predecessor:0,prefer:0,prefix:0,presenc:0,present:0,pretti:0,pretty_print:0,previous_sequ:0,print_attribut:0,print_circular_connections_in_log:0,print_combo:0,print_contain:0,print_coupl:0,print_graph:0,print_in_log:0,print_in_t:0,print_indec:0,print_indexed_list:0,problem:0,problem_rol:0,problemat:0,process:0,process_hierarchi:0,process_step:0,produc:0,product:0,project:0,prompt:0,properti:0,propuls:0,provid:0,psg:0,psn:0,pull:0,pure:0,purpos:0,pymerg:0,pyplot:0,python:0,quantiti:0,queri:0,quickli:0,quot:0,rais:0,raise_error:0,raise_error_if_tru:0,rang:0,rce:0,rcg:0,recognis:0,recommend:0,recurs:0,recursively_empti:0,recursively_stringifi:0,recursively_unique_attribut:0,reduc:0,ref:0,refer:0,reference_fil:0,reference_valu:0,refin:0,regular:0,reinstanti:0,rel:0,relabel:0,relabel_function_nod:0,relat:0,remain:0,remi:0,remot:0,remote_engin:0,remov:0,remove_after_compress:0,remove_children_of_uid:0,remove_children_of_xpath:0,remove_contact:0,remove_data_graph_el:0,remove_element_based_on_uid:0,remove_element_based_on_xpath:0,remove_function_nod:0,remove_if_exist:0,remove_in_and_output:0,remove_input:0,remove_nod:0,remove_node_from_diagon:0,remove_output:0,remove_paramet:0,remove_parameters_el:0,remove_process_graph_el:0,remove_unused_contact:0,remove_unused_output:0,remove_workflow_el:0,renam:0,replac:0,replacement_id:0,repres:0,request:0,requir:0,resolv:0,resolve_uid:0,resourc:0,respect:0,result:0,retriev:0,revers:0,rgb:0,right:0,role:0,root:0,round:0,row1:0,row2:0,rtype:[],run:0,run_tim:0,runtim:0,safe:0,same:0,sampl:0,sampledir:0,samplefil:0,satisfi:0,save:0,save_a:0,scalar:0,schema:0,scope:0,script:0,search:0,second:0,see:0,seidel:0,select:0,select_distributed_architectur:0,select_function_combination_from:0,select_number_of_partit:0,select_objectives_from_graph:0,self:0,sellar:0,separ:0,sequenc:0,server:0,set:0,sever:0,shallow:0,share:0,shorter:0,should:0,show:0,show_now:0,shown:0,side:0,sidebar:0,signific:0,simpl:0,simpli:0,simplifi:0,simplify_equ:0,sinc:0,singl:0,single_or_multi:0,single_or_multi_execut:0,singular:0,sink:0,situat:0,size:0,slave:0,small:0,some:0,some_fold:0,some_url:0,song:0,sonic:0,sort:0,sort_bi:0,sort_kei:0,sort_nodes_for_process:0,sourc:0,space:0,specif:0,specifi:0,split:0,split_vari:0,splittabl:0,spring:0,squar:0,standard:0,start:0,start_step:0,statement:0,statu:0,step:0,still:0,stop:0,store:0,str:0,stringifi:0,structur:0,student:0,sub:0,subcategori:0,subclass:0,subel:0,subgraph:0,subgroup:0,subscript:0,subset:0,suffix:0,suit:0,summar:0,summarize_var:0,suppli:0,sure:0,svg:0,sylvain:0,symbol:0,system:0,system_input:0,system_vari:0,tabl:0,tabul:0,tag:0,take:0,taken:0,target:0,telephon:0,test:0,test_attr_cond:0,test_valu:0,tex:0,text:0,textfil:0,thank:0,thei:0,them:0,therefor:0,thi:0,think:0,third:0,though:0,through:0,thu:0,time:0,timestamp:0,titl:0,todo:[],togeth:0,tool:0,toolspecialist:0,total:0,tpwgt:0,transform:0,transform_data_into_str:0,transform_string_into_format:0,translat:0,translate_dict_kei:0,translate_list:0,tree:0,tudelft:0,tupl:0,two:0,type:0,uid:0,uid_length:0,uml:0,umn:0,unconnect:0,under:0,underscor:0,undirect:0,uniqu:0,unmake_camel_cas:0,unmark:0,unmark_vari:0,unnamed_funct:0,until:0,unus:0,updat:0,upper:0,upper_bound:0,urlsit:0,usag:0,use:0,use_d3js_node_id:0,use_png_fig:0,use_pretty_print:0,used:0,used_id:0,useful:0,user:0,user_prompt_select_opt:0,using:0,utf:0,utm:0,uxpath:0,valid:0,valu:0,var_dim:0,var_valu:0,variabl:0,variableinstance1:0,variableinstance2:0,variableinstance3:0,variableinstance4:0,varieti:0,variou:0,verif:0,verifi:0,versatil:0,version:0,vispack_vers:0,vistom:0,vistoms_add:0,vistoms_cr:0,vistoms_dir:0,vistoms_vers:0,visual:0,wai:0,wang:0,want:0,warn:0,weight:0,well:0,were:0,when:0,whether:0,which:0,window:0,wing:0,wit:0,within:0,without:0,work:0,workflow:0,write:0,write_problem_to_textfil:0,written:0,wrong:[],xdsm:0,xml_declar:0,xml_file:0,xpath:0,xpath_exclud:0,xpath_includ:0,yet:0,you:0,your:0,zero:0,zhang:0,zip:0},titles:["Welcome to KADMOS\u2019s documentation!"],titleterms:{cmdow:0,code:0,datagraph:0,document:0,equationmixin:0,fundamentalproblemgraph:0,gener:0,graph:0,kadmo:0,kadmosgraph:0,knowledgebas:0,mdaomixin:0,mdaoprocessgraph:0,print:0,processgraph:0,repositoryconnectivitygraph:0,string:0,util:0,vistomsmixin:0,welcom:0,xml:0}})
\ No newline at end of file
diff --git a/doc_source/KADMOS.rst b/doc_source/KADMOS.rst
index 0d6721f5080856020c770ae466f0043a774b101d..8edad5a3c1f972ef3cec887b87410a852b323222 100644
--- a/doc_source/KADMOS.rst
+++ b/doc_source/KADMOS.rst
@@ -38,13 +38,11 @@ KadmosGraph
~~~~~~~~~~~
.. autoclass:: kadmos.graph.graph_kadmos.KadmosGraph
:members:
- :inherited-members:
DataGraph
~~~~~~~~~
.. autoclass:: kadmos.graph.graph_data.DataGraph
:members:
- :inherited-members:
RepositoryConnectivityGraph
~~~~~~~~~~~~~~~~~~~~~~~~~~~
diff --git a/kadmos/graph/graph_data.py b/kadmos/graph/graph_data.py
index 7a4fba70fbf1f0035d195b81b66e81b92018e276..217c7b7737c2e7818eea2943ea80b0dabbeb5565 100644
--- a/kadmos/graph/graph_data.py
+++ b/kadmos/graph/graph_data.py
@@ -18,7 +18,7 @@ from types import NoneType
from kadmos.utilities.strings import get_correctly_extended_latex_label
from ..utilities import prompting
from ..utilities import printing
-from ..utilities.general import make_camel_case, unmake_camel_case, make_plural, get_list_entries, translate_dict_keys, \
+from ..utilities.general import make_camel_case, unmake_camel_case, make_plural, get_list_entries, translate_dict_keys,\
get_mdao_setup, get_group_vars
from ..utilities.testing import check
from ..utilities.plotting import AnnoteFinder
@@ -92,12 +92,12 @@ class DataGraph(KadmosGraph):
if cmdows_problem_role_attr == 'samples':
# Create problemDefinition/problemRoles/parameters/designVariables/designVariable/samples
cmdows_samples = cmdows_problem_role.add('samples')
- if self.node[graph_problem_role].get(cmdows_problem_role_attr) is not None:
- for idx, itm in enumerate(self.node[graph_problem_role].get(cmdows_problem_role_attr)):
+ if self.nodes[graph_problem_role].get(cmdows_problem_role_attr) is not None:
+ for idx, itm in enumerate(self.nodes[graph_problem_role].get(cmdows_problem_role_attr)):
cmdows_samples.add('sample', format(itm, '.12f'), attrib={'position': str(idx + 1)})
else:
cmdows_problem_role.add(self.CMDOWS_ATTRIBUTE_DICT[cmdows_problem_role_attr],
- self.node[graph_problem_role].get(cmdows_problem_role_attr),
+ self.nodes[graph_problem_role].get(cmdows_problem_role_attr),
camel_case_conversion=True)
# Create problemDefinition/problemRoles/executableBlocks
@@ -125,7 +125,8 @@ class DataGraph(KadmosGraph):
if cmdows_problem_formulation is not None:
graph_problem_form['mdao_architecture'] = cmdows_problem_formulation.findtext('mdaoArchitecture')
graph_problem_form['convergence_type'] = cmdows_problem_formulation.findtext('convergerType')
- cmdows_executable_blocks = cmdows_problem_formulation.find('executableBlocksOrder').findall('executableBlock')
+ cmdows_executable_blocks = \
+ cmdows_problem_formulation.find('executableBlocksOrder').findall('executableBlock')
cmdows_executable_blocks_order = [None] * len(list(cmdows_executable_blocks))
for cmdows_executable_block in cmdows_executable_blocks:
cmdows_executable_blocks_order[int(cmdows_executable_block.get('position')
@@ -151,10 +152,10 @@ class DataGraph(KadmosGraph):
else:
arr = list()
for cmdows_block in list(cmdows_blocks):
- if self.node.get(cmdows_block.text) is None:
+ if self.nodes.get(cmdows_block.text) is None:
# Add node if it does not exist yet
self.add_node(cmdows_block.text, category='function')
- self.node[cmdows_block.text]['problem_role'] = role
+ self.nodes[cmdows_block.text]['problem_role'] = role
arr.append(cmdows_block.text)
graph_problem_form['function_ordering'][role] = arr
@@ -167,18 +168,20 @@ class DataGraph(KadmosGraph):
cmdows_suffix = '__' + re.findall(r'(?<=__).*?(?=__)', cmdows_variable.get('uID'))[0] + '__'
# Add problem role
try:
- self.node[cmdows_parameter_uid]['problem_role'] = self.CMDOWS_ROLES_DICT_INV[cmdows_suffix]
+ self.nodes[cmdows_parameter_uid]['problem_role'] = self.CMDOWS_ROLES_DICT_INV[cmdows_suffix]
# TODO: Find a more elegant way to handle samples and parameterUID
for attribute in cmdows_variable.getchildren():
if attribute.tag == 'samples':
cmdows_samples = attribute.findall('sample')
cmdows_sample_data = [None] * len(list(cmdows_samples))
for cmdows_sample in cmdows_samples:
- cmdows_sample_data[int(cmdows_sample.get('position')) - 1] = float(cmdows_sample.text)
- self.node[cmdows_parameter_uid]['samples'] = cmdows_sample_data
+ cmdows_sample_data[int(cmdows_sample.get('position')) - 1] = \
+ float(cmdows_sample.text)
+ self.nodes[cmdows_parameter_uid]['samples'] = cmdows_sample_data
cmdows_variable.remove(attribute)
- self.node[cmdows_parameter_uid].update(cmdows.finddict(cmdows_variable, camel_case_conversion=True))
- del self.node[cmdows_parameter_uid]['parameter_u_i_d']
+ self.nodes[cmdows_parameter_uid].update(cmdows.finddict(cmdows_variable,
+ camel_case_conversion=True))
+ del self.nodes[cmdows_parameter_uid]['parameter_u_i_d']
except KeyError:
logger.error('Could not find the node "{}" for some reason when loading the CMDOWS'
.format(cmdows_parameter_uid))
@@ -189,14 +192,23 @@ class DataGraph(KadmosGraph):
# ---------------------------------------------------------------------------------------------------------------- #
# GRAPH-SPECIFIC METHODS #
# ---------------------------------------------------------------------------------------------------------------- #
- def mark_as_design_variable(self, node, lower_bound=None, upper_bound=None, samples=None, nominal_value=0.0, ignore_outdegree=False):
+ def mark_as_design_variable(self, node, lower_bound=None, upper_bound=None, samples=None, nominal_value=0.0,
+ ignore_outdegree=False):
"""Method to mark a single node as a design variable and add the required metadata for its definition.
- :param node:
- :param lower_bound:
- :param upper_bound:
- :param samples:
- :return:
+ :param node: node
+ :type node: str
+ :param lower_bound: lower bound of design variable
+ :type lower_bound: float
+ :param upper_bound: upper bound of design variable
+ :type upper_bound: float
+ :param samples: samples of design variable
+ :type samples: list
+ :param nominal_value: nominal value of design variable
+ :type nominal_value: float
+ :param ignore_outdegree: option to ignore the outdegree required
+ :type ignore_outdegree: bool
+ :returns: graph with enriched design variable node
"""
# Input assertions
assert self.has_node(node), 'Node {} is not present in the graph.'.format(node)
@@ -211,20 +223,20 @@ class DataGraph(KadmosGraph):
assert isinstance(samples, (list, NoneType)), 'Samples should be a list.'
# Mark nodes
- self.node[node]['problem_role'] = self.PROBLEM_ROLES_VARS[0]
+ self.nodes[node]['problem_role'] = self.PROBLEM_ROLES_VARS[0]
if lower_bound is not None:
- self.node[node]['valid_ranges'] = {'limit_range':{'minimum': lower_bound}}
+ self.nodes[node]['valid_ranges'] = {'limit_range': {'minimum': lower_bound}}
if upper_bound is not None:
- if 'valid_ranges' in self.node[node]:
- if 'limit_range' in self.node[node]['valid_ranges']:
- self.node[node]['valid_ranges']['limit_range']['maximum'] = upper_bound
+ if 'valid_ranges' in self.nodes[node]:
+ if 'limit_range' in self.nodes[node]['valid_ranges']:
+ self.nodes[node]['valid_ranges']['limit_range']['maximum'] = upper_bound
else:
- self.node[node]['valid_ranges']['limit_range'] = {'maximum': upper_bound}
+ self.nodes[node]['valid_ranges']['limit_range'] = {'maximum': upper_bound}
else:
- self.node[node]['valid_ranges'] = {'limit_range': {'maximum': upper_bound}}
+ self.nodes[node]['valid_ranges'] = {'limit_range': {'maximum': upper_bound}}
if samples is not None:
- self.node[node]['samples'] = samples
- self.node[node]['nominal_value'] = nominal_value
+ self.nodes[node]['samples'] = samples
+ self.nodes[node]['nominal_value'] = nominal_value
return
@@ -234,17 +246,19 @@ class DataGraph(KadmosGraph):
:param nodes: list of nodes present in the graph
:type nodes: list or str
:param lower_bounds: list of lower bound values
- :type lower_bounds: list or numbers.Number
+ :type lower_bounds: list, numbers.Number
:param upper_bounds: list of upper bounds
- :type upper_bounds: list or numbers.Number
+ :type upper_bounds: list, numbers.Number
:param samples: nested list of kadmos values
:type samples: list
:param nominal_values: list of nominal values
- :type nominal_values: list or numbers.Number
+ :type nominal_values: list, numbers.Number
+ :return: graph with enriched design variable nodes
"""
# Input assertions
- assert isinstance(nodes, list), 'Input nodes should be a list of graph nodes. Use mark_as_design_variable for single node.'
+ assert isinstance(nodes, list), 'Input nodes should be a list of graph nodes. Use mark_as_design_variable for' \
+ ' single node.'
if isinstance(lower_bounds, numbers.Number) or lower_bounds is None:
lower_bounds = [lower_bounds]*len(nodes)
else:
@@ -267,7 +281,7 @@ class DataGraph(KadmosGraph):
assert len(samples) == len(nodes), 'Number of nominal values is not equal to the number of nodes.'
# Mark nodes
- for node,lb,ub,sm,nv in zip(nodes, lower_bounds, upper_bounds, samples, nominal_values):
+ for node, lb, ub, sm, nv in zip(nodes, lower_bounds, upper_bounds, samples, nominal_values):
self.mark_as_design_variable(node, lower_bound=lb, upper_bound=ub, samples=sm, nominal_value=nv)
return
@@ -277,13 +291,16 @@ class DataGraph(KadmosGraph):
:param node: variable node
:type node: basestring
+ :param remove_unused_outputs: option to remove unused outputs
+ :type remove_unused_outputs: bool
+ :return: graph enriched with objective node
"""
# Input assertions
assert self.has_node(node), 'Node %s is not present in the graph.' % node
# Mark node
- self.node[node]['problem_role'] = self.PROBLEM_ROLES_VARS[1]
+ self.nodes[node]['problem_role'] = self.PROBLEM_ROLES_VARS[1]
if remove_unused_outputs:
self.remove_unused_outputs()
@@ -294,14 +311,18 @@ class DataGraph(KadmosGraph):
"""Method to mark a node as a constraint.
:param node: node to be marked (on the left side of the operator
- :type nodes: str
+ :type node: str
:param operator: constraint operator or list of constraint operators
:type operator: str or string list
- :param reference_value: value on the right side of the operator or list of values corresponding to the list of operators
+ :param reference_value: value on the right side of the operator or list of values corresponding to the list of
+ operators
:type reference_value: numbers.Number or list
+ :param remove_unused_outputs: option to remove unused outputs
+ :type remove_unused_outputs: bool
+ :returns: graph with enriched constraint node
"""
- #dict of inequality operators
+ # dict of inequality operators
operators = {'>': oper.gt,
'>=': oper.ge,
'<': oper.lt,
@@ -318,17 +339,19 @@ class DataGraph(KadmosGraph):
'provide equal sized lists.'.format(len(operator),
len(reference_value))
for op in operator:
- assert operators[op](1,0) or operators[op](0,1), 'Operator has to be one of the following: >, >=, < or <='
+ assert operators[op](1, 0) or operators[op](0, 1), 'Operator has to be one of the following: >, >=, <' \
+ ' or <='
else:
raise AssertionError('operator input is of wrong type {}.'.format(type(operator)))
assert isinstance(reference_value, (numbers.Number, list)), 'Reference value is not a number or list.'
- #check if multiple bounds are used correctly.
+ # check if multiple bounds are used correctly.
if isinstance(operator, list):
- if (operators[operator[0]](0,1) and operators[operator[1]](1,0)) or ((operators[operator[0]](1,0) and operators[operator[1]](0,1))):
+ if (operators[operator[0]](0, 1) and operators[operator[1]](1, 0)) or ((operators[operator[0]](1, 0) and
+ operators[operator[1]](0, 1))):
a = reference_value[0]
b = reference_value[1]
- if operators[operator[1]](a,b) and operators[operator[0]](b,a):
+ if operators[operator[1]](a, b) and operators[operator[0]](b, a):
pass
else:
raise IOError("ERROR: x {} {} and x {} {} are not consistent as "
@@ -338,17 +361,17 @@ class DataGraph(KadmosGraph):
"Please correct the operators provided".format(operator[0], operator[1]))
# Mark nodes
- self.node[node]['problem_role'] = self.PROBLEM_ROLES_VARS[2]
+ self.nodes[node]['problem_role'] = self.PROBLEM_ROLES_VARS[2]
if isinstance(operator, basestring):
- self.node[node]['constraint_operator'] = operator
- self.node[node]['reference_value'] = reference_value
+ self.nodes[node]['constraint_operator'] = operator
+ self.nodes[node]['reference_value'] = reference_value
else:
- self.node[node]['constraint_operator'] = ';'.join(operator)
- self.node[node]['reference_value'] = ';'.join([str(item) for item in reference_value])
+ self.nodes[node]['constraint_operator'] = ';'.join(operator)
+ self.nodes[node]['reference_value'] = ';'.join([str(item) for item in reference_value])
if operator == '==':
- self.node[node]['constraint_type'] = 'equality'
+ self.nodes[node]['constraint_type'] = 'equality'
else:
- self.node[node]['constraint_type'] = 'inequality'
+ self.nodes[node]['constraint_type'] = 'inequality'
if remove_unused_outputs:
self.remove_unused_outputs()
@@ -358,15 +381,23 @@ class DataGraph(KadmosGraph):
def mark_as_constraints(self, nodes, operators, reference_values, remove_unused_outputs=False):
"""Method to mark multiple nodes as constraints.
- :param nodes: list of nodes to be marked.
+ :param nodes: nodes to be marked.
+ :type nodes: list
:param operators: operators to be implemented (as list per node or as single operator for all)
+ :type operators: str, list
:param reference_values: reference values to be used (as list of values per node or as single value for all)
+ :type reference_values: float, list
+ :param remove_unused_outputs: option to remove unused outputs
+ :type remove_unused_outputs: bool
:return: graph with enriched constraint nodes
+
+ Operators: '==', '>', '<', '>=' and '<='
"""
# Input assertions
# poss_ops = ['==', '>', '<', '>=', '<=']
- assert isinstance(nodes, list), 'Input nodes should be a list of graph nodes. Use mark_as_constraint for single node.'
+ assert isinstance(nodes, list), 'Input nodes should be a list of graph nodes. Use mark_as_constraint for ' \
+ 'single node.'
if isinstance(operators, str):
operators = [operators]*len(nodes)
else:
@@ -376,9 +407,10 @@ class DataGraph(KadmosGraph):
reference_values = [reference_values]*len(nodes)
else:
assert isinstance(reference_values, list), 'Reference values should be a list.'
- assert len(reference_values) == len(nodes), 'Number of reference values is not equal to the number of nodes.'
- for node,op,ref in zip(nodes,operators,reference_values):
- self.mark_as_constraint(node,op,ref)
+ assert len(reference_values) == len(nodes), 'Number of reference values is not equal to the number of ' \
+ 'nodes.'
+ for node, op, ref in zip(nodes, operators, reference_values):
+ self.mark_as_constraint(node, op, ref)
if remove_unused_outputs:
self.remove_unused_outputs()
@@ -390,6 +422,8 @@ class DataGraph(KadmosGraph):
:param nodes: list of nodes present in the graph
:type nodes: list
+ :param remove_unused_outputs: option to remove unused outputs
+ :type remove_unused_outputs: bool
"""
# Input assertions
@@ -399,7 +433,7 @@ class DataGraph(KadmosGraph):
# Mark nodes
for node in nodes:
- self.node[node]['problem_role'] = self.PROBLEM_ROLES_VARS[3]
+ self.nodes[node]['problem_role'] = self.PROBLEM_ROLES_VARS[3]
if remove_unused_outputs:
self.remove_unused_outputs()
@@ -411,32 +445,33 @@ class DataGraph(KadmosGraph):
:param node: variable node to be unmarked
:type node: basestring
+ :return: graph with unmarked node
"""
# Input assertions
assert isinstance(node, basestring)
assert self.has_node(node), 'Node {} is not present in the graph.'.format(node)
- assert self.node[node]['category'] == 'variable', 'Node {} should be of category variable.'.format(node)
+ assert self.nodes[node]['category'] == 'variable', 'Node {} should be of category variable.'.format(node)
# Unmark design variable
- if 'problem_role' in self.node[node]:
- pr = self.node[node]['problem_role']
+ if 'problem_role' in self.nodes[node]:
+ pr = self.nodes[node]['problem_role']
if pr == self.PROBLEM_ROLES_VARS[0]: # design variable
- del self.node[node]['problem_role']
- if 'valid_ranges' in self.node[node]:
- del self.node[node]['valid_ranges']
- if 'samples' in self.node[node]:
- del self.node[node]['samples']
- if 'nominal_value' in self.node[node]:
- del self.node[node]['nominal_value']
+ del self.nodes[node]['problem_role']
+ if 'valid_ranges' in self.nodes[node]:
+ del self.nodes[node]['valid_ranges']
+ if 'samples' in self.nodes[node]:
+ del self.nodes[node]['samples']
+ if 'nominal_value' in self.nodes[node]:
+ del self.nodes[node]['nominal_value']
elif pr == self.PROBLEM_ROLES_VARS[1]: # objective
- del self.node[node]['problem_role']
+ del self.nodes[node]['problem_role']
elif pr == self.PROBLEM_ROLES_VARS[2]: # constraint
- del self.node[node]['problem_role']
- del self.node[node]['constraint_operator']
- del self.node[node]['reference_value']
+ del self.nodes[node]['problem_role']
+ del self.nodes[node]['constraint_operator']
+ del self.nodes[node]['reference_value']
elif pr == self.PROBLEM_ROLES_VARS[3]: # quantity of interest
- del self.node[node]['problem_role']
+ del self.nodes[node]['problem_role']
else:
raise AssertionError('Invalid problem role {} found on variable node {}'.format(pr, node))
@@ -450,7 +485,7 @@ class DataGraph(KadmosGraph):
output_nodes = self.find_all_nodes(subcategory='all outputs')
removed_nodes = []
for output_node in output_nodes:
- if 'problem_role' not in self.node[output_node]:
+ if 'problem_role' not in self.nodes[output_node]:
self.remove_node(output_node)
removed_nodes.append(output_node)
return removed_nodes
@@ -490,7 +525,8 @@ class DataGraph(KadmosGraph):
if node_selection:
function_order = node_selection
else:
- assert 'function_order' in graph.graph['problem_formulation'], 'function_order must be given as attribute.'
+ assert 'function_order' in graph.graph['problem_formulation'], 'function_order must be given as ' \
+ 'attribute.'
function_order = graph.graph['problem_formulation']['function_order']
elif function_order_method == 'random':
function_order = graph.find_all_nodes(category='function')
@@ -514,17 +550,18 @@ class DataGraph(KadmosGraph):
return coupling_matrix
def get_coupling_dictionary(self):
- """ Function to get a coupling dictionary. For each function node, the dictionary indicates from which function
- nodes it gets its input and the number of variables it gets.
-
- F2 ==> x1, x2 ==> F1
- F3 ==> x3 ==> F1
-
- Will give:
- {F1: {F2: 2, F3: 1}}
+ """ Function to get a coupling dictionary.
:return: coupling dictionary
:rtype: dict
+
+ For each function node, the dictionary indicates from which function
+ nodes it gets its input and the number of variables it gets.
+
+ * F2 ==> x1, x2 ==> F1
+ * F3 ==> x3 ==> F1
+
+ Will give: {F1: {F2: 2, F3: 1}}
"""
coupling_dict = dict()
@@ -551,8 +588,8 @@ class DataGraph(KadmosGraph):
:type multi_start: int
:param check_graph: check whether graph has problematic variables
:type check_graph: bool
- :return Possible function order
- :rtype list
+ :return: Possible function order
+ :rtype: list
"""
# Input assertions
@@ -641,10 +678,10 @@ class DataGraph(KadmosGraph):
"""
Method to get the highest instance of a node.
- :param node:
- :type node:
- :return:
- :rtype:
+ :param node: node
+ :type node: str
+ :return: highest instance of the node
+ :rtype: int
"""
assert 'instance' in self.nodes[node], 'node {} does not have the expected attribute "instance".'.format(node)
highest_instance = self.nodes[node]['instance']
@@ -665,8 +702,8 @@ class DataGraph(KadmosGraph):
:param nodes: function nodes to sort
:type nodes: list
- :return nodes in sorted order
- :rtype list
+ :return: nodes in sorted order
+ :rtype: list
"""
# Input assertions
@@ -711,10 +748,10 @@ class DataGraph(KadmosGraph):
:type multi_start: int
:param get_evaluations: option to give the number of evaluations as output
:type get_evaluations: bool
- :return function order
- :rtype list
- :return number of evaluations
- :rtype int
+ :return: function order
+ :rtype: list
+ :return: number of evaluations
+ :rtype: list
"""
# TODO: check if input nodes > 1
@@ -796,8 +833,8 @@ class DataGraph(KadmosGraph):
:param nodes: nodes that need to be ordered
:type nodes: list
- :return function order
- :rtype list
+ :return: function order
+ :rtype: list
"""
# Calculate the number of runs that are needed and give a warning when it exceeds a threshold
@@ -830,8 +867,8 @@ class DataGraph(KadmosGraph):
:param nodes: nodes that need to be ordered
:type nodes: list
- :return function order
- :rtype list
+ :return: function order
+ :rtype: list
"""
converged = False
@@ -892,8 +929,8 @@ class DataGraph(KadmosGraph):
:param nodes: nodes that need to be ordered
:type nodes: list
- :return function order
- :rtype list
+ :return: function order
+ :rtype: list
"""
converged = False
@@ -947,8 +984,8 @@ class DataGraph(KadmosGraph):
:param nodes: nodes that need to be ordered
:type nodes: list
- :return function order
- :rtype list
+ :return: function order
+ :rtype: list
"""
active_branches = []
@@ -1001,8 +1038,8 @@ class DataGraph(KadmosGraph):
:type branch: list
:param nodes: the nodes that are considered in the sequencing problem
:type nodes: list
- :return lower bound
- :rtype int
+ :return: lower bound
+ :rtype: int
"""
# Get a random function order with the nodes of the branch at the start
@@ -1050,7 +1087,7 @@ class DataGraph(KadmosGraph):
toolbox.register('population', tools.initRepeat, list, toolbox.individual)
toolbox.register('mate', tools.cxOrdered)
toolbox.register('mutate', tools.mutShuffleIndexes, indpb=INDPB)
- #toolbox.register('select', tools.selBest)
+ # toolbox.register('select', tools.selBest)
toolbox.register('select', tools.selTournament, tournsize=3)
toolbox.register('evaluate', self._get_fitness_individual, mapping=mapping, coupling_dict=coupling_dict)
@@ -1083,15 +1120,17 @@ class DataGraph(KadmosGraph):
function_order.append(mapping[idx])
feedback, size = self.get_feedback_info(function_order, coupling_dict)
- return feedback,
+ return feedback
def get_feedback_info(self, function_order, coupling_dict):
"""Function to determine the number of feedback loops for a given function order
:param function_order: function order of the nodes
:type function_order: list
- :return number of feedback loops
- :rtype int
+ :param coupling_dict: function couplings
+ :type coupling_dict: dict
+ :return: number of feedback loops
+ :rtype: int
"""
# Determine number of feedback loops
@@ -1135,12 +1174,19 @@ class RepositoryConnectivityGraph(DataGraph):
Complexity Problem', Mathematical Problems in Engineering, 2017.
:param n_disciplines: Number of disciplines
+ :type n_disciplines: int
:param coupling_strength: percentage of couplings, 0 no couplings, 1 all possible couplings
+ :type coupling_strength: int
:param n_global_var: Number of global design variables
+ :type n_global_var: int
:param n_local_var: Number of local design variables for each discipline
+ :type n_local_var: int
:param n_coupling_var: Number of output variables for each discipline
+ :type n_coupling_var: int
:param n_local_constraints: Number of local constraints
+ :type n_local_constraints: int
:param n_global_constraints: Number of global constraints
+ :type n_global_constraints: int
:param B: relation between the coupling variables
:param C: relation between the global design variables and coupling variables
:param D: relation between the local design variables and coupling variables
@@ -1151,10 +1197,14 @@ class RepositoryConnectivityGraph(DataGraph):
:param I: relation between the local design variables and global constraints
:param J: relation between the coupling variables and global constraints
:param r: positive scalars to be used for the local constraints
+ :type r: float
:param s: positive scalars to be used for the global constraints
+ :type s: float
:param write_problem_to_textfile: option to write generated problem to a textfile
+ :type write_problem_to_textfile: bool
"""
+ # TODO Imco add type of B-J in docstring
# Input assertions
assert not B if coupling_strength else B is not None, 'Either the coupling strength or the B-matrix must be ' \
'given'
@@ -1602,22 +1652,25 @@ class RepositoryConnectivityGraph(DataGraph):
"""This function takes an arbitrary amount of objective nodes as graph sinks and returns all path combinations
of tools.
+ :param args: arbitrary amount of objective nodes
+ :type args: list, str
+ :param kwargs: filter options to limit possible path combinations
+ :type kwargs: bool, str
+ :return: all possible FPG path combinations for the provided objective nodes
+
If no arguments are given, user is prompted to select objectives from the graph.
- The tool combinations are found using the function itertools.product() and can lead to significant computation
- times for large graphs. If this is the case, the user is prompted whether to continue or not.
+ .. hint:: The tool combinations are found using the function itertools.product() and can lead to significant
+ computation times for large graphs. If this is the case, the user is prompted whether to continue or not.
A variety of filters can be applied to the search of possible tools combinations, some of which reduce the
computation time.
- kwargs:
- obj_vars_covered - ensures that all objective variables are used in tool configurations
- ignore_funcs - ignores functions for the config
- source - source node; if provided, must be in config
+ .. note:: kwargs:
- :param args: arbitrary amount of objective nodes
- :param kwargs: filter options to limit possible path combinations
- :return: all possible FPG path combinations for the provided objective nodes
+ * obj_vars_covered - ensures that all objective variables are used in tool configurations
+ * ignore_funcs - ignores functions for the config
+ * source - source node; if provided, must be in config
"""
# TODO: Add filters
@@ -1723,17 +1776,20 @@ class RepositoryConnectivityGraph(DataGraph):
def get_path_combinations(self, *args, **kwargs):
"""This function takes lists of subsets and generates all possible combinations between them.
+ :param args: lists of subsets that will be used to find configurations
+ :type args: list
+ :param kwargs: see optional arguments
+ :type kwargs: int
+ :return: set of all unique path combinations
+
This is done by using the itertools.product() function. If the amount of expected evaluations exceeds a pre-set
minimum, the user will be asked if to continue or not; because the process can take a long time and use up many
resources.
- Optional arguments:
- min_func: minimum amount of functions in each configuration
- max_func: maximum amount of functions in each configuration
+ .. note:: Optional arguments:
- :param args: lists of subsets that will be used to find configurations
- :type args: list
- :return: set of all unique path combinations
+ * min_func: minimum amount of functions in each configuration
+ * max_func: maximum amount of functions in each configuration
"""
# get list of subsets
@@ -1917,10 +1973,27 @@ class RepositoryConnectivityGraph(DataGraph):
def select_function_combination_from(self, *args, **kwargs):
"""This function takes all provided workflow configurations and lists them according to their characteristics.
- The user can then choose the workflow configuration from the list.
+ :param args: workflow configurations
+ :type args: list
+ :param kwargs: see optional arguments
+ :type kwargs: bool, str, int
+ :return: sorted list of workflow configurations
+ :rtype: list
+
+ .. note:: Optional arguments:
+
+ * 'print_combos' - option to print the combinations in a table
+ * 'n_limit' - amount of combinations that will be printed in the table
+ * 'sort_by' - characteristic to sort workflow configurations by
+ * 'sort_by ascending' - option to sort workflow configurations by ascension
+ * 'plot_combos' - option to plot the combinations in a graph
+
+ The user can choose the workflow configuration from the list.
+
A warning is given to the user if the amount of total configurations exceeds n = 1e4.
Print limit is set to [0-20] by default.
- sort_by must be one of ["couplings", "system_inputs", "edges", "nodes"].
+
+ .. note:: sort_by must be one of ["couplings", "system_inputs", "edges", "nodes"].
"""
# make sure arguments provided
@@ -2030,6 +2103,8 @@ class RepositoryConnectivityGraph(DataGraph):
def get_fpg_by_function_nodes(self, *args):
"""This function creates a new (FPG)-graph based on the selected function nodes.
+ :param args: arbitrary amount of graph nodes
+ :type args: list, str
:return: new fpg graph
:rtype: FundamentalProblemGraph
"""
@@ -2166,7 +2241,7 @@ class FundamentalProblemGraph(DataGraph, KeChainMixin):
category='A',
i=i)
for out_node in out_nodes:
- category_check, i_not = check('problem_role' not in self.node[out_node],
+ category_check, i_not = check('problem_role' not in self.nodes[out_node],
'The attribute problem_role is missing on the output node %s.'
% str(out_node),
status=category_check,
@@ -2174,7 +2249,7 @@ class FundamentalProblemGraph(DataGraph, KeChainMixin):
i=i)
i += 1
for func_node in func_nodes:
- category_check, i_not = check('problem_role' not in self.node[func_node],
+ category_check, i_not = check('problem_role' not in self.nodes[func_node],
'The attribute problem_role is missing on the function node %s.'
% str(func_node),
status=category_check,
@@ -2535,14 +2610,14 @@ class FundamentalProblemGraph(DataGraph, KeChainMixin):
if self.graph['problem_formulation']['doe_settings']['doe_method'] == self.OPTIONS_DOE_METHODS[3]:
all_samples = []
for des_var_node in des_var_nodes:
- category_check, i_not = check('samples' not in self.node[des_var_node],
+ category_check, i_not = check('samples' not in self.nodes[des_var_node],
'The samples attributes is missing for design variable node'
' %s.' % des_var_node,
status=category_check,
category='C',
i=i)
if category_check:
- all_samples.append(self.node[des_var_node]['samples'])
+ all_samples.append(self.nodes[des_var_node]['samples'])
i += 1
sample_lengths = [len(item) for item in all_samples]
# Check whether all samples have the same length
@@ -2555,7 +2630,6 @@ class FundamentalProblemGraph(DataGraph, KeChainMixin):
# Return
return category_check, i
-
# ---------------------------------------------------------------------------------------------------------------- #
# GRAPH SPECIFIC METHODS #
# ---------------------------------------------------------------------------------------------------------------- #
@@ -2613,19 +2687,19 @@ class FundamentalProblemGraph(DataGraph, KeChainMixin):
function_ordering[self.FUNCTION_ROLES[2]] = list()
if left_ind is not None:
for i in range(0, left_ind):
- self.node[function_order[i]]['problem_role'] = self.FUNCTION_ROLES[0]
+ self.nodes[function_order[i]]['problem_role'] = self.FUNCTION_ROLES[0]
function_ordering[self.FUNCTION_ROLES[0]].append(function_order[i])
for i in range(left_ind, low_ind+1):
- self.node[function_order[i]]['problem_role'] = self.FUNCTION_ROLES[1]
+ self.nodes[function_order[i]]['problem_role'] = self.FUNCTION_ROLES[1]
function_ordering[self.FUNCTION_ROLES[1]].append(function_order[i])
if low_ind < len(function_order)-1:
for i in range(low_ind+1, len(function_order)):
- self.node[function_order[i]]['problem_role'] = self.FUNCTION_ROLES[2]
+ self.nodes[function_order[i]]['problem_role'] = self.FUNCTION_ROLES[2]
function_ordering[self.FUNCTION_ROLES[2]].append(function_order[i])
else:
# noinspection PyUnboundLocalVariable
for function in function_order:
- self.node[function]['problem_role'] = self.FUNCTION_ROLES[0]
+ self.nodes[function]['problem_role'] = self.FUNCTION_ROLES[0]
function_ordering[self.FUNCTION_ROLES[0]].append(function)
# Add function ordering to the graph as well
@@ -2794,10 +2868,10 @@ class FundamentalProblemGraph(DataGraph, KeChainMixin):
:type partitions: dict
:param include_run_time:
:type include_run_time: bool
- :return partition_variables:
- :rtype partition_variables: list of sets
- :return system_variables:
- :rtype system_variables: set
+ :return: partition_variables:
+ :rtype: partition_variables: list of sets
+ :return: system_variables:
+ :rtype: system_variables: set
"""
# Get complete function order of nodes in the partitions
@@ -2929,7 +3003,7 @@ class FundamentalProblemGraph(DataGraph, KeChainMixin):
def select_distributed_architecture(self):
""" Function for easy selection of a distributed architecture for a partitioned graph.
- :return Extended problem formulation
+ :return: Extended problem formulation
"""
# Check if graph is partitioned
@@ -3041,7 +3115,8 @@ class FundamentalProblemGraph(DataGraph, KeChainMixin):
if mdao_arch == self.OPTIONS_ARCHITECTURES[7]: # Distributed-conv
mdao_arch = self.graph['problem_formulation']['system_architecture']
- if mdao_arch in self.OPTIONS_ARCHITECTURES[2:7]+self.OPTIONS_ARCHITECTURES[8:10]: # IDF, MDF, unc-OPT, unc-DOE, con-DOE, CO, BLISS-2000
+ # OPTIONS_ARCHITECTURE: IDF, MDF, unc-OPT, unc-DOE, con-DOE, CO, BLISS-2000
+ if mdao_arch in self.OPTIONS_ARCHITECTURES[2:7]+self.OPTIONS_ARCHITECTURES[8:10]:
del mg_function_ordering[self.FUNCTION_ROLES[0]]
if pre_functions:
target_set = set()
@@ -3105,7 +3180,8 @@ class FundamentalProblemGraph(DataGraph, KeChainMixin):
return mdg
- def determine_scope_design_variables(self, des_vars=None, coupled_functions_groups=None, pre_coupling_functions=None):
+ def determine_scope_design_variables(self, des_vars=None, coupled_functions_groups=None,
+ pre_coupling_functions=None):
"""
Method to determine the scope (global, local) of the design variables and to determine to which coupled function
groups the design variable belongs.
@@ -3114,6 +3190,8 @@ class FundamentalProblemGraph(DataGraph, KeChainMixin):
:type des_vars: list
:param coupled_functions_groups: list with list of coupled function groups
:type coupled_functions_groups: list
+ :param pre_coupling_functions: list with list of pre-coupled function groups
+ :type pre_coupling_functions: list
:return: list of global design variables, list of local design variables, dictionary with dependencies
:rtype: tuple
"""
@@ -3127,10 +3205,12 @@ class FundamentalProblemGraph(DataGraph, KeChainMixin):
des_vars = self.check_and_get_design_variables(des_vars=des_vars)
# Get and check coupled function groups
- coupled_functions_groups = self.check_and_get_coupled_functions_groups(coupled_functions_groups=coupled_functions_groups)
+ coupled_functions_groups = \
+ self.check_and_get_coupled_functions_groups(coupled_functions_groups=coupled_functions_groups)
# Get and check pre-coupling functions
- pre_coupling_functions = self.check_and_get_pre_coupling_functions(pre_coupling_functions=pre_coupling_functions)
+ pre_coupling_functions = \
+ self.check_and_get_pre_coupling_functions(pre_coupling_functions=pre_coupling_functions)
# Determine the scope of the design variables
for des_var in des_vars:
@@ -3156,18 +3236,17 @@ class FundamentalProblemGraph(DataGraph, KeChainMixin):
def determine_scope_constraint_functions(self, cnstrnt_vars=None, coupled_functions_groups=None,
post_coupling_functions=None):
- """
- Method to determine the scope (global, local) of the contraint functions based on the constraint variables and
- to determine on which coupled function groups the constraint function depends.
+ """Method to determine the scope (global, local) of the constraint functions based on the constraint variables
+ and to determine on which coupled function groups the constraint function depends.
:param cnstrnt_vars: (optional) constraint variables to be determined
:type cnstrnt_vars: list
:param coupled_functions_groups: (optional) list of lists with coupled functions groups
:type coupled_functions_groups: list
- :param post_coupling_functions: (optional) list with post-coupling functionss
+ :param post_coupling_functions: (optional) list with post-coupling functions
:type post_coupling_functions: list
- :return: global constraint variables and functions, local constraint variables and functions, groups indices per
- constraint function
+ :return: global constraint variables and functions, local constraint variables and functions, groups indices
+ per constraint function
:rtype: tuple
"""
@@ -3180,10 +3259,12 @@ class FundamentalProblemGraph(DataGraph, KeChainMixin):
cnstrnt_funcs_group_idxs = dict()
# Get and check coupled function groups
- coupled_functions_groups = self.check_and_get_coupled_functions_groups(coupled_functions_groups=coupled_functions_groups)
+ coupled_functions_groups = \
+ self.check_and_get_coupled_functions_groups(coupled_functions_groups=coupled_functions_groups)
# Get and check post-coupling functions
- post_coupling_functions = self.check_and_get_post_coupling_functions(post_coupling_functions=post_coupling_functions)
+ post_coupling_functions = \
+ self.check_and_get_post_coupling_functions(post_coupling_functions=post_coupling_functions)
# Associate constraint variables with the constraint functions
cnstrnt_funcs = dict()
@@ -3204,8 +3285,8 @@ class FundamentalProblemGraph(DataGraph, KeChainMixin):
linked_groups.append(idx)
break
if len(linked_groups) == 0:
- raise AssertionError(
- "Constraint function {} could not be associated with a coupled function group.".format(cnstrnt_func))
+ raise AssertionError("Constraint function {} could not be associated with a coupled function "
+ "group.".format(cnstrnt_func))
elif len(linked_groups) == 1:
local_cnstrnt_funcs.append(cnstrnt_func)
local_cnstrnt_vars.extend(cnstrnt_funcs[cnstrnt_func])
@@ -3216,13 +3297,15 @@ class FundamentalProblemGraph(DataGraph, KeChainMixin):
cnstrnt_vars_group_idxs[cnstrnt_var] = linked_groups
cnstrnt_funcs_group_idxs[cnstrnt_func] = linked_groups
- return global_cnstrnt_vars, global_cnstrnt_funcs, local_cnstrnt_vars, local_cnstrnt_funcs, cnstrnt_vars_group_idxs, cnstrnt_funcs_group_idxs
+ return global_cnstrnt_vars, global_cnstrnt_funcs, local_cnstrnt_vars, local_cnstrnt_funcs, \
+ cnstrnt_vars_group_idxs, cnstrnt_funcs_group_idxs
def get_group_couplings(self, coupled_functions_groups=None):
# TODO: Add docstring
# Get and check coupled function groups
- coupled_functions_groups = self.check_and_get_coupled_functions_groups(coupled_functions_groups=coupled_functions_groups)
+ coupled_functions_groups = \
+ self.check_and_get_coupled_functions_groups(coupled_functions_groups=coupled_functions_groups)
all_coupled_functions = [item for sublist in coupled_functions_groups for item in sublist]
# Create subgraph of just the coupled functions
@@ -3256,7 +3339,8 @@ class FundamentalProblemGraph(DataGraph, KeChainMixin):
'Node {} is does not have problem_role {}.'.format(fun, self.FUNCTION_ROLES[2])
# Get and check coupled function groups
- coupled_functions_groups = self.check_and_get_coupled_functions_groups(coupled_functions_groups=coupled_functions_groups)
+ coupled_functions_groups = \
+ self.check_and_get_coupled_functions_groups(coupled_functions_groups=coupled_functions_groups)
all_coupled_functions = [item for sublist in coupled_functions_groups for item in sublist]
# Create subgraph of just the coupled and system-level post-coupling functions
@@ -3281,7 +3365,8 @@ class FundamentalProblemGraph(DataGraph, KeChainMixin):
return sys_post_couplings, sys_post_couplings_groups_idx
- def get_system_level_functions(self, global_objective_function, global_cnstrnt_functions, mg_function_ordering=None):
+ def get_system_level_functions(self, global_objective_function, global_cnstrnt_functions,
+ mg_function_ordering=None):
# TODO: Add docstring
# Initiate dictionary
@@ -3366,11 +3451,13 @@ class FundamentalProblemGraph(DataGraph, KeChainMixin):
assert isinstance(pre_coupling_functions, list), \
'The pre_coupling_functions input should be a list.'
for pre_coupling_function in pre_coupling_functions:
- assert self.has_node(pre_coupling_function), 'Function {} is not a node in the graph.'.format(pre_coupling_function)
- assert 'problem_role' in self.node[pre_coupling_function], \
+ assert self.has_node(pre_coupling_function), \
+ 'Function {} is not a node in the graph.'.format(pre_coupling_function)
+ assert 'problem_role' in self.nodes[pre_coupling_function], \
'Function {} does not have a problem role.'.format(pre_coupling_function)
- assert self.node[pre_coupling_function]['problem_role'] == self.FUNCTION_ROLES[0], \
- 'Pre-coupled function {} lacks the problem role "{}".'.format(pre_coupling_function, self.FUNCTION_ROLES[0])
+ assert self.nodes[pre_coupling_function]['problem_role'] == self.FUNCTION_ROLES[0], \
+ 'Pre-coupled function {} lacks the problem ' \
+ 'role "{}".'.format(pre_coupling_function, self.FUNCTION_ROLES[0])
return pre_coupling_functions
def check_and_get_coupled_functions_groups(self, coupled_functions_groups=None):
@@ -3383,9 +3470,9 @@ class FundamentalProblemGraph(DataGraph, KeChainMixin):
'The elements of the coupled_functions_groups should be lists.'
for func in coupled_functions_group:
assert self.has_node(func), 'Function {} is not a node in the graph.'.format(func)
- assert 'problem_role' in self.node[func], \
+ assert 'problem_role' in self.nodes[func], \
'Function {} does not have a problem role.'.format(func)
- assert self.node[func]['problem_role'] == self.FUNCTION_ROLES[1], \
+ assert self.nodes[func]['problem_role'] == self.FUNCTION_ROLES[1], \
'Coupled function {} lacks the problem role "{}".'.format(func, self.FUNCTION_ROLES[1])
assert func not in functions_found, \
'Coupled function {} is present multiple times in the coupled_functions_group.'.format(func)
@@ -3398,20 +3485,22 @@ class FundamentalProblemGraph(DataGraph, KeChainMixin):
assert isinstance(post_coupling_functions, list), \
'The post_coupling_functions input should be a list.'
for post_coupling_function in post_coupling_functions:
- assert self.has_node(post_coupling_function), 'Function {} is not a node in the graph.'.format(post_coupling_function)
- assert 'problem_role' in self.node[post_coupling_function], \
+ assert self.has_node(post_coupling_function), \
+ 'Function {} is not a node in the graph.'.format(post_coupling_function)
+ assert 'problem_role' in self.nodes[post_coupling_function], \
'Function {} does not have a problem role.'.format(post_coupling_function)
- assert self.node[post_coupling_function]['problem_role'] == self.FUNCTION_ROLES[2], \
- 'Post-coupled function {} lacks the problem role "{}".'.format(post_coupling_function, self.FUNCTION_ROLES[2])
+ assert self.nodes[post_coupling_function]['problem_role'] == self.FUNCTION_ROLES[2], \
+ 'Post-coupled function {} lacks the problem ' \
+ 'role "{}".'.format(post_coupling_function, self.FUNCTION_ROLES[2])
return post_coupling_functions
def check_and_get_design_variables(self, des_vars=None):
if des_vars:
for des_var in des_vars:
assert self.has_node(des_var), 'Design variable {} is not a node in the graph.'.format(des_var)
- assert 'problem_role' in self.node[des_var], \
+ assert 'problem_role' in self.nodes[des_var], \
'Design variable {} does not have a problem role.'.format(des_var)
- assert self.node[des_var]['problem_role'] == self.PROBLEM_ROLES_VARS[0], \
+ assert self.nodes[des_var]['problem_role'] == self.PROBLEM_ROLES_VARS[0], \
'Design variable {} lacks the problem role "{}".'.format(des_var, self.PROBLEM_ROLES_VARS[0])
else:
des_vars = self.find_all_nodes(category='variable',
@@ -3447,26 +3536,21 @@ class FundamentalProblemGraph(DataGraph, KeChainMixin):
# TODO: Assert that objective function only has one output
# Determine local and global design variables
- global_des_vars, \
- local_des_vars, \
- des_vars_group_idxs = self.determine_scope_design_variables(des_vars=des_var_nodes)
+ global_des_vars, local_des_vars, des_vars_group_idxs = \
+ self.determine_scope_design_variables(des_vars=des_var_nodes)
# TODO: assess that each discipline group is dependent on at least one design variable (?)
# Get global and local constraints and their functions
- global_cnstrnt_vars, \
- global_cnstrnt_funcs, \
- local_cnstrnt_vars, \
- local_cnstrnt_funcs, \
- cnstrnt_vars_group_idxs, \
+ global_cnstrnt_vars, global_cnstrnt_funcs, local_cnstrnt_vars, local_cnstrnt_funcs, cnstrnt_vars_group_idxs, \
cnstrnt_funcs_group_idxs = self.determine_scope_constraint_functions(cnstrnt_vars=constraint_nodes)
# Create dictionary of pre-desvar, post-desvar, and post-coupling functions for the system optimizer
sys_functions_dict = self.get_system_level_functions(global_objective_function, global_cnstrnt_funcs,
- mg_function_ordering=mg_function_ordering)
+ mg_function_ordering=mg_function_ordering)
# Determine couplings between coupled groups and system-level post-coupling functions
- add_group_couplings, \
- add_group_couplings_groups_idx = self.get_sys_post_couplings(sys_functions_dict[self.FUNCTION_ROLES[2]])
+ add_group_couplings, add_group_couplings_groups_idx = \
+ self.get_sys_post_couplings(sys_functions_dict[self.FUNCTION_ROLES[2]])
# Add additional couplings to the group_couplings
for add_group_coupling in add_group_couplings:
@@ -3483,8 +3567,8 @@ class FundamentalProblemGraph(DataGraph, KeChainMixin):
if idx in groups:
local_cnstrnt_funcs_group.append(cnstrnt_func)
subsys_functions_dict = self.get_sub_level_functions(None, local_cnstrnt_funcs_group,
- coupled_functions_group,
- mg_function_ordering=mg_function_ordering)
+ coupled_functions_group,
+ mg_function_ordering=mg_function_ordering)
# Create dict collecting the subsystem functions dictionary
subsys_functions_dicts.append(subsys_functions_dict)
@@ -3748,7 +3832,7 @@ class FundamentalProblemGraph(DataGraph, KeChainMixin):
function_order.extend([self.OPTIMIZER_STRING])
function_order.extend([target for target in targets if target not in function_order])
mdg.split_variables(var, function_order=function_order)
- elif mdao_arch == graph.OPTIONS_ARCHITECTURES[8]: # CO
+ elif mdao_arch == graph.OPTIONS_ARCHITECTURES[8]: # CO
coupled_functions_groups = graph.graph['problem_formulation']['coupled_functions_groups']
n_groups = len(coupled_functions_groups)
sys_opt, sub_opts = self.get_architecture_node_ids('CO', number_of_groups=n_groups)
@@ -3757,7 +3841,7 @@ class FundamentalProblemGraph(DataGraph, KeChainMixin):
sa = self._analyze_distributed_system(des_var_nodes, objective_node, constraint_nodes, mg_function_ordering)
# TODO: Assert that function instances are not required (future functionality)
- # TODO: Determine the functions that require instances, add them, and adjust subsys_functions_dict accordingly
+ # TODO: Determine the functions requiring instances, add them and adjust subsys_functions_dict accordingly
# sys_functions_dict, subsys_functions_dicts = graph.create_function_instances(sys_functions_dict,
# subsys_functions_dicts)
@@ -3770,8 +3854,7 @@ class FundamentalProblemGraph(DataGraph, KeChainMixin):
for idx, subsys_functions_dict in enumerate(sa['functions_dicts'][1]):
# Get global and local design nodes and local constraint nodes involved in the group
subsys_functions = [item for sublist in subsys_functions_dict.values() for item in sublist]
- global_des_vars_group, local_des_vars_group, \
- local_cnstrnt_vars_group, local_group_couplings_group, \
+ global_des_vars_group, local_des_vars_group, local_cnstrnt_vars_group, local_group_couplings_group, \
external_group_couplings_group = get_group_vars(sa, idx)
# Make the groups local by introducing the right copies
@@ -3779,8 +3862,7 @@ class FundamentalProblemGraph(DataGraph, KeChainMixin):
mdg.localize_design_variables(subsys_functions, global_des_vars_group, local_des_vars_group)
sys_lev_des_vars.update(global_des_vars_copies_group)
- external_group_couplings_copies_group, \
- local_group_couplings_copies_group, \
+ external_group_couplings_copies_group, local_group_couplings_copies_group, \
mapping_locals= mdg.localize_group_couplings(subsys_functions,
external_group_couplings_group,
local_group_couplings_group)
@@ -3828,15 +3910,15 @@ class FundamentalProblemGraph(DataGraph, KeChainMixin):
elif mdao_arch == graph.OPTIONS_ARCHITECTURES[9]: # BLISS-2000
coupled_functions_groups = graph.graph['problem_formulation']['coupled_functions_groups']
n_groups = len(coupled_functions_groups)
- sys_opt, sys_conv, sys_sms, sub_smbds, sub_does, \
- sub_opts, sub_smbs = self.get_architecture_node_ids(mdao_arch, number_of_groups=n_groups)
+ sys_opt, sys_conv, sys_sms, sub_smbds, sub_does, sub_opts, sub_smbs = \
+ self.get_architecture_node_ids(mdao_arch, number_of_groups=n_groups)
sys_opt_label, sys_conv_label, sys_sms_labels, sub_smbds_labels, sub_does_labels, sub_opts_labels, \
sub_smbs_labels = self.get_architecture_node_labels(mdao_arch, number_of_groups=n_groups)
sa = self._analyze_distributed_system(des_var_nodes, objective_node, constraint_nodes, mg_function_ordering)
# TODO: Assert that function instances are not required (future functionality)
- # TODO: Determine the functions that require instances, add them, and adjust subsys_functions_dict accordingly
+ # TODO: Determine the functions requiring instances, add them, and adjust subsys_functions_dict accordingly
# sys_functions_dict, subsys_functions_dicts = graph.create_function_instances(sys_functions_dict,
# subsys_functions_dicts)
@@ -3855,33 +3937,32 @@ class FundamentalProblemGraph(DataGraph, KeChainMixin):
for idx, subsys_functions_dict in enumerate(sa['functions_dicts'][1]):
# Get global and local design nodes and local constraint nodes involved in the group
subsys_functions = [item for sublist in subsys_functions_dict.values() for item in sublist]
- global_des_vars_group, local_des_vars_group, \
- local_cnstrnt_vars_group, local_group_couplings_group, \
+ global_des_vars_group, local_des_vars_group, local_cnstrnt_vars_group, local_group_couplings_group, \
external_group_couplings_group = get_group_vars(sa, idx)
# Make the groups local by introducing the right copies
local_des_vars_copies_group, global_des_vars_copies_group, mapping_des_vars = \
mdg.localize_design_variables(subsys_functions, global_des_vars_group, local_des_vars_group)
- external_group_couplings_copies_group, \
- local_group_couplings_copies_group, \
- mapping_locals = mdg.localize_group_couplings(subsys_functions, external_group_couplings_group+
+ external_group_couplings_copies_group, local_group_couplings_copies_group, \
+ mapping_locals = mdg.localize_group_couplings(subsys_functions, external_group_couplings_group +
prev_local_group_couplings_copies,
local_group_couplings_group, instances_for_externals=True)
# Add the weighted couplings objective function according to BLISS-2000
- group_wcf_node, group_wcf_obj_node, weight_nodes = mdg.connect_weighted_couplings_objective_function(idx, local_group_couplings_group)
+ group_wcf_node, group_wcf_obj_node, weight_nodes = \
+ mdg.connect_weighted_couplings_objective_function(idx, local_group_couplings_group)
sa['functions_dicts'][1][idx][mdg.FUNCTION_ROLES[2]].append(group_wcf_node)
# Add and connect the sub-level optimizer
fin_des_vars, _, _, _ = mdg.connect_optimizer(sub_opts[idx], local_des_vars_group, group_wcf_obj_node,
- local_cnstrnt_vars_group, label=sub_opts_labels[idx])
+ local_cnstrnt_vars_group, label=sub_opts_labels[idx])
# Add local coupling nodes as final output in the graph
lgcg_finals = []
for node in local_group_couplings_group:
lgcg_final = mdg.copy_node_as(node,
- mdg.ARCHITECTURE_ROLES_VARS[5], # final output variables
+ mdg.ARCHITECTURE_ROLES_VARS[5], # final output variables
add_instance_if_exists=True)
lgcg_finals.append(lgcg_final)
source = mdg.get_sources(node)[0]
@@ -3889,7 +3970,7 @@ class FundamentalProblemGraph(DataGraph, KeChainMixin):
# Add and connect the sub-level DOE
doe_inps, doe_outs = mdg.connect_doe_block(sub_does[idx],
- external_group_couplings_copies_group+
+ external_group_couplings_copies_group +
local_des_vars_copies_group+weight_nodes,
lgcg_finals+fin_des_vars)
@@ -3919,7 +4000,8 @@ class FundamentalProblemGraph(DataGraph, KeChainMixin):
mdg.mark_as_design_variable(node2, ignore_outdegree=True)
sm_inps.extend(global_des_vars_group)
sm_out_originals = [mdg.nodes[node]['related_to_schema_node'] for node in lgcg_finals+fin_des_vars]
- sm_outs = mdg.connect_surrogate_model(sys_sms[idx], sm_def_node, sm_inps, sm_out_originals, label=sys_sms_labels[idx])
+ sm_outs = mdg.connect_surrogate_model(sys_sms[idx], sm_def_node, sm_inps, sm_out_originals,
+ label=sys_sms_labels[idx])
sm_inps_lists.append(sm_inps)
sms_ins.extend(sm_inps)
sms_outs.extend(sm_outs)
@@ -3942,10 +4024,12 @@ class FundamentalProblemGraph(DataGraph, KeChainMixin):
mdg.add_edge(sm_node, func)
# Create and connect the consistency constraint function
- sms_outs_couplings = [node for node in sms_outs if mdg.nodes[node]['related_to_schema_node'] in sa['couplings']['basic']]
+ sms_outs_couplings = [node for node in sms_outs if mdg.nodes[node]['related_to_schema_node'] in
+ sa['couplings']['basic']]
sms_outs_couplings_related = [mdg.nodes[node]['related_to_schema_node'] for node in sms_outs_couplings]
sms_ins2 = [node for node in sms_ins if 'related_to_schema_node' in mdg.nodes[node]]
- sms_ins_couplings = [node for node in sms_ins2 if mdg.nodes[node]['related_to_schema_node'] in sa['couplings']['basic']]
+ sms_ins_couplings = [node for node in sms_ins2 if mdg.nodes[node]['related_to_schema_node'] in
+ sa['couplings']['basic']]
sms_ins_couplings_related = [mdg.nodes[node]['related_to_schema_node'] for node in sms_ins_couplings]
ccf_mapping = dict()
for sms_out, sms_out_related in zip(sms_outs_couplings, sms_outs_couplings_related):
@@ -3959,7 +4043,7 @@ class FundamentalProblemGraph(DataGraph, KeChainMixin):
# Connect the system-level optimizer
fin_des_vars, _, _, ini_guess_nodes = mdg.connect_optimizer(sys_opt,
- list(sys_lev_des_vars)+weight_nodes2+
+ list(sys_lev_des_vars)+weight_nodes2 +
ccf_mapping.values(),
objective_node, list(sys_lev_cnstrnts)+cc_nodes,
label=sys_opt_label)
@@ -3980,7 +4064,8 @@ class FundamentalProblemGraph(DataGraph, KeChainMixin):
# First the initial guesses
if 'related_to_schema_node' in mdg.nodes[smbo_source]:
if mdg.nodes[smbo_source]['related_to_schema_node'] in ini_guess_nodes_related:
- ini_inp = ini_guess_nodes[ini_guess_nodes_related.index(mdg.nodes[smbo_source]['related_to_schema_node'])]
+ ini_inp = ini_guess_nodes[ini_guess_nodes_related.index(mdg.nodes[smbo_source]
+ ['related_to_schema_node'])]
else:
raise NotImplementedError('Could not find related node.')
else:
@@ -3991,7 +4076,8 @@ class FundamentalProblemGraph(DataGraph, KeChainMixin):
# Then the final values
if 'related_to_schema_node' in mdg.nodes[smbo_source]:
if mdg.nodes[smbo_source]['related_to_schema_node'] in fin_val_nodes_related:
- fin_inp = fin_des_vars[fin_val_nodes_related.index(mdg.nodes[smbo_source]['related_to_schema_node'])]
+ fin_inp = fin_des_vars[fin_val_nodes_related.index(mdg.nodes[smbo_source]
+ ['related_to_schema_node'])]
else:
raise NotImplementedError('Could not find related node.')
else:
@@ -4082,7 +4168,7 @@ class MdaoDataGraph(DataGraph, MdaoMixin):
category='A',
i=i)
for node in func_nodes:
- category_check, i_not = check('architecture_role' not in self.node[node],
+ category_check, i_not = check('architecture_role' not in self.nodes[node],
'The architecture_role attribute is missing on the node %s.' % node,
status=category_check,
category='A',
@@ -4140,23 +4226,23 @@ class MdaoDataGraph(DataGraph, MdaoMixin):
cmdows_executable_block_elem = cmdows_executable_block.add(make_camel_case(architecture_roles_fun))
cmdows_executable_block_elem.set('uID', graph_node)
- cmdows_executable_block_elem.add('label', self.node[graph_node].get('label'))
+ cmdows_executable_block_elem.add('label', self.nodes[graph_node].get('label'))
if architecture_roles_fun == 'optimizer':
- cmdows_executable_block_elem.add('settings', self.node[graph_node].get('settings'),
+ cmdows_executable_block_elem.add('settings', self.nodes[graph_node].get('settings'),
camel_case_conversion=True)
- graph_des_vars = [{'designVariableUID': self.PROBLEM_ROLES_VAR_SUFFIXES[0]+var} for var in
- self.node[graph_node].get('design_variables')]
+ graph_des_vars = [{'designVariableUID': self.PROBLEM_ROLES_VAR_SUFFIXES[0] + var} for var in
+ self.nodes[graph_node].get('design_variables')]
cmdows_executable_block_elem.add('designVariables', graph_des_vars)
graph_obj_vars = [{'objectiveVariableUID': self.PROBLEM_ROLES_VAR_SUFFIXES[1] + var} for var in
- self.node[graph_node].get('objective_variable')]
+ self.nodes[graph_node].get('objective_variable')]
cmdows_executable_block_elem.add('objectiveVariables', graph_obj_vars)
graph_con_vars = [{'constraintVariableUID': self.PROBLEM_ROLES_VAR_SUFFIXES[2] + var} for var in
- self.node[graph_node].get('constraint_variables')]
+ self.nodes[graph_node].get('constraint_variables')]
cmdows_executable_block_elem.add('constraintVariables', graph_con_vars)
elif architecture_roles_fun == 'doe':
- graph_settings = self.node[graph_node].get('settings')
+ graph_settings = self.nodes[graph_node].get('settings')
if graph_settings is not None:
cmdows_settings = cmdows_executable_block_elem.add('settings')
cmdows_settings.add('doeMethod', graph_settings.get('doe_method'))
@@ -4164,18 +4250,20 @@ class MdaoDataGraph(DataGraph, MdaoMixin):
cmdows_settings.add('doeRuns', graph_settings.get('doe_runs'))
if graph_settings.get('doe_seed') is not None:
cmdows_settings.add('doeSeed', graph_settings.get('doe_seed'))
- if graph_settings.get('doe_table') is not None: # TODO: Temp fix, doe should always have settings
+ if graph_settings.get('doe_table') is not None: # TODO: Temp fix, doe should have settings
cmdows_table = cmdows_settings.add('doeTable')
for graph_row_index, graph_row in enumerate(graph_settings.get('doe_table_order')):
- cmdows_row = cmdows_table.add('tableRow', attrib={'relatedParameterUID': str(graph_row)})
+ cmdows_row = cmdows_table.add('tableRow',
+ attrib={'relatedParameterUID': str(graph_row)})
for graph_element_index, graph_element in enumerate(graph_settings.get('doe_table')):
- cmdows_row.add('tableElement', str(format(float(graph_element[graph_row_index]),'.12f')),
+ cmdows_row.add('tableElement', str(format(float(graph_element[graph_row_index]),
+ '.12f')),
attrib={'experimentID': str(graph_element_index)})
graph_des_vars = [{'designVariableUID': self.PROBLEM_ROLES_VAR_SUFFIXES[0] + var} for var in
- self.node[graph_node].get('design_variables')]
+ self.nodes[graph_node].get('design_variables')]
cmdows_executable_block_elem.add('designVariables', graph_des_vars)
else:
- cmdows_executable_block_elem.add('settings', self.node[graph_node].get('settings'),
+ cmdows_executable_block_elem.add('settings', self.nodes[graph_node].get('settings'),
camel_case_conversion=True)
# Create architectureElements/executableBlocks/...Analyses/...
@@ -4226,37 +4314,42 @@ class MdaoDataGraph(DataGraph, MdaoMixin):
if role == 'optimizer' or role == 'doe':
cmdows_des_vars = cmdows_single_architecture_exe_block.findall('designVariables/designVariable')
graph_des_vars = [var.findtext('designVariableUID')[10:] for var in list(cmdows_des_vars)]
- self.node[cmdows_uid]['design_variables'] = graph_des_vars
+ self.nodes[cmdows_uid]['design_variables'] = graph_des_vars
if role == 'converger' or role == 'optimizer':
- if 'settings' not in self.node[cmdows_uid] or self.node[cmdows_uid]['settings'] is None:
- self.node[cmdows_uid]['settings'] = {}
+ if 'settings' not in self.nodes[cmdows_uid] or self.nodes[cmdows_uid]['settings'] is None:
+ self.nodes[cmdows_uid]['settings'] = {}
if role == 'converger':
- setting_options = {'last_iterations_to_consider':'lastIterationsToConsider',
- 'maximum_iterations':'maximumIterations',
- 'convergence_tolerance_relative':'convergenceToleranceRelative',
- 'convergence_tolerance_absolute':'convergenceToleranceAbsolute'}
+ setting_options = {'last_iterations_to_consider': 'lastIterationsToConsider',
+ 'maximum_iterations': 'maximumIterations',
+ 'convergence_tolerance_relative': 'convergenceToleranceRelative',
+ 'convergence_tolerance_absolute': 'convergenceToleranceAbsolute'}
else:
- setting_options = {'maximum_iterations':'maximumIterations',
- 'algorithm':'algorithm',
- 'apply_scaling':'applyScaling',
- 'maximum_function_evaluations':'maximumFunctionEvaluations',
- 'constraint_tolerance':'constraintTolerance',
- 'convergence_tolerance':'convergenceTolerance'}
+ setting_options = {'maximum_iterations': 'maximumIterations',
+ 'algorithm': 'algorithm',
+ 'apply_scaling': 'applyScaling',
+ 'maximum_function_evaluations': 'maximumFunctionEvaluations',
+ 'constraint_tolerance': 'constraintTolerance',
+ 'convergence_tolerance': 'convergenceTolerance'}
for setting_option in setting_options:
if setting_option == 'apply_scaling':
- bool_options = {'true':True,'false':False}
- self.node[cmdows_uid]['settings'][setting_option] = \
- bool_options[cmdows_single_architecture_exe_block.findtext('settings/'+setting_options[setting_option])]
+ bool_options = {'true': True, 'false': False}
+ self.nodes[cmdows_uid]['settings'][setting_option] = \
+ bool_options[cmdows_single_architecture_exe_block.findtext('settings/' +
+ setting_options
+ [setting_option])]
else:
- self.node[cmdows_uid]['settings'][setting_option] = \
- cmdows_single_architecture_exe_block.findtext('settings/'+setting_options[setting_option])
+ self.nodes[cmdows_uid]['settings'][setting_option] = \
+ cmdows_single_architecture_exe_block.findtext('settings/' +
+ setting_options[setting_option])
if role == 'optimizer':
- cmdows_des_vars = cmdows_single_architecture_exe_block.findall('objectiveVariables/objectiveVariable')
+ cmdows_des_vars = \
+ cmdows_single_architecture_exe_block.findall('objectiveVariables/objectiveVariable')
graph_des_vars = [var.findtext('objectiveVariableUID')[10:] for var in list(cmdows_des_vars)]
- self.node[cmdows_uid]['objective_variable'] = graph_des_vars
- cmdows_des_vars = cmdows_single_architecture_exe_block.findall('constraintVariables/constraintVariable')
+ self.nodes[cmdows_uid]['objective_variable'] = graph_des_vars
+ cmdows_des_vars = \
+ cmdows_single_architecture_exe_block.findall('constraintVariables/constraintVariable')
graph_des_vars = [var.findtext('constraintVariableUID')[10:] for var in list(cmdows_des_vars)]
- self.node[cmdows_uid]['constraint_variables'] = graph_des_vars
+ self.nodes[cmdows_uid]['constraint_variables'] = graph_des_vars
elif role == 'doe':
cmdows_rows = list(cmdows_single_architecture_exe_block.findall('settings/doeTable/tableRow'))
graph_rows = [cmdows_row.get('relatedParameterUID') for cmdows_row in cmdows_rows]
@@ -4267,23 +4360,26 @@ class MdaoDataGraph(DataGraph, MdaoMixin):
elements = sorted(cmdows_row, key=get_experiment_id)
entry = []
for element in elements:
- entry.append(format(element.findasttext(),'.12f'))
+ entry.append(format(element.findasttext(), '.12f'))
graph_table.append(entry)
graph_table = map(list, zip(*graph_table))
- if 'settings' not in self.node[cmdows_uid] or self.node[cmdows_uid]['settings'] is None:
- self.node[cmdows_uid]['settings'] = {}
- self.node[cmdows_uid]['settings']['doe_table_order'] = graph_rows
- self.node[cmdows_uid]['settings']['doe_table'] = graph_table
- self.node[cmdows_uid]['settings']['doe_method'] = cmdows_single_architecture_exe_block.findtext('settings/doeMethod')
- self.node[cmdows_uid]['settings']['doe_runs'] = cmdows_single_architecture_exe_block.findtext('settings/doeRuns')
- self.node[cmdows_uid]['settings']['doe_seed'] = cmdows_single_architecture_exe_block.findtext('settings/doeSeed')
+ if 'settings' not in self.nodes[cmdows_uid] or self.nodes[cmdows_uid]['settings'] is None:
+ self.nodes[cmdows_uid]['settings'] = {}
+ self.nodes[cmdows_uid]['settings']['doe_table_order'] = graph_rows
+ self.nodes[cmdows_uid]['settings']['doe_table'] = graph_table
+ self.nodes[cmdows_uid]['settings']['doe_method'] = \
+ cmdows_single_architecture_exe_block.findtext('settings/doeMethod')
+ self.nodes[cmdows_uid]['settings']['doe_runs'] = \
+ cmdows_single_architecture_exe_block.findtext('settings/doeRuns')
+ self.nodes[cmdows_uid]['settings']['doe_seed'] = \
+ cmdows_single_architecture_exe_block.findtext('settings/doeSeed')
else:
for role in self.ARCHITECTURE_ROLES_FUNS:
cmdows_role_name = make_camel_case(role)
if cmdows_single_architecture_exe_block.tag == cmdows_role_name:
cmdows_uid = cmdows_single_architecture_exe_block.find('relatedExecutableBlockUID').text
- self.node[cmdows_uid]['architecture_role'] = role
+ self.nodes[cmdows_uid]['architecture_role'] = role
# ---------------------------------------------------------------------------------------------------------------- #
# GRAPH SPECIFIC METHODS #
@@ -4316,14 +4412,14 @@ class MdaoDataGraph(DataGraph, MdaoMixin):
if self.FUNCTION_ROLES[0] in mg_function_ordering:
functions = mg_function_ordering[self.FUNCTION_ROLES[0]]
for func in functions:
- self.node[func]['architecture_role'] = self.ARCHITECTURE_ROLES_FUNS[4]
+ self.nodes[func]['architecture_role'] = self.ARCHITECTURE_ROLES_FUNS[4]
# Optimizer / DOE present
if self.FUNCTION_ROLES[3] in mg_function_ordering:
# Add pre-optimizer functions
functions = mg_function_ordering[self.FUNCTION_ROLES[3]]
for func in functions:
- self.node[func]['architecture_role'] = 'pre-iterator analysis'
+ self.nodes[func]['architecture_role'] = 'pre-iterator analysis'
# Add optimizer / DOE
if mdao_arch in self.OPTIONS_ARCHITECTURES[2:5]: # IDF, MDF, unc-OPT
assert not self.has_node(self.OPTIMIZER_STRING), 'Optimizer name already in use in FPG.'
@@ -4349,7 +4445,7 @@ class MdaoDataGraph(DataGraph, MdaoMixin):
# Add architecture role to post-iterator functions
functions = mg_function_ordering[self.FUNCTION_ROLES[4]]
for func in functions:
- self.node[func]['architecture_role'] = self.ARCHITECTURE_ROLES_FUNS[6]
+ self.nodes[func]['architecture_role'] = self.ARCHITECTURE_ROLES_FUNS[6]
# Converger required
if mdao_arch in [self.OPTIONS_ARCHITECTURES[1]] + [self.OPTIONS_ARCHITECTURES[3]] + \
@@ -4378,12 +4474,12 @@ class MdaoDataGraph(DataGraph, MdaoMixin):
# Add architecture role to coupled functions
for func in mg_function_ordering[self.FUNCTION_ROLES[1]]:
- self.node[func]['architecture_role'] = self.ARCHITECTURE_ROLES_FUNS[7]
+ self.nodes[func]['architecture_role'] = self.ARCHITECTURE_ROLES_FUNS[7]
# Add post-coupling functions
for func in mg_function_ordering[self.FUNCTION_ROLES[2]]:
if func != self.CONSCONS_STRING:
- self.node[func]['architecture_role'] = self.ARCHITECTURE_ROLES_FUNS[8]
+ self.nodes[func]['architecture_role'] = self.ARCHITECTURE_ROLES_FUNS[8]
else:
assert not self.has_node(self.CONSCONS_STRING), 'Consistency constraint name already in use in FPG.'
self.add_node(self.CONSCONS_STRING,
@@ -4452,7 +4548,7 @@ class MdaoDataGraph(DataGraph, MdaoMixin):
else:
raise IOError('Label extension could not be found.')
- node_data_dict = dict(self.node[node])
+ node_data_dict = dict(self.nodes[node])
# Determine the related schema node
if 'related_to_schema_node' in node_data_dict:
@@ -4496,8 +4592,8 @@ class MdaoDataGraph(DataGraph, MdaoMixin):
schema_related_nodes = self.find_all_nodes(category='variable',
attr_cond=['related_to_schema_node', '==', node])
for schema_related_node in schema_related_nodes:
- if 'architecture_role' in self.node[schema_related_node]:
- if self.node[schema_related_node]['architecture_role'] in \
+ if 'architecture_role' in self.nodes[schema_related_node]:
+ if self.nodes[schema_related_node]['architecture_role'] in \
get_list_entries(self.ARCHITECTURE_ROLES_VARS, 1, 4, 5):
node = schema_related_node
self.add_edge(node, function)
@@ -4676,7 +4772,7 @@ class MdaoDataGraph(DataGraph, MdaoMixin):
# Create a local copy of the design variable
local_des_var_copy = self.copy_node_as(global_des_var,
- self.ARCHITECTURE_ROLES_VARS[9], # copy design variable
+ self.ARCHITECTURE_ROLES_VARS[9], # copy design variable
add_instance_if_exists=True)
local_des_var_copies.append(local_des_var_copy)
mapping[global_des_var] = local_des_var_copy
@@ -4710,7 +4806,8 @@ class MdaoDataGraph(DataGraph, MdaoMixin):
return local_des_var_copies, global_des_var_copies, mapping
- def localize_group_couplings(self, group_functions, external_couplings, local_couplings, instances_for_externals=False):
+ def localize_group_couplings(self, group_functions, external_couplings, local_couplings,
+ instances_for_externals=False):
"""Method for distributed architecture to create instances of local and global coupling variables with respect
to the subgroup.
@@ -4851,7 +4948,6 @@ class MdaoDataGraph(DataGraph, MdaoMixin):
return conv_check_node
-
def connect_converger(self, converger, conv_type, coupling_functions, include_couplings_as_final_output,
system_converger=False, label='CONV'):
"""Method to automatically connect a converger around a collection of coupled functions.
@@ -4864,6 +4960,10 @@ class MdaoDataGraph(DataGraph, MdaoMixin):
:type coupling_functions: list
:param include_couplings_as_final_output: setting on whether coupling variables should always be added as output
:type include_couplings_as_final_output: bool
+ :param system_converger: converger is a system converger
+ :type system_converger: bool
+ :param label: converger label
+ :type label: str
"""
# Input assertions
@@ -4911,6 +5011,8 @@ class MdaoDataGraph(DataGraph, MdaoMixin):
:type objective_node: basestring
:param constraint_nodes: list of constraint nodes
:type constraint_nodes: list
+ :param label: optimizer label
+ :type label: str
:return: enriched MDAO data graph with connected optimizer
:rtype: MdaoDataGraph
"""
@@ -4923,12 +5025,12 @@ class MdaoDataGraph(DataGraph, MdaoMixin):
architecture_role=self.ARCHITECTURE_ROLES_FUNS[1],
label=label,
instance=1,
- settings = {'algorithm': 'Dakota Quasi-Newton method',
- 'maximum_iterations': 1000,
- 'maximum_function_evaluations': 1000,
- 'constraint_tolerance': 1e-4,
- 'convergence_tolerance': 1e-4,
- 'apply_scaling': True})
+ settings={'algorithm': 'Dakota Quasi-Newton method',
+ 'maximum_iterations': 1000,
+ 'maximum_function_evaluations': 1000,
+ 'constraint_tolerance': 1e-4,
+ 'convergence_tolerance': 1e-4,
+ 'apply_scaling': True})
assert isinstance(design_variable_nodes, list)
for des_var in design_variable_nodes:
assert self.has_node(des_var), 'Design variable %s is missing in the graph.' % des_var
@@ -4939,33 +5041,36 @@ class MdaoDataGraph(DataGraph, MdaoMixin):
assert self.has_node(con_var), 'Constraint variable %s is missing in the graph.' % con_var
# Add attributes to the optimizer block
- self.node[optimizer]['design_variables'] = dict()
+ self.nodes[optimizer]['design_variables'] = dict()
for des_var in design_variable_nodes:
- self.node[optimizer]['design_variables'][des_var] = dict()
- if 'upper_bound' in self.node[des_var]:
- self.node[optimizer]['design_variables'][des_var]['upper_bound'] = self.node[des_var]['upper_bound']
+ self.nodes[optimizer]['design_variables'][des_var] = dict()
+ if 'upper_bound' in self.nodes[des_var]:
+ self.nodes[optimizer]['design_variables'][des_var]['upper_bound'] = self.nodes[des_var]['upper_bound']
else:
- self.node[optimizer]['design_variables'][des_var]['upper_bound'] = None
- if 'lower_bound' in self.node[des_var]:
- self.node[optimizer]['design_variables'][des_var]['lower_bound'] = self.node[des_var]['lower_bound']
+ self.nodes[optimizer]['design_variables'][des_var]['upper_bound'] = None
+ if 'lower_bound' in self.nodes[des_var]:
+ self.nodes[optimizer]['design_variables'][des_var]['lower_bound'] = self.nodes[des_var]['lower_bound']
else:
- self.node[optimizer]['design_variables'][des_var]['lower_bound'] = None
- if 'nominal_value' in self.node[des_var]:
- self.node[optimizer]['design_variables'][des_var]['nominal_value'] = self.node[des_var]['nominal_value']
+ self.nodes[optimizer]['design_variables'][des_var]['lower_bound'] = None
+ if 'nominal_value' in self.nodes[des_var]:
+ self.nodes[optimizer]['design_variables'][des_var]['nominal_value'] = \
+ self.nodes[des_var]['nominal_value']
else:
- self.node[optimizer]['design_variables'][des_var]['nominal_value'] = None
- self.node[optimizer]['objective_variable'] = [objective_node]
- self.node[optimizer]['constraint_variables'] = dict()
+ self.nodes[optimizer]['design_variables'][des_var]['nominal_value'] = None
+ self.nodes[optimizer]['objective_variable'] = [objective_node]
+ self.nodes[optimizer]['constraint_variables'] = dict()
for con_var in constraint_nodes:
- self.node[optimizer]['constraint_variables'][con_var] = dict()
- if 'upper_bound' in self.node[con_var]:
- self.node[optimizer]['constraint_variables'][con_var]['upper_bound'] = self.node[con_var]['upper_bound']
+ self.nodes[optimizer]['constraint_variables'][con_var] = dict()
+ if 'upper_bound' in self.nodes[con_var]:
+ self.nodes[optimizer]['constraint_variables'][con_var]['upper_bound'] = \
+ self.nodes[con_var]['upper_bound']
else:
- self.node[optimizer]['constraint_variables'][con_var]['upper_bound'] = None
- if 'lower_bound' in self.node[con_var]:
- self.node[optimizer]['constraint_variables'][con_var]['lower_bound'] = self.node[con_var]['lower_bound']
+ self.nodes[optimizer]['constraint_variables'][con_var]['upper_bound'] = None
+ if 'lower_bound' in self.nodes[con_var]:
+ self.nodes[optimizer]['constraint_variables'][con_var]['lower_bound'] = \
+ self.nodes[con_var]['lower_bound']
else:
- self.node[optimizer]['constraint_variables'][con_var]['lower_bound'] = None
+ self.nodes[optimizer]['constraint_variables'][con_var]['lower_bound'] = None
# Manipulate the graph based on the architecture
# Connect design variables to the optimizer
@@ -5003,23 +5108,23 @@ class MdaoDataGraph(DataGraph, MdaoMixin):
if fin_obj is not None:
fin_cnstrnts.append(fin_value_node)
fin_obj = fin_value_node
- self.copy_edge([self.get_sources(var)[0], var],[self.get_sources(var)[0], fin_value_node])
+ self.copy_edge([self.get_sources(var)[0], var], [self.get_sources(var)[0], fin_value_node])
# If the graph contains consistency constraint variables, then connect these to the optimizer as well
consconcs_nodes = self.find_all_nodes(category='variable',
attr_cond=['architecture_role', '==', self.ARCHITECTURE_ROLES_VARS[6]])
# Add consistency constraints as constraints in the graph
for node in consconcs_nodes:
- rel_node = self.node[node]['related_to_schema_node']
+ rel_node = self.nodes[node]['related_to_schema_node']
# Add design variables to optimizer attributes
- self.node[optimizer]['design_variables'][rel_node] = dict()
- if 'upper_bound' in self.node[rel_node]:
- self.node[optimizer]['design_variables'][rel_node]['upper_bound'] = self.node[rel_node]['upper_bound']
+ self.nodes[optimizer]['design_variables'][rel_node] = dict()
+ if 'upper_bound' in self.nodes[rel_node]:
+ self.nodes[optimizer]['design_variables'][rel_node]['upper_bound'] = self.nodes[rel_node]['upper_bound']
else:
- self.node[optimizer]['design_variables'][rel_node]['upper_bound'] = None
- if 'lower_bound' in self.node[rel_node]:
- self.node[optimizer]['design_variables'][rel_node]['lower_bound'] = self.node[rel_node]['lower_bound']
+ self.nodes[optimizer]['design_variables'][rel_node]['upper_bound'] = None
+ if 'lower_bound' in self.nodes[rel_node]:
+ self.nodes[optimizer]['design_variables'][rel_node]['lower_bound'] = self.nodes[rel_node]['lower_bound']
else:
- self.node[optimizer]['design_variables'][rel_node]['lower_bound'] = None
+ self.nodes[optimizer]['design_variables'][rel_node]['lower_bound'] = None
self.add_edge(node, optimizer)
return fin_des_vars, fin_obj, fin_cnstrnts, ini_guess_nodes
@@ -5054,38 +5159,38 @@ class MdaoDataGraph(DataGraph, MdaoMixin):
assert self.has_node(qoi_var), 'Q.O.I. variable %s is missing in the graph.' % qoi_var
# Add attributes to the doe block
- self.node[doe_block]['design_variables'] = dict()
+ self.nodes[doe_block]['design_variables'] = dict()
for des_var in design_variable_nodes:
- self.node[doe_block]['design_variables'][des_var] = dict()
- if 'upper_bound' in self.node[des_var]:
- self.node[doe_block]['design_variables'][des_var]['upper_bound'] = self.node[des_var]['upper_bound']
+ self.nodes[doe_block]['design_variables'][des_var] = dict()
+ if 'upper_bound' in self.nodes[des_var]:
+ self.nodes[doe_block]['design_variables'][des_var]['upper_bound'] = self.nodes[des_var]['upper_bound']
else:
- self.node[doe_block]['design_variables'][des_var]['upper_bound'] = None
- if 'lower_bound' in self.node[des_var]:
- self.node[doe_block]['design_variables'][des_var]['lower_bound'] = self.node[des_var]['lower_bound']
+ self.nodes[doe_block]['design_variables'][des_var]['upper_bound'] = None
+ if 'lower_bound' in self.nodes[des_var]:
+ self.nodes[doe_block]['design_variables'][des_var]['lower_bound'] = self.nodes[des_var]['lower_bound']
else:
- self.node[doe_block]['design_variables'][des_var]['lower_bound'] = None
- if 'nominal_value' in self.node[des_var]:
- self.node[doe_block]['design_variables'][des_var]['nominal_value'] = self.node[des_var][
+ self.nodes[doe_block]['design_variables'][des_var]['lower_bound'] = None
+ if 'nominal_value' in self.nodes[des_var]:
+ self.nodes[doe_block]['design_variables'][des_var]['nominal_value'] = self.nodes[des_var][
'nominal_value']
else:
- self.node[doe_block]['design_variables'][des_var]['nominal_value'] = None
- if 'samples' in self.node[des_var]:
- self.node[doe_block]['design_variables'][des_var]['samples'] = self.node[des_var]['samples']
+ self.nodes[doe_block]['design_variables'][des_var]['nominal_value'] = None
+ if 'samples' in self.nodes[des_var]:
+ self.nodes[doe_block]['design_variables'][des_var]['samples'] = self.nodes[des_var]['samples']
else:
- self.node[doe_block]['design_variables'][des_var]['samples'] = None
- self.node[doe_block]['quantities_of_interest'] = qoi_nodes
+ self.nodes[doe_block]['design_variables'][des_var]['samples'] = None
+ self.nodes[doe_block]['quantities_of_interest'] = qoi_nodes
# For the custom design table, add the table with values to the settings
if 'doe_settings' in self.graph['problem_formulation']:
if 'doe_method' in self.graph['problem_formulation']['doe_settings']:
if self.graph['problem_formulation']['doe_settings']['doe_method'] == 'Custom design table':
- n_samples = len(self.node[doe_block]['design_variables'][design_variable_nodes[-1]]['samples'])
+ n_samples = len(self.nodes[doe_block]['design_variables'][design_variable_nodes[-1]]['samples'])
doe_table = []
for idj in range(n_samples):
doe_table.append([])
for des_var in design_variable_nodes:
- doe_table[idj].append(self.node[des_var]['samples'][idj])
+ doe_table[idj].append(self.nodes[des_var]['samples'][idj])
self.graph['problem_formulation']['doe_settings']['doe_table'] = doe_table
self.graph['problem_formulation']['doe_settings']['doe_table_order'] = design_variable_nodes
@@ -5165,9 +5270,9 @@ class MdaoDataGraph(DataGraph, MdaoMixin):
# Add the surrogate model definition as output of the block
output_node = '/{}/surrogateModels/{}/definition'.format(self.get_schema_root_name(input_x_entry[0]),
- label.replace('-',''))
+ label.replace('-', ''))
assert not self.has_node(output_node), 'The node {} already exists.'.format(output_node)
- self.add_node(output_node, category='variable', instance=1, label='def{}'.format(label.replace('-','')))
+ self.add_node(output_node, category='variable', instance=1, label='def{}'.format(label.replace('-', '')))
self.add_edge(sm_builder, output_node)
return output_node
@@ -5275,6 +5380,8 @@ class MdaoDataGraph(DataGraph, MdaoMixin):
:type converger: basestring or None
:param include_couplings_as_final_output: setting on whether coupling variables should always be added as output
:type include_couplings_as_final_output: bool
+ :param system_converger: converger is a system converger
+ :type system_converger: bool
"""
# Get all the relevant couplings
@@ -5319,7 +5426,7 @@ class MdaoDataGraph(DataGraph, MdaoMixin):
coupling_copy_node = self.copy_node_as(coupling[2], self.ARCHITECTURE_ROLES_VARS[2])
if not self.has_edge(converger, coupling_copy_node):
self.add_edge(converger, coupling_copy_node)
- self.copy_edge((coupling[2], coupling[1]) ,(coupling_copy_node, coupling[1]))
+ self.copy_edge((coupling[2], coupling[1]), (coupling_copy_node, coupling[1]))
# Connect original coupling node to the converger
self.add_edge(coupling[2], converger)
# If the converger node is an optimizer (IDF), then connect it accordingly
@@ -5342,18 +5449,18 @@ class MdaoDataGraph(DataGraph, MdaoMixin):
self.mark_as_constraint(consistency_node, '==', 0.0)
self.add_edge(self.CONSCONS_STRING, consistency_node)
self.add_equation((self.CONSCONS_STRING, consistency_node), 'y{}-y{}c'.format(idx, idx), 'Python')
- if 'consistency_nodes' in self.node[self.CONSCONS_STRING]:
- self.node[self.CONSCONS_STRING]['consistency_nodes'].append(consistency_node)
+ if 'consistency_nodes' in self.nodes[self.CONSCONS_STRING]:
+ self.nodes[self.CONSCONS_STRING]['consistency_nodes'].append(consistency_node)
else:
- self.node[self.CONSCONS_STRING]['consistency_nodes'] = [consistency_node]
+ self.nodes[self.CONSCONS_STRING]['consistency_nodes'] = [consistency_node]
# Remove coupling edge between coupling variable -> function
self.remove_edge(coupling[2], coupling[1])
# If required, create final coupling variable node and let it come from the coupled function
- if converger and ('problem_role' in self.node[coupling[2]] or include_couplings_as_final_output):
+ if converger and ('problem_role' in self.nodes[coupling[2]] or include_couplings_as_final_output):
final_node = self.copy_node_as(coupling[2], self.ARCHITECTURE_ROLES_VARS[1])
self.copy_edge([coupling[0], coupling[2]], [coupling[0], final_node])
keep_original_coupling_node = False
- elif not converger and ('problem_role' in self.node[coupling[2]] or include_couplings_as_final_output):
+ elif not converger and ('problem_role' in self.nodes[coupling[2]] or include_couplings_as_final_output):
keep_original_coupling_node = True
else:
keep_original_coupling_node = False
@@ -5375,12 +5482,13 @@ class MdaoDataGraph(DataGraph, MdaoMixin):
mpg = MdaoProcessGraph(self, name=name)
node_list = list(mpg.nodes)
for node in node_list:
- if 'category' not in mpg.node[node]:
+ if 'category' not in mpg.nodes[node]:
raise AssertionError('category attribute missing for node: {}.'.format(node))
- elif mpg.node[node]['category'] == 'variable':
+ elif mpg.nodes[node]['category'] == 'variable':
mpg.remove_node(node)
- elif mpg.node[node]['category'] not in ['variable', 'function']:
- raise AssertionError('Node {} has invalid category attribute: {}.'.format(node, mpg.node[node]['category']))
+ elif mpg.nodes[node]['category'] not in ['variable', 'function']:
+ raise AssertionError('Node {} has invalid category attribute: {}.'.format(node,
+ mpg.nodes[node]['category']))
mpg._add_diagonal_positions()
return mpg
@@ -5419,7 +5527,7 @@ class MdaoDataGraph(DataGraph, MdaoMixin):
mpg = mdg.create_mpg(name=name)
# Make process step of the coordinator equal to zero
- mpg.node[coor]['process_step'] = 0
+ mpg.nodes[coor]['process_step'] = 0
# Add process edges for each architecture
if mdao_arch == mdg.OPTIONS_ARCHITECTURES[0]: # unconverged-MDA
@@ -5430,10 +5538,10 @@ class MdaoDataGraph(DataGraph, MdaoMixin):
sequence = [coor] + pre_functions + [conv]
mpg.add_process(sequence, 0, mdg)
sequence2 = [conv] + coup_functions
- mpg.add_process(sequence2, mpg.node[sequence[-1]]['process_step'], mdg, end_in_iterative_node=conv)
+ mpg.add_process(sequence2, mpg.nodes[sequence[-1]]['process_step'], mdg, end_in_iterative_node=conv)
if post_functions:
sequence3 = [conv] + post_functions
- mpg.add_process(sequence3, mpg.node[conv]['converger_step'], mdg, end_in_iterative_node=coor)
+ mpg.add_process(sequence3, mpg.nodes[conv]['converger_step'], mdg, end_in_iterative_node=coor)
else:
mpg.connect_nested_iterators(coor, conv)
elif mdao_arch == mdg.OPTIONS_ARCHITECTURES[2]: # IDF
@@ -5441,7 +5549,7 @@ class MdaoDataGraph(DataGraph, MdaoMixin):
sequence1 = [coor] + pre_desvars_funcs + [opt]
mpg.add_process(sequence1, 0, mdg)
sequence2 = [opt] + post_desvars_funcs + coup_functions + post_functions
- mpg.add_process(sequence2, mpg.node[sequence1[-1]]['process_step'], mdg, end_in_iterative_node=opt)
+ mpg.add_process(sequence2, mpg.nodes[sequence1[-1]]['process_step'], mdg, end_in_iterative_node=opt)
mpg.connect_nested_iterators(coor, opt)
elif mdao_arch == mdg.OPTIONS_ARCHITECTURES[3]: # MDF
opt = mdg.OPTIMIZER_STRING
@@ -5449,25 +5557,25 @@ class MdaoDataGraph(DataGraph, MdaoMixin):
sequence1 = [coor] + pre_desvars_funcs + [opt]
mpg.add_process(sequence1, 0, mdg)
sequence2 = [opt] + post_desvars_funcs + [conv]
- mpg.add_process(sequence2, mpg.node[sequence1[-1]]['process_step'], mdg)
+ mpg.add_process(sequence2, mpg.nodes[sequence1[-1]]['process_step'], mdg)
sequence3 = [conv] + coup_functions
- mpg.add_process(sequence3, mpg.node[sequence2[-1]]['process_step'], mdg, end_in_iterative_node=conv)
+ mpg.add_process(sequence3, mpg.nodes[sequence2[-1]]['process_step'], mdg, end_in_iterative_node=conv)
sequence4 = [conv] + post_functions
- mpg.add_process(sequence4, mpg.node[conv]['converger_step'], mdg, end_in_iterative_node=opt)
+ mpg.add_process(sequence4, mpg.nodes[conv]['converger_step'], mdg, end_in_iterative_node=opt)
mpg.connect_nested_iterators(coor, opt)
elif mdao_arch == mdg.OPTIONS_ARCHITECTURES[4]: # unconverged-OPT
opt = mdg.OPTIMIZER_STRING
sequence1 = [coor] + pre_desvars_funcs + [opt]
mpg.add_process(sequence1, 0, mdg)
sequence2 = [opt] + post_desvars_funcs + coup_functions + post_functions
- mpg.add_process(sequence2, mpg.node[sequence1[-1]]['process_step'], mdg, end_in_iterative_node=opt)
+ mpg.add_process(sequence2, mpg.nodes[sequence1[-1]]['process_step'], mdg, end_in_iterative_node=opt)
mpg.connect_nested_iterators(coor, opt)
elif mdao_arch == mdg.OPTIONS_ARCHITECTURES[5]: # unconverged-DOE
doe = mdg.DOE_STRING
sequence1 = [coor] + pre_desvars_funcs + [doe]
mpg.add_process(sequence1, 0, mdg)
sequence2 = [doe] + post_desvars_funcs + coup_functions + post_functions
- mpg.add_process(sequence2, mpg.node[sequence1[-1]]['process_step'], mdg, end_in_iterative_node=doe)
+ mpg.add_process(sequence2, mpg.nodes[sequence1[-1]]['process_step'], mdg, end_in_iterative_node=doe)
mpg.connect_nested_iterators(coor, doe)
elif mdao_arch == mdg.OPTIONS_ARCHITECTURES[6]: # converged-DOE
doe = mdg.DOE_STRING
@@ -5475,12 +5583,12 @@ class MdaoDataGraph(DataGraph, MdaoMixin):
sequence1 = [coor] + pre_desvars_funcs + [doe]
mpg.add_process(sequence1, 0, mdg)
sequence2 = [doe] + post_desvars_funcs + [conv]
- mpg.add_process(sequence2, mpg.node[sequence1[-1]]['process_step'], mdg)
+ mpg.add_process(sequence2, mpg.nodes[sequence1[-1]]['process_step'], mdg)
sequence3 = [conv] + coup_functions
- mpg.add_process(sequence3, mpg.node[sequence2[-1]]['process_step'], mdg, end_in_iterative_node=conv)
+ mpg.add_process(sequence3, mpg.nodes[sequence2[-1]]['process_step'], mdg, end_in_iterative_node=conv)
if post_functions:
sequence4 = [conv] + post_functions
- mpg.add_process(sequence4, mpg.node[conv]['converger_step'], mdg, end_in_iterative_node=doe)
+ mpg.add_process(sequence4, mpg.nodes[conv]['converger_step'], mdg, end_in_iterative_node=doe)
else:
mpg.connect_nested_iterators(doe, conv)
mpg.connect_nested_iterators(coor, doe)
@@ -5544,34 +5652,37 @@ class MdaoDataGraph(DataGraph, MdaoMixin):
sequence1 = [coor] + distr_function_ordering[0][self.FUNCTION_ROLES[3]] + [sys_opt]
mpg.add_process(sequence1, 0, mdg)
sequence2 = [sys_opt] + distr_function_ordering[0][self.FUNCTION_ROLES[2]]
- mpg.add_process(sequence2, mpg.node[sequence1[-1]]['process_step'], mdg, end_in_iterative_node=sys_opt)
+ mpg.add_process(sequence2, mpg.nodes[sequence1[-1]]['process_step'], mdg, end_in_iterative_node=sys_opt)
for idx, subgroup in enumerate(distr_function_ordering[1]):
sequence3 = [sys_opt, sub_opts[idx]]
mpg.connect_nested_iterators(sys_opt, sub_opts[idx], direction='master->slave')
sequence4 = [sub_opts[idx]] + subgroup[self.FUNCTION_ROLES[4]] + subgroup[self.FUNCTION_ROLES[1]] + \
- subgroup[self.FUNCTION_ROLES[2]]
- mpg.add_process(sequence4, mpg.node[sequence3[-1]]['process_step'], mdg, end_in_iterative_node=sub_opts[idx])
+ subgroup[self.FUNCTION_ROLES[2]]
+ mpg.add_process(sequence4, mpg.nodes[sequence3[-1]]['process_step'], mdg,
+ end_in_iterative_node=sub_opts[idx])
mpg.connect_nested_iterators(sys_opt, sub_opts[idx])
mpg.connect_nested_iterators(coor, sys_opt)
elif mdao_arch == mdg.OPTIONS_ARCHITECTURES[9]: # BLISS-2000
distr_function_ordering = mdg.graph['distr_function_ordering']
n_groups = len(distr_function_ordering[1])
- sys_opt, sys_conv, _, sub_smbds, \
- sub_does, sub_opts, sub_smbs = self.get_architecture_node_ids(mdao_arch, number_of_groups=n_groups)
+ sys_opt, sys_conv, _, sub_smbds, sub_does, sub_opts, sub_smbs = \
+ self.get_architecture_node_ids(mdao_arch, number_of_groups=n_groups)
sequence1 = [coor] + distr_function_ordering[0][self.FUNCTION_ROLES[3]] + [sys_conv]
mpg.add_process(sequence1, 0, mdg)
for idx, subgroup in enumerate(distr_function_ordering[1]):
sequence2 = [sys_conv] + subgroup[self.FUNCTION_ROLES[3]] + [sub_smbds[idx]] + [sub_does[idx]] + \
- [sub_opts[idx]] + subgroup[self.FUNCTION_ROLES[4]] + subgroup[self.FUNCTION_ROLES[1]] + \
+ [sub_opts[idx]] + subgroup[self.FUNCTION_ROLES[4]] + subgroup[self.FUNCTION_ROLES[1]] + \
subgroup[self.FUNCTION_ROLES[2]]
- mpg.add_process(sequence2, mpg.node[sequence1[-1]]['process_step'], mdg, end_in_iterative_node=sub_opts[idx])
+ mpg.add_process(sequence2, mpg.nodes[sequence1[-1]]['process_step'], mdg,
+ end_in_iterative_node=sub_opts[idx])
mpg.connect_nested_iterators(sub_does[idx], sub_opts[idx])
sequence3 = [sub_does[idx]] + [sub_smbs[idx]] + [sys_opt]
- mpg.add_process(sequence3, mpg.node[sub_does[idx]]['converger_step'], mdg)
+ mpg.add_process(sequence3, mpg.nodes[sub_does[idx]]['converger_step'], mdg)
sequence4 = [sys_opt] + distr_function_ordering[0][self.FUNCTION_ROLES[4]] + \
distr_function_ordering[0][self.FUNCTION_ROLES[1]] + \
distr_function_ordering[0][self.FUNCTION_ROLES[2]]
- mpg.add_process(sequence4, mpg.node[sequence3[-1]]['process_step'], mdg, end_in_iterative_node=sequence4[0])
+ mpg.add_process(sequence4, mpg.nodes[sequence3[-1]]['process_step'], mdg,
+ end_in_iterative_node=sequence4[0])
mpg.connect_nested_iterators(sys_conv, sys_opt)
mpg.connect_nested_iterators(coor, sys_conv)
diff --git a/kadmos/graph/graph_kadmos.py b/kadmos/graph/graph_kadmos.py
index fa699e5f7dcc54b844ec5173ee796e04f9a61cae..cc670fbfd88c50d009e81dc6d751441736239d67 100644
--- a/kadmos/graph/graph_kadmos.py
+++ b/kadmos/graph/graph_kadmos.py
@@ -50,16 +50,16 @@ file_extensions = ['xml', 'kdms', 'graphml']
class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
# Hardcoded values and naming convention
- OPTIONS_ARCHITECTURES = ['unconverged-MDA', # 0
- 'converged-MDA', # 1
- 'IDF', # 2
- 'MDF', # 3
- 'unconverged-OPT', # 4
- 'unconverged-DOE', # 5
- 'converged-DOE', # 6
- 'distributed-convergence', # 7
- 'CO', # 8
- 'BLISS-2000'] # 9
+ OPTIONS_ARCHITECTURES = ['unconverged-MDA', # 0
+ 'converged-MDA', # 1
+ 'IDF', # 2
+ 'MDF', # 3
+ 'unconverged-OPT', # 4
+ 'unconverged-DOE', # 5
+ 'converged-DOE', # 6
+ 'distributed-convergence', # 7
+ 'CO', # 8
+ 'BLISS-2000'] # 9
OPTIONS_DOE_METHODS = ['Full factorial design', # 0
'Latin hypercube design', # 1
'Monte Carlo design', # 2
@@ -154,12 +154,11 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
SMB_LABEL = 'SMB'
INSTANCE_SUFFIX = '__i'
NODE_GROUP_SUBCATS = {'all variables':
- ['hole', 'supplied input', 'supplied shared input', 'output', 'collision',
- 'coupling', 'shared coupling', 'collided coupling', 'collided shared coupling',
- 'pure circular coupling', 'shared circular coupling',
- 'collided circular coupling', 'collided shared circular coupling',
- 'initial guess design variable', 'final design variable',
- 'MDA coupling variable', 'initial guess MDA coupling variable',
+ ['hole', 'supplied input', 'supplied shared input', 'output', 'collision', 'coupling',
+ 'shared coupling', 'collided coupling', 'collided shared coupling',
+ 'pure circular coupling', 'shared circular coupling', 'collided circular coupling',
+ 'collided shared circular coupling', 'initial guess design variable',
+ 'final design variable', 'MDA coupling variable', 'initial guess MDA coupling variable',
'final MDA coupling variable', 'final output variable',
'consistency constraint variable'],
'all inputs':
@@ -378,7 +377,11 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
return copied_graph
def change_graph_class(self, graph_class):
- """Method to adjust the class of a graph."""
+ """Method to adjust the class of a graph.
+
+ :return: newly classed graph.
+ :rtype: graph_class
+ """
self = graph_class(self)
return self
@@ -390,17 +393,17 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
def check(self, raise_error=False):
"""Method to check the graph for validity and completeness.
- Several checks are performed. However the method does not guarantee the validity of the graph.
-
- The checks are split into several categories and the methods _check_category_a, _check_category_b and
- _check_category_c are used to determine the overall validity and completeness. These sub methods are generally
- defined below and are then further refined in child classes.
-
:param raise_error: determines if an error should be raised in case of an invalid graph
:type raise_error: bool
:return: result of the check
:rtype: bool
+
+ .. note:: Several checks are performed. However the method does not guarantee the validity of the graph.
+
+ The checks are split into several categories and the methods _check_category_a, _check_category_b and
+ _check_category_c are used to determine the overall validity and completeness. These sub methods are generally
+ defined below and are then further refined in child classes.
"""
# Logging
@@ -557,10 +560,6 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
def check_cmdows_integrity(self, convention=True, mpg=None):
"""Method to check the integrity of the CMDOWS file that can be created with the save method.
- The integrity check is graph specific and thus needs to be executed for every graph before saving as CMDOWS if
- one wants to be sure that the CMDOWS file is integer. Due to its relative long runtime this check is however not
- performed automatically when using the save method.
-
:param convention: option for applying a UID convention
:type convention: bool
:param mpg: MPG to be saved together with graph
@@ -568,6 +567,10 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
:return: check result
:rtype: bool
+
+ The integrity check is graph specific and thus needs to be executed for every graph before saving as CMDOWS if
+ one wants to be sure that the CMDOWS file is integer. Due to its relative long runtime this check is however not
+ performed automatically when using the save method.
"""
logger.info('Performing CMDOWS integrity check...')
@@ -765,25 +768,26 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
if isinstance(graph, FundamentalProblemGraph):
if colors_based_on == 'partitions' and 'part_id' in graph.nodes[node]:
node_style = 'EvenPartitions' if int(graph.nodes[node]['part_id']) % 2 == 0 else 'OddPartitions'
- elif 'problem_role' in graph.node[node]:
- if graph.node[node]['problem_role'] == graph.FUNCTION_ROLES[0]:
+ elif 'problem_role' in graph.nodes[node]:
+ if graph.nodes[node]['problem_role'] == graph.FUNCTION_ROLES[0]:
node_style = 'PreAnalysis'
- elif graph.node[node]['problem_role'] == graph.FUNCTION_ROLES[1]:
+ elif graph.nodes[node]['problem_role'] == graph.FUNCTION_ROLES[1]:
node_style = 'CoupledAnalysis'
- elif graph.node[node]['problem_role'] == graph.FUNCTION_ROLES[2]:
+ elif graph.nodes[node]['problem_role'] == graph.FUNCTION_ROLES[2]:
node_style = 'PostAnalysis'
else:
logger.warning('An invalid FPG has been provided: problem_role missing for: %s.' % node)
node_style = 'RcgAnalysis'
elif isinstance(graph, MdaoDataGraph):
- if 'architecture_role' in graph.node[node]:
+ if 'architecture_role' in graph.nodes[node]:
try:
- role_index = self.ARCHITECTURE_ROLES_FUNS.index(graph.node[node]['architecture_role'])
+ role_index = self.ARCHITECTURE_ROLES_FUNS.index(graph.nodes[node]['architecture_role'])
except ValueError:
raise AssertionError('Architecture role %s is not supported for creation of XDSMs.'
- % graph.node[node]['architecture_role'])
+ % graph.nodes[node]['architecture_role'])
if colors_based_on == 'partitions' and 'part_id' in graph.nodes[node]:
- node_style = 'EvenPartitions' if int(graph.nodes[node]['part_id']) % 2 == 0 else 'OddPartitions'
+ node_style = 'EvenPartitions' if int(graph.nodes[node]['part_id']) % 2 == 0 \
+ else 'OddPartitions'
else:
node_style = self.ARCHITECTURE_ROLES_NODESTYLES[role_index]
else:
@@ -792,7 +796,7 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
else:
node_style = 'RcgAnalysis'
- node_text = graph.node[node].get('label', str(node))
+ node_text = graph.nodes[node].get('label', str(node))
assert node_text if node != pseudo_node else True, 'Node label is empty for node: %s' % node
dsm.addComp(node, node_style, node_text)
@@ -805,10 +809,10 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
' data graph.' % idx
node = node_list[0]
try:
- role_index = self.ARCHITECTURE_ROLES_FUNS.index(graph_mpg.node[node]['architecture_role'])
+ role_index = self.ARCHITECTURE_ROLES_FUNS.index(graph_mpg.nodes[node]['architecture_role'])
except ValueError:
raise AssertionError('Architecture role %s is not supported for creation of XDSMs.'
- % graph_mpg.node[node]['architecture_role'])
+ % graph_mpg.nodes[node]['architecture_role'])
if colors_based_on == 'partitions' and 'part_id' in graph.nodes[node]:
node_style = 'EvenPartitions' if int(graph.nodes[node]['part_id']) % 2 == 0 else 'OddPartitions'
else:
@@ -887,25 +891,25 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
else:
if node_set_upp:
str_upp = r'\\[1pt] '.join(
- map(str, map((lambda x: '$' + graph.node[x]['label'] + '$'), node_set_upp)))
+ map(str, map((lambda x: '$' + graph.nodes[x]['label'] + '$'), node_set_upp)))
if node_set_low:
str_low = r'\\[1pt] '.join(
- map(str, map((lambda x: '$' + graph.node[x]['label'] + '$'), node_set_low)))
+ map(str, map((lambda x: '$' + graph.nodes[x]['label'] + '$'), node_set_low)))
# Additional strings for XDSMs
str_num_up = ''
str_num_low = ''
if node_set_upp and mpg is not None:
- if 'process_step' in graph_mpg.node[node2]:
- str_num_up = str(graph_mpg.node[node2]['process_step']) + ': '
+ if 'process_step' in graph_mpg.nodes[node2]:
+ str_num_up = str(graph_mpg.nodes[node2]['process_step']) + ': '
else:
str_num_up = ''
if node_set_low and mpg is not None:
# Check existence of process edge and add edge number if it exists
- if 'converger_step' in graph_mpg.node[node1]:
- str_num_low = (str(graph_mpg.node[node1]['converger_step']) + ': ')
- elif 'process_step' in graph_mpg.node[node1]:
- str_num_low = (str(graph_mpg.node[node1]['process_step']) + ': ')
+ if 'converger_step' in graph_mpg.nodes[node1]:
+ str_num_low = (str(graph_mpg.nodes[node1]['converger_step']) + ': ')
+ elif 'process_step' in graph_mpg.nodes[node1]:
+ str_num_low = (str(graph_mpg.nodes[node1]['process_step']) + ': ')
else:
str_num_low = ''
@@ -984,7 +988,7 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
for graph_design_competence in graph_design_competences:
# Create designCompetences/designCompetence
- graph_design_competence_data = self.node[graph_design_competence]
+ graph_design_competence_data = self.nodes[graph_design_competence]
cmdows_design_competence = cmdows_design_competences.add('designCompetence')
cmdows_design_competence.set('uID', graph_design_competence)
cmdows_design_competence.add('ID', graph_design_competence_data.get('name'))
@@ -1035,11 +1039,11 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
# Create parameters/parameter
cmdows_parameter = cmdows_parameters.add('parameter')
cmdows_parameter.set('uID', graph_parameter)
- cmdows_parameter.add('label', self.node[graph_parameter].get('label'))
- cmdows_parameter.add('description', self.node[graph_parameter].get('description'))
- cmdows_parameter.add('note', self.node[graph_parameter].get('note'))
- cmdows_parameter.add('unit', self.node[graph_parameter].get('unit'))
- cmdows_parameter.add('dataType', self.node[graph_parameter].get('data_type'))
+ cmdows_parameter.add('label', self.nodes[graph_parameter].get('label'))
+ cmdows_parameter.add('description', self.nodes[graph_parameter].get('description'))
+ cmdows_parameter.add('note', self.nodes[graph_parameter].get('note'))
+ cmdows_parameter.add('unit', self.nodes[graph_parameter].get('unit'))
+ cmdows_parameter.add('dataType', self.nodes[graph_parameter].get('data_type'))
return cmdows_parameters
@@ -1062,8 +1066,8 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
for u, v, w in self.edges(data=True):
# Create workflow/dataGraph/edges/edge
cmdows_edge = cmdows_edges.add('edge')
- from_name = 'fromExecutableBlockUID' if self.node[u].get('category') == 'function' else 'fromParameterUID'
- to_name = 'toExecutableBlockUID' if self.node[v].get('category') == 'function' else 'toParameterUID'
+ from_name = 'fromExecutableBlockUID' if self.nodes[u].get('category') == 'function' else 'fromParameterUID'
+ to_name = 'toExecutableBlockUID' if self.nodes[v].get('category') == 'function' else 'toParameterUID'
cmdows_edge.add(from_name, u)
cmdows_edge.add(to_name, v)
cmdows_data_graph.add('metadata')
@@ -1094,11 +1098,11 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
:return: mpg
:rtype: MdaoProcessGraph
- Check_list options:
+ .. note:: check_list options:
- * 'consistent_root': check if all in-/output files have the same root element
- * 'invalid_leaf_elements': check for leaf elements that still have child elements in other in-/output files
- * 'schemas': check if the in-/output files are consistent with the schema.
+ * 'consistent_root': check if all in-/output files have the same root element
+ * 'invalid_leaf_elements': check for leaf elements that still have child elements in other in-/output files
+ * 'schemas': check if the in-/output files are consistent with the schema.
To perform all of the checks without stopping if an error is found by the checks:
@@ -1243,8 +1247,10 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
cmdows_edges = cmdows_data_graph.find('edges')
if cmdows_edges is not None:
for edge in list(cmdows_edges):
- from_id = edge.findtext('fromExecutableBlockUID', default=edge.findtext('fromParameterUID')).replace("'", '"')
- to_id = edge.findtext('toExecutableBlockUID', default=edge.findtext('toParameterUID')).replace("'", '"')
+ from_id = edge.findtext('fromExecutableBlockUID',
+ default=edge.findtext('fromParameterUID')).replace("'", '"')
+ to_id = edge.findtext('toExecutableBlockUID',
+ default=edge.findtext('toParameterUID')).replace("'", '"')
self.assert_node_exists(from_id)
self.assert_node_exists(to_id)
self.add_edge(from_id, to_id)
@@ -1270,12 +1276,6 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
pretty_print=False, convention=True, integrity=False):
"""Method to save the graph.
- Different output file types are implemented for saving graphs. They are listed below:
-
- * kdms: the most simple file type which makes use of pickling
- * cmdows: the most versatile file type especially suited for file exchange with other tools
- * graphml: another file type especially suited for file exchange with other tools based on graphs
-
:param file_name: name of the file to be saved
:type file_name: str
:param file_type: file_type
@@ -1293,7 +1293,7 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
:param creator: name of the creator of the file (only applicable for the cmdows file type)
:type creator: str
:param version: version of the file (only applicable for the cmdows file type)
- :type version: str | float | int
+ :type version: str, float, int
:param timestamp: timestamp to be saved in the file (only applicable for the cmdows file type)
:type timestamp: datetime
:param keep_empty_elements: option for keeping empty XML elements (only applicable for the cmdows file type)
@@ -1304,6 +1304,12 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
:type convention: bool
:param integrity: option for doing an integrity file check (only applicable for the cmdows file type)
:type integrity: bool
+
+ .. note:: Different output file types are implemented for saving graphs. They are listed below:
+
+ * kdms: the most simple file type which makes use of pickling
+ * cmdows: the most versatile file type especially suited for file exchange with other tools
+ * graphml: another file type especially suited for file exchange with other tools based on graphs
"""
# Check if the file type is valid
@@ -1498,7 +1504,11 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
# ---------------------------------------------------------------------------------------------------------------- #
def inspect(self):
- """Method to print an overview of the graph."""
+ """Method to print an overview of the graph.
+
+ :return: printed overview of the graph
+ :rtype: str
+ """
print '\n- - - - - - - - - -'
print ' GRAPH INSPECTION '
@@ -1517,6 +1527,8 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
:param node: node
:type node: str
+ :return: printed node details
+ :rtype: str
"""
pp = pprint.PrettyPrinter(indent=2)
@@ -1534,7 +1546,7 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
print '\nnode targets:'
pp.pprint(self.get_targets(node))
print '\nnode attributes:'
- pp.pprint(self.node[node])
+ pp.pprint(self.nodes[node])
print '- - - - - - - - - - - - -\n'
def inspect_nodes(self, list_of_nodes):
@@ -1542,6 +1554,8 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
:param list_of_nodes: node list
:type list_of_nodes: list
+ :return: printed details of nodes
+ :rtype: str
"""
assert isinstance(list_of_nodes, list)
@@ -1596,19 +1610,19 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
>>> roles = ['integrator', 'architect']
>>> add_contact('Maaike de Wit', 'M.D.deWit@student.tudelft.nl', 'mddewit', company='TU Delft', roles=roles)
- In case the contact uid already exists the old contact attributes are conserved and only new roles are added to
- the roles already present for that contact. To change old contact information, this has to be adjusted in the
- XML-file from which the old contact information is loaded.
+ .. note:: In case the contact uid already exists the old contact attributes are conserved and only new roles
+ are added to the roles already present for that contact. To change old contact information, this has to be
+ adjusted in the XML-file from which the old contact information is loaded.
- To add (more) roles to the existing contact, it is recommended to use the method: add_contact_roles()
+ .. hint:: To add (more) roles to the existing contact, it is recommended to use the method: add_contact_roles()
"""
already = False
contacts = []
organigram = {}
- contact = OrderedDict([('attrib', {'uID': uid}), ('name', name), ('email', email),('company', company),
- ('department', department),('function', function),('address', address),
- ('telephone', telephone),('country', country)])
+ contact = OrderedDict([('attrib', {'uID': uid}), ('name', name), ('email', email), ('company', company),
+ ('department', department), ('function', function), ('address', address),
+ ('telephone', telephone), ('country', country)])
role_options = ['architect', 'integrator', 'collaborativeEngineer', 'toolSpecialist', 'customer']
architects = []
@@ -1617,8 +1631,8 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
tool_specialists = []
customers = []
- dict = {'architect':architects, 'integrator':integrators,'collaborativeEngineer':collaborative_engineers,
- 'toolSpecialist':tool_specialists,'customer':customers}
+ dict = {'architect': architects, 'integrator': integrators,'collaborativeEngineer': collaborative_engineers,
+ 'toolSpecialist': tool_specialists,'customer': customers}
if isinstance(roles, list):
for role in roles:
@@ -1626,14 +1640,14 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
logger.warning('Invalid role {} was provided for {}. Appropriate roles are: '
'{}'.format(role, name, role_options))
else:
- dict[role].append({'contactUID':uid})
+ dict[role].append({'contactUID': uid})
elif isinstance(roles, basestring):
role = roles
if role not in role_options:
logger.warning('Invalid role {} was provided for {}. Appropriate roles are: {}'.format(role, name,
role_options))
else:
- dict[role].append({'contactUID':uid})
+ dict[role].append({'contactUID': uid})
# Check for existing organigram
for role in role_options:
@@ -1661,7 +1675,7 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
contacts.append(contact)
else:
logger.debug("{} is already defined in CMDOWS. Please use add_contact_roles() to add new roles to this"
- " existing contact.".format(contact['attrib']))
+ " existing contact.".format(contact['attrib']))
self.graph['organization']['contacts'] = contacts
self.graph['organization']['organigram'] = organigram
else:
@@ -1693,7 +1707,7 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
>>> roles = ['integrator', 'architect']
>>> add_contact('mddewit', company='TU Delft', roles=roles)
- This method only works for existing contacts. To add a contact use the method: add_contact()
+ .. hint:: This method only works for existing contacts. To add a contact use the method: add_contact()
"""
assert 'organization' in self.graph, 'There are no contacts present to add a role to.'
@@ -1767,17 +1781,17 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
:type model_definition: str
"""
- self.node[dc_uid]['general_info'] = {'description': description}
+ self.nodes[dc_uid]['general_info'] = {'description': description}
options = ['status', 'creation_date', 'owner', 'creator', 'operator', 'model_definition']
- uid_options = ['owner','creator','operator']
- dict = {'status':status,'creation_date': creation_date, 'owner': owner_uid, 'creator': creator_uid,
+ uid_options = ['owner', 'creator', 'operator']
+ dict = {'status':status, 'creation_date': creation_date, 'owner': owner_uid, 'creator': creator_uid,
'operator': operator_uid, 'model_definition': model_definition}
for option in options:
if option in uid_options and dict[option]:
- self.node[dc_uid]['general_info'].update({option : {'contactUID': dict[option]}})
+ self.nodes[dc_uid]['general_info'].update({option: {'contactUID': dict[option]}})
elif dict[option]:
- self.node[dc_uid]['general_info'].update({option : dict[option]})
+ self.nodes[dc_uid]['general_info'].update({option: dict[option]})
return
def add_dc_performance_info(self, dc_uid, precision=None, fidelity_level=None, run_time=None, verification=None):
@@ -1796,8 +1810,8 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
At least one of the optional elements for the performance information has to be defined.
"""
- options = ['precision','fidelity_level','run_time','verification']
- dict = {'precision': precision, 'fidelity_level':fidelity_level, 'run_time': run_time,
+ options = ['precision', 'fidelity_level', 'run_time', 'verification']
+ dict = {'precision': precision, 'fidelity_level': fidelity_level, 'run_time': run_time,
'verification': verification}
if not precision and not fidelity_level and not run_time and not verification:
logger.warning("At least one element of the performance info of {} must have a value".format(dc_uid))
@@ -1806,10 +1820,10 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
for option in options:
if dict[option]:
if first:
- self.node[dc_uid].update({'performance_info':{option : dict[option]}})
+ self.nodes[dc_uid].update({'performance_info': {option: dict[option]}})
first = False
else:
- self.node[dc_uid]['performance_info'].update({option: dict[option]})
+ self.nodes[dc_uid]['performance_info'].update({option: dict[option]})
return
def add_dc_remote_component_info(self, dc_uid, single_or_multi_execution, job_name, remote_engineer,
@@ -1818,8 +1832,8 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
:param dc_uid: uid of the design competence
:type dc_uid: str
- :param single_or_multi_execution: execution type
- :type single_or_multi_execution: 'single' or 'multiple'
+ :param single_or_multi_execution: execution type. Choose from 'single' or 'multiple'.
+ :type single_or_multi_execution: str
:param job_name: job name of the design competence
:type job_name: str
:param remote_engineer: contact uid of remote engineering of the design competence
@@ -1832,22 +1846,22 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
Example use:
>>> single_or_multi = "single"
- >>> job_name = 'job_{}'.format(fpg.node[node]['label'].replace(' ', ''))
- >>> notification_message = 'Hi, could you please run this tool {} for me for my {} AGILE workflow ' \
- 'execution. Thanks.'.format(fpg.node[node]['label'].replace(' ', ''), architecture)
+ >>> job_name = 'job_{}'.format(fpg.nodes[node]['label'].replace(' ', ''))
+ >>> notification_message = 'Hi, could you please run this tool {} for me for my {} AGILE workflow '
+ >>> 'execution. Thanks.'.format(fpg.nodes[node]['label'].replace(' ', ''), architecture)
>>> fpg.add_dc_remote_component_info(node, single_or_multi, job_name, 'ivangent', notification_message,
>>> data_exchange_dict={'urlsite': 'some_url',
>>> 'folder': 'some_folder'})
"""
- self.node[dc_uid].update({'execution_info'
- :{'remote_component_info'
- :{'job_settings':{'single_or_multi_execution': single_or_multi_execution,
- 'remote_engineer': {'contact_u_i_d': remote_engineer},
- 'job_name': job_name,
- 'notification_message': notification_message}}}})
+ self.nodes[dc_uid].update({'execution_info':
+ {'remote_component_info':
+ {'job_settings': {'single_or_multi_execution': single_or_multi_execution,
+ 'remote_engineer': {'contact_u_i_d': remote_engineer},
+ 'job_name': job_name,
+ 'notification_message': notification_message}}}})
if data_exchange_dict:
- self.node[dc_uid]['execution_info']['remote_component_info'].update({'data_exchange_settings' :
- data_exchange_dict})
+ self.nodes[dc_uid]['execution_info']['remote_component_info'].update({'data_exchange_settings':
+ data_exchange_dict})
return
def add_node(self, n, attr_dict=None, **attr):
@@ -1857,8 +1871,8 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
:type n: A node can be any hashable Python object except None.
:param attr_dict: dictionary of attribute keyword arguments.
:type attr_dict: dict
- :param attr: keyword arguments, optional
- :type attr: Set or change node attributes using attr_dict.
+ :param attr: Set or change node attributes using attr_dict.
+ :type attr: str, dict
Examples:
@@ -1874,15 +1888,15 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
>>> G.add_node(1, size=10)
>>> G.add_node(3, weight=0.4, UTM=('13S', 382871, 3972649))
- Notes:
-
- A hashable object is one that can be used as a key in a Python
- dictionary. This includes strings, numbers, tuples of strings
- and numbers, etc.
+ .. note::
+ A hashable object is one that can be used as a key in a Python
+ dictionary. This includes strings, numbers, tuples of strings
+ and numbers, etc.
- On many platforms hashable items also include mutables such as
- NetworkX Graphs, though one should be careful that the hash
- doesn't change on mutables.
+ .. note::
+ On many platforms hashable items also include mutables such as
+ NetworkX Graphs, though one should be careful that the hash
+ doesn't change on mutables.
"""
# Execute base function
@@ -1892,14 +1906,23 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
self.nodes[n][key] = attr_dict[key]
# Set some default attributes
- if 'name' not in self.node[n]:
- self.node[n]['name'] = n
- if 'label' not in self.node[n]:
- self.node[n]['label'] = n
+ if 'name' not in self.nodes[n]:
+ self.nodes[n]['name'] = n
+ if 'label' not in self.nodes[n]:
+ self.nodes[n]['label'] = n
def add_edge(self, u, v, attr_dict=None, **attr):
"""Add an edge between u and v.
+ :param u: node
+ :type u: can be, for example, strings or numbers. Nodes must be hashable (and not None) Python objects.
+ :param v: node
+ :type v: see u
+ :param attr_dict: keyword arguments
+ :type attr_dict: str
+ :param attr: edge data (or labels or objects) can be assigned using keyword arguments.
+ :type attr: str
+
The nodes u and v will be automatically added if they are not already in the graph.
Adding an existing edge results in an update of the edge data.
@@ -1907,11 +1930,6 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
Edge attributes can be specified with keywords or by directly accessing the edge's attribute dictionary.
See examples below.
- :param u, v: nodes
- :type u, v: can be, for example, strings or numbers. Nodes must be hashable (and not None) Python objects.
- :param attr: keyword arguments, optional
- :type attr: Edge data (or labels or objects) can be assigned using keyword arguments.
-
The following examples both add the edge e=(1,2) to graph G:
>>> G = nx.Graph() # or DiGraph, MultiGraph, MultiDiGraph, etc
@@ -1963,7 +1981,7 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
:rtype: bool
"""
- return self.node[node]["category"] == "function"
+ return self.nodes[node]["category"] == "function"
def node_is_variable(self, node):
"""Function that checks whether a node is a variable node or not.
@@ -1974,7 +1992,7 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
:rtype: bool
"""
- return self.node[node]["category"] == "variable"
+ return self.nodes[node]["category"] == "variable"
def node_is_output(self, node):
"""Function that checks whether a node is a system output.
@@ -2045,20 +2063,17 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
def get_function_graph(self, keep_objective_variables=False):
"""Method for replacing variable nodes by function connections.
- This function removes all variable nodes from the graph and replaces the variable connections of each function
- with function connections, such that:
-
- F(1) => N(1) => F(2) => N(2) => F(3)
-
- becomes:
-
- F(1) => F(2) => F(3)
-
- Note: N(i) is a variable node, and F(i) a function node.
-
:param: keep_objective_variables: if given the objective variables will remain in graph
:type: keep_objective_variables: bool
:return: new graph without variable nodes
+
+ .. note::
+ This function removes all variable nodes from the graph and replaces the variable connections of each function
+ with function connections, such that if N(i) is a variable node, and F(i) a function node:
+
+ F(1) => N(1) => F(2) => N(2) => F(3)
+
+ becomes: F(1) => F(2) => F(3)
"""
# TODO: create separate function to get coupling strength between two nodes: get_coupling_strength
@@ -2078,14 +2093,14 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
is_obj_var = False
# Only consider variable nodes
- node_cat = function_graph.node[node]['category']
+ node_cat = function_graph.nodes[node]['category']
if node_cat == 'variable' or node_cat == 'variable group':
# Loop in/out edges and get all function nodes connected to variable
for edge in function_graph.out_edges(node):
- if function_graph.node[edge[1]]['category'] == 'function':
+ if function_graph.nodes[edge[1]]['category'] == 'function':
if keep_objective_variables:
- if function_graph.node[edge[1]]["name"] == "Objective":
+ if function_graph.nodes[edge[1]]["name"] == "Objective":
is_obj_var = True
else:
out_funcs.append(edge[1])
@@ -2093,7 +2108,7 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
else:
out_funcs.append(edge[1])
for edge in function_graph.in_edges(node):
- if function_graph.node[edge[0]]['category'] == 'function':
+ if function_graph.nodes[edge[0]]['category'] == 'function':
in_funcs.append(edge[0])
# Add all variable nodes to remove list
@@ -2124,12 +2139,16 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
def get_system_inputs(self, *args, **kwargs):
"""This method checks whether there are system inputs in the graph using the function nodes provided.
- The function nodes should be provided in the args. If system inputs exist they are returned.
-
:param args: function nodes
+ :type args:
+ :param kwargs:
+ :type kwargs:
:return: system input nodes dictionary
:rtype: dict
+
+ .. note:: The function nodes should be provided in the args. If system inputs exist they are returned.
"""
+ # TODO: Imco add type of args and doc of kwargs
assert all(self.node_is_function(arg) for arg in args), "At least one node in args is not a function node."
@@ -2152,12 +2171,12 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
def get_graph_properties(self, *args):
"""This function retrieves the properties of a graph.
- If no argument is given, the standard list of properties GRAPH_PROPERTIES is analyzed and their values are
- returned in a dict. If arguments are given, only this list will be used as standard list of properties.
-
:param: args: specific properties to be retrieved (optional)
:return: dictionary containing the properties of the graph
:rtype: dict
+
+ If no argument is given, the standard list of properties GRAPH_PROPERTIES is analyzed and their values are
+ returned in a dict. If arguments are given, only this list will be used as standard list of properties.
"""
# Make sure that arguments are valid
@@ -2205,7 +2224,7 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
:param node: input node
:return: number of couplings for the input node
- :type: int
+ :rtype: int
"""
assert node in self, "The specified node is not present in graph."
@@ -2221,6 +2240,15 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
def get_direct_coupling_nodes(self, *args, **kwargs):
"""This method returns the direct couplings between two nodes in a graph.
+ :param args: nodes to be checked for couplings; at least two must be provided
+ :type args: str, list
+ :param kwargs: print_couplings: option for printing all couplings with coupling direction and node (optional)
+ :type kwargs: print_couplings: bool
+ :param kwargs: direction: set only coupling in certain direction (optional)
+ :type kwargs: direction: str
+ :return: couplings: list of tuples containing the coupled nodes and the coupling node
+ :rtype: list
+
This method is specifically written (and tested) with function nodes in mind. Direct coupling is defined as
coupling with between two nodes through a third node.
@@ -2231,23 +2259,8 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
Example:
- The connection:
-
- F1 => N1 => F2
-
- leads to:
-
- [(F1, F2, N1)]
-
-
- :param args: nodes to be checked for couplings; at least two must be provided
- :type args: str, list
- :param kwargs: print_couplings: option for printing all couplings with coupling direction and node (optional)
- :type kwargs: print_couplings: bool
- :param kwargs: direction: set only coupling in certain direction (optional)
- :type kwargs: direction: str
- :return: couplings: list of tuples containing the coupled nodes and the coupling node
- :rtype: list
+ * The connection: F1 => N1 => F2
+ * Leads to: [(F1, F2, N1)]
"""
# Assert that every argument is string, and node in graph
@@ -2344,14 +2357,14 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
def get_nodes_based_on_strings(self, *args, **kwargs):
"""This function enables the user to search graph nodes for specific strings.
- Each provided string will be searched for, and if multiple node are found for each string, the user will be able
- to select the ones desired. The other matched nodes are disregarded.
-
:param args: strings that graph nodes being searched for
:type args: str
:param kwargs: include_all: If include_all is set to True, all matching nodes are added to returned list
:type kwargs: include_all: bool
:return: matching nodes that user selected (all if include_all is True)
+
+ Each provided string will be searched for, and if multiple node are found for each string, the user will be able
+ to select the ones desired. The other matched nodes are disregarded.
"""
# Check if all found nodes should be included or not
@@ -2431,13 +2444,13 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
def get_subgraph_by_function_nodes(self, *args, **kwargs):
"""This function retrieves a subgraph from the original graph only containing the argument nodes.
- All arguments must be found in the graph.
-
:param args: arbitrary amount of graph nodes
:type args: list, str
:param kwargs: copy_type: type of copy (clean or deep)
:type kwargs: copy_type: str
:return: sub-graph only containing nodes provided as arguments, and their edges
+
+ .. note:: All arguments must be found in the graph.
"""
# handle the fact that the *args could also be a list or tuple directly
@@ -2501,6 +2514,10 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
def get_contracted_graph(self, contraction_level):
"""This function contracts the nodes of a graph to the provided contraction level.
+ :param contraction_level: from 0 (highest level) to X (lowest level existing in XML schema)
+ :type contraction_level: int
+ :return: contracted_graph: graph with contracted nodes
+
The contraction level refers to the xpath-level, which represents the position of the descendant with respect
to its predecessors. The example below represents a level 3 node, with "cpacs" being at level zero.
@@ -2514,14 +2531,10 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
------------wing
-
- All nodes above the contraction level are removed from the graph and replaced by a "variable group" node, which
- groups the removed nodes in a node at contraction level. This allows for a "de-cluttering" of the graph, with
- the graph connections still being represented.
-
- :param contraction_level: from 0 (highest level) to X (lowest level existing in XML schema)
- :type contraction_level: int
- :return: contracted_graph: graph with contracted nodes
+ .. note::
+ All nodes above the contraction level are removed from the graph and replaced by a "variable group" node, which
+ groups the removed nodes in a node at contraction level. This allows for a "de-cluttering" of the graph, with
+ the graph connections still being represented.
"""
# check input
@@ -2632,6 +2645,11 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
def get_node_subcategory(self, node):
"""Method to analyse a node and to update the subcategory attribute of the node.
+ :param node: node in the graph
+ :type node: basestring
+ :return: subcategory of the node
+ :rtype: basestring
+
The following table illustrates how the subcategory is determined based on the category, indegree and outdegree:
+-------------------+-----------------------------------+----------+-----------+
@@ -2671,11 +2689,6 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
| +-----------------------------------+----------+-----------+
| | complete | >0 | >0 |
+-------------------+-----------------------------------+----------+-----------+
-
- :param node: node in the graph
- :type node: basestring
- :return: subcategory of the node
- :rtype: basestring
"""
# Check node
@@ -2825,17 +2838,17 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
attr_list = [attr_list]
if attr_list == 'all':
- node_attr = self.node[node]
+ node_attr = self.nodes[node]
if print_in_log:
- for key in self.node[node]:
- print ' ' + key + ': ' + str(self.node[node][key])
+ for key in self.nodes[node]:
+ print ' ' + key + ': ' + str(self.nodes[node][key])
elif isinstance(attr_list, list):
for key in attr_list:
# check if key is part of the attributes
- if key in self.node[node]:
- node_attr[key] = self.node[node][key]
+ if key in self.nodes[node]:
+ node_attr[key] = self.nodes[node][key]
if print_in_log:
- print ' ' + key + ': ' + str(self.node[node][key])
+ print ' ' + key + ': ' + str(self.nodes[node][key])
else:
if print_in_log:
print ' ' + key + ': attribute not defined for this node'
@@ -2863,7 +2876,7 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
# Gather data
metadata = []
- node_data = dict(self.node[node])
+ node_data = dict(self.nodes[node])
# First loop over preferred data
for item in preferred_data:
@@ -2994,6 +3007,13 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
def add_objective_function_by_nodes(self, *args, **kwargs):
"""This function adds objective functions to the graph using lists of variable nodes.
+ :param args: list of nodes (list elements must be strings)
+ :type args: list
+ :param kwargs: list of nodes (list elements must be strings)
+ :type kwargs: list
+ :return: list of Objective Functions added to Graph
+ :rtype: list
+
Each list produces a separate objective function node in the graph. If the list if passed as a keyword argument,
the keyword is taken as the name of the objective function node. Otherwise, a standard name will be given to the
node. Each objective function node has one output variable, and takes the nodes given in the argument list as
@@ -3010,14 +3030,7 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
The added objective function nodes can be queried by the attribute:
- >>> Graph.node[node]["name"] == "Objective"
-
- :param args: list of nodes (list elements must be strings)
- :type args: list
- :param kwargs: list of nodes (list elements must be strings)
- :type kwargs: list
- :return: list of Objective Functions added to Graph
- :rtype: list
+ >>> Graph.nodes[node]["name"] == "Objective"
"""
standard_func_name = "OBJECTIVE"
@@ -3089,7 +3102,7 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
for element in obj_fun_tpl[1]:
# make sure node is in graph and in category "variable"
- if element not in self or not self.node[element]["category"] == "variable":
+ if element not in self or not self.nodes[element]["category"] == "variable":
invalid_nodes.append(element)
# remove invalid elements from list
@@ -3147,11 +3160,13 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
def select_objectives_from_graph(self, *args):
"""This functions lets the user select one or more objective functions from the graph.
- Only functions can be selected as objectives. If no arguments are provided, user is prompted to select an
- objective from all functions in graph.
-
- :param: args: objective functions to choose from
+ :param args: objective functions to choose from
+ :type args: str
:return: list of objective functions
+ :rtype: list
+
+ .. note:: Only functions can be selected as objectives. If no arguments are provided, user is prompted to select
+ an objective from all functions in graph.
"""
# check if arguments provided
@@ -3195,24 +3210,24 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
def node_is_objective_function(self, node):
"""This function checks whether the provided node is a objective function.
- This function checks whether the provided node:
- 1) exists in graph
- 2) has name-attribute "Objective"
- 3) has an out-degree of 1
- 4) has an outgoing node with an out-degree of zero # TODO: THIS IS WRONG!
-
- Only if all checks are satisfied, is the node a valid objective function node.
-
:param node: graph node to be tested
:type node: str
:return: check result
:rtype: bool
+
+ This function checks whether the provided node:
+ 1. exists in graph
+ 2. has name-attribute "Objective"
+ 3. has an out-degree of 1
+ 4. has an outgoing node with an out-degree of zero
+
+ .. note:: Only if all checks are satisfied, is the node a valid objective function node.
"""
# TODO: This may not be a good approach (see condition 4 above)
if self.node_is_function(node):
if node in self:
- name_check = self.node[node]['name'] == 'Objective' # TODO: Fix this
+ name_check = self.nodes[node]['name'] == 'Objective' # TODO: Fix this
out_deg_check = self.out_degree(node) == 1
try:
out_node = list(self.out_edges(node))[0][1]
@@ -3228,12 +3243,12 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
def merge_function_nodes_based_on_modes(self, merge_funcs=None):
"""This class method merges all execution modes of the same function into a single node.
- Mainly used for illustration purposes since information on the execution modes gets lost. Functions must be
- present in graph.
-
:param merge_funcs: List of tuple of functions to merge. If empty (default), all functions are merged.
:type merge_funcs: list, tuple
:return: merged graph
+
+ Mainly used for illustration purposes since information on the execution modes gets lost. Functions must be
+ present in graph.
"""
# TODO: What if empty list is given?
@@ -3262,7 +3277,7 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
for super_func in merge_funcs:
if super_func in m_graph: # check if that "super"-function already exists
- func_node = m_graph.node.get(super_func)
+ func_node = m_graph.nodes.get(super_func)
func_keys = [k for k in func_node]
for key in func_keys:
if key in ["mode", "runtime", "precision", "fidelity"]:
@@ -3306,7 +3321,7 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
else:
original_node = node
- node_data_dict = dict(self.node[node])
+ node_data_dict = dict(self.nodes[node])
# Determine the related schema node
if 'related_to_schema_node' in node_data_dict:
@@ -3346,7 +3361,7 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
:param label_extension: extension for labels
:type label_extension: str
:param kwargs: keyword arguments will be added as node attributes
- :type kwargs: dict
+ :type kwargs: dict, int
:return: new node name and enriched graph
:rtype: str
"""
@@ -3356,11 +3371,11 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
assert len(suffix) > 0, 'Suffix string should be larger than zero length.'
new_node = node + suffix
- node_data_dict = dict(self.node[node])
+ node_data_dict = dict(self.nodes[node])
# determine the related schema node
- if 'related_to_schema_node' in self.node[node]:
- related_schema_node = self.node[node]['related_to_schema_node']
+ if 'related_to_schema_node' in self.nodes[node]:
+ related_schema_node = self.nodes[node]['related_to_schema_node']
else:
related_schema_node = node
@@ -3372,7 +3387,7 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
label=get_correctly_extended_latex_label(node_data_dict['label'], label_extension))
if kwargs:
for key, item in kwargs.iteritems():
- self.node[new_node][key] = item
+ self.nodes[new_node][key] = item
return new_node
@@ -3380,40 +3395,36 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
"""Method to relabel all function nodes so that they meet the minimum CMDOWS convention
:param mapping: application of mapping required, optional (default=None)
- :type mapping: None, True
+ :type mapping: None, bool
+ :returns: relabeled graph
CMDOWS convention:
* Minimum information: ID
* Maximum information: ID[modeID][instanceID][version]
- Note: modeID, instanceID and version are only provided if there is a function with the same ID that requires
- this specification to differentiate between the functions.
+ .. note:: modeID, instanceID and version are only provided if there is a function with the same ID that requires
+ this specification to differentiate between the functions.
Example:
Design competences (full information):
- * Aerodynamics[A][1][v1]
- * Aerodynamics[A][2][v1]
- * Aerodynamics[B][1][v1]
-
- * Structures[A][1][v1]
- * Structures[A}[1][v2]
-
- * Propulsion[A][1][v2]
+ #. Aerodynamics[A][1][v1]
+ #. Aerodynamics[A][2][v1]
+ #. Aerodynamics[B][1][v1]
+ #. Structures[A][1][v1]
+ #. Structures[A}[1][v2]
+ #. Propulsion[A][1][v2]
Design competences relabeled:
- * Aerodynamics[A][1]
- * Aerodynamics[A][2]
- * Aerodynamics[B][1]
-
- * Structure[v1]
- * Structure[v2]
-
- * Propulsion
-
+ #. Aerodynamics[A][1]
+ #. Aerodynamics[A][2]
+ #. Aerodynamics[B][1]
+ #. Structure[v1]
+ #. Structure[v2]
+ #. Propulsion
"""
# Determine nodes to be renamed
@@ -3435,10 +3446,10 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
des_comps = []
for design_competence in design_competences:
- id = self.node[design_competence].get('name', design_competence)
- mode = self.node[design_competence].get('mode', 'main')
- instance = self.node[design_competence].get('instance', '1')
- version = self.node[design_competence].get('version', '1.0')
+ id = self.nodes[design_competence].get('name', design_competence)
+ mode = self.nodes[design_competence].get('mode', 'main')
+ instance = self.nodes[design_competence].get('instance', '1')
+ version = self.nodes[design_competence].get('version', '1.0')
mapping[design_competence] = '{}[{}][{}][{}]'.format(id, mode, instance, version)
des_comps.append(design_competence)
labels.append([id])
@@ -3463,7 +3474,7 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
ids_dict[ids[i]] = update
multiples.add(ids[i])
else:
- ids_dict[ids[i]]=i
+ ids_dict[ids[i]] = i
# for the IDs that are used multiple times determine if there is a difference in mode/instance/version
for multiple in multiples:
indices = ids_dict[multiple]
@@ -3500,8 +3511,8 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
[group], mapping)
if 'function_order' in self.graph['problem_formulation']:
- self.graph['problem_formulation']['function_order'] = translate_list(self.graph['problem_formulation']
- ['function_order'], mapping)
+ self.graph['problem_formulation']['function_order'] = \
+ translate_list(self.graph['problem_formulation']['function_order'], mapping)
if 'function_ordering' in self.graph['problem_formulation']:
for group in self.graph['problem_formulation']['function_ordering']:
self.graph['problem_formulation']['function_ordering'][group] = \
@@ -3512,11 +3523,13 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
def remove_function_nodes(self, *args):
"""Function that removes a function node
- Also the input and output variables that only have links to this specific function node are deleted. A simple
- remove_node of a function node might lead to unconnected variables in the graph.
-
:param args: function node id(s)
- :type args: str or list
+ :type args: str, list
+ :return: graph with nodes removed
+ :rtype: KadmosGraph
+
+ .. attention:: Also the input and output variables that only have links to this specific function node are
+ deleted. A simple remove_node of a function node might lead to unconnected variables in the graph.
"""
# Input assertions
@@ -3526,7 +3539,7 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
assert isinstance(arg, basestring), 'Argument %s is not of type basestring.' % arg
assert self.has_node(arg), 'Node "' + str(arg) + '" is not present in the graph.'
assert self.node_is_function(arg), \
- 'Node "' + str(arg) + '" is not of category function (but ' + self.node[arg]['category'] + ').'
+ 'Node "' + str(arg) + '" is not of category function (but ' + self.nodes[arg]['category'] + ').'
# Remove functions including input and output variables (if allowed)
for node in args:
@@ -3552,6 +3565,8 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
:type args: node_ids
:param kwargs: new_label to specify new node label manually (optional)
:type kwargs: dict
+ :return: graph with merged functions
+ :rtype: KadmosGraph
"""
# Handle the fact that the *args could also be a list or tuple directly
@@ -3607,6 +3622,8 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
:type args: node_ids
:param kwargs: new_label to specify new node label manually (optional)
:type kwargs: dict
+ :return: graph with merged function
+ :rtype: KadmosGraph
"""
# Handle the fact that the *args could also be a list or tuple directly
@@ -3646,13 +3663,15 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
def merge_sequential_functions(self, *args, **kwargs):
"""Function to merge a collection of functions.
- It is assumed that the merged functions are actually executed in the sequence in which they are given to this
- function.
-
:param args: functions to be merged in the given sequence
:type args: node_ids
:param kwargs: new_label to specify new node label manually (optional)
:type kwargs: str
+ :return: graph with merged functions
+ :rtype: KadmosGraph
+
+ .. attention:: It is assumed that the merged functions are actually executed in the sequence in which they are
+ given to this function.
"""
# Handle the fact that the *args could also be a list or tuple directly
@@ -3706,7 +3725,7 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
new_graph.remove_edge(coupling_node, new_label)
# If the couplings can be removed, then do so
if 'remove_internal_couplings' in kwargs:
- if kwargs['remove_internal_couplings'] == True:
+ if kwargs['remove_internal_couplings']:
new_graph.remove_node(coupling_node)
new_graph = graph_class(new_graph)
return new_graph
@@ -3796,17 +3815,24 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
def split_variables(self, *args, **kwargs):
"""Method to split a problematic variable node into multiple separate valid nodes.
+ :param args: problematic node in the graph
+ :type args: basestring, list
+ :param kwargs:
+ :type kwargs:
+ :return: graph with split variables
+ :rtype: KadmosGraph
+
The following variables are considered problematic and will be handled by this function:
- * pure circular coupling
- * shared circular coupling
- * collided coupling
- * collision
- * collided circular coupling
- * collided shared coupling
- * collided shared circular coupling
+ * pure circular coupling
+ * shared circular coupling
+ * collided coupling
+ * collision
+ * collided circular coupling
+ * collided shared coupling
+ * collided shared circular coupling
- The following table shows an example situation for each of the different problematic variables:
+ The following table shows an example situation for each of the different problematic variables:
+----------------------+------------------------+----------------+---------------------------------------+
| PROBLEMATIC VARIABLE | SITUATION | FUNCTION ORDER | RESOLVED AS |
@@ -3841,9 +3867,8 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
| | | | x1/variableInstance4 => F6 |
+----------------------+------------------------+----------------+---------------------------------------+
- :param args: problematic node in the graph
- :type args: basestring, list
"""
+ #TODO Imco add kwargs documentation
# Input assertions
if len(args) == 0:
@@ -3941,6 +3966,8 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
def make_all_variables_valid(self):
"""Method to analyze all variables in a graph and make any problematic variables valid.
+ :return: graph with problematic variables removed.
+
Problematic variable are holes and splittables. Splittable variables are split and holes will simply be removed.
"""
@@ -3963,22 +3990,23 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
disconnect_shared_sources=True, ignore_list=[]):
"""Method to automatically disconnect certain problematic variables with respect to a given function.
- If given as setting (disconnect_collided_targets=True) then the collided targets will be disconnected from this
- function. Also, if given as setting (disconnect_shared_sources=True), shared sources are also disconnected.
-
:param function: function around which problematic variables are disconnected
:type function: basestring
:param disconnect_collided_targets: setting to disconnect collided targets
:type disconnect_collided_targets: bool
:param disconnect_shared_sources: setting to disconnect shared sources
:type disconnect_shared_sources: bool
- :param disconnect_shared_sources: setting to ignore certain nodes
- :type disconnect_shared_sources: list
+ :param ignore_list: setting to ignore certain nodes
+ :type ignore_list: list
+
+ If given as setting (disconnect_collided_targets=True) then the collided targets will be disconnected from this
+ function. Also, if given as setting (disconnect_shared_sources=True), shared sources are also disconnected.
"""
# Input assertions
assert self.has_node(function), 'Node {} not present in the graph.'.format(function)
- assert self.node[function]['category'] == 'function', 'Node {} should be of category function.'.format(function)
+ assert self.nodes[function]['category'] == 'function', \
+ 'Node {} should be of category function.'.format(function)
assert isinstance(disconnect_collided_targets, bool)
assert isinstance(disconnect_shared_sources, bool)
assert isinstance(ignore_list, list)
@@ -3999,11 +4027,11 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
# Disconnect if required
for target_node in target_nodes:
- if self.node[target_node]['subcategory'] in \
+ if self.nodes[target_node]['subcategory'] in \
self.NODE_GROUP_SUBCATS['all problematic variables'][3:8]: # all collided subcategories
self.remove_edge(function, target_node)
for source_node in source_nodes:
- if self.node[source_node]['subcategory'] in \
+ if self.nodes[source_node]['subcategory'] in \
get_list_entries(self.NODE_GROUP_SUBCATS['all problematic variables'], 2, 6, 7): # all shared
# subcategories
self.remove_edge(source_node, function)
@@ -4013,8 +4041,6 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
def check_for_coupling(self, function_order, only_feedback=False, raise_error_if_true=False):
"""Function to check for the presence of coupling in a graph for a list of analyses in a given analysis order.
- Note that only the functions in the function_order list are checked for feedback.
-
:param function_order: list with node names of functions
:type function_order: list
:param only_feedback: Boolean on whether to check for feedback coupling only (this is useful for Gauss-Seidel)
@@ -4023,6 +4049,8 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
:type raise_error_if_true: bool
:return: Boolean value on whether coupling exists
:rtype: bool
+
+ .. note:: only the functions in the function_order list are checked for feedback.
"""
# Set coupling initially to False.
@@ -4198,7 +4226,8 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
Get all nodes with any of the listed attribute values:
>>> all_nodes = self.find_all_nodes(category='all', subcategory='all',
- >>> attr_include=[['problem_role', ['constraint', 'objective']], ['instance', 1]])
+ >>> attr_include=[['problem_role', ['constraint', 'objective']],
+ >>> ['instance', 1]])
"""
# TODO: Update docstring
@@ -4296,18 +4325,19 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
if attr_cond is None:
eval_node = True
elif isinstance(attr_cond[0], basestring):
- if attr_cond[0] in self.node[item]:
- if test_attr_cond(self.node[item][attr_cond[0]], attr_cond[1], attr_cond[2]):
+ if attr_cond[0] in self.nodes[item]:
+ if test_attr_cond(self.nodes[item][attr_cond[0]], attr_cond[1], attr_cond[2]):
eval_node = True
else:
eval_node = False
else:
eval_node = False
else:
- eval_node=True
+ eval_node = True
for attr in attr_cond:
- if attr[0] in self.node[item]:
- if test_attr_cond(self.node[item][attr[0]], attr[1], attr[2]) and eval_node:
+ if attr[0] in self.nodes[item]:
+ if test_attr_cond(self.nodes[item][attr[0]], attr[1], attr[2]) and \
+ eval_node:
eval_node = True
else:
eval_node = False
@@ -4326,18 +4356,18 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
# include all nodes (from selection) that have any of the specified attributes.
if attr_include:
filtered = set()
- if isinstance(attr_include,type(None)):
+ if isinstance(attr_include, type(None)):
pass
elif isinstance(attr_include[0], basestring):
for node in all_nodes:
- if self.node[node].get(attr_include[0]):
- if self.node[node][attr_include[0]] in attr_include[1]:
+ if self.nodes[node].get(attr_include[0]):
+ if self.nodes[node][attr_include[0]] in attr_include[1]:
filtered.add(node)
else:
for attr in attr_include:
for node in all_nodes:
- if self.node[node].get(attr[0]):
- if self.node[node][attr[0]] in attr[1]:
+ if self.nodes[node].get(attr[0]):
+ if self.nodes[node][attr[0]] in attr[1]:
filtered.add(node)
filtered = list(filtered)
all_nodes = filtered
@@ -4350,8 +4380,8 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
elif isinstance(attr_exclude[0], basestring):
for node in all_nodes:
choice = True
- if self.node[node].get(attr_exclude[0]):
- if self.node[node][attr_exclude[0]] in attr_exclude[1]:
+ if self.nodes[node].get(attr_exclude[0]):
+ if self.nodes[node][attr_exclude[0]] in attr_exclude[1]:
choice = False
if choice:
filtered.append(node)
@@ -4359,8 +4389,8 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
for attr in attr_exclude:
for node in all_nodes:
choice = True
- if self.node[node].get(attr[0]):
- if self.node[node][attr[0]] in attr[1]:
+ if self.nodes[node].get(attr[0]):
+ if self.nodes[node][attr[0]] in attr[1]:
choice = False
if choice:
filtered.append(node)
@@ -4371,7 +4401,7 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
for xpath in xpath_include:
path = xpath.split('/')
for node in all_nodes:
- node_path = self.node[node]['name'].split('/')
+ node_path = self.nodes[node]['name'].split('/')
for el in range(len(path)):
choice = False
if node_path[el] == path[el]:
@@ -4387,7 +4417,7 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
for xpath in xpath_exclude:
path = xpath.split('/')
for node in all_nodes:
- node_path = self.node[node]['name'].split('/')
+ node_path = self.nodes[node]['name'].split('/')
for el in range(len(path)):
choice = True
if node_path[el] == path[el]:
@@ -4468,24 +4498,29 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
title=None, edge_label=False):
"""Function to plot a graph.
- Note that you need to add matplotlib.pyplot.show() at the end of your code to see the plot window.
-
:param fig_num: figure number
- :param fig_size: size of figure window
+ :type fig_num: int
:param color_setting: choose from 'default', 'sinks', 'categories', 'partitions'
+ :type color_setting: str
:param positioning: choose from 'circular', 'spring'
+ :type positioning: str
:param save_as: save plot as figure file
+ :type save_as: bool
:param show_now: Boolean whether to plot directly (pausing the execution until the plot is closed), or not.
- :param title: title string of the graph
+ :type show_now: bool
+ :param title: title of the graph
+ :type title: str
:param edge_label: edge attribute that will be shown for each edge in graph
+ :type edge_label: str
:return: window with plot
- """
+ .. hint:: if the plot window is not showing, you need to add matplotlib.pyplot.show() at the end of your code
+ """
# Create node labels
node_labels = {}
for node, data in self.nodes(data=True):
- node_labels[node] = self.node[node]['label']
+ node_labels[node] = self.nodes[node]['label']
# Create figure
f = plt.figure(num=fig_num, figsize=(min(len(node_labels)/3, 50), min(len(node_labels)/3, 50)))
@@ -4530,8 +4565,8 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
'function': '#FFD700',
'architecture element': '#66FF99'} # Based on html hex string colors
legend_names = {'variable': 'variable',
- 'variable group':'variable group',
- 'function':'function',
+ 'variable group': 'variable group',
+ 'function': 'function',
'architecture element': 'architecture element'}
for category in node_cate:
@@ -4539,7 +4574,7 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
# the use of the layout.
nx.draw_networkx_nodes(self, pos, with_labels=False,
nodelist=[s_node[0] for s_node in
- filter(lambda x: x[1]["category"] == category, self.nodes(data=True))],
+ filter(lambda x: x[1]["category"] == category, self.nodes(data=True))],
node_shape=node_shapes[category],
node_color=node_colors[category],
node_size=node_sizes[category])
@@ -4559,7 +4594,7 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
node_cate = set((category[1]["category"] for category in self.nodes(data=True)))
for category in node_cate:
- nodelist = nodelist=[s_node[0] for s_node in
+ nodelist = [s_node[0] for s_node in
filter(lambda x: x[1]["category"] == category, self.nodes(data=True))]
node_color = []
for entry in nodelist:
@@ -4602,28 +4637,26 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
node_color = []
for node in nodelist:
if node in grouped_nodes['variable']['hole'] or \
- node in grouped_nodes['variable']['collision'] or \
- node in grouped_nodes['variable']['collided coupling'] or \
- node in grouped_nodes['variable']['collided shared coupling'] or \
- node in grouped_nodes['variable group']['hole group'] or \
- node in grouped_nodes['variable group']['hole group'] or \
- node in grouped_nodes['function']['independent']:
- node_color.append(node_colors['wrong'])
+ node in grouped_nodes['variable']['collision'] or \
+ node in grouped_nodes['variable']['collided coupling'] or \
+ node in grouped_nodes['variable']['collided shared coupling'] or \
+ node in grouped_nodes['variable group']['hole group'] or \
+ node in grouped_nodes['variable group']['hole group'] or \
+ node in grouped_nodes['function']['independent']: node_color.append(node_colors['wrong'])
elif node in grouped_nodes['function']['inputless'] or \
- node in grouped_nodes['function']['outputless']:
+ node in grouped_nodes['function']['outputless']:
node_color.append(node_colors['problematic'])
elif node in grouped_nodes['variable']['supplied input'] or \
- node in grouped_nodes['variable']['supplied shared input'] or \
- node in grouped_nodes['variable']['output'] or \
- node in grouped_nodes['variable group']['supplied input group'] or \
- node in grouped_nodes['variable group']['supplied shared input group'] or \
- node in grouped_nodes['variable group']['output group'] or \
- node in grouped_nodes['function']['complete']:
- node_color.append(node_colors['accepted'])
+ node in grouped_nodes['variable']['supplied shared input'] or \
+ node in grouped_nodes['variable']['output'] or \
+ node in grouped_nodes['variable group']['supplied input group'] or \
+ node in grouped_nodes['variable group']['supplied shared input group'] or \
+ node in grouped_nodes['variable group']['output group'] or \
+ node in grouped_nodes['function']['complete']: node_color.append(node_colors['accepted'])
elif node in grouped_nodes['variable']['coupling'] or \
- node in grouped_nodes['variable']['shared coupling'] or \
- node in grouped_nodes['variable group']['coupling group'] or \
- node in grouped_nodes['variable group']['shared coupling group']:
+ node in grouped_nodes['variable']['shared coupling'] or \
+ node in grouped_nodes['variable group']['coupling group'] or \
+ node in grouped_nodes['variable group']['shared coupling group']:
node_color.append(node_colors['couplings'])
else:
raise AttributeError('Node not found in node grouping dictionary.')
@@ -4650,8 +4683,8 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
filter(lambda x: x[1]["category"] == category, self.nodes(data=True))]
node_color = []
for node in nodelist:
- node_color.append(self.node[node]['part_color'])
- color_set.add(self.node[node]['part_color'])
+ node_color.append(self.nodes[node]['part_color'])
+ color_set.add(self.nodes[node]['part_color'])
# Draw the subset of nodes with the same symbol in the positions that are now known through the
# use of the layout.
nx.draw_networkx_nodes(self, pos,
@@ -4675,7 +4708,7 @@ class KadmosGraph(nx.DiGraph, EquationMixin, VistomsMixin):
nx.draw_networkx_edges(self, pos, arrows=True, ax=ax, width=0.5, arrowstyle='->',
nodesize=node_sizes['function'])
- if len(node_labels)<100:
+ if len(node_labels) < 100:
nx.draw_networkx_labels(self, pos, node_labels, fontsize=10, ax=ax)
if edge_label:
# noinspection PyUnboundLocalVariable
@@ -4752,7 +4785,10 @@ def load(file_name, file_type=None, check_list=None, file_check_critical=True, s
'schemas': to check XML input/output files against a schema file (XSD) in case of CMDOWS file in combination
with in- and output XML files.
:type check_list: list
-
+ :param ignore_modes: for determining if modes are taken into account
+ :type ignore_modes: bool
+ :param keep_running: for determining if errors should be raised
+ :type keep_running: bool
:return: graph loaded from file
:rtype: KadmosGraph
"""
@@ -4813,28 +4849,27 @@ def load(file_name, file_type=None, check_list=None, file_check_critical=True, s
def check_database(file_name, source_folder=None, check_list=None, keep_running=False):
"""Method to check the XML-files inside the database for parse errors, inconsistent roots, invalid leaf elements
- and schema inconsistencies.
+ and schema inconsistencies.
- :param file_name: name of the cmdows file.
- :type file_name: str
- :param file_type: file_type
- :type file_type: str
- :param source_folder: source folder which contains the input file
- :type source_folder: str
- :param check_list: list with checks to be performed on in case of CMDOWS file with in-/output XML files.
- :type check_list: list
-
- :return: graph loaded from file
- :rtype: KadmosGraph
+ :param file_name: name of the cmdows file.
+ :type file_name: str
+ :param source_folder: source folder which contains the input file
+ :type source_folder: str
+ :param check_list: list with checks to be performed on in case of CMDOWS file with in-/output XML files.
+ :type check_list: list
+ :param keep_running: for determining if errors should be raised
+ :type keep_running: bool
+ :return: graph loaded from file
+ :rtype: KadmosGraph
- Check_list options:
+ Check_list options:
- * 'consistent_root': to check XML input/output files have the same, single root element.
- * 'invalid_leaf_elements': to check XML input/output files for invalid leaf elements.
- * 'schemas': to check XML input/output files against a schema file (XSD) in case of CMDOWS file in combination
- with in- and output XML files.
+ * 'consistent_root': to check XML input/output files have the same, single root element.
+ * 'invalid_leaf_elements': to check XML input/output files for invalid leaf elements.
+ * 'schemas': to check XML input/output files against a schema file (XSD) in case of CMDOWS file in combination
+ with in- and output XML files.
- """
+ """
# Try to detect the file type automatically
if file_name.lower().endswith(tuple(file_extensions)):
@@ -4938,6 +4973,7 @@ def _perform_check_list(io_list, check_list, keep_running=False):
return
+
def _load_kdms(file_path):
# Parse
@@ -5060,7 +5096,7 @@ def _read_io_xml_file(file_path, mode, ignore_modes=False):
if not el.getchildren(): # if leaf node
- if _check_execution_mode_for_element(el, tree, file_path, mode, ignore_modes=ignore_modes): # if right mode specification
+ if _check_execution_mode_for_element(el, tree, file_path, mode, ignore_modes=ignore_modes):
# append path to list of leaf nodes
leafNodesList.append(path)
@@ -5158,12 +5194,12 @@ def _check_execution_mode_for_element(element, tree, file, req_mode, ignore_mode
else:
# get element xpath
elementPath = tree.getpath(element)
-
# get function modes from info file and assert that they are unique
- execModes = '' # NOTE: if no modes indicated, all modes are applied to node
+ execModes = '' # NOTE: if no modes indicated, all modes are applied to node
modesFound = False
- if 'modes' in element.attrib and re.search("[^\s]", element.attrib['modes']): # if 'modes' key present and has characters
+ # if 'modes' key present and has characters
+ if 'modes' in element.attrib and re.search("[^\s]", element.attrib['modes']):
assert isinstance(element.attrib['modes'], basestring), "If provided, modes-attribute of element {} in " \
"{} must be of type string.".format(elementPath,
file)
@@ -5171,13 +5207,13 @@ def _check_execution_mode_for_element(element, tree, file, req_mode, ignore_mode
modesFound = True
for anc in element.iterancestors():
- if 'modes' in anc.attrib and re.search("[^\s]", anc.attrib['modes']):
+ if 'modes' in anc.attrib and re.search("[^\s]", anc.attrib['modes']):
if not modesFound:
modesFound = True
execModes = anc.attrib['modes']
else:
- logger.warning("Multiple 'modes' attributes found in ancestry of element {} in {}; lowest one is " \
- "applied.".format(elementPath, file))
+ logger.warning("Multiple 'modes' attributes found in ancestry of element {} in {}; lowest one is "
+ "applied.".format(elementPath, file))
break
negModesList = []
@@ -5195,7 +5231,6 @@ def _check_execution_mode_for_element(element, tree, file, req_mode, ignore_mode
negModesList = [mode[1:] for mode in modesList]
modesList = []
-
# check if the mode is the required mode
if req_mode in modesList or not modesList:
if req_mode not in negModesList:
@@ -5263,11 +5298,13 @@ def _validate_file_against_schema(file_path, schema_path, keep_running=False):
'additional info).'.format(os.path.split(file_path)[1], os.path.split(schema_path)[1]))
return
+
def _check_roots(io_list, keep_running=False):
- """
- This function checks if there are inconsistent roots in the XML input and output files.
+ """This function checks if there are inconsistent roots in the XML input and output files.
+
:rtype: Warning
"""
+
logger.info('Checking for inconsistent roots...')
first_file = True
@@ -5353,7 +5390,7 @@ def _check_leafs(io_list, leafs, keep_running=False):
return
-def _parse_check(io_list, keep_running=False):
+def _parse_check(io_list):
logger.info('Checking for parsing errors...')
for entry in io_list:
file_path=entry[0]
@@ -5372,4 +5409,3 @@ def _try_parsing(file_path, keep_running=False):
raise IOError('Could not parse XML file {}. Check file structure.'.format(os.path.split(file_path)[1]))
return tree
-
diff --git a/kadmos/utilities/printing.py b/kadmos/utilities/printing.py
index e98fa21cd4efb34522c86f1d9d789f90ef699443..213d207a73625b9fea3dcc326572c8977279d4b4 100644
--- a/kadmos/utilities/printing.py
+++ b/kadmos/utilities/printing.py
@@ -42,7 +42,7 @@ def print_in_table(print_container, **kwargs):
:param print_container: container for iterables --> [[row1], [row2], ...]
:type print_container: iterable
:param kwargs: keyword arguments for printing
- :type kwargs: str
+ :type kwargs: str, bool
Kwargs options: