deploy: 5b3d7a6

_sources/autoapi/lasdi/param/index.rst.txt

@@ -93,11 +93,11 @@ Module Contents
 
       Concatenates the provided lists of training points into a 2D array.
 
-      param_list: A list of parameter dictionaries
+      :Parameters: **param_list** (:obj:`list(dict)`) -- A list of parameter dictionaries
 
-      Output: mesh_grid
-          - np.array of size [d, k], where d is the number of points provided on the exterior of
-            the training space and k is the number of parameters (k == len(param_list)).
+      :returns: **mesh_grids** -- np.array of size [d, k], where d is the number of points provided on the exterior of
+                the training space and k is the number of parameters (k == len(param_list)).
+      :rtype: :obj:`numpy.array`
 
 
 
@@ -108,9 +108,12 @@ Module Contents
 
       Builds an initial uniform grid for the testing parameters when the test_space is 'hull'.
 
-      param_list: A list of parameter dictionaries
+      :Parameters: **param_list** (:obj:`list(dict)`) -- A list of parameter dictionaries
 
-      Output: gridSizes, mesh_grids, param_grid
+      :returns: * **gridSizes** (:obj:`list(Nx)`) -- A list containing the number of elements on the grid in each parameter.
+                * **mesh_grids** (:obj:`numpy.array`) -- tuple of numpy nd arrays, corresponding to each parameter.
+                  Dimension of the array equals to the number of parameters.
+                * **param_grid** (:obj:`numpy.array`) -- numpy 2d array of size (grid size x number of parameters).
 
 
 
@@ -120,9 +123,13 @@ Module Contents
       returns any testing points which are within the convex hull of the provided
       training parameters.
 
-      param_list: A list of parameter dictionaries
+      :Parameters: **param_list** (:obj:`list(dict)`) -- A list of parameter dictionaries
 
-      Output: gridSizes, mesh_grids, test_space
+      :returns: * **gridSizes** (:obj:`list(Nx)`) -- A list containing the number of elements on the grid in each parameter.
+                * **mesh_grids** (:obj:`numpy.array`) -- tuple of numpy nd arrays, corresponding to each parameter.
+                  Dimension of the array equals to the number of parameters.
+                * **test_space** (:obj:`numpy.array`) -- numpy 2d array of size [d, k], where d is the number of testing points within
+                  convex hull of the training space and k is the number of parameters (k == len(param_list)).
 
 
 

autoapi/lasdi/param/index.html

@@ -208,12 +208,16 @@ <h2>Module Contents<a class="headerlink" href="#module-contents" title="Permalin
 <dt class="sig sig-object py" id="lasdi.param.ParameterSpace.createInitialTrainSpaceForHull">
 <span class="sig-name descname"><span class="pre">createInitialTrainSpaceForHull</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">param_list</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#lasdi.param.ParameterSpace.createInitialTrainSpaceForHull" title="Permalink to this definition"></a></dt>
 <dd><p>Concatenates the provided lists of training points into a 2D array.</p>
-<p>param_list: A list of parameter dictionaries</p>
-<dl class="simple">
-<dt>Output: mesh_grid</dt><dd><ul class="simple">
-<li><p>np.array of size [d, k], where d is the number of points provided on the exterior of
-the training space and k is the number of parameters (k == len(param_list)).</p></li>
-</ul>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><p><strong>param_list</strong> (<code class="xref py py-obj docutils literal notranslate"><span class="pre">list(dict)</span></code>) – A list of parameter dictionaries</p>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p><strong>mesh_grids</strong> – np.array of size [d, k], where d is the number of points provided on the exterior of
+the training space and k is the number of parameters (k == len(param_list)).</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">numpy.array</span></code></p>
 </dd>
 </dl>
 </dd></dl>
@@ -227,8 +231,20 @@ <h2>Module Contents<a class="headerlink" href="#module-contents" title="Permalin
 <dt class="sig sig-object py" id="lasdi.param.ParameterSpace.createTestGridSpaceForHull">
 <span class="sig-name descname"><span class="pre">createTestGridSpaceForHull</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">param_list</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#lasdi.param.ParameterSpace.createTestGridSpaceForHull" title="Permalink to this definition"></a></dt>
 <dd><p>Builds an initial uniform grid for the testing parameters when the test_space is ‘hull’.</p>
-<p>param_list: A list of parameter dictionaries</p>
-<p>Output: gridSizes, mesh_grids, param_grid</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><p><strong>param_list</strong> (<code class="xref py py-obj docutils literal notranslate"><span class="pre">list(dict)</span></code>) – A list of parameter dictionaries</p>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p><ul class="simple">
+<li><p><strong>gridSizes</strong> (<code class="xref py py-obj docutils literal notranslate"><span class="pre">list(Nx)</span></code>) – A list containing the number of elements on the grid in each parameter.</p></li>
+<li><p><strong>mesh_grids</strong> (<code class="xref py py-obj docutils literal notranslate"><span class="pre">numpy.array</span></code>) – tuple of numpy nd arrays, corresponding to each parameter.
+Dimension of the array equals to the number of parameters.</p></li>
+<li><p><strong>param_grid</strong> (<code class="xref py py-obj docutils literal notranslate"><span class="pre">numpy.array</span></code>) – numpy 2d array of size (grid size x number of parameters).</p></li>
+</ul>
+</p>
+</dd>
+</dl>
 </dd></dl>
 
 <dl class="py method">
@@ -237,8 +253,21 @@ <h2>Module Contents<a class="headerlink" href="#module-contents" title="Permalin
 <dd><p>This function builds an initial uniform grid for the testing parameters, and then
 returns any testing points which are within the convex hull of the provided
 training parameters.</p>
-<p>param_list: A list of parameter dictionaries</p>
-<p>Output: gridSizes, mesh_grids, test_space</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><p><strong>param_list</strong> (<code class="xref py py-obj docutils literal notranslate"><span class="pre">list(dict)</span></code>) – A list of parameter dictionaries</p>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p><ul class="simple">
+<li><p><strong>gridSizes</strong> (<code class="xref py py-obj docutils literal notranslate"><span class="pre">list(Nx)</span></code>) – A list containing the number of elements on the grid in each parameter.</p></li>
+<li><p><strong>mesh_grids</strong> (<code class="xref py py-obj docutils literal notranslate"><span class="pre">numpy.array</span></code>) – tuple of numpy nd arrays, corresponding to each parameter.
+Dimension of the array equals to the number of parameters.</p></li>
+<li><p><strong>test_space</strong> (<code class="xref py py-obj docutils literal notranslate"><span class="pre">numpy.array</span></code>) – numpy 2d array of size [d, k], where d is the number of testing points within
+convex hull of the training space and k is the number of parameters (k == len(param_list)).</p></li>
+</ul>
+</p>
+</dd>
+</dl>
 </dd></dl>
 
 <dl class="py method">