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51  <h1>Source code for sas.models.dispersion_models</h1><div class="highlight"><pre>
52<span class="c">################################################################################</span>
53<span class="c">#This software was developed by the University of Tennessee as part of the</span>
54<span class="c">#Distributed Data Analysis of Neutron Scattering Experiments (DANSE)</span>
55<span class="c">#project funded by the US National Science Foundation.</span>
56<span class="c">#</span>
57<span class="c">#If you use DANSE applications to do scientific research that leads to</span>
58<span class="c">#publication, we ask that you acknowledge the use of the software with the</span>
59<span class="c">#following sentence:</span>
60<span class="c">#</span>
61<span class="c">#&quot;This work benefited from DANSE software developed under NSF award DMR-0520547.&quot;</span>
62<span class="c">#</span>
63<span class="c">#copyright 2008, University of Tennessee</span>
64<span class="c">################################################################################</span>
65
66<span class="sd">&quot;&quot;&quot;</span>
67<span class="sd">Class definitions for python dispersion model for </span>
68<span class="sd">model parameters. These classes are bridges to the C++</span>
69<span class="sd">dispersion object.</span>
70
71<span class="sd">The ArrayDispersion class takes in numpy arrays only.</span>
72
73<span class="sd">Usage:</span>
74<span class="sd">These classes can be used to set the dispersion model of a SAS model</span>
75<span class="sd">parameter:</span>
76
77<span class="sd">    cyl = CylinderModel()</span>
78<span class="sd">    cyl.set_dispersion(&#39;radius&#39;, GaussianDispersion())</span>
79
80
81<span class="sd">After the dispersion model is set, you can access it&#39;s</span>
82<span class="sd">parameter through the dispersion dictionary:</span>
83
84<span class="sd">    cyl.dispersion[&#39;radius&#39;][&#39;width&#39;] = 5.0</span>
85
86<span class="sd">:TODO: For backward compatibility, the model parameters are still kept in</span>
87<span class="sd">    a dictionary. The next iteration of refactoring work should involve moving</span>
88<span class="sd">    away from value-based parameters to object-based parameter. We want to</span>
89<span class="sd">    store parameters as objects so that we can unify the &#39;params&#39; and &#39;dispersion&#39;</span>
90<span class="sd">    dictionaries into a single dictionary of parameter objects that hold the</span>
91<span class="sd">    complete information about the parameter (units, limits, dispersion model, etc...).  </span>
92
93<span class="sd">    </span>
94<span class="sd">&quot;&quot;&quot;</span>
95<span class="kn">import</span> <span class="nn">sas_extension.c_models</span> <span class="kn">as</span> <span class="nn">c_models</span> 
96
97
98
99<span class="k">class</span> <span class="nc">DispersionModel</span><span class="p">:</span>
100<div class="viewcode-block" id="DispersionModel"><a class="viewcode-back" href="../../../dev/api/sas.models.html#sas.models.dispersion_models.DispersionModel">[docs]</a>    <span class="sd">&quot;&quot;&quot;</span>
101<span class="sd">    Python bridge class for a basic dispersion model </span>
102<span class="sd">    class with a constant parameter value distribution</span>
103<span class="sd">    &quot;&quot;&quot;</span>
104    <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
105        <span class="bp">self</span><span class="o">.</span><span class="n">cdisp</span> <span class="o">=</span> <span class="n">c_models</span><span class="o">.</span><span class="n">new_dispersion_model</span><span class="p">()</span>
106       
107    <span class="k">def</span> <span class="nf">set_weights</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">,</span> <span class="n">weights</span><span class="p">):</span>
108<div class="viewcode-block" id="DispersionModel.set_weights"><a class="viewcode-back" href="../../../dev/api/sas.models.html#sas.models.dispersion_models.DispersionModel.set_weights">[docs]</a>        <span class="sd">&quot;&quot;&quot;</span>
109<span class="sd">        Set the weights of an array dispersion</span>
110<span class="sd">        &quot;&quot;&quot;</span>
111        <span class="n">message</span> <span class="o">=</span> <span class="s">&quot;set_weights is not available for DispersionModel.</span><span class="se">\n</span><span class="s">&quot;</span>
112        <span class="n">message</span> <span class="o">+=</span> <span class="s">&quot;  Solution: Use an ArrayDispersion object&quot;</span>
113        <span class="k">raise</span> <span class="s">&quot;RuntimeError&quot;</span><span class="p">,</span> <span class="n">message</span>
114       
115<span class="k">class</span> <span class="nc">GaussianDispersion</span><span class="p">(</span><span class="n">DispersionModel</span><span class="p">):</span></div></div>
116<div class="viewcode-block" id="GaussianDispersion"><a class="viewcode-back" href="../../../dev/api/sas.models.html#sas.models.dispersion_models.GaussianDispersion">[docs]</a>    <span class="sd">&quot;&quot;&quot;</span>
117<span class="sd">    Python bridge class for a dispersion model based </span>
118<span class="sd">    on a Gaussian distribution.</span>
119<span class="sd">    &quot;&quot;&quot;</span>
120    <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
121        <span class="bp">self</span><span class="o">.</span><span class="n">cdisp</span> <span class="o">=</span> <span class="n">c_models</span><span class="o">.</span><span class="n">new_gaussian_model</span><span class="p">()</span>
122       
123    <span class="k">def</span> <span class="nf">set_weights</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">,</span> <span class="n">weights</span><span class="p">):</span>
124<div class="viewcode-block" id="GaussianDispersion.set_weights"><a class="viewcode-back" href="../../../dev/api/sas.models.html#sas.models.dispersion_models.GaussianDispersion.set_weights">[docs]</a>        <span class="sd">&quot;&quot;&quot;</span>
125<span class="sd">            Set the weights of an array dispersion</span>
126<span class="sd">        &quot;&quot;&quot;</span>
127        <span class="n">message</span> <span class="o">=</span> <span class="s">&quot;set_weights is not available for GaussianDispersion.</span><span class="se">\n</span><span class="s">&quot;</span>
128        <span class="n">message</span> <span class="o">+=</span> <span class="s">&quot;  Solution: Use an ArrayDispersion object&quot;</span>
129        <span class="k">raise</span> <span class="s">&quot;RuntimeError&quot;</span><span class="p">,</span> <span class="n">message</span>
130       
131<span class="k">class</span> <span class="nc">RectangleDispersion</span><span class="p">(</span><span class="n">DispersionModel</span><span class="p">):</span></div></div>
132<div class="viewcode-block" id="RectangleDispersion"><a class="viewcode-back" href="../../../dev/api/sas.models.html#sas.models.dispersion_models.RectangleDispersion">[docs]</a>    <span class="sd">&quot;&quot;&quot;</span>
133<span class="sd">    Python bridge class for a dispersion model based </span>
134<span class="sd">    on a Gaussian distribution.</span>
135<span class="sd">    &quot;&quot;&quot;</span>
136    <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
137        <span class="bp">self</span><span class="o">.</span><span class="n">cdisp</span> <span class="o">=</span> <span class="n">c_models</span><span class="o">.</span><span class="n">new_rectangle_model</span><span class="p">()</span>
138       
139    <span class="k">def</span> <span class="nf">set_weights</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">,</span> <span class="n">weights</span><span class="p">):</span>
140<div class="viewcode-block" id="RectangleDispersion.set_weights"><a class="viewcode-back" href="../../../dev/api/sas.models.html#sas.models.dispersion_models.RectangleDispersion.set_weights">[docs]</a>        <span class="sd">&quot;&quot;&quot;</span>
141<span class="sd">            Set the weights of an array dispersion</span>
142<span class="sd">        &quot;&quot;&quot;</span>
143        <span class="n">message</span> <span class="o">=</span> <span class="s">&quot;set_weights is not available for GaussianDispersion.</span><span class="se">\n</span><span class="s">&quot;</span>
144        <span class="n">message</span> <span class="o">+=</span> <span class="s">&quot;  Solution: Use an ArrayDispersion object&quot;</span>
145        <span class="k">raise</span> <span class="s">&quot;RuntimeError&quot;</span><span class="p">,</span> <span class="n">message</span> 
146   
147<span class="k">class</span> <span class="nc">SchulzDispersion</span><span class="p">(</span><span class="n">DispersionModel</span><span class="p">):</span></div></div>
148<div class="viewcode-block" id="SchulzDispersion"><a class="viewcode-back" href="../../../dev/api/sas.models.html#sas.models.dispersion_models.SchulzDispersion">[docs]</a>    <span class="sd">&quot;&quot;&quot;</span>
149<span class="sd">        Python bridge class for a dispersion model based </span>
150<span class="sd">        on a Schulz distribution.</span>
151<span class="sd">    &quot;&quot;&quot;</span>
152    <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
153        <span class="sd">&quot;&quot;&quot;</span>
154<span class="sd">        &quot;&quot;&quot;</span>
155        <span class="bp">self</span><span class="o">.</span><span class="n">cdisp</span> <span class="o">=</span> <span class="n">c_models</span><span class="o">.</span><span class="n">new_schulz_model</span><span class="p">()</span>
156       
157    <span class="k">def</span> <span class="nf">set_weights</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">,</span> <span class="n">weights</span><span class="p">):</span>
158<div class="viewcode-block" id="SchulzDispersion.set_weights"><a class="viewcode-back" href="../../../dev/api/sas.models.html#sas.models.dispersion_models.SchulzDispersion.set_weights">[docs]</a>        <span class="sd">&quot;&quot;&quot;</span>
159<span class="sd">        Set the weights of an array dispersion</span>
160<span class="sd">        &quot;&quot;&quot;</span>
161        <span class="n">message</span> <span class="o">=</span> <span class="s">&quot;set_weights is not available for SchulzDispersion.</span><span class="se">\n</span><span class="s">&quot;</span>
162        <span class="n">message</span> <span class="o">+=</span> <span class="s">&quot;  Solution: Use an ArrayDispersion object&quot;</span>
163        <span class="k">raise</span> <span class="s">&quot;RuntimeError&quot;</span><span class="p">,</span> <span class="n">message</span>
164   
165<span class="k">class</span> <span class="nc">LogNormalDispersion</span><span class="p">(</span><span class="n">DispersionModel</span><span class="p">):</span></div></div>
166<div class="viewcode-block" id="LogNormalDispersion"><a class="viewcode-back" href="../../../dev/api/sas.models.html#sas.models.dispersion_models.LogNormalDispersion">[docs]</a>    <span class="sd">&quot;&quot;&quot;</span>
167<span class="sd">    Python bridge class for a dispersion model based </span>
168<span class="sd">    on a Log Normal distribution.</span>
169<span class="sd">    &quot;&quot;&quot;</span>
170    <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
171        <span class="bp">self</span><span class="o">.</span><span class="n">cdisp</span> <span class="o">=</span> <span class="n">c_models</span><span class="o">.</span><span class="n">new_lognormal_model</span><span class="p">()</span>
172       
173    <span class="k">def</span> <span class="nf">set_weights</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">,</span> <span class="n">weights</span><span class="p">):</span>
174<div class="viewcode-block" id="LogNormalDispersion.set_weights"><a class="viewcode-back" href="../../../dev/api/sas.models.html#sas.models.dispersion_models.LogNormalDispersion.set_weights">[docs]</a>        <span class="sd">&quot;&quot;&quot;</span>
175<span class="sd">        Set the weights of an array dispersion</span>
176<span class="sd">        &quot;&quot;&quot;</span>
177        <span class="n">message</span> <span class="o">=</span> <span class="s">&quot;set_weights is not available for LogNormalDispersion.</span><span class="se">\n</span><span class="s">&quot;</span>
178        <span class="n">message</span> <span class="o">+=</span> <span class="s">&quot;  Solution: Use an ArrayDispersion object&quot;</span>
179        <span class="k">raise</span> <span class="s">&quot;RuntimeError&quot;</span><span class="p">,</span> <span class="n">message</span>
180       
181<span class="k">class</span> <span class="nc">ArrayDispersion</span><span class="p">(</span><span class="n">DispersionModel</span><span class="p">):</span></div></div>
182<div class="viewcode-block" id="ArrayDispersion"><a class="viewcode-back" href="../../../dev/api/sas.models.html#sas.models.dispersion_models.ArrayDispersion">[docs]</a>    <span class="sd">&quot;&quot;&quot;</span>
183<span class="sd">    Python bridge class for a dispersion model based on arrays.</span>
184<span class="sd">    The user has to set a weight distribution that</span>
185<span class="sd">    will be used in the averaging the model parameter</span>
186<span class="sd">    it is applied to. </span>
187<span class="sd">    &quot;&quot;&quot;</span>
188    <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
189        <span class="bp">self</span><span class="o">.</span><span class="n">cdisp</span> <span class="o">=</span> <span class="n">c_models</span><span class="o">.</span><span class="n">new_array_model</span><span class="p">()</span>
190       
191    <span class="k">def</span> <span class="nf">set_weights</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">,</span> <span class="n">weights</span><span class="p">):</span>
192<div class="viewcode-block" id="ArrayDispersion.set_weights"><a class="viewcode-back" href="../../../dev/api/sas.models.html#sas.models.dispersion_models.ArrayDispersion.set_weights">[docs]</a>        <span class="sd">&quot;&quot;&quot;</span>
193<span class="sd">        Set the weights of an array dispersion</span>
194<span class="sd">        Only accept numpy arrays.</span>
195<span class="sd">        </span>
196<span class="sd">        :param values: numpy array of values</span>
197<span class="sd">        :param weights: numpy array of weights for each value entry</span>
198<span class="sd">        </span>
199<span class="sd">        &quot;&quot;&quot;</span>
200        <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">values</span><span class="p">)</span> <span class="o">!=</span> <span class="nb">len</span><span class="p">(</span><span class="n">weights</span><span class="p">):</span>
201            <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">,</span> <span class="s">&quot;ArrayDispersion.set_weights: </span><span class="se">\</span>
202<span class="s">            given arrays are of different lengths&quot;</span>
203       
204        <span class="n">c_models</span><span class="o">.</span><span class="n">set_dispersion_weights</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">cdisp</span><span class="p">,</span> <span class="n">values</span><span class="p">,</span> <span class="n">weights</span><span class="p">)</span>
205       
206<span class="n">models</span> <span class="o">=</span> <span class="p">{</span><span class="s">&quot;gaussian&quot;</span><span class="p">:</span><span class="n">GaussianDispersion</span><span class="p">,</span>  <span class="s">&quot;rectangula&quot;</span><span class="p">:</span><span class="n">RectangleDispersion</span><span class="p">,</span></div></div>
207          <span class="s">&quot;array&quot;</span><span class="p">:</span><span class="n">ArrayDispersion</span><span class="p">,</span> <span class="s">&quot;schulz&quot;</span><span class="p">:</span><span class="n">SchulzDispersion</span><span class="p">,</span> 
208          <span class="s">&quot;lognormal&quot;</span><span class="p">:</span><span class="n">LogNormalDispersion</span><span class="p">}</span>       
209       
210</pre></div>
211
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