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51  <h1>Source code for sas.models.LineModel</h1><div class="highlight"><pre>
52<span class="c">#!/usr/bin/env python</span>
53<span class="sd">&quot;&quot;&quot; </span>
54<span class="sd">    Provide Line function (y= A + Bx) as a BaseComponent model</span>
55<span class="sd">&quot;&quot;&quot;</span>
56
57<span class="kn">from</span> <span class="nn">sas.models.BaseComponent</span> <span class="kn">import</span> <span class="n">BaseComponent</span>
58<span class="kn">import</span> <span class="nn">math</span>
59<span class="kn">import</span> <span class="nn">numpy</span>
60
61
62<div class="viewcode-block" id="LineModel"><a class="viewcode-back" href="../../../dev/api/sas.models.html#sas.models.LineModel.LineModel">[docs]</a><span class="k">class</span> <span class="nc">LineModel</span><span class="p">(</span><span class="n">BaseComponent</span><span class="p">):</span>
63    <span class="sd">&quot;&quot;&quot; </span>
64<span class="sd">        Class that evaluates a linear model.</span>
65<span class="sd">        </span>
66<span class="sd">        f(x) = A + Bx</span>
67<span class="sd">         </span>
68<span class="sd">        List of default parameters:</span>
69<span class="sd">          A = 1.0</span>
70<span class="sd">          B = 1.0 </span>
71<span class="sd">    &quot;&quot;&quot;</span>
72       
73    <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
74        <span class="sd">&quot;&quot;&quot; Initialization &quot;&quot;&quot;</span>
75       
76        <span class="c"># Initialize BaseComponent first, then sphere</span>
77        <span class="n">BaseComponent</span><span class="o">.</span><span class="n">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span>
78       
79        <span class="c">## Name of the model</span>
80        <span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s">&quot;LineModel&quot;</span>
81
82        <span class="c">## Define parameters</span>
83        <span class="bp">self</span><span class="o">.</span><span class="n">params</span> <span class="o">=</span> <span class="p">{}</span>
84        <span class="bp">self</span><span class="o">.</span><span class="n">params</span><span class="p">[</span><span class="s">&#39;A&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="mf">1.0</span>
85        <span class="bp">self</span><span class="o">.</span><span class="n">params</span><span class="p">[</span><span class="s">&#39;B&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="mf">1.0</span>
86        <span class="bp">self</span><span class="o">.</span><span class="n">description</span><span class="o">=</span><span class="s">&#39;f(x) = A + Bx&#39;</span>
87        <span class="c">## Parameter details [units, min, max]</span>
88        <span class="bp">self</span><span class="o">.</span><span class="n">details</span> <span class="o">=</span> <span class="p">{}</span>
89        <span class="bp">self</span><span class="o">.</span><span class="n">details</span><span class="p">[</span><span class="s">&#39;A&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="p">[</span><span class="s">&#39;&#39;</span><span class="p">,</span> <span class="bp">None</span><span class="p">,</span> <span class="bp">None</span><span class="p">]</span>
90        <span class="bp">self</span><span class="o">.</span><span class="n">details</span><span class="p">[</span><span class="s">&#39;B&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="p">[</span><span class="s">&#39;&#39;</span><span class="p">,</span> <span class="bp">None</span><span class="p">,</span> <span class="bp">None</span><span class="p">]</span>
91        <span class="c"># fixed paramaters</span>
92        <span class="bp">self</span><span class="o">.</span><span class="n">fixed</span><span class="o">=</span><span class="p">[]</span>
93    <span class="k">def</span> <span class="nf">_line</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">):</span>
94        <span class="sd">&quot;&quot;&quot;</span>
95<span class="sd">            Evaluate the function</span>
96<span class="sd">            @param x: x-value</span>
97<span class="sd">            @return: function value</span>
98<span class="sd">        &quot;&quot;&quot;</span>
99        <span class="k">return</span>  <span class="bp">self</span><span class="o">.</span><span class="n">params</span><span class="p">[</span><span class="s">&#39;A&#39;</span><span class="p">]</span> <span class="o">+</span> <span class="n">x</span> <span class="o">*</span><span class="bp">self</span><span class="o">.</span><span class="n">params</span><span class="p">[</span><span class="s">&#39;B&#39;</span><span class="p">]</span>
100   
101<div class="viewcode-block" id="LineModel.run"><a class="viewcode-back" href="../../../dev/api/sas.models.html#sas.models.LineModel.LineModel.run">[docs]</a>    <span class="k">def</span> <span class="nf">run</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span> <span class="o">=</span> <span class="mf">0.0</span><span class="p">):</span>
102        <span class="sd">&quot;&quot;&quot; Evaluate the model</span>
103<span class="sd">            @param x: simple value</span>
104<span class="sd">            @return: (Line value)</span>
105<span class="sd">        &quot;&quot;&quot;</span>
106        <span class="k">if</span> <span class="n">x</span><span class="o">.</span><span class="n">__class__</span><span class="o">.</span><span class="n">__name__</span> <span class="o">==</span> <span class="s">&#39;list&#39;</span><span class="p">:</span>
107            <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_line</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">*</span><span class="n">math</span><span class="o">.</span><span class="n">cos</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">1</span><span class="p">]))</span><span class="o">*</span><span class="bp">self</span><span class="o">.</span><span class="n">_line</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">*</span><span class="n">math</span><span class="o">.</span><span class="n">sin</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">1</span><span class="p">]))</span>
108        <span class="k">elif</span> <span class="n">x</span><span class="o">.</span><span class="n">__class__</span><span class="o">.</span><span class="n">__name__</span> <span class="o">==</span> <span class="s">&#39;tuple&#39;</span><span class="p">:</span>
109            <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">,</span> <span class="s">&quot;Tuples are not allowed as input to BaseComponent models&quot;</span>
110        <span class="k">else</span><span class="p">:</span>
111            <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_line</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
112   </div>
113<div class="viewcode-block" id="LineModel.runXY"><a class="viewcode-back" href="../../../dev/api/sas.models.html#sas.models.LineModel.LineModel.runXY">[docs]</a>    <span class="k">def</span> <span class="nf">runXY</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span> <span class="o">=</span> <span class="mf">0.0</span><span class="p">):</span>
114        <span class="sd">&quot;&quot;&quot; Evaluate the model</span>
115<span class="sd">            @param x: simple value</span>
116<span class="sd">            @return: Line value</span>
117<span class="sd">        &quot;&quot;&quot;</span>
118        <span class="k">if</span> <span class="n">x</span><span class="o">.</span><span class="n">__class__</span><span class="o">.</span><span class="n">__name__</span> <span class="o">==</span> <span class="s">&#39;list&#39;</span><span class="p">:</span>
119            <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_line</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span>
120        <span class="k">elif</span> <span class="n">x</span><span class="o">.</span><span class="n">__class__</span><span class="o">.</span><span class="n">__name__</span> <span class="o">==</span> <span class="s">&#39;tuple&#39;</span><span class="p">:</span>
121            <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">,</span> <span class="s">&quot;Tuples are not allowed as input to BaseComponent models&quot;</span>
122        <span class="k">else</span><span class="p">:</span>
123            <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_line</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
124        </div>
125<div class="viewcode-block" id="LineModel.evalDistribution"><a class="viewcode-back" href="../../../dev/api/sas.models.html#sas.models.LineModel.LineModel.evalDistribution">[docs]</a>    <span class="k">def</span> <span class="nf">evalDistribution</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">qdist</span><span class="p">):</span>
126        <span class="sd">&quot;&quot;&quot;</span>
127<span class="sd">        Evaluate a distribution of q-values.</span>
128<span class="sd">        </span>
129<span class="sd">        * For 1D, a numpy array is expected as input:</span>
130<span class="sd">        </span>
131<span class="sd">            evalDistribution(q)</span>
132<span class="sd">            </span>
133<span class="sd">        where q is a numpy array.</span>
134<span class="sd">        </span>
135<span class="sd">        </span>
136<span class="sd">        * For 2D, a list of numpy arrays are expected: [qx_prime,qy_prime],</span>
137<span class="sd">          where 1D arrays,</span>
138<span class="sd">                </span>
139<span class="sd">        :param qdist: ndarray of scalar q-values or list [qx,qy] </span>
140<span class="sd">                    where qx,qy are 1D ndarrays </span>
141<span class="sd">        </span>
142<span class="sd">        &quot;&quot;&quot;</span>
143        <span class="k">if</span> <span class="n">qdist</span><span class="o">.</span><span class="n">__class__</span><span class="o">.</span><span class="n">__name__</span> <span class="o">==</span> <span class="s">&#39;list&#39;</span><span class="p">:</span>
144            <span class="c"># Check whether we have a list of ndarrays [qx,qy]</span>
145            <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">qdist</span><span class="p">)</span><span class="o">!=</span><span class="mi">2</span> <span class="ow">or</span> \
146                <span class="n">qdist</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">__class__</span><span class="o">.</span><span class="n">__name__</span> <span class="o">!=</span> <span class="s">&#39;ndarray&#39;</span> <span class="ow">or</span> \
147                <span class="n">qdist</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">__class__</span><span class="o">.</span><span class="n">__name__</span> <span class="o">!=</span> <span class="s">&#39;ndarray&#39;</span><span class="p">:</span>
148                    <span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">,</span> <span class="s">&quot;evalDistribution expects a list of 2 ndarrays&quot;</span>
149               
150            <span class="c"># Extract qx and qy for code clarity</span>
151            <span class="n">qx</span> <span class="o">=</span> <span class="n">qdist</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
152            <span class="n">qy</span> <span class="o">=</span> <span class="n">qdist</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span>
153            <span class="c">#For 2D, Z = A + B * Y, </span>
154            <span class="c"># so that it keeps its linearity in y-direction.</span>
155            <span class="c"># calculate q_r component for 2D isotropic</span>
156            <span class="n">q</span> <span class="o">=</span>  <span class="n">qy</span>
157            <span class="c"># vectorize the model function runXY</span>
158            <span class="n">v_model</span> <span class="o">=</span> <span class="n">numpy</span><span class="o">.</span><span class="n">vectorize</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">runXY</span><span class="p">,</span><span class="n">otypes</span><span class="o">=</span><span class="p">[</span><span class="nb">float</span><span class="p">])</span>
159            <span class="c"># calculate the scattering</span>
160            <span class="n">iq_array</span> <span class="o">=</span> <span class="n">v_model</span><span class="p">(</span><span class="n">q</span><span class="p">)</span>
161
162            <span class="k">return</span> <span class="n">iq_array</span>
163               
164        <span class="k">elif</span> <span class="n">qdist</span><span class="o">.</span><span class="n">__class__</span><span class="o">.</span><span class="n">__name__</span> <span class="o">==</span> <span class="s">&#39;ndarray&#39;</span><span class="p">:</span>
165                <span class="c"># We have a simple 1D distribution of q-values</span>
166                <span class="n">v_model</span> <span class="o">=</span> <span class="n">numpy</span><span class="o">.</span><span class="n">vectorize</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">runXY</span><span class="p">,</span><span class="n">otypes</span><span class="o">=</span><span class="p">[</span><span class="nb">float</span><span class="p">])</span>
167                <span class="n">iq_array</span> <span class="o">=</span> <span class="n">v_model</span><span class="p">(</span><span class="n">qdist</span><span class="p">)</span>
168
169                <span class="k">return</span> <span class="n">iq_array</span>
170           
171        <span class="k">else</span><span class="p">:</span>
172            <span class="n">mesg</span> <span class="o">=</span> <span class="s">&quot;evalDistribution is expecting an ndarray of scalar q-values&quot;</span>
173            <span class="n">mesg</span> <span class="o">+=</span> <span class="s">&quot; or a list [qx,qy] where qx,qy are 2D ndarrays.&quot;</span>
174            <span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">,</span> <span class="n">mesg</span>
175       
176   
177   
178</div></div>
179<span class="k">if</span> <span class="n">__name__</span> <span class="o">==</span> <span class="s">&quot;__main__&quot;</span><span class="p">:</span> 
180    <span class="n">l</span> <span class="o">=</span> <span class="n">LineModel</span><span class="p">()</span>
181    <span class="k">print</span> <span class="s">&quot;hello&quot;</span>
182       
183<span class="c"># End of file</span>
184</pre></div>
185
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