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+# Sphinx build info version 1
+# This file records the configuration used when building these files. When it is not found, a full rebuild will be done.
+config: 292c2c4c18973b0c51527665131fea15
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+<li class="toctree-l1"><a class="reference internal" href="test_Inference.html">Bayesian inference analysis notebook</a></li>
+</ul>
+<p class="caption" role="heading"><span class="caption-text">EOS generators module</span></p>
+<ul>
+<li class="toctree-l1"><a class="reference internal" href="crust_EOS.html">Crust Equation of state interpolation</a></li>
+<li class="toctree-l1"><a class="reference internal" href="RMF_EOS.html">RMF EOS solver</a></li>
+<li class="toctree-l1"><a class="reference internal" href="fastRMF_EoS.html">RMF EOS solver (numba speed up version)</a></li>
+</ul>
+<p class="caption" role="heading"><span class="caption-text">TOV solver module</span></p>
+<ul>
+<li class="toctree-l1"><a class="reference internal" href="EoS_import.html">Import Equation of State</a></li>
+<li class="toctree-l1"><a class="reference internal" href="main.html">Main functions</a></li>
+<li class="toctree-l1"><a class="reference internal" href="TOV_solver.html">Solve TOV Equation</a></li>
+<li class="toctree-l1"><a class="reference internal" href="speed_of_sound.html">Calculate Speed of Sound</a></li>
+</ul>
+<p class="caption" role="heading"><span class="caption-text">Bayesian Inference module</span></p>
+<ul class="current">
+<li class="toctree-l1 current"><a class="current reference internal" href="#">Bayesian Inference smapler setup module</a><ul>
+<li class="toctree-l2"><a class="reference internal" href="#InferenceWorkflow.BayesianSampler.UltranestSampler"><code class="docutils literal notranslate"><span class="pre">UltranestSampler()</span></code></a></li>
+<li class="toctree-l2"><a class="reference internal" href="#InferenceWorkflow.BayesianSampler.UltranestSamplerResume"><code class="docutils literal notranslate"><span class="pre">UltranestSamplerResume()</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l1"><a class="reference internal" href="prior.html">Prior Definition Module</a></li>
+<li class="toctree-l1"><a class="reference internal" href="Likelihood.html">Likelihood function definition module</a></li>
+</ul>
+<p class="caption" role="heading"><span class="caption-text">Postprocessing module</span></p>
+<ul>
+<li class="toctree-l1"><a class="reference internal" href="Cornerplot.html">Postprocessing module: Cornerplot</a></li>
+</ul>
+
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+
+  <section id="bayesian-inference-smapler-setup-module">
+<span id="bayesian-sampler"></span><h1>Bayesian Inference smapler setup module<a class="headerlink" href="#bayesian-inference-smapler-setup-module" title="Link to this heading"></a></h1>
+<p>Functions to start run Bayesian inference by calling UltraNest package</p>
+<dl class="py function" id="module-InferenceWorkflow.BayesianSampler">
+<dt class="sig sig-object py" id="InferenceWorkflow.BayesianSampler.UltranestSampler">
+<span class="sig-prename descclassname"><span class="pre">InferenceWorkflow.BayesianSampler.</span></span><span class="sig-name descname"><span class="pre">UltranestSampler</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">parameters</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">likelihood</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prior</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">step</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">live_points</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_calls</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/InferenceWorkflow/BayesianSampler.html#UltranestSampler"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#InferenceWorkflow.BayesianSampler.UltranestSampler" title="Link to this definition"></a></dt>
+<dd><p>UltraNest based nested sampler by given likelihood prior, and parameters.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>parameters</strong> (<em>array</em>) – parameters array that want to be constrained.</p></li>
+<li><p><strong>likelihood</strong> (<em>array</em>) – theta as input. likelihood function defined by user.</p></li>
+<li><p><strong>prior</strong> (<em>array</em>) – cube as input, prior function defined by user. please check our test_inference.ipynb</p></li>
+<li><p><strong>prior.</strong> (<em>to check how to define likelihood and</em>)</p></li>
+<li><p><strong>step</strong> (<em>int</em>) – as a step sampler, define this inference want to devided to how many steps.</p></li>
+<li><p><strong>live_points</strong> (<em>int</em>) – define how many live points will be used to explore the whole</p></li>
+<li><p><strong>space.</strong> (<em>parameters</em>)</p></li>
+<li><p><strong>max_ncalls</strong> (<em>int</em>) – define after how many steps the sampler will stop work.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>equal weighted samples of whole posteior parameter space,
+this run will generate a dirctory as ‘output’, please check the run# folder, and the
+chain dirctory, there is a ‘equal_weighted_samples’ file, that is same with flat_samples here.
+It will be easier to check if you are using clusters to do this inference.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p>flat_samples (array)</p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py function">
+<dt class="sig sig-object py" id="InferenceWorkflow.BayesianSampler.UltranestSamplerResume">
+<span class="sig-prename descclassname"><span class="pre">InferenceWorkflow.BayesianSampler.</span></span><span class="sig-name descname"><span class="pre">UltranestSamplerResume</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">parameters</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">likelihood</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prior</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nsteps</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">live_points</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_calls</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/InferenceWorkflow/BayesianSampler.html#UltranestSamplerResume"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#InferenceWorkflow.BayesianSampler.UltranestSamplerResume" title="Link to this definition"></a></dt>
+<dd><p>UltraNest based nested sampler by given likelihood prior, and parameters. (resume true verion
+could restart you run from your previous stopped results)</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>parameters</strong> (<em>array</em>) – parameters array that want to be constrained.</p></li>
+<li><p><strong>likelihood</strong> (<em>array</em>) – theta as input. likelihood function defined by user.</p></li>
+<li><p><strong>prior</strong> (<em>array</em>) – cube as input, prior function defined by user. please check our test_inference.ipynb</p></li>
+<li><p><strong>prior.</strong> (<em>to check how to define likelihood and</em>)</p></li>
+<li><p><strong>step</strong> (<em>int</em>) – as a step sampler, define this inference want to devided to how many steps.</p></li>
+<li><p><strong>live_points</strong> (<em>int</em>) – define how many live points will be used to explore the whole</p></li>
+<li><p><strong>space.</strong> (<em>parameters</em>)</p></li>
+<li><p><strong>max_ncalls</strong> (<em>int</em>) – define after how many steps the sampler will stop work.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>equal weighted samples of whole posteior parameter space,
+this run will generate a dirctory as ‘output’, please check the run# folder, and the
+chain dirctory, there is a ‘equal_weighted_samples’ file, that is same with flat_samples here.
+It will be easier to check if you are using clusters to do this inference.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p>flat_samples (array)</p>
+</dd>
+</dl>
+</dd></dl>
+
+</section>
+
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+              <p class="caption" role="heading"><span class="caption-text">Illustration Notebooks</span></p>
+<ul>
+<li class="toctree-l1"><a class="reference internal" href="test_EOSgenerators.html">Equation of State Generators illustration notebook</a></li>
+<li class="toctree-l1"><a class="reference internal" href="test_TOVsolver.html">TOV solver sampled notebook</a></li>
+<li class="toctree-l1"><a class="reference internal" href="test_Inference.html">Bayesian inference analysis notebook</a></li>
+</ul>
+<p class="caption" role="heading"><span class="caption-text">EOS generators module</span></p>
+<ul>
+<li class="toctree-l1"><a class="reference internal" href="crust_EOS.html">Crust Equation of state interpolation</a></li>
+<li class="toctree-l1"><a class="reference internal" href="RMF_EOS.html">RMF EOS solver</a></li>
+<li class="toctree-l1"><a class="reference internal" href="fastRMF_EoS.html">RMF EOS solver (numba speed up version)</a></li>
+</ul>
+<p class="caption" role="heading"><span class="caption-text">TOV solver module</span></p>
+<ul>
+<li class="toctree-l1"><a class="reference internal" href="EoS_import.html">Import Equation of State</a></li>
+<li class="toctree-l1"><a class="reference internal" href="main.html">Main functions</a></li>
+<li class="toctree-l1"><a class="reference internal" href="TOV_solver.html">Solve TOV Equation</a></li>
+<li class="toctree-l1"><a class="reference internal" href="speed_of_sound.html">Calculate Speed of Sound</a></li>
+</ul>
+<p class="caption" role="heading"><span class="caption-text">Bayesian Inference module</span></p>
+<ul>
+<li class="toctree-l1"><a class="reference internal" href="BayesianSampler.html">Bayesian Inference smapler setup module</a></li>
+<li class="toctree-l1"><a class="reference internal" href="prior.html">Prior Definition Module</a></li>
+<li class="toctree-l1"><a class="reference internal" href="Likelihood.html">Likelihood function definition module</a></li>
+</ul>
+<p class="caption" role="heading"><span class="caption-text">Postprocessing module</span></p>
+<ul class="current">
+<li class="toctree-l1 current"><a class="current reference internal" href="#">Postprocessing module: Cornerplot</a></li>
+</ul>
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+           <div itemprop="articleBody">
+
+  <section id="postprocessing-module-cornerplot">
+<span id="corner-plot-module"></span><h1>Postprocessing module: Cornerplot<a class="headerlink" href="#postprocessing-module-cornerplot" title="Link to this heading"></a></h1>
+<p>Function to plot overlapping corner plots with input as two or three 2d posterior arrays</p>
+</section>
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