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<div class="section" id="gpy-inference-mcmc-package">
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<h1>GPy.inference.mcmc package<a class="headerlink" href="#gpy-inference-mcmc-package" title="Permalink to this headline">¶</a></h1>
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<div class="section" id="submodules">
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<h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this headline">¶</a></h2>
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</div>
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<div class="section" id="module-GPy.inference.mcmc.hmc">
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<span id="gpy-inference-mcmc-hmc-module"></span><h2>GPy.inference.mcmc.hmc module<a class="headerlink" href="#module-GPy.inference.mcmc.hmc" title="Permalink to this headline">¶</a></h2>
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<dl class="class">
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<dt id="GPy.inference.mcmc.hmc.HMC">
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<em class="property">class </em><code class="descclassname">GPy.inference.mcmc.hmc.</code><code class="descname">HMC</code><span class="sig-paren">(</span><em>model</em>, <em>M=None</em>, <em>stepsize=0.1</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/GPy/inference/mcmc/hmc.html#HMC"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#GPy.inference.mcmc.hmc.HMC" title="Permalink to this definition">¶</a></dt>
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<dd><p>An implementation of Hybrid Monte Carlo (HMC) for GPy models</p>
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<p>Initialize an object for HMC sampling. Note that the status of the model (model parameters) will be changed during sampling.</p>
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<table class="docutils field-list" frame="void" rules="none">
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<col class="field-name" />
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<col class="field-body" />
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<tbody valign="top">
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<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
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<li><strong>model</strong> (<em>GPy.core.Model</em>) – the GPy model that will be sampled</li>
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<li><strong>M</strong> (<em>numpy.ndarray</em>) – the mass matrix (an identity matrix by default)</li>
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<li><strong>stepsize</strong> (<em>float</em>) – the step size for HMC sampling</li>
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</ul>
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</td>
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</tr>
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</tbody>
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</table>
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<dl class="method">
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<dt id="GPy.inference.mcmc.hmc.HMC.sample">
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<code class="descname">sample</code><span class="sig-paren">(</span><em>num_samples=1000</em>, <em>hmc_iters=20</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/GPy/inference/mcmc/hmc.html#HMC.sample"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#GPy.inference.mcmc.hmc.HMC.sample" title="Permalink to this definition">¶</a></dt>
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<dd><p>Sample the (unfixed) model parameters.</p>
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<table class="docutils field-list" frame="void" rules="none">
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<col class="field-name" />
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<col class="field-body" />
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<tbody valign="top">
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<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
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<li><strong>num_samples</strong> (<em>int</em>) – the number of samples to draw (1000 by default)</li>
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<li><strong>hmc_iters</strong> (<em>int</em>) – the number of leap-frog iterations (20 by default)</li>
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</ul>
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</td>
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</tr>
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<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">the list of parameters samples with the size N x P (N - the number of samples, P - the number of parameters to sample)</p>
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</td>
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</tr>
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<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last">numpy.ndarray</p>
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</td>
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</tr>
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</tbody>
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</table>
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</dd></dl>
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</dd></dl>
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<dl class="class">
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<dt id="GPy.inference.mcmc.hmc.HMC_shortcut">
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<em class="property">class </em><code class="descclassname">GPy.inference.mcmc.hmc.</code><code class="descname">HMC_shortcut</code><span class="sig-paren">(</span><em>model, M=None, stepsize_range=[1e-06, 0.1], groupsize=5, Hstd_th=[1e-05, 3.0]</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/GPy/inference/mcmc/hmc.html#HMC_shortcut"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#GPy.inference.mcmc.hmc.HMC_shortcut" title="Permalink to this definition">¶</a></dt>
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<dd><dl class="method">
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<dt id="GPy.inference.mcmc.hmc.HMC_shortcut.sample">
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<code class="descname">sample</code><span class="sig-paren">(</span><em>m_iters=1000</em>, <em>hmc_iters=20</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/GPy/inference/mcmc/hmc.html#HMC_shortcut.sample"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#GPy.inference.mcmc.hmc.HMC_shortcut.sample" title="Permalink to this definition">¶</a></dt>
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<dd></dd></dl>
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</dd></dl>
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</div>
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<div class="section" id="module-GPy.inference.mcmc.samplers">
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<span id="gpy-inference-mcmc-samplers-module"></span><h2>GPy.inference.mcmc.samplers module<a class="headerlink" href="#module-GPy.inference.mcmc.samplers" title="Permalink to this headline">¶</a></h2>
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<dl class="class">
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<dt id="GPy.inference.mcmc.samplers.Metropolis_Hastings">
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<em class="property">class </em><code class="descclassname">GPy.inference.mcmc.samplers.</code><code class="descname">Metropolis_Hastings</code><span class="sig-paren">(</span><em>model</em>, <em>cov=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/GPy/inference/mcmc/samplers.html#Metropolis_Hastings"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#GPy.inference.mcmc.samplers.Metropolis_Hastings" title="Permalink to this definition">¶</a></dt>
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<dd><dl class="method">
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<dt id="GPy.inference.mcmc.samplers.Metropolis_Hastings.new_chain">
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<code class="descname">new_chain</code><span class="sig-paren">(</span><em>start=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/GPy/inference/mcmc/samplers.html#Metropolis_Hastings.new_chain"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#GPy.inference.mcmc.samplers.Metropolis_Hastings.new_chain" title="Permalink to this definition">¶</a></dt>
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<dd></dd></dl>
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<dl class="method">
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<dt id="GPy.inference.mcmc.samplers.Metropolis_Hastings.predict">
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<code class="descname">predict</code><span class="sig-paren">(</span><em>function</em>, <em>args</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/GPy/inference/mcmc/samplers.html#Metropolis_Hastings.predict"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#GPy.inference.mcmc.samplers.Metropolis_Hastings.predict" title="Permalink to this definition">¶</a></dt>
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<dd><p>Make a prediction for the function, to which we will pass the additional arguments</p>
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</dd></dl>
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<dl class="method">
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<dt id="GPy.inference.mcmc.samplers.Metropolis_Hastings.sample">
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<code class="descname">sample</code><span class="sig-paren">(</span><em>Ntotal</em>, <em>Nburn</em>, <em>Nthin</em>, <em>tune=True</em>, <em>tune_throughout=False</em>, <em>tune_interval=400</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/GPy/inference/mcmc/samplers.html#Metropolis_Hastings.sample"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#GPy.inference.mcmc.samplers.Metropolis_Hastings.sample" title="Permalink to this definition">¶</a></dt>
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<dd></dd></dl>
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</dd></dl>
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</div>
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<div class="section" id="module-GPy.inference.mcmc">
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<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-GPy.inference.mcmc" title="Permalink to this headline">¶</a></h2>
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<h3><a href="index.html">Table Of Contents</a></h3>
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<ul>
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<li><a class="reference internal" href="#">GPy.inference.mcmc package</a><ul>
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<li><a class="reference internal" href="#submodules">Submodules</a></li>
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<li><a class="reference internal" href="#module-GPy.inference.mcmc.hmc">GPy.inference.mcmc.hmc module</a></li>
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<li><a class="reference internal" href="#module-GPy.inference.mcmc.samplers">GPy.inference.mcmc.samplers module</a></li>
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<li><a class="reference internal" href="#module-GPy.inference.mcmc">Module contents</a></li>
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