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Update notebooks *.html
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turion committed Oct 2, 2023
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6,286 changes: 3,132 additions & 3,154 deletions docs/docs/notebooks/ClassicalPhysics.html
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24,202 changes: 12,105 additions & 12,097 deletions docs/docs/notebooks/Diagrams.html
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78 changes: 47 additions & 31 deletions docs/docs/notebooks/Histogram.html
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Original file line number Diff line number Diff line change
Expand Up @@ -36,6 +36,7 @@
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display: none;
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.highlight {
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overflow: hidden;
Expand All @@ -14477,9 +14474,26 @@
overflow: hidden;
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font-family: inherit;
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color: var(--jp-content-font-color1);
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/* Using table instead of flexbox so that we can use break-inside property */
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display: none;
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@page {
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@media print {
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<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
<div class="CodeMirror cm-s-jupyter">
<div class=" highlight hl-Haskell"><pre><span></span><span class="kr">import</span><span class="w"> </span><span class="nn">Prelude</span><span class="w"> </span>
<span class="kr">import</span><span class="w"> </span><span class="nn">Control.Monad.Bayes.Class</span><span class="w"></span>
<span class="kr">import</span><span class="w"> </span><span class="nn">Control.Monad.Bayes.Enumerator</span><span class="w"></span>
<span class="kr">import</span><span class="w"> </span><span class="nn">Control.Monad.Bayes.Weighted</span><span class="w"></span>
<span class="kr">import</span><span class="w"> </span><span class="nn">Control.Monad.Bayes.Sampler.Strict</span><span class="w"></span>
<span class="kr">import</span><span class="w"> </span><span class="nn">Control.Monad</span><span class="w"></span>
<span class="kr">import</span><span class="w"> </span><span class="nn">Numeric.Log</span><span class="w"></span>

<span class="kt">:</span><span class="n">l</span><span class="w"> </span><span class="o">../</span><span class="n">plotting</span><span class="o">.</span><span class="n">hs</span><span class="w"></span>
<span class="kr">import</span><span class="w"> </span><span class="nn">Control.Monad.Bayes.Class</span>
<span class="kr">import</span><span class="w"> </span><span class="nn">Control.Monad.Bayes.Enumerator</span>
<span class="kr">import</span><span class="w"> </span><span class="nn">Control.Monad.Bayes.Weighted</span>
<span class="kr">import</span><span class="w"> </span><span class="nn">Control.Monad.Bayes.Sampler.Strict</span>
<span class="kr">import</span><span class="w"> </span><span class="nn">Control.Monad</span>
<span class="kr">import</span><span class="w"> </span><span class="nn">Numeric.Log</span>

<span class="kt">:</span><span class="n">l</span><span class="w"> </span><span class="o">../</span><span class="n">plotting</span><span class="o">.</span><span class="n">hs</span>
</pre></div>

</div>
Expand Down Expand Up @@ -14616,24 +14634,24 @@ <h1 id="Distributions-over-anything">Distributions over <strong>anything</strong
<div class="jp-InputPrompt jp-InputArea-prompt">In&nbsp;[2]:</div>
<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
<div class="CodeMirror cm-s-jupyter">
<div class=" highlight hl-Haskell"><pre><span></span><span class="nf">unnormalizedDistribution</span><span class="w"> </span><span class="ow">::</span><span class="w"> </span><span class="kt">Measure</span><span class="w"> </span><span class="kt">Double</span><span class="w"></span>
<span class="nf">unnormalizedDistribution</span><span class="w"> </span><span class="ow">=</span><span class="w"> </span><span class="kr">do</span><span class="w"></span>
<span class="w"> </span><span class="n">x</span><span class="w"> </span><span class="ow">&lt;-</span><span class="w"> </span><span class="n">bernoulli</span><span class="w"> </span><span class="mf">0.5</span><span class="w"></span>
<span class="w"> </span><span class="n">y</span><span class="w"> </span><span class="ow">&lt;-</span><span class="w"> </span><span class="n">normal</span><span class="w"> </span><span class="p">(</span><span class="kr">if</span><span class="w"> </span><span class="n">x</span><span class="w"> </span><span class="kr">then</span><span class="w"> </span><span class="p">(</span><span class="o">-</span><span class="mi">2</span><span class="p">)</span><span class="w"> </span><span class="kr">else</span><span class="w"> </span><span class="mi">2</span><span class="p">)</span><span class="w"> </span><span class="mi">1</span><span class="w"></span>
<span class="w"> </span><span class="n">factor</span><span class="w"> </span><span class="p">(</span><span class="n">normalPdf</span><span class="w"> </span><span class="mi">0</span><span class="w"> </span><span class="mi">4</span><span class="w"> </span><span class="n">y</span><span class="p">)</span><span class="w"></span>
<span class="w"> </span><span class="n">return</span><span class="w"> </span><span class="n">y</span><span class="w"></span>
<div class=" highlight hl-Haskell"><pre><span></span><span class="nf">unnormalizedDistribution</span><span class="w"> </span><span class="ow">::</span><span class="w"> </span><span class="kt">Measure</span><span class="w"> </span><span class="kt">Double</span>
<span class="nf">unnormalizedDistribution</span><span class="w"> </span><span class="ow">=</span><span class="w"> </span><span class="kr">do</span>
<span class="w"> </span><span class="n">x</span><span class="w"> </span><span class="ow">&lt;-</span><span class="w"> </span><span class="n">bernoulli</span><span class="w"> </span><span class="mf">0.5</span>
<span class="w"> </span><span class="n">y</span><span class="w"> </span><span class="ow">&lt;-</span><span class="w"> </span><span class="n">normal</span><span class="w"> </span><span class="p">(</span><span class="kr">if</span><span class="w"> </span><span class="n">x</span><span class="w"> </span><span class="kr">then</span><span class="w"> </span><span class="p">(</span><span class="o">-</span><span class="mi">2</span><span class="p">)</span><span class="w"> </span><span class="kr">else</span><span class="w"> </span><span class="mi">2</span><span class="p">)</span><span class="w"> </span><span class="mi">1</span>
<span class="w"> </span><span class="n">factor</span><span class="w"> </span><span class="p">(</span><span class="n">normalPdf</span><span class="w"> </span><span class="mi">0</span><span class="w"> </span><span class="mi">4</span><span class="w"> </span><span class="n">y</span><span class="p">)</span>
<span class="w"> </span><span class="n">return</span><span class="w"> </span><span class="n">y</span>
<span class="w"> </span>
<span class="nf">distributionOverWeightedSamples</span><span class="w"> </span><span class="ow">::</span><span class="w"> </span><span class="kt">Distribution</span><span class="w"> </span><span class="p">(</span><span class="kt">Double</span><span class="p">,</span><span class="w"> </span><span class="kt">Log</span><span class="w"> </span><span class="kt">Double</span><span class="p">)</span><span class="w"></span>
<span class="nf">distributionOverWeightedSamples</span><span class="w"> </span><span class="ow">=</span><span class="w"> </span><span class="n">weighted</span><span class="w"> </span><span class="n">unnormalizedDistribution</span><span class="w"></span>
<span class="nf">distributionOverWeightedSamples</span><span class="w"> </span><span class="ow">::</span><span class="w"> </span><span class="kt">Distribution</span><span class="w"> </span><span class="p">(</span><span class="kt">Double</span><span class="p">,</span><span class="w"> </span><span class="kt">Log</span><span class="w"> </span><span class="kt">Double</span><span class="p">)</span>
<span class="nf">distributionOverWeightedSamples</span><span class="w"> </span><span class="ow">=</span><span class="w"> </span><span class="n">weighted</span><span class="w"> </span><span class="n">unnormalizedDistribution</span>
<span class="w"> </span>
<span class="nf">iidDistribution</span><span class="w"> </span><span class="ow">::</span><span class="w"> </span><span class="kt">Distribution</span><span class="w"> </span><span class="p">[(</span><span class="kt">Double</span><span class="p">,</span><span class="w"> </span><span class="kt">Log</span><span class="w"> </span><span class="kt">Double</span><span class="p">)]</span><span class="w"></span>
<span class="nf">iidDistribution</span><span class="w"> </span><span class="ow">=</span><span class="w"> </span><span class="n">replicateM</span><span class="w"> </span><span class="mi">100000</span><span class="w"> </span><span class="n">distributionOverWeightedSamples</span><span class="w"></span>
<span class="nf">iidDistribution</span><span class="w"> </span><span class="ow">::</span><span class="w"> </span><span class="kt">Distribution</span><span class="w"> </span><span class="p">[(</span><span class="kt">Double</span><span class="p">,</span><span class="w"> </span><span class="kt">Log</span><span class="w"> </span><span class="kt">Double</span><span class="p">)]</span>
<span class="nf">iidDistribution</span><span class="w"> </span><span class="ow">=</span><span class="w"> </span><span class="n">replicateM</span><span class="w"> </span><span class="mi">100000</span><span class="w"> </span><span class="n">distributionOverWeightedSamples</span>
<span class="w"> </span>
<span class="nf">histogramDistribution</span><span class="w"> </span><span class="ow">::</span><span class="w"> </span><span class="kt">Distribution</span><span class="w"> </span><span class="kt">Histogram</span><span class="w"></span>
<span class="nf">histogramDistribution</span><span class="w"> </span><span class="ow">=</span><span class="w"> </span><span class="n">histogram</span><span class="w"> </span><span class="mi">500</span><span class="w"> </span><span class="o">&lt;$&gt;</span><span class="w"> </span><span class="n">iidDistribution</span><span class="w"></span>
<span class="nf">histogramDistribution</span><span class="w"> </span><span class="ow">::</span><span class="w"> </span><span class="kt">Distribution</span><span class="w"> </span><span class="kt">Histogram</span>
<span class="nf">histogramDistribution</span><span class="w"> </span><span class="ow">=</span><span class="w"> </span><span class="n">histogram</span><span class="w"> </span><span class="mi">500</span><span class="w"> </span><span class="o">&lt;$&gt;</span><span class="w"> </span><span class="n">iidDistribution</span>
<span class="w"> </span>
<span class="nf">plotDistribution</span><span class="w"> </span><span class="ow">::</span><span class="w"> </span><span class="kt">Distribution</span><span class="w"> </span><span class="kt">Plot</span><span class="w"></span>
<span class="nf">plotDistribution</span><span class="w"> </span><span class="ow">=</span><span class="w"> </span><span class="n">plot</span><span class="w"> </span><span class="o">.</span><span class="w"> </span><span class="n">histogramToList</span><span class="w"> </span><span class="o">&lt;$&gt;</span><span class="w"> </span><span class="n">histogramDistribution</span><span class="w"></span>
<span class="nf">plotDistribution</span><span class="w"> </span><span class="ow">::</span><span class="w"> </span><span class="kt">Distribution</span><span class="w"> </span><span class="kt">Plot</span>
<span class="nf">plotDistribution</span><span class="w"> </span><span class="ow">=</span><span class="w"> </span><span class="n">plot</span><span class="w"> </span><span class="o">.</span><span class="w"> </span><span class="n">histogramToList</span><span class="w"> </span><span class="o">&lt;$&gt;</span><span class="w"> </span><span class="n">histogramDistribution</span>
</pre></div>

</div>
Expand Down Expand Up @@ -14665,7 +14683,7 @@ <h1 id="Distributions-over-anything">Distributions over <strong>anything</strong
<div class="jp-InputPrompt jp-InputArea-prompt">In&nbsp;[3]:</div>
<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
<div class="CodeMirror cm-s-jupyter">
<div class=" highlight hl-Haskell"><pre><span></span><span class="nf">sampler</span><span class="w"> </span><span class="n">plotDistribution</span><span class="w"></span>
<div class=" highlight hl-Haskell"><pre><span></span><span class="nf">sampler</span><span class="w"> </span><span class="n">plotDistribution</span>
</pre></div>

</div>
Expand All @@ -14679,9 +14697,7 @@ <h1 id="Distributions-over-anything">Distributions over <strong>anything</strong


<div class="jp-OutputArea jp-Cell-outputArea">

<div class="jp-OutputArea-child">


<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>

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