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jeffjennings committed Dec 6, 2023
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21 changes: 17 additions & 4 deletions _modules/mpol/crossval.html
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Expand Up @@ -544,7 +544,7 @@ <h1>Source code for mpol.crossval</h1><div class="highlight"><pre>
<span class="bp">self</span><span class="o">.</span><span class="n">_diagnostics</span><span class="p">[</span><span class="s2">&quot;models&quot;</span><span class="p">]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_model</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_diagnostics</span><span class="p">[</span><span class="s2">&quot;regularizers&quot;</span><span class="p">]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_regularizers</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_diagnostics</span><span class="p">[</span><span class="s2">&quot;loss_histories&quot;</span><span class="p">]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">loss_history</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_diagnostics</span><span class="p">[</span><span class="s2">&quot;train_figures&quot;</span><span class="p">]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_train_figure</span><span class="p">)</span>
<span class="c1"># self._diagnostics[&quot;train_figures&quot;].append(self._train_figure)</span>

<span class="c1"># average individual test scores to get the cross-val metric for chosen</span>
<span class="c1"># hyperparameters</span>
Expand Down Expand Up @@ -588,7 +588,7 @@ <h1>Source code for mpol.crossval</h1><div class="highlight"><pre>

<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">diagnostics</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="w"> </span><span class="sd">&quot;&quot;&quot;Dict containing diagnostics of the cross-validation loop across all kfolds: models, regularizers, loss values, training figures&quot;&quot;&quot;</span>
<span class="w"> </span><span class="sd">&quot;&quot;&quot;Dict containing diagnostics of the cross-validation loop across all kfolds: models, regularizers, loss values&quot;&quot;&quot;</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_diagnostics</span></div>


Expand Down Expand Up @@ -734,6 +734,7 @@ <h1>Source code for mpol.crossval</h1><div class="highlight"><pre>
<span class="n">k</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span>
<span class="n">dartboard</span><span class="p">:</span> <span class="n">Dartboard</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
<span class="n">seed</span><span class="p">:</span> <span class="nb">int</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
<span class="n">verbose</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span>
<span class="p">):</span>
<span class="k">if</span> <span class="n">k</span> <span class="o">&lt;=</span> <span class="mi">0</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">&quot;k must be a positive integer&quot;</span><span class="p">)</span>
Expand All @@ -744,6 +745,7 @@ <h1>Source code for mpol.crossval</h1><div class="highlight"><pre>
<span class="bp">self</span><span class="o">.</span><span class="n">griddedDataset</span> <span class="o">=</span> <span class="n">gridded_dataset</span>
<span class="bp">self</span><span class="o">.</span><span class="n">k</span> <span class="o">=</span> <span class="n">k</span>
<span class="bp">self</span><span class="o">.</span><span class="n">dartboard</span> <span class="o">=</span> <span class="n">dartboard</span>
<span class="bp">self</span><span class="o">.</span><span class="n">verbose</span> <span class="o">=</span> <span class="n">verbose</span>

<span class="c1"># 2D mask for any UV cells that contain visibilities</span>
<span class="c1"># in *any* channel</span>
Expand Down Expand Up @@ -781,6 +783,7 @@ <h1>Source code for mpol.crossval</h1><div class="highlight"><pre>
<span class="n">q_edges</span><span class="p">:</span> <span class="n">NDArray</span><span class="p">[</span><span class="n">floating</span><span class="p">[</span><span class="n">Any</span><span class="p">]],</span>
<span class="n">phi_edges</span><span class="p">:</span> <span class="n">NDArray</span><span class="p">[</span><span class="n">floating</span><span class="p">[</span><span class="n">Any</span><span class="p">]],</span>
<span class="n">seed</span><span class="p">:</span> <span class="nb">int</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
<span class="n">verbose</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span>
<span class="p">)</span> <span class="o">-&gt;</span> <span class="n">DartboardSplitGridded</span><span class="p">:</span>
<span class="w"> </span><span class="sa">r</span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Alternative method to initialize a DartboardSplitGridded object from Dartboard parameters.</span>
Expand All @@ -791,9 +794,10 @@ <h1>Source code for mpol.crossval</h1><div class="highlight"><pre>
<span class="sd"> q_edges (1D numpy array): an array of radial bin edges to set the dartboard cells in :math:`[\mathrm{k}\lambda]`. If ``None``, defaults to 12 log-linearly radial bins stretching from 0 to the :math:`q_\mathrm{max}` represented by ``coords``.</span>
<span class="sd"> phi_edges (1D numpy array): an array of azimuthal bin edges to set the dartboard cells in [radians]. If ``None``, defaults to 8 equal-spaced azimuthal bins stretched from :math:`0` to :math:`\pi`.</span>
<span class="sd"> seed (int): (optional) numpy random seed to use for the permutation, for reproducibility</span>
<span class="sd"> verbose (bool): whether to print notification messages</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="n">dartboard</span> <span class="o">=</span> <span class="n">Dartboard</span><span class="p">(</span><span class="n">gridded_dataset</span><span class="o">.</span><span class="n">coords</span><span class="p">,</span> <span class="n">q_edges</span><span class="p">,</span> <span class="n">phi_edges</span><span class="p">)</span>
<span class="k">return</span> <span class="bp">cls</span><span class="p">(</span><span class="n">gridded_dataset</span><span class="p">,</span> <span class="n">k</span><span class="p">,</span> <span class="n">dartboard</span><span class="p">,</span> <span class="n">seed</span><span class="p">)</span></div>
<span class="k">return</span> <span class="bp">cls</span><span class="p">(</span><span class="n">gridded_dataset</span><span class="p">,</span> <span class="n">k</span><span class="p">,</span> <span class="n">dartboard</span><span class="p">,</span> <span class="n">seed</span><span class="p">,</span> <span class="n">verbose</span><span class="p">)</span></div>

<span class="k">def</span> <span class="fm">__iter__</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">DartboardSplitGridded</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">n</span> <span class="o">=</span> <span class="mi">0</span> <span class="c1"># the current k-slice we&#39;re on</span>
Expand All @@ -802,7 +806,16 @@ <h1>Source code for mpol.crossval</h1><div class="highlight"><pre>
<span class="k">def</span> <span class="fm">__next__</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">tuple</span><span class="p">[</span><span class="n">GriddedDataset</span><span class="p">,</span> <span class="n">GriddedDataset</span><span class="p">]:</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">n</span> <span class="o">&lt;</span> <span class="bp">self</span><span class="o">.</span><span class="n">k</span><span class="p">:</span>
<span class="n">k_list</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">k_split_cell_list</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>
<span class="n">cell_list_test</span> <span class="o">=</span> <span class="n">k_list</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">n</span><span class="p">)</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">k</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">verbose</span> <span class="ow">is</span> <span class="kc">True</span><span class="p">:</span>
<span class="n">logging</span><span class="o">.</span><span class="n">info</span><span class="p">(</span><span class="s2">&quot; DartboardSplitGridded: only 1 k-fold: splitting dataset as ~80/20 train/test&quot;</span><span class="p">)</span>
<span class="n">ntest</span> <span class="o">=</span> <span class="nb">round</span><span class="p">(</span><span class="mf">0.2</span> <span class="o">*</span> <span class="nb">len</span><span class="p">(</span><span class="n">k_list</span><span class="p">[</span><span class="mi">0</span><span class="p">]))</span>
<span class="c1"># put ~20% of cells into test set</span>
<span class="n">cell_list_test</span> <span class="o">=</span> <span class="n">k_list</span><span class="p">[</span><span class="mi">0</span><span class="p">][:</span><span class="n">ntest</span><span class="p">]</span>
<span class="c1"># remove cells in test set from train set</span>
<span class="n">k_list</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">delete</span><span class="p">(</span><span class="n">k_list</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="nb">range</span><span class="p">(</span><span class="n">ntest</span><span class="p">),</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">cell_list_test</span> <span class="o">=</span> <span class="n">k_list</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">n</span><span class="p">)</span>

<span class="c1"># put the remaining indices back into a full list</span>
<span class="n">cell_list_train</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">concatenate</span><span class="p">(</span><span class="n">k_list</span><span class="p">)</span>
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