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<p class="caption" role="heading"><span class="caption-text">Introduction</span></p>
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<li class="toctree-l1"><a class="reference internal" href="../installation/">Installation</a></li>
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<li class="toctree-l1"><a class="reference internal" href="../posthoc/">Layer Activations</a></li>
<li class="toctree-l1"><a class="reference internal" href="../uq/">Uncertainty Quantification</a></li>
<li class="toctree-l1"><a class="reference internal" href="../features/">Generating Features</a></li>
<li class="toctree-l1"><a class="reference internal" href="../mil/">Multiple-Instance Learning (MIL)</a></li>
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<li class="toctree-l1"><a class="reference internal" href="../plugins/">Creating a Slideflow Plugin</a></li>
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<li class="toctree-l1"><a class="reference internal" href="../slideflow/">slideflow</a></li>
<li class="toctree-l1"><a class="reference internal" href="../project/">slideflow.Project</a></li>
<li class="toctree-l1"><a class="reference internal" href="../dataset/">slideflow.Dataset</a></li>
<li class="toctree-l1"><a class="reference internal" href="../dataset_features/">slideflow.DatasetFeatures</a></li>
<li class="toctree-l1"><a class="reference internal" href="../heatmap/">slideflow.Heatmap</a></li>
<li class="toctree-l1"><a class="reference internal" href="../model_params/">slideflow.ModelParams</a></li>
<li class="toctree-l1"><a class="reference internal" href="../mosaic/">slideflow.Mosaic</a></li>
<li class="toctree-l1"><a class="reference internal" href="../slidemap/">slideflow.SlideMap</a></li>
<li class="toctree-l1 current"><a class="current reference internal" href="#">slideflow.biscuit</a></li>
<li class="toctree-l1"><a class="reference internal" href="../slideflow_cellseg/">slideflow.cellseg</a></li>
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<section id="slideflow-biscuit">
<h1>slideflow.biscuit<a class="headerlink" href="#slideflow-biscuit" title="Permalink to this heading">¶</a></h1>
<p>This module contains an official implementation of <a class="reference external" href="https://www.nature.com/articles/s41467-022-34025-x">BISCUIT</a>, an uncertainty quantification and confidence thresholding algorithm for whole-slide images. The original implementation, which includes instructions for reproducing experimental results reported in the manuscript, is available on <a class="reference external" href="https://github.com/jamesdolezal/biscuit">GitHub</a>.</p>
<p>This module is requires the <code class="docutils literal notranslate"><span class="pre">slideflow-noncommercial</span></code> package, which can be installed with:</p>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>pip<span class="w"> </span>install<span class="w"> </span>slideflow-noncommercial
</pre></div>
</div>
<p>See <a class="reference internal" href="../uq/#uncertainty"><span class="std std-ref">Uncertainty Quantification</span></a> for more information.</p>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.biscuit.find_cv">
<span class="sig-name descname"><span class="pre">find_cv</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">project</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">label</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">outcome</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">epoch</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">3</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/slideflow_noncommercial/biscuit/utils/#find_cv"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#slideflow.biscuit.find_cv" title="Permalink to this definition">¶</a></dt>
<dd><p>Finds paths to cross-validation models.</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>project</strong> (<a class="reference internal" href="../project/#slideflow.Project" title="slideflow.Project"><em>slideflow.Project</em></a>) – Project.</p></li>
<li><p><strong>label</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a>) – Experimental label.</p></li>
<li><p><strong>outcome</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>optional</em>) – Outcome name.</p></li>
<li><p><strong>epoch</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><em>int</em></a><em>, </em><em>optional</em>) – Epoch number of saved model. Defaults to None.</p></li>
<li><p><strong>kfold</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><em>int</em></a><em>, </em><em>optional</em>) – K-fold iteration. Defaults to None.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>Paths to cross-validation models.</p>
</dd>
<dt class="field-odd">Return type<span class="colon">:</span></dt>
<dd class="field-odd"><p><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.12)">list</a>(<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)">str</a>)</p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.biscuit.get_model_results">
<span class="sig-name descname"><span class="pre">get_model_results</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">path</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">epoch</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">outcome</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/slideflow_noncommercial/biscuit/utils/#get_model_results"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#slideflow.biscuit.get_model_results" title="Permalink to this definition">¶</a></dt>
<dd><p>Reads results/metrics from a trained model.</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>path</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a>) – Path to model.</p></li>
<li><p><strong>outcome</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a>) – Outcome name.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p><dl class="simple">
<dt>pt_auc, pt_ap, slide_auc, slide_ap,</dt><dd><p>tile_auc, tile_ap, opt_thresh</p>
</dd>
</dl>
</p>
</dd>
<dt class="field-odd">Return type<span class="colon">:</span></dt>
<dd class="field-odd"><p>Dict of results with the keys</p>
</dd>
</dl>
</dd></dl>
<section id="biscuit-experiment">
<h2>biscuit.Experiment<a class="headerlink" href="#biscuit-experiment" title="Permalink to this heading">¶</a></h2>
<dl class="py class">
<dt class="sig sig-object py" id="slideflow.biscuit.Experiment">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">Experiment</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">train_project</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">eval_projects</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">outcome</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'cohort'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">outcome1</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'LUAD'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">outcome2</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'LUSC'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">outdir</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'results'</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/slideflow_noncommercial/biscuit/experiment/#Experiment"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#slideflow.biscuit.Experiment" title="Permalink to this definition">¶</a></dt>
<dd><p>Supervises uncertainty thresholding experiments.</p>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.biscuit.Experiment.display">
<span class="sig-name descname"><span class="pre">display</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">self</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">eval_dfs</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">hue</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'uq'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">palette</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'tab10'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">relplot_uq_compare</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">boxplot_uq_compare</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ttest_uq_groups</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">['all',</span> <span class="pre">'include']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prefix</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#slideflow.biscuit.Experiment.display" title="Permalink to this definition">¶</a></dt>
<dd><p>Creates plots from assmebled results, exports results to CSV.</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>df</strong> (<em>pandas.DataFrame</em>) – Cross-validation results metrics, as generated
by results()</p></li>
<li><p><strong>eval_dfs</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.12)"><em>dict</em></a><em>(</em><em>pandas.DataFrame</em><em>)</em>) – Dict of external eval dataset names
(keys) mapped to pandas DataFrame of result metrics (values).</p></li>
<li><p><strong>hue</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>optional</em>) – Comparison to show with different hue on plots.
Defaults to ‘uq’.</p></li>
<li><p><strong>palette</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>optional</em>) – Seaborn color palette. Defaults to ‘tab10’.</p></li>
<li><p><strong>relplot_uq_compare</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a><em>, </em><em>optional</em>) – For the Relplot display, ensure
non-UQ and UQ results are generated from the same models/preds.</p></li>
<li><p><strong>boxplot_uq_compare</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a><em>, </em><em>optional</em>) – For the boxplot display, ensure
non-UQ and UQ results are generated from the same models/preds.</p></li>
<li><p><strong>ttest_uq_groups</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.12)"><em>list</em></a><em>(</em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>)</em>) – UQ groups to compare via t-test. Defaults
to [‘all’, ‘include’].</p></li>
<li><p><strong>prefix</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>optional</em>) – Prefix to use when saving figures.
Defaults to empty string.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>None</p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.biscuit.Experiment.plot_uq_calibration">
<span class="sig-name descname"><span class="pre">plot_uq_calibration</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">self</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">label</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tile_uq</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">slide_uq</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">slide_pred</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">epoch</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#slideflow.biscuit.Experiment.plot_uq_calibration" title="Permalink to this definition">¶</a></dt>
<dd><p>Plots a graph of predictions vs. uncertainty.</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>label</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a>) – Experiment label.</p></li>
<li><p><strong>kfold</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><em>int</em></a>) – Validation k-fold.</p></li>
<li><p><strong>tile_uq</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.12)"><em>float</em></a>) – Tile-level uncertainty threshold.</p></li>
<li><p><strong>slide_uq</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.12)"><em>float</em></a>) – Slide-level uncertainty threshold.</p></li>
<li><p><strong>slide_pred</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.12)"><em>float</em></a>) – Slide-level prediction threshold.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>None</p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.biscuit.Experiment.results">
<span class="sig-name descname"><span class="pre">results</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">self</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">exp_to_run</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">uq</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">eval</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">plot</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#slideflow.biscuit.Experiment.results" title="Permalink to this definition">¶</a></dt>
<dd><p>Assembles results from experiments, applies UQ thresholding,
and returns pandas dataframes with metrics.</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>exp_to_run</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.12)"><em>list</em></a>) – List of experiment IDs to search for results.</p></li>
<li><p><strong>uq</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a><em>, </em><em>optional</em>) – Apply UQ thresholds. Defaults to True.</p></li>
<li><p><strong>eval</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a><em>, </em><em>optional</em>) – Calculate results of external evaluation models.
Defaults to True.</p></li>
<li><p><strong>plot</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a><em>, </em><em>optional</em>) – Show plots. Defaults to False.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>Cross-val results,
pandas.DataFrame: Dxternal eval results</p>
</dd>
<dt class="field-odd">Return type<span class="colon">:</span></dt>
<dd class="field-odd"><p>pandas.DataFrame</p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.biscuit.Experiment.thresholds_from_nested_cv">
<span class="sig-name descname"><span class="pre">thresholds_from_nested_cv</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">self</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">label</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">outer_k</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">inner_k</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">id</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">threshold_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">epoch</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tile_filename</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'tile_predictions_val_epoch1.csv'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y_true</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y_pred</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">uncertainty</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#slideflow.biscuit.Experiment.thresholds_from_nested_cv" title="Permalink to this definition">¶</a></dt>
<dd><p>Detects tile- and slide-level UQ thresholds and slide-level prediction
thresholds from nested cross-validation.</p>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.biscuit.Experiment.train">
<span class="sig-name descname"><span class="pre">train</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">self</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">hp</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">label</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">filters</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">save_predictions</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'csv'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">validate_on_batch</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">32</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">validation_steps</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">32</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#slideflow.biscuit.Experiment.train" title="Permalink to this definition">¶</a></dt>
<dd><p>Train outer cross-validation models.</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>hp</strong> (<a class="reference internal" href="../model_params/#slideflow.ModelParams" title="slideflow.ModelParams"><code class="xref py py-class docutils literal notranslate"><span class="pre">slideflow.ModelParams</span></code></a>) – Hyperparameters object.</p></li>
<li><p><strong>label</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a>) – Experimental label.</p></li>
<li><p><strong>filters</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.12)"><em>dict</em></a><em>, </em><em>optional</em>) – Dataset filters to use for
selecting slides. See <a class="reference internal" href="../dataset/#slideflow.Dataset.filter" title="slideflow.Dataset.filter"><code class="xref py py-meth docutils literal notranslate"><span class="pre">slideflow.Dataset.filter()</span></code></a> for
more information. Defaults to None.</p></li>
<li><p><strong>save_predictions</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a><em>, </em><em>optional</em>) – Save validation predictions to
model folder. Defaults to ‘csv’.</p></li>
</ul>
</dd>
<dt class="field-even">Keyword Arguments<span class="colon">:</span></dt>
<dd class="field-even"><ul class="simple">
<li><p><strong>validate_on_batch</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><em>int</em></a>) – Frequency of validation checks during
training, in steps. Defaults to 32.</p></li>
<li><p><strong>validation_steps</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><em>int</em></a>) – Number of validation steps to perform
during each mid-training evaluation check. Defaults to 32.</p></li>
<li><p><strong>**kwargs</strong> – All remaining keyword arguments are passed to
<a class="reference internal" href="../project/#slideflow.Project.train" title="slideflow.Project.train"><code class="xref py py-meth docutils literal notranslate"><span class="pre">slideflow.Project.train()</span></code></a>.</p></li>
</ul>
</dd>
<dt class="field-odd">Returns<span class="colon">:</span></dt>
<dd class="field-odd"><p>None</p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.biscuit.Experiment.train_nested_cv">
<span class="sig-name descname"><span class="pre">train_nested_cv</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">self</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">hp</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">label</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">outer_k</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">inner_k</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#slideflow.biscuit.Experiment.train_nested_cv" title="Permalink to this definition">¶</a></dt>
<dd><p>Train models using nested cross-validation (outer_k=3, inner_k=5),
skipping already-generated models.</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>hp</strong> (<a class="reference internal" href="../model_params/#slideflow.ModelParams" title="slideflow.ModelParams"><em>slideflow.ModelParams</em></a>) – Hyperparameters object.</p></li>
<li><p><strong>label</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a>) – Experimental label.</p></li>
</ul>
</dd>
<dt class="field-even">Keyword Arguments<span class="colon">:</span></dt>
<dd class="field-even"><ul class="simple">
<li><p><strong>outer_k</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><em>int</em></a>) – Number of outer cross-folds. Defaults to 3.</p></li>
<li><p><strong>inner_k</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><em>int</em></a>) – Number of inner cross-folds. Defaults to 5.</p></li>
<li><p><strong>**kwargs</strong> – All remaining keyword arguments are passed to
<a class="reference internal" href="../project/#slideflow.Project.train" title="slideflow.Project.train"><code class="xref py py-meth docutils literal notranslate"><span class="pre">slideflow.Project.train()</span></code></a>.</p></li>
</ul>
</dd>
<dt class="field-odd">Returns<span class="colon">:</span></dt>
<dd class="field-odd"><p>None</p>
</dd>
</dl>
</dd></dl>
</section>
<section id="biscuit-hp">
<h2>biscuit.hp<a class="headerlink" href="#biscuit-hp" title="Permalink to this heading">¶</a></h2>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.biscuit.hp.nature2022">
<span class="sig-name descname"><span class="pre">nature2022</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../_modules/slideflow/biscuit/hp/#nature2022"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#slideflow.biscuit.hp.nature2022" title="Permalink to this definition">¶</a></dt>
<dd><p>Hyperparameters used in the associated manuscript.</p>
<p>Dolezal, J.M., Srisuwananukorn, A., Karpeyev, D. et al.
Uncertainty-informed deep learning models enable high-confidence
predictions for digital histopathology. Nat Commun 13, 6572 (2022).
<a class="reference external" href="https://doi.org/10.1038/s41467-022-34025-x">https://doi.org/10.1038/s41467-022-34025-x</a></p>
<dl class="field-list simple">
<dt class="field-odd">Returns<span class="colon">:</span></dt>
<dd class="field-odd"><p><code class="docutils literal notranslate"><span class="pre">sf.ModelParams</span></code></p>
</dd>
</dl>
</dd></dl>
</section>
<section id="biscuit-threshold">
<h2>biscuit.threshold<a class="headerlink" href="#biscuit-threshold" title="Permalink to this heading">¶</a></h2>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.biscuit.threshold.apply">
<span class="sig-name descname"><span class="pre">apply</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tile_uq</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">slide_uq</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tile_pred</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">slide_pred</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">plot</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">keep</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'high_confidence'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">patients</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">level</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'slide'</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/slideflow/biscuit/threshold/#apply"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#slideflow.biscuit.threshold.apply" title="Permalink to this definition">¶</a></dt>
<dd><p>Apply pre-calculcated tile- and group-level uncertainty thresholds.</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>df</strong> (<em>pandas.DataFrame</em>) – Must contain columns ‘y_true’, ‘y_pred’,
and ‘uncertainty’.</p></li>
<li><p><strong>tile_uq</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.12)"><em>float</em></a>) – Tile-level uncertainty threshold.</p></li>
<li><p><strong>slide_uq</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.12)"><em>float</em></a>) – Slide-level uncertainty threshold.</p></li>
<li><p><strong>tile_pred</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.12)"><em>float</em></a><em>, </em><em>optional</em>) – Tile-level prediction threshold.
Defaults to 0.5.</p></li>
<li><p><strong>slide_pred</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.12)"><em>float</em></a><em>, </em><em>optional</em>) – Slide-level prediction threshold.
Defaults to 0.5.</p></li>
<li><p><strong>plot</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a><em>, </em><em>optional</em>) – Plot slide-level uncertainty. Defaults to False.</p></li>
<li><p><strong>keep</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>optional</em>) – Either ‘high_confidence’ or ‘low_confidence’.
Cohort to keep after thresholding. Defaults to ‘high_confidence’.</p></li>
<li><p><strong>title</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>optional</em>) – Title for uncertainty plot. Defaults to None.</p></li>
<li><p><strong>patients</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.12)"><em>dict</em></a><em>, </em><em>optional</em>) – Dictionary mapping slides to patients. Adds
a ‘patient’ column in the tile prediction dataframe, enabling
patient-level thresholding. Defaults to None.</p></li>
<li><p><strong>level</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>optional</em>) – Either ‘slide’ or ‘patient’. Level at which to
apply threshold. If ‘patient’, requires patient dict be supplied.
Defaults to ‘slide’.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p><dl class="simple">
<dt>Dictionary of results, with keys auc, percent_incl, accuracy,</dt><dd><p>sensitivity, and specificity</p>
</dd>
</dl>
<p>DataFrame of thresholded group-level predictions</p>
</p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.biscuit.threshold.detect">
<span class="sig-name descname"><span class="pre">detect</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tile_uq</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'detect'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">slide_uq</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'detect'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tile_pred</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'detect'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">slide_pred</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'detect'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">plot</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">patients</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/slideflow/biscuit/threshold/#detect"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#slideflow.biscuit.threshold.detect" title="Permalink to this definition">¶</a></dt>
<dd><p>Detect optimal tile- and slide-level uncertainty thresholds.</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>df</strong> (<em>pandas.DataFrame</em>) – Tile-level predictions. Must contain columns
‘y_true’, ‘y_pred’, and ‘uncertainty’.</p></li>
<li><p><strong>tile_uq</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em> or </em><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.12)"><em>float</em></a>) – Either ‘detect’ or float. If ‘detect’,
will detect tile-level uncertainty threshold. If float, will use
the specified tile-level uncertainty threshold.</p></li>
<li><p><strong>slide_uq</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em> or </em><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.12)"><em>float</em></a>) – Either ‘detect’ or float. If ‘detect’,
will detect slide-level uncertainty threshold. If float, will use
the specified slide-level uncertainty threshold.</p></li>
<li><p><strong>tile_pred</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em> or </em><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.12)"><em>float</em></a>) – Either ‘detect’ or float. If ‘detect’,
will detect tile-level prediction threshold. If float, will use the
specified tile-level prediction threshold.</p></li>
<li><p><strong>slide_pred</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em> or </em><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.12)"><em>float</em></a>) – Either ‘detect’ or float. If ‘detect’
will detect slide-level prediction threshold. If float, will use
the specified slide-level prediction threshold.</p></li>
<li><p><strong>plot</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a><em>, </em><em>optional</em>) – Plot slide-level uncertainty. Defaults to False.</p></li>
<li><p><strong>patients</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.12)"><em>dict</em></a><em>, </em><em>optional</em>) – Dict mapping slides to patients. Required
for patient-level thresholding.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p><dl class="simple">
<dt>Dictionary with tile- and slide-level UQ and prediction threhsolds,</dt><dd><p>with keys: ‘tile_uq’, ‘tile_pred’, ‘slide_uq’, ‘slide_pred’</p>
</dd>
</dl>
<p>Float: Slide-level AUROC</p>
</p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.biscuit.threshold.from_cv">
<span class="sig-name descname"><span class="pre">from_cv</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dfs</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/slideflow/biscuit/threshold/#from_cv"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#slideflow.biscuit.threshold.from_cv" title="Permalink to this definition">¶</a></dt>
<dd><p>Finds the optimal tile and slide-level thresholds from a set of nested
cross-validation experiments.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><p><strong>dfs</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.12)"><em>list</em></a><em>(</em><em>DataFrame</em><em>)</em>) – List of DataFrames with tile predictions,
containing headers ‘y_true’, ‘y_pred’, ‘uncertainty’, ‘slide’,
and ‘patient’.</p>
</dd>
<dt class="field-even">Keyword Arguments<span class="colon">:</span></dt>
<dd class="field-even"><ul class="simple">
<li><p><strong>tile_uq</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em> or </em><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.12)"><em>float</em></a>) – Either ‘detect’ or float. If ‘detect’,
will detect tile-level uncertainty threshold. If float, will use
the specified tile-level uncertainty threshold.</p></li>
<li><p><strong>slide_uq</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em> or </em><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.12)"><em>float</em></a>) – Either ‘detect’ or float. If ‘detect’,
will detect slide-level uncertainty threshold. If float, will use
the specified slide-level uncertainty threshold.</p></li>
<li><p><strong>tile_pred</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em> or </em><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.12)"><em>float</em></a>) – Either ‘detect’ or float. If ‘detect’,
will detect tile-level prediction threshold. If float, will use the
specified tile-level prediction threshold.</p></li>
<li><p><strong>slide_pred</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em> or </em><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.12)"><em>float</em></a>) – Either ‘detect’ or float. If ‘detect’
will detect slide-level prediction threshold. If float, will use
the specified slide-level prediction threshold.</p></li>
<li><p><strong>plot</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a><em>, </em><em>optional</em>) – Plot slide-level uncertainty. Defaults to False.</p></li>
<li><p><strong>patients</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.12)"><em>dict</em></a><em>, </em><em>optional</em>) – Dict mapping slides to patients. Required
for patient-level thresholding.</p></li>
</ul>
</dd>
<dt class="field-odd">Returns<span class="colon">:</span></dt>
<dd class="field-odd"><p><dl class="simple">
<dt>Dictionary with tile- and slide-level UQ and prediction threhsolds,</dt><dd><p>with keys: ‘tile_uq’, ‘tile_pred’, ‘slide_uq’, ‘slide_pred’</p>
</dd>
</dl>
</p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.biscuit.threshold.plot_uncertainty">
<span class="sig-name descname"><span class="pre">plot_uncertainty</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">kind</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">threshold</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">title</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/slideflow/biscuit/threshold/#plot_uncertainty"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#slideflow.biscuit.threshold.plot_uncertainty" title="Permalink to this definition">¶</a></dt>
<dd><p>Plots figure of tile or slide-level predictions vs. uncertainty.</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>df</strong> (<em>pandas.DataFrame</em>) – Processed dataframe containing columns
‘uncertainty’, ‘correct’, ‘y_pred’.</p></li>
<li><p><strong>kind</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a>) – Kind of plot. If ‘tile’, subsample to only 1000 points.
Included in title.</p></li>
<li><p><strong>threshold</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.12)"><em>float</em></a><em>, </em><em>optional</em>) – Uncertainty threshold.
Defaults to None.</p></li>
<li><p><strong>title</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>optional</em>) – Title for plots. Defaults to None.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>None</p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.biscuit.threshold.process_group_predictions">
<span class="sig-name descname"><span class="pre">process_group_predictions</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">pred_thresh</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">level</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/slideflow/biscuit/threshold/#process_group_predictions"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#slideflow.biscuit.threshold.process_group_predictions" title="Permalink to this definition">¶</a></dt>
<dd><p>From a given dataframe of tile-level predictions, calculate group-level
predictions and uncertainty.</p>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.biscuit.threshold.process_tile_predictions">
<span class="sig-name descname"><span class="pre">process_tile_predictions</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">pred_thresh</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">patients</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/slideflow/biscuit/threshold/#process_tile_predictions"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#slideflow.biscuit.threshold.process_tile_predictions" title="Permalink to this definition">¶</a></dt>
<dd><p>Load and process tile-level predictions from CSV.</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>df</strong> (<em>pandas.DataFrame</em>) – Unprocessed DataFrame from reading tile-level
predictions.</p></li>
<li><p><strong>pred_thresh</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.12)"><em>float</em></a><em> or </em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>optional</em>) – Tile-level prediction threshold.
If ‘detect’, will auto-detect via Youden’s J. Defaults to 0.5.</p></li>
<li><p><strong>patients</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.12)"><em>dict</em></a><em>, </em><em>optional</em>) – Dict mapping slides to patients, used for
patient-level thresholding. Defaults to None.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>pandas.DataFrame, tile prediction threshold</p>
</dd>
</dl>
</dd></dl>
</section>
<section id="biscuit-utils">
<h2>biscuit.utils<a class="headerlink" href="#biscuit-utils" title="Permalink to this heading">¶</a></h2>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.biscuit.utils.auc">
<span class="sig-name descname"><span class="pre">auc</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">y_true</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y_pred</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/slideflow/biscuit/utils/#auc"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#slideflow.biscuit.utils.auc" title="Permalink to this definition">¶</a></dt>
<dd><p>Calculate Area Under Receiver Operator Curve (AUC / AUROC)</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>y_true</strong> (<em>np.ndarray</em>) – True labels.</p></li>
<li><p><strong>y_pred</strong> (<em>np.ndarray</em>) – Predictions.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>AUC</p>
</dd>
<dt class="field-odd">Return type<span class="colon">:</span></dt>
<dd class="field-odd"><p>Float</p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.biscuit.utils.auc_and_threshold">
<span class="sig-name descname"><span class="pre">auc_and_threshold</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">y_true</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y_pred</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/slideflow/biscuit/utils/#auc_and_threshold"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#slideflow.biscuit.utils.auc_and_threshold" title="Permalink to this definition">¶</a></dt>
<dd><p>Calculates AUC and optimal threshold (via Youden’s J)</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>y_true</strong> (<em>np.ndarray</em>) – Y true (labels).</p></li>
<li><p><strong>y_pred</strong> (<em>np.ndarray</em>) – Y pred (predictions).</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>AUC
float: Optimal threshold</p>
</dd>
<dt class="field-odd">Return type<span class="colon">:</span></dt>
<dd class="field-odd"><p><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.12)">float</a></p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.biscuit.utils.df_from_cv">
<span class="sig-name descname"><span class="pre">df_from_cv</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">project</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">label</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">outcome</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">epoch</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y_true</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y_pred</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">uncertainty</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/slideflow/biscuit/utils/#df_from_cv"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#slideflow.biscuit.utils.df_from_cv" title="Permalink to this definition">¶</a></dt>
<dd><p>Loads tile predictions from cross-fold models & renames columns.</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>project</strong> (<em>sf.Project</em>) – Slideflow project.</p></li>
<li><p><strong>label</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a>) – Experimental label.</p></li>
<li><p><strong>epoch</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><em>int</em></a><em>, </em><em>optional</em>) – Epoch number of saved model. Defaults to None.</p></li>
<li><p><strong>k</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><em>int</em></a><em>, </em><em>optional</em>) – K-fold iteration. Defaults to 3.</p></li>
<li><p><strong>outcome</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>optional</em>) – Outcome name.</p></li>
<li><p><strong>y_true</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>optional</em>) – Column name for ground truth labels.
Defaults to {outcome}_y_true0.</p></li>
<li><p><strong>y_pred</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>optional</em>) – Column name for predictions.
Defaults to {outcome}_y_pred1.</p></li>
<li><p><strong>uncertainty</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>optional</em>) – Column name for uncertainty.
Defaults to {outcome}_y_uncertainty1.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>DataFrame for each k-fold.</p>
</dd>
<dt class="field-odd">Return type<span class="colon">:</span></dt>
<dd class="field-odd"><p><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.12)">list</a>(DataFrame)</p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.biscuit.utils.eval_exists">
<span class="sig-name descname"><span class="pre">eval_exists</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">project</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">label</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">outcome</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">epoch</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/slideflow/biscuit/utils/#eval_exists"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#slideflow.biscuit.utils.eval_exists" title="Permalink to this definition">¶</a></dt>
<dd><p>Check if matching eval exists.</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>project</strong> (<a class="reference internal" href="../project/#slideflow.Project" title="slideflow.Project"><em>slideflow.Project</em></a>) – Project.</p></li>
<li><p><strong>label</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a>) – Experimental label.</p></li>
<li><p><strong>epoch</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><em>int</em></a><em>, </em><em>optional</em>) – Epoch number of saved model. Defaults to None.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>If eval exists</p>
</dd>
<dt class="field-odd">Return type<span class="colon">:</span></dt>
<dd class="field-odd"><p><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)">bool</a></p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.biscuit.utils.find_cv">
<span class="sig-name descname"><span class="pre">find_cv</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">project</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">label</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">outcome</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">epoch</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">3</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/slideflow/biscuit/utils/#find_cv"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#slideflow.biscuit.utils.find_cv" title="Permalink to this definition">¶</a></dt>
<dd><p>Finds paths to cross-validation models.</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>project</strong> (<a class="reference internal" href="../project/#slideflow.Project" title="slideflow.Project"><em>slideflow.Project</em></a>) – Project.</p></li>
<li><p><strong>label</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a>) – Experimental label.</p></li>
<li><p><strong>outcome</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>optional</em>) – Outcome name.</p></li>
<li><p><strong>epoch</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><em>int</em></a><em>, </em><em>optional</em>) – Epoch number of saved model. Defaults to None.</p></li>
<li><p><strong>kfold</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><em>int</em></a><em>, </em><em>optional</em>) – K-fold iteration. Defaults to None.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>Paths to cross-validation models.</p>
</dd>
<dt class="field-odd">Return type<span class="colon">:</span></dt>
<dd class="field-odd"><p><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.12)">list</a>(<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)">str</a>)</p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.biscuit.utils.find_cv_early_stop">
<span class="sig-name descname"><span class="pre">find_cv_early_stop</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">project</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">label</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">outcome</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">3</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/slideflow/biscuit/utils/#find_cv_early_stop"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#slideflow.biscuit.utils.find_cv_early_stop" title="Permalink to this definition">¶</a></dt>
<dd><p>Detects early stop batch from cross-val trained models.</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>project</strong> (<a class="reference internal" href="../project/#slideflow.Project" title="slideflow.Project"><em>slideflow.Project</em></a>) – Project.</p></li>
<li><p><strong>label</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a>) – Experimental label.</p></li>
<li><p><strong>k</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><em>int</em></a><em>, </em><em>optional</em>) – Number of k-fold iterations. Defaults to 3.</p></li>
<li><p><strong>outcome</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a>) – Outcome name.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>Early stop batch.</p>
</dd>
<dt class="field-odd">Return type<span class="colon">:</span></dt>
<dd class="field-odd"><p><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)">int</a></p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.biscuit.utils.find_eval">
<span class="sig-name descname"><span class="pre">find_eval</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">project</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">label</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">outcome</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">epoch</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/slideflow/biscuit/utils/#find_eval"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#slideflow.biscuit.utils.find_eval" title="Permalink to this definition">¶</a></dt>
<dd><p>Finds matching eval directory.</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>project</strong> (<a class="reference internal" href="../project/#slideflow.Project" title="slideflow.Project"><em>slideflow.Project</em></a>) – Project.</p></li>
<li><p><strong>label</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a>) – Experimental label.</p></li>
<li><p><strong>outcome</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>optional</em>) – Outcome name.</p></li>
<li><p><strong>epoch</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><em>int</em></a><em>, </em><em>optional</em>) – Epoch number of saved model. Defaults to None.</p></li>
</ul>
</dd>
<dt class="field-even">Raises<span class="colon">:</span></dt>
<dd class="field-even"><ul class="simple">
<li><p><strong>MultipleModelsFoundError</strong> – If multiple matches are found.</p></li>
<li><p><strong>ModelNotFoundError</strong> – If no match is found.</p></li>
</ul>
</dd>
<dt class="field-odd">Returns<span class="colon">:</span></dt>
<dd class="field-odd"><p>path to eval directory</p>
</dd>
<dt class="field-even">Return type<span class="colon">:</span></dt>
<dd class="field-even"><p><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)">str</a></p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.biscuit.utils.find_model">
<span class="sig-name descname"><span class="pre">find_model</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">project</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">label</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">outcome</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">epoch</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">kfold</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/slideflow/biscuit/utils/#find_model"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#slideflow.biscuit.utils.find_model" title="Permalink to this definition">¶</a></dt>
<dd><p>Searches for a model in a project model directory.</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>project</strong> (<a class="reference internal" href="../project/#slideflow.Project" title="slideflow.Project"><em>slideflow.Project</em></a>) – Project.</p></li>
<li><p><strong>label</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a>) – Experimental label.</p></li>
<li><p><strong>outcome</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a>) – Outcome name.</p></li>
<li><p><strong>epoch</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><em>int</em></a><em>, </em><em>optional</em>) – Epoch to search for. If not None, returns
path to the saved model. If None, returns path to parent model
folder. Defaults to None.</p></li>
<li><p><strong>kfold</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><em>int</em></a><em>, </em><em>optional</em>) – K-fold iteration. Defaults to None.</p></li>
</ul>
</dd>
<dt class="field-even">Raises<span class="colon">:</span></dt>
<dd class="field-even"><ul class="simple">
<li><p><strong>MultipleModelsFoundError</strong> – If multiple potential matches are found.</p></li>
<li><p><strong>ModelNotFoundError</strong> – If no matching model is found.</p></li>
</ul>
</dd>
<dt class="field-odd">Returns<span class="colon">:</span></dt>
<dd class="field-odd"><p>Path to matching model.</p>
</dd>
<dt class="field-even">Return type<span class="colon">:</span></dt>
<dd class="field-even"><p><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)">str</a></p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.biscuit.utils.get_model_results">
<span class="sig-name descname"><span class="pre">get_model_results</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">path</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">epoch</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">outcome</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/slideflow/biscuit/utils/#get_model_results"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#slideflow.biscuit.utils.get_model_results" title="Permalink to this definition">¶</a></dt>
<dd><p>Reads results/metrics from a trained model.</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>path</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a>) – Path to model.</p></li>
<li><p><strong>outcome</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a>) – Outcome name.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p><dl class="simple">
<dt>pt_auc, pt_ap, slide_auc, slide_ap,</dt><dd><p>tile_auc, tile_ap, opt_thresh</p>
</dd>
</dl>
</p>
</dd>
<dt class="field-odd">Return type<span class="colon">:</span></dt>
<dd class="field-odd"><p>Dict of results with the keys</p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.biscuit.utils.get_eval_results">
<span class="sig-name descname"><span class="pre">get_eval_results</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">path</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">outcome</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/slideflow/biscuit/utils/#get_eval_results"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#slideflow.biscuit.utils.get_eval_results" title="Permalink to this definition">¶</a></dt>
<dd><p>Reads results/metrics from a trained model.</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>path</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a>) – Path to model.</p></li>
<li><p><strong>outcome</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a>) – Outcome name.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p><dl class="simple">
<dt>pt_auc, pt_ap, slide_auc, slide_ap,</dt><dd><p>tile_auc, tile_ap, opt_thresh</p>
</dd>
</dl>
</p>
</dd>
<dt class="field-odd">Return type<span class="colon">:</span></dt>
<dd class="field-odd"><p>Dict of results with the keys</p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.biscuit.utils.model_exists">
<span class="sig-name descname"><span class="pre">model_exists</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">project</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">label</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">outcome</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">epoch</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">kfold</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/slideflow/biscuit/utils/#model_exists"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#slideflow.biscuit.utils.model_exists" title="Permalink to this definition">¶</a></dt>
<dd><p>Check if matching model exists.</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>project</strong> (<a class="reference internal" href="../project/#slideflow.Project" title="slideflow.Project"><em>slideflow.Project</em></a>) – Project.</p></li>
<li><p><strong>label</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a>) – Experimental label.</p></li>
<li><p><strong>outcome</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>optional</em>) – Outcome name.</p></li>
<li><p><strong>epoch</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><em>int</em></a><em>, </em><em>optional</em>) – Epoch number of saved model. Defaults to None.</p></li>
<li><p><strong>kfold</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><em>int</em></a><em>, </em><em>optional</em>) – K-fold iteration. Defaults to None.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>If model exists</p>
</dd>
<dt class="field-odd">Return type<span class="colon">:</span></dt>
<dd class="field-odd"><p><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)">bool</a></p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.biscuit.utils.prediction_metrics">
<span class="sig-name descname"><span class="pre">prediction_metrics</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">y_true</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y_pred</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">threshold</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/slideflow/biscuit/utils/#prediction_metrics"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#slideflow.biscuit.utils.prediction_metrics" title="Permalink to this definition">¶</a></dt>
<dd><p>Calculate prediction metrics (AUC, sensitivity/specificity, etc)</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>y_true</strong> (<em>np.ndarray</em>) – True labels.</p></li>
<li><p><strong>y_pred</strong> (<em>np.ndarray</em>) – Predictions.</p></li>
<li><p><strong>threshold</strong> (<em>_type_</em>) – Prediction threshold.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>Prediction metrics.</p>
</dd>
<dt class="field-odd">Return type<span class="colon">:</span></dt>
<dd class="field-odd"><p><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.12)">dict</a></p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.biscuit.utils.read_group_predictions">
<span class="sig-name descname"><span class="pre">read_group_predictions</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">path</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/slideflow/biscuit/utils/#read_group_predictions"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#slideflow.biscuit.utils.read_group_predictions" title="Permalink to this definition">¶</a></dt>
<dd><p>Reads patient- or slide-level predictions CSV or parquet file,
returning y_true and y_pred.</p>
<p>Expects a binary categorical outcome.</p>
<p>Compatible with Slideflow 1.1 and 1.2.</p>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.biscuit.utils.truncate_colormap">
<span class="sig-name descname"><span class="pre">truncate_colormap</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">cmap</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">minval</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">maxval</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">100</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/slideflow/biscuit/utils/#truncate_colormap"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#slideflow.biscuit.utils.truncate_colormap" title="Permalink to this definition">¶</a></dt>
<dd><p>Truncates matplotlib colormap.</p>
</dd></dl>
</section>
<section id="biscuit-delong">
<h2>biscuit.delong<a class="headerlink" href="#biscuit-delong" title="Permalink to this heading">¶</a></h2>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.biscuit.delong.fastDeLong">
<span class="sig-name descname"><span class="pre">fastDeLong</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">predictions_sorted_transposed</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">label_1_count</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/slideflow/biscuit/delong/#fastDeLong"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#slideflow.biscuit.delong.fastDeLong" title="Permalink to this definition">¶</a></dt>
<dd><p>The fast version of DeLong’s method for computing the covariance of
unadjusted AUC.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><p><strong>predictions_sorted_transposed</strong> – a 2D numpy.array[n_classifiers, n_examples]
sorted such as the examples with label “1” are first</p>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>(AUC value, DeLong covariance)</p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.biscuit.delong.delong_roc_variance">
<span class="sig-name descname"><span class="pre">delong_roc_variance</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ground_truth</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">predictions</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/slideflow/biscuit/delong/#delong_roc_variance"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#slideflow.biscuit.delong.delong_roc_variance" title="Permalink to this definition">¶</a></dt>
<dd><p>Computes ROC AUC variance for a single set of predictions</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>ground_truth</strong> – np.array of 0 and 1</p></li>
<li><p><strong>predictions</strong> – np.array of floats of the probability of being class 1</p></li>
</ul>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.biscuit.delong.delong_roc_test">
<span class="sig-name descname"><span class="pre">delong_roc_test</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ground_truth</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">predictions_one</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">predictions_two</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/slideflow/biscuit/delong/#delong_roc_test"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#slideflow.biscuit.delong.delong_roc_test" title="Permalink to this definition">¶</a></dt>
<dd><p>Computes log(p-value) for hypothesis that two ROC AUCs are different</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>ground_truth</strong> – np.array of 0 and 1</p></li>
<li><p><strong>predictions_one</strong> – predictions of the first model,
np.array of floats of the probability of being class 1</p></li>
<li><p><strong>predictions_two</strong> – predictions of the second model,
np.array of floats of the probability of being class 1</p></li>
</ul>
</dd>
</dl>
</dd></dl>
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