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<h3>
Andreas Tille pushed to branch upstream
at <a href="https://salsa.debian.org/med-team/q2-sample-classifier">Debian Med / q2-sample-classifier</a>
</h3>
<h4>
Commits:
</h4>
<ul>
<li>
<strong><a href="https://salsa.debian.org/med-team/q2-sample-classifier/-/commit/7c4b78faf33bc50e958843964685cf5d73d1374d">7c4b78fa</a></strong>
<div>
<span>by Andreas Tille</span>
<i>at 2021-09-27T21:05:46+02:00</i>
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<pre class="commit-message" style="white-space: pre-wrap; margin: 0;">New upstream version 2021.8.0</pre>
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<h4>26 changed files:</h4>
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.github/workflows/ci.yml
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.travis.yml
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<a href="#0398ccd0f49298b10a3d76a47800d2ebecd49859">
LICENSE
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<a href="#8ec9a00bfd09b3190ac6b22251dbb1aa95a0579d">
README.md
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ci/recipe/conda_build_config.yaml
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<a href="#22fbe0b68848772d4b1c45f0d62dcd71a06cde00">
ci/recipe/meta.yaml
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<a href="#4dcec7b702b20e60f6249e2b7dea2024d22592ce">
q2_sample_classifier/__init__.py
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<a href="#623bd4f7ed2d962b3c814341035f74215cd49fbb">
q2_sample_classifier/_format.py
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<a href="#f2f769f37064993413ab00a80b781f7beba9af8c">
q2_sample_classifier/_transformer.py
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<a href="#2de341b25fc2b9fbf25f6d9875184a488e500131">
q2_sample_classifier/_type.py
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<a href="#8515f1a26069e2433b6eb1b2467029a285c54307">
q2_sample_classifier/_version.py
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<a href="#d03e8c1be7a2c3f1153f07d555333a24acafc744">
q2_sample_classifier/assets/index.html
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<a href="#7cc5deec9c3ee7ce9ba719cb8f4de3aed956b0b0">
q2_sample_classifier/classify.py
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<a href="#c08051df7bfc269d890469f18a611f1e3730f850">
q2_sample_classifier/plugin_setup.py
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<a href="#1b690d92d63b3499c2ca3d9b95eb15070797d08d">
q2_sample_classifier/tests/__init__.py
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q2_sample_classifier/tests/data/true_targets.tsv
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q2_sample_classifier/tests/test_actions.py
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<a href="#1e7213981596409508f1bb2c78c18bb9d19078e8">
q2_sample_classifier/tests/test_base_class.py
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q2_sample_classifier/tests/test_classifier.py
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<a href="#bf556fc40b98a4a248e31e633c175e9744ae3286">
q2_sample_classifier/tests/test_estimators.py
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<a href="#479a2fb6d0756ddb6a08bc0ddf764b87668ecbb6">
q2_sample_classifier/tests/test_types_formats_transformers.py
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<a href="#0ccb90ff3ed1ae1e67d1463b5bc4e15be435030a">
q2_sample_classifier/tests/test_utilities.py
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<a href="#2607554eb0fe14065eea07f68c7991db73cfa7f8">
q2_sample_classifier/tests/test_visualization.py
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<a href="#0be6602492251a34b00c1d37085f5deaca6be29e">
q2_sample_classifier/utilities.py
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<a href="#1445eb5a166ed40e8d437f17b2765bc1a0daa6fb">
q2_sample_classifier/visuals.py
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<li class="file-stats">
<a href="#8e2edce0d507e1297474f25c00cae94258db38d8">
setup.py
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<h4>Changes:</h4>
<li id="899ce9c202bf7bb5480e72836c3edc773c9c4244">
<a href="https://salsa.debian.org/med-team/q2-sample-classifier/-/commit/7c4b78faf33bc50e958843964685cf5d73d1374d#899ce9c202bf7bb5480e72836c3edc773c9c4244"><strong>.github/workflows/ci.yml</strong></a>
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<pre style="margin: 0;">+<span id="LC1" class="line" lang="yaml"><span class="c1" style="color: #998; font-style: italic;"># This file is automatically generated by busywork.qiime2.org and</span></span>
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<pre style="margin: 0;">+<span id="LC2" class="line" lang="yaml"><span class="c1" style="color: #998; font-style: italic;"># template-repos - any manual edits made to this file will be erased when</span></span>
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<pre style="margin: 0;">+<span id="LC3" class="line" lang="yaml"><span class="c1" style="color: #998; font-style: italic;"># busywork performs maintenance updates.</span></span>
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<pre style="margin: 0;">+<span id="LC5" class="line" lang="yaml"><span class="na" style="color: #008080;">name</span><span class="pi">:</span> <span class="s" style="color: #d14;">ci</span></span>
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<pre style="margin: 0;">+<span id="LC6" class="line" lang="yaml"></span>
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<pre style="margin: 0;">+<span id="LC8" class="line" lang="yaml"> <span class="na" style="color: #008080;">pull_request</span><span class="pi">:</span></span>
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<pre style="margin: 0;">+<span id="LC9" class="line" lang="yaml"> <span class="na" style="color: #008080;">push</span><span class="pi">:</span></span>
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<pre style="margin: 0;">+<span id="LC10" class="line" lang="yaml"> <span class="na" style="color: #008080;">branches</span><span class="pi">:</span></span>
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<pre style="margin: 0;">+<span id="LC11" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">master</span></span>
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<pre style="margin: 0;">+<span id="LC12" class="line" lang="yaml"></span>
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<pre style="margin: 0;">+<span id="LC13" class="line" lang="yaml"><span class="na" style="color: #008080;">jobs</span><span class="pi">:</span></span>
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<pre style="margin: 0;">+<span id="LC14" class="line" lang="yaml"> <span class="na" style="color: #008080;">lint</span><span class="pi">:</span></span>
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<pre style="margin: 0;">+<span id="LC15" class="line" lang="yaml"> <span class="na" style="color: #008080;">runs-on</span><span class="pi">:</span> <span class="s" style="color: #d14;">ubuntu-latest</span></span>
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<pre style="margin: 0;">+<span id="LC16" class="line" lang="yaml"> <span class="na" style="color: #008080;">steps</span><span class="pi">:</span></span>
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<pre style="margin: 0;">+<span id="LC17" class="line" lang="yaml"> <span class="pi">-</span> <span class="na" style="color: #008080;">name</span><span class="pi">:</span> <span class="s" style="color: #d14;">checkout source</span></span>
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<pre style="margin: 0;">+<span id="LC18" class="line" lang="yaml"> <span class="na" style="color: #008080;">uses</span><span class="pi">:</span> <span class="s" style="color: #d14;">actions/checkout@v2</span></span>
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19
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<pre style="margin: 0;">+<span id="LC19" class="line" lang="yaml"></span>
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<pre style="margin: 0;">+<span id="LC20" class="line" lang="yaml"> <span class="pi">-</span> <span class="na" style="color: #008080;">name</span><span class="pi">:</span> <span class="s" style="color: #d14;">set up python </span><span class="m" style="color: #099;">3.8</span></span>
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21
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<pre style="margin: 0;">+<span id="LC21" class="line" lang="yaml"> <span class="na" style="color: #008080;">uses</span><span class="pi">:</span> <span class="s" style="color: #d14;">actions/setup-python@v1</span></span>
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22
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<pre style="margin: 0;">+<span id="LC22" class="line" lang="yaml"> <span class="na" style="color: #008080;">with</span><span class="pi">:</span></span>
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23
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<pre style="margin: 0;">+<span id="LC23" class="line" lang="yaml"> <span class="na" style="color: #008080;">python-version</span><span class="pi">:</span> <span class="m" style="color: #099;">3.8</span></span>
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24
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<pre style="margin: 0;">+<span id="LC24" class="line" lang="yaml"></span>
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25
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<pre style="margin: 0;">+<span id="LC25" class="line" lang="yaml"> <span class="pi">-</span> <span class="na" style="color: #008080;">name</span><span class="pi">:</span> <span class="s" style="color: #d14;">install dependencies</span></span>
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26
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<pre style="margin: 0;">+<span id="LC26" class="line" lang="yaml"> <span class="na" style="color: #008080;">run</span><span class="pi">:</span> <span class="s" style="color: #d14;">python -m pip install --upgrade pip</span></span>
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27
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<pre style="margin: 0;">+<span id="LC27" class="line" lang="yaml"></span>
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28
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<pre style="margin: 0;">+<span id="LC28" class="line" lang="yaml"> <span class="pi">-</span> <span class="na" style="color: #008080;">name</span><span class="pi">:</span> <span class="s" style="color: #d14;">lint</span></span>
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29
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<pre style="margin: 0;">+<span id="LC29" class="line" lang="yaml"> <span class="na" style="color: #008080;">run</span><span class="pi">:</span> <span class="pi">|</span></span>
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<pre style="margin: 0;">+<span id="LC30" class="line" lang="yaml"> <span class="s" style="color: #d14;">pip install -q https://github.com/qiime2/q2lint/archive/master.zip</span></span>
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31
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<pre style="margin: 0;">+<span id="LC31" class="line" lang="yaml"> <span class="s" style="color: #d14;">q2lint</span></span>
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32
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<pre style="margin: 0;">+<span id="LC32" class="line" lang="yaml"> <span class="s" style="color: #d14;">pip install -q flake8</span></span>
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33
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<pre style="margin: 0;">+<span id="LC33" class="line" lang="yaml"> <span class="s" style="color: #d14;">flake8</span></span>
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34
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<pre style="margin: 0;">+<span id="LC34" class="line" lang="yaml"></span>
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35
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<pre style="margin: 0;">+<span id="LC35" class="line" lang="yaml"> <span class="na" style="color: #008080;">build-and-test</span><span class="pi">:</span></span>
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36
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<pre style="margin: 0;">+<span id="LC36" class="line" lang="yaml"> <span class="na" style="color: #008080;">needs</span><span class="pi">:</span> <span class="s" style="color: #d14;">lint</span></span>
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37
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<pre style="margin: 0;">+<span id="LC37" class="line" lang="yaml"> <span class="na" style="color: #008080;">strategy</span><span class="pi">:</span></span>
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38
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<pre style="margin: 0;">+<span id="LC38" class="line" lang="yaml"> <span class="na" style="color: #008080;">matrix</span><span class="pi">:</span></span>
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39
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<pre style="margin: 0;">+<span id="LC39" class="line" lang="yaml"> <span class="na" style="color: #008080;">os</span><span class="pi">:</span> <span class="pi">[</span><span class="nv" style="color: #008080;">ubuntu-latest</span><span class="pi">,</span> <span class="nv" style="color: #008080;">macos-latest</span><span class="pi">]</span></span>
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40
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<pre style="margin: 0;">+<span id="LC40" class="line" lang="yaml"> <span class="na" style="color: #008080;">runs-on</span><span class="pi">:</span> <span class="s" style="color: #d14;">${{ matrix.os }}</span></span>
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41
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<pre style="margin: 0;">+<span id="LC41" class="line" lang="yaml"> <span class="na" style="color: #008080;">steps</span><span class="pi">:</span></span>
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<pre style="margin: 0;">+<span id="LC42" class="line" lang="yaml"> <span class="pi">-</span> <span class="na" style="color: #008080;">name</span><span class="pi">:</span> <span class="s" style="color: #d14;">checkout source</span></span>
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43
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<pre style="margin: 0;">+<span id="LC43" class="line" lang="yaml"> <span class="na" style="color: #008080;">uses</span><span class="pi">:</span> <span class="s" style="color: #d14;">actions/checkout@v2</span></span>
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<pre style="margin: 0;">+<span id="LC44" class="line" lang="yaml"> <span class="na" style="color: #008080;">with</span><span class="pi">:</span></span>
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45
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<pre style="margin: 0;">+<span id="LC45" class="line" lang="yaml"> <span class="na" style="color: #008080;">fetch-depth</span><span class="pi">:</span> <span class="m" style="color: #099;">0</span></span>
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46
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<pre style="margin: 0;">+<span id="LC46" class="line" lang="yaml"></span>
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47
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<pre style="margin: 0;">+<span id="LC47" class="line" lang="yaml"> <span class="pi">-</span> <span class="na" style="color: #008080;">name</span><span class="pi">:</span> <span class="s" style="color: #d14;">set up git repo for versioneer</span></span>
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48
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<pre style="margin: 0;">+<span id="LC48" class="line" lang="yaml"> <span class="na" style="color: #008080;">run</span><span class="pi">:</span> <span class="s" style="color: #d14;">git fetch --depth=1 origin +refs/tags/*:refs/tags/*</span></span>
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<pre style="margin: 0;">+<span id="LC49" class="line" lang="yaml"></span>
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<pre style="margin: 0;">+<span id="LC50" class="line" lang="yaml"> <span class="pi">-</span> <span class="na" style="color: #008080;">uses</span><span class="pi">:</span> <span class="s" style="color: #d14;">qiime2/action-library-packaging@alpha1</span></span>
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51
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<pre style="margin: 0;">+<span id="LC51" class="line" lang="yaml"> <span class="na" style="color: #008080;">with</span><span class="pi">:</span></span>
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<pre style="margin: 0;">+<span id="LC52" class="line" lang="yaml"> <span class="na" style="color: #008080;">package-name</span><span class="pi">:</span> <span class="s" style="color: #d14;">q2-sample-classifier</span></span>
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53
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<pre style="margin: 0;">+<span id="LC53" class="line" lang="yaml"> <span class="na" style="color: #008080;">build-target</span><span class="pi">:</span> <span class="s" style="color: #d14;">dev</span></span>
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<pre style="margin: 0;">+<span id="LC54" class="line" lang="yaml"> <span class="na" style="color: #008080;">additional-tests</span><span class="pi">:</span> <span class="s" style="color: #d14;">py.test --pyargs q2_sample_classifier</span></span>
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<pre style="margin: 0;">+<span id="LC55" class="line" lang="yaml"> <span class="na" style="color: #008080;">library-token</span><span class="pi">:</span> <span class="s" style="color: #d14;">${{ secrets.LIBRARY_TOKEN }}</span></span></pre>
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<a href="https://salsa.debian.org/med-team/q2-sample-classifier/-/commit/7c4b78faf33bc50e958843964685cf5d73d1374d#dea01dd89a3b602828e630677fde5d77c06441c8"><strong>.travis.yml</strong>
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1
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<pre style="margin: 0;">-<span id="LC1" class="line" lang="yaml"><span class="na" style="color: #008080;">sudo</span><span class="pi">:</span> <span class="no" style="color: #008080;">false</span></span>
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2
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<pre style="margin: 0;">-<span id="LC2" class="line" lang="yaml"><span class="na" style="color: #008080;">language</span><span class="pi">:</span> <span class="s" style="color: #d14;">python</span></span>
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3
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<pre style="margin: 0;">-<span id="LC3" class="line" lang="yaml"><span class="na" style="color: #008080;">before_install</span><span class="pi">:</span></span>
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4
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<pre style="margin: 0;">-<span id="LC4" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">export MPLBACKEND='Agg'</span></span>
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5
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<pre style="margin: 0;">-<span id="LC5" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">wget -q https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh</span></span>
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6
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<pre style="margin: 0;">-<span id="LC6" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">export MINICONDA_PREFIX="$HOME/miniconda"</span></span>
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7
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<pre style="margin: 0;">-<span id="LC7" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">bash miniconda.sh -b -p $MINICONDA_PREFIX</span></span>
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8
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<pre style="margin: 0;">-<span id="LC8" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">export PATH="$MINICONDA_PREFIX/bin:$PATH"</span></span>
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9
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<pre style="margin: 0;">-<span id="LC9" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">conda config --set always_yes yes</span></span>
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<pre style="margin: 0;">-<span id="LC10" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">conda update -q conda</span></span>
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<pre style="margin: 0;">-<span id="LC11" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">conda info -a</span></span>
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<pre style="margin: 0;">-<span id="LC12" class="line" lang="yaml"><span class="na" style="color: #008080;">install</span><span class="pi">:</span></span>
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<pre style="margin: 0;">-<span id="LC13" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">wget -q https://raw.githubusercontent.com/qiime2/environment-files/master/latest/staging/qiime2-latest-py36-linux-conda.yml</span></span>
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<pre style="margin: 0;">-<span id="LC14" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">conda env create -q -n test-env --file qiime2-latest-py36-linux-conda.yml</span></span>
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<pre style="margin: 0;">-<span id="LC15" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">source activate test-env</span></span>
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<pre style="margin: 0;">-<span id="LC16" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">conda install -q pytest-cov</span></span>
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<pre style="margin: 0;">-<span id="LC17" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">pip install flake8 coveralls</span></span>
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<pre style="margin: 0;">-<span id="LC18" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">pip install -q https://github.com/qiime2/q2lint/archive/master.zip</span></span>
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<pre style="margin: 0;">-<span id="LC19" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">make install</span></span>
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20
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<pre style="margin: 0;">-<span id="LC20" class="line" lang="yaml"><span class="na" style="color: #008080;">script</span><span class="pi">:</span></span>
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<pre style="margin: 0;">-<span id="LC21" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">make lint</span></span>
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<pre style="margin: 0;">-<span id="LC22" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">make test-cov</span></span>
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<pre style="margin: 0;">-<span id="LC23" class="line" lang="yaml"><span class="na" style="color: #008080;">after_success</span><span class="pi">:</span></span>
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<pre style="margin: 0;">-<span id="LC24" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">coveralls</span></span>
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<pre style="margin: 0;">-<span id="LC25" class="line" lang="yaml"></span></pre>
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<a href="https://salsa.debian.org/med-team/q2-sample-classifier/-/commit/7c4b78faf33bc50e958843964685cf5d73d1374d#0398ccd0f49298b10a3d76a47800d2ebecd49859"><strong>LICENSE</strong></a>
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<pre style="margin: 0;"> <span id="LC1" class="line" lang="plaintext">BSD 3-Clause License</span>
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<pre style="margin: 0;">-<span id="LC3" class="line" lang="plaintext">Copyright (c) 2017-202<span class="idiff left right">0</span>, QIIME 2 development team.</span>
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<pre style="margin: 0;">+<span id="LC3" class="line" lang="plaintext">Copyright (c) 2017-202<span class="idiff left right">1</span>, QIIME 2 development team.</span>
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<pre style="margin: 0;"> <span id="LC4" class="line" lang="plaintext">All rights reserved.</span>
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<pre style="margin: 0;"> <span id="LC6" class="line" lang="plaintext">Redistribution and use in source and binary forms, with or without</span>
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<a href="https://salsa.debian.org/med-team/q2-sample-classifier/-/commit/7c4b78faf33bc50e958843964685cf5d73d1374d#8ec9a00bfd09b3190ac6b22251dbb1aa95a0579d"><strong>README.md</strong></a>
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<pre style="margin: 0;"> <span id="LC1" class="line" lang="markdown"><span class="gh" style="color: #800080; font-weight: 600;"># q2-sample-classifier</span></span>
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<pre style="margin: 0;"> <span id="LC2" class="line" lang="markdown"></span>
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<pre style="margin: 0;">-<span id="LC3" class="line" lang="markdown"><span class="p"><span class="idiff left">[</span></span><span class="nv" style="color: #008080;">![<span class="idiff">Build Status</span></span><span class="p"><span class="idiff">](</span></span><span class="sx" style="color: #d14;"><span class="idiff">https://travis-ci.org/qiime2/q2-sample-classifier.svg?branch=master</span></span><span class="p"><span class="idiff">)</span></span><span class="idiff">](https://travis-ci.org/qiime2/q2-sample-classifier) </span><span class="p"><span class="idiff">[</span></span><span class="nv" style="color: #008080;"><span class="idiff">![Coverage Status</span></span><span class="p"><span class="idiff">](</span></span><span class="sx" style="color: #d14;"><span class="idiff">https://coveralls.io/repos/github/qiime2/q2-sample-classifier/badge.svg?branch=master</span></span><span class="p"><span class="idiff">)</span></span><span class="idiff">](https://coveralls.io/github/qiime2/q2-sample-classifier?branch=master) </span><span class="p"><span class="idiff">[</span></span><span class="nv" style="color: #008080;"><span class="idiff">![DOI</span></span><span class="p"><span class="idiff">](</span></span><span class="sx" style="color: #d14;"><span class="idiff">https://zenodo.org/badge/DOI/10.5281/zenodo.1468879.svg</span></span><span class="p"><span class="idiff">)</span></span><span class="idiff">](https://doi.org/10.5281/zenodo.1468879) </span><span class="p"><span class="idiff">[</span></span><span class="nv" style="color: #008080;"><span class="idiff">![status</span></span><span class="p"><span class="idiff">](</span></span><span class="sx" style="color: #d14;"><span class="idiff">http://joss.theoj.org/papers/d828a4ecf73eb6a147f8634e9054eeee/status.svg</span></span><span class="p"><span class="idiff">)</span></span><span class="idiff right">](http://joss.theoj.org/papers/d828a4ecf73eb6a147f8634e9054eeee</span>)</span>
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<pre style="margin: 0;">+<span id="LC3" class="line" lang="markdown"><span class="p">![<span class="idiff left">](</span></span><span class="sx" style="color: #d14;"><span class="idiff right">https://github.com/qiime2/q2-sample-classifier/workflows/ci/badge.svg</span></span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC4" class="line" lang="markdown"></span>
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<pre style="margin: 0;">-<span id="LC5" class="line" lang="markdown"></span>
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<pre style="margin: 0;">-<span id="LC6" class="line" lang="markdown">QIIME 2 plugin for machine learning prediction of sample data.</span>
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<pre style="margin: 0;">-<span id="LC7" class="line" lang="markdown"></span>
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<pre style="margin: 0;">-<span id="LC8" class="line" lang="markdown">Microbiome studies often aim to predict outcomes or differentiate samples based on their microbial compositions, tasks that can be efficiently performed by supervised learning methods. The q2-sample-classifier plugin makes these methods more accessible, reproducible, and interpretable to a broad audience of microbiologists, clinicians, and others who wish to utilize supervised learning methods for predicting sample characteristics based on microbiome composition or other "omics" data.</span>
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<pre style="margin: 0;">-<span id="LC9" class="line" lang="markdown"></span>
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<pre style="margin: 0;">-<span id="LC10" class="line" lang="markdown"><span class="gu" style="color: #800080; font-weight: 600;">## Installation</span></span>
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<pre style="margin: 0;">-<span id="LC11" class="line" lang="markdown"></span>
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<pre style="margin: 0;">-<span id="LC12" class="line" lang="markdown">Follow the QIIME 2 core distribution installation instructions at https://qiime2.org/ to install q2-sample-classifier as part of the QIIME 2 analysis platform.</span>
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<pre style="margin: 0;">-<span id="LC13" class="line" lang="markdown"></span>
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<pre style="margin: 0;">-<span id="LC14" class="line" lang="markdown">To test deployment, run:</span>
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<pre style="margin: 0;">-<span id="LC15" class="line" lang="markdown"><span class="p">```</span></span>
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<pre style="margin: 0;">-<span id="LC16" class="line" lang="markdown">pytest --disable-pytest-warnings --pyargs q2_sample_classifier</span>
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<pre style="margin: 0;">-<span id="LC17" class="line" lang="markdown"><span class="p">```</span></span>
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<pre style="margin: 0;">-<span id="LC18" class="line" lang="markdown"></span>
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<pre style="margin: 0;">-<span id="LC19" class="line" lang="markdown"><span class="gu" style="color: #800080; font-weight: 600;">## Example usage</span></span>
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<pre style="margin: 0;">-<span id="LC20" class="line" lang="markdown"></span>
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<pre style="margin: 0;">-<span id="LC21" class="line" lang="markdown">This is a QIIME 2 plugin. For details on QIIME 2 and tutorials demonstrating how to use this plugin, see the <span class="p">[</span><span class="nv" style="color: #008080;">QIIME 2 documentation</span><span class="p">](</span><span class="sx" style="color: #d14;">https://qiime2.org/</span><span class="p">)</span>. Tutorials for this plugin can be found <span class="p">[</span><span class="nv" style="color: #008080;">here</span><span class="p">](</span><span class="sx" style="color: #d14;">https://docs.qiime2.org/2018.8/tutorials/sample-classifier/</span><span class="p">)</span>.</span>
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<pre style="margin: 0;">-<span id="LC22" class="line" lang="markdown"></span>
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<pre style="margin: 0;">-<span id="LC23" class="line" lang="markdown">Not sure which learning model to use? A good starting point is <span class="p">[</span><span class="nv" style="color: #008080;">this flowchart</span><span class="p">](</span><span class="sx" style="color: #d14;">http://scikit-learn.org/dev/tutorial/machine_learning_map/index.html</span><span class="p">)</span>. Most of the classification and regression models shown in that chart (and a few extras) are implemented in q2-sample-classifier.</span>
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<pre style="margin: 0;">-<span id="LC24" class="line" lang="markdown"></span>
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<pre style="margin: 0;">-<span id="LC25" class="line" lang="markdown"><span class="gu" style="color: #800080; font-weight: 600;">## API documentation</span></span>
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<pre style="margin: 0;">-<span id="LC26" class="line" lang="markdown"></span>
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<pre style="margin: 0;">-<span id="LC27" class="line" lang="markdown">API documentation can be found <span class="p">[</span><span class="nv" style="color: #008080;">here</span><span class="p">](</span><span class="sx" style="color: #d14;">https://docs.qiime2.org/2018.8/plugins/available/sample-classifier/</span><span class="p">)</span>.</span>
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<pre style="margin: 0;">-<span id="LC28" class="line" lang="markdown"></span>
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<pre style="margin: 0;">-<span id="LC29" class="line" lang="markdown"><span class="gu" style="color: #800080; font-weight: 600;">## Help</span></span>
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<pre style="margin: 0;">-<span id="LC30" class="line" lang="markdown"></span>
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<pre style="margin: 0;">-<span id="LC31" class="line" lang="markdown">For user support, see the <span class="p">[</span><span class="nv" style="color: #008080;">QIIME 2 Forum</span><span class="p">](</span><span class="sx" style="color: #d14;">https://forum.qiime2.org</span><span class="p">)</span>. Bug reports and feature requests can also be made <span class="p">[</span><span class="nv" style="color: #008080;">via a new issue</span><span class="p">](</span><span class="sx" style="color: #d14;">https://github.com/qiime2/q2-sample-classifier/issues/new/choose</span><span class="p">)</span>.</span>
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<pre style="margin: 0;">-<span id="LC32" class="line" lang="markdown"></span>
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<pre style="margin: 0;">-<span id="LC33" class="line" lang="markdown"><span class="gu" style="color: #800080; font-weight: 600;">## Contributing</span></span>
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<pre style="margin: 0;">-<span id="LC34" class="line" lang="markdown"></span>
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<pre style="margin: 0;">-<span id="LC35" class="line" lang="markdown">QIIME 2 is an open-source project, and we are very interested in contributions from the community. Please see the <span class="p">[</span><span class="nv" style="color: #008080;">contributing guidelines</span><span class="p">](</span><span class="sx" style="color: #d14;">https://github.com/qiime2/q2-sample-classifier/blob/master/.github/CONTRIBUTING.md</span><span class="p">)</span> if you would like to get involved.</span></pre>
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<pre style="margin: 0;">+<span id="LC5" class="line" lang="markdown">This is a QIIME 2 plugin. For details on QIIME 2, see https://qiime2.org.</span></pre>
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<td class="line_content match" style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">\ No newline at end of file</td>
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<a href="https://salsa.debian.org/med-team/q2-sample-classifier/-/commit/7c4b78faf33bc50e958843964685cf5d73d1374d#243f1ef343e8375e9296d24d5fc49b37a3869bcc"><strong>ci/recipe/conda_build_config.yaml</strong>
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1
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<pre style="margin: 0;">-<span id="LC1" class="line" lang="yaml"><span class="na" style="color: #008080;">python</span><span class="pi">:</span></span>
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2
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<pre style="margin: 0;">-<span id="LC2" class="line" lang="yaml"> <span class="pi">-</span> <span class="m" style="color: #099;">3.6</span></span></pre>
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<a href="https://salsa.debian.org/med-team/q2-sample-classifier/-/commit/7c4b78faf33bc50e958843964685cf5d73d1374d#22fbe0b68848772d4b1c45f0d62dcd71a06cde00"><strong>ci/recipe/meta.yaml</strong></a>
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1
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<pre style="margin: 0;"> <span id="LC1" class="line" lang="yaml"><span class="pi">{</span><span class="err" style="color: #a61717; background-color: #e3d2d2;">%</span> <span class="nv" style="color: #008080;">set data = load_setup_py_data() %</span><span class="pi">}</span></span>
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<pre style="margin: 0;"> <span id="LC2" class="line" lang="yaml"><span class="pi">{</span><span class="err" style="color: #a61717; background-color: #e3d2d2;">%</span> <span class="nv" style="color: #008080;">set version = data.get('version') or 'placehold' %</span><span class="pi">}</span></span>
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<pre style="margin: 0;">-<span id="LC3" class="line" lang="yaml"><span class="pi">{</span><span class="err" style="color: #a61717; background-color: #e3d2d2;">%</span> <span class="nv" style="color: #008080;">set release = '.'.join(version.split('.')</span><span class="pi">[:</span><span class="nv" style="color: #008080;">2</span><span class="pi">]</span><span class="nv" style="color: #008080;">) %</span><span class="pi">}</span></span>
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4
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<pre style="margin: 0;"> <span id="LC3" class="line" lang="yaml"></span>
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<pre style="margin: 0;"> <span id="LC4" class="line" lang="yaml"><span class="na" style="color: #008080;">package</span><span class="pi">:</span></span>
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<pre style="margin: 0;"> <span id="LC5" class="line" lang="yaml"> <span class="na" style="color: #008080;">name</span><span class="pi">:</span> <span class="s" style="color: #d14;">q2-sample-classifier</span></span>
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<td class="diff-line-num unfold js-unfold old_line" data-linenumber="19" style="width: 35px; color: rgba(0,0,0,0.3); border-right-width: 1px; border-right-color: #f0f0f0; border-right-style: solid; padding: 0 5px;" align="right" bgcolor="#fafafa">...</td>
<td class="diff-line-num unfold js-unfold new_line" data-linenumber="18" style="width: 35px; color: rgba(0,0,0,0.3); border-right-width: 1px; border-right-color: #f0f0f0; border-right-style: solid; padding: 0 5px;" align="right" bgcolor="#fafafa">...</td>
<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -19,19 +18,27 @@ requirements:</td>
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<pre style="margin: 0;"> <span id="LC18" class="line" lang="yaml"></span>
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<pre style="margin: 0;"> <span id="LC19" class="line" lang="yaml"> <span class="na" style="color: #008080;">run</span><span class="pi">:</span></span>
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<pre style="margin: 0;"> <span id="LC20" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">python {{ python }}</span></span>
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<pre style="margin: 0;">-<span id="LC22" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">pandas <span class="idiff left right">>=1</span></span></span>
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<pre style="margin: 0;">+<span id="LC21" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">pandas <span class="idiff left right">{{ pandas }}</span></span></span>
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<pre style="margin: 0;"> <span id="LC22" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">scipy</span></span>
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<pre style="margin: 0;">+<span id="LC23" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">numpy</span></span>
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<pre style="margin: 0;"> <span id="LC24" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">joblib</span></span>
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<pre style="margin: 0;"> <span id="LC25" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">scikit-learn >=0.22.1</span></span>
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<pre style="margin: 0;"> <span id="LC26" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">scikit-bio</span></span>
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<pre style="margin: 0;"> <span id="LC27" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">seaborn >=0.8</span></span>
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<pre style="margin: 0;"> <span id="LC28" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">fastcluster</span></span>
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<pre style="margin: 0;">-<span id="LC29" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">qiime2 {{ <span class="idiff left right">release</span> }}.*</span></span>
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<pre style="margin: 0;">-<span id="LC30" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">q2-types {{ <span class="idiff left right">release</span> }}.*</span></span>
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<pre style="margin: 0;">-<span id="LC31" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">q2templates {{ <span class="idiff left right">release</span> }}.*</span></span>
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<pre style="margin: 0;">-<span id="LC32" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">q2-feature-table {{ <span class="idiff left right">release</span> }}.*</span></span>
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<pre style="margin: 0;">+<span id="LC29" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">qiime2 {{ <span class="idiff left right">qiime2_epoch</span> }}.*</span></span>
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<pre style="margin: 0;">+<span id="LC30" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">q2-types {{ <span class="idiff left right">qiime2_epoch</span> }}.*</span></span>
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<pre style="margin: 0;">+<span id="LC31" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">q2templates {{ <span class="idiff left right">qiime2_epoch</span> }}.*</span></span>
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<pre style="margin: 0;">+<span id="LC32" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">q2-feature-table {{ <span class="idiff left right">qiime2_epoch</span> }}.*</span></span>
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<pre style="margin: 0;"> <span id="LC33" class="line" lang="yaml"></span>
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<pre style="margin: 0;"> <span id="LC34" class="line" lang="yaml"><span class="na" style="color: #008080;">test</span><span class="pi">:</span></span>
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<pre style="margin: 0;">+<span id="LC35" class="line" lang="yaml"> <span class="na" style="color: #008080;">requires</span><span class="pi">:</span></span>
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<pre style="margin: 0;">+<span id="LC36" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">qiime2 >={{ qiime2 }}</span></span>
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<pre style="margin: 0;">+<span id="LC37" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">q2-types >={{ q2_types }}</span></span>
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<pre style="margin: 0;">+<span id="LC38" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">q2templates >={{ q2templates }}</span></span>
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<pre style="margin: 0;">+<span id="LC39" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">q2-feature-table >={{ q2_feature_table }}</span></span>
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<pre style="margin: 0;">+<span id="LC40" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">pytest</span></span>
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<pre style="margin: 0;">+<span id="LC41" class="line" lang="yaml"></span>
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<pre style="margin: 0;"> <span id="LC42" class="line" lang="yaml"> <span class="na" style="color: #008080;">imports</span><span class="pi">:</span></span>
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<pre style="margin: 0;"> <span id="LC43" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">q2_sample_classifier</span></span>
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<pre style="margin: 0;"> <span id="LC44" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">qiime2.plugins.sample_classifier</span></span>
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<a href="https://salsa.debian.org/med-team/q2-sample-classifier/-/commit/7c4b78faf33bc50e958843964685cf5d73d1374d#4dcec7b702b20e60f6249e2b7dea2024d22592ce"><strong>q2_sample_classifier/__init__.py</strong></a>
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<pre style="margin: 0;"> <span id="LC1" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># ----------------------------------------------------------------------------</span></span>
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<pre style="margin: 0;">-<span id="LC2" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Copyright (c) 2017-202<span class="idiff left right">0</span>, QIIME 2 development team.</span></span>
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<pre style="margin: 0;">+<span id="LC2" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Copyright (c) 2017-202<span class="idiff left right">1</span>, QIIME 2 development team.</span></span>
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<pre style="margin: 0;"> <span id="LC3" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;">#</span></span>
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<pre style="margin: 0;"> <span id="LC4" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Distributed under the terms of the Modified BSD License.</span></span>
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<pre style="margin: 0;"> <span id="LC5" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;">#</span></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -10,10 +10,11 @@ from ._format import (</td>
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<pre style="margin: 0;"> <span id="LC10" class="line" lang="python"> <span class="n" style="color: #333;">BooleanSeriesFormat</span><span class="p">,</span> <span class="n" style="color: #333;">BooleanSeriesDirectoryFormat</span><span class="p">,</span></span>
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11
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<pre style="margin: 0;"> <span id="LC11" class="line" lang="python"> <span class="n" style="color: #333;">PredictionsFormat</span><span class="p">,</span> <span class="n" style="color: #333;">PredictionsDirectoryFormat</span><span class="p">,</span> <span class="n" style="color: #333;">ImportanceFormat</span><span class="p">,</span></span>
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<pre style="margin: 0;"> <span id="LC12" class="line" lang="python"> <span class="n" style="color: #333;">ImportanceDirectoryFormat</span><span class="p">,</span> <span class="n" style="color: #333;">SampleEstimatorDirFmt</span><span class="p">,</span> <span class="n" style="color: #333;">PickleFormat</span><span class="p">,</span></span>
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<pre style="margin: 0;">-<span id="LC13" class="line" lang="python"> <span class="n" style="color: #333;">ProbabilitiesFormat</span><span class="p">,</span> <span class="n" style="color: #333;">ProbabilitiesDirectoryFormat</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC13" class="line" lang="python"> <span class="n" style="color: #333;">ProbabilitiesFormat</span><span class="p">,</span> <span class="n" style="color: #333;">ProbabilitiesDirectoryFormat</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC14" class="line" lang="python"> <span class="n" style="color: #333;">TrueTargetsDirectoryFormat</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC15" class="line" lang="python"><span class="kn" style="font-weight: 600;">from</span> <span class="nn" style="color: #555;">._type</span> <span class="kn" style="font-weight: 600;">import</span> <span class="p">(</span><span class="n" style="color: #333;">BooleanSeries</span><span class="p">,</span> <span class="n" style="color: #333;">ClassifierPredictions</span><span class="p">,</span> <span class="n" style="color: #333;">RegressorPredictions</span><span class="p">,</span></span>
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<pre style="margin: 0;"> <span id="LC16" class="line" lang="python"> <span class="n" style="color: #333;">Importance</span><span class="p">,</span> <span class="n" style="color: #333;">SampleEstimator</span><span class="p">,</span> <span class="n" style="color: #333;">Classifier</span><span class="p">,</span> <span class="n" style="color: #333;">Regressor</span><span class="p">,</span></span>
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<pre style="margin: 0;">-<span id="LC16" class="line" lang="python"> <span class="n" style="color: #333;">Probabilities</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC17" class="line" lang="python"> <span class="n" style="color: #333;">Probabilities</span><span class="p"><span class="idiff left">,</span></span><span class="idiff"> </span><span class="n" style="color: #333;"><span class="idiff right">TrueTargets</span></span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC18" class="line" lang="python"><span class="kn" style="font-weight: 600;">from</span> <span class="nn" style="color: #555;">._version</span> <span class="kn" style="font-weight: 600;">import</span> <span class="n" style="color: #333;">get_versions</span></span>
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<pre style="margin: 0;"> <span id="LC19" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC20" class="line" lang="python"></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -26,4 +27,5 @@ __all__ = ['BooleanSeriesFormat', 'BooleanSeriesDirectoryFormat',</td>
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<pre style="margin: 0;"> <span id="LC27" class="line" lang="python"> <span class="s" style="color: #d14;">'SampleEstimatorDirFmt'</span><span class="p">,</span> <span class="s" style="color: #d14;">'PickleFormat'</span><span class="p">,</span> <span class="s" style="color: #d14;">'BooleanSeries'</span><span class="p">,</span></span>
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<pre style="margin: 0;"> <span id="LC28" class="line" lang="python"> <span class="s" style="color: #d14;">'ClassifierPredictions'</span><span class="p">,</span> <span class="s" style="color: #d14;">'RegressorPredictions'</span><span class="p">,</span> <span class="s" style="color: #d14;">'Importance'</span><span class="p">,</span></span>
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<pre style="margin: 0;"> <span id="LC29" class="line" lang="python"> <span class="s" style="color: #d14;">'Classifier'</span><span class="p">,</span> <span class="s" style="color: #d14;">'Regressor'</span><span class="p">,</span> <span class="s" style="color: #d14;">'SampleEstimator'</span><span class="p">,</span> <span class="s" style="color: #d14;">'Probabilities'</span><span class="p">,</span></span>
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<pre style="margin: 0;">-<span id="LC29" class="line" lang="python"> <span class="s" style="color: #d14;">'ProbabilitiesFormat'</span><span class="p">,</span> <span class="s" style="color: #d14;">'ProbabilitiesDirectoryFormat'</span><span class="p">]</span></span></pre>
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<pre style="margin: 0;">+<span id="LC30" class="line" lang="python"> <span class="s" style="color: #d14;">'ProbabilitiesFormat'</span><span class="p">,</span> <span class="s" style="color: #d14;">'ProbabilitiesDirectoryFormat'</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC31" class="line" lang="python"> <span class="s" style="color: #d14;">'TrueTargets'</span><span class="p">,</span> <span class="s" style="color: #d14;">'TrueTargetsDirectoryFormat'</span><span class="p">]</span></span></pre>
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<pre style="margin: 0;"> <span id="LC1" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># ----------------------------------------------------------------------------</span></span>
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<pre style="margin: 0;">-<span id="LC2" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Copyright (c) 2017-202<span class="idiff left right">0</span>, QIIME 2 development team.</span></span>
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<pre style="margin: 0;">+<span id="LC2" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Copyright (c) 2017-202<span class="idiff left right">1</span>, QIIME 2 development team.</span></span>
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<pre style="margin: 0;"> <span id="LC3" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;">#</span></span>
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<pre style="margin: 0;"> <span id="LC4" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Distributed under the terms of the Modified BSD License.</span></span>
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<pre style="margin: 0;"> <span id="LC5" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;">#</span></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -176,3 +176,8 @@ class ProbabilitiesFormat(_MultiColumnNumericFormat):</td>
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<pre style="margin: 0;"> <span id="LC176" class="line" lang="python"><span class="n" style="color: #333;">ProbabilitiesDirectoryFormat</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">model</span><span class="p">.</span><span class="n" style="color: #333;">SingleFileDirectoryFormat</span><span class="p">(</span></span>
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<pre style="margin: 0;"> <span id="LC177" class="line" lang="python"> <span class="s" style="color: #d14;">'ProbabilitiesDirectoryFormat'</span><span class="p">,</span> <span class="s" style="color: #d14;">'class_probabilities.tsv'</span><span class="p">,</span></span>
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<pre style="margin: 0;"> <span id="LC178" class="line" lang="python"> <span class="n" style="color: #333;">ProbabilitiesFormat</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC180" class="line" lang="python"></span>
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<pre style="margin: 0;">+<span id="LC181" class="line" lang="python"><span class="n" style="color: #333;">TrueTargetsDirectoryFormat</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">model</span><span class="p">.</span><span class="n" style="color: #333;">SingleFileDirectoryFormat</span><span class="p">(</span></span>
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<pre style="margin: 0;">+<span id="LC182" class="line" lang="python"> <span class="s" style="color: #d14;">'TrueTargetsDirectoryFormat'</span><span class="p">,</span> <span class="s" style="color: #d14;">'true_targets.tsv'</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC183" class="line" lang="python"> <span class="n" style="color: #333;">PredictionsFormat</span><span class="p">)</span></span></pre>
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<pre style="margin: 0;"> <span id="LC1" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># ----------------------------------------------------------------------------</span></span>
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<pre style="margin: 0;">-<span id="LC2" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Copyright (c) 2017-202<span class="idiff left right">0</span>, QIIME 2 development team.</span></span>
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<pre style="margin: 0;">+<span id="LC2" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Copyright (c) 2017-202<span class="idiff left right">1</span>, QIIME 2 development team.</span></span>
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<pre style="margin: 0;"> <span id="LC3" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;">#</span></span>
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<pre style="margin: 0;"> <span id="LC4" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Distributed under the terms of the Modified BSD License.</span></span>
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<pre style="margin: 0;"> <span id="LC5" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;">#</span></span>
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<pre style="margin: 0;"> <span id="LC1" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># ----------------------------------------------------------------------------</span></span>
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<pre style="margin: 0;">-<span id="LC2" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Copyright (c) 2017-202<span class="idiff left right">0</span>, QIIME 2 development team.</span></span>
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<pre style="margin: 0;">+<span id="LC2" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Copyright (c) 2017-202<span class="idiff left right">1</span>, QIIME 2 development team.</span></span>
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<pre style="margin: 0;"> <span id="LC3" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;">#</span></span>
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<pre style="margin: 0;"> <span id="LC4" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Distributed under the terms of the Modified BSD License.</span></span>
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<pre style="margin: 0;"> <span id="LC5" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;">#</span></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -26,3 +26,5 @@ Importance = SemanticType(</td>
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<pre style="margin: 0;"> <span id="LC26" class="line" lang="python"> <span class="s" style="color: #d14;">'Importance'</span><span class="p">,</span> <span class="n" style="color: #333;">variant_of</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">FeatureData</span><span class="p">.</span><span class="n" style="color: #333;">field</span><span class="p">[</span><span class="s" style="color: #d14;">'type'</span><span class="p">])</span></span>
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<pre style="margin: 0;"> <span id="LC27" class="line" lang="python"><span class="n" style="color: #333;">Probabilities</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">SemanticType</span><span class="p">(</span></span>
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<pre style="margin: 0;"> <span id="LC28" class="line" lang="python"> <span class="s" style="color: #d14;">'Probabilities'</span><span class="p">,</span> <span class="n" style="color: #333;">variant_of</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">SampleData</span><span class="p">.</span><span class="n" style="color: #333;">field</span><span class="p">[</span><span class="s" style="color: #d14;">'type'</span><span class="p">])</span></span>
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<pre style="margin: 0;">+<span id="LC29" class="line" lang="python"><span class="n" style="color: #333;">TrueTargets</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">SemanticType</span><span class="p">(</span></span>
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<pre style="margin: 0;">+<span id="LC30" class="line" lang="python"> <span class="s" style="color: #d14;">'TrueTargets'</span><span class="p">,</span> <span class="n" style="color: #333;">variant_of</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">SampleData</span><span class="p">.</span><span class="n" style="color: #333;">field</span><span class="p">[</span><span class="s" style="color: #d14;">'type'</span><span class="p">])</span></span></pre>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -23,9 +23,9 @@ def get_keywords():</td>
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<pre style="margin: 0;"> <span id="LC23" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># setup.py/versioneer.py will grep for the variable names, so they must</span></span>
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<pre style="margin: 0;"> <span id="LC24" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># each be defined on a line of their own. _version.py will just call</span></span>
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<pre style="margin: 0;"> <span id="LC25" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># get_keywords().</span></span>
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<pre style="margin: 0;">-<span id="LC26" class="line" lang="python"> <span class="n" style="color: #333;">git_refnames</span> <span class="o" style="font-weight: 600;">=</span> <span class="s" style="color: #d14;">" (<span class="idiff left">HEAD -> master, </span>tag: 202<span class="idiff right">0.11.1</span>)"</span></span>
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<pre style="margin: 0;">-<span id="LC27" class="line" lang="python"> <span class="n" style="color: #333;">git_full</span> <span class="o" style="font-weight: 600;">=</span> <span class="s" style="color: #d14;">"<span class="idiff left right">392e5454b7cb6a91d43968d62178fb6a216e193f</span>"</span></span>
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<pre style="margin: 0;">-<span id="LC28" class="line" lang="python"> <span class="n" style="color: #333;">git_date</span> <span class="o" style="font-weight: 600;">=</span> <span class="s" style="color: #d14;">"202<span class="idiff left right">0-12-05 20:44:51</span> +0000"</span></span>
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<pre style="margin: 0;">+<span id="LC26" class="line" lang="python"> <span class="n" style="color: #333;">git_refnames</span> <span class="o" style="font-weight: 600;">=</span> <span class="s" style="color: #d14;">" (tag: 202<span class="idiff left right">1.8.0</span>)"</span></span>
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<pre style="margin: 0;">+<span id="LC27" class="line" lang="python"> <span class="n" style="color: #333;">git_full</span> <span class="o" style="font-weight: 600;">=</span> <span class="s" style="color: #d14;">"<span class="idiff left right">916eb0799fa2c95a04766b44c22335c6a097ce13</span>"</span></span>
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<pre style="margin: 0;">+<span id="LC28" class="line" lang="python"> <span class="n" style="color: #333;">git_date</span> <span class="o" style="font-weight: 600;">=</span> <span class="s" style="color: #d14;">"202<span class="idiff left right">1-09-09 18:35:33</span> +0000"</span></span>
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<pre style="margin: 0;"> <span id="LC29" class="line" lang="python"> <span class="n" style="color: #333;">keywords</span> <span class="o" style="font-weight: 600;">=</span> <span class="p">{</span><span class="s" style="color: #d14;">"refnames"</span><span class="p">:</span> <span class="n" style="color: #333;">git_refnames</span><span class="p">,</span> <span class="s" style="color: #d14;">"full"</span><span class="p">:</span> <span class="n" style="color: #333;">git_full</span><span class="p">,</span> <span class="s" style="color: #d14;">"date"</span><span class="p">:</span> <span class="n" style="color: #333;">git_date</span><span class="p">}</span></span>
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<pre style="margin: 0;"> <span id="LC30" class="line" lang="python"> <span class="k" style="font-weight: 600;">return</span> <span class="n" style="color: #333;">keywords</span></span>
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<pre style="margin: 0;">+<span id="LC9" class="line" lang="html">{% if warning_msg %}</span>
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<pre style="margin: 0;">+<span id="LC10" class="line" lang="html"><span class="nt" style="color: #000080;"><div</span> <span class="na" style="color: #008080;">class=</span><span class="s" style="color: #d14;">"panel-group"</span> <span class="na" style="color: #008080;">id=</span><span class="s" style="color: #d14;">"warnings"</span> <span class="na" style="color: #008080;">role=</span><span class="s" style="color: #d14;">"tablist"</span> <span class="na" style="color: #008080;">aria-multiselectable=</span><span class="s" style="color: #d14;">"true"</span><span class="nt" style="color: #000080;">></span></span>
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<pre style="margin: 0;">+<span id="LC13" class="line" lang="html"> <span class="nt" style="color: #000080;"><h4</span> <span class="na" style="color: #008080;">class=</span><span class="s" style="color: #d14;">"panel-title"</span><span class="nt" style="color: #000080;">></span></span>
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<pre style="margin: 0;">+<span id="LC14" class="line" lang="html"> <span class="nt" style="color: #000080;"><a</span> <span class="na" style="color: #008080;">role=</span><span class="s" style="color: #d14;">"button"</span> <span class="na" style="color: #008080;">data-toggle=</span><span class="s" style="color: #d14;">"collapse"</span> <span class="na" style="color: #008080;">data-parent=</span><span class="s" style="color: #d14;">"#warnings"</span> <span class="na" style="color: #008080;">href=</span><span class="s" style="color: #d14;">"#warnings-list"</span> <span class="na" style="color: #008080;">aria-expanded=</span><span class="s" style="color: #d14;">"true"</span> <span class="na" style="color: #008080;">aria-controls=</span><span class="s" style="color: #d14;">"warnings-list"</span><span class="nt" style="color: #000080;">></span></span>
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<pre style="margin: 0;">+<span id="LC15" class="line" lang="html"> Warnings (click here to collapse/expand):</span>
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<pre style="margin: 0;">+<span id="LC19" class="line" lang="html"> <span class="nt" style="color: #000080;"><div</span> <span class="na" style="color: #008080;">id=</span><span class="s" style="color: #d14;">"warnings-list"</span> <span class="na" style="color: #008080;">class=</span><span class="s" style="color: #d14;">"panel-collapse collapse in"</span> <span class="na" style="color: #008080;">role=</span><span class="s" style="color: #d14;">"tabpanel"</span> <span class="na" style="color: #008080;">aria-labelledby=</span><span class="s" style="color: #d14;">"warnings-heading"</span><span class="nt" style="color: #000080;">></span></span>
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<pre style="margin: 0;">+<span id="LC20" class="line" lang="html"> <span class="nt" style="color: #000080;"><div</span> <span class="na" style="color: #008080;">class=</span><span class="s" style="color: #d14;">"alert alert-warning col-md-12"</span><span class="nt" style="color: #000080;">></span></span>
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<pre style="margin: 0;">+<span id="LC21" class="line" lang="html"> <span class="nt" style="color: #000080;"><p><strong></span>{{ warning_msg }}<span class="nt" style="color: #000080;"></strong></p></span></span>
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<pre style="margin: 0;">+<span id="LC26" class="line" lang="html">{% endif %}</span>
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<pre style="margin: 0;"> <span id="LC28" class="line" lang="html"><span class="nt" style="color: #000080;"><div</span> <span class="na" style="color: #008080;">class=</span><span class="s" style="color: #d14;">"row"</span><span class="nt" style="color: #000080;">></span></span>
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<pre style="margin: 0;"> <span id="LC29" class="line" lang="html"> {% if predictions %}</span>
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<pre style="margin: 0;"> <span id="LC30" class="line" lang="html"> <span class="nt" style="color: #000080;"><h1></span>Model Accuracy<span class="nt" style="color: #000080;"></h1></span></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -65,6 +84,9 @@</td>
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<pre style="margin: 0;"> <span id="LC84" class="line" lang="html"> <span class="nt" style="color: #000080;"><br></span></span>
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<pre style="margin: 0;"> <span id="LC85" class="line" lang="html"> <span class="nt" style="color: #000080;"><p></span>Download as PDF<span class="nt" style="color: #000080;"></p></span></span>
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<pre style="margin: 0;"> <span id="LC86" class="line" lang="html"> <span class="nt" style="color: #000080;"></a></span></span>
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<pre style="margin: 0;">+<span id="LC87" class="line" lang="html"> <span class="nt" style="color: #000080;"><a</span> <span class="na" style="color: #008080;">href=</span><span class="s" style="color: #d14;">"rfe_scores.tsv"</span><span class="nt" style="color: #000080;">></span></span>
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88
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<pre style="margin: 0;">+<span id="LC88" class="line" lang="html"> <span class="nt" style="color: #000080;"><p></span>Download as TSV<span class="nt" style="color: #000080;"></p></span></span>
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<pre style="margin: 0;"> <span id="LC91" class="line" lang="html"> {% endif %}</span>
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<pre style="margin: 0;"> <span id="LC92" class="line" lang="html"> {% if result %}</span>
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<a href="https://salsa.debian.org/med-team/q2-sample-classifier/-/commit/7c4b78faf33bc50e958843964685cf5d73d1374d#7cc5deec9c3ee7ce9ba719cb8f4de3aed956b0b0"><strong>q2_sample_classifier/classify.py</strong></a>
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<pre style="margin: 0;"> <span id="LC1" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># ----------------------------------------------------------------------------</span></span>
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<pre style="margin: 0;">-<span id="LC2" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Copyright (c) 2017-202<span class="idiff left right">0</span>, QIIME 2 development team.</span></span>
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<pre style="margin: 0;">+<span id="LC2" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Copyright (c) 2017-202<span class="idiff left right">1</span>, QIIME 2 development team.</span></span>
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<pre style="margin: 0;"> <span id="LC3" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;">#</span></span>
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<pre style="margin: 0;"> <span id="LC4" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Distributed under the terms of the Modified BSD License.</span></span>
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<pre style="margin: 0;"> <span id="LC5" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;">#</span></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -163,8 +163,10 @@ def classify_samples(ctx,</td>
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<pre style="margin: 0;"> <span id="LC163" class="line" lang="python"> <span class="n" style="color: #333;">confusion</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">ctx</span><span class="p">.</span><span class="n" style="color: #333;">get_action</span><span class="p">(</span><span class="s" style="color: #d14;">'sample_classifier'</span><span class="p">,</span> <span class="s" style="color: #d14;">'confusion_matrix'</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC164" class="line" lang="python"> <span class="n" style="color: #333;">heat</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">ctx</span><span class="p">.</span><span class="n" style="color: #333;">get_action</span><span class="p">(</span><span class="s" style="color: #d14;">'sample_classifier'</span><span class="p">,</span> <span class="s" style="color: #d14;">'heatmap'</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC165" class="line" lang="python"></span>
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<pre style="margin: 0;">-<span id="LC166" class="line" lang="python"> <span class="n" style="color: #333;">X_train</span><span class="p">,</span> <span class="n" style="color: #333;">X_test</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">split</span><span class="p">(</span><span class="n" style="color: #333;">table</span><span class="p">,</span> <span class="n" style="color: #333;">metadata</span><span class="p">,</span> <span class="n" style="color: #333;">test_size</span><span class="p">,</span> <span class="n" style="color: #333;">random_state</span><span class="p">,</span></span>
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<pre style="margin: 0;">-<span id="LC167" class="line" lang="python"> <span class="n" style="color: #333;">stratify</span><span class="o" style="font-weight: 600;">=</span><span class="bp" style="color: #999;">True</span><span class="p">,</span> <span class="n" style="color: #333;">missing_samples</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">missing_samples</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC166" class="line" lang="python"> <span class="n" style="color: #333;">X_train</span><span class="p">,</span> <span class="n" style="color: #333;">X_test</span><span class="p">,</span> <span class="n" style="color: #333;">y_train</span><span class="p">,</span> <span class="n" style="color: #333;">y_test</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">split</span><span class="p">(</span><span class="n" style="color: #333;">table</span><span class="p">,</span> <span class="n" style="color: #333;">metadata</span><span class="p">,</span> <span class="n" style="color: #333;">test_size</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC167" class="line" lang="python"> <span class="n" style="color: #333;">random_state</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC168" class="line" lang="python"> <span class="n" style="color: #333;">stratify</span><span class="o" style="font-weight: 600;">=</span><span class="bp" style="color: #999;">True</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC169" class="line" lang="python"> <span class="n" style="color: #333;">missing_samples</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">missing_samples</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC170" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC171" class="line" lang="python"> <span class="n" style="color: #333;">sample_estimator</span><span class="p">,</span> <span class="n" style="color: #333;">importance</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">fit</span><span class="p">(</span></span>
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<pre style="margin: 0;"> <span id="LC172" class="line" lang="python"> <span class="n" style="color: #333;">X_train</span><span class="p">,</span> <span class="n" style="color: #333;">metadata</span><span class="p">,</span> <span class="n" style="color: #333;">step</span><span class="p">,</span> <span class="n" style="color: #333;">cv</span><span class="p">,</span> <span class="n" style="color: #333;">random_state</span><span class="p">,</span> <span class="n" style="color: #333;">n_jobs</span><span class="p">,</span> <span class="n" style="color: #333;">n_estimators</span><span class="p">,</span></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -183,7 +185,7 @@ def classify_samples(ctx,</td>
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<pre style="margin: 0;"> <span id="LC185" class="line" lang="python"> <span class="n" style="color: #333;">group_samples</span><span class="o" style="font-weight: 600;">=</span><span class="bp" style="color: #999;">True</span><span class="p">,</span> <span class="n" style="color: #333;">missing_samples</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">missing_samples</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC186" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC187" class="line" lang="python"> <span class="k" style="font-weight: 600;">return</span> <span class="p">(</span><span class="n" style="color: #333;">sample_estimator</span><span class="p">,</span> <span class="n" style="color: #333;">importance</span><span class="p">,</span> <span class="n" style="color: #333;">predictions</span><span class="p">,</span> <span class="n" style="color: #333;">summary</span><span class="p">,</span></span>
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<pre style="margin: 0;">-<span id="LC186" class="line" lang="python"> <span class="n" style="color: #333;">accuracy_results</span><span class="p">,</span> <span class="n" style="color: #333;">probabilities</span><span class="p">,</span> <span class="n" style="color: #333;">_heatmap</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC188" class="line" lang="python"> <span class="n" style="color: #333;">accuracy_results</span><span class="p">,</span> <span class="n" style="color: #333;">probabilities</span><span class="p">,</span> <span class="n" style="color: #333;">_heatmap</span><span class="p"><span class="idiff left">,</span></span><span class="idiff"> </span><span class="n" style="color: #333;"><span class="idiff">y_train</span></span><span class="p"><span class="idiff">,</span></span><span class="idiff"> </span><span class="n" style="color: #333;"><span class="idiff right">y_test</span></span><span class="p">)</span></span>
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189
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<pre style="margin: 0;"> <span id="LC189" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC190" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC191" class="line" lang="python"><span class="k" style="font-weight: 600;">def</span> <span class="nf" style="color: #900; font-weight: 600;">regress_samples</span><span class="p">(</span><span class="n" style="color: #333;">ctx</span><span class="p">,</span></span>
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<td class="diff-line-num unfold js-unfold old_line" data-linenumber="207" style="width: 35px; color: rgba(0,0,0,0.3); border-right-width: 1px; border-right-color: #f0f0f0; border-right-style: solid; padding: 0 5px;" align="right" bgcolor="#fafafa">...</td>
<td class="diff-line-num unfold js-unfold new_line" data-linenumber="209" style="width: 35px; color: rgba(0,0,0,0.3); border-right-width: 1px; border-right-color: #f0f0f0; border-right-style: solid; padding: 0 5px;" align="right" bgcolor="#fafafa">...</td>
<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -207,8 +209,10 @@ def regress_samples(ctx,</td>
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<pre style="margin: 0;"> <span id="LC209" class="line" lang="python"> <span class="n" style="color: #333;">summarize_estimator</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">ctx</span><span class="p">.</span><span class="n" style="color: #333;">get_action</span><span class="p">(</span><span class="s" style="color: #d14;">'sample_classifier'</span><span class="p">,</span> <span class="s" style="color: #d14;">'summarize'</span><span class="p">)</span></span>
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210
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<pre style="margin: 0;"> <span id="LC210" class="line" lang="python"> <span class="n" style="color: #333;">scatter</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">ctx</span><span class="p">.</span><span class="n" style="color: #333;">get_action</span><span class="p">(</span><span class="s" style="color: #d14;">'sample_classifier'</span><span class="p">,</span> <span class="s" style="color: #d14;">'scatterplot'</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC211" class="line" lang="python"></span>
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<pre style="margin: 0;">-<span id="LC210" class="line" lang="python"> <span class="n" style="color: #333;">X_train</span><span class="p">,</span> <span class="n" style="color: #333;">X_test</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">split</span><span class="p">(</span><span class="n" style="color: #333;">table</span><span class="p">,</span> <span class="n" style="color: #333;">metadata</span><span class="p">,</span> <span class="n" style="color: #333;">test_size</span><span class="p">,</span> <span class="n" style="color: #333;">random_state</span><span class="p">,</span></span>
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<pre style="margin: 0;">-<span id="LC211" class="line" lang="python"> <span class="n" style="color: #333;">stratify</span><span class="p">,</span> <span class="n" style="color: #333;">missing_samples</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">missing_samples</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC212" class="line" lang="python"> <span class="n" style="color: #333;">X_train</span><span class="p">,</span> <span class="n" style="color: #333;">X_test</span><span class="p">,</span> <span class="n" style="color: #333;">y_train</span><span class="p">,</span> <span class="n" style="color: #333;">y_test</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">split</span><span class="p">(</span><span class="n" style="color: #333;">table</span><span class="p">,</span> <span class="n" style="color: #333;">metadata</span><span class="p">,</span> <span class="n" style="color: #333;">test_size</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC213" class="line" lang="python"> <span class="n" style="color: #333;">random_state</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC214" class="line" lang="python"> <span class="n" style="color: #333;">stratify</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC215" class="line" lang="python"> <span class="n" style="color: #333;">missing_samples</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">missing_samples</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC216" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC217" class="line" lang="python"> <span class="n" style="color: #333;">sample_estimator</span><span class="p">,</span> <span class="n" style="color: #333;">importance</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">fit</span><span class="p">(</span></span>
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<pre style="margin: 0;"> <span id="LC218" class="line" lang="python"> <span class="n" style="color: #333;">X_train</span><span class="p">,</span> <span class="n" style="color: #333;">metadata</span><span class="p">,</span> <span class="n" style="color: #333;">step</span><span class="p">,</span> <span class="n" style="color: #333;">cv</span><span class="p">,</span> <span class="n" style="color: #333;">random_state</span><span class="p">,</span> <span class="n" style="color: #333;">n_jobs</span><span class="p">,</span> <span class="n" style="color: #333;">n_estimators</span><span class="p">,</span></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -303,15 +307,12 @@ def split_table(table: biom.Table, metadata: qiime2.MetadataColumn,</td>
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<pre style="margin: 0;"> <span id="LC307" class="line" lang="python"> <span class="n" style="color: #333;">test_size</span><span class="p">:</span> <span class="nb" style="color: #0086b3;">float</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">defaults</span><span class="p">[</span><span class="s" style="color: #d14;">'test_size'</span><span class="p">],</span></span>
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<pre style="margin: 0;"> <span id="LC308" class="line" lang="python"> <span class="n" style="color: #333;">random_state</span><span class="p">:</span> <span class="nb" style="color: #0086b3;">int</span> <span class="o" style="font-weight: 600;">=</span> <span class="bp" style="color: #999;">None</span><span class="p">,</span> <span class="n" style="color: #333;">stratify</span><span class="p">:</span> <span class="nb" style="color: #0086b3;">str</span> <span class="o" style="font-weight: 600;">=</span> <span class="bp" style="color: #999;">True</span><span class="p">,</span></span>
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<pre style="margin: 0;"> <span id="LC309" class="line" lang="python"> <span class="n" style="color: #333;">missing_samples</span><span class="p">:</span> <span class="nb" style="color: #0086b3;">str</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">defaults</span><span class="p">[</span><span class="s" style="color: #d14;">'missing_samples'</span><span class="p">]</span></span>
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<pre style="margin: 0;">-<span id="LC306" class="line" lang="python"> <span class="p">)</span> <span class="o" style="font-weight: 600;">-></span> <span class="p">(</span><span class="n" style="color: #333;">biom</span><span class="p">.</span><span class="n" style="color: #333;">Table</span><span class="p">,</span> <span class="n" style="color: #333;">biom</span><span class="p">.</span><span class="n" style="color: #333;">Table</span><span class="p">):</span></span>
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<pre style="margin: 0;">+<span id="LC310" class="line" lang="python"> <span class="p">)</span> <span class="o" style="font-weight: 600;">-></span> <span class="p">(</span><span class="n" style="color: #333;">biom</span><span class="p">.</span><span class="n" style="color: #333;">Table</span><span class="p">,</span> <span class="n" style="color: #333;">biom</span><span class="p">.</span><span class="n" style="color: #333;">Table</span><span class="p"><span class="idiff left">,</span></span><span class="idiff"> </span><span class="n" style="color: #333;"><span class="idiff">pd</span></span><span class="p"><span class="idiff">.</span></span><span class="n" style="color: #333;"><span class="idiff">Series</span></span><span class="p"><span class="idiff">,</span></span><span class="idiff"> </span><span class="n" style="color: #333;"><span class="idiff">pd</span></span><span class="p"><span class="idiff">.</span></span><span class="n" style="color: #333;"><span class="idiff right">Series</span></span><span class="p">):</span></span>
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<pre style="margin: 0;"> <span id="LC311" class="line" lang="python"> <span class="n" style="color: #333;">column</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">metadata</span><span class="p">.</span><span class="n" style="color: #333;">name</span></span>
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<pre style="margin: 0;"> <span id="LC312" class="line" lang="python"> <span class="n" style="color: #333;">X_train</span><span class="p">,</span> <span class="n" style="color: #333;">X_test</span><span class="p">,</span> <span class="n" style="color: #333;">y_train</span><span class="p">,</span> <span class="n" style="color: #333;">y_test</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">_prepare_training_data</span><span class="p">(</span></span>
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<pre style="margin: 0;"> <span id="LC313" class="line" lang="python"> <span class="n" style="color: #333;">table</span><span class="p">,</span> <span class="n" style="color: #333;">metadata</span><span class="p">,</span> <span class="n" style="color: #333;">column</span><span class="p">,</span> <span class="n" style="color: #333;">test_size</span><span class="p">,</span> <span class="n" style="color: #333;">random_state</span><span class="p">,</span> <span class="n" style="color: #333;">load_data</span><span class="o" style="font-weight: 600;">=</span><span class="bp" style="color: #999;">True</span><span class="p">,</span></span>
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<pre style="margin: 0;"> <span id="LC314" class="line" lang="python"> <span class="n" style="color: #333;">stratify</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">stratify</span><span class="p">,</span> <span class="n" style="color: #333;">missing_samples</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">missing_samples</span><span class="p">)</span></span>
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<pre style="margin: 0;">-<span id="LC311" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># TODO: we can consider returning the metadata (y_train, y_test) if a</span></span>
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<pre style="margin: 0;">-<span id="LC312" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># SampleData[Metadata] type comes into existence. For now we will just</span></span>
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<pre style="margin: 0;">-<span id="LC313" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># throw this out.</span></span>
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<pre style="margin: 0;">-<span id="LC314" class="line" lang="python"> <span class="k" style="font-weight: 600;">return</span> <span class="n" style="color: #333;">X_train</span><span class="p">,</span> <span class="n" style="color: #333;">X_test</span></span>
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<pre style="margin: 0;">+<span id="LC315" class="line" lang="python"> <span class="k" style="font-weight: 600;">return</span> <span class="n" style="color: #333;">X_train</span><span class="p">,</span> <span class="n" style="color: #333;">X_test</span><span class="p">,</span> <span class="n" style="color: #333;">y_train</span><span class="p">,</span> <span class="n" style="color: #333;">y_test</span></span>
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<pre style="margin: 0;"> <span id="LC316" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC317" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC318" class="line" lang="python"><span class="k" style="font-weight: 600;">def</span> <span class="nf" style="color: #900; font-weight: 600;">regress_samples_ncv</span><span class="p">(</span></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -366,6 +367,7 @@ def confusion_matrix(output_dir: str,</td>
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<pre style="margin: 0;"> <span id="LC367" class="line" lang="python"> <span class="n" style="color: #333;">missing_samples</span><span class="p">:</span> <span class="nb" style="color: #0086b3;">str</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">defaults</span><span class="p">[</span><span class="s" style="color: #d14;">'missing_samples'</span><span class="p">],</span></span>
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<pre style="margin: 0;"> <span id="LC368" class="line" lang="python"> <span class="n" style="color: #333;">vmin</span><span class="p">:</span> <span class="nb" style="color: #0086b3;">int</span> <span class="o" style="font-weight: 600;">=</span> <span class="s" style="color: #d14;">'auto'</span><span class="p">,</span> <span class="n" style="color: #333;">vmax</span><span class="p">:</span> <span class="nb" style="color: #0086b3;">int</span> <span class="o" style="font-weight: 600;">=</span> <span class="s" style="color: #d14;">'auto'</span><span class="p">,</span></span>
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<pre style="margin: 0;"> <span id="LC369" class="line" lang="python"> <span class="n" style="color: #333;">palette</span><span class="p">:</span> <span class="nb" style="color: #0086b3;">str</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">defaults</span><span class="p">[</span><span class="s" style="color: #d14;">'palette'</span><span class="p">])</span> <span class="o" style="font-weight: 600;">-></span> <span class="bp" style="color: #999;">None</span><span class="p">:</span></span>
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<pre style="margin: 0;">+<span id="LC370" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC371" class="line" lang="python"> <span class="k" style="font-weight: 600;">if</span> <span class="n" style="color: #333;">vmin</span> <span class="o" style="font-weight: 600;">==</span> <span class="s" style="color: #d14;">'auto'</span><span class="p">:</span></span>
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<pre style="margin: 0;"> <span id="LC372" class="line" lang="python"> <span class="n" style="color: #333;">vmin</span> <span class="o" style="font-weight: 600;">=</span> <span class="bp" style="color: #999;">None</span></span>
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<pre style="margin: 0;"> <span id="LC373" class="line" lang="python"> <span class="k" style="font-weight: 600;">if</span> <span class="n" style="color: #333;">vmax</span> <span class="o" style="font-weight: 600;">==</span> <span class="s" style="color: #d14;">'auto'</span><span class="p">:</span></span>
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<pre style="margin: 0;"> <span id="LC1" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># ----------------------------------------------------------------------------</span></span>
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<pre style="margin: 0;">-<span id="LC2" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Copyright (c) 2017-202<span class="idiff left right">0</span>, QIIME 2 development team.</span></span>
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<pre style="margin: 0;">+<span id="LC2" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Copyright (c) 2017-202<span class="idiff left right">1</span>, QIIME 2 development team.</span></span>
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<pre style="margin: 0;"> <span id="LC3" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;">#</span></span>
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<pre style="margin: 0;"> <span id="LC4" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Distributed under the terms of the Modified BSD License.</span></span>
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<pre style="margin: 0;"> <span id="LC5" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;">#</span></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -33,11 +33,13 @@ from ._format import (SampleEstimatorDirFmt,</td>
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<pre style="margin: 0;"> <span id="LC33" class="line" lang="python"> <span class="n" style="color: #333;">PredictionsFormat</span><span class="p">,</span></span>
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<pre style="margin: 0;"> <span id="LC34" class="line" lang="python"> <span class="n" style="color: #333;">PredictionsDirectoryFormat</span><span class="p">,</span></span>
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<pre style="margin: 0;"> <span id="LC35" class="line" lang="python"> <span class="n" style="color: #333;">ProbabilitiesFormat</span><span class="p">,</span></span>
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<pre style="margin: 0;">-<span id="LC36" class="line" lang="python"> <span class="n" style="color: #333;">ProbabilitiesDirectoryFormat</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC36" class="line" lang="python"> <span class="n" style="color: #333;">ProbabilitiesDirectoryFormat</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC37" class="line" lang="python"> <span class="n" style="color: #333;">TrueTargetsDirectoryFormat</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC38" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC39" class="line" lang="python"><span class="kn" style="font-weight: 600;">from</span> <span class="nn" style="color: #555;">._type</span> <span class="kn" style="font-weight: 600;">import</span> <span class="p">(</span><span class="n" style="color: #333;">ClassifierPredictions</span><span class="p">,</span> <span class="n" style="color: #333;">RegressorPredictions</span><span class="p">,</span></span>
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<pre style="margin: 0;"> <span id="LC40" class="line" lang="python"> <span class="n" style="color: #333;">SampleEstimator</span><span class="p">,</span> <span class="n" style="color: #333;">BooleanSeries</span><span class="p">,</span> <span class="n" style="color: #333;">Importance</span><span class="p">,</span></span>
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<pre style="margin: 0;">-<span id="LC40" class="line" lang="python"> <span class="n" style="color: #333;">Classifier</span><span class="p">,</span> <span class="n" style="color: #333;">Regressor</span><span class="p">,</span> <span class="n" style="color: #333;">Probabilities</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC41" class="line" lang="python"> <span class="n" style="color: #333;">Classifier</span><span class="p">,</span> <span class="n" style="color: #333;">Regressor</span><span class="p">,</span> <span class="n" style="color: #333;">Probabilities</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC42" class="line" lang="python"> <span class="n" style="color: #333;">TrueTargets</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC43" class="line" lang="python"><span class="kn" style="font-weight: 600;">import</span> <span class="nn" style="color: #555;">q2_sample_classifier</span></span>
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<pre style="margin: 0;"> <span id="LC44" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC45" class="line" lang="python"><span class="n" style="color: #333;">citations</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">Citations</span><span class="p">.</span><span class="n" style="color: #333;">load</span><span class="p">(</span><span class="s" style="color: #d14;">'citations.bib'</span><span class="p">,</span> <span class="n" style="color: #333;">package</span><span class="o" style="font-weight: 600;">=</span><span class="s" style="color: #d14;">'q2_sample_classifier'</span><span class="p">)</span></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -102,7 +104,7 @@ parameters = {</td>
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<pre style="margin: 0;"> <span id="LC104" class="line" lang="python"> <span class="s" style="color: #d14;">'missing_samples'</span><span class="p">:</span> <span class="n" style="color: #333;">Str</span> <span class="o" style="font-weight: 600;">%</span> <span class="n" style="color: #333;">Choices</span><span class="p">([</span><span class="s" style="color: #d14;">'error'</span><span class="p">,</span> <span class="s" style="color: #d14;">'ignore'</span><span class="p">])},</span></span>
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<pre style="margin: 0;"> <span id="LC105" class="line" lang="python"> <span class="s" style="color: #d14;">'splitter'</span><span class="p">:</span> <span class="p">{</span></span>
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<pre style="margin: 0;"> <span id="LC106" class="line" lang="python"> <span class="s" style="color: #d14;">'test_size'</span><span class="p">:</span> <span class="n" style="color: #333;">Float</span> <span class="o" style="font-weight: 600;">%</span> <span class="n" style="color: #333;">Range</span><span class="p">(</span><span class="mf" style="color: #099;">0.0</span><span class="p">,</span> <span class="mf" style="color: #099;">1.0</span><span class="p">,</span> <span class="n" style="color: #333;">inclusive_end</span><span class="o" style="font-weight: 600;">=</span><span class="bp" style="color: #999;">False</span><span class="p">,</span></span>
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<pre style="margin: 0;">-<span id="LC105" class="line" lang="python"> <span class="n" style="color: #333;">inclusive_start</span><span class="o" style="font-weight: 600;">=</span><span class="bp" style="color: #999;"><span class="idiff left right">Fals</span>e</span><span class="p">)},</span></span>
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<pre style="margin: 0;">+<span id="LC107" class="line" lang="python"> <span class="n" style="color: #333;">inclusive_start</span><span class="o" style="font-weight: 600;">=</span><span class="bp" style="color: #999;"><span class="idiff left right">Tru</span>e</span><span class="p">)},</span></span>
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<pre style="margin: 0;"> <span id="LC108" class="line" lang="python"> <span class="s" style="color: #d14;">'rfe'</span><span class="p">:</span> <span class="p">{</span></span>
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<pre style="margin: 0;"> <span id="LC109" class="line" lang="python"> <span class="s" style="color: #d14;">'step'</span><span class="p">:</span> <span class="n" style="color: #333;">Float</span> <span class="o" style="font-weight: 600;">%</span> <span class="n" style="color: #333;">Range</span><span class="p">(</span><span class="mf" style="color: #099;">0.0</span><span class="p">,</span> <span class="mf" style="color: #099;">1.0</span><span class="p">,</span> <span class="n" style="color: #333;">inclusive_end</span><span class="o" style="font-weight: 600;">=</span><span class="bp" style="color: #999;">False</span><span class="p">,</span></span>
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<pre style="margin: 0;"> <span id="LC110" class="line" lang="python"> <span class="n" style="color: #333;">inclusive_start</span><span class="o" style="font-weight: 600;">=</span><span class="bp" style="color: #999;">False</span><span class="p">),</span></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -226,15 +228,21 @@ plugin.pipelines.register_function(</td>
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<pre style="margin: 0;"> <span id="LC228" class="line" lang="python"> <span class="p">(</span><span class="s" style="color: #d14;">'feature_importance'</span><span class="p">,</span> <span class="n" style="color: #333;">FeatureData</span><span class="p">[</span><span class="n" style="color: #333;">Importance</span><span class="p">]),</span></span>
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<pre style="margin: 0;"> <span id="LC229" class="line" lang="python"> <span class="p">(</span><span class="s" style="color: #d14;">'predictions'</span><span class="p">,</span> <span class="n" style="color: #333;">SampleData</span><span class="p">[</span><span class="n" style="color: #333;">ClassifierPredictions</span><span class="p">])</span></span>
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<pre style="margin: 0;"> <span id="LC230" class="line" lang="python"> <span class="p">]</span> <span class="o" style="font-weight: 600;">+</span> <span class="n" style="color: #333;">pipeline_outputs</span> <span class="o" style="font-weight: 600;">+</span> <span class="p">[</span></span>
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<pre style="margin: 0;">-<span id="LC229" class="line" lang="python"> <span class="p">(</span><span class="s" style="color: #d14;">'probabilities'</span><span class="p">,</span> <span class="n" style="color: #333;">SampleData</span><span class="p">[</span><span class="n" style="color: #333;">Probabilities</span><span class="p">]),</span></span>
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<pre style="margin: 0;">-<span id="LC230" class="line" lang="python"> <span class="p">(</span><span class="s" style="color: #d14;">'heatmap'</span><span class="p">,</span> <span class="n" style="color: #333;">Visualization</span><span class="p">)],</span></span>
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<pre style="margin: 0;">+<span id="LC231" class="line" lang="python"> <span class="p">(</span><span class="s" style="color: #d14;">'probabilities'</span><span class="p">,</span> <span class="n" style="color: #333;">SampleData</span><span class="p">[</span><span class="n" style="color: #333;">Probabilities</span><span class="p">]),</span></span>
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<pre style="margin: 0;">+<span id="LC232" class="line" lang="python"> <span class="p">(</span><span class="s" style="color: #d14;">'heatmap'</span><span class="p">,</span> <span class="n" style="color: #333;">Visualization</span><span class="p">),</span></span>
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<pre style="margin: 0;">+<span id="LC233" class="line" lang="python"> <span class="p">(</span><span class="s" style="color: #d14;">'training_targets'</span><span class="p">,</span> <span class="n" style="color: #333;">SampleData</span><span class="p">[</span><span class="n" style="color: #333;">TrueTargets</span><span class="p">]),</span></span>
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<pre style="margin: 0;">+<span id="LC234" class="line" lang="python"> <span class="p">(</span><span class="s" style="color: #d14;">'test_targets'</span><span class="p">,</span> <span class="n" style="color: #333;">SampleData</span><span class="p">[</span><span class="n" style="color: #333;">TrueTargets</span><span class="p">])],</span></span>
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<pre style="margin: 0;"> <span id="LC235" class="line" lang="python"> <span class="n" style="color: #333;">input_descriptions</span><span class="o" style="font-weight: 600;">=</span><span class="p">{</span><span class="s" style="color: #d14;">'table'</span><span class="p">:</span> <span class="n" style="color: #333;">input_descriptions</span><span class="p">[</span><span class="s" style="color: #d14;">'table'</span><span class="p">]},</span></span>
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<pre style="margin: 0;"> <span id="LC236" class="line" lang="python"> <span class="n" style="color: #333;">parameter_descriptions</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">classifier_pipeline_parameter_descriptions</span><span class="p">,</span></span>
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<pre style="margin: 0;"> <span id="LC237" class="line" lang="python"> <span class="n" style="color: #333;">output_descriptions</span><span class="o" style="font-weight: 600;">=</span><span class="p">{</span></span>
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<pre style="margin: 0;"> <span id="LC238" class="line" lang="python"> <span class="o" style="font-weight: 600;">**</span><span class="n" style="color: #333;">pipeline_output_descriptions</span><span class="p">,</span></span>
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<pre style="margin: 0;"> <span id="LC239" class="line" lang="python"> <span class="s" style="color: #d14;">'probabilities'</span><span class="p">:</span> <span class="n" style="color: #333;">input_descriptions</span><span class="p">[</span><span class="s" style="color: #d14;">'probabilities'</span><span class="p">],</span></span>
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<pre style="margin: 0;"> <span id="LC240" class="line" lang="python"> <span class="s" style="color: #d14;">'heatmap'</span><span class="p">:</span> <span class="s" style="color: #d14;">'A heatmap of the top 50 most important features from the '</span></span>
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<pre style="margin: 0;">-<span id="LC237" class="line" lang="python"> <span class="s" style="color: #d14;">'table.'</span><span class="p">},</span></span>
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<pre style="margin: 0;">+<span id="LC241" class="line" lang="python"> <span class="s" style="color: #d14;">'table.'</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC242" class="line" lang="python"> <span class="s" style="color: #d14;">'training_targets'</span><span class="p">:</span> <span class="s" style="color: #d14;">'Series containing true target values of '</span></span>
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<pre style="margin: 0;">+<span id="LC243" class="line" lang="python"> <span class="s" style="color: #d14;">'train samples'</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC244" class="line" lang="python"> <span class="s" style="color: #d14;">'test_targets'</span><span class="p">:</span> <span class="s" style="color: #d14;">'Series containing true target values '</span></span>
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<pre style="margin: 0;">+<span id="LC245" class="line" lang="python"> <span class="s" style="color: #d14;">'of test samples'</span><span class="p">},</span></span>
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<pre style="margin: 0;"> <span id="LC246" class="line" lang="python"> <span class="n" style="color: #333;">name</span><span class="o" style="font-weight: 600;">=</span><span class="s" style="color: #d14;">'Train and test a cross-validated supervised learning classifier.'</span><span class="p">,</span></span>
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<pre style="margin: 0;"> <span id="LC247" class="line" lang="python"> <span class="n" style="color: #333;">description</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">description</span><span class="p">.</span><span class="nb" style="color: #0086b3;">format</span><span class="p">(</span></span>
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<pre style="margin: 0;"> <span id="LC248" class="line" lang="python"> <span class="s" style="color: #d14;">'categorical'</span><span class="p">,</span> <span class="s" style="color: #d14;">'supervised learning classifier'</span><span class="p">)</span></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -258,7 +266,7 @@ plugin.pipelines.register_function(</td>
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<pre style="margin: 0;"> <span id="LC266" class="line" lang="python"> <span class="s" style="color: #d14;">'metadata'</span><span class="p">:</span> <span class="s" style="color: #d14;">'Categorical metadata column to use as prediction target.'</span><span class="p">,</span></span>
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<pre style="margin: 0;"> <span id="LC267" class="line" lang="python"> <span class="s" style="color: #d14;">'k'</span><span class="p">:</span> <span class="s" style="color: #d14;">'Number of nearest neighbors'</span><span class="p">,</span></span>
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<pre style="margin: 0;"> <span id="LC268" class="line" lang="python"> <span class="s" style="color: #d14;">'palette'</span><span class="p">:</span> <span class="s" style="color: #d14;">'The color palette to use for plotting.'</span><span class="p">,</span></span>
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<pre style="margin: 0;">-<span id="LC261" class="line" lang="python"><span class="idiff left right"> </span> <span class="p">},</span></span>
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<pre style="margin: 0;">+<span id="LC269" class="line" lang="python"> <span class="p">},</span></span>
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<pre style="margin: 0;"> <span id="LC270" class="line" lang="python"> <span class="n" style="color: #333;">output_descriptions</span><span class="o" style="font-weight: 600;">=</span><span class="p">{</span></span>
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<pre style="margin: 0;"> <span id="LC271" class="line" lang="python"> <span class="s" style="color: #d14;">'predictions'</span><span class="p">:</span> <span class="s" style="color: #d14;">'leave one out predictions for each sample'</span><span class="p">,</span></span>
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<pre style="margin: 0;"> <span id="LC272" class="line" lang="python"> <span class="s" style="color: #d14;">'accuracy_results'</span><span class="p">:</span> <span class="s" style="color: #d14;">'Accuracy results visualization.'</span><span class="p">,</span></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -486,7 +494,9 @@ plugin.methods.register_function(</td>
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<pre style="margin: 0;"> <span id="LC494" class="line" lang="python"> <span class="s" style="color: #d14;">'metadata'</span><span class="p">:</span> <span class="n" style="color: #333;">MetadataColumn</span><span class="p">[</span><span class="n" style="color: #333;">Numeric</span> <span class="o" style="font-weight: 600;">|</span> <span class="n" style="color: #333;">Categorical</span><span class="p">],</span></span>
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<pre style="margin: 0;"> <span id="LC495" class="line" lang="python"> <span class="o" style="font-weight: 600;">**</span><span class="n" style="color: #333;">parameters</span><span class="p">[</span><span class="s" style="color: #d14;">'regressor'</span><span class="p">]},</span></span>
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<pre style="margin: 0;"> <span id="LC496" class="line" lang="python"> <span class="n" style="color: #333;">outputs</span><span class="o" style="font-weight: 600;">=</span><span class="p">[(</span><span class="s" style="color: #d14;">'training_table'</span><span class="p">,</span> <span class="n" style="color: #333;">FeatureTable</span><span class="p">[</span><span class="n" style="color: #333;">T</span><span class="p">]),</span></span>
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<pre style="margin: 0;">-<span id="LC489" class="line" lang="python"> <span class="p">(</span><span class="s" style="color: #d14;">'test_table'</span><span class="p">,</span> <span class="n" style="color: #333;">FeatureTable</span><span class="p">[</span><span class="n" style="color: #333;">T</span><span class="p">])],</span></span>
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<pre style="margin: 0;">+<span id="LC497" class="line" lang="python"> <span class="p">(</span><span class="s" style="color: #d14;">'test_table'</span><span class="p">,</span> <span class="n" style="color: #333;">FeatureTable</span><span class="p">[</span><span class="n" style="color: #333;">T</span><span class="p">]),</span></span>
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<pre style="margin: 0;">+<span id="LC498" class="line" lang="python"> <span class="p">(</span><span class="s" style="color: #d14;">'training_targets'</span><span class="p">,</span> <span class="n" style="color: #333;">SampleData</span><span class="p">[</span><span class="n" style="color: #333;">TrueTargets</span><span class="p">]),</span></span>
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<pre style="margin: 0;">+<span id="LC499" class="line" lang="python"> <span class="p">(</span><span class="s" style="color: #d14;">'test_targets'</span><span class="p">,</span> <span class="n" style="color: #333;">SampleData</span><span class="p">[</span><span class="n" style="color: #333;">TrueTargets</span><span class="p">])],</span></span>
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<pre style="margin: 0;"> <span id="LC500" class="line" lang="python"> <span class="n" style="color: #333;">input_descriptions</span><span class="o" style="font-weight: 600;">=</span><span class="p">{</span><span class="s" style="color: #d14;">'table'</span><span class="p">:</span> <span class="s" style="color: #d14;">'Feature table containing all features that '</span></span>
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<pre style="margin: 0;"> <span id="LC501" class="line" lang="python"> <span class="s" style="color: #d14;">'should be used for target prediction.'</span><span class="p">},</span></span>
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<pre style="margin: 0;"> <span id="LC502" class="line" lang="python"> <span class="n" style="color: #333;">parameter_descriptions</span><span class="o" style="font-weight: 600;">=</span><span class="p">{</span></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -497,7 +507,11 @@ plugin.methods.register_function(</td>
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<pre style="margin: 0;"> <span id="LC507" class="line" lang="python"> <span class="s" style="color: #d14;">'metadata'</span><span class="p">:</span> <span class="s" style="color: #d14;">'Numeric metadata column to use as prediction target.'</span><span class="p">},</span></span>
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<pre style="margin: 0;"> <span id="LC508" class="line" lang="python"> <span class="n" style="color: #333;">output_descriptions</span><span class="o" style="font-weight: 600;">=</span><span class="p">{</span></span>
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<pre style="margin: 0;"> <span id="LC509" class="line" lang="python"> <span class="s" style="color: #d14;">'training_table'</span><span class="p">:</span> <span class="s" style="color: #d14;">'Feature table containing training samples'</span><span class="p">,</span></span>
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<pre style="margin: 0;">-<span id="LC500" class="line" lang="python"> <span class="s" style="color: #d14;">'test_table'</span><span class="p">:</span> <span class="s" style="color: #d14;">'Feature table containing test samples'</span><span class="p">},</span></span>
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<pre style="margin: 0;">+<span id="LC510" class="line" lang="python"> <span class="s" style="color: #d14;">'test_table'</span><span class="p">:</span> <span class="s" style="color: #d14;">'Feature table containing test samples'</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC511" class="line" lang="python"> <span class="s" style="color: #d14;">'training_targets'</span><span class="p">:</span> <span class="s" style="color: #d14;">'Series containing true target values of '</span></span>
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<pre style="margin: 0;">+<span id="LC512" class="line" lang="python"> <span class="s" style="color: #d14;">'train samples'</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC513" class="line" lang="python"> <span class="s" style="color: #d14;">'test_targets'</span><span class="p">:</span> <span class="s" style="color: #d14;">'Series containing true target values of '</span></span>
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<pre style="margin: 0;">+<span id="LC514" class="line" lang="python"> <span class="s" style="color: #d14;">'test samples'</span><span class="p">},</span></span>
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<pre style="margin: 0;"> <span id="LC515" class="line" lang="python"> <span class="n" style="color: #333;">name</span><span class="o" style="font-weight: 600;">=</span><span class="s" style="color: #d14;">'Split a feature table into training and testing sets.'</span><span class="p">,</span></span>
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<pre style="margin: 0;"> <span id="LC516" class="line" lang="python"> <span class="n" style="color: #333;">description</span><span class="o" style="font-weight: 600;">=</span><span class="p">(</span></span>
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<pre style="margin: 0;"> <span id="LC517" class="line" lang="python"> <span class="s" style="color: #d14;">'Split a feature table into training and testing sets. By default '</span></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -623,7 +637,7 @@ plugin.pipelines.register_function(</td>
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637
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<pre style="margin: 0;"> <span id="LC637" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Registrations</span></span>
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638
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<pre style="margin: 0;"> <span id="LC638" class="line" lang="python"><span class="n" style="color: #333;">plugin</span><span class="p">.</span><span class="n" style="color: #333;">register_semantic_types</span><span class="p">(</span></span>
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<pre style="margin: 0;"> <span id="LC639" class="line" lang="python"> <span class="n" style="color: #333;">SampleEstimator</span><span class="p">,</span> <span class="n" style="color: #333;">BooleanSeries</span><span class="p">,</span> <span class="n" style="color: #333;">Importance</span><span class="p">,</span> <span class="n" style="color: #333;">ClassifierPredictions</span><span class="p">,</span></span>
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<pre style="margin: 0;">-<span id="LC626" class="line" lang="python"> <span class="n" style="color: #333;">RegressorPredictions</span><span class="p">,</span> <span class="n" style="color: #333;">Classifier</span><span class="p">,</span> <span class="n" style="color: #333;">Regressor</span><span class="p">,</span> <span class="n" style="color: #333;">Probabilities</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC640" class="line" lang="python"> <span class="n" style="color: #333;">RegressorPredictions</span><span class="p">,</span> <span class="n" style="color: #333;">Classifier</span><span class="p">,</span> <span class="n" style="color: #333;">Regressor</span><span class="p">,</span> <span class="n" style="color: #333;">Probabilities</span><span class="p"><span class="idiff left">,</span></span><span class="idiff"> </span><span class="n" style="color: #333;"><span class="idiff right">TrueTargets</span></span><span class="p">)</span></span>
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641
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<pre style="margin: 0;"> <span id="LC641" class="line" lang="python"><span class="n" style="color: #333;">plugin</span><span class="p">.</span><span class="n" style="color: #333;">register_semantic_type_to_format</span><span class="p">(</span></span>
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642
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<pre style="margin: 0;"> <span id="LC642" class="line" lang="python"> <span class="n" style="color: #333;">SampleEstimator</span><span class="p">[</span><span class="n" style="color: #333;">Classifier</span><span class="p">],</span></span>
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643
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<pre style="margin: 0;"> <span id="LC643" class="line" lang="python"> <span class="n" style="color: #333;">artifact_format</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">SampleEstimatorDirFmt</span><span class="p">)</span></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -645,9 +659,13 @@ plugin.register_semantic_type_to_format(</td>
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659
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<pre style="margin: 0;"> <span id="LC659" class="line" lang="python"><span class="n" style="color: #333;">plugin</span><span class="p">.</span><span class="n" style="color: #333;">register_semantic_type_to_format</span><span class="p">(</span></span>
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660
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<pre style="margin: 0;"> <span id="LC660" class="line" lang="python"> <span class="n" style="color: #333;">SampleData</span><span class="p">[</span><span class="n" style="color: #333;">Probabilities</span><span class="p">],</span></span>
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661
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<pre style="margin: 0;"> <span id="LC661" class="line" lang="python"> <span class="n" style="color: #333;">artifact_format</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">ProbabilitiesDirectoryFormat</span><span class="p">)</span></span>
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662
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<pre style="margin: 0;">+<span id="LC662" class="line" lang="python"><span class="n" style="color: #333;">plugin</span><span class="p">.</span><span class="n" style="color: #333;">register_semantic_type_to_format</span><span class="p">(</span></span>
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663
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<pre style="margin: 0;">+<span id="LC663" class="line" lang="python"> <span class="n" style="color: #333;">SampleData</span><span class="p">[</span><span class="n" style="color: #333;">TrueTargets</span><span class="p">],</span></span>
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664
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<pre style="margin: 0;">+<span id="LC664" class="line" lang="python"> <span class="n" style="color: #333;">artifact_format</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">TrueTargetsDirectoryFormat</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC665" class="line" lang="python"><span class="n" style="color: #333;">plugin</span><span class="p">.</span><span class="n" style="color: #333;">register_formats</span><span class="p">(</span></span>
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<pre style="margin: 0;"> <span id="LC666" class="line" lang="python"> <span class="n" style="color: #333;">SampleEstimatorDirFmt</span><span class="p">,</span> <span class="n" style="color: #333;">BooleanSeriesFormat</span><span class="p">,</span> <span class="n" style="color: #333;">BooleanSeriesDirectoryFormat</span><span class="p">,</span></span>
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<pre style="margin: 0;"> <span id="LC667" class="line" lang="python"> <span class="n" style="color: #333;">ImportanceFormat</span><span class="p">,</span> <span class="n" style="color: #333;">ImportanceDirectoryFormat</span><span class="p">,</span> <span class="n" style="color: #333;">PredictionsFormat</span><span class="p">,</span></span>
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<pre style="margin: 0;"> <span id="LC668" class="line" lang="python"> <span class="n" style="color: #333;">PredictionsDirectoryFormat</span><span class="p">,</span> <span class="n" style="color: #333;">ProbabilitiesFormat</span><span class="p">,</span></span>
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<pre style="margin: 0;">-<span id="LC652" class="line" lang="python"> <span class="n" style="color: #333;">ProbabilitiesDirectoryFormat</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC669" class="line" lang="python"> <span class="n" style="color: #333;">ProbabilitiesDirectoryFormat</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC670" class="line" lang="python"> <span class="n" style="color: #333;">TrueTargetsDirectoryFormat</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC671" class="line" lang="python"><span class="n" style="color: #333;">importlib</span><span class="p">.</span><span class="n" style="color: #333;">import_module</span><span class="p">(</span><span class="s" style="color: #d14;">'q2_sample_classifier._transformer'</span><span class="p">)</span></span></pre>
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<a href="https://salsa.debian.org/med-team/q2-sample-classifier/-/commit/7c4b78faf33bc50e958843964685cf5d73d1374d#1b690d92d63b3499c2ca3d9b95eb15070797d08d"><strong>q2_sample_classifier/tests/__init__.py</strong></a>
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<pre style="margin: 0;"> <span id="LC1" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># ----------------------------------------------------------------------------</span></span>
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<pre style="margin: 0;">-<span id="LC2" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Copyright (c) 2017-202<span class="idiff left right">0</span>, QIIME 2 development team.</span></span>
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<pre style="margin: 0;">+<span id="LC2" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Copyright (c) 2017-202<span class="idiff left right">1</span>, QIIME 2 development team.</span></span>
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<pre style="margin: 0;"> <span id="LC3" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;">#</span></span>
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<pre style="margin: 0;"> <span id="LC4" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Distributed under the terms of the Modified BSD License.</span></span>
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<pre style="margin: 0;"> <span id="LC5" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;">#</span></span>
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<a href="https://salsa.debian.org/med-team/q2-sample-classifier/-/commit/7c4b78faf33bc50e958843964685cf5d73d1374d#08f78176813161090d6ef77f0c52ff67e5ba1b84"><strong>q2_sample_classifier/tests/data/true_targets.tsv</strong></a>
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<pre style="margin: 0;">+<span id="LC1" class="line" lang="plaintext">sample-id delivery</span>
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<pre style="margin: 0;">+<span id="LC2" class="line" lang="plaintext">10249.C041.08SS Vaginal</span>
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<pre style="margin: 0;">+<span id="LC3" class="line" lang="plaintext">10249.C055.08SS Cesarean</span>
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<pre style="margin: 0;">+<span id="LC4" class="line" lang="plaintext">10249.C027.07SS Vaginal</span>
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<pre style="margin: 0;">+<span id="LC5" class="line" lang="plaintext">10249.C042.07SS Vaginal</span>
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<pre style="margin: 0;">+<span id="LC6" class="line" lang="plaintext">10249.C005.08SS Cesarean</span>
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<pre style="margin: 0;">+<span id="LC8" class="line" lang="plaintext">10249.C035.07SD Vaginal</span>
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<pre style="margin: 0;">+<span id="LC9" class="line" lang="plaintext">10249.C001.10SS Vaginal</span></pre>
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<a href="https://salsa.debian.org/med-team/q2-sample-classifier/-/commit/7c4b78faf33bc50e958843964685cf5d73d1374d#c78b037f63bf727dfb951db2f49cfed0ce6ece59"><strong>q2_sample_classifier/tests/test_actions.py</strong></a>
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<pre style="margin: 0;"> <span id="LC1" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># ----------------------------------------------------------------------------</span></span>
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<pre style="margin: 0;">-<span id="LC2" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Copyright (c) 2017-202<span class="idiff left right">0</span>, QIIME 2 development team.</span></span>
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<pre style="margin: 0;">+<span id="LC2" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Copyright (c) 2017-202<span class="idiff left right">1</span>, QIIME 2 development team.</span></span>
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<pre style="margin: 0;"> <span id="LC3" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;">#</span></span>
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<pre style="margin: 0;"> <span id="LC4" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Distributed under the terms of the Modified BSD License.</span></span>
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<pre style="margin: 0;"> <span id="LC5" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;">#</span></span>
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<pre style="margin: 0;"> <span id="LC6" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># The full license is in the file LICENSE, distributed with this software.</span></span>
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<pre style="margin: 0;"> <span id="LC7" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># ----------------------------------------------------------------------------</span></span>
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<pre style="margin: 0;">+<span id="LC8" class="line" lang="python"></span>
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<pre style="margin: 0;">+<span id="LC9" class="line" lang="python"><span class="kn" style="font-weight: 600;">import</span> <span class="nn" style="color: #555;">os</span></span>
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<pre style="margin: 0;">+<span id="LC10" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC11" class="line" lang="python"><span class="kn" style="font-weight: 600;">import</span> <span class="nn" style="color: #555;">pandas</span> <span class="k" style="font-weight: 600;">as</span> <span class="n" style="color: #333;">pd</span></span>
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<pre style="margin: 0;">+<span id="LC12" class="line" lang="python"><span class="kn" style="font-weight: 600;">import</span> <span class="nn" style="color: #555;">pandas.testing</span> <span class="k" style="font-weight: 600;">as</span> <span class="n" style="color: #333;">pdt</span></span>
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<pre style="margin: 0;"> <span id="LC13" class="line" lang="python"><span class="kn" style="font-weight: 600;">import</span> <span class="nn" style="color: #555;">numpy</span> <span class="k" style="font-weight: 600;">as</span> <span class="n" style="color: #333;">np</span></span>
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<pre style="margin: 0;"> <span id="LC14" class="line" lang="python"><span class="kn" style="font-weight: 600;">import</span> <span class="nn" style="color: #555;">biom</span></span>
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<pre style="margin: 0;"> <span id="LC15" class="line" lang="python"></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -43,11 +47,21 @@ class NowLetsTestTheActions(SampleClassifierTestPluginBase):</td>
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<pre style="margin: 0;"> <span id="LC47" class="line" lang="python"> <span class="n" style="color: #333;">md2</span><span class="p">.</span><span class="n" style="color: #333;">index</span><span class="p">.</span><span class="n" style="color: #333;">name</span> <span class="o" style="font-weight: 600;">=</span> <span class="s" style="color: #d14;">'SampleID'</span></span>
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<pre style="margin: 0;"> <span id="LC48" class="line" lang="python"> <span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">md2</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">qiime2</span><span class="p">.</span><span class="n" style="color: #333;">Metadata</span><span class="p">(</span><span class="n" style="color: #333;">md2</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC49" class="line" lang="python"></span>
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<pre style="margin: 0;">-<span id="LC46" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># let's make sure the correct transformers are in place! See issue 114</span></span>
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<pre style="margin: 0;">-<span id="LC47" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># if this runs without error, that's good enough for me. We already</span></span>
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<pre style="margin: 0;">-<span id="LC48" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># validate the function above.</span></span>
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<pre style="margin: 0;">+<span id="LC50" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># let's make sure the function runs w/o errors and that the correct</span></span>
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<pre style="margin: 0;">+<span id="LC51" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># transformers are in place (see issue 114)</span></span>
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<pre style="margin: 0;"> <span id="LC52" class="line" lang="python"> <span class="k" style="font-weight: 600;">def</span> <span class="nf" style="color: #900; font-weight: 600;">test_action_split_table</span><span class="p">(</span><span class="bp" style="color: #999;">self</span><span class="p">):</span></span>
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<pre style="margin: 0;">-<span id="LC50" class="line" lang="python"> <span class="n" style="color: #333;">sample_classifier</span><span class="p">.</span><span class="n" style="color: #333;">actions</span><span class="p">.</span><span class="n" style="color: #333;">split_table</span><span class="p">(</span><span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">tab</span><span class="p">,</span> <span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">md</span><span class="p">,</span> <span class="n" style="color: #333;">test_size</span><span class="o" style="font-weight: 600;">=</span><span class="mf" style="color: #099;">0.5</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC53" class="line" lang="python"> <span class="n" style="color: #333;">res</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">sample_classifier</span><span class="p">.</span><span class="n" style="color: #333;">actions</span><span class="p">.</span><span class="n" style="color: #333;">split_table</span><span class="p">(</span></span>
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<pre style="margin: 0;">+<span id="LC54" class="line" lang="python"> <span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">tab</span><span class="p">,</span> <span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">md</span><span class="p">,</span> <span class="n" style="color: #333;">test_size</span><span class="o" style="font-weight: 600;">=</span><span class="mf" style="color: #099;">0.5</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC55" class="line" lang="python"> <span class="n" style="color: #333;">y_train</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">res</span><span class="p">.</span><span class="n" style="color: #333;">training_targets</span><span class="p">.</span><span class="n" style="color: #333;">view</span><span class="p">(</span><span class="n" style="color: #333;">pd</span><span class="p">.</span><span class="n" style="color: #333;">Series</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC56" class="line" lang="python"> <span class="n" style="color: #333;">y_test</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">res</span><span class="p">.</span><span class="n" style="color: #333;">test_targets</span><span class="p">.</span><span class="n" style="color: #333;">view</span><span class="p">(</span><span class="n" style="color: #333;">pd</span><span class="p">.</span><span class="n" style="color: #333;">Series</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC57" class="line" lang="python"></span>
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<pre style="margin: 0;">+<span id="LC58" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># test whether extracted target is correct</span></span>
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<pre style="margin: 0;">+<span id="LC59" class="line" lang="python"> <span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">assertEqual</span><span class="p">(</span><span class="n" style="color: #333;">y_train</span><span class="p">.</span><span class="n" style="color: #333;">name</span><span class="p">,</span> <span class="s" style="color: #d14;">'bugs'</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC60" class="line" lang="python"></span>
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<pre style="margin: 0;">+<span id="LC61" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># test if complete target column is covered</span></span>
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<pre style="margin: 0;">+<span id="LC62" class="line" lang="python"> <span class="n" style="color: #333;">y_all</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">y_train</span><span class="p">.</span><span class="n" style="color: #333;">append</span><span class="p">(</span><span class="n" style="color: #333;">y_test</span><span class="p">).</span><span class="n" style="color: #333;">sort_index</span><span class="p">()</span></span>
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<pre style="margin: 0;">+<span id="LC63" class="line" lang="python"> <span class="n" style="color: #333;">y_all</span><span class="p">.</span><span class="n" style="color: #333;">index</span><span class="p">.</span><span class="n" style="color: #333;">name</span> <span class="o" style="font-weight: 600;">=</span> <span class="s" style="color: #d14;">'SampleID'</span></span>
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<pre style="margin: 0;">+<span id="LC64" class="line" lang="python"> <span class="n" style="color: #333;">pdt</span><span class="p">.</span><span class="n" style="color: #333;">assert_series_equal</span><span class="p">(</span><span class="n" style="color: #333;">y_all</span><span class="p">,</span> <span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">md</span><span class="p">.</span><span class="n" style="color: #333;">_series</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC65" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC66" class="line" lang="python"> <span class="k" style="font-weight: 600;">def</span> <span class="nf" style="color: #900; font-weight: 600;">test_metatable</span><span class="p">(</span><span class="bp" style="color: #999;">self</span><span class="p">):</span></span>
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<pre style="margin: 0;"> <span id="LC67" class="line" lang="python"> <span class="n" style="color: #333;">exp</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">biom</span><span class="p">.</span><span class="n" style="color: #333;">Table</span><span class="p">(</span></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -155,6 +169,15 @@ class TestSummarize(SampleEstimatorTestBase):</td>
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<pre style="margin: 0;"> <span id="LC169" class="line" lang="python"> <span class="k" style="font-weight: 600;">def</span> <span class="nf" style="color: #900; font-weight: 600;">test_summary_with_rfecv</span><span class="p">(</span><span class="bp" style="color: #999;">self</span><span class="p">):</span></span>
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<pre style="margin: 0;"> <span id="LC170" class="line" lang="python"> <span class="n" style="color: #333;">summarize</span><span class="p">(</span><span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">temp_dir</span><span class="p">.</span><span class="n" style="color: #333;">name</span><span class="p">,</span> <span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">pipeline</span><span class="p">)</span></span>
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171
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<pre style="margin: 0;"> <span id="LC171" class="line" lang="python"></span>
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<pre style="margin: 0;">+<span id="LC172" class="line" lang="python"> <span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">assertTrue</span><span class="p">(</span><span class="s" style="color: #d14;">'rfe_plot.pdf'</span> <span class="ow" style="font-weight: 600;">in</span> <span class="n" style="color: #333;">os</span><span class="p">.</span><span class="n" style="color: #333;">listdir</span><span class="p">(</span><span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">temp_dir</span><span class="p">.</span><span class="n" style="color: #333;">name</span><span class="p">))</span></span>
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173
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<pre style="margin: 0;">+<span id="LC173" class="line" lang="python"> <span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">assertTrue</span><span class="p">(</span><span class="s" style="color: #d14;">'rfe_plot.png'</span> <span class="ow" style="font-weight: 600;">in</span> <span class="n" style="color: #333;">os</span><span class="p">.</span><span class="n" style="color: #333;">listdir</span><span class="p">(</span><span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">temp_dir</span><span class="p">.</span><span class="n" style="color: #333;">name</span><span class="p">))</span></span>
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<pre style="margin: 0;">+<span id="LC174" class="line" lang="python"> <span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">assertTrue</span><span class="p">(</span><span class="s" style="color: #d14;">'rfe_scores.tsv'</span> <span class="ow" style="font-weight: 600;">in</span> <span class="n" style="color: #333;">os</span><span class="p">.</span><span class="n" style="color: #333;">listdir</span><span class="p">(</span><span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">temp_dir</span><span class="p">.</span><span class="n" style="color: #333;">name</span><span class="p">))</span></span>
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<pre style="margin: 0;">+<span id="LC175" class="line" lang="python"></span>
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158
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176
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<pre style="margin: 0;"> <span id="LC176" class="line" lang="python"> <span class="k" style="font-weight: 600;">def</span> <span class="nf" style="color: #900; font-weight: 600;">test_summary_without_rfecv</span><span class="p">(</span><span class="bp" style="color: #999;">self</span><span class="p">):</span></span>
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177
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<pre style="margin: 0;">+<span id="LC177" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># nuke the rfe_scores to test the other branch of _summarize_estimator</span></span>
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159
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178
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<pre style="margin: 0;"> <span id="LC178" class="line" lang="python"> <span class="k" style="font-weight: 600;">del</span> <span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">pipeline</span><span class="p">.</span><span class="n" style="color: #333;">rfe_scores</span></span>
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179
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<pre style="margin: 0;"> <span id="LC179" class="line" lang="python"> <span class="n" style="color: #333;">summarize</span><span class="p">(</span><span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">temp_dir</span><span class="p">.</span><span class="n" style="color: #333;">name</span><span class="p">,</span> <span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">pipeline</span><span class="p">)</span></span>
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180
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<pre style="margin: 0;">+<span id="LC180" class="line" lang="python"></span>
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<pre style="margin: 0;">+<span id="LC181" class="line" lang="python"> <span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">assertFalse</span><span class="p">(</span><span class="s" style="color: #d14;">'rfe_plot.pdf'</span> <span class="ow" style="font-weight: 600;">in</span> <span class="n" style="color: #333;">os</span><span class="p">.</span><span class="n" style="color: #333;">listdir</span><span class="p">(</span><span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">temp_dir</span><span class="p">.</span><span class="n" style="color: #333;">name</span><span class="p">))</span></span>
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<pre style="margin: 0;">+<span id="LC182" class="line" lang="python"> <span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">assertFalse</span><span class="p">(</span><span class="s" style="color: #d14;">'rfe_plot.png'</span> <span class="ow" style="font-weight: 600;">in</span> <span class="n" style="color: #333;">os</span><span class="p">.</span><span class="n" style="color: #333;">listdir</span><span class="p">(</span><span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">temp_dir</span><span class="p">.</span><span class="n" style="color: #333;">name</span><span class="p">))</span></span>
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<pre style="margin: 0;">+<span id="LC183" class="line" lang="python"> <span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">assertFalse</span><span class="p">(</span><span class="s" style="color: #d14;">'rfe_scores.tsv'</span> <span class="ow" style="font-weight: 600;">in</span> <span class="n" style="color: #333;">os</span><span class="p">.</span><span class="n" style="color: #333;">listdir</span><span class="p">(</span><span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">temp_dir</span><span class="p">.</span><span class="n" style="color: #333;">name</span><span class="p">))</span></span></pre>
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<a href="https://salsa.debian.org/med-team/q2-sample-classifier/-/commit/7c4b78faf33bc50e958843964685cf5d73d1374d#1e7213981596409508f1bb2c78c18bb9d19078e8"><strong>q2_sample_classifier/tests/test_base_class.py</strong></a>
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<pre style="margin: 0;"> <span id="LC1" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># ----------------------------------------------------------------------------</span></span>
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<pre style="margin: 0;">-<span id="LC2" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Copyright (c) 2017-202<span class="idiff left right">0</span>, QIIME 2 development team.</span></span>
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<pre style="margin: 0;">+<span id="LC2" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Copyright (c) 2017-202<span class="idiff left right">1</span>, QIIME 2 development team.</span></span>
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<pre style="margin: 0;"> <span id="LC3" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;">#</span></span>
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4
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<pre style="margin: 0;"> <span id="LC4" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Distributed under the terms of the Modified BSD License.</span></span>
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<pre style="margin: 0;"> <span id="LC5" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;">#</span></span>
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<pre style="margin: 0;"> <span id="LC1" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># ----------------------------------------------------------------------------</span></span>
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<pre style="margin: 0;">-<span id="LC2" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Copyright (c) 2017-202<span class="idiff left right">0</span>, QIIME 2 development team.</span></span>
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<pre style="margin: 0;">+<span id="LC2" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Copyright (c) 2017-202<span class="idiff left right">1</span>, QIIME 2 development team.</span></span>
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<pre style="margin: 0;"> <span id="LC3" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;">#</span></span>
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<pre style="margin: 0;"> <span id="LC4" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Distributed under the terms of the Modified BSD License.</span></span>
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<pre style="margin: 0;"> <span id="LC5" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;">#</span></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -10,7 +10,7 @@ import pandas as pd</td>
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<pre style="margin: 0;"> <span id="LC10" class="line" lang="python"><span class="kn" style="font-weight: 600;">import</span> <span class="nn" style="color: #555;">numpy</span> <span class="k" style="font-weight: 600;">as</span> <span class="n" style="color: #333;">np</span></span>
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<pre style="margin: 0;"> <span id="LC11" class="line" lang="python"><span class="kn" style="font-weight: 600;">from</span> <span class="nn" style="color: #555;">sklearn.ensemble</span> <span class="kn" style="font-weight: 600;">import</span> <span class="n" style="color: #333;">RandomForestClassifier</span></span>
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<pre style="margin: 0;"> <span id="LC12" class="line" lang="python"><span class="kn" style="font-weight: 600;">from</span> <span class="nn" style="color: #555;">sklearn.feature_selection</span> <span class="kn" style="font-weight: 600;">import</span> <span class="n" style="color: #333;">RFECV</span></span>
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<pre style="margin: 0;">-<span id="LC13" class="line" lang="python"><span class="kn" style="font-weight: 600;">import</span> <span class="nn" style="color: #555;">pandas.<span class="idiff left right">util.</span>testing</span> <span class="k" style="font-weight: 600;">as</span> <span class="n" style="color: #333;">pdt</span></span>
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<pre style="margin: 0;">+<span id="LC13" class="line" lang="python"><span class="kn" style="font-weight: 600;">import</span> <span class="nn" style="color: #555;">pandas.testing</span> <span class="k" style="font-weight: 600;">as</span> <span class="n" style="color: #333;">pdt</span></span>
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<pre style="margin: 0;"> <span id="LC14" class="line" lang="python"><span class="kn" style="font-weight: 600;">import</span> <span class="nn" style="color: #555;">biom</span></span>
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<pre style="margin: 0;"> <span id="LC15" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC16" class="line" lang="python"><span class="kn" style="font-weight: 600;">import</span> <span class="nn" style="color: #555;">qiime2</span></span>
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<a href="https://salsa.debian.org/med-team/q2-sample-classifier/-/commit/7c4b78faf33bc50e958843964685cf5d73d1374d#bf556fc40b98a4a248e31e633c175e9744ae3286"><strong>q2_sample_classifier/tests/test_estimators.py</strong></a>
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<pre style="margin: 0;"> <span id="LC1" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># ----------------------------------------------------------------------------</span></span>
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<pre style="margin: 0;">-<span id="LC2" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Copyright (c) 2017-202<span class="idiff left right">0</span>, QIIME 2 development team.</span></span>
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<pre style="margin: 0;">+<span id="LC2" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Copyright (c) 2017-202<span class="idiff left right">1</span>, QIIME 2 development team.</span></span>
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<pre style="margin: 0;"> <span id="LC3" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;">#</span></span>
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<pre style="margin: 0;"> <span id="LC4" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Distributed under the terms of the Modified BSD License.</span></span>
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<pre style="margin: 0;"> <span id="LC5" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;">#</span></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -7,7 +7,7 @@</td>
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<pre style="margin: 0;"> <span id="LC7" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># ----------------------------------------------------------------------------</span></span>
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<pre style="margin: 0;"> <span id="LC8" class="line" lang="python"><span class="kn" style="font-weight: 600;">import</span> <span class="nn" style="color: #555;">os</span></span>
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<pre style="margin: 0;"> <span id="LC9" class="line" lang="python"><span class="kn" style="font-weight: 600;">import</span> <span class="nn" style="color: #555;">pandas</span> <span class="k" style="font-weight: 600;">as</span> <span class="n" style="color: #333;">pd</span></span>
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<pre style="margin: 0;">-<span id="LC10" class="line" lang="python"><span class="kn" style="font-weight: 600;">import</span> <span class="nn" style="color: #555;">pandas.<span class="idiff left right">util.</span>testing</span> <span class="k" style="font-weight: 600;">as</span> <span class="n" style="color: #333;">pdt</span></span>
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<pre style="margin: 0;">+<span id="LC10" class="line" lang="python"><span class="kn" style="font-weight: 600;">import</span> <span class="nn" style="color: #555;">pandas.testing</span> <span class="k" style="font-weight: 600;">as</span> <span class="n" style="color: #333;">pdt</span></span>
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<pre style="margin: 0;"> <span id="LC11" class="line" lang="python"><span class="kn" style="font-weight: 600;">import</span> <span class="nn" style="color: #555;">biom</span></span>
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<pre style="margin: 0;"> <span id="LC12" class="line" lang="python"><span class="kn" style="font-weight: 600;">import</span> <span class="nn" style="color: #555;">shutil</span></span>
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<pre style="margin: 0;"> <span id="LC13" class="line" lang="python"><span class="kn" style="font-weight: 600;">import</span> <span class="nn" style="color: #555;">json</span></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -113,7 +113,7 @@ class EstimatorsTests(SampleClassifierTestPluginBase):</td>
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<pre style="margin: 0;"> <span id="LC113" class="line" lang="python"> <span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">mdc_ecam_fp</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">_load_nmc</span><span class="p">(</span><span class="s" style="color: #d14;">'ecam_map_maturity.txt'</span><span class="p">,</span> <span class="s" style="color: #d14;">'month'</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC114" class="line" lang="python"> <span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">exp_imp</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">pd</span><span class="p">.</span><span class="n" style="color: #333;">read_csv</span><span class="p">(</span></span>
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<pre style="margin: 0;"> <span id="LC115" class="line" lang="python"> <span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">get_data_path</span><span class="p">(</span><span class="s" style="color: #d14;">'importance.tsv'</span><span class="p">),</span> <span class="n" style="color: #333;">sep</span><span class="o" style="font-weight: 600;">=</span><span class="s" style="color: #d14;">'</span><span class="se" style="color: #d14;">\t</span><span class="s" style="color: #d14;">'</span><span class="p">,</span> <span class="n" style="color: #333;">header</span><span class="o" style="font-weight: 600;">=</span><span class="mi" style="color: #099;">0</span><span class="p">,</span></span>
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<pre style="margin: 0;">-<span id="LC116" class="line" lang="python"> <span class="n" style="color: #333;">index_col</span><span class="o" style="font-weight: 600;">=</span><span class="mi" style="color: #099;">0</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC116" class="line" lang="python"> <span class="n" style="color: #333;">index_col</span><span class="o" style="font-weight: 600;">=</span><span class="mi" style="color: #099;">0</span><span class="p"><span class="idiff left">,</span></span><span class="idiff"> </span><span class="n" style="color: #333;"><span class="idiff">names</span></span><span class="o" style="font-weight: 600;"><span class="idiff">=</span></span><span class="p"><span class="idiff">[</span></span><span class="s" style="color: #d14;"><span class="idiff">'feature'</span></span><span class="p"><span class="idiff">,</span></span><span class="idiff"> </span><span class="s" style="color: #d14;"><span class="idiff">'importance'</span></span><span class="p"><span class="idiff right">]</span>)</span></span>
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<pre style="margin: 0;"> <span id="LC117" class="line" lang="python"> <span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">exp_pred</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">pd</span><span class="p">.</span><span class="n" style="color: #333;">read_csv</span><span class="p">(</span></span>
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<pre style="margin: 0;"> <span id="LC118" class="line" lang="python"> <span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">get_data_path</span><span class="p">(</span><span class="s" style="color: #d14;">'predictions.tsv'</span><span class="p">),</span> <span class="n" style="color: #333;">sep</span><span class="o" style="font-weight: 600;">=</span><span class="s" style="color: #d14;">'</span><span class="se" style="color: #d14;">\t</span><span class="s" style="color: #d14;">'</span><span class="p">,</span> <span class="n" style="color: #333;">header</span><span class="o" style="font-weight: 600;">=</span><span class="mi" style="color: #099;">0</span><span class="p">,</span></span>
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<pre style="margin: 0;"> <span id="LC119" class="line" lang="python"> <span class="n" style="color: #333;">index_col</span><span class="o" style="font-weight: 600;">=</span><span class="mi" style="color: #099;">0</span><span class="p">,</span> <span class="n" style="color: #333;">squeeze</span><span class="o" style="font-weight: 600;">=</span><span class="bp" style="color: #999;">True</span><span class="p">)</span></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -152,7 +152,7 @@ class EstimatorsTests(SampleClassifierTestPluginBase):</td>
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<pre style="margin: 0;"> <span id="LC152" class="line" lang="python"> <span class="p">[</span><span class="mi" style="color: #099;">1</span><span class="p">,</span> <span class="mi" style="color: #099;">0</span><span class="p">,</span> <span class="mi" style="color: #099;">4</span><span class="p">,</span> <span class="mi" style="color: #099;">4</span><span class="p">],</span></span>
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<pre style="margin: 0;"> <span id="LC153" class="line" lang="python"> <span class="p">[</span><span class="mi" style="color: #099;">4</span><span class="p">,</span> <span class="mi" style="color: #099;">4</span><span class="p">,</span> <span class="mi" style="color: #099;">0</span><span class="p">,</span> <span class="mi" style="color: #099;">1</span><span class="p">],</span></span>
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<pre style="margin: 0;"> <span id="LC154" class="line" lang="python"> <span class="p">[</span><span class="mi" style="color: #099;">4</span><span class="p">,</span> <span class="mi" style="color: #099;">4</span><span class="p">,</span> <span class="mi" style="color: #099;">1</span><span class="p">,</span> <span class="mi" style="color: #099;">0</span><span class="p">],</span></span>
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<pre style="margin: 0;">-<span id="LC155" class="line" lang="python"> <span class="idiff left right"> </span><span class="p">],</span> <span class="n" style="color: #333;">ids</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">sample_ids</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC155" class="line" lang="python"> <span class="p">],</span> <span class="n" style="color: #333;">ids</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">sample_ids</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC156" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC157" class="line" lang="python"> <span class="n" style="color: #333;">dm</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">qiime2</span><span class="p">.</span><span class="n" style="color: #333;">Artifact</span><span class="p">.</span><span class="n" style="color: #333;">import_data</span><span class="p">(</span><span class="s" style="color: #d14;">'DistanceMatrix'</span><span class="p">,</span> <span class="n" style="color: #333;">distance_matrix</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC158" class="line" lang="python"> <span class="n" style="color: #333;">categories</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">pd</span><span class="p">.</span><span class="n" style="color: #333;">Series</span><span class="p">((</span><span class="s" style="color: #d14;">'skinny'</span><span class="p">,</span> <span class="s" style="color: #d14;">'skinny'</span><span class="p">,</span> <span class="s" style="color: #d14;">'fat'</span><span class="p">,</span> <span class="s" style="color: #d14;">'fat'</span><span class="p">),</span></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -182,7 +182,7 @@ class EstimatorsTests(SampleClassifierTestPluginBase):</td>
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182
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<pre style="margin: 0;"> <span id="LC182" class="line" lang="python"> <span class="p">[</span><span class="mi" style="color: #099;">2</span><span class="p">,</span> <span class="mi" style="color: #099;">0</span><span class="p">,</span> <span class="mi" style="color: #099;">1</span><span class="p">,</span> <span class="mi" style="color: #099;">1</span><span class="p">],</span></span>
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183
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<pre style="margin: 0;"> <span id="LC183" class="line" lang="python"> <span class="p">[</span><span class="mi" style="color: #099;">3</span><span class="p">,</span> <span class="mi" style="color: #099;">1</span><span class="p">,</span> <span class="mi" style="color: #099;">0</span><span class="p">,</span> <span class="mi" style="color: #099;">1</span><span class="p">],</span></span>
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184
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<pre style="margin: 0;"> <span id="LC184" class="line" lang="python"> <span class="p">[</span><span class="mi" style="color: #099;">3</span><span class="p">,</span> <span class="mi" style="color: #099;">1</span><span class="p">,</span> <span class="mi" style="color: #099;">1</span><span class="p">,</span> <span class="mi" style="color: #099;">0</span><span class="p">],</span></span>
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<pre style="margin: 0;">-<span id="LC185" class="line" lang="python"> <span class="idiff left right"> </span><span class="p">],</span> <span class="n" style="color: #333;">ids</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">sample_ids</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC185" class="line" lang="python"> <span class="p">],</span> <span class="n" style="color: #333;">ids</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">sample_ids</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC186" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC187" class="line" lang="python"> <span class="n" style="color: #333;">dm</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">qiime2</span><span class="p">.</span><span class="n" style="color: #333;">Artifact</span><span class="p">.</span><span class="n" style="color: #333;">import_data</span><span class="p">(</span><span class="s" style="color: #d14;">'DistanceMatrix'</span><span class="p">,</span> <span class="n" style="color: #333;">distance_matrix</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC188" class="line" lang="python"> <span class="n" style="color: #333;">categories</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">pd</span><span class="p">.</span><span class="n" style="color: #333;">Series</span><span class="p">((</span><span class="s" style="color: #d14;">'fat'</span><span class="p">,</span> <span class="s" style="color: #d14;">'skinny'</span><span class="p">,</span> <span class="s" style="color: #d14;">'skinny'</span><span class="p">,</span> <span class="s" style="color: #d14;">'skinny'</span><span class="p">),</span></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -212,7 +212,7 @@ class EstimatorsTests(SampleClassifierTestPluginBase):</td>
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<pre style="margin: 0;"> <span id="LC212" class="line" lang="python"> <span class="p">[</span><span class="mi" style="color: #099;">2</span><span class="p">,</span> <span class="mi" style="color: #099;">0</span><span class="p">,</span> <span class="mi" style="color: #099;">3</span><span class="p">,</span> <span class="mi" style="color: #099;">4</span><span class="p">],</span></span>
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<pre style="margin: 0;"> <span id="LC213" class="line" lang="python"> <span class="p">[</span><span class="mi" style="color: #099;">1</span><span class="p">,</span> <span class="mi" style="color: #099;">3</span><span class="p">,</span> <span class="mi" style="color: #099;">0</span><span class="p">,</span> <span class="mi" style="color: #099;">3</span><span class="p">],</span></span>
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<pre style="margin: 0;"> <span id="LC214" class="line" lang="python"> <span class="p">[</span><span class="mi" style="color: #099;">5</span><span class="p">,</span> <span class="mi" style="color: #099;">4</span><span class="p">,</span> <span class="mi" style="color: #099;">3</span><span class="p">,</span> <span class="mi" style="color: #099;">0</span><span class="p">],</span></span>
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<pre style="margin: 0;">-<span id="LC215" class="line" lang="python"> <span class="idiff left right"> </span><span class="p">],</span> <span class="n" style="color: #333;">ids</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">sample_ids</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC215" class="line" lang="python"> <span class="p">],</span> <span class="n" style="color: #333;">ids</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">sample_ids</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC216" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC217" class="line" lang="python"> <span class="n" style="color: #333;">dm</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">qiime2</span><span class="p">.</span><span class="n" style="color: #333;">Artifact</span><span class="p">.</span><span class="n" style="color: #333;">import_data</span><span class="p">(</span><span class="s" style="color: #d14;">'DistanceMatrix'</span><span class="p">,</span> <span class="n" style="color: #333;">distance_matrix</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC218" class="line" lang="python"> <span class="n" style="color: #333;">categories</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">pd</span><span class="p">.</span><span class="n" style="color: #333;">Series</span><span class="p">((</span><span class="s" style="color: #d14;">'fat'</span><span class="p">,</span> <span class="s" style="color: #d14;">'skinny'</span><span class="p">,</span> <span class="s" style="color: #d14;">'skinny'</span><span class="p">,</span> <span class="s" style="color: #d14;">'skinny'</span><span class="p">),</span></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -251,6 +251,20 @@ class EstimatorsTests(SampleClassifierTestPluginBase):</td>
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<pre style="margin: 0;"> <span id="LC251" class="line" lang="python"> <span class="n" style="color: #333;">msg</span><span class="o" style="font-weight: 600;">=</span><span class="s" style="color: #d14;">'Accuracy of %s classifier was %f, but expected %f'</span> <span class="o" style="font-weight: 600;">%</span> <span class="p">(</span></span>
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<pre style="margin: 0;"> <span id="LC252" class="line" lang="python"> <span class="n" style="color: #333;">classifier</span><span class="p">,</span> <span class="n" style="color: #333;">accuracy</span><span class="p">,</span> <span class="n" style="color: #333;">seeded_results</span><span class="p">[</span><span class="n" style="color: #333;">classifier</span><span class="p">]))</span></span>
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<pre style="margin: 0;"> <span id="LC253" class="line" lang="python"></span>
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<pre style="margin: 0;">+<span id="LC254" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># test if training classifier with pipeline classify_samples raises</span></span>
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<pre style="margin: 0;">+<span id="LC255" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># warning when test_size = 0.0</span></span>
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<pre style="margin: 0;">+<span id="LC256" class="line" lang="python"> <span class="k" style="font-weight: 600;">def</span> <span class="nf" style="color: #900; font-weight: 600;">test_classify_samples_w_all_train_set</span><span class="p">(</span><span class="bp" style="color: #999;">self</span><span class="p">):</span></span>
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<pre style="margin: 0;">+<span id="LC257" class="line" lang="python"> <span class="k" style="font-weight: 600;">with</span> <span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">assertWarnsRegex</span><span class="p">(</span><span class="nb" style="color: #0086b3;">Warning</span><span class="p">,</span> <span class="s" style="color: #d14;">"not representative of "</span></span>
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258
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<pre style="margin: 0;">+<span id="LC258" class="line" lang="python"> <span class="s" style="color: #d14;">"your model's performance"</span><span class="p">):</span></span>
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259
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<pre style="margin: 0;">+<span id="LC259" class="line" lang="python"> <span class="n" style="color: #333;">table_fp</span> <span class="o" style="font-weight: 600;">=</span> <span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">get_data_path</span><span class="p">(</span><span class="s" style="color: #d14;">'chardonnay.table.qza'</span><span class="p">)</span></span>
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260
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<pre style="margin: 0;">+<span id="LC260" class="line" lang="python"> <span class="n" style="color: #333;">table</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">qiime2</span><span class="p">.</span><span class="n" style="color: #333;">Artifact</span><span class="p">.</span><span class="n" style="color: #333;">load</span><span class="p">(</span><span class="n" style="color: #333;">table_fp</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC261" class="line" lang="python"> <span class="n" style="color: #333;">sample_classifier</span><span class="p">.</span><span class="n" style="color: #333;">actions</span><span class="p">.</span><span class="n" style="color: #333;">classify_samples</span><span class="p">(</span></span>
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262
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<pre style="margin: 0;">+<span id="LC262" class="line" lang="python"> <span class="n" style="color: #333;">table</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">table</span><span class="p">,</span> <span class="n" style="color: #333;">metadata</span><span class="o" style="font-weight: 600;">=</span><span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">mdc_chard_fp</span><span class="p">,</span></span>
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263
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<pre style="margin: 0;">+<span id="LC263" class="line" lang="python"> <span class="n" style="color: #333;">test_size</span><span class="o" style="font-weight: 600;">=</span><span class="mf" style="color: #099;">0.0</span><span class="p">,</span> <span class="n" style="color: #333;">cv</span><span class="o" style="font-weight: 600;">=</span><span class="mi" style="color: #099;">1</span><span class="p">,</span> <span class="n" style="color: #333;">n_estimators</span><span class="o" style="font-weight: 600;">=</span><span class="mi" style="color: #099;">10</span><span class="p">,</span> <span class="n" style="color: #333;">n_jobs</span><span class="o" style="font-weight: 600;">=</span><span class="mi" style="color: #099;">1</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC264" class="line" lang="python"> <span class="n" style="color: #333;">estimator</span><span class="o" style="font-weight: 600;">=</span><span class="s" style="color: #d14;">'RandomForestClassifier'</span><span class="p">,</span> <span class="n" style="color: #333;">random_state</span><span class="o" style="font-weight: 600;">=</span><span class="mi" style="color: #099;">123</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC265" class="line" lang="python"> <span class="n" style="color: #333;">parameter_tuning</span><span class="o" style="font-weight: 600;">=</span><span class="bp" style="color: #999;">False</span><span class="p">,</span> <span class="n" style="color: #333;">optimize_feature_selection</span><span class="o" style="font-weight: 600;">=</span><span class="bp" style="color: #999;">False</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC266" class="line" lang="python"> <span class="n" style="color: #333;">missing_samples</span><span class="o" style="font-weight: 600;">=</span><span class="s" style="color: #d14;">'ignore'</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC267" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC268" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># test that the plugin methods/visualizers work</span></span>
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<pre style="margin: 0;"> <span id="LC269" class="line" lang="python"> <span class="k" style="font-weight: 600;">def</span> <span class="nf" style="color: #900; font-weight: 600;">test_regress_samples_ncv</span><span class="p">(</span><span class="bp" style="color: #999;">self</span><span class="p">):</span></span>
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<pre style="margin: 0;"> <span id="LC270" class="line" lang="python"> <span class="n" style="color: #333;">y_pred</span><span class="p">,</span> <span class="n" style="color: #333;">importances</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">regress_samples_ncv</span><span class="p">(</span></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -289,7 +303,8 @@ class EstimatorsTests(SampleClassifierTestPluginBase):</td>
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<pre style="margin: 0;"> <span id="LC303" class="line" lang="python"> <span class="n" style="color: #333;">name</span><span class="o" style="font-weight: 600;">=</span><span class="s" style="color: #d14;">'prediction'</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC304" class="line" lang="python"> <span class="n" style="color: #333;">exp_importances</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">pd</span><span class="p">.</span><span class="n" style="color: #333;">DataFrame</span><span class="p">(</span></span>
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305
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<pre style="margin: 0;"> <span id="LC305" class="line" lang="python"> <span class="p">[</span><span class="mf" style="color: #099;">0.595111111111111</span><span class="p">,</span> <span class="mf" style="color: #099;">0.23155555555555551</span><span class="p">,</span> <span class="mf" style="color: #099;">0.17333333333333334</span><span class="p">],</span></span>
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<pre style="margin: 0;">-<span id="LC292" class="line" lang="python"> <span class="n" style="color: #333;">index</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">pd</span><span class="p">.</span><span class="n" style="color: #333;">Index</span><span class="p">([</span><span class="s" style="color: #d14;">'o3'</span><span class="p">,</span> <span class="s" style="color: #d14;">'o1'</span><span class="p">,</span> <span class="s" style="color: #d14;">'o2'</span><span class="p">]),</span> <span class="n" style="color: #333;">columns</span><span class="o" style="font-weight: 600;">=</span><span class="p">[</span><span class="s" style="color: #d14;">'importance'</span><span class="p">])</span></span>
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<pre style="margin: 0;">+<span id="LC306" class="line" lang="python"> <span class="n" style="color: #333;">index</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">pd</span><span class="p">.</span><span class="n" style="color: #333;">Index</span><span class="p">([</span><span class="s" style="color: #d14;">'o3'</span><span class="p">,</span> <span class="s" style="color: #d14;">'o1'</span><span class="p">,</span> <span class="s" style="color: #d14;">'o2'</span><span class="p">],</span> <span class="n" style="color: #333;">name</span><span class="o" style="font-weight: 600;">=</span><span class="s" style="color: #d14;">'feature'</span><span class="p">),</span></span>
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<pre style="margin: 0;">+<span id="LC307" class="line" lang="python"> <span class="n" style="color: #333;">columns</span><span class="o" style="font-weight: 600;">=</span><span class="p">[</span><span class="s" style="color: #d14;">'importance'</span><span class="p">])</span></span>
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<pre style="margin: 0;"> <span id="LC308" class="line" lang="python"> <span class="n" style="color: #333;">exp_probabilities</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">pd</span><span class="p">.</span><span class="n" style="color: #333;">DataFrame</span><span class="p">(</span></span>
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<pre style="margin: 0;"> <span id="LC309" class="line" lang="python"> <span class="p">[[</span><span class="mf" style="color: #099;">0.5</span><span class="p">,</span> <span class="mf" style="color: #099;">0.5</span><span class="p">],</span> <span class="p">[</span><span class="mf" style="color: #099;">0.</span><span class="p">,</span> <span class="mf" style="color: #099;">1.</span><span class="p">],</span> <span class="p">[</span><span class="mf" style="color: #099;">0.</span><span class="p">,</span> <span class="mf" style="color: #099;">1.</span><span class="p">],</span> <span class="p">[</span><span class="mf" style="color: #099;">0.5</span><span class="p">,</span> <span class="mf" style="color: #099;">0.5</span><span class="p">],</span> <span class="p">[</span><span class="mf" style="color: #099;">0.5</span><span class="p">,</span> <span class="mf" style="color: #099;">0.5</span><span class="p">],</span></span>
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<pre style="margin: 0;"> <span id="LC310" class="line" lang="python"> <span class="p">[</span><span class="mf" style="color: #099;">0.5</span><span class="p">,</span> <span class="mf" style="color: #099;">0.5</span><span class="p">],</span> <span class="p">[</span><span class="mf" style="color: #099;">0.5</span><span class="p">,</span> <span class="mf" style="color: #099;">0.5</span><span class="p">],</span> <span class="p">[</span><span class="mf" style="color: #099;">0.</span><span class="p">,</span> <span class="mf" style="color: #099;">1.</span><span class="p">],</span> <span class="p">[</span><span class="mf" style="color: #099;">1.</span><span class="p">,</span> <span class="mf" style="color: #099;">0.</span><span class="p">],</span> <span class="p">[</span><span class="mf" style="color: #099;">1.</span><span class="p">,</span> <span class="mf" style="color: #099;">0.</span><span class="p">]],</span></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -390,28 +405,31 @@ class EstimatorsTests(SampleClassifierTestPluginBase):</td>
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<pre style="margin: 0;"> <span id="LC405" class="line" lang="python"> <span class="n" style="color: #333;">missing_samples</span><span class="o" style="font-weight: 600;">=</span><span class="s" style="color: #d14;">'ignore'</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC406" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC407" class="line" lang="python"> <span class="k" style="font-weight: 600;">def</span> <span class="nf" style="color: #900; font-weight: 600;">test_split_table_no_rounding_error</span><span class="p">(</span><span class="bp" style="color: #999;">self</span><span class="p">):</span></span>
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<pre style="margin: 0;">-<span id="LC393" class="line" lang="python"> <span class="n" style="color: #333;">X_train</span><span class="p">,</span> <span class="n" style="color: #333;">X_test</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">split_table</span><span class="p">(</span></span>
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408
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<pre style="margin: 0;">+<span id="LC408" class="line" lang="python"> <span class="n" style="color: #333;">X_train</span><span class="p">,</span> <span class="n" style="color: #333;">X_test</span><span class="p"><span class="idiff left">,</span></span><span class="idiff"> </span><span class="n" style="color: #333;"><span class="idiff">y_train</span></span><span class="p"><span class="idiff">,</span></span><span class="idiff"> </span><span class="n" style="color: #333;"><span class="idiff right">y_test</span></span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">split_table</span><span class="p">(</span></span>
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409
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<pre style="margin: 0;"> <span id="LC409" class="line" lang="python"> <span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">table_chard_fp</span><span class="p">,</span> <span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">mdc_chard_fp</span><span class="p">,</span> <span class="n" style="color: #333;">test_size</span><span class="o" style="font-weight: 600;">=</span><span class="mf" style="color: #099;">0.5</span><span class="p">,</span></span>
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410
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<pre style="margin: 0;"> <span id="LC410" class="line" lang="python"> <span class="n" style="color: #333;">random_state</span><span class="o" style="font-weight: 600;">=</span><span class="mi" style="color: #099;">123</span><span class="p">,</span> <span class="n" style="color: #333;">stratify</span><span class="o" style="font-weight: 600;">=</span><span class="bp" style="color: #999;">True</span><span class="p">,</span> <span class="n" style="color: #333;">missing_samples</span><span class="o" style="font-weight: 600;">=</span><span class="s" style="color: #d14;">'ignore'</span><span class="p">)</span></span>
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411
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<pre style="margin: 0;"> <span id="LC411" class="line" lang="python"> <span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">assertEqual</span><span class="p">(</span><span class="nb" style="color: #0086b3;">len</span><span class="p">(</span><span class="n" style="color: #333;">X_train</span><span class="p">.</span><span class="n" style="color: #333;">ids</span><span class="p">())</span> <span class="o" style="font-weight: 600;">+</span> <span class="nb" style="color: #0086b3;">len</span><span class="p">(</span><span class="n" style="color: #333;">X_test</span><span class="p">.</span><span class="n" style="color: #333;">ids</span><span class="p">()),</span> <span class="mi" style="color: #099;">21</span><span class="p">)</span></span>
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412
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<pre style="margin: 0;">+<span id="LC412" class="line" lang="python"> <span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">assertEqual</span><span class="p">(</span><span class="n" style="color: #333;">y_train</span><span class="p">.</span><span class="n" style="color: #333;">shape</span><span class="p">[</span><span class="mi" style="color: #099;">0</span><span class="p">]</span> <span class="o" style="font-weight: 600;">+</span> <span class="n" style="color: #333;">y_test</span><span class="p">.</span><span class="n" style="color: #333;">shape</span><span class="p">[</span><span class="mi" style="color: #099;">0</span><span class="p">],</span> <span class="mi" style="color: #099;">21</span><span class="p">)</span></span>
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397
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413
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<pre style="margin: 0;"> <span id="LC413" class="line" lang="python"></span>
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398
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414
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<pre style="margin: 0;"> <span id="LC414" class="line" lang="python"> <span class="k" style="font-weight: 600;">def</span> <span class="nf" style="color: #900; font-weight: 600;">test_split_table_no_split</span><span class="p">(</span><span class="bp" style="color: #999;">self</span><span class="p">):</span></span>
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399
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<pre style="margin: 0;">-<span id="LC399" class="line" lang="python"> <span class="n" style="color: #333;">X_train</span><span class="p">,</span> <span class="n" style="color: #333;">X_test</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">split_table</span><span class="p">(</span></span>
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415
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<pre style="margin: 0;">+<span id="LC415" class="line" lang="python"> <span class="n" style="color: #333;">X_train</span><span class="p">,</span> <span class="n" style="color: #333;">X_test</span><span class="p"><span class="idiff left">,</span></span><span class="idiff"> </span><span class="n" style="color: #333;"><span class="idiff">y_train</span></span><span class="p"><span class="idiff">,</span></span><span class="idiff"> </span><span class="n" style="color: #333;"><span class="idiff right">y_test</span></span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">split_table</span><span class="p">(</span></span>
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400
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416
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<pre style="margin: 0;"> <span id="LC416" class="line" lang="python"> <span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">table_chard_fp</span><span class="p">,</span> <span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">mdc_chard_fp</span><span class="p">,</span> <span class="n" style="color: #333;">test_size</span><span class="o" style="font-weight: 600;">=</span><span class="mf" style="color: #099;">0.0</span><span class="p">,</span></span>
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401
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417
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<pre style="margin: 0;"> <span id="LC417" class="line" lang="python"> <span class="n" style="color: #333;">random_state</span><span class="o" style="font-weight: 600;">=</span><span class="mi" style="color: #099;">123</span><span class="p">,</span> <span class="n" style="color: #333;">stratify</span><span class="o" style="font-weight: 600;">=</span><span class="bp" style="color: #999;">True</span><span class="p">,</span> <span class="n" style="color: #333;">missing_samples</span><span class="o" style="font-weight: 600;">=</span><span class="s" style="color: #d14;">'ignore'</span><span class="p">)</span></span>
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402
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418
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<pre style="margin: 0;"> <span id="LC418" class="line" lang="python"> <span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">assertEqual</span><span class="p">(</span><span class="nb" style="color: #0086b3;">len</span><span class="p">(</span><span class="n" style="color: #333;">X_train</span><span class="p">.</span><span class="n" style="color: #333;">ids</span><span class="p">()),</span> <span class="mi" style="color: #099;">21</span><span class="p">)</span></span>
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419
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<pre style="margin: 0;">+<span id="LC419" class="line" lang="python"> <span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">assertEqual</span><span class="p">(</span><span class="n" style="color: #333;">y_train</span><span class="p">.</span><span class="n" style="color: #333;">shape</span><span class="p">[</span><span class="mi" style="color: #099;">0</span><span class="p">],</span> <span class="mi" style="color: #099;">21</span><span class="p">)</span></span>
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403
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420
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<pre style="margin: 0;"> <span id="LC420" class="line" lang="python"></span>
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404
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421
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<pre style="margin: 0;"> <span id="LC421" class="line" lang="python"> <span class="k" style="font-weight: 600;">def</span> <span class="nf" style="color: #900; font-weight: 600;">test_split_table_invalid_test_size</span><span class="p">(</span><span class="bp" style="color: #999;">self</span><span class="p">):</span></span>
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405
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422
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<pre style="margin: 0;"> <span id="LC422" class="line" lang="python"> <span class="k" style="font-weight: 600;">with</span> <span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">assertRaisesRegex</span><span class="p">(</span><span class="nb" style="color: #0086b3;">ValueError</span><span class="p">,</span> <span class="s" style="color: #d14;">"at least two samples"</span><span class="p">):</span></span>
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406
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<pre style="margin: 0;">-<span id="LC406" class="line" lang="python"> <span class="n" style="color: #333;">X_train</span><span class="p">,</span> <span class="n" style="color: #333;">X_test</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">split_table</span><span class="p">(</span></span>
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423
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<pre style="margin: 0;">+<span id="LC423" class="line" lang="python"> <span class="n" style="color: #333;">X_train</span><span class="p">,</span> <span class="n" style="color: #333;">X_test</span><span class="p"><span class="idiff left">,</span></span><span class="idiff"> </span><span class="n" style="color: #333;"><span class="idiff">y_train</span></span><span class="p"><span class="idiff">,</span></span><span class="idiff"> </span><span class="n" style="color: #333;"><span class="idiff right">y_test</span></span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">split_table</span><span class="p">(</span></span>
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407
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424
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<pre style="margin: 0;"> <span id="LC424" class="line" lang="python"> <span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">table_chard_fp</span><span class="p">,</span> <span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">mdc_chard_fp</span><span class="p">,</span> <span class="n" style="color: #333;">test_size</span><span class="o" style="font-weight: 600;">=</span><span class="mf" style="color: #099;">1.0</span><span class="p">,</span></span>
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408
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425
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<pre style="margin: 0;"> <span id="LC425" class="line" lang="python"> <span class="n" style="color: #333;">random_state</span><span class="o" style="font-weight: 600;">=</span><span class="mi" style="color: #099;">123</span><span class="p">,</span> <span class="n" style="color: #333;">stratify</span><span class="o" style="font-weight: 600;">=</span><span class="bp" style="color: #999;">True</span><span class="p">,</span> <span class="n" style="color: #333;">missing_samples</span><span class="o" style="font-weight: 600;">=</span><span class="s" style="color: #d14;">'ignore'</span><span class="p">)</span></span>
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409
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426
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<pre style="margin: 0;"> <span id="LC426" class="line" lang="python"></span>
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427
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<pre style="margin: 0;"> <span id="LC427" class="line" lang="python"> <span class="k" style="font-weight: 600;">def</span> <span class="nf" style="color: #900; font-weight: 600;">test_split_table_percnorm</span><span class="p">(</span><span class="bp" style="color: #999;">self</span><span class="p">):</span></span>
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<pre style="margin: 0;">-<span id="LC411" class="line" lang="python"> <span class="n" style="color: #333;">X_train</span><span class="p">,</span> <span class="n" style="color: #333;">X_test</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">split_table</span><span class="p">(</span></span>
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<pre style="margin: 0;">+<span id="LC428" class="line" lang="python"> <span class="n" style="color: #333;">X_train</span><span class="p">,</span> <span class="n" style="color: #333;">X_test</span><span class="p"><span class="idiff left">,</span></span><span class="idiff"> </span><span class="n" style="color: #333;"><span class="idiff">y_train</span></span><span class="p"><span class="idiff">,</span></span><span class="idiff"> </span><span class="n" style="color: #333;"><span class="idiff right">y_test</span></span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">split_table</span><span class="p">(</span></span>
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<pre style="margin: 0;"> <span id="LC429" class="line" lang="python"> <span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">table_percnorm</span><span class="p">,</span> <span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">mdc_percnorm</span><span class="p">,</span> <span class="n" style="color: #333;">test_size</span><span class="o" style="font-weight: 600;">=</span><span class="mf" style="color: #099;">0.5</span><span class="p">,</span></span>
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<pre style="margin: 0;"> <span id="LC430" class="line" lang="python"> <span class="n" style="color: #333;">random_state</span><span class="o" style="font-weight: 600;">=</span><span class="mi" style="color: #099;">123</span><span class="p">,</span> <span class="n" style="color: #333;">stratify</span><span class="o" style="font-weight: 600;">=</span><span class="bp" style="color: #999;">True</span><span class="p">,</span> <span class="n" style="color: #333;">missing_samples</span><span class="o" style="font-weight: 600;">=</span><span class="s" style="color: #d14;">'ignore'</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC431" class="line" lang="python"> <span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">assertEqual</span><span class="p">(</span><span class="nb" style="color: #0086b3;">len</span><span class="p">(</span><span class="n" style="color: #333;">X_train</span><span class="p">.</span><span class="n" style="color: #333;">ids</span><span class="p">())</span> <span class="o" style="font-weight: 600;">+</span> <span class="nb" style="color: #0086b3;">len</span><span class="p">(</span><span class="n" style="color: #333;">X_test</span><span class="p">.</span><span class="n" style="color: #333;">ids</span><span class="p">()),</span> <span class="mi" style="color: #099;">4</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC432" class="line" lang="python"> <span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">assertEqual</span><span class="p">(</span><span class="n" style="color: #333;">y_train</span><span class="p">.</span><span class="n" style="color: #333;">shape</span><span class="p">[</span><span class="mi" style="color: #099;">0</span><span class="p">]</span> <span class="o" style="font-weight: 600;">+</span> <span class="n" style="color: #333;">y_test</span><span class="p">.</span><span class="n" style="color: #333;">shape</span><span class="p">[</span><span class="mi" style="color: #099;">0</span><span class="p">],</span> <span class="mi" style="color: #099;">4</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC433" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC434" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># test experimental functions</span></span>
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<pre style="margin: 0;"> <span id="LC435" class="line" lang="python"> <span class="k" style="font-weight: 600;">def</span> <span class="nf" style="color: #900; font-weight: 600;">test_detect_outliers</span><span class="p">(</span><span class="bp" style="color: #999;">self</span><span class="p">):</span></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -450,6 +468,7 @@ class EstimatorsTests(SampleClassifierTestPluginBase):</td>
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<pre style="margin: 0;"> <span id="LC468" class="line" lang="python"> <span class="n" style="color: #333;">sample_ids</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">pred</span><span class="p">.</span><span class="n" style="color: #333;">index</span><span class="p">.</span><span class="n" style="color: #333;">intersection</span><span class="p">(</span><span class="n" style="color: #333;">exp</span><span class="p">.</span><span class="n" style="color: #333;">index</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC469" class="line" lang="python"> <span class="n" style="color: #333;">pred</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">pred</span><span class="p">.</span><span class="n" style="color: #333;">loc</span><span class="p">[</span><span class="n" style="color: #333;">sample_ids</span><span class="p">]</span></span>
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<pre style="margin: 0;"> <span id="LC470" class="line" lang="python"> <span class="n" style="color: #333;">exp</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">exp</span><span class="p">.</span><span class="n" style="color: #333;">loc</span><span class="p">[</span><span class="n" style="color: #333;">sample_ids</span><span class="p">]</span></span>
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<pre style="margin: 0;">+<span id="LC471" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># verify predictions:</span></span>
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<pre style="margin: 0;"> <span id="LC472" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># test that expected number of correct results is achieved (these</span></span>
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<pre style="margin: 0;"> <span id="LC473" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># are mostly quite high as we would expect (total n=21))</span></span>
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<pre style="margin: 0;"> <span id="LC474" class="line" lang="python"> <span class="n" style="color: #333;">correct_results</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">np</span><span class="p">.</span><span class="nb" style="color: #0086b3;">sum</span><span class="p">(</span><span class="n" style="color: #333;">pred</span> <span class="o" style="font-weight: 600;">==</span> <span class="n" style="color: #333;">exp</span><span class="p">)</span></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -458,6 +477,17 @@ class EstimatorsTests(SampleClassifierTestPluginBase):</td>
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<pre style="margin: 0;"> <span id="LC477" class="line" lang="python"> <span class="n" style="color: #333;">msg</span><span class="o" style="font-weight: 600;">=</span><span class="s" style="color: #d14;">'Accuracy of %s classifier was %f, but expected %f'</span> <span class="o" style="font-weight: 600;">%</span> <span class="p">(</span></span>
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<pre style="margin: 0;"> <span id="LC478" class="line" lang="python"> <span class="n" style="color: #333;">classifier</span><span class="p">,</span> <span class="n" style="color: #333;">correct_results</span><span class="p">,</span></span>
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<pre style="margin: 0;"> <span id="LC479" class="line" lang="python"> <span class="n" style="color: #333;">seeded_predict_results</span><span class="p">[</span><span class="n" style="color: #333;">classifier</span><span class="p">]))</span></span>
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<pre style="margin: 0;">+<span id="LC480" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># verify probabilities</span></span>
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<pre style="margin: 0;">+<span id="LC481" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># test whether all are in correct range (0 to 1)</span></span>
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<pre style="margin: 0;">+<span id="LC482" class="line" lang="python"> <span class="n" style="color: #333;">ls_pred_classes</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">prob</span><span class="p">.</span><span class="n" style="color: #333;">columns</span><span class="p">.</span><span class="n" style="color: #333;">tolist</span><span class="p">()</span></span>
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<pre style="margin: 0;">+<span id="LC483" class="line" lang="python"> <span class="n" style="color: #333;">ls_correct_range</span> <span class="o" style="font-weight: 600;">=</span> <span class="p">[</span><span class="n" style="color: #333;">col</span> <span class="k" style="font-weight: 600;">for</span> <span class="n" style="color: #333;">col</span> <span class="ow" style="font-weight: 600;">in</span> <span class="n" style="color: #333;">ls_pred_classes</span> <span class="k" style="font-weight: 600;">if</span></span>
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<pre style="margin: 0;">+<span id="LC484" class="line" lang="python"> <span class="n" style="color: #333;">prob</span><span class="p">[</span><span class="n" style="color: #333;">col</span><span class="p">].</span><span class="n" style="color: #333;">between</span><span class="p">(</span></span>
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<pre style="margin: 0;">+<span id="LC485" class="line" lang="python"> <span class="mi" style="color: #099;">0</span><span class="p">,</span> <span class="mi" style="color: #099;">1</span><span class="p">,</span> <span class="n" style="color: #333;">inclusive</span><span class="o" style="font-weight: 600;">=</span><span class="bp" style="color: #999;">True</span><span class="p">).</span><span class="nb" style="color: #0086b3;">all</span><span class="p">()]</span></span>
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<pre style="margin: 0;">+<span id="LC486" class="line" lang="python"> <span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">assertEqual</span><span class="p">(</span><span class="nb" style="color: #0086b3;">len</span><span class="p">(</span><span class="n" style="color: #333;">ls_correct_range</span><span class="p">),</span> <span class="n" style="color: #333;">prob</span><span class="p">.</span><span class="n" style="color: #333;">shape</span><span class="p">[</span><span class="mi" style="color: #099;">1</span><span class="p">],</span></span>
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<pre style="margin: 0;">+<span id="LC487" class="line" lang="python"> <span class="n" style="color: #333;">msg</span><span class="o" style="font-weight: 600;">=</span><span class="s" style="color: #d14;">'Predicted probabilities of class {}'</span></span>
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<pre style="margin: 0;">+<span id="LC488" class="line" lang="python"> <span class="s" style="color: #d14;">'are not in range [0,1]'</span><span class="p">.</span><span class="nb" style="color: #0086b3;">format</span><span class="p">(</span></span>
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<pre style="margin: 0;">+<span id="LC489" class="line" lang="python"> <span class="p">[</span><span class="n" style="color: #333;">col</span> <span class="k" style="font-weight: 600;">for</span> <span class="n" style="color: #333;">col</span> <span class="ow" style="font-weight: 600;">in</span> <span class="n" style="color: #333;">ls_pred_classes</span></span>
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<pre style="margin: 0;">+<span id="LC490" class="line" lang="python"> <span class="k" style="font-weight: 600;">if</span> <span class="n" style="color: #333;">col</span> <span class="ow" style="font-weight: 600;">not</span> <span class="ow" style="font-weight: 600;">in</span> <span class="n" style="color: #333;">ls_correct_range</span><span class="p">]))</span></span>
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<pre style="margin: 0;"> <span id="LC491" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC492" class="line" lang="python"> <span class="k" style="font-weight: 600;">def</span> <span class="nf" style="color: #900; font-weight: 600;">test_predict_regressions</span><span class="p">(</span><span class="bp" style="color: #999;">self</span><span class="p">):</span></span>
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<pre style="margin: 0;"> <span id="LC493" class="line" lang="python"> <span class="k" style="font-weight: 600;">for</span> <span class="n" style="color: #333;">regressor</span> <span class="ow" style="font-weight: 600;">in</span> <span class="p">[</span><span class="s" style="color: #d14;">'RandomForestRegressor'</span><span class="p">,</span> <span class="s" style="color: #d14;">'ExtraTreesRegressor'</span><span class="p">,</span></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -526,7 +556,7 @@ seeded_results = {</td>
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<pre style="margin: 0;"> <span id="LC556" class="line" lang="python"> <span class="s" style="color: #d14;">'ExtraTreesClassifier'</span><span class="p">:</span> <span class="mf" style="color: #099;">0.454545454545</span><span class="p">,</span></span>
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557
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<pre style="margin: 0;"> <span id="LC557" class="line" lang="python"> <span class="s" style="color: #d14;">'GradientBoostingClassifier'</span><span class="p">:</span> <span class="mf" style="color: #099;">0.272727272727</span><span class="p">,</span></span>
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558
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<pre style="margin: 0;"> <span id="LC558" class="line" lang="python"> <span class="s" style="color: #d14;">'AdaBoostClassifier'</span><span class="p">:</span> <span class="mf" style="color: #099;">0.272727272727</span><span class="p">,</span></span>
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<pre style="margin: 0;">-<span id="LC529" class="line" lang="python"> <span class="s" style="color: #d14;">'LinearSVC'</span><span class="p">:</span> <span class="mf" style="color: #099;">0.<span class="idiff left right">727272727273</span></span><span class="p">,</span></span>
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559
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<pre style="margin: 0;">+<span id="LC559" class="line" lang="python"> <span class="s" style="color: #d14;">'LinearSVC'</span><span class="p">:</span> <span class="mf" style="color: #099;">0.<span class="idiff left right">818182</span></span><span class="p">,</span></span>
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<pre style="margin: 0;"> <span id="LC560" class="line" lang="python"> <span class="s" style="color: #d14;">'SVC'</span><span class="p">:</span> <span class="mf" style="color: #099;">0.36363636363636365</span><span class="p">,</span></span>
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561
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<pre style="margin: 0;"> <span id="LC561" class="line" lang="python"> <span class="s" style="color: #d14;">'KNeighborsClassifier'</span><span class="p">:</span> <span class="mf" style="color: #099;">0.363636363636</span><span class="p">,</span></span>
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<pre style="margin: 0;"> <span id="LC562" class="line" lang="python"> <span class="s" style="color: #d14;">'RandomForestRegressor'</span><span class="p">:</span> <span class="mf" style="color: #099;">23.226508</span><span class="p">,</span></span>
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<a href="https://salsa.debian.org/med-team/q2-sample-classifier/-/commit/7c4b78faf33bc50e958843964685cf5d73d1374d#479a2fb6d0756ddb6a08bc0ddf764b87668ecbb6"><strong>q2_sample_classifier/tests/test_types_formats_transformers.py</strong></a>
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<pre style="margin: 0;"> <span id="LC1" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># ----------------------------------------------------------------------------</span></span>
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<pre style="margin: 0;">-<span id="LC2" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Copyright (c) 2017-202<span class="idiff left right">0</span>, QIIME 2 development team.</span></span>
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<pre style="margin: 0;">+<span id="LC2" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Copyright (c) 2017-202<span class="idiff left right">1</span>, QIIME 2 development team.</span></span>
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<pre style="margin: 0;"> <span id="LC3" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;">#</span></span>
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<pre style="margin: 0;"> <span id="LC4" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Distributed under the terms of the Modified BSD License.</span></span>
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<pre style="margin: 0;"> <span id="LC5" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;">#</span></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -7,7 +7,7 @@</td>
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<pre style="margin: 0;"> <span id="LC7" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># ----------------------------------------------------------------------------</span></span>
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<pre style="margin: 0;"> <span id="LC8" class="line" lang="python"><span class="kn" style="font-weight: 600;">import</span> <span class="nn" style="color: #555;">os</span></span>
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<pre style="margin: 0;"> <span id="LC9" class="line" lang="python"><span class="kn" style="font-weight: 600;">import</span> <span class="nn" style="color: #555;">pandas</span> <span class="k" style="font-weight: 600;">as</span> <span class="n" style="color: #333;">pd</span></span>
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<pre style="margin: 0;">-<span id="LC10" class="line" lang="python"><span class="kn" style="font-weight: 600;">import</span> <span class="nn" style="color: #555;">pandas.<span class="idiff left right">util.</span>testing</span> <span class="k" style="font-weight: 600;">as</span> <span class="n" style="color: #333;">pdt</span></span>
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<pre style="margin: 0;">+<span id="LC10" class="line" lang="python"><span class="kn" style="font-weight: 600;">import</span> <span class="nn" style="color: #555;">pandas.testing</span> <span class="k" style="font-weight: 600;">as</span> <span class="n" style="color: #333;">pdt</span></span>
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<pre style="margin: 0;"> <span id="LC11" class="line" lang="python"><span class="kn" style="font-weight: 600;">import</span> <span class="nn" style="color: #555;">numpy</span> <span class="k" style="font-weight: 600;">as</span> <span class="n" style="color: #333;">np</span></span>
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<pre style="margin: 0;"> <span id="LC12" class="line" lang="python"><span class="kn" style="font-weight: 600;">import</span> <span class="nn" style="color: #555;">shutil</span></span>
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<pre style="margin: 0;"> <span id="LC13" class="line" lang="python"><span class="kn" style="font-weight: 600;">import</span> <span class="nn" style="color: #555;">tempfile</span></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -28,7 +28,8 @@ from q2_sample_classifier import (</td>
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<pre style="margin: 0;"> <span id="LC28" class="line" lang="python"> <span class="n" style="color: #333;">RegressorPredictions</span><span class="p">,</span> <span class="n" style="color: #333;">ImportanceFormat</span><span class="p">,</span> <span class="n" style="color: #333;">ImportanceDirectoryFormat</span><span class="p">,</span></span>
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<pre style="margin: 0;"> <span id="LC29" class="line" lang="python"> <span class="n" style="color: #333;">Importance</span><span class="p">,</span> <span class="n" style="color: #333;">PickleFormat</span><span class="p">,</span> <span class="n" style="color: #333;">ProbabilitiesFormat</span><span class="p">,</span></span>
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<pre style="margin: 0;"> <span id="LC30" class="line" lang="python"> <span class="n" style="color: #333;">ProbabilitiesDirectoryFormat</span><span class="p">,</span> <span class="n" style="color: #333;">Probabilities</span><span class="p">,</span> <span class="n" style="color: #333;">Classifier</span><span class="p">,</span> <span class="n" style="color: #333;">Regressor</span><span class="p">,</span></span>
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<pre style="margin: 0;">-<span id="LC31" class="line" lang="python"> <span class="n" style="color: #333;">SampleEstimator</span><span class="p">,</span> <span class="n" style="color: #333;">SampleEstimatorDirFmt</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC31" class="line" lang="python"> <span class="n" style="color: #333;">SampleEstimator</span><span class="p">,</span> <span class="n" style="color: #333;">SampleEstimatorDirFmt</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC32" class="line" lang="python"> <span class="n" style="color: #333;">TrueTargetsDirectoryFormat</span><span class="p">,</span> <span class="n" style="color: #333;">TrueTargets</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC33" class="line" lang="python"><span class="kn" style="font-weight: 600;">from</span> <span class="nn" style="color: #555;">q2_sample_classifier.visuals</span> <span class="kn" style="font-weight: 600;">import</span> <span class="p">(</span></span>
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<pre style="margin: 0;"> <span id="LC34" class="line" lang="python"> <span class="n" style="color: #333;">_custom_palettes</span><span class="p">,</span> <span class="n" style="color: #333;">_plot_heatmap_from_confusion_matrix</span><span class="p">,)</span></span>
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<pre style="margin: 0;"> <span id="LC35" class="line" lang="python"><span class="kn" style="font-weight: 600;">from</span> <span class="nn" style="color: #555;">q2_sample_classifier._format</span> <span class="kn" style="font-weight: 600;">import</span> <span class="n" style="color: #333;">JSONFormat</span></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -356,6 +357,21 @@ class TestSemanticTypes(SampleClassifierTestPluginBase):</td>
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<pre style="margin: 0;"> <span id="LC357" class="line" lang="python"> <span class="k" style="font-weight: 600;">for</span> <span class="n" style="color: #333;">palette</span> <span class="ow" style="font-weight: 600;">in</span> <span class="n" style="color: #333;">_custom_palettes</span><span class="p">().</span><span class="n" style="color: #333;">keys</span><span class="p">():</span></span>
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<pre style="margin: 0;"> <span id="LC358" class="line" lang="python"> <span class="n" style="color: #333;">_plot_heatmap_from_confusion_matrix</span><span class="p">(</span><span class="n" style="color: #333;">confused</span><span class="p">,</span> <span class="n" style="color: #333;">palette</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC359" class="line" lang="python"></span>
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<pre style="margin: 0;">+<span id="LC360" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># test TrueTarget</span></span>
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<pre style="margin: 0;">+<span id="LC361" class="line" lang="python"> <span class="k" style="font-weight: 600;">def</span> <span class="nf" style="color: #900; font-weight: 600;">test_TrueTargets_semantic_type_registration</span><span class="p">(</span><span class="bp" style="color: #999;">self</span><span class="p">):</span></span>
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<pre style="margin: 0;">+<span id="LC362" class="line" lang="python"> <span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">assertRegisteredSemanticType</span><span class="p">(</span><span class="n" style="color: #333;">TrueTargets</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC363" class="line" lang="python"></span>
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<pre style="margin: 0;">+<span id="LC364" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># test TrueTargetDirectoryFormats</span></span>
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<pre style="margin: 0;">+<span id="LC365" class="line" lang="python"> <span class="k" style="font-weight: 600;">def</span> <span class="nf" style="color: #900; font-weight: 600;">test_TrueTargets_dir_fmt_validate_positive</span><span class="p">(</span><span class="bp" style="color: #999;">self</span><span class="p">):</span></span>
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<pre style="margin: 0;">+<span id="LC366" class="line" lang="python"> <span class="n" style="color: #333;">filepath</span> <span class="o" style="font-weight: 600;">=</span> <span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">get_data_path</span><span class="p">(</span><span class="s" style="color: #d14;">'true_targets.tsv'</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC367" class="line" lang="python"> <span class="n" style="color: #333;">shutil</span><span class="p">.</span><span class="n" style="color: #333;">copy</span><span class="p">(</span><span class="n" style="color: #333;">filepath</span><span class="p">,</span> <span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">temp_dir</span><span class="p">.</span><span class="n" style="color: #333;">name</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC368" class="line" lang="python"> <span class="nb" style="color: #0086b3;">format</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">TrueTargetsDirectoryFormat</span><span class="p">(</span><span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">temp_dir</span><span class="p">.</span><span class="n" style="color: #333;">name</span><span class="p">,</span> <span class="n" style="color: #333;">mode</span><span class="o" style="font-weight: 600;">=</span><span class="s" style="color: #d14;">'r'</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC369" class="line" lang="python"> <span class="nb" style="color: #0086b3;">format</span><span class="p">.</span><span class="n" style="color: #333;">validate</span><span class="p">()</span></span>
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<pre style="margin: 0;">+<span id="LC371" class="line" lang="python"> <span class="k" style="font-weight: 600;">def</span> <span class="nf" style="color: #900; font-weight: 600;">test_TrueTarget_to_TrueTargets_dir_fmt_registration</span><span class="p">(</span><span class="bp" style="color: #999;">self</span><span class="p">):</span></span>
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<pre style="margin: 0;">+<span id="LC372" class="line" lang="python"> <span class="bp" style="color: #999;">self</span><span class="p">.</span><span class="n" style="color: #333;">assertSemanticTypeRegisteredToFormat</span><span class="p">(</span></span>
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<pre style="margin: 0;">+<span id="LC373" class="line" lang="python"> <span class="n" style="color: #333;">SampleData</span><span class="p">[</span><span class="n" style="color: #333;">TrueTargets</span><span class="p">],</span> <span class="n" style="color: #333;">TrueTargetsDirectoryFormat</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC375" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC376" class="line" lang="python"><span class="k" style="font-weight: 600;">class</span> <span class="nc" style="color: #458; font-weight: 600;">TestTypes</span><span class="p">(</span><span class="n" style="color: #333;">SampleClassifierTestPluginBase</span><span class="p">):</span></span>
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<pre style="margin: 0;"> <span id="LC377" class="line" lang="python"> <span class="k" style="font-weight: 600;">def</span> <span class="nf" style="color: #900; font-weight: 600;">test_sample_estimator_semantic_type_registration</span><span class="p">(</span><span class="bp" style="color: #999;">self</span><span class="p">):</span></span>
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<pre style="margin: 0;"> <span id="LC1" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># ----------------------------------------------------------------------------</span></span>
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<pre style="margin: 0;">-<span id="LC2" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Copyright (c) 2017-202<span class="idiff left right">0</span>, QIIME 2 development team.</span></span>
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<pre style="margin: 0;">+<span id="LC2" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Copyright (c) 2017-202<span class="idiff left right">1</span>, QIIME 2 development team.</span></span>
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<pre style="margin: 0;"> <span id="LC3" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;">#</span></span>
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<pre style="margin: 0;"> <span id="LC4" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Distributed under the terms of the Modified BSD License.</span></span>
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<pre style="margin: 0;"> <span id="LC5" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;">#</span></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -12,7 +12,7 @@ from sklearn.svm import LinearSVC</td>
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<pre style="margin: 0;"> <span id="LC12" class="line" lang="python"><span class="kn" style="font-weight: 600;">from</span> <span class="nn" style="color: #555;">sklearn.feature_extraction</span> <span class="kn" style="font-weight: 600;">import</span> <span class="n" style="color: #333;">DictVectorizer</span></span>
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<pre style="margin: 0;"> <span id="LC13" class="line" lang="python"><span class="kn" style="font-weight: 600;">from</span> <span class="nn" style="color: #555;">sklearn.pipeline</span> <span class="kn" style="font-weight: 600;">import</span> <span class="n" style="color: #333;">Pipeline</span></span>
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<pre style="margin: 0;"> <span id="LC14" class="line" lang="python"><span class="kn" style="font-weight: 600;">from</span> <span class="nn" style="color: #555;">sklearn.ensemble</span> <span class="kn" style="font-weight: 600;">import</span> <span class="n" style="color: #333;">RandomForestClassifier</span></span>
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<pre style="margin: 0;">-<span id="LC15" class="line" lang="python"><span class="kn" style="font-weight: 600;">import</span> <span class="nn" style="color: #555;">pandas.<span class="idiff left right">util.</span>testing</span> <span class="k" style="font-weight: 600;">as</span> <span class="n" style="color: #333;">pdt</span></span>
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<pre style="margin: 0;">+<span id="LC15" class="line" lang="python"><span class="kn" style="font-weight: 600;">import</span> <span class="nn" style="color: #555;">pandas.testing</span> <span class="k" style="font-weight: 600;">as</span> <span class="n" style="color: #333;">pdt</span></span>
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<pre style="margin: 0;"> <span id="LC16" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC17" class="line" lang="python"><span class="kn" style="font-weight: 600;">import</span> <span class="nn" style="color: #555;">qiime2</span></span>
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<pre style="margin: 0;"> <span id="LC18" class="line" lang="python"></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -121,8 +121,9 @@ class UtilitiesTests(SampleClassifierTestPluginBase):</td>
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<pre style="margin: 0;"> <span id="LC121" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># and this should not occur now, but theoretically should just concat and</span></span>
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<pre style="margin: 0;"> <span id="LC122" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># sort but not collapse if all column names are unique</span></span>
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<pre style="margin: 0;"> <span id="LC123" class="line" lang="python"> <span class="k" style="font-weight: 600;">def</span> <span class="nf" style="color: #900; font-weight: 600;">test_mean_feature_importance_do_not_collapse</span><span class="p">(</span><span class="bp" style="color: #999;">self</span><span class="p">):</span></span>
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<pre style="margin: 0;">-<span id="LC124" class="line" lang="python"> <span class="n" style="color: #333;">imps</span> <span class="o" style="font-weight: 600;">=</span> <span class="p">[</span><span class="n" style="color: #333;">pd</span><span class="p">.</span><span class="n" style="color: #333;">DataFrame</span><span class="p">([</span><span class="mi" style="color: #099;">4</span><span class="p">,</span> <span class="mi" style="color: #099;">3</span><span class="p">,</span> <span class="mi" style="color: #099;">2</span><span class="p">,</span> <span class="mi" style="color: #099;">1</span><span class="p">],</span> <span class="n" style="color: #333;">columns</span><span class="o" style="font-weight: 600;">=</span><span class="p">[</span><span class="s" style="color: #d14;">"importance0"</span><span class="p">]),</span></span>
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<pre style="margin: 0;">-<span id="LC125" class="line" lang="python"> <span class="n" style="color: #333;">pd</span><span class="p">.</span><span class="n" style="color: #333;">DataFrame</span><span class="p">([</span><span class="mi" style="color: #099;">16</span><span class="p">,</span> <span class="mi" style="color: #099;">15</span><span class="p">,</span> <span class="mi" style="color: #099;">14</span><span class="p">,</span> <span class="mi" style="color: #099;">13</span><span class="p">],</span> <span class="n" style="color: #333;">columns</span><span class="o" style="font-weight: 600;">=</span><span class="p">[</span><span class="s" style="color: #d14;">"importance1"</span><span class="p">])]</span></span>
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<pre style="margin: 0;">+<span id="LC124" class="line" lang="python"> <span class="n" style="color: #333;">imps</span> <span class="o" style="font-weight: 600;">=</span> <span class="p">[</span><span class="n" style="color: #333;">pd</span><span class="p">.</span><span class="n" style="color: #333;">DataFrame</span><span class="p">([</span><span class="mf" style="color: #099;">4.0</span><span class="p">,</span> <span class="mf" style="color: #099;">3.0</span><span class="p">,</span> <span class="mf" style="color: #099;">2.0</span><span class="p">,</span> <span class="mf" style="color: #099;">1.0</span><span class="p">],</span> <span class="n" style="color: #333;">columns</span><span class="o" style="font-weight: 600;">=</span><span class="p">[</span><span class="s" style="color: #d14;">"importance0"</span><span class="p">]),</span></span>
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<pre style="margin: 0;">+<span id="LC125" class="line" lang="python"> <span class="n" style="color: #333;">pd</span><span class="p">.</span><span class="n" style="color: #333;">DataFrame</span><span class="p">([</span><span class="mf" style="color: #099;">16.0</span><span class="p">,</span> <span class="mf" style="color: #099;">15.0</span><span class="p">,</span> <span class="mf" style="color: #099;">14.0</span><span class="p">,</span> <span class="mf" style="color: #099;">13.0</span><span class="p">],</span></span>
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<pre style="margin: 0;">+<span id="LC126" class="line" lang="python"> <span class="n" style="color: #333;">columns</span><span class="o" style="font-weight: 600;">=</span><span class="p">[</span><span class="s" style="color: #d14;">"importance1"</span><span class="p">])]</span></span>
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<pre style="margin: 0;"> <span id="LC127" class="line" lang="python"> <span class="n" style="color: #333;">exp</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">pd</span><span class="p">.</span><span class="n" style="color: #333;">concat</span><span class="p">(</span><span class="n" style="color: #333;">imps</span><span class="p">,</span> <span class="n" style="color: #333;">axis</span><span class="o" style="font-weight: 600;">=</span><span class="mi" style="color: #099;">1</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC128" class="line" lang="python"> <span class="n" style="color: #333;">pdt</span><span class="p">.</span><span class="n" style="color: #333;">assert_frame_equal</span><span class="p">(</span><span class="n" style="color: #333;">_mean_feature_importance</span><span class="p">(</span><span class="n" style="color: #333;">imps</span><span class="p">),</span> <span class="n" style="color: #333;">exp</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC129" class="line" lang="python"></span>
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<a href="https://salsa.debian.org/med-team/q2-sample-classifier/-/commit/7c4b78faf33bc50e958843964685cf5d73d1374d#2607554eb0fe14065eea07f68c7991db73cfa7f8"><strong>q2_sample_classifier/tests/test_visualization.py</strong></a>
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<pre style="margin: 0;"> <span id="LC1" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># ----------------------------------------------------------------------------</span></span>
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<pre style="margin: 0;">-<span id="LC2" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Copyright (c) 2017-202<span class="idiff left right">0</span>, QIIME 2 development team.</span></span>
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<pre style="margin: 0;">+<span id="LC2" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Copyright (c) 2017-202<span class="idiff left right">1</span>, QIIME 2 development team.</span></span>
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<pre style="margin: 0;"> <span id="LC3" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;">#</span></span>
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<pre style="margin: 0;"> <span id="LC4" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Distributed under the terms of the Modified BSD License.</span></span>
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<pre style="margin: 0;"> <span id="LC5" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;">#</span></span>
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<pre style="margin: 0;"> <span id="LC6" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># The full license is in the file LICENSE, distributed with this software.</span></span>
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<pre style="margin: 0;"> <span id="LC7" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># ----------------------------------------------------------------------------</span></span>
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<pre style="margin: 0;"> <span id="LC8" class="line" lang="python"><span class="kn" style="font-weight: 600;">import</span> <span class="nn" style="color: #555;">pandas</span> <span class="k" style="font-weight: 600;">as</span> <span class="n" style="color: #333;">pd</span></span>
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<pre style="margin: 0;">-<span id="LC9" class="line" lang="python"><span class="kn" style="font-weight: 600;">import</span> <span class="nn" style="color: #555;">pandas.<span class="idiff left right">util.</span>testing</span> <span class="k" style="font-weight: 600;">as</span> <span class="n" style="color: #333;">pdt</span></span>
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<pre style="margin: 0;">+<span id="LC9" class="line" lang="python"><span class="kn" style="font-weight: 600;">import</span> <span class="nn" style="color: #555;">pandas.testing</span> <span class="k" style="font-weight: 600;">as</span> <span class="n" style="color: #333;">pdt</span></span>
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<pre style="margin: 0;"> <span id="LC10" class="line" lang="python"><span class="kn" style="font-weight: 600;">from</span> <span class="nn" style="color: #555;">os</span> <span class="kn" style="font-weight: 600;">import</span> <span class="n" style="color: #333;">mkdir</span><span class="p">,</span> <span class="n" style="color: #333;">listdir</span></span>
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<pre style="margin: 0;"> <span id="LC11" class="line" lang="python"><span class="kn" style="font-weight: 600;">from</span> <span class="nn" style="color: #555;">os.path</span> <span class="kn" style="font-weight: 600;">import</span> <span class="n" style="color: #333;">join</span></span>
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<pre style="margin: 0;"> <span id="LC12" class="line" lang="python"><span class="kn" style="font-weight: 600;">import</span> <span class="nn" style="color: #555;">biom</span></span>
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<a href="https://salsa.debian.org/med-team/q2-sample-classifier/-/commit/7c4b78faf33bc50e958843964685cf5d73d1374d#0be6602492251a34b00c1d37085f5deaca6be29e"><strong>q2_sample_classifier/utilities.py</strong></a>
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<pre style="margin: 0;"> <span id="LC1" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># ----------------------------------------------------------------------------</span></span>
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<pre style="margin: 0;">-<span id="LC2" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Copyright (c) 2017-202<span class="idiff left right">0</span>, QIIME 2 development team.</span></span>
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<pre style="margin: 0;">+<span id="LC2" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Copyright (c) 2017-202<span class="idiff left right">1</span>, QIIME 2 development team.</span></span>
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<pre style="margin: 0;"> <span id="LC3" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;">#</span></span>
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<pre style="margin: 0;"> <span id="LC4" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Distributed under the terms of the Modified BSD License.</span></span>
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<pre style="margin: 0;"> <span id="LC5" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;">#</span></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -18,7 +18,7 @@ from sklearn.ensemble import (RandomForestRegressor, RandomForestClassifier,</td>
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<pre style="margin: 0;"> <span id="LC18" class="line" lang="python"> <span class="n" style="color: #333;">ExtraTreesClassifier</span><span class="p">,</span> <span class="n" style="color: #333;">ExtraTreesRegressor</span><span class="p">,</span></span>
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<pre style="margin: 0;"> <span id="LC19" class="line" lang="python"> <span class="n" style="color: #333;">AdaBoostClassifier</span><span class="p">,</span> <span class="n" style="color: #333;">GradientBoostingClassifier</span><span class="p">,</span></span>
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<pre style="margin: 0;"> <span id="LC20" class="line" lang="python"> <span class="n" style="color: #333;">AdaBoostRegressor</span><span class="p">,</span> <span class="n" style="color: #333;">GradientBoostingRegressor</span><span class="p">)</span></span>
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<pre style="margin: 0;">-<span id="LC21" class="line" lang="python"><span class="kn" style="font-weight: 600;">from</span> <span class="nn" style="color: #555;">sklearn.svm</span> <span class="kn" style="font-weight: 600;">import</span> <span class="n" style="color: #333;"><span class="idiff left">LinearSVC</span></span><span class="p"><span class="idiff">,</span></span><span class="idiff right"> </span><span class="n" style="color: #333;">SVR</span><span class="p">,</span> <span class="n" style="color: #333;">SVC</span></span>
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<pre style="margin: 0;">+<span id="LC21" class="line" lang="python"><span class="kn" style="font-weight: 600;">from</span> <span class="nn" style="color: #555;">sklearn.svm</span> <span class="kn" style="font-weight: 600;">import</span> <span class="n" style="color: #333;">SVR</span><span class="p">,</span> <span class="n" style="color: #333;">SVC</span></span>
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<pre style="margin: 0;"> <span id="LC22" class="line" lang="python"><span class="kn" style="font-weight: 600;">from</span> <span class="nn" style="color: #555;">sklearn.linear_model</span> <span class="kn" style="font-weight: 600;">import</span> <span class="n" style="color: #333;">Ridge</span><span class="p">,</span> <span class="n" style="color: #333;">Lasso</span><span class="p">,</span> <span class="n" style="color: #333;">ElasticNet</span></span>
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<pre style="margin: 0;"> <span id="LC23" class="line" lang="python"><span class="kn" style="font-weight: 600;">from</span> <span class="nn" style="color: #555;">sklearn.neighbors</span> <span class="kn" style="font-weight: 600;">import</span> <span class="n" style="color: #333;">KNeighborsClassifier</span><span class="p">,</span> <span class="n" style="color: #333;">KNeighborsRegressor</span></span>
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<pre style="margin: 0;"> <span id="LC24" class="line" lang="python"><span class="kn" style="font-weight: 600;">from</span> <span class="nn" style="color: #555;">sklearn.tree</span> <span class="kn" style="font-weight: 600;">import</span> <span class="n" style="color: #333;">DecisionTreeClassifier</span><span class="p">,</span> <span class="n" style="color: #333;">DecisionTreeRegressor</span></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -47,20 +47,6 @@ parameters = {</td>
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<pre style="margin: 0;"> <span id="LC47" class="line" lang="python"> <span class="s" style="color: #d14;">"min_weight_fraction_leaf"</span><span class="p">:</span> <span class="p">[</span><span class="mf" style="color: #099;">0.0001</span><span class="p">,</span> <span class="mf" style="color: #099;">0.001</span><span class="p">,</span> <span class="mf" style="color: #099;">0.01</span><span class="p">]},</span></span>
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<pre style="margin: 0;"> <span id="LC48" class="line" lang="python"> <span class="s" style="color: #d14;">'bootstrap'</span><span class="p">:</span> <span class="p">{</span><span class="s" style="color: #d14;">"bootstrap"</span><span class="p">:</span> <span class="p">[</span><span class="bp" style="color: #999;">True</span><span class="p">,</span> <span class="bp" style="color: #999;">False</span><span class="p">]},</span></span>
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<pre style="margin: 0;"> <span id="LC49" class="line" lang="python"> <span class="s" style="color: #d14;">'criterion'</span><span class="p">:</span> <span class="p">{</span><span class="s" style="color: #d14;">"criterion"</span><span class="p">:</span> <span class="p">[</span><span class="s" style="color: #d14;">"gini"</span><span class="p">,</span> <span class="s" style="color: #d14;">"entropy"</span><span class="p">]},</span></span>
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<pre style="margin: 0;">-<span id="LC50" class="line" lang="python"> <span class="s" style="color: #d14;">'linear_svm'</span><span class="p">:</span> <span class="p">{</span><span class="s" style="color: #d14;">"C"</span><span class="p">:</span> <span class="p">[</span><span class="mi" style="color: #099;">1</span><span class="p">,</span> <span class="mf" style="color: #099;">0.5</span><span class="p">,</span> <span class="mf" style="color: #099;">0.1</span><span class="p">,</span> <span class="mf" style="color: #099;">0.9</span><span class="p">,</span> <span class="mf" style="color: #099;">0.8</span><span class="p">],</span></span>
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<pre style="margin: 0;">-<span id="LC51" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># should probably include penalty in grid search, but:</span></span>
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<pre style="margin: 0;">-<span id="LC52" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># Unsupported set of arguments: The combination of</span></span>
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<pre style="margin: 0;">-<span id="LC53" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># penalty='l1' and loss='hinge' is not supported</span></span>
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<pre style="margin: 0;">-<span id="LC54" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># "penalty": ["l1", "l2"],</span></span>
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<pre style="margin: 0;">-<span id="LC55" class="line" lang="python"> <span class="s" style="color: #d14;">"loss"</span><span class="p">:</span> <span class="p">[</span><span class="s" style="color: #d14;">"hinge"</span><span class="p">,</span> <span class="s" style="color: #d14;">"squared_hinge"</span><span class="p">],</span></span>
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<pre style="margin: 0;">-<span id="LC56" class="line" lang="python"> <span class="s" style="color: #d14;">"tol"</span><span class="p">:</span> <span class="p">[</span><span class="mf" style="color: #099;">0.00001</span><span class="p">,</span> <span class="mf" style="color: #099;">0.0001</span><span class="p">,</span> <span class="mf" style="color: #099;">0.001</span><span class="p">]</span></span>
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<pre style="margin: 0;">-<span id="LC57" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># should probably include this in grid search, as</span></span>
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<pre style="margin: 0;">-<span id="LC58" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># dual=False is preferred when samples>features. However:</span></span>
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<pre style="margin: 0;">-<span id="LC59" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># Unsupported set of arguments: The combination of</span></span>
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<pre style="margin: 0;">-<span id="LC60" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># penalty='l2' and loss='hinge' are not supported when</span></span>
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<pre style="margin: 0;">-<span id="LC61" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># dual=False</span></span>
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<pre style="margin: 0;">-<span id="LC62" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># "dual": [True, False]</span></span>
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<pre style="margin: 0;">-<span id="LC63" class="line" lang="python"> <span class="p">},</span></span>
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<pre style="margin: 0;"> <span id="LC50" class="line" lang="python"> <span class="s" style="color: #d14;">'svm'</span><span class="p">:</span> <span class="p">{</span><span class="s" style="color: #d14;">"C"</span><span class="p">:</span> <span class="p">[</span><span class="mi" style="color: #099;">1</span><span class="p">,</span> <span class="mf" style="color: #099;">0.5</span><span class="p">,</span> <span class="mf" style="color: #099;">0.1</span><span class="p">,</span> <span class="mf" style="color: #099;">0.9</span><span class="p">,</span> <span class="mf" style="color: #099;">0.8</span><span class="p">],</span></span>
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<pre style="margin: 0;"> <span id="LC51" class="line" lang="python"> <span class="s" style="color: #d14;">"tol"</span><span class="p">:</span> <span class="p">[</span><span class="mf" style="color: #099;">0.00001</span><span class="p">,</span> <span class="mf" style="color: #099;">0.0001</span><span class="p">,</span> <span class="mf" style="color: #099;">0.001</span><span class="p">,</span> <span class="mf" style="color: #099;">0.01</span><span class="p">],</span></span>
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<pre style="margin: 0;"> <span id="LC52" class="line" lang="python"> <span class="s" style="color: #d14;">"shrinking"</span><span class="p">:</span> <span class="p">[</span><span class="bp" style="color: #999;">True</span><span class="p">,</span> <span class="bp" style="color: #999;">False</span><span class="p">]},</span></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -171,6 +157,9 @@ def _split_training_data(feature_data, targets, column, test_size=0.2,</td>
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<pre style="margin: 0;"> <span id="LC157" class="line" lang="python"> <span class="k" style="font-weight: 600;">except</span> <span class="nb" style="color: #0086b3;">ValueError</span><span class="p">:</span></span>
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<pre style="margin: 0;"> <span id="LC158" class="line" lang="python"> <span class="n" style="color: #333;">_stratification_error</span><span class="p">()</span></span>
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<pre style="margin: 0;"> <span id="LC159" class="line" lang="python"> <span class="k" style="font-weight: 600;">else</span><span class="p">:</span></span>
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<pre style="margin: 0;">+<span id="LC160" class="line" lang="python"> <span class="n" style="color: #333;">warning_msg</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">_warn_zero_test_split</span><span class="p">()</span></span>
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<pre style="margin: 0;">+<span id="LC161" class="line" lang="python"> <span class="n" style="color: #333;">warnings</span><span class="p">.</span><span class="n" style="color: #333;">warn</span><span class="p">(</span><span class="n" style="color: #333;">warning_msg</span><span class="p">,</span> <span class="nb" style="color: #0086b3;">UserWarning</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC162" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC163" class="line" lang="python"> <span class="n" style="color: #333;">X_train</span><span class="p">,</span> <span class="n" style="color: #333;">X_test</span><span class="p">,</span> <span class="n" style="color: #333;">y_train</span><span class="p">,</span> <span class="n" style="color: #333;">y_test</span> <span class="o" style="font-weight: 600;">=</span> <span class="p">(</span></span>
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<pre style="margin: 0;"> <span id="LC164" class="line" lang="python"> <span class="n" style="color: #333;">feature_data</span><span class="p">,</span> <span class="n" style="color: #333;">feature_data</span><span class="p">,</span> <span class="n" style="color: #333;">targets</span><span class="p">,</span> <span class="n" style="color: #333;">targets</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC165" class="line" lang="python"></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -438,11 +427,14 @@ def _predict_and_plot(output_dir, y_test, y_pred, vmin=None, vmax=None,</td>
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<pre style="margin: 0;"> <span id="LC427" class="line" lang="python"> <span class="k" style="font-weight: 600;">else</span><span class="p">:</span></span>
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<pre style="margin: 0;"> <span id="LC428" class="line" lang="python"> <span class="n" style="color: #333;">predictions</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">_linear_regress</span><span class="p">(</span><span class="n" style="color: #333;">y_test</span><span class="p">,</span> <span class="n" style="color: #333;">y_pred</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC429" class="line" lang="python"> <span class="n" style="color: #333;">predict_plot</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">_regplot_from_dataframe</span><span class="p">(</span><span class="n" style="color: #333;">y_test</span><span class="p">,</span> <span class="n" style="color: #333;">y_pred</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC430" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC431" class="line" lang="python"> <span class="k" style="font-weight: 600;">if</span> <span class="n" style="color: #333;">output_dir</span> <span class="ow" style="font-weight: 600;">is</span> <span class="ow" style="font-weight: 600;">not</span> <span class="bp" style="color: #999;">None</span><span class="p">:</span></span>
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<pre style="margin: 0;"> <span id="LC432" class="line" lang="python"> <span class="n" style="color: #333;">predict_plot</span><span class="p">.</span><span class="n" style="color: #333;">get_figure</span><span class="p">().</span><span class="n" style="color: #333;">savefig</span><span class="p">(</span></span>
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<pre style="margin: 0;"> <span id="LC433" class="line" lang="python"> <span class="n" style="color: #333;">join</span><span class="p">(</span><span class="n" style="color: #333;">output_dir</span><span class="p">,</span> <span class="s" style="color: #d14;">'predictions.png'</span><span class="p">),</span> <span class="n" style="color: #333;">bbox_inches</span><span class="o" style="font-weight: 600;">=</span><span class="s" style="color: #d14;">'tight'</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC434" class="line" lang="python"> <span class="n" style="color: #333;">predict_plot</span><span class="p">.</span><span class="n" style="color: #333;">get_figure</span><span class="p">().</span><span class="n" style="color: #333;">savefig</span><span class="p">(</span></span>
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<pre style="margin: 0;"> <span id="LC435" class="line" lang="python"> <span class="n" style="color: #333;">join</span><span class="p">(</span><span class="n" style="color: #333;">output_dir</span><span class="p">,</span> <span class="s" style="color: #d14;">'predictions.pdf'</span><span class="p">),</span> <span class="n" style="color: #333;">bbox_inches</span><span class="o" style="font-weight: 600;">=</span><span class="s" style="color: #d14;">'tight'</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC436" class="line" lang="python"></span>
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<pre style="margin: 0;">+<span id="LC437" class="line" lang="python"> <span class="n" style="color: #333;">plt</span><span class="p">.</span><span class="n" style="color: #333;">close</span><span class="p">(</span><span class="s" style="color: #d14;">'all'</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC438" class="line" lang="python"> <span class="k" style="font-weight: 600;">return</span> <span class="n" style="color: #333;">predictions</span><span class="p">,</span> <span class="n" style="color: #333;">predict_plot</span></span>
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<pre style="margin: 0;"> <span id="LC439" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC440" class="line" lang="python"></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -480,6 +472,14 @@ def _plot_accuracy(output_dir, predictions, truth, probabilities,</td>
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<pre style="margin: 0;"> <span id="LC472" class="line" lang="python"><span class="s" style="color: #d14;"> or numeric data inside two pd.Series</span></span>
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<pre style="margin: 0;"> <span id="LC473" class="line" lang="python"><span class="s" style="color: #d14;"> '''</span></span>
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<pre style="margin: 0;"> <span id="LC474" class="line" lang="python"> <span class="n" style="color: #333;">truth</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">truth</span><span class="p">.</span><span class="n" style="color: #333;">to_series</span><span class="p">()</span></span>
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<pre style="margin: 0;">+<span id="LC475" class="line" lang="python"></span>
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<pre style="margin: 0;">+<span id="LC476" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># check if test_size == 0.0 and all predictions are complete dataset</span></span>
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<pre style="margin: 0;">+<span id="LC477" class="line" lang="python"> <span class="k" style="font-weight: 600;">if</span> <span class="p">(</span><span class="n" style="color: #333;">missing_samples</span> <span class="o" style="font-weight: 600;">==</span> <span class="s" style="color: #d14;">'ignore'</span><span class="p">)</span> <span class="o" style="font-weight: 600;">&</span> <span class="p">(</span></span>
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<pre style="margin: 0;">+<span id="LC478" class="line" lang="python"> <span class="n" style="color: #333;">predictions</span><span class="p">.</span><span class="n" style="color: #333;">shape</span><span class="p">[</span><span class="mi" style="color: #099;">0</span><span class="p">]</span> <span class="o" style="font-weight: 600;">==</span> <span class="n" style="color: #333;">truth</span><span class="p">.</span><span class="n" style="color: #333;">shape</span><span class="p">[</span><span class="mi" style="color: #099;">0</span><span class="p">]):</span></span>
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<pre style="margin: 0;">+<span id="LC479" class="line" lang="python"> <span class="n" style="color: #333;">warning_msg</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">_warn_zero_test_split</span><span class="p">()</span></span>
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<pre style="margin: 0;">+<span id="LC480" class="line" lang="python"> <span class="k" style="font-weight: 600;">else</span><span class="p">:</span></span>
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<pre style="margin: 0;">+<span id="LC481" class="line" lang="python"> <span class="n" style="color: #333;">warning_msg</span> <span class="o" style="font-weight: 600;">=</span> <span class="bp" style="color: #999;">None</span></span>
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<pre style="margin: 0;">+<span id="LC482" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC483" class="line" lang="python"> <span class="n" style="color: #333;">predictions</span><span class="p">,</span> <span class="n" style="color: #333;">truth</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">_match_series_or_die</span><span class="p">(</span></span>
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<pre style="margin: 0;"> <span id="LC484" class="line" lang="python"> <span class="n" style="color: #333;">predictions</span><span class="p">,</span> <span class="n" style="color: #333;">truth</span><span class="p">,</span> <span class="n" style="color: #333;">missing_samples</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC485" class="line" lang="python"></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -499,7 +499,7 @@ def _plot_accuracy(output_dir, predictions, truth, probabilities,</td>
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<pre style="margin: 0;"> <span id="LC499" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># output to viz</span></span>
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<pre style="margin: 0;"> <span id="LC500" class="line" lang="python"> <span class="n" style="color: #333;">_visualize</span><span class="p">(</span><span class="n" style="color: #333;">output_dir</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">output_dir</span><span class="p">,</span> <span class="n" style="color: #333;">estimator</span><span class="o" style="font-weight: 600;">=</span><span class="bp" style="color: #999;">None</span><span class="p">,</span> <span class="n" style="color: #333;">cm</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">predictions</span><span class="p">,</span></span>
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<pre style="margin: 0;"> <span id="LC501" class="line" lang="python"> <span class="n" style="color: #333;">roc</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">probabilities</span><span class="p">,</span> <span class="n" style="color: #333;">optimize_feature_selection</span><span class="o" style="font-weight: 600;">=</span><span class="bp" style="color: #999;">False</span><span class="p">,</span></span>
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<pre style="margin: 0;">-<span id="LC502" class="line" lang="python"> <span class="n" style="color: #333;">title</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">plot_title</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC502" class="line" lang="python"> <span class="n" style="color: #333;">title</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">plot_title</span><span class="p"><span class="idiff left">,</span></span><span class="idiff"> </span><span class="n" style="color: #333;"><span class="idiff">warning_msg</span></span><span class="o" style="font-weight: 600;"><span class="idiff">=</span></span><span class="n" style="color: #333;"><span class="idiff right">warning_msg</span></span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC503" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC504" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC505" class="line" lang="python"><span class="k" style="font-weight: 600;">def</span> <span class="nf" style="color: #900; font-weight: 600;">sort_importances</span><span class="p">(</span><span class="n" style="color: #333;">importances</span><span class="p">,</span> <span class="n" style="color: #333;">ascending</span><span class="o" style="font-weight: 600;">=</span><span class="bp" style="color: #999;">False</span><span class="p">):</span></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -523,6 +523,11 @@ def _summarize_estimator(output_dir, sample_estimator):</td>
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<pre style="margin: 0;"> <span id="LC523" class="line" lang="python"> <span class="n" style="color: #333;">rfep</span><span class="p">.</span><span class="n" style="color: #333;">savefig</span><span class="p">(</span><span class="n" style="color: #333;">join</span><span class="p">(</span><span class="n" style="color: #333;">output_dir</span><span class="p">,</span> <span class="s" style="color: #d14;">'rfe_plot.pdf'</span><span class="p">))</span></span>
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<pre style="margin: 0;"> <span id="LC524" class="line" lang="python"> <span class="n" style="color: #333;">plt</span><span class="p">.</span><span class="n" style="color: #333;">close</span><span class="p">(</span><span class="s" style="color: #d14;">'all'</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC525" class="line" lang="python"> <span class="n" style="color: #333;">optimize_feature_selection</span> <span class="o" style="font-weight: 600;">=</span> <span class="bp" style="color: #999;">True</span></span>
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<pre style="margin: 0;">+<span id="LC526" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># generate rfe scores file</span></span>
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<pre style="margin: 0;">+<span id="LC527" class="line" lang="python"> <span class="n" style="color: #333;">df</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">pd</span><span class="p">.</span><span class="n" style="color: #333;">DataFrame</span><span class="p">(</span><span class="n" style="color: #333;">data</span><span class="o" style="font-weight: 600;">=</span><span class="p">{</span><span class="s" style="color: #d14;">'rfe_score'</span><span class="p">:</span> <span class="n" style="color: #333;">sample_estimator</span><span class="p">.</span><span class="n" style="color: #333;">rfe_scores</span><span class="p">},</span></span>
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<pre style="margin: 0;">+<span id="LC528" class="line" lang="python"> <span class="n" style="color: #333;">index</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">sample_estimator</span><span class="p">.</span><span class="n" style="color: #333;">rfe_scores</span><span class="p">.</span><span class="n" style="color: #333;">index</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC529" class="line" lang="python"> <span class="n" style="color: #333;">df</span><span class="p">.</span><span class="n" style="color: #333;">index</span><span class="p">.</span><span class="n" style="color: #333;">name</span> <span class="o" style="font-weight: 600;">=</span> <span class="s" style="color: #d14;">'feature_count'</span></span>
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<pre style="margin: 0;">+<span id="LC530" class="line" lang="python"> <span class="n" style="color: #333;">df</span><span class="p">.</span><span class="n" style="color: #333;">to_csv</span><span class="p">(</span><span class="n" style="color: #333;">join</span><span class="p">(</span><span class="n" style="color: #333;">output_dir</span><span class="p">,</span> <span class="s" style="color: #d14;">'rfe_scores.tsv'</span><span class="p">),</span> <span class="n" style="color: #333;">sep</span><span class="o" style="font-weight: 600;">=</span><span class="s" style="color: #d14;">'</span><span class="se" style="color: #d14;">\t</span><span class="s" style="color: #d14;">'</span><span class="p">,</span> <span class="n" style="color: #333;">index</span><span class="o" style="font-weight: 600;">=</span><span class="bp" style="color: #999;">True</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC531" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># if the rfe_scores attribute does not exist, do nothing</span></span>
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<pre style="margin: 0;"> <span id="LC532" class="line" lang="python"> <span class="k" style="font-weight: 600;">except</span> <span class="nb" style="color: #0086b3;">AttributeError</span><span class="p">:</span></span>
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<pre style="margin: 0;"> <span id="LC533" class="line" lang="python"> <span class="n" style="color: #333;">optimize_feature_selection</span> <span class="o" style="font-weight: 600;">=</span> <span class="bp" style="color: #999;">False</span></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -533,7 +538,8 @@ def _summarize_estimator(output_dir, sample_estimator):</td>
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<pre style="margin: 0;"> <span id="LC538" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC539" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC540" class="line" lang="python"><span class="k" style="font-weight: 600;">def</span> <span class="nf" style="color: #900; font-weight: 600;">_visualize</span><span class="p">(</span><span class="n" style="color: #333;">output_dir</span><span class="p">,</span> <span class="n" style="color: #333;">estimator</span><span class="p">,</span> <span class="n" style="color: #333;">cm</span><span class="p">,</span> <span class="n" style="color: #333;">roc</span><span class="p">,</span></span>
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<pre style="margin: 0;">-<span id="LC536" class="line" lang="python"> <span class="n" style="color: #333;">optimize_feature_selection</span><span class="o" style="font-weight: 600;">=</span><span class="bp" style="color: #999;">True</span><span class="p">,</span> <span class="n" style="color: #333;">title</span><span class="o" style="font-weight: 600;">=</span><span class="s" style="color: #d14;">'results'</span><span class="p">):</span></span>
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<pre style="margin: 0;">+<span id="LC541" class="line" lang="python"> <span class="n" style="color: #333;">optimize_feature_selection</span><span class="o" style="font-weight: 600;">=</span><span class="bp" style="color: #999;">True</span><span class="p">,</span> <span class="n" style="color: #333;">title</span><span class="o" style="font-weight: 600;">=</span><span class="s" style="color: #d14;">'results'</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC542" class="line" lang="python"> <span class="n" style="color: #333;">warning_msg</span><span class="o" style="font-weight: 600;">=</span><span class="bp" style="color: #999;">None</span><span class="p">):</span></span>
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<pre style="margin: 0;"> <span id="LC543" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC544" class="line" lang="python"> <span class="n" style="color: #333;">pd</span><span class="p">.</span><span class="n" style="color: #333;">set_option</span><span class="p">(</span><span class="s" style="color: #d14;">'display.max_colwidth'</span><span class="p">,</span> <span class="bp" style="color: #999;">None</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC545" class="line" lang="python"></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -558,7 +564,8 @@ def _visualize(output_dir, estimator, cm, roc,</td>
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<pre style="margin: 0;"> <span id="LC564" class="line" lang="python"> <span class="s" style="color: #d14;">'result'</span><span class="p">:</span> <span class="n" style="color: #333;">result</span><span class="p">,</span></span>
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<pre style="margin: 0;"> <span id="LC565" class="line" lang="python"> <span class="s" style="color: #d14;">'predictions'</span><span class="p">:</span> <span class="n" style="color: #333;">cm</span><span class="p">,</span></span>
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<pre style="margin: 0;"> <span id="LC566" class="line" lang="python"> <span class="s" style="color: #d14;">'roc'</span><span class="p">:</span> <span class="n" style="color: #333;">roc</span><span class="p">,</span></span>
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<pre style="margin: 0;">-<span id="LC561" class="line" lang="python"> <span class="s" style="color: #d14;">'optimize_feature_selection'</span><span class="p">:</span> <span class="n" style="color: #333;">optimize_feature_selection</span><span class="p">})</span></span>
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<pre style="margin: 0;">+<span id="LC567" class="line" lang="python"> <span class="s" style="color: #d14;">'optimize_feature_selection'</span><span class="p">:</span> <span class="n" style="color: #333;">optimize_feature_selection</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC568" class="line" lang="python"> <span class="s" style="color: #d14;">'warning_msg'</span><span class="p">:</span> <span class="n" style="color: #333;">warning_msg</span><span class="p">})</span></span>
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<pre style="margin: 0;"> <span id="LC569" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC570" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC571" class="line" lang="python"><span class="k" style="font-weight: 600;">def</span> <span class="nf" style="color: #900; font-weight: 600;">_visualize_knn</span><span class="p">(</span><span class="n" style="color: #333;">output_dir</span><span class="p">,</span> <span class="n" style="color: #333;">params</span><span class="p">:</span> <span class="n" style="color: #333;">pd</span><span class="p">.</span><span class="n" style="color: #333;">Series</span><span class="p">):</span></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -678,14 +685,11 @@ def predict_probabilities(estimator, test_set, index):</td>
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<pre style="margin: 0;"> <span id="LC685" class="line" lang="python"><span class="s" style="color: #d14;"> have their class probabilities predicted.</span></span>
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<pre style="margin: 0;"> <span id="LC686" class="line" lang="python"><span class="s" style="color: #d14;"> index: array-like of sample names</span></span>
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<pre style="margin: 0;"> <span id="LC687" class="line" lang="python"><span class="s" style="color: #d14;"> '''</span></span>
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<pre style="margin: 0;">-<span id="LC681" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># most classifiers have a predict_proba attribute</span></span>
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<pre style="margin: 0;">-<span id="LC682" class="line" lang="python"> <span class="k" style="font-weight: 600;">try</span><span class="p">:</span></span>
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<pre style="margin: 0;">-<span id="LC683" class="line" lang="python"> <span class="n" style="color: #333;">probs</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">pd</span><span class="p">.</span><span class="n" style="color: #333;">DataFrame</span><span class="p">(</span><span class="n" style="color: #333;">estimator</span><span class="p">.</span><span class="n" style="color: #333;">predict_proba</span><span class="p">(</span><span class="n" style="color: #333;">test_set</span><span class="p">),</span></span>
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<pre style="margin: 0;">-<span id="LC684" class="line" lang="python"> <span class="n" style="color: #333;">index</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">index</span><span class="p">,</span> <span class="n" style="color: #333;">columns</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">estimator</span><span class="p">.</span><span class="n" style="color: #333;">classes_</span><span class="p">)</span></span>
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<pre style="margin: 0;">-<span id="LC685" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># SVMs use the decision_function attribute</span></span>
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<pre style="margin: 0;">-<span id="LC686" class="line" lang="python"> <span class="k" style="font-weight: 600;">except</span> <span class="nb" style="color: #0086b3;">AttributeError</span><span class="p">:</span></span>
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<pre style="margin: 0;">-<span id="LC687" class="line" lang="python"> <span class="n" style="color: #333;">probs</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">pd</span><span class="p">.</span><span class="n" style="color: #333;">DataFrame</span><span class="p">(</span><span class="n" style="color: #333;">estimator</span><span class="p">.</span><span class="n" style="color: #333;">decision_function</span><span class="p">(</span><span class="n" style="color: #333;">test_set</span><span class="p">),</span></span>
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<pre style="margin: 0;">-<span id="LC688" class="line" lang="python"> <span class="n" style="color: #333;">index</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">index</span><span class="p">,</span> <span class="n" style="color: #333;">columns</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">estimator</span><span class="p">.</span><span class="n" style="color: #333;">classes_</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC688" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># all used classifiers have a predict_proba attribute</span></span>
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<pre style="margin: 0;">+<span id="LC689" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># (approximated for SVCs)</span></span>
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<pre style="margin: 0;">+<span id="LC690" class="line" lang="python"> <span class="n" style="color: #333;">probs</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">pd</span><span class="p">.</span><span class="n" style="color: #333;">DataFrame</span><span class="p">(</span><span class="n" style="color: #333;">estimator</span><span class="p">.</span><span class="n" style="color: #333;">predict_proba</span><span class="p">(</span><span class="n" style="color: #333;">test_set</span><span class="p">),</span></span>
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<pre style="margin: 0;">+<span id="LC691" class="line" lang="python"> <span class="n" style="color: #333;">index</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">index</span><span class="p">,</span> <span class="n" style="color: #333;">columns</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">estimator</span><span class="p">.</span><span class="n" style="color: #333;">classes_</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC692" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC693" class="line" lang="python"> <span class="k" style="font-weight: 600;">return</span> <span class="n" style="color: #333;">probs</span></span>
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<pre style="margin: 0;"> <span id="LC694" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC695" class="line" lang="python"></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -763,11 +767,13 @@ def _select_estimator(estimator, n_jobs, n_estimators, random_state=None):</td>
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<pre style="margin: 0;"> <span id="LC767" class="line" lang="python"> <span class="n" style="color: #333;">estimator</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">GradientBoostingClassifier</span><span class="p">(</span></span>
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<pre style="margin: 0;"> <span id="LC768" class="line" lang="python"> <span class="n" style="color: #333;">n_estimators</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">n_estimators</span><span class="p">,</span> <span class="n" style="color: #333;">random_state</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">random_state</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC769" class="line" lang="python"> <span class="k" style="font-weight: 600;">elif</span> <span class="n" style="color: #333;">estimator</span> <span class="o" style="font-weight: 600;">==</span> <span class="s" style="color: #d14;">'LinearSVC'</span><span class="p">:</span></span>
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<pre style="margin: 0;">-<span id="LC766" class="line" lang="python"> <span class="n" style="color: #333;">param_dist</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">parameters</span><span class="p">[</span><span class="s" style="color: #d14;">'linear_svm'</span><span class="p">]</span></span>
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<pre style="margin: 0;">-<span id="LC767" class="line" lang="python"> <span class="n" style="color: #333;">estimator</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">LinearSVC</span><span class="p">(</span><span class="n" style="color: #333;">random_state</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">random_state</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC770" class="line" lang="python"> <span class="n" style="color: #333;">param_dist</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">parameters</span><span class="p">[</span><span class="s" style="color: #d14;">'svm'</span><span class="p">]</span></span>
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<pre style="margin: 0;">+<span id="LC771" class="line" lang="python"> <span class="n" style="color: #333;">estimator</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">SVC</span><span class="p">(</span><span class="n" style="color: #333;">kernel</span><span class="o" style="font-weight: 600;">=</span><span class="s" style="color: #d14;">'linear'</span><span class="p">,</span> <span class="n" style="color: #333;">random_state</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">random_state</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC772" class="line" lang="python"> <span class="n" style="color: #333;">gamma</span><span class="o" style="font-weight: 600;">=</span><span class="s" style="color: #d14;">'scale'</span><span class="p">,</span> <span class="n" style="color: #333;">probability</span><span class="o" style="font-weight: 600;">=</span><span class="bp" style="color: #999;">True</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC773" class="line" lang="python"> <span class="k" style="font-weight: 600;">elif</span> <span class="n" style="color: #333;">estimator</span> <span class="o" style="font-weight: 600;">==</span> <span class="s" style="color: #d14;">'SVC'</span><span class="p">:</span></span>
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<pre style="margin: 0;"> <span id="LC774" class="line" lang="python"> <span class="n" style="color: #333;">param_dist</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">parameters</span><span class="p">[</span><span class="s" style="color: #d14;">'svm'</span><span class="p">]</span></span>
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<pre style="margin: 0;">-<span id="LC770" class="line" lang="python"> <span class="n" style="color: #333;">estimator</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">SVC</span><span class="p">(</span><span class="n" style="color: #333;">kernel</span><span class="o" style="font-weight: 600;">=</span><span class="s" style="color: #d14;">'rbf'</span><span class="p">,</span> <span class="n" style="color: #333;">random_state</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">random_state</span><span class="p">,</span> <span class="n" style="color: #333;">gamma</span><span class="o" style="font-weight: 600;">=</span><span class="s" style="color: #d14;">'scale'</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC775" class="line" lang="python"> <span class="n" style="color: #333;">estimator</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">SVC</span><span class="p">(</span><span class="n" style="color: #333;">kernel</span><span class="o" style="font-weight: 600;">=</span><span class="s" style="color: #d14;">'rbf'</span><span class="p">,</span> <span class="n" style="color: #333;">random_state</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">random_state</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC776" class="line" lang="python"> <span class="n" style="color: #333;">gamma</span><span class="o" style="font-weight: 600;">=</span><span class="s" style="color: #d14;">'scale'</span><span class="p">,</span> <span class="n" style="color: #333;">probability</span><span class="o" style="font-weight: 600;">=</span><span class="bp" style="color: #999;">True</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC777" class="line" lang="python"> <span class="k" style="font-weight: 600;">elif</span> <span class="n" style="color: #333;">estimator</span> <span class="o" style="font-weight: 600;">==</span> <span class="s" style="color: #d14;">'KNeighborsClassifier'</span><span class="p">:</span></span>
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<pre style="margin: 0;"> <span id="LC778" class="line" lang="python"> <span class="n" style="color: #333;">param_dist</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">parameters</span><span class="p">[</span><span class="s" style="color: #d14;">'kneighbors'</span><span class="p">]</span></span>
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<pre style="margin: 0;"> <span id="LC779" class="line" lang="python"> <span class="n" style="color: #333;">estimator</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">KNeighborsClassifier</span><span class="p">(</span><span class="n" style="color: #333;">algorithm</span><span class="o" style="font-weight: 600;">=</span><span class="s" style="color: #d14;">'auto'</span><span class="p">)</span></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -845,3 +851,11 @@ def _warn_feature_selection():</td>
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<pre style="margin: 0;"> <span id="LC851" class="line" lang="python"> <span class="s" style="color: #d14;">'the parameter settings requested. See documentation or try a '</span></span>
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<pre style="margin: 0;"> <span id="LC852" class="line" lang="python"> <span class="s" style="color: #d14;">'different estimator model.'</span><span class="p">))</span></span>
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<pre style="margin: 0;"> <span id="LC853" class="line" lang="python"> <span class="n" style="color: #333;">warnings</span><span class="p">.</span><span class="n" style="color: #333;">warn</span><span class="p">(</span><span class="n" style="color: #333;">warning</span><span class="p">,</span> <span class="nb" style="color: #0086b3;">UserWarning</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC854" class="line" lang="python"></span>
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<pre style="margin: 0;">+<span id="LC855" class="line" lang="python"></span>
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<pre style="margin: 0;">+<span id="LC856" class="line" lang="python"><span class="k" style="font-weight: 600;">def</span> <span class="nf" style="color: #900; font-weight: 600;">_warn_zero_test_split</span><span class="p">():</span></span>
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<pre style="margin: 0;">+<span id="LC857" class="line" lang="python"> <span class="k" style="font-weight: 600;">return</span> <span class="s" style="color: #d14;">'Using test_size = 0.0, you are using your complete dataset for '</span> \</span>
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<pre style="margin: 0;">+<span id="LC858" class="line" lang="python"> <span class="s" style="color: #d14;">'fitting the estimator. Hence, any returned model evaluations are '</span> \</span>
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<pre style="margin: 0;">+<span id="LC859" class="line" lang="python"> <span class="s" style="color: #d14;">'based on that same training dataset and are not representative of '</span> \</span>
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<pre style="margin: 0;">+<span id="LC860" class="line" lang="python"> <span class="s" style="color: #d14;">'your model</span><span class="se" style="color: #d14;">\'</span><span class="s" style="color: #d14;">s performance on a previously unseen dataset. Please '</span> \</span>
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<pre style="margin: 0;">+<span id="LC861" class="line" lang="python"> <span class="s" style="color: #d14;">'consider evaluating this model on a separate dataset.'</span></span></pre>
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<a href="https://salsa.debian.org/med-team/q2-sample-classifier/-/commit/7c4b78faf33bc50e958843964685cf5d73d1374d#1445eb5a166ed40e8d437f17b2765bc1a0daa6fb"><strong>q2_sample_classifier/visuals.py</strong></a>
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<pre style="margin: 0;"> <span id="LC1" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># ----------------------------------------------------------------------------</span></span>
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<pre style="margin: 0;">-<span id="LC2" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Copyright (c) 2017-202<span class="idiff left right">0</span>, QIIME 2 development team.</span></span>
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<pre style="margin: 0;">+<span id="LC2" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Copyright (c) 2017-202<span class="idiff left right">1</span>, QIIME 2 development team.</span></span>
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<pre style="margin: 0;"> <span id="LC3" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;">#</span></span>
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<pre style="margin: 0;"> <span id="LC4" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Distributed under the terms of the Modified BSD License.</span></span>
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<pre style="margin: 0;"> <span id="LC5" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;">#</span></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -10,7 +10,7 @@ from sklearn.metrics import (</td>
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<pre style="margin: 0;"> <span id="LC10" class="line" lang="python"> <span class="n" style="color: #333;">mean_squared_error</span><span class="p">,</span> <span class="n" style="color: #333;">confusion_matrix</span><span class="p">,</span> <span class="n" style="color: #333;">accuracy_score</span><span class="p">,</span> <span class="n" style="color: #333;">roc_curve</span><span class="p">,</span> <span class="n" style="color: #333;">auc</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC11" class="line" lang="python"><span class="kn" style="font-weight: 600;">from</span> <span class="nn" style="color: #555;">sklearn.preprocessing</span> <span class="kn" style="font-weight: 600;">import</span> <span class="n" style="color: #333;">label_binarize</span></span>
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<pre style="margin: 0;"> <span id="LC12" class="line" lang="python"><span class="kn" style="font-weight: 600;">from</span> <span class="nn" style="color: #555;">itertools</span> <span class="kn" style="font-weight: 600;">import</span> <span class="n" style="color: #333;">cycle</span></span>
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<pre style="margin: 0;">-<span id="LC13" class="line" lang="python"><span class="kn" style="font-weight: 600;">from</span> <span class="nn" style="color: #555;"><span class="idiff left right">sci</span>py</span> <span class="kn" style="font-weight: 600;">import</span> <span class="n" style="color: #333;">interp</span></span>
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<pre style="margin: 0;">+<span id="LC13" class="line" lang="python"><span class="kn" style="font-weight: 600;">from</span> <span class="nn" style="color: #555;"><span class="idiff left right">num</span>py</span> <span class="kn" style="font-weight: 600;">import</span> <span class="n" style="color: #333;">interp</span></span>
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<pre style="margin: 0;"> <span id="LC14" class="line" lang="python"><span class="kn" style="font-weight: 600;">import</span> <span class="nn" style="color: #555;">pandas</span> <span class="k" style="font-weight: 600;">as</span> <span class="n" style="color: #333;">pd</span></span>
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<pre style="margin: 0;"> <span id="LC15" class="line" lang="python"><span class="kn" style="font-weight: 600;">import</span> <span class="nn" style="color: #555;">numpy</span> <span class="k" style="font-weight: 600;">as</span> <span class="n" style="color: #333;">np</span></span>
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<pre style="margin: 0;"> <span id="LC16" class="line" lang="python"><span class="kn" style="font-weight: 600;">import</span> <span class="nn" style="color: #555;">seaborn</span> <span class="k" style="font-weight: 600;">as</span> <span class="n" style="color: #333;">sns</span></span>
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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -72,7 +72,7 @@ def _regplot_from_dataframe(x, y, plot_style="whitegrid", arb=True,</td>
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<pre style="margin: 0;"> <span id="LC72" class="line" lang="python"> <span class="n" style="color: #333;">color</span><span class="o" style="font-weight: 600;">=</span><span class="s" style="color: #d14;">"grey"</span><span class="p">):</span></span>
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<pre style="margin: 0;"> <span id="LC73" class="line" lang="python"> <span class="s" style="color: #d14;">'''Seaborn regplot with true 1:1 ratio set by arb (bool).'''</span></span>
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<pre style="margin: 0;"> <span id="LC74" class="line" lang="python"> <span class="n" style="color: #333;">sns</span><span class="p">.</span><span class="n" style="color: #333;">set_style</span><span class="p">(</span><span class="n" style="color: #333;">plot_style</span><span class="p">)</span></span>
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<pre style="margin: 0;">-<span id="LC75" class="line" lang="python"> <span class="n" style="color: #333;">reg</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">sns</span><span class="p">.</span><span class="n" style="color: #333;">regplot</span><span class="p">(</span><span class="n" style="color: #333;">x</span><span class="p"><span class="idiff left">,</span></span><span class="idiff right"> </span><span class="n" style="color: #333;">y</span><span class="p">,</span> <span class="n" style="color: #333;">color</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">color</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC75" class="line" lang="python"> <span class="n" style="color: #333;">reg</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">sns</span><span class="p">.</span><span class="n" style="color: #333;">regplot</span><span class="p">(</span><span class="n" style="color: #333;">x</span><span class="o" style="font-weight: 600;"><span class="idiff left">=</span></span><span class="n" style="color: #333;"><span class="idiff">x</span></span><span class="p"><span class="idiff">,</span></span><span class="idiff"> </span><span class="n" style="color: #333;"><span class="idiff">y</span></span><span class="o" style="font-weight: 600;"><span class="idiff right">=</span></span><span class="n" style="color: #333;">y</span><span class="p">,</span> <span class="n" style="color: #333;">color</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">color</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC76" class="line" lang="python"> <span class="n" style="color: #333;">plt</span><span class="p">.</span><span class="n" style="color: #333;">xlabel</span><span class="p">(</span><span class="s" style="color: #d14;">'True value'</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC77" class="line" lang="python"> <span class="n" style="color: #333;">plt</span><span class="p">.</span><span class="n" style="color: #333;">ylabel</span><span class="p">(</span><span class="s" style="color: #d14;">'Predicted value'</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC78" class="line" lang="python"> <span class="k" style="font-weight: 600;">if</span> <span class="n" style="color: #333;">arb</span> <span class="ow" style="font-weight: 600;">is</span> <span class="bp" style="color: #999;">True</span><span class="p">:</span></span>
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<pre style="margin: 0;"> <span id="LC1" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># ----------------------------------------------------------------------------</span></span>
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<pre style="margin: 0;">-<span id="LC2" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Copyright (c) 2017-202<span class="idiff left right">0</span>, QIIME 2 development team.</span></span>
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<pre style="margin: 0;">+<span id="LC2" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Copyright (c) 2017-202<span class="idiff left right">1</span>, QIIME 2 development team.</span></span>
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<pre style="margin: 0;"> <span id="LC3" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;">#</span></span>
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<pre style="margin: 0;"> <span id="LC4" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;"># Distributed under the terms of the Modified BSD License.</span></span>
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<pre style="margin: 0;"> <span id="LC5" class="line" lang="python"><span class="c1" style="color: #998; font-style: italic;">#</span></span>
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