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<h3>
Liubov Chuprikova pushed to branch upstream
at <a href="https://salsa.debian.org/med-team/q2-feature-classifier">Debian Med / q2-feature-classifier</a>
</h3>
<h4>
Commits:
</h4>
<ul>
<li>
<strong><a href="https://salsa.debian.org/med-team/q2-feature-classifier/commit/ce3f2d71dc19f5e2778f83d61d5b0be27a8bee02">ce3f2d71</a></strong>
<div>
<span>by Liubov Chuprikova</span>
<i>at 2019-09-07T11:40:49Z</i>
</div>
<pre class="commit-message" style="white-space: pre-wrap; margin: 0;">New upstream version 2019.7.0</pre>
</li>
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<h4>11 changed files:</h4>
<ul>
<li class="file-stats">
<a href="#22fbe0b68848772d4b1c45f0d62dcd71a06cde00">
ci/recipe/meta.yaml
</a>
</li>
<li class="file-stats">
<a href="#51782921baee3f3292d09d4edb05c90bb30e5458">
q2_feature_classifier/_consensus_assignment.py
</a>
</li>
<li class="file-stats">
<a href="#a983074a9a2caf11735d1d54cef2229d079a453b">
q2_feature_classifier/_skl.py
</a>
</li>
<li class="file-stats">
<a href="#71ef0c2491ce3a86a4eb9be230cd72759b8b3fbe">
q2_feature_classifier/_taxonomic_classifier.py
</a>
</li>
<li class="file-stats">
<a href="#e1b612463caf8bb74f319ce3000e7a5fe7ccc722">
q2_feature_classifier/_version.py
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</li>
<li class="file-stats">
<a href="#755fedce54140c1dd2a4118628932cf48cc68dc1">
q2_feature_classifier/_vsearch.py
</a>
</li>
<li class="file-stats">
<a href="#8b429ca6f0ecc3f6f870bba70ce4d821c711e1a6">
q2_feature_classifier/classifier.py
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</li>
<li class="file-stats">
<a href="#d366b52f7b974621443c8a456ad87a6231c9ae53">
q2_feature_classifier/tests/data/class_weight.biom
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</li>
<li class="file-stats">
<a href="#43c534546ab6a7d5ef0423b90cd0e1b64c1614f7">
q2_feature_classifier/tests/test_classifier.py
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</li>
<li class="file-stats">
<a href="#9119ec5d547606e633f235bfd8d07e884992502a">
q2_feature_classifier/tests/test_consensus_assignment.py
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</li>
<li class="file-stats">
<a href="#d1ace7f5ea694e1686443cb8424bc9921f057f2b">
q2_feature_classifier/tests/test_taxonomic_classifier.py
</a>
</li>
</ul>
<h4>Changes:</h4>
<li id="22fbe0b68848772d4b1c45f0d62dcd71a06cde00">
<a href="https://salsa.debian.org/med-team/q2-feature-classifier/commit/ce3f2d71dc19f5e2778f83d61d5b0be27a8bee02#22fbe0b68848772d4b1c45f0d62dcd71a06cde00"><strong>ci/recipe/meta.yaml</strong></a>
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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="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="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -19,7 +19,8 @@ requirements:</td>
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<td class="diff-line-num 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">
19
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<td class="diff-line-num new_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">
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<td class="line_content" style="padding-left: 0.5em; padding-right: 0.5em;">
<pre style="margin: 0;"> <span id="LC19" class="line" lang="yaml"></span>
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<td class="diff-line-num old_line" data-linenumber="20" 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">
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<td class="diff-line-num new_line" data-linenumber="20" 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">
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<td class="line_content" style="padding-left: 0.5em; padding-right: 0.5em;">
<pre style="margin: 0;"> <span id="LC20" class="line" lang="yaml"> <span class="na" style="color: #008080;">run</span><span class="pi">:</span></span>
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<td class="diff-line-num old_line" data-linenumber="21" 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">
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<td class="diff-line-num new_line" data-linenumber="21" 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">
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<td class="line_content" style="padding-left: 0.5em; padding-right: 0.5em;">
<pre style="margin: 0;"> <span id="LC21" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">python {{ python }}</span></span>
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<td class="diff-line-num old old_line" data-linenumber="22" style="width: 35px; color: rgba(0,0,0,0.3); border-right-width: 1px; border-right-color: #fac5cd; border-right-style: solid; padding: 0 5px;" align="right" bgcolor="#f9d7dc">
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<td class="diff-line-num new_line old" data-linenumber="22" style="width: 35px; color: rgba(0,0,0,0.3); border-right-width: 1px; border-right-color: #fac5cd; border-right-style: solid; padding: 0 5px;" align="right" bgcolor="#f9d7dc">
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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;">scikit-learn 0.20.2</span></span>
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<td class="diff-line-num new old_line" data-linenumber="23" style="width: 35px; color: rgba(0,0,0,0.3); border-right-width: 1px; border-right-color: #c7f0d2; border-right-style: solid; padding: 0 5px;" align="right" bgcolor="#ddfbe6">
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<td class="diff-line-num new new_line" data-linenumber="22" style="width: 35px; color: rgba(0,0,0,0.3); border-right-width: 1px; border-right-color: #c7f0d2; border-right-style: solid; padding: 0 5px;" align="right" bgcolor="#ddfbe6">
22
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<td class="line_content new" style="padding-left: 0.5em; padding-right: 0.5em;" bgcolor="#ecfdf0">
<pre style="margin: 0;">+<span id="LC22" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">scikit-learn 0.21.2</span></span>
</pre>
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<td class="diff-line-num new old_line" data-linenumber="23" style="width: 35px; color: rgba(0,0,0,0.3); border-right-width: 1px; border-right-color: #c7f0d2; border-right-style: solid; padding: 0 5px;" align="right" bgcolor="#ddfbe6">
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<td class="diff-line-num new new_line" data-linenumber="23" style="width: 35px; color: rgba(0,0,0,0.3); border-right-width: 1px; border-right-color: #c7f0d2; border-right-style: solid; padding: 0 5px;" align="right" bgcolor="#ddfbe6">
23
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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;">joblib</span></span>
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<td class="diff-line-num new_line" data-linenumber="24" 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">
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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;">scikit-bio</span></span>
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<td class="diff-line-num old_line" data-linenumber="24" 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">
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<td class="diff-line-num new_line" data-linenumber="25" 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">
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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;">biom-format >=2.1.5,<2.2.0</span></span>
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<td class="diff-line-num old_line" data-linenumber="25" 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">
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<td class="diff-line-num new_line" data-linenumber="26" 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">
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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;">blast >=2.6.0</span></span>
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<td class="diff-line-num unfold js-unfold old_line" data-linenumber="27" 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="28" 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">@@ -27,6 +28,9 @@ requirements:</td>
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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;">vsearch <=2.7.0</span></span>
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<td class="diff-line-num old_line" data-linenumber="28" 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">
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<td class="diff-line-num new_line" data-linenumber="29" 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">
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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 {{ release }}.*</span></span>
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<td class="diff-line-num old_line" data-linenumber="29" 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">
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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 {{ release }}.*</span></span>
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<td class="diff-line-num new new_line" data-linenumber="31" style="width: 35px; color: rgba(0,0,0,0.3); border-right-width: 1px; border-right-color: #c7f0d2; border-right-style: solid; padding: 0 5px;" align="right" bgcolor="#ddfbe6">
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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;">q2-quality-control {{ release }}.*</span></span>
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<td class="diff-line-num new new_line" data-linenumber="32" style="width: 35px; color: rgba(0,0,0,0.3); border-right-width: 1px; border-right-color: #c7f0d2; border-right-style: solid; padding: 0 5px;" align="right" bgcolor="#ddfbe6">
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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-taxa {{ release }}.*</span></span>
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<td class="diff-line-num new new_line" data-linenumber="33" style="width: 35px; color: rgba(0,0,0,0.3); border-right-width: 1px; border-right-color: #c7f0d2; border-right-style: solid; padding: 0 5px;" align="right" bgcolor="#ddfbe6">
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<pre style="margin: 0;">+<span id="LC33" class="line" lang="yaml"> <span class="pi">-</span> <span class="s" style="color: #d14;">q2-feature-table {{ release }}.*</span></span>
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<pre style="margin: 0;"> <span id="LC34" class="line" lang="yaml"></span>
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<pre style="margin: 0;"> <span id="LC35" 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="LC36" class="line" lang="yaml"> <span class="na" style="color: #008080;">imports</span><span class="pi">:</span></span>
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<li id="51782921baee3f3292d09d4edb05c90bb30e5458">
<a href="https://salsa.debian.org/med-team/q2-feature-classifier/commit/ce3f2d71dc19f5e2778f83d61d5b0be27a8bee02#51782921baee3f3292d09d4edb05c90bb30e5458"><strong>q2_feature_classifier/_consensus_assignment.py</strong></a>
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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">@@ -11,6 +11,7 @@ import subprocess</td>
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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;">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;">isfile</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;">collections</span> <span class="kn" style="font-weight: 600;">import</span> <span class="n" style="color: #333;">Counter</span><span class="p">,</span> <span class="n" style="color: #333;">defaultdict</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;">qiime2</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>
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<pre style="margin: 0;"> <span id="LC17" class="line" lang="python"><span class="k" style="font-weight: 600;">def</span> <span class="nf" style="color: #900; font-weight: 600;">_get_default_unassignable_label</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">@@ -40,7 +41,7 @@ def _consensus_assignments(</td>
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<pre style="margin: 0;"> <span id="LC41" class="line" lang="python"> <span class="n" style="color: #333;">consensus</span> <span class="o" style="font-weight: 600;">=</span> <span class="p">{</span><span class="s" style="color: #d14;">''</span><span class="p">:</span> <span class="p">(</span><span class="s" style="color: #d14;">''</span><span class="p">,</span> <span class="s" style="color: #d14;">''</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;">result</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">pd</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">DataFrame</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">from_dict</span><span class="p">(</span><span class="n" style="color: #333;">consensus</span><span class="p">,</span> <span class="s" style="color: #d14;">'index'</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC43" class="line" lang="python"> <span class="n" style="color: #333;">result</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">index</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">name</span> <span class="o" style="font-weight: 600;">=</span> <span class="s" style="color: #d14;">'Feature ID'</span></span>
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<pre style="margin: 0;">-<span id="LC43" class="line" lang="python"> <span class="n" style="color: #333;">result</span><span class="o" style="font-weight: 600;">.</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;">'Taxon'</span><span class="p">,</span> <span class="s" style="color: #d14;">'Con<span class="idiff left right">fidence</span>'</span><span class="p">]</span></span>
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<pre style="margin: 0;">+<span id="LC44" class="line" lang="python"> <span class="n" style="color: #333;">result</span><span class="o" style="font-weight: 600;">.</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;">'Taxon'</span><span class="p">,</span> <span class="s" style="color: #d14;">'Con<span class="idiff left right">sensus</span>'</span><span class="p">]</span></span>
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<pre style="margin: 0;"> <span id="LC45" class="line" lang="python"> <span class="k" style="font-weight: 600;">return</span> <span class="n" style="color: #333;">result</span></span>
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<pre style="margin: 0;"> <span id="LC46" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC47" 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">@@ -242,3 +243,9 @@ def _compute_consensus_annotation(annotations, min_consensus,</td>
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<pre style="margin: 0;"> <span id="LC243" class="line" lang="python"> <span class="n" style="color: #333;">consensus_fraction_result</span> <span class="o" style="font-weight: 600;">=</span> <span class="mf" style="color: #099;">1.0</span></span>
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<pre style="margin: 0;"> <span id="LC244" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC245" class="line" lang="python"> <span class="k" style="font-weight: 600;">return</span> <span class="n" style="color: #333;">annotation</span><span class="p">,</span> <span class="n" style="color: #333;">consensus_fraction_result</span></span>
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<pre style="margin: 0;">+<span id="LC246" class="line" lang="python"></span>
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<pre style="margin: 0;">+<span id="LC248" class="line" lang="python"><span class="k" style="font-weight: 600;">def</span> <span class="nf" style="color: #900; font-weight: 600;">_annotate_method</span><span class="p">(</span><span class="n" style="color: #333;">taxa</span><span class="p">,</span> <span class="n" style="color: #333;">method</span><span class="p">):</span></span>
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<pre style="margin: 0;">+<span id="LC249" class="line" lang="python"> <span class="n" style="color: #333;">taxa</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">taxa</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">view</span><span class="p">(</span><span class="n" style="color: #333;">pd</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">DataFrame</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC250" class="line" lang="python"> <span class="n" style="color: #333;">taxa</span><span class="p">[</span><span class="s" style="color: #d14;">'Method'</span><span class="p">]</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">method</span></span>
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<pre style="margin: 0;">+<span id="LC251" class="line" lang="python"> <span class="k" style="font-weight: 600;">return</span> <span class="n" style="color: #333;">qiime2</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">Artifact</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">import_data</span><span class="p">(</span><span class="s" style="color: #d14;">'FeatureData[Taxonomy]'</span><span class="p">,</span> <span class="n" style="color: #333;">taxa</span><span class="p">)</span></span></pre>
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<a href="https://salsa.debian.org/med-team/q2-feature-classifier/commit/ce3f2d71dc19f5e2778f83d61d5b0be27a8bee02#a983074a9a2caf11735d1d54cef2229d079a453b"><strong>q2_feature_classifier/_skl.py</strong></a>
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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">@@ -9,7 +9,7 @@</td>
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<pre style="margin: 0;"> <span id="LC9" 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;">islice</span><span class="p">,</span> <span class="n" style="color: #333;">repeat</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;">copy</span> <span class="kn" style="font-weight: 600;">import</span> <span class="n" style="color: #333;">deepcopy</span></span>
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<pre style="margin: 0;"> <span id="LC11" class="line" lang="python"></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;"><span class="idiff left right">sklearn.externals.</span>joblib</span> <span class="kn" style="font-weight: 600;">import</span> <span class="n" style="color: #333;">Parallel</span><span class="p">,</span> <span class="n" style="color: #333;">delayed</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;">joblib</span> <span class="kn" style="font-weight: 600;">import</span> <span class="n" style="color: #333;">Parallel</span><span class="p">,</span> <span class="n" style="color: #333;">delayed</span></span>
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<pre style="margin: 0;"> <span id="LC13" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC14" class="line" lang="python"><span class="n" style="color: #333;">_specific_fitters</span> <span class="o" style="font-weight: 600;">=</span> <span class="p">[</span></span>
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<pre style="margin: 0;"> <span id="LC15" class="line" lang="python"> <span class="p">[</span><span class="s" style="color: #d14;">'naive_bayes'</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">@@ -38,7 +38,7 @@ def _extract_reads(reads):</td>
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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>
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<pre style="margin: 0;"> <span id="LC40" class="line" lang="python"><span class="k" style="font-weight: 600;">def</span> <span class="nf" style="color: #900; font-weight: 600;">predict</span><span class="p">(</span><span class="n" style="color: #333;">reads</span><span class="p">,</span> <span class="n" style="color: #333;">pipeline</span><span class="p">,</span> <span class="n" style="color: #333;">separator</span><span class="o" style="font-weight: 600;">=</span><span class="s" style="color: #d14;">';'</span><span class="p">,</span> <span class="n" style="color: #333;">chunk_size</span><span class="o" style="font-weight: 600;">=</span><span class="mi" style="color: #099;">262144</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="LC41" class="line" lang="python"> <span class="n" style="color: #333;">pre_dispatch</span><span class="o" style="font-weight: 600;">=</span><span class="s" style="color: #d14;">'2*n_jobs'</span><span class="p">,</span> <span class="n" style="color: #333;">confidence</span><span class="o" style="font-weight: 600;">=<span class="idiff left">-</span></span><span class="mf" style="color: #099;"><span class="idiff right">1.</span></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;">pre_dispatch</span><span class="o" style="font-weight: 600;">=</span><span class="s" style="color: #d14;">'2*n_jobs'</span><span class="p">,</span> <span class="n" style="color: #333;">confidence</span><span class="o" style="font-weight: 600;">=</span><span class="s" style="color: #d14;"><span class="idiff left right">'disable'</span></span><span class="p">):</span></span>
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<pre style="margin: 0;"> <span id="LC42" class="line" lang="python"> <span class="k" style="font-weight: 600;">return</span> <span class="p">(</span><span class="n" style="color: #333;">m</span> <span class="k" style="font-weight: 600;">for</span> <span class="n" style="color: #333;">c</span> <span class="ow" style="font-weight: 600;">in</span> <span class="n" style="color: #333;">Parallel</span><span class="p">(</span><span class="n" style="color: #333;">n_jobs</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">n_jobs</span><span class="p">,</span> <span class="n" style="color: #333;">batch_size</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="LC43" class="line" lang="python"> <span class="n" style="color: #333;">pre_dispatch</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">pre_dispatch</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC44" class="line" lang="python"> <span class="p">(</span><span class="n" style="color: #333;">delayed</span><span class="p">(</span><span class="n" style="color: #333;">_predict_chunk</span><span class="p">)(</span><span class="n" style="color: #333;">pipeline</span><span class="p">,</span> <span class="n" style="color: #333;">separator</span><span class="p">,</span> <span class="n" style="color: #333;">confidence</span><span class="p">,</span> <span class="n" style="color: #333;">chunk</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">@@ -46,7 +46,7 @@ def predict(reads, pipeline, separator=';', chunk_size=262144, n_jobs=1,</td>
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<pre style="margin: 0;"> <span id="LC46" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC47" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC48" class="line" lang="python"><span class="k" style="font-weight: 600;">def</span> <span class="nf" style="color: #900; font-weight: 600;">_predict_chunk</span><span class="p">(</span><span class="n" style="color: #333;">pipeline</span><span class="p">,</span> <span class="n" style="color: #333;">separator</span><span class="p">,</span> <span class="n" style="color: #333;">confidence</span><span class="p">,</span> <span class="n" style="color: #333;">chunk</span><span class="p">):</span></span>
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<pre style="margin: 0;">-<span id="LC49" class="line" lang="python"> <span class="k" style="font-weight: 600;">if</span> <span class="n" style="color: #333;">confidence</span> <span class="o" style="font-weight: 600;"><span class="idiff left"><</span></span><span class="idiff"> </span><span class="mf" style="color: #099;"><span class="idiff right">0.</span></span><span class="p">:</span></span>
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<pre style="margin: 0;">+<span id="LC49" class="line" lang="python"> <span class="k" style="font-weight: 600;">if</span> <span class="n" style="color: #333;">confidence</span> <span class="o" style="font-weight: 600;"><span class="idiff left">==</span></span><span class="idiff"> </span><span class="s" style="color: #d14;"><span class="idiff right">'disable'</span></span><span class="p">:</span></span>
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<pre style="margin: 0;"> <span id="LC50" class="line" lang="python"> <span class="k" style="font-weight: 600;">return</span> <span class="n" style="color: #333;">_predict_chunk_without_conf</span><span class="p">(</span><span class="n" style="color: #333;">pipeline</span><span class="p">,</span> <span class="n" style="color: #333;">chunk</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC51" 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="LC52" class="line" lang="python"> <span class="k" style="font-weight: 600;">return</span> <span class="n" style="color: #333;">_predict_chunk_with_conf</span><span class="p">(</span><span class="n" style="color: #333;">pipeline</span><span class="p">,</span> <span class="n" style="color: #333;">separator</span><span class="p">,</span> <span class="n" style="color: #333;">confidence</span><span class="p">,</span> <span class="n" style="color: #333;">chunk</span><span class="p">)</span></span>
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<a href="https://salsa.debian.org/med-team/q2-feature-classifier/commit/ce3f2d71dc19f5e2778f83d61d5b0be27a8bee02#71ef0c2491ce3a86a4eb9be230cd72759b8b3fbe"><strong>q2_feature_classifier/_taxonomic_classifier.py</strong></a>
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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">@@ -11,7 +11,7 @@ import tarfile</td>
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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;">os</span></span>
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<pre style="margin: 0;"> <span id="LC12" class="line" lang="python"></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;">sklearn</span></span>
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<pre style="margin: 0;">-<span id="LC14" class="line" lang="python"><span class="kn" style="font-weight: 600;"><span class="idiff left">from</span></span><span class="idiff"> </span><span class="nn" style="color: #555;"><span class="idiff">sklearn.externals</span></span><span class="idiff right"> </span><span class="kn" style="font-weight: 600;">import</span> <span class="n" style="color: #333;">joblib</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;">joblib</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;">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="LC16" class="line" lang="python"><span class="kn" style="font-weight: 600;">import</span> <span class="nn" style="color: #555;">qiime2.plugin</span></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.plugin.model</span> <span class="k" style="font-weight: 600;">as</span> <span class="n" style="color: #333;">model</span></span>
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<a href="https://salsa.debian.org/med-team/q2-feature-classifier/commit/ce3f2d71dc19f5e2778f83d61d5b0be27a8bee02#e1b612463caf8bb74f319ce3000e7a5fe7ccc722"><strong>q2_feature_classifier/_version.py</strong></a>
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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;">" (tag: 2019.<span class="idiff left right">4</span>.0)"</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">e2ba97ea232a02f4c489b51ff0481583d394a339</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;">"2019-0<span class="idiff left right">5-03 04:14:49</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: 2019.<span class="idiff left right">7</span>.0)"</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">bc7ed3a741779ccb32114a229af65cc8c1510743</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;">"2019-0<span class="idiff left right">7-30 18:15:57</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="LC31" 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">@@ -6,13 +6,19 @@</td>
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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;">tempfile</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> <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="LC11" 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="LC12" class="line" lang="python"></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;">q2_types.feature_data</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="LC14" class="line" lang="python"> <span class="n" style="color: #333;">FeatureData</span><span class="p">,</span> <span class="n" style="color: #333;">Taxonomy</span><span class="p">,</span> <span class="n" style="color: #333;">Sequence</span><span class="p">,</span> <span class="n" style="color: #333;">DNAFASTAFormat</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;">.plugin_setup</span> <span class="kn" style="font-weight: 600;">import</span> <span class="n" style="color: #333;">plugin</span><span class="p">,</span> <span class="n" style="color: #333;">citations</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;">qiime2.plugin</span> <span class="kn" style="font-weight: 600;">import</span> <span class="n" style="color: #333;">Int</span><span class="p">,</span> <span class="n" style="color: #333;">Str</span><span class="p">,</span> <span class="n" style="color: #333;">Float</span><span class="p">,</span> <span class="n" style="color: #333;">Choices</span><span class="p">,</span> <span class="n" style="color: #333;">Range</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;">._consensus_assignment</span> <span class="kn" style="font-weight: 600;">import</span> <span class="p">(</span><span class="n" style="color: #333;">_consensus_assignments</span><span class="p">,</span></span>
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<pre style="margin: 0;">-<span id="LC15" class="line" lang="python"> <span class="n" style="color: #333;">_get_default_unassignable_label</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC16" class="line" lang="python"><span class="kn" style="font-weight: 600;">from</span> <span class="nn" style="color: #555;">qiime2.plugin</span> <span class="kn" style="font-weight: 600;">import</span> <span class="n" style="color: #333;">Int</span><span class="p">,</span> <span class="n" style="color: #333;">Str</span><span class="p">,</span> <span class="n" style="color: #333;">Float</span><span class="p">,</span> <span class="n" style="color: #333;">Choices</span><span class="p">,</span> <span class="n" style="color: #333;">Range</span><span class="p">,</span> <span class="n" style="color: #333;">Bool</span></span>
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<pre style="margin: 0;">+<span id="LC17" class="line" lang="python"><span class="kn" style="font-weight: 600;">from</span> <span class="nn" style="color: #555;">._consensus_assignment</span> <span class="kn" style="font-weight: 600;">import</span> <span class="p">(</span><span class="n" style="color: #333;">_consensus_assignments</span><span class="p">,</span> <span class="n" style="color: #333;">_run_command</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC18" class="line" lang="python"> <span class="n" style="color: #333;">_get_default_unassignable_label</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;">_annotate_method</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC20" class="line" lang="python"><span class="kn" style="font-weight: 600;">from</span> <span class="nn" style="color: #555;">._taxonomic_classifier</span> <span class="kn" style="font-weight: 600;">import</span> <span class="n" style="color: #333;">TaxonomicClassifier</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;">.classifier</span> <span class="kn" style="font-weight: 600;">import</span> <span class="n" style="color: #333;">_classify_parameters</span><span class="p">,</span> <span class="n" style="color: #333;">_parameter_descriptions</span></span>
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<pre style="margin: 0;"> <span id="LC22" class="line" lang="python"></span>
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23
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<pre style="margin: 0;"> <span id="LC23" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC24" class="line" lang="python"><span class="k" style="font-weight: 600;">def</span> <span class="nf" style="color: #900; font-weight: 600;">classify_consensus_vsearch</span><span class="p">(</span><span class="n" style="color: #333;">query</span><span class="p">:</span> <span class="n" style="color: #333;">DNAFASTAFormat</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">@@ -25,53 +31,164 @@ def classify_consensus_vsearch(query: DNAFASTAFormat,</td>
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<pre style="margin: 0;"> <span id="LC31" class="line" lang="python"> <span class="n" style="color: #333;">min_consensus</span><span class="p">:</span> <span class="nb" style="color: #0086b3;">float</span> <span class="o" style="font-weight: 600;">=</span> <span class="mf" style="color: #099;">0.51</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;">unassignable_label</span><span class="p">:</span> <span class="nb" style="color: #0086b3;">str</span> <span class="o" style="font-weight: 600;">=</span></span>
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<pre style="margin: 0;"> <span id="LC33" class="line" lang="python"> <span class="n" style="color: #333;">_get_default_unassignable_label</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;">search_exact</span><span class="p">:</span> <span class="nb" style="color: #0086b3;">bool</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="LC35" class="line" lang="python"> <span class="n" style="color: #333;">top_hits_only</span><span class="p">:</span> <span class="nb" style="color: #0086b3;">bool</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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36
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<pre style="margin: 0;"> <span id="LC36" class="line" lang="python"> <span class="n" style="color: #333;">threads</span><span class="p">:</span> <span class="nb" style="color: #0086b3;">str</span> <span class="o" style="font-weight: 600;">=</span> <span class="mi" style="color: #099;">1</span><span class="p">)</span> <span class="o" style="font-weight: 600;">-></span> <span class="n" style="color: #333;">pd</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">DataFrame</span><span class="p">:</span></span>
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29
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37
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<pre style="margin: 0;"> <span id="LC37" class="line" lang="python"> <span class="n" style="color: #333;">seqs_fp</span> <span class="o" style="font-weight: 600;">=</span> <span class="nb" style="color: #0086b3;">str</span><span class="p">(</span><span class="n" style="color: #333;">query</span><span class="p">)</span></span>
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38
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<pre style="margin: 0;"> <span id="LC38" class="line" lang="python"> <span class="n" style="color: #333;">ref_fp</span> <span class="o" style="font-weight: 600;">=</span> <span class="nb" style="color: #0086b3;">str</span><span class="p">(</span><span class="n" style="color: #333;">reference_reads</span><span class="p">)</span></span>
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39
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<pre style="margin: 0;">+<span id="LC39" class="line" lang="python"> <span class="k" style="font-weight: 600;">if</span> <span class="n" style="color: #333;">maxaccepts</span> <span class="o" style="font-weight: 600;">==</span> <span class="s" style="color: #d14;">'all'</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;">maxaccepts</span> <span class="o" style="font-weight: 600;">=</span> <span class="mi" style="color: #099;">0</span></span>
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<pre style="margin: 0;"> <span id="LC41" class="line" lang="python"> <span class="n" style="color: #333;">cmd</span> <span class="o" style="font-weight: 600;">=</span> <span class="p">[</span><span class="s" style="color: #d14;">'vsearch'</span><span class="p">,</span> <span class="s" style="color: #d14;">'--usearch_global'</span><span class="p">,</span> <span class="n" style="color: #333;">seqs_fp</span><span class="p">,</span> <span class="s" style="color: #d14;">'--id'</span><span class="p">,</span> <span class="nb" style="color: #0086b3;">str</span><span class="p">(</span><span class="n" style="color: #333;">perc_identity</span><span class="p">),</span></span>
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<pre style="margin: 0;"> <span id="LC42" class="line" lang="python"> <span class="s" style="color: #d14;">'--query_cov'</span><span class="p">,</span> <span class="nb" style="color: #0086b3;">str</span><span class="p">(</span><span class="n" style="color: #333;">query_cov</span><span class="p">),</span> <span class="s" style="color: #d14;">'--strand'</span><span class="p">,</span> <span class="n" style="color: #333;">strand</span><span class="p">,</span> <span class="s" style="color: #d14;">'--maxaccepts'</span><span class="p">,</span></span>
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<pre style="margin: 0;"> <span id="LC43" class="line" lang="python"> <span class="nb" style="color: #0086b3;">str</span><span class="p">(</span><span class="n" style="color: #333;">maxaccepts</span><span class="p">),</span> <span class="s" style="color: #d14;">'--maxrejects'</span><span class="p">,</span> <span class="s" style="color: #d14;">'0'</span><span class="p">,</span> <span class="s" style="color: #d14;">'--output_no_hits'</span><span class="p">,</span> <span class="s" style="color: #d14;">'--db'</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;">ref_fp</span><span class="p">,</span> <span class="s" style="color: #d14;">'--threads'</span><span class="p">,</span> <span class="nb" style="color: #0086b3;">str</span><span class="p">(</span><span class="n" style="color: #333;">threads</span><span class="p">),</span> <span class="s" style="color: #d14;">'--blast6out'</span><span class="p">]</span></span>
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<pre style="margin: 0;">+<span id="LC44" class="line" lang="python"> <span class="n" style="color: #333;">ref_fp</span><span class="p">,</span> <span class="s" style="color: #d14;">'--threads'</span><span class="p">,</span> <span class="nb" style="color: #0086b3;">str</span><span class="p">(</span><span class="n" style="color: #333;">threads</span><span class="p">)]</span></span>
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<pre style="margin: 0;">+<span id="LC45" class="line" lang="python"> <span class="k" style="font-weight: 600;">if</span> <span class="n" style="color: #333;">search_exact</span><span class="p">:</span></span>
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<pre style="margin: 0;">+<span id="LC46" class="line" lang="python"> <span class="n" style="color: #333;">cmd</span><span class="p">[</span><span class="mi" style="color: #099;">1</span><span class="p">]</span> <span class="o" style="font-weight: 600;">=</span> <span class="s" style="color: #d14;">'--search_exact'</span></span>
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<pre style="margin: 0;">+<span id="LC47" class="line" lang="python"> <span class="k" style="font-weight: 600;">if</span> <span class="n" style="color: #333;">top_hits_only</span><span class="p">:</span></span>
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<pre style="margin: 0;">+<span id="LC48" class="line" lang="python"> <span class="n" style="color: #333;">cmd</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">append</span><span class="p">(</span><span class="s" style="color: #d14;">'--top_hits_only'</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC49" class="line" lang="python"> <span class="n" style="color: #333;">cmd</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">append</span><span class="p">(</span><span class="s" style="color: #d14;">'--blast6out'</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;">consensus</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">_consensus_assignments</span><span class="p">(</span></span>
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<pre style="margin: 0;"> <span id="LC51" class="line" lang="python"> <span class="n" style="color: #333;">cmd</span><span class="p">,</span> <span class="n" style="color: #333;">reference_taxonomy</span><span class="p">,</span> <span class="n" style="color: #333;">min_consensus</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">min_consensus</span><span class="p">,</span></span>
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<pre style="margin: 0;"> <span id="LC52" class="line" lang="python"> <span class="n" style="color: #333;">unassignable_label</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">unassignable_label</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC53" class="line" lang="python"> <span class="k" style="font-weight: 600;">return</span> <span class="n" style="color: #333;">consensus</span></span>
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<pre style="margin: 0;"> <span id="LC54" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC55" class="line" lang="python"></span>
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<pre style="margin: 0;">+<span id="LC56" class="line" lang="python"><span class="k" style="font-weight: 600;">def</span> <span class="nf" style="color: #900; font-weight: 600;">classify_hybrid_vsearch_sklearn</span><span class="p">(</span><span class="n" style="color: #333;">ctx</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC57" class="line" lang="python"> <span class="n" style="color: #333;">query</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC58" class="line" lang="python"> <span class="n" style="color: #333;">reference_reads</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC59" class="line" lang="python"> <span class="n" style="color: #333;">reference_taxonomy</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC60" class="line" lang="python"> <span class="n" style="color: #333;">classifier</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC61" class="line" lang="python"> <span class="n" style="color: #333;">maxaccepts</span><span class="o" style="font-weight: 600;">=</span><span class="mi" style="color: #099;">10</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC62" class="line" lang="python"> <span class="n" style="color: #333;">perc_identity</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="LC63" class="line" lang="python"> <span class="n" style="color: #333;">query_cov</span><span class="o" style="font-weight: 600;">=</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="LC64" class="line" lang="python"> <span class="n" style="color: #333;">strand</span><span class="o" style="font-weight: 600;">=</span><span class="s" style="color: #d14;">'both'</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC65" class="line" lang="python"> <span class="n" style="color: #333;">min_consensus</span><span class="o" style="font-weight: 600;">=</span><span class="mf" style="color: #099;">0.51</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC66" class="line" lang="python"> <span class="n" style="color: #333;">reads_per_batch</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="LC67" class="line" lang="python"> <span class="n" style="color: #333;">confidence</span><span class="o" style="font-weight: 600;">=</span><span class="mf" style="color: #099;">0.7</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC68" class="line" lang="python"> <span class="n" style="color: #333;">read_orientation</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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69
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<pre style="margin: 0;">+<span id="LC69" class="line" lang="python"> <span class="n" style="color: #333;">threads</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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70
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<pre style="margin: 0;">+<span id="LC70" class="line" lang="python"> <span class="n" style="color: #333;">prefilter</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="LC71" class="line" lang="python"> <span class="n" style="color: #333;">sample_size</span><span class="o" style="font-weight: 600;">=</span><span class="mi" style="color: #099;">1000</span><span class="p">,</span></span>
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72
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<pre style="margin: 0;">+<span id="LC72" class="line" lang="python"> <span class="n" style="color: #333;">randseed</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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73
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<pre style="margin: 0;">+<span id="LC73" class="line" lang="python"> <span class="n" style="color: #333;">exclude</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">ctx</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">get_action</span><span class="p">(</span><span class="s" style="color: #d14;">'quality_control'</span><span class="p">,</span> <span class="s" style="color: #d14;">'exclude_seqs'</span><span class="p">)</span></span>
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74
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<pre style="margin: 0;">+<span id="LC74" class="line" lang="python"> <span class="n" style="color: #333;">ccv</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">ctx</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">get_action</span><span class="p">(</span><span class="s" style="color: #d14;">'feature_classifier'</span><span class="p">,</span> <span class="s" style="color: #d14;">'classify_consensus_vsearch'</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;">cs</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">ctx</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">get_action</span><span class="p">(</span><span class="s" style="color: #d14;">'feature_classifier'</span><span class="p">,</span> <span class="s" style="color: #d14;">'classify_sklearn'</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;">filter_seqs</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">ctx</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">get_action</span><span class="p">(</span><span class="s" style="color: #d14;">'taxa'</span><span class="p">,</span> <span class="s" style="color: #d14;">'filter_seqs'</span><span class="p">)</span></span>
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77
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<pre style="margin: 0;">+<span id="LC77" class="line" lang="python"> <span class="n" style="color: #333;">merge</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">ctx</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">get_action</span><span class="p">(</span><span class="s" style="color: #d14;">'feature_table'</span><span class="p">,</span> <span class="s" style="color: #d14;">'merge_taxa'</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC78" class="line" lang="python"></span>
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<pre style="margin: 0;">+<span id="LC79" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># randomly subsample reference sequences for rough positive filter</span></span>
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80
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<pre style="margin: 0;">+<span id="LC80" class="line" lang="python"> <span class="k" style="font-weight: 600;">if</span> <span class="n" style="color: #333;">prefilter</span><span class="p">:</span></span>
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<pre style="margin: 0;">+<span id="LC81" class="line" lang="python"> <span class="n" style="color: #333;">ref</span> <span class="o" style="font-weight: 600;">=</span> <span class="nb" style="color: #0086b3;">str</span><span class="p">(</span><span class="n" style="color: #333;">reference_reads</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">view</span><span class="p">(</span><span class="n" style="color: #333;">DNAFASTAFormat</span><span class="p">))</span></span>
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82
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<pre style="margin: 0;">+<span id="LC82" class="line" lang="python"> <span class="k" style="font-weight: 600;">with</span> <span class="n" style="color: #333;">tempfile</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">NamedTemporaryFile</span><span class="p">()</span> <span class="k" style="font-weight: 600;">as</span> <span class="n" style="color: #333;">output</span><span class="p">:</span></span>
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83
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<pre style="margin: 0;">+<span id="LC83" class="line" lang="python"> <span class="n" style="color: #333;">cmd</span> <span class="o" style="font-weight: 600;">=</span> <span class="p">[</span><span class="s" style="color: #d14;">'vsearch'</span><span class="p">,</span> <span class="s" style="color: #d14;">'--fastx_subsample'</span><span class="p">,</span> <span class="n" style="color: #333;">ref</span><span class="p">,</span> <span class="s" style="color: #d14;">'--sample_size'</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC84" class="line" lang="python"> <span class="nb" style="color: #0086b3;">str</span><span class="p">(</span><span class="n" style="color: #333;">sample_size</span><span class="p">),</span> <span class="s" style="color: #d14;">'--randseed'</span><span class="p">,</span> <span class="nb" style="color: #0086b3;">str</span><span class="p">(</span><span class="n" style="color: #333;">randseed</span><span class="p">),</span></span>
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85
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<pre style="margin: 0;">+<span id="LC85" class="line" lang="python"> <span class="s" style="color: #d14;">'--fastaout'</span><span class="p">,</span> <span class="n" style="color: #333;">output</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">name</span><span class="p">]</span></span>
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<pre style="margin: 0;">+<span id="LC86" class="line" lang="python"> <span class="n" style="color: #333;">_run_command</span><span class="p">(</span><span class="n" style="color: #333;">cmd</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC87" class="line" lang="python"> <span class="n" style="color: #333;">sparse_reference</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">qiime2</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">Artifact</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">import_data</span><span class="p">(</span></span>
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88
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<pre style="margin: 0;">+<span id="LC88" class="line" lang="python"> <span class="s" style="color: #d14;">'FeatureData[Sequence]'</span><span class="p">,</span> <span class="n" style="color: #333;">output</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">name</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC89" class="line" lang="python"></span>
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<pre style="margin: 0;">+<span id="LC90" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># perform rough positive filter on query sequences</span></span>
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91
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<pre style="margin: 0;">+<span id="LC91" class="line" lang="python"> <span class="n" style="color: #333;">query</span><span class="p">,</span> <span class="n" style="color: #333;">misses</span><span class="p">,</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">exclude</span><span class="p">(</span></span>
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92
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<pre style="margin: 0;">+<span id="LC92" class="line" lang="python"> <span class="n" style="color: #333;">query_sequences</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">query</span><span class="p">,</span> <span class="n" style="color: #333;">reference_sequences</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">sparse_reference</span><span class="p">,</span></span>
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93
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<pre style="margin: 0;">+<span id="LC93" class="line" lang="python"> <span class="n" style="color: #333;">method</span><span class="o" style="font-weight: 600;">=</span><span class="s" style="color: #d14;">'vsearch'</span><span class="p">,</span> <span class="n" style="color: #333;">perc_identity</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">perc_identity</span><span class="p">,</span></span>
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94
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<pre style="margin: 0;">+<span id="LC94" class="line" lang="python"> <span class="n" style="color: #333;">perc_query_aligned</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">query_cov</span><span class="p">,</span> <span class="n" style="color: #333;">threads</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">threads</span><span class="p">)</span></span>
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95
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<pre style="margin: 0;">+<span id="LC95" class="line" lang="python"></span>
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<pre style="margin: 0;">+<span id="LC96" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># find exact matches, perform LCA consensus classification</span></span>
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97
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<pre style="margin: 0;">+<span id="LC97" class="line" lang="python"> <span class="n" style="color: #333;">taxa1</span><span class="p">,</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">ccv</span><span class="p">(</span><span class="n" style="color: #333;">query</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">query</span><span class="p">,</span> <span class="n" style="color: #333;">reference_reads</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">reference_reads</span><span class="p">,</span></span>
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98
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<pre style="margin: 0;">+<span id="LC98" class="line" lang="python"> <span class="n" style="color: #333;">reference_taxonomy</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">reference_taxonomy</span><span class="p">,</span> <span class="n" style="color: #333;">maxaccepts</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">maxaccepts</span><span class="p">,</span></span>
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99
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<pre style="margin: 0;">+<span id="LC99" class="line" lang="python"> <span class="n" style="color: #333;">strand</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">strand</span><span class="p">,</span> <span class="n" style="color: #333;">min_consensus</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">min_consensus</span><span class="p">,</span></span>
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100
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<pre style="margin: 0;">+<span id="LC100" class="line" lang="python"> <span class="n" style="color: #333;">search_exact</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;">threads</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">threads</span><span class="p">)</span></span>
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101
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<pre style="margin: 0;">+<span id="LC101" class="line" lang="python"></span>
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<pre style="margin: 0;">+<span id="LC102" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># Annotate taxonomic assignments with classification method</span></span>
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<pre style="margin: 0;">+<span id="LC103" class="line" lang="python"> <span class="n" style="color: #333;">taxa1</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">_annotate_method</span><span class="p">(</span><span class="n" style="color: #333;">taxa1</span><span class="p">,</span> <span class="s" style="color: #d14;">'VSEARCH'</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC104" class="line" lang="python"></span>
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<pre style="margin: 0;">+<span id="LC105" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># perform second pass classification on unassigned taxa</span></span>
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<pre style="margin: 0;">+<span id="LC106" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># filter out unassigned seqs</span></span>
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107
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<pre style="margin: 0;">+<span id="LC107" class="line" lang="python"> <span class="k" style="font-weight: 600;">try</span><span class="p">:</span></span>
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108
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<pre style="margin: 0;">+<span id="LC108" class="line" lang="python"> <span class="n" style="color: #333;">query</span><span class="p">,</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">filter_seqs</span><span class="p">(</span><span class="n" style="color: #333;">sequences</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">query</span><span class="p">,</span> <span class="n" style="color: #333;">taxonomy</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">taxa1</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC109" class="line" lang="python"> <span class="n" style="color: #333;">include</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">_get_default_unassignable_label</span><span class="p">())</span></span>
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<pre style="margin: 0;">+<span id="LC110" 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="LC111" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># get ValueError if all sequences are filtered out.</span></span>
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<pre style="margin: 0;">+<span id="LC112" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># so if no sequences are unassigned, return exact match results</span></span>
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<pre style="margin: 0;">+<span id="LC113" class="line" lang="python"> <span class="k" style="font-weight: 600;">return</span> <span class="n" style="color: #333;">taxa1</span></span>
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<pre style="margin: 0;">+<span id="LC114" class="line" lang="python"></span>
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<pre style="margin: 0;">+<span id="LC115" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># classify with sklearn classifier</span></span>
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<pre style="margin: 0;">+<span id="LC116" class="line" lang="python"> <span class="n" style="color: #333;">taxa2</span><span class="p">,</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">cs</span><span class="p">(</span><span class="n" style="color: #333;">reads</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">query</span><span class="p">,</span> <span class="n" style="color: #333;">classifier</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">classifier</span><span class="p">,</span></span>
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117
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<pre style="margin: 0;">+<span id="LC117" class="line" lang="python"> <span class="n" style="color: #333;">reads_per_batch</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">reads_per_batch</span><span class="p">,</span> <span class="n" style="color: #333;">n_jobs</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">threads</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC118" class="line" lang="python"> <span class="n" style="color: #333;">confidence</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">confidence</span><span class="p">,</span> <span class="n" style="color: #333;">read_orientation</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">read_orientation</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC119" class="line" lang="python"></span>
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<pre style="margin: 0;">+<span id="LC120" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># Annotate taxonomic assignments with classification method</span></span>
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<pre style="margin: 0;">+<span id="LC121" class="line" lang="python"> <span class="n" style="color: #333;">taxa2</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">_annotate_method</span><span class="p">(</span><span class="n" style="color: #333;">taxa2</span><span class="p">,</span> <span class="s" style="color: #d14;">'sklearn'</span><span class="p">)</span></span>
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122
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<pre style="margin: 0;">+<span id="LC122" class="line" lang="python"></span>
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<pre style="margin: 0;">+<span id="LC123" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># merge into one big happy result</span></span>
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<pre style="margin: 0;">+<span id="LC124" class="line" lang="python"> <span class="n" style="color: #333;">taxa</span><span class="p">,</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">merge</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="n" style="color: #333;">taxa2</span><span class="p">,</span> <span class="n" style="color: #333;">taxa1</span><span class="p">])</span></span>
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<pre style="margin: 0;">+<span id="LC125" class="line" lang="python"> <span class="k" style="font-weight: 600;">return</span> <span class="n" style="color: #333;">taxa</span></span>
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<pre style="margin: 0;">+<span id="LC126" class="line" lang="python"></span>
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<pre style="margin: 0;">+<span id="LC127" class="line" lang="python"></span>
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<pre style="margin: 0;">+<span id="LC128" 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="LC129" class="line" lang="python"> <span class="s" style="color: #d14;">'classification'</span><span class="p">:</span> <span class="s" style="color: #d14;">'The resulting taxonomy classifications.'</span><span class="p">}</span></span>
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<pre style="margin: 0;">+<span id="LC130" class="line" lang="python"></span>
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<pre style="margin: 0;">+<span id="LC131" class="line" lang="python"><span class="n" style="color: #333;">parameters</span> <span class="o" style="font-weight: 600;">=</span> <span class="p">{</span><span class="s" style="color: #d14;">'maxaccepts'</span><span class="p">:</span> <span class="n" style="color: #333;">Int</span> <span class="o" style="font-weight: 600;">%</span> <span class="n" style="color: #333;">Range</span><span class="p">(</span><span class="mi" style="color: #099;">1</span><span class="p">,</span> <span class="bp" style="color: #999;">None</span><span class="p">)</span> <span class="o" style="font-weight: 600;">|</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;">'all'</span><span class="p">]),</span></span>
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<pre style="margin: 0;">+<span id="LC132" class="line" lang="python"> <span class="s" style="color: #d14;">'perc_identity'</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;">True</span><span class="p">),</span></span>
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<pre style="margin: 0;">+<span id="LC133" class="line" lang="python"> <span class="s" style="color: #d14;">'query_cov'</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;">True</span><span class="p">),</span></span>
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<pre style="margin: 0;">+<span id="LC134" class="line" lang="python"> <span class="s" style="color: #d14;">'strand'</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;">'both'</span><span class="p">,</span> <span class="s" style="color: #d14;">'plus'</span><span class="p">]),</span></span>
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135
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<pre style="margin: 0;">+<span id="LC135" class="line" lang="python"> <span class="s" style="color: #d14;">'min_consensus'</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;">0.5</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;">True</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC136" 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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<pre style="margin: 0;">+<span id="LC137" class="line" lang="python"> <span class="s" style="color: #d14;">'threads'</span><span class="p">:</span> <span class="n" style="color: #333;">Int</span> <span class="o" style="font-weight: 600;">%</span> <span class="n" style="color: #333;">Range</span><span class="p">(</span><span class="mi" style="color: #099;">1</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="LC138" class="line" lang="python"></span>
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<pre style="margin: 0;">+<span id="LC139" class="line" lang="python"><span class="n" style="color: #333;">inputs</span> <span class="o" style="font-weight: 600;">=</span> <span class="p">{</span><span class="s" style="color: #d14;">'query'</span><span class="p">:</span> <span class="n" style="color: #333;">FeatureData</span><span class="p">[</span><span class="n" style="color: #333;">Sequence</span><span class="p">],</span></span>
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140
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<pre style="margin: 0;">+<span id="LC140" class="line" lang="python"> <span class="s" style="color: #d14;">'reference_reads'</span><span class="p">:</span> <span class="n" style="color: #333;">FeatureData</span><span class="p">[</span><span class="n" style="color: #333;">Sequence</span><span class="p">],</span></span>
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141
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<pre style="margin: 0;">+<span id="LC141" class="line" lang="python"> <span class="s" style="color: #d14;">'reference_taxonomy'</span><span class="p">:</span> <span class="n" style="color: #333;">FeatureData</span><span class="p">[</span><span class="n" style="color: #333;">Taxonomy</span><span class="p">]}</span></span>
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142
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<pre style="margin: 0;">+<span id="LC142" class="line" lang="python"></span>
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<pre style="margin: 0;">+<span id="LC143" 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;">'query'</span><span class="p">:</span> <span class="s" style="color: #d14;">'Sequences to classify taxonomically.'</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC144" class="line" lang="python"> <span class="s" style="color: #d14;">'reference_reads'</span><span class="p">:</span> <span class="s" style="color: #d14;">'reference sequences.'</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC145" class="line" lang="python"> <span class="s" style="color: #d14;">'reference_taxonomy'</span><span class="p">:</span> <span class="s" style="color: #d14;">'reference taxonomy labels.'</span><span class="p">}</span></span>
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<pre style="margin: 0;">+<span id="LC146" class="line" lang="python"></span>
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<pre style="margin: 0;">+<span id="LC147" 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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148
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<pre style="margin: 0;">+<span id="LC148" class="line" lang="python"> <span class="s" style="color: #d14;">'strand'</span><span class="p">:</span> <span class="s" style="color: #d14;">'Align against reference sequences in forward ("plus") '</span></span>
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149
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<pre style="margin: 0;">+<span id="LC149" class="line" lang="python"> <span class="s" style="color: #d14;">'or both directions ("both").'</span><span class="p">,</span></span>
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150
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<pre style="margin: 0;">+<span id="LC150" class="line" lang="python"> <span class="s" style="color: #d14;">'maxaccepts'</span><span class="p">:</span> <span class="s" style="color: #d14;">'Maximum number of hits to keep for each query. Set to '</span></span>
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151
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<pre style="margin: 0;">+<span id="LC151" class="line" lang="python"> <span class="s" style="color: #d14;">'"all" to keep all hits > perc_identity similarity.'</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC152" class="line" lang="python"> <span class="s" style="color: #d14;">'perc_identity'</span><span class="p">:</span> <span class="s" style="color: #d14;">'Reject match if percent identity to query is '</span></span>
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153
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<pre style="margin: 0;">+<span id="LC153" class="line" lang="python"> <span class="s" style="color: #d14;">'lower.'</span><span class="p">,</span></span>
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154
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<pre style="margin: 0;">+<span id="LC154" class="line" lang="python"> <span class="s" style="color: #d14;">'query_cov'</span><span class="p">:</span> <span class="s" style="color: #d14;">'Reject match if query alignment coverage per high-'</span></span>
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155
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<pre style="margin: 0;">+<span id="LC155" class="line" lang="python"> <span class="s" style="color: #d14;">'scoring pair is lower.'</span><span class="p">,</span></span>
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156
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<pre style="margin: 0;">+<span id="LC156" class="line" lang="python"> <span class="s" style="color: #d14;">'min_consensus'</span><span class="p">:</span> <span class="s" style="color: #d14;">'Minimum fraction of assignments must match top '</span></span>
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157
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<pre style="margin: 0;">+<span id="LC157" class="line" lang="python"> <span class="s" style="color: #d14;">'hit to be accepted as consensus assignment.'</span><span class="p">,</span></span>
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158
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<pre style="margin: 0;">+<span id="LC158" class="line" lang="python"> <span class="s" style="color: #d14;">'threads'</span><span class="p">:</span> <span class="s" style="color: #d14;">'Number of threads to use for job parallelization.'</span><span class="p">}</span></span>
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159
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<pre style="margin: 0;">+<span id="LC159" class="line" lang="python"></span>
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160
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<pre style="margin: 0;">+<span id="LC160" 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;">'classification'</span><span class="p">,</span> <span class="n" style="color: #333;">FeatureData</span><span class="p">[</span><span class="n" style="color: #333;">Taxonomy</span><span class="p">])]</span></span>
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161
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<pre style="margin: 0;">+<span id="LC161" class="line" lang="python"></span>
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162
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<pre style="margin: 0;">+<span id="LC162" class="line" lang="python"><span class="n" style="color: #333;">ignore_prefilter</span> <span class="o" style="font-weight: 600;">=</span> <span class="s" style="color: #d14;">' This parameter is ignored if `prefilter` is disabled.'</span></span>
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163
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<pre style="margin: 0;">+<span id="LC163" class="line" lang="python"></span>
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164
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<pre style="margin: 0;">+<span id="LC164" class="line" lang="python"></span>
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165
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<pre style="margin: 0;"> <span id="LC165" class="line" lang="python"><span class="n" style="color: #333;">plugin</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">methods</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">register_function</span><span class="p">(</span></span>
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166
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<pre style="margin: 0;"> <span id="LC166" class="line" lang="python"> <span class="n" style="color: #333;">function</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">classify_consensus_vsearch</span><span class="p">,</span></span>
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<pre style="margin: 0;">-<span id="LC43" class="line" lang="python"> <span class="n" style="color: #333;">inputs</span><span class="o" style="font-weight: 600;">=</span><span class="p">{</span><span class="s" style="color: #d14;">'query'</span><span class="p">:</span> <span class="n" style="color: #333;">FeatureData</span><span class="p">[</span><span class="n" style="color: #333;">Sequence</span><span class="p">],</span></span>
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<pre style="margin: 0;">-<span id="LC44" class="line" lang="python"> <span class="s" style="color: #d14;">'reference_reads'</span><span class="p">:</span> <span class="n" style="color: #333;">FeatureData</span><span class="p">[</span><span class="n" style="color: #333;">Sequence</span><span class="p">],</span></span>
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<pre style="margin: 0;">-<span id="LC45" class="line" lang="python"> <span class="s" style="color: #d14;">'reference_taxonomy'</span><span class="p">:</span> <span class="n" style="color: #333;">FeatureData</span><span class="p">[</span><span class="n" style="color: #333;">Taxonomy</span><span class="p">]},</span></span>
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<pre style="margin: 0;">-<span id="LC46" class="line" lang="python"> <span class="n" style="color: #333;">parameters</span><span class="o" style="font-weight: 600;">=</span><span class="p">{</span><span class="s" style="color: #d14;">'maxaccepts'</span><span class="p">:</span> <span class="n" style="color: #333;">Int</span> <span class="o" style="font-weight: 600;">%</span> <span class="n" style="color: #333;">Range</span><span class="p">(</span><span class="mi" style="color: #099;">0</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="LC47" class="line" lang="python"> <span class="s" style="color: #d14;">'perc_identity'</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;">True</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;">'query_cov'</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;">True</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;">'strand'</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;">'both'</span><span class="p">,</span> <span class="s" style="color: #d14;">'plus'</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;">'min_consensus'</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;">0.5</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;">True</span><span class="p">,</span></span>
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<pre style="margin: 0;">-<span id="LC51" 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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<pre style="margin: 0;">+<span id="LC167" class="line" lang="python"> <span class="n" style="color: #333;">inputs</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">inputs</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;">parameters</span><span class="o" style="font-weight: 600;">=</span><span class="p">{</span><span class="o" style="font-weight: 600;">**</span><span class="n" style="color: #333;">parameters</span><span class="p">,</span></span>
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<pre style="margin: 0;"> <span id="LC169" class="line" lang="python"> <span class="s" style="color: #d14;">'unassignable_label'</span><span class="p">:</span> <span class="n" style="color: #333;">Str</span><span class="p">,</span></span>
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<pre style="margin: 0;">-<span id="LC53" class="line" lang="python"> <span class="s" style="color: #d14;">'threads'</span><span class="p">:</span> <span class="n" style="color: #333;">Int</span><span class="p">},</span></span>
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<pre style="margin: 0;">-<span id="LC54" 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;">'classification'</span><span class="p">,</span> <span class="n" style="color: #333;">FeatureData</span><span class="p">[</span><span class="n" style="color: #333;">Taxonomy</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;">input_descriptions</span><span class="o" style="font-weight: 600;">=</span><span class="p">{</span><span class="s" style="color: #d14;">'query'</span><span class="p">:</span> <span class="s" style="color: #d14;">'Sequences to classify taxonomically.'</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;">'reference_reads'</span><span class="p">:</span> <span class="s" style="color: #d14;">'reference sequences.'</span><span class="p">,</span></span>
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<pre style="margin: 0;">-<span id="LC57" class="line" lang="python"> <span class="s" style="color: #d14;">'reference_taxonomy'</span><span class="p">:</span> <span class="s" style="color: #d14;">'reference taxonomy labels.'</span><span class="p">},</span></span>
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<pre style="margin: 0;">+<span id="LC170" class="line" lang="python"> <span class="s" style="color: #d14;">'search_exact'</span><span class="p">:</span> <span class="n" style="color: #333;">Bool</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 class="s" style="color: #d14;">'top_hits_only'</span><span class="p">:</span> <span class="n" style="color: #333;">Bool</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;">outputs</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">outputs</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC173" class="line" lang="python"> <span class="n" style="color: #333;">input_descriptions</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">input_descriptions</span><span class="p">,</span></span>
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<pre style="margin: 0;"> <span id="LC174" 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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<pre style="margin: 0;">-<span id="LC59" class="line" lang="python"> <span class="s" style="color: #d14;">'strand'</span><span class="p">:</span> <span class="p">(</span><span class="s" style="color: #d14;">'Align against reference sequences in forward ("plus") '</span></span>
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<pre style="margin: 0;">-<span id="LC60" class="line" lang="python"> <span class="s" style="color: #d14;">'or both directions ("both").'</span><span class="p">),</span></span>
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<pre style="margin: 0;">-<span id="LC61" class="line" lang="python"> <span class="s" style="color: #d14;">'maxaccepts'</span><span class="p">:</span> <span class="p">(</span><span class="s" style="color: #d14;">'Maximum number of hits to keep for each query. Set to '</span></span>
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<pre style="margin: 0;">-<span id="LC62" class="line" lang="python"> <span class="s" style="color: #d14;">'0 to keep all hits > perc_identity similarity. Must '</span></span>
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<pre style="margin: 0;">-<span id="LC63" class="line" lang="python"> <span class="s" style="color: #d14;">'be in range [0, infinity].'</span><span class="p">),</span></span>
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<pre style="margin: 0;">-<span id="LC64" class="line" lang="python"> <span class="s" style="color: #d14;">'perc_identity'</span><span class="p">:</span> <span class="p">(</span><span class="s" style="color: #d14;">'Reject match if percent identity to query is '</span></span>
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<pre style="margin: 0;">-<span id="LC65" class="line" lang="python"> <span class="s" style="color: #d14;">'lower. Must be in range [0.0, 1.0].'</span><span class="p">),</span></span>
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<pre style="margin: 0;">-<span id="LC66" class="line" lang="python"> <span class="s" style="color: #d14;">'query_cov'</span><span class="p">:</span> <span class="s" style="color: #d14;">'Reject match if query alignment coverage per high-'</span></span>
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<pre style="margin: 0;">-<span id="LC67" class="line" lang="python"> <span class="s" style="color: #d14;">'scoring pair is lower. Must be in range [0.0, 1.0].'</span><span class="p">,</span></span>
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<pre style="margin: 0;">-<span id="LC68" class="line" lang="python"> <span class="s" style="color: #d14;">'min_consensus'</span><span class="p">:</span> <span class="p">(</span><span class="s" style="color: #d14;">'Minimum fraction of assignments must match top '</span></span>
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<pre style="margin: 0;">-<span id="LC69" class="line" lang="python"> <span class="s" style="color: #d14;">'hit to be accepted as consensus assignment. Must '</span></span>
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<pre style="margin: 0;">-<span id="LC70" class="line" lang="python"> <span class="s" style="color: #d14;">'be in range (0.5, 1.0].'</span><span class="p">)</span></span>
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175
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<pre style="margin: 0;">+<span id="LC175" class="line" lang="python"> <span class="o" style="font-weight: 600;">**</span><span class="n" style="color: #333;">parameter_descriptions</span><span class="p">,</span></span>
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176
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<pre style="margin: 0;">+<span id="LC176" class="line" lang="python"> <span class="s" style="color: #d14;">'search_exact'</span><span class="p">:</span> <span class="s" style="color: #d14;">'Search for exact full-length matches to the query '</span></span>
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177
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<pre style="margin: 0;">+<span id="LC177" class="line" lang="python"> <span class="s" style="color: #d14;">'sequences. Only 100</span><span class="si" style="color: #d14;">% </span><span class="s" style="color: #d14;">exact matches are reported and '</span></span>
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178
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<pre style="margin: 0;">+<span id="LC178" class="line" lang="python"> <span class="s" style="color: #d14;">'this command is much faster than the default. If '</span></span>
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179
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<pre style="margin: 0;">+<span id="LC179" class="line" lang="python"> <span class="s" style="color: #d14;">'True, the perc_identity and query_cov settings are '</span></span>
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180
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<pre style="margin: 0;">+<span id="LC180" class="line" lang="python"> <span class="s" style="color: #d14;">'ignored. Note: query and reference reads must be '</span></span>
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181
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<pre style="margin: 0;">+<span id="LC181" class="line" lang="python"> <span class="s" style="color: #d14;">'trimmed to the exact same DNA locus (e.g., primer '</span></span>
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182
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<pre style="margin: 0;">+<span id="LC182" class="line" lang="python"> <span class="s" style="color: #d14;">'site) because only exact matches will be reported.'</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="s" style="color: #d14;">'top_hits_only'</span><span class="p">:</span> <span class="s" style="color: #d14;">'Only the top hits between the query and reference '</span></span>
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184
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<pre style="margin: 0;">+<span id="LC184" class="line" lang="python"> <span class="s" style="color: #d14;">'sequence sets are reported. For each query, the top '</span></span>
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<pre style="margin: 0;">+<span id="LC185" class="line" lang="python"> <span class="s" style="color: #d14;">'hit is the one presenting the highest percentage of '</span></span>
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186
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<pre style="margin: 0;">+<span id="LC186" class="line" lang="python"> <span class="s" style="color: #d14;">'identity. Multiple equally scored top hits will be '</span></span>
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187
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<pre style="margin: 0;">+<span id="LC187" class="line" lang="python"> <span class="s" style="color: #d14;">'used for consensus taxonomic assignment if '</span></span>
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188
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<pre style="margin: 0;">+<span id="LC188" class="line" lang="python"> <span class="s" style="color: #d14;">'maxaccepts is greater than 1.'</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 class="p">},</span></span>
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<pre style="margin: 0;">-<span id="LC72" 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 class="s" style="color: #d14;">'classification'</span><span class="p">:</span> <span class="s" style="color: #d14;">'The resulting taxonomy '</span></span>
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<pre style="margin: 0;">-<span id="LC73" class="line" lang="python"> <span class="s" style="color: #d14;">'classifications.'</span><span class="p">},</span></span>
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<pre style="margin: 0;">-<span id="LC74" 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;">'VSEARCH consensus taxonomy classifier'</span><span class="p">,</span></span>
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190
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<pre style="margin: 0;">+<span id="LC190" class="line" lang="python"> <span class="n" style="color: #333;">output_descriptions</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">output_descriptions</span><span class="p">,</span></span>
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191
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<pre style="margin: 0;">+<span id="LC191" 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;">'VSEARCH-based consensus taxonomy classifier'</span><span class="p">,</span></span>
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192
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<pre style="margin: 0;"> <span id="LC192" 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 class="s" style="color: #d14;">'Assign taxonomy to query sequences using VSEARCH. Performs '</span></span>
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193
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<pre style="margin: 0;"> <span id="LC193" class="line" lang="python"> <span class="s" style="color: #d14;">'VSEARCH global alignment between query and reference_reads, '</span></span>
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194
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<pre style="margin: 0;"> <span id="LC194" class="line" lang="python"> <span class="s" style="color: #d14;">'then assigns consensus taxonomy to each query sequence from '</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">@@ -81,3 +198,68 @@ plugin.methods.register_function(</td>
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198
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<pre style="margin: 0;"> <span id="LC198" class="line" lang="python"> <span class="s" style="color: #d14;">'choosing the top N hits, not the first N hits.'</span><span class="p">),</span></span>
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<pre style="margin: 0;"> <span id="LC199" class="line" lang="python"> <span class="n" style="color: #333;">citations</span><span class="o" style="font-weight: 600;">=</span><span class="p">[</span><span class="n" style="color: #333;">citations</span><span class="p">[</span><span class="s" style="color: #d14;">'rognes2016vsearch'</span><span class="p">]]</span></span>
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200
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<pre style="margin: 0;"> <span id="LC200" class="line" lang="python"><span class="p">)</span></span>
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201
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<pre style="margin: 0;">+<span id="LC201" class="line" lang="python"></span>
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202
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<pre style="margin: 0;">+<span id="LC202" class="line" lang="python"></span>
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203
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<pre style="margin: 0;">+<span id="LC203" class="line" lang="python"><span class="n" style="color: #333;">plugin</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">pipelines</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">register_function</span><span class="p">(</span></span>
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204
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<pre style="margin: 0;">+<span id="LC204" class="line" lang="python"> <span class="n" style="color: #333;">function</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">classify_hybrid_vsearch_sklearn</span><span class="p">,</span></span>
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205
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<pre style="margin: 0;">+<span id="LC205" class="line" lang="python"> <span class="n" style="color: #333;">inputs</span><span class="o" style="font-weight: 600;">=</span><span class="p">{</span><span class="o" style="font-weight: 600;">**</span><span class="n" style="color: #333;">inputs</span><span class="p">,</span> <span class="s" style="color: #d14;">'classifier'</span><span class="p">:</span> <span class="n" style="color: #333;">TaxonomicClassifier</span><span class="p">},</span></span>
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206
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<pre style="margin: 0;">+<span id="LC206" class="line" lang="python"> <span class="n" style="color: #333;">parameters</span><span class="o" style="font-weight: 600;">=</span><span class="p">{</span><span class="o" style="font-weight: 600;">**</span><span class="n" style="color: #333;">parameters</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC207" class="line" lang="python"> <span class="s" style="color: #d14;">'reads_per_batch'</span><span class="p">:</span> <span class="n" style="color: #333;">_classify_parameters</span><span class="p">[</span><span class="s" style="color: #d14;">'reads_per_batch'</span><span class="p">],</span></span>
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208
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<pre style="margin: 0;">+<span id="LC208" class="line" lang="python"> <span class="s" style="color: #d14;">'confidence'</span><span class="p">:</span> <span class="n" style="color: #333;">_classify_parameters</span><span class="p">[</span><span class="s" style="color: #d14;">'confidence'</span><span class="p">],</span></span>
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209
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<pre style="margin: 0;">+<span id="LC209" class="line" lang="python"> <span class="s" style="color: #d14;">'read_orientation'</span><span class="p">:</span> <span class="n" style="color: #333;">_classify_parameters</span><span class="p">[</span><span class="s" style="color: #d14;">'read_orientation'</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="s" style="color: #d14;">'prefilter'</span><span class="p">:</span> <span class="n" style="color: #333;">Bool</span><span class="p">,</span></span>
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211
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<pre style="margin: 0;">+<span id="LC211" class="line" lang="python"> <span class="s" style="color: #d14;">'sample_size'</span><span class="p">:</span> <span class="n" style="color: #333;">Int</span> <span class="o" style="font-weight: 600;">%</span> <span class="n" style="color: #333;">Range</span><span class="p">(</span><span class="mi" style="color: #099;">1</span><span class="p">,</span> <span class="bp" style="color: #999;">None</span><span class="p">),</span></span>
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212
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<pre style="margin: 0;">+<span id="LC212" class="line" lang="python"> <span class="s" style="color: #d14;">'randseed'</span><span class="p">:</span> <span class="n" style="color: #333;">Int</span> <span class="o" style="font-weight: 600;">%</span> <span class="n" style="color: #333;">Range</span><span class="p">(</span><span class="mi" style="color: #099;">0</span><span class="p">,</span> <span class="bp" style="color: #999;">None</span><span class="p">)},</span></span>
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213
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<pre style="margin: 0;">+<span id="LC213" class="line" lang="python"> <span class="n" style="color: #333;">outputs</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">outputs</span><span class="p">,</span></span>
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214
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<pre style="margin: 0;">+<span id="LC214" 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="o" style="font-weight: 600;">**</span><span class="n" style="color: #333;">input_descriptions</span><span class="p">,</span></span>
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215
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<pre style="margin: 0;">+<span id="LC215" class="line" lang="python"> <span class="s" style="color: #d14;">'classifier'</span><span class="p">:</span> <span class="s" style="color: #d14;">'Pre-trained sklearn taxonomic '</span></span>
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216
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<pre style="margin: 0;">+<span id="LC216" class="line" lang="python"> <span class="s" style="color: #d14;">'classifier for classifying the reads.'</span><span class="p">},</span></span>
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217
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<pre style="margin: 0;">+<span id="LC217" 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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218
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<pre style="margin: 0;">+<span id="LC218" class="line" lang="python"> <span class="o" style="font-weight: 600;">**</span><span class="p">{</span><span class="n" style="color: #333;">k</span><span class="p">:</span> <span class="n" style="color: #333;">parameter_descriptions</span><span class="p">[</span><span class="n" style="color: #333;">k</span><span class="p">]</span> <span class="k" style="font-weight: 600;">for</span> <span class="n" style="color: #333;">k</span> <span class="ow" style="font-weight: 600;">in</span> <span class="p">[</span></span>
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219
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<pre style="margin: 0;">+<span id="LC219" class="line" lang="python"> <span class="s" style="color: #d14;">'strand'</span><span class="p">,</span> <span class="s" style="color: #d14;">'maxaccepts'</span><span class="p">,</span> <span class="s" style="color: #d14;">'min_consensus'</span><span class="p">,</span> <span class="s" style="color: #d14;">'threads'</span><span class="p">]},</span></span>
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220
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<pre style="margin: 0;">+<span id="LC220" class="line" lang="python"> <span class="s" style="color: #d14;">'perc_identity'</span><span class="p">:</span> <span class="s" style="color: #d14;">'Percent sequence similarity to use for PREFILTER. '</span> <span class="o" style="font-weight: 600;">+</span></span>
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221
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<pre style="margin: 0;">+<span id="LC221" class="line" lang="python"> <span class="n" style="color: #333;">parameter_descriptions</span><span class="p">[</span><span class="s" style="color: #d14;">'perc_identity'</span><span class="p">]</span> <span class="o" style="font-weight: 600;">+</span> <span class="s" style="color: #d14;">' Set to a '</span></span>
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222
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<pre style="margin: 0;">+<span id="LC222" class="line" lang="python"> <span class="s" style="color: #d14;">'lower value to perform a rough pre-filter.'</span> <span class="o" style="font-weight: 600;">+</span></span>
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223
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<pre style="margin: 0;">+<span id="LC223" class="line" lang="python"> <span class="n" style="color: #333;">ignore_prefilter</span><span class="p">,</span></span>
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224
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<pre style="margin: 0;">+<span id="LC224" class="line" lang="python"> <span class="s" style="color: #d14;">'query_cov'</span><span class="p">:</span> <span class="s" style="color: #d14;">'Query coverage threshold to use for PREFILTER. '</span> <span class="o" style="font-weight: 600;">+</span></span>
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225
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<pre style="margin: 0;">+<span id="LC225" class="line" lang="python"> <span class="n" style="color: #333;">parameter_descriptions</span><span class="p">[</span><span class="s" style="color: #d14;">'query_cov'</span><span class="p">]</span> <span class="o" style="font-weight: 600;">+</span> <span class="s" style="color: #d14;">' Set to a '</span></span>
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226
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<pre style="margin: 0;">+<span id="LC226" class="line" lang="python"> <span class="s" style="color: #d14;">'lower value to perform a rough pre-filter.'</span> <span class="o" style="font-weight: 600;">+</span></span>
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227
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<pre style="margin: 0;">+<span id="LC227" class="line" lang="python"> <span class="n" style="color: #333;">ignore_prefilter</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC228" class="line" lang="python"> <span class="s" style="color: #d14;">'confidence'</span><span class="p">:</span> <span class="n" style="color: #333;">_parameter_descriptions</span><span class="p">[</span><span class="s" style="color: #d14;">'confidence'</span><span class="p">],</span></span>
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<pre style="margin: 0;">+<span id="LC229" class="line" lang="python"> <span class="s" style="color: #d14;">'read_orientation'</span><span class="p">:</span> <span class="s" style="color: #d14;">'Direction of reads with respect to reference '</span></span>
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<pre style="margin: 0;">+<span id="LC230" class="line" lang="python"> <span class="s" style="color: #d14;">'sequences in pre-trained sklearn classifier. '</span></span>
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<pre style="margin: 0;">+<span id="LC231" class="line" lang="python"> <span class="s" style="color: #d14;">'same will cause reads to be classified unchanged'</span></span>
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<pre style="margin: 0;">+<span id="LC232" class="line" lang="python"> <span class="s" style="color: #d14;">'; reverse-complement will cause reads to be '</span></span>
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<pre style="margin: 0;">+<span id="LC233" class="line" lang="python"> <span class="s" style="color: #d14;">'reversed and complemented prior to '</span></span>
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<pre style="margin: 0;">+<span id="LC234" class="line" lang="python"> <span class="s" style="color: #d14;">'classification. "auto" will autodetect '</span></span>
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<pre style="margin: 0;">+<span id="LC235" class="line" lang="python"> <span class="s" style="color: #d14;">'orientation based on the confidence estimates '</span></span>
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<pre style="margin: 0;">+<span id="LC236" class="line" lang="python"> <span class="s" style="color: #d14;">'for the first 100 reads.'</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC237" class="line" lang="python"> <span class="s" style="color: #d14;">'reads_per_batch'</span><span class="p">:</span> <span class="s" style="color: #d14;">'Number of reads to process in each batch for '</span></span>
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238
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<pre style="margin: 0;">+<span id="LC238" class="line" lang="python"> <span class="s" style="color: #d14;">'sklearn classification. If "auto", this parameter '</span></span>
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<pre style="margin: 0;">+<span id="LC239" class="line" lang="python"> <span class="s" style="color: #d14;">'is autoscaled to min(number of query sequences / '</span></span>
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240
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<pre style="margin: 0;">+<span id="LC240" class="line" lang="python"> <span class="s" style="color: #d14;">'threads, 20000).'</span><span class="p">,</span></span>
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241
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<pre style="margin: 0;">+<span id="LC241" class="line" lang="python"> <span class="s" style="color: #d14;">'prefilter'</span><span class="p">:</span> <span class="s" style="color: #d14;">'Toggle positive filter of query sequences on or off.'</span><span class="p">,</span></span>
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242
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<pre style="margin: 0;">+<span id="LC242" class="line" lang="python"> <span class="s" style="color: #d14;">'sample_size'</span><span class="p">:</span> <span class="s" style="color: #d14;">'Randomly extract the given number of sequences from '</span></span>
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<pre style="margin: 0;">+<span id="LC243" class="line" lang="python"> <span class="s" style="color: #d14;">'the reference database to use for prefiltering.'</span> <span class="o" style="font-weight: 600;">+</span></span>
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<pre style="margin: 0;">+<span id="LC244" class="line" lang="python"> <span class="n" style="color: #333;">ignore_prefilter</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC245" class="line" lang="python"> <span class="s" style="color: #d14;">'randseed'</span><span class="p">:</span> <span class="s" style="color: #d14;">'Use integer as a seed for the pseudo-random generator '</span></span>
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<pre style="margin: 0;">+<span id="LC246" class="line" lang="python"> <span class="s" style="color: #d14;">'used during prefiltering. A given seed always produces '</span></span>
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<pre style="margin: 0;">+<span id="LC247" class="line" lang="python"> <span class="s" style="color: #d14;">'the same output, which is useful for replicability. Set '</span></span>
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248
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<pre style="margin: 0;">+<span id="LC248" class="line" lang="python"> <span class="s" style="color: #d14;">'to 0 to use a pseudo-random seed.'</span> <span class="o" style="font-weight: 600;">+</span> <span class="n" style="color: #333;">ignore_prefilter</span><span class="p">,</span></span>
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249
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<pre style="margin: 0;">+<span id="LC249" class="line" lang="python"> <span class="p">},</span></span>
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250
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<pre style="margin: 0;">+<span id="LC250" class="line" lang="python"> <span class="n" style="color: #333;">output_descriptions</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">output_descriptions</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC251" 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;">'ALPHA Hybrid classifier: VSEARCH exact match + sklearn classifier'</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;">description</span><span class="o" style="font-weight: 600;">=</span><span class="p">(</span><span class="s" style="color: #d14;">'NOTE: THIS PIPELINE IS AN ALPHA RELEASE. Please report bugs '</span></span>
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<pre style="margin: 0;">+<span id="LC253" class="line" lang="python"> <span class="s" style="color: #d14;">'to https://forum.qiime2.org!</span><span class="se" style="color: #d14;">\n</span><span class="s" style="color: #d14;">'</span></span>
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<pre style="margin: 0;">+<span id="LC254" class="line" lang="python"> <span class="s" style="color: #d14;">'Assign taxonomy to query sequences using hybrid classifier. '</span></span>
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<pre style="margin: 0;">+<span id="LC255" class="line" lang="python"> <span class="s" style="color: #d14;">'First performs rough positive filter to remove artifact and '</span></span>
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<pre style="margin: 0;">+<span id="LC256" class="line" lang="python"> <span class="s" style="color: #d14;">'low-coverage sequences (use "prefilter" parameter to toggle '</span></span>
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<pre style="margin: 0;">+<span id="LC257" class="line" lang="python"> <span class="s" style="color: #d14;">'this step on or off). Second, performs VSEARCH exact match '</span></span>
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<pre style="margin: 0;">+<span id="LC258" class="line" lang="python"> <span class="s" style="color: #d14;">'between query and reference_reads to find exact matches, '</span></span>
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<pre style="margin: 0;">+<span id="LC259" class="line" lang="python"> <span class="s" style="color: #d14;">'followed by least common ancestor consensus taxonomy '</span></span>
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<pre style="margin: 0;">+<span id="LC260" class="line" lang="python"> <span class="s" style="color: #d14;">'assignment from among maxaccepts top hits, min_consensus of '</span></span>
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<pre style="margin: 0;">+<span id="LC261" class="line" lang="python"> <span class="s" style="color: #d14;">'which share that taxonomic assignment. Query sequences '</span></span>
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<pre style="margin: 0;">+<span id="LC262" class="line" lang="python"> <span class="s" style="color: #d14;">'without an exact match are then classified with a pre-'</span></span>
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<pre style="margin: 0;">+<span id="LC263" class="line" lang="python"> <span class="s" style="color: #d14;">'trained sklearn taxonomy classifier to predict the most '</span></span>
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<pre style="margin: 0;">+<span id="LC264" class="line" lang="python"> <span class="s" style="color: #d14;">'likely taxonomic lineage.'</span><span class="p">),</span></span>
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<pre style="margin: 0;">+<span id="LC265" class="line" lang="python"><span class="p">)</span></span></pre>
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<a href="https://salsa.debian.org/med-team/q2-feature-classifier/commit/ce3f2d71dc19f5e2778f83d61d5b0be27a8bee02#8b429ca6f0ecc3f6f870bba70ce4d821c711e1a6"><strong>q2_feature_classifier/classifier.py</strong></a>
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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">@@ -23,6 +23,7 @@ import sklearn</td>
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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;">numpy</span> <span class="kn" style="font-weight: 600;">import</span> <span class="n" style="color: #333;">median</span><span class="p">,</span> <span class="n" style="color: #333;">array</span><span class="p">,</span> <span class="n" style="color: #333;">ceil</span></span>
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<pre style="margin: 0;"> <span id="LC24" 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="LC25" class="line" lang="python"><span class="kn" style="font-weight: 600;">import</span> <span class="nn" style="color: #555;">skbio</span></span>
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<pre style="margin: 0;">+<span id="LC26" class="line" lang="python"><span class="kn" style="font-weight: 600;">import</span> <span class="nn" style="color: #555;">joblib</span></span>
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<pre style="margin: 0;"> <span id="LC27" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC28" class="line" lang="python"><span class="kn" style="font-weight: 600;">from</span> <span class="nn" style="color: #555;">._skl</span> <span class="kn" style="font-weight: 600;">import</span> <span class="n" style="color: #333;">fit_pipeline</span><span class="p">,</span> <span class="n" style="color: #333;">predict</span><span class="p">,</span> <span class="n" style="color: #333;">_specific_fitters</span></span>
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<pre style="margin: 0;"> <span id="LC29" class="line" lang="python"><span class="kn" style="font-weight: 600;">from</span> <span class="nn" style="color: #555;">._taxonomic_classifier</span> <span class="kn" style="font-weight: 600;">import</span> <span class="n" style="color: #333;">TaxonomicClassifier</span></span>
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<td class="diff-line-num unfold js-unfold new_line" data-linenumber="183" 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">@@ -182,7 +183,7 @@ def _autotune_reads_per_batch(reads, n_jobs):</td>
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<pre style="margin: 0;"> <span id="LC183" class="line" lang="python"> <span class="k" style="font-weight: 600;">raise</span> <span class="nb" style="color: #0086b3;">ValueError</span><span class="p">(</span><span class="s" style="color: #d14;">"Value other than zero must be specified as number "</span></span>
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<pre style="margin: 0;"> <span id="LC184" class="line" lang="python"> <span class="s" style="color: #d14;">"of jobs to run."</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC185" 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="LC185" class="line" lang="python"> <span class="n" style="color: #333;">n_jobs</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;"><span class="idiff left">sklearn</span></span><span class="o" style="font-weight: 600;"><span class="idiff">.</span></span><span class="n" style="color: #333;"><span class="idiff">externals</span></span><span class="o" style="font-weight: 600;"><span class="idiff right">.</span></span><span class="n" style="color: #333;">joblib</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">effective_n_jobs</span><span class="p">(</span><span class="n" style="color: #333;">n_jobs</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;">n_jobs</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">joblib</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">effective_n_jobs</span><span class="p">(</span><span class="n" style="color: #333;">n_jobs</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC187" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC188" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># we really only want to calculate this if running in parallel</span></span>
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<pre style="margin: 0;"> <span id="LC189" class="line" lang="python"> <span class="k" style="font-weight: 600;">if</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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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -200,7 +201,7 @@ def _autotune_reads_per_batch(reads, n_jobs):</td>
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201
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<pre style="margin: 0;"> <span id="LC201" class="line" lang="python"><span class="k" style="font-weight: 600;">def</span> <span class="nf" style="color: #900; font-weight: 600;">classify_sklearn</span><span class="p">(</span><span class="n" style="color: #333;">reads</span><span class="p">:</span> <span class="n" style="color: #333;">DNAFASTAFormat</span><span class="p">,</span> <span class="n" style="color: #333;">classifier</span><span class="p">:</span> <span class="n" style="color: #333;">Pipeline</span><span class="p">,</span></span>
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<pre style="margin: 0;"> <span id="LC202" class="line" lang="python"> <span class="n" style="color: #333;">reads_per_batch</span><span class="p">:</span> <span class="nb" style="color: #0086b3;">int</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;">n_jobs</span><span class="p">:</span> <span class="nb" style="color: #0086b3;">int</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="LC203" class="line" lang="python"> <span class="n" style="color: #333;">pre_dispatch</span><span class="p">:</span> <span class="nb" style="color: #0086b3;">str</span> <span class="o" style="font-weight: 600;">=</span> <span class="s" style="color: #d14;">'2*n_jobs'</span><span class="p">,</span> <span class="n" style="color: #333;">confidence</span><span class="p">:</span> <span class="nb" style="color: #0086b3;">float</span> <span class="o" style="font-weight: 600;">=</span> <span class="mf" style="color: #099;">0.7</span><span class="p">,</span></span>
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<pre style="margin: 0;">-<span id="LC203" class="line" lang="python"> <span class="n" style="color: #333;">read_orientation</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;"><span class="idiff left right">None</span></span></span>
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<pre style="margin: 0;">+<span id="LC204" class="line" lang="python"> <span class="n" style="color: #333;">read_orientation</span><span class="p">:</span> <span class="nb" style="color: #0086b3;">str</span> <span class="o" style="font-weight: 600;">=</span> <span class="s" style="color: #d14;"><span class="idiff left right">'auto'</span></span></span>
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<pre style="margin: 0;"> <span id="LC205" class="line" lang="python"> <span class="p">)</span> <span class="o" style="font-weight: 600;">-></span> <span class="n" style="color: #333;">pd</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">DataFrame</span><span class="p">:</span></span>
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<pre style="margin: 0;"> <span id="LC206" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># autotune reads per batch</span></span>
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<pre style="margin: 0;"> <span id="LC207" class="line" lang="python"> <span class="k" style="font-weight: 600;">if</span> <span class="n" style="color: #333;">reads_per_batch</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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<td class="line_content match " style="padding-left: 0.5em; padding-right: 0.5em; color: rgba(0,0,0,0.3);" bgcolor="#fafafa">@@ -226,9 +227,35 @@ _classify_parameters = {</td>
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<pre style="margin: 0;"> <span id="LC227" class="line" lang="python"> <span class="s" style="color: #d14;">'reads_per_batch'</span><span class="p">:</span> <span class="n" style="color: #333;">Int</span> <span class="o" style="font-weight: 600;">%</span> <span class="n" style="color: #333;">Range</span><span class="p">(</span><span class="mi" style="color: #099;">0</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="LC228" class="line" lang="python"> <span class="s" style="color: #d14;">'n_jobs'</span><span class="p">:</span> <span class="n" style="color: #333;">Int</span><span class="p">,</span></span>
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<pre style="margin: 0;"> <span id="LC229" class="line" lang="python"> <span class="s" style="color: #d14;">'pre_dispatch'</span><span class="p">:</span> <span class="n" style="color: #333;">Str</span><span class="p">,</span></span>
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<pre style="margin: 0;">-<span id="LC229" class="line" lang="python"> <span class="s" style="color: #d14;">'confidence'</span><span class="p">:</span> <span class="n" style="color: #333;">Float</span><span class="p">,</span></span>
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<pre style="margin: 0;">-<span id="LC230" class="line" lang="python"> <span class="s" style="color: #d14;">'read_orientation'</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;">'same'</span><span class="p">,</span> <span class="s" style="color: #d14;">'reverse-complement'</span><span class="p">])}</span></span>
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<pre style="margin: 0;">-<span id="LC231" class="line" lang="python"></span>
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<pre style="margin: 0;">+<span id="LC230" class="line" lang="python"> <span class="s" style="color: #d14;">'confidence'</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>
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<pre style="margin: 0;">+<span id="LC231" 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_start</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;">inclusive_end</span><span class="o" style="font-weight: 600;">=</span><span class="bp" style="color: #999;">True</span><span class="p">)</span> <span class="o" style="font-weight: 600;">|</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>
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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;">'disable'</span><span class="p">]),</span></span>
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<pre style="margin: 0;">+<span id="LC233" class="line" lang="python"> <span class="s" style="color: #d14;">'read_orientation'</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;">'same'</span><span class="p">,</span> <span class="s" style="color: #d14;">'reverse-complement'</span><span class="p">,</span> <span class="s" style="color: #d14;">'auto'</span><span class="p">])}</span></span>
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<pre style="margin: 0;">+<span id="LC234" class="line" lang="python"></span>
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<pre style="margin: 0;">+<span id="LC235" 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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<pre style="margin: 0;">+<span id="LC236" class="line" lang="python"> <span class="s" style="color: #d14;">'confidence'</span><span class="p">:</span> <span class="s" style="color: #d14;">'Confidence threshold for limiting '</span></span>
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<pre style="margin: 0;">+<span id="LC237" class="line" lang="python"> <span class="s" style="color: #d14;">'taxonomic depth. Set to "disable" to disable '</span></span>
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<pre style="margin: 0;">+<span id="LC238" class="line" lang="python"> <span class="s" style="color: #d14;">'confidence calculation, or 0 to calculate '</span></span>
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<pre style="margin: 0;">+<span id="LC239" class="line" lang="python"> <span class="s" style="color: #d14;">'confidence but not apply it to limit the '</span></span>
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<pre style="margin: 0;">+<span id="LC240" class="line" lang="python"> <span class="s" style="color: #d14;">'taxonomic depth of the assignments.'</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;">'read_orientation'</span><span class="p">:</span> <span class="s" style="color: #d14;">'Direction of reads with '</span></span>
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<pre style="margin: 0;">+<span id="LC242" class="line" lang="python"> <span class="s" style="color: #d14;">'respect to reference sequences. same will cause '</span></span>
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<pre style="margin: 0;">+<span id="LC243" class="line" lang="python"> <span class="s" style="color: #d14;">'reads to be classified unchanged; reverse-'</span></span>
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<pre style="margin: 0;">+<span id="LC244" class="line" lang="python"> <span class="s" style="color: #d14;">'complement will cause reads to be reversed '</span></span>
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<pre style="margin: 0;">+<span id="LC245" class="line" lang="python"> <span class="s" style="color: #d14;">'and complemented prior to classification. '</span></span>
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<pre style="margin: 0;">+<span id="LC246" class="line" lang="python"> <span class="s" style="color: #d14;">'"auto" will autodetect orientation based on the '</span></span>
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<pre style="margin: 0;">+<span id="LC247" class="line" lang="python"> <span class="s" style="color: #d14;">'confidence estimates for the first 100 reads.'</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;">'reads_per_batch'</span><span class="p">:</span> <span class="s" style="color: #d14;">'Number of reads to process in each batch. If "auto", '</span></span>
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<pre style="margin: 0;">+<span id="LC249" class="line" lang="python"> <span class="s" style="color: #d14;">'this parameter is autoscaled to '</span></span>
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<pre style="margin: 0;">+<span id="LC250" class="line" lang="python"> <span class="s" style="color: #d14;">'min( number of query sequences / n_jobs, 20000).'</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC251" class="line" lang="python"> <span class="s" style="color: #d14;">'n_jobs'</span><span class="p">:</span> <span class="s" style="color: #d14;">'The maximum number of concurrently worker processes. If -1 '</span></span>
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<pre style="margin: 0;">+<span id="LC252" class="line" lang="python"> <span class="s" style="color: #d14;">'all CPUs are used. If 1 is given, no parallel computing '</span></span>
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<pre style="margin: 0;">+<span id="LC253" class="line" lang="python"> <span class="s" style="color: #d14;">'code is used at all, which is useful for debugging. For '</span></span>
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<pre style="margin: 0;">+<span id="LC254" class="line" lang="python"> <span class="s" style="color: #d14;">'n_jobs below -1, (n_cpus + 1 + n_jobs) are used. Thus for '</span></span>
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<pre style="margin: 0;">+<span id="LC255" class="line" lang="python"> <span class="s" style="color: #d14;">'n_jobs = -2, all CPUs but one are used.'</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC256" class="line" lang="python"> <span class="s" style="color: #d14;">'pre_dispatch'</span><span class="p">:</span> <span class="s" style="color: #d14;">'"all" or expression, as in "3*n_jobs". The number of '</span></span>
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<pre style="margin: 0;">+<span id="LC257" class="line" lang="python"> <span class="s" style="color: #d14;">'batches (of tasks) to be pre-dispatched.'</span></span>
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<pre style="margin: 0;">+<span id="LC258" class="line" lang="python"><span class="p">}</span></span>
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<pre style="margin: 0;"> <span id="LC259" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC260" class="line" lang="python"><span class="n" style="color: #333;">plugin</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">methods</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">register_function</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;">function</span><span class="o" style="font-weight: 600;">=</span><span class="n" style="color: #333;">classify_sklearn</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">@@ -242,30 +269,7 @@ plugin.methods.register_function(</td>
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<pre style="margin: 0;"> <span id="LC269" class="line" lang="python"> <span class="s" style="color: #d14;">'reads'</span><span class="p">:</span> <span class="s" style="color: #d14;">'The feature data to be classified.'</span><span class="p">,</span></span>
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<pre style="margin: 0;"> <span id="LC270" class="line" lang="python"> <span class="s" style="color: #d14;">'classifier'</span><span class="p">:</span> <span class="s" style="color: #d14;">'The taxonomic classifier for classifying the reads.'</span></span>
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<pre style="margin: 0;"> <span id="LC271" class="line" lang="python"> <span class="p">},</span></span>
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<pre style="margin: 0;">-<span id="LC245" 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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<pre style="margin: 0;">-<span id="LC246" class="line" lang="python"> <span class="s" style="color: #d14;">'confidence'</span><span class="p">:</span> <span class="s" style="color: #d14;">'Confidence threshold for limiting '</span></span>
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<pre style="margin: 0;">-<span id="LC247" class="line" lang="python"> <span class="s" style="color: #d14;">'taxonomic depth. Provide -1 to disable '</span></span>
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<pre style="margin: 0;">-<span id="LC248" class="line" lang="python"> <span class="s" style="color: #d14;">'confidence calculation, or 0 to calculate '</span></span>
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<pre style="margin: 0;">-<span id="LC249" class="line" lang="python"> <span class="s" style="color: #d14;">'confidence but not apply it to limit the '</span></span>
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<pre style="margin: 0;">-<span id="LC250" class="line" lang="python"> <span class="s" style="color: #d14;">'taxonomic depth of the assignments.'</span><span class="p">,</span></span>
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<pre style="margin: 0;">-<span id="LC251" class="line" lang="python"> <span class="s" style="color: #d14;">'read_orientation'</span><span class="p">:</span> <span class="s" style="color: #d14;">'Direction of reads with '</span></span>
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<pre style="margin: 0;">-<span id="LC252" class="line" lang="python"> <span class="s" style="color: #d14;">'respect to reference sequences. same will cause '</span></span>
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<pre style="margin: 0;">-<span id="LC253" class="line" lang="python"> <span class="s" style="color: #d14;">'reads to be classified unchanged; reverse-'</span></span>
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<pre style="margin: 0;">-<span id="LC254" class="line" lang="python"> <span class="s" style="color: #d14;">'complement will cause reads to be reversed '</span></span>
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<pre style="margin: 0;">-<span id="LC255" class="line" lang="python"> <span class="s" style="color: #d14;">'and complemented prior to classification. '</span></span>
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<pre style="margin: 0;">-<span id="LC256" class="line" lang="python"> <span class="s" style="color: #d14;">'Default is to autodetect based on the '</span></span>
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<pre style="margin: 0;">-<span id="LC257" class="line" lang="python"> <span class="s" style="color: #d14;">'confidence estimates for the first 100 reads.'</span><span class="p">,</span></span>
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<pre style="margin: 0;">-<span id="LC258" class="line" lang="python"> <span class="s" style="color: #d14;">'reads_per_batch'</span><span class="p">:</span> <span class="s" style="color: #d14;">'Number of reads to process in each batch. If 0, '</span></span>
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<pre style="margin: 0;">-<span id="LC259" class="line" lang="python"> <span class="s" style="color: #d14;">'this parameter is autoscaled to '</span></span>
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<pre style="margin: 0;">-<span id="LC260" class="line" lang="python"> <span class="s" style="color: #d14;">'min( number of query sequences / n_jobs, 20000).'</span><span class="p">,</span></span>
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<pre style="margin: 0;">-<span id="LC261" class="line" lang="python"> <span class="s" style="color: #d14;">'n_jobs'</span><span class="p">:</span> <span class="s" style="color: #d14;">'The maximum number of concurrently worker processes. If -1 '</span></span>
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<pre style="margin: 0;">-<span id="LC262" class="line" lang="python"> <span class="s" style="color: #d14;">'all CPUs are used. If 1 is given, no parallel computing '</span></span>
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<pre style="margin: 0;">-<span id="LC263" class="line" lang="python"> <span class="s" style="color: #d14;">'code is used at all, which is useful for debugging. For '</span></span>
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<pre style="margin: 0;">-<span id="LC264" class="line" lang="python"> <span class="s" style="color: #d14;">'n_jobs below -1, (n_cpus + 1 + n_jobs) are used. Thus for '</span></span>
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<pre style="margin: 0;">-<span id="LC265" class="line" lang="python"> <span class="s" style="color: #d14;">'n_jobs = -2, all CPUs but one are used.'</span><span class="p">,</span></span>
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<pre style="margin: 0;">-<span id="LC266" class="line" lang="python"> <span class="s" style="color: #d14;">'pre_dispatch'</span><span class="p">:</span> <span class="s" style="color: #d14;">'"all" or expression, as in "3*n_jobs". The number of '</span></span>
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<pre style="margin: 0;">-<span id="LC267" class="line" lang="python"> <span class="s" style="color: #d14;">'batches (of tasks) to be pre-dispatched.'</span></span>
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<pre style="margin: 0;">-<span id="LC268" class="line" lang="python"> <span class="p">},</span></span>
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<pre style="margin: 0;">+<span id="LC272" 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 class="o" style="font-weight: 600;">**</span><span class="n" style="color: #333;">_parameter_descriptions</span><span class="p">},</span></span>
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<pre style="margin: 0;"> <span id="LC273" class="line" lang="python"> <span class="n" style="color: #333;">citations</span><span class="o" style="font-weight: 600;">=</span><span class="p">[</span><span class="n" style="color: #333;">citations</span><span class="p">[</span><span class="s" style="color: #d14;">'pedregosa2011scikit'</span><span class="p">]]</span></span>
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<pre style="margin: 0;"> <span id="LC274" class="line" lang="python"><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC275" 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">@@ -59,8 +59,7 @@ class ClassifierTests(FeatureClassifierTestPluginBase):</td>
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<pre style="margin: 0;"> <span id="LC59" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># should populate the class weight of a pipeline</span></span>
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<pre style="margin: 0;"> <span id="LC60" class="line" lang="python"> <span class="n" style="color: #333;">weights</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">Artifact</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">import_data</span><span class="p">(</span></span>
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<pre style="margin: 0;"> <span id="LC61" class="line" lang="python"> <span class="s" style="color: #d14;">'FeatureTable[RelativeFrequency]'</span><span class="p">,</span></span>
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<pre style="margin: 0;">-<span id="LC62" class="line" lang="python"> <span class="bp" style="color: #999;">self</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">get_data_path</span><span class="p">(</span><span class="s" style="color: #d14;">'class_weight.biom'</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;">view_type</span><span class="o" style="font-weight: 600;">=</span><span class="s" style="color: #d14;">'BIOMV100Format'</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC62" class="line" lang="python"> <span class="bp" style="color: #999;">self</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">get_data_path</span><span class="p">(</span><span class="s" style="color: #d14;">'class_weight.biom'</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;">table</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">weights</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">view</span><span class="p">(</span><span class="n" style="color: #333;">biom</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">Table</span><span class="p">)</span></span>
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<pre style="margin: 0;"> <span id="LC64" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC65" class="line" lang="python"> <span class="n" style="color: #333;">svc_spec</span> <span class="o" style="font-weight: 600;">=</span> <span class="p">[[</span><span class="s" style="color: #d14;">'feat_ext'</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">@@ -89,8 +88,7 @@ class ClassifierTests(FeatureClassifierTestPluginBase):</td>
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<pre style="margin: 0;"> <span id="LC88" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># we should be able to input class_weight to fit_classifier</span></span>
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<pre style="margin: 0;"> <span id="LC89" class="line" lang="python"> <span class="n" style="color: #333;">weights</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">Artifact</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">import_data</span><span class="p">(</span></span>
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<pre style="margin: 0;"> <span id="LC90" class="line" lang="python"> <span class="s" style="color: #d14;">'FeatureTable[RelativeFrequency]'</span><span class="p">,</span></span>
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<pre style="margin: 0;">-<span id="LC92" class="line" lang="python"> <span class="bp" style="color: #999;">self</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">get_data_path</span><span class="p">(</span><span class="s" style="color: #d14;">'class_weight.biom'</span><span class="p">),</span></span>
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<pre style="margin: 0;">-<span id="LC93" class="line" lang="python"> <span class="n" style="color: #333;">view_type</span><span class="o" style="font-weight: 600;">=</span><span class="s" style="color: #d14;">'BIOMV100Format'</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC91" class="line" lang="python"> <span class="bp" style="color: #999;">self</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">get_data_path</span><span class="p">(</span><span class="s" style="color: #d14;">'class_weight.biom'</span><span class="p">))</span></span>
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<pre style="margin: 0;"> <span id="LC92" class="line" lang="python"> <span class="n" style="color: #333;">reads</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">Artifact</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">import_data</span><span class="p">(</span></span>
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<pre style="margin: 0;"> <span id="LC93" class="line" lang="python"> <span class="s" style="color: #d14;">'FeatureData[Sequence]'</span><span class="p">,</span></span>
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<pre style="margin: 0;"> <span id="LC94" class="line" lang="python"> <span class="bp" style="color: #999;">self</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">get_data_path</span><span class="p">(</span><span class="s" style="color: #d14;">'se-dna-sequences.fasta'</span><span class="p">))</span></span>
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<a href="https://salsa.debian.org/med-team/q2-feature-classifier/commit/ce3f2d71dc19f5e2778f83d61d5b0be27a8bee02#9119ec5d547606e633f235bfd8d07e884992502a"><strong>q2_feature_classifier/tests/test_consensus_assignment.py</strong></a>
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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">@@ -9,6 +9,8 @@</td>
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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>
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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;">qiime2.sdk</span> <span class="kn" style="font-weight: 600;">import</span> <span class="n" style="color: #333;">Artifact</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;">qiime2.plugins</span> <span class="kn" style="font-weight: 600;">import</span> <span class="n" style="color: #333;">feature_classifier</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;">q2_feature_classifier._skl</span> <span class="kn" style="font-weight: 600;">import</span> <span class="n" style="color: #333;">_specific_fitters</span></span>
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14
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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;">q2_feature_classifier._blast</span> <span class="kn" style="font-weight: 600;">import</span> <span class="n" style="color: #333;">classify_consensus_blast</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;">q2_feature_classifier._vsearch</span> <span class="kn" style="font-weight: 600;">import</span> <span class="n" style="color: #333;">classify_consensus_vsearch</span></span>
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<pre style="margin: 0;"> <span id="LC16" class="line" lang="python"><span class="kn" style="font-weight: 600;">from</span> <span class="nn" style="color: #555;">q2_feature_classifier._consensus_assignment</span> <span class="kn" style="font-weight: 600;">import</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">@@ -55,6 +57,88 @@ class ConsensusAssignmentsTests(FeatureClassifierTestPluginBase):</td>
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<pre style="margin: 0;"> <span id="LC57" class="line" lang="python"> <span class="n" style="color: #333;">right</span> <span class="o" style="font-weight: 600;">+=</span> <span class="n" style="color: #333;">tax</span><span class="p">[</span><span class="n" style="color: #333;">taxon</span><span class="p">]</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">startswith</span><span class="p">(</span><span class="n" style="color: #333;">res</span><span class="p">[</span><span class="n" style="color: #333;">taxon</span><span class="p">])</span></span>
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<pre style="margin: 0;"> <span id="LC58" class="line" lang="python"> <span class="bp" style="color: #999;">self</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">assertGreater</span><span class="p">(</span><span class="n" style="color: #333;">right</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;">res</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="LC59" class="line" lang="python"></span>
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<pre style="margin: 0;">+<span id="LC60" class="line" lang="python"> <span class="k" style="font-weight: 600;">def</span> <span class="nf" style="color: #900; font-weight: 600;">test_vsearch_search_exact</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="LC61" class="line" lang="python"> <span class="n" style="color: #333;">result</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">classify_consensus_vsearch</span><span class="p">(</span><span class="bp" style="color: #999;">self</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">reads</span><span class="p">,</span> <span class="bp" style="color: #999;">self</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">reads</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC62" class="line" lang="python"> <span class="bp" style="color: #999;">self</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">taxonomy</span><span class="p">,</span> <span class="n" style="color: #333;">search_exact</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="LC63" 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;">result</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">Taxon</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">to_dict</span><span class="p">()</span></span>
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<pre style="margin: 0;">+<span id="LC64" class="line" lang="python"> <span class="n" style="color: #333;">tax</span> <span class="o" style="font-weight: 600;">=</span> <span class="bp" style="color: #999;">self</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">taxonomy</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">to_dict</span><span class="p">()</span></span>
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<pre style="margin: 0;">+<span id="LC65" class="line" lang="python"> <span class="n" style="color: #333;">right</span> <span class="o" style="font-weight: 600;">=</span> <span class="mf" style="color: #099;">0.</span></span>
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<pre style="margin: 0;">+<span id="LC66" class="line" lang="python"> <span class="k" style="font-weight: 600;">for</span> <span class="n" style="color: #333;">taxon</span> <span class="ow" style="font-weight: 600;">in</span> <span class="n" style="color: #333;">res</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;">right</span> <span class="o" style="font-weight: 600;">+=</span> <span class="n" style="color: #333;">tax</span><span class="p">[</span><span class="n" style="color: #333;">taxon</span><span class="p">]</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">startswith</span><span class="p">(</span><span class="n" style="color: #333;">res</span><span class="p">[</span><span class="n" style="color: #333;">taxon</span><span class="p">])</span></span>
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<pre style="margin: 0;">+<span id="LC68" class="line" lang="python"> <span class="bp" style="color: #999;">self</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">assertGreater</span><span class="p">(</span><span class="n" style="color: #333;">right</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;">res</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="LC69" class="line" lang="python"></span>
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<pre style="margin: 0;">+<span id="LC70" class="line" lang="python"> <span class="k" style="font-weight: 600;">def</span> <span class="nf" style="color: #900; font-weight: 600;">test_vsearch_top_hits_only</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="LC71" class="line" lang="python"> <span class="n" style="color: #333;">result</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">classify_consensus_vsearch</span><span class="p">(</span><span class="bp" style="color: #999;">self</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">reads</span><span class="p">,</span> <span class="bp" style="color: #999;">self</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">reads</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC72" class="line" lang="python"> <span class="bp" style="color: #999;">self</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">taxonomy</span><span class="p">,</span> <span class="n" style="color: #333;">top_hits_only</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="LC73" 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;">result</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">Taxon</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">to_dict</span><span class="p">()</span></span>
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<pre style="margin: 0;">+<span id="LC74" class="line" lang="python"> <span class="n" style="color: #333;">tax</span> <span class="o" style="font-weight: 600;">=</span> <span class="bp" style="color: #999;">self</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">taxonomy</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">to_dict</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;">right</span> <span class="o" style="font-weight: 600;">=</span> <span class="mf" style="color: #099;">0.</span></span>
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<pre style="margin: 0;">+<span id="LC76" class="line" lang="python"> <span class="k" style="font-weight: 600;">for</span> <span class="n" style="color: #333;">taxon</span> <span class="ow" style="font-weight: 600;">in</span> <span class="n" style="color: #333;">res</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;">right</span> <span class="o" style="font-weight: 600;">+=</span> <span class="n" style="color: #333;">tax</span><span class="p">[</span><span class="n" style="color: #333;">taxon</span><span class="p">]</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">startswith</span><span class="p">(</span><span class="n" style="color: #333;">res</span><span class="p">[</span><span class="n" style="color: #333;">taxon</span><span class="p">])</span></span>
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<pre style="margin: 0;">+<span id="LC78" class="line" lang="python"> <span class="bp" style="color: #999;">self</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">assertGreater</span><span class="p">(</span><span class="n" style="color: #333;">right</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;">res</span><span class="p">),</span> <span class="mf" style="color: #099;">0.5</span><span class="p">)</span></span>
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79
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<pre style="margin: 0;">+<span id="LC79" class="line" lang="python"></span>
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<pre style="margin: 0;">+<span id="LC80" class="line" lang="python"></span>
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<pre style="margin: 0;">+<span id="LC81" class="line" lang="python"><span class="k" style="font-weight: 600;">class</span> <span class="nc" style="color: #458; font-weight: 600;">HybridClassiferTests</span><span class="p">(</span><span class="n" style="color: #333;">FeatureClassifierTestPluginBase</span><span class="p">):</span></span>
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<pre style="margin: 0;">+<span id="LC82" class="line" lang="python"> <span class="n" style="color: #333;">package</span> <span class="o" style="font-weight: 600;">=</span> <span class="s" style="color: #d14;">'q2_feature_classifier.tests'</span></span>
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<pre style="margin: 0;">+<span id="LC83" class="line" lang="python"></span>
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<pre style="margin: 0;">+<span id="LC84" class="line" lang="python"> <span class="k" style="font-weight: 600;">def</span> <span class="nf" style="color: #900; font-weight: 600;">setUp</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="LC85" class="line" lang="python"> <span class="nb" style="color: #0086b3;">super</span><span class="p">()</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">setUp</span><span class="p">()</span></span>
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<pre style="margin: 0;">+<span id="LC86" class="line" lang="python"> <span class="n" style="color: #333;">taxonomy</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">Artifact</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">import_data</span><span class="p">(</span></span>
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87
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<pre style="margin: 0;">+<span id="LC87" class="line" lang="python"> <span class="s" style="color: #d14;">'FeatureData[Taxonomy]'</span><span class="p">,</span> <span class="bp" style="color: #999;">self</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">get_data_path</span><span class="p">(</span><span class="s" style="color: #d14;">'taxonomy.tsv'</span><span class="p">))</span></span>
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<pre style="margin: 0;">+<span id="LC88" class="line" lang="python"> <span class="bp" style="color: #999;">self</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">taxonomy</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">taxonomy</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">view</span><span class="p">(</span><span class="n" style="color: #333;">pd</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">Series</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC89" class="line" lang="python"> <span class="bp" style="color: #999;">self</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">taxartifact</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">taxonomy</span></span>
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<pre style="margin: 0;">+<span id="LC90" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># TODO: use `Artifact.import_data` here once we have a transformer</span></span>
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<pre style="margin: 0;">+<span id="LC91" class="line" lang="python"> <span class="c1" style="color: #998; font-style: italic;"># for DNASequencesDirectoryFormat -> DNAFASTAFormat</span></span>
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<pre style="margin: 0;">+<span id="LC92" class="line" lang="python"> <span class="n" style="color: #333;">reads_fp</span> <span class="o" style="font-weight: 600;">=</span> <span class="bp" style="color: #999;">self</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">get_data_path</span><span class="p">(</span><span class="s" style="color: #d14;">'se-dna-sequences.fasta'</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC93" class="line" lang="python"> <span class="n" style="color: #333;">reads</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">DNAFASTAFormat</span><span class="p">(</span><span class="n" style="color: #333;">reads_fp</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="LC94" class="line" lang="python"> <span class="bp" style="color: #999;">self</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">reads</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">Artifact</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">import_data</span><span class="p">(</span><span class="s" style="color: #d14;">'FeatureData[Sequence]'</span><span class="p">,</span> <span class="n" style="color: #333;">reads</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC95" class="line" lang="python"></span>
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<pre style="margin: 0;">+<span id="LC96" class="line" lang="python"> <span class="n" style="color: #333;">fitter</span> <span class="o" style="font-weight: 600;">=</span> <span class="nb" style="color: #0086b3;">getattr</span><span class="p">(</span><span class="n" style="color: #333;">feature_classifier</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">methods</span><span class="p">,</span></span>
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97
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<pre style="margin: 0;">+<span id="LC97" class="line" lang="python"> <span class="s" style="color: #d14;">'fit_classifier_'</span> <span class="o" style="font-weight: 600;">+</span> <span class="n" style="color: #333;">_specific_fitters</span><span class="p">[</span><span class="mi" style="color: #099;">0</span><span class="p">][</span><span class="mi" style="color: #099;">0</span><span class="p">])</span></span>
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98
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<pre style="margin: 0;">+<span id="LC98" class="line" lang="python"> <span class="bp" style="color: #999;">self</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">classifier</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">fitter</span><span class="p">(</span><span class="bp" style="color: #999;">self</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">reads</span><span class="p">,</span> <span class="bp" style="color: #999;">self</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">taxartifact</span><span class="p">)</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">classifier</span></span>
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99
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<pre style="margin: 0;">+<span id="LC99" class="line" lang="python"></span>
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100
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<pre style="margin: 0;">+<span id="LC100" class="line" lang="python"> <span class="bp" style="color: #999;">self</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">query</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">Artifact</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">import_data</span><span class="p">(</span><span class="s" style="color: #d14;">'FeatureData[Sequence]'</span><span class="p">,</span> <span class="n" style="color: #333;">pd</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">Series</span><span class="p">(</span></span>
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101
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<pre style="margin: 0;">+<span id="LC101" class="line" lang="python"> <span class="p">{</span><span class="s" style="color: #d14;">'A'</span><span class="p">:</span> <span class="s" style="color: #d14;">'GCCTAACACATGCAAGTCGAACGGCAGCGGGGGAAAGCTTGCTTTCCTGCCGGCGA'</span><span class="p">,</span></span>
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102
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<pre style="margin: 0;">+<span id="LC102" class="line" lang="python"> <span class="s" style="color: #d14;">'B'</span><span class="p">:</span> <span class="s" style="color: #d14;">'TAACACATGCAAGTCAACGATGCTTATGTAGCAATATGTAAGTAGAGTGGCGCACG'</span><span class="p">,</span></span>
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103
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<pre style="margin: 0;">+<span id="LC103" class="line" lang="python"> <span class="s" style="color: #d14;">'C'</span><span class="p">:</span> <span class="s" style="color: #d14;">'ATACATGCAAGTCGTACGGTATTCCGGTTTCGGCCGGGAGAGAGTGGCGGATGGGT'</span><span class="p">,</span></span>
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104
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<pre style="margin: 0;">+<span id="LC104" class="line" lang="python"> <span class="s" style="color: #d14;">'D'</span><span class="p">:</span> <span class="s" style="color: #d14;">'GACGAACGCTGGCGACGTGCTTAACACATGCAAGTCGTGCGAGGACGGGCGGTGCT'</span></span>
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105
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<pre style="margin: 0;">+<span id="LC105" class="line" lang="python"> <span class="s" style="color: #d14;">'TGCACTGCTCGAGCCGAGCGGCGGACGGGTGAGTAACACGTGAGCAACCTATCTCC'</span></span>
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106
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<pre style="margin: 0;">+<span id="LC106" class="line" lang="python"> <span class="s" style="color: #d14;">'GTGCGGGGGACAACCCGGGGAAACCCGGGCTAATACCG'</span><span class="p">}))</span></span>
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107
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<pre style="margin: 0;">+<span id="LC107" class="line" lang="python"></span>
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108
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<pre style="margin: 0;">+<span id="LC108" class="line" lang="python"> <span class="k" style="font-weight: 600;">def</span> <span class="nf" style="color: #900; font-weight: 600;">test_classify_hybrid_vsearch_sklearn_all_exact_match</span><span class="p">(</span><span class="bp" style="color: #999;">self</span><span class="p">):</span></span>
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109
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<pre style="margin: 0;">+<span id="LC109" class="line" lang="python"></span>
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110
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<pre style="margin: 0;">+<span id="LC110" class="line" lang="python"> <span class="n" style="color: #333;">result</span><span class="p">,</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">feature_classifier</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">actions</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">classify_hybrid_vsearch_sklearn</span><span class="p">(</span></span>
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111
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<pre style="margin: 0;">+<span id="LC111" class="line" lang="python"> <span class="n" style="color: #333;">query</span><span class="o" style="font-weight: 600;">=</span><span class="bp" style="color: #999;">self</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">reads</span><span class="p">,</span> <span class="n" style="color: #333;">reference_reads</span><span class="o" style="font-weight: 600;">=</span><span class="bp" style="color: #999;">self</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">reads</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC112" class="line" lang="python"> <span class="n" style="color: #333;">reference_taxonomy</span><span class="o" style="font-weight: 600;">=</span><span class="bp" style="color: #999;">self</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">taxartifact</span><span class="p">,</span> <span class="n" style="color: #333;">classifier</span><span class="o" style="font-weight: 600;">=</span><span class="bp" style="color: #999;">self</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">classifier</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC113" class="line" lang="python"> <span class="n" style="color: #333;">prefilter</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="LC114" class="line" lang="python"> <span class="n" style="color: #333;">result</span><span class="p">,</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">feature_classifier</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">actions</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">classify_hybrid_vsearch_sklearn</span><span class="p">(</span></span>
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<pre style="margin: 0;">+<span id="LC115" class="line" lang="python"> <span class="n" style="color: #333;">query</span><span class="o" style="font-weight: 600;">=</span><span class="bp" style="color: #999;">self</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">reads</span><span class="p">,</span> <span class="n" style="color: #333;">reference_reads</span><span class="o" style="font-weight: 600;">=</span><span class="bp" style="color: #999;">self</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">reads</span><span class="p">,</span></span>
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116
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<pre style="margin: 0;">+<span id="LC116" class="line" lang="python"> <span class="n" style="color: #333;">reference_taxonomy</span><span class="o" style="font-weight: 600;">=</span><span class="bp" style="color: #999;">self</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">taxartifact</span><span class="p">,</span> <span class="n" style="color: #333;">classifier</span><span class="o" style="font-weight: 600;">=</span><span class="bp" style="color: #999;">self</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">classifier</span><span class="p">)</span></span>
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117
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<pre style="margin: 0;">+<span id="LC117" class="line" lang="python"> <span class="n" style="color: #333;">result</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">result</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">view</span><span class="p">(</span><span class="n" style="color: #333;">pd</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">DataFrame</span><span class="p">)</span></span>
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118
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<pre style="margin: 0;">+<span id="LC118" 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;">result</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">Taxon</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">to_dict</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;">tax</span> <span class="o" style="font-weight: 600;">=</span> <span class="bp" style="color: #999;">self</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">taxonomy</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">to_dict</span><span class="p">()</span></span>
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120
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<pre style="margin: 0;">+<span id="LC120" class="line" lang="python"> <span class="n" style="color: #333;">right</span> <span class="o" style="font-weight: 600;">=</span> <span class="mf" style="color: #099;">0.</span></span>
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121
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<pre style="margin: 0;">+<span id="LC121" class="line" lang="python"> <span class="k" style="font-weight: 600;">for</span> <span class="n" style="color: #333;">taxon</span> <span class="ow" style="font-weight: 600;">in</span> <span class="n" style="color: #333;">res</span><span class="p">:</span></span>
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122
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<pre style="margin: 0;">+<span id="LC122" class="line" lang="python"> <span class="n" style="color: #333;">right</span> <span class="o" style="font-weight: 600;">+=</span> <span class="n" style="color: #333;">tax</span><span class="p">[</span><span class="n" style="color: #333;">taxon</span><span class="p">]</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">startswith</span><span class="p">(</span><span class="n" style="color: #333;">res</span><span class="p">[</span><span class="n" style="color: #333;">taxon</span><span class="p">])</span></span>
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<pre style="margin: 0;">+<span id="LC123" class="line" lang="python"> <span class="bp" style="color: #999;">self</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">assertGreater</span><span class="p">(</span><span class="n" style="color: #333;">right</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;">res</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="LC124" class="line" lang="python"></span>
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125
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<pre style="margin: 0;">+<span id="LC125" class="line" lang="python"> <span class="k" style="font-weight: 600;">def</span> <span class="nf" style="color: #900; font-weight: 600;">test_classify_hybrid_vsearch_sklearn_mixed_query</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="LC126" class="line" lang="python"></span>
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<pre style="margin: 0;">+<span id="LC127" class="line" lang="python"> <span class="n" style="color: #333;">result</span><span class="p">,</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">feature_classifier</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">actions</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">classify_hybrid_vsearch_sklearn</span><span class="p">(</span></span>
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128
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<pre style="margin: 0;">+<span id="LC128" class="line" lang="python"> <span class="n" style="color: #333;">query</span><span class="o" style="font-weight: 600;">=</span><span class="bp" style="color: #999;">self</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">query</span><span class="p">,</span> <span class="n" style="color: #333;">reference_reads</span><span class="o" style="font-weight: 600;">=</span><span class="bp" style="color: #999;">self</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">reads</span><span class="p">,</span></span>
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129
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<pre style="margin: 0;">+<span id="LC129" class="line" lang="python"> <span class="n" style="color: #333;">reference_taxonomy</span><span class="o" style="font-weight: 600;">=</span><span class="bp" style="color: #999;">self</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">taxartifact</span><span class="p">,</span> <span class="n" style="color: #333;">classifier</span><span class="o" style="font-weight: 600;">=</span><span class="bp" style="color: #999;">self</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">classifier</span><span class="p">,</span></span>
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<pre style="margin: 0;">+<span id="LC130" class="line" lang="python"> <span class="n" style="color: #333;">prefilter</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;">read_orientation</span><span class="o" style="font-weight: 600;">=</span><span class="s" style="color: #d14;">'same'</span><span class="p">,</span> <span class="n" style="color: #333;">randseed</span><span class="o" style="font-weight: 600;">=</span><span class="mi" style="color: #099;">1001</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC131" class="line" lang="python"> <span class="n" style="color: #333;">result</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">result</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">view</span><span class="p">(</span><span class="n" style="color: #333;">pd</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">DataFrame</span><span class="p">)</span></span>
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<pre style="margin: 0;">+<span id="LC132" class="line" lang="python"> <span class="n" style="color: #333;">obs</span> <span class="o" style="font-weight: 600;">=</span> <span class="n" style="color: #333;">result</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">Taxon</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">to_dict</span><span class="p">()</span></span>
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133
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<pre style="margin: 0;">+<span id="LC133" class="line" lang="python"> <span class="n" style="color: #333;">exp</span> <span class="o" style="font-weight: 600;">=</span> <span class="p">{</span><span class="s" style="color: #d14;">'A'</span><span class="p">:</span> <span class="s" style="color: #d14;">'k__Bacteria; p__Proteobacteria; c__Gammaproteobacteria; '</span></span>
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134
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<pre style="margin: 0;">+<span id="LC134" class="line" lang="python"> <span class="s" style="color: #d14;">'o__Legionellales; f__; g__; s__'</span><span class="p">,</span></span>
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135
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<pre style="margin: 0;">+<span id="LC135" class="line" lang="python"> <span class="s" style="color: #d14;">'B'</span><span class="p">:</span> <span class="s" style="color: #d14;">'k__Bacteria; p__Chlorobi; c__; o__; f__; g__; s__'</span><span class="p">,</span></span>
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136
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<pre style="margin: 0;">+<span id="LC136" class="line" lang="python"> <span class="s" style="color: #d14;">'C'</span><span class="p">:</span> <span class="s" style="color: #d14;">'k__Bacteria; p__Bacteroidetes; c__Cytophagia; '</span></span>
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137
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<pre style="margin: 0;">+<span id="LC137" class="line" lang="python"> <span class="s" style="color: #d14;">'o__Cytophagales; f__Cyclobacteriaceae; g__; s__'</span><span class="p">,</span></span>
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138
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<pre style="margin: 0;">+<span id="LC138" class="line" lang="python"> <span class="s" style="color: #d14;">'D'</span><span class="p">:</span> <span class="s" style="color: #d14;">'k__Bacteria; p__Gemmatimonadetes; c__Gemm-5; o__; f__; '</span></span>
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139
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<pre style="margin: 0;">+<span id="LC139" class="line" lang="python"> <span class="s" style="color: #d14;">'g__; s__'</span><span class="p">}</span></span>
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<pre style="margin: 0;">+<span id="LC140" class="line" lang="python"> <span class="bp" style="color: #999;">self</span><span class="o" style="font-weight: 600;">.</span><span class="n" style="color: #333;">assertDictEqual</span><span class="p">(</span><span class="n" style="color: #333;">obs</span><span class="p">,</span> <span class="n" style="color: #333;">exp</span><span class="p">)</span></span>
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141
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<pre style="margin: 0;">+<span id="LC141" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC142" class="line" lang="python"></span>
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<pre style="margin: 0;"> <span id="LC143" class="line" lang="python"><span class="k" style="font-weight: 600;">class</span> <span class="nc" style="color: #458; font-weight: 600;">ImportBlastAssignmentTests</span><span class="p">(</span><span class="n" style="color: #333;">FeatureClassifierTestPluginBase</span><span class="p">):</span></span>
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<pre style="margin: 0;"> <span id="LC144" class="line" lang="python"></span>
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<a href="https://salsa.debian.org/med-team/q2-feature-classifier/commit/ce3f2d71dc19f5e2778f83d61d5b0be27a8bee02#d1ace7f5ea694e1686443cb8424bc9921f057f2b"><strong>q2_feature_classifier/tests/test_taxonomic_classifier.py</strong></a>
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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">@@ -14,7 +14,7 @@ import os</td>
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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;">shutil</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;">sklearn</span></span>
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<pre style="margin: 0;">-<span id="LC17" class="line" lang="python"><span class="kn" style="font-weight: 600;"><span class="idiff left">from</span></span><span class="idiff"> </span><span class="nn" style="color: #555;"><span class="idiff">sklearn.externals</span></span><span class="idiff right"> </span><span class="kn" style="font-weight: 600;">import</span> <span class="n" style="color: #333;">joblib</span></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;">joblib</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;">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="LC19" class="line" lang="python"><span class="kn" style="font-weight: 600;">from</span> <span class="nn" style="color: #555;">qiime2.sdk</span> <span class="kn" style="font-weight: 600;">import</span> <span class="n" style="color: #333;">Artifact</span></span>
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<pre style="margin: 0;"> <span id="LC20" class="line" lang="python"><span class="kn" style="font-weight: 600;">from</span> <span class="nn" style="color: #555;">qiime2.plugins.feature_classifier.methods</span> <span class="kn" style="font-weight: 600;">import</span> \</span>
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