Repository 'qiime2__sample_classifier__classify_samples'
hg clone https://toolshed.g2.bx.psu.edu/repos/q2d2/qiime2__sample_classifier__classify_samples

Changeset 4:84156d6e1291 (2024-06-03)
Previous changeset 3:096916b40a5a (2024-04-25) Next changeset 5:6c18cbbf0f5b (2024-10-30)
Commit message:
planemo upload for repository https://github.com/qiime2/galaxy-tools/tree/main/tools/suite_qiime2__sample_classifier commit c7e80dcda727ce63b42aa8a946e9330310929797
modified:
qiime2__sample_classifier__classify_samples.xml
b
diff -r 096916b40a5a -r 84156d6e1291 qiime2__sample_classifier__classify_samples.xml
--- a/qiime2__sample_classifier__classify_samples.xml Thu Apr 25 21:26:22 2024 +0000
+++ b/qiime2__sample_classifier__classify_samples.xml Mon Jun 03 23:32:06 2024 +0000
[
@@ -6,14 +6,14 @@
 -->
 <!--
 This tool was automatically generated by:
-    q2galaxy (version: 2024.2.1)
+    q2galaxy (version: 2024.5.0)
 for:
-    qiime2 (version: 2024.2.0)
+    qiime2 (version: 2024.5.0)
 -->
-<tool name="qiime2 sample-classifier classify-samples" id="qiime2__sample_classifier__classify_samples" version="2024.2.0+q2galaxy.2024.2.1" profile="22.05" license="BSD-3-Clause">
+<tool name="qiime2 sample-classifier classify-samples" id="qiime2__sample_classifier__classify_samples" version="2024.5.0+q2galaxy.2024.5.0" profile="22.05" license="BSD-3-Clause">
     <description>Train and test a cross-validated supervised learning classifier.</description>
     <requirements>
-        <container type="docker">quay.io/qiime2/amplicon:2024.2</container>
+        <container type="docker">quay.io/qiime2/amplicon:2024.5</container>
     </requirements>
     <version_command>q2galaxy version sample_classifier</version_command>
     <command detect_errors="exit_code">q2galaxy run sample_classifier classify_samples '$inputs'</command>
@@ -23,10 +23,10 @@
     <inputs>
         <param name="table" type="data" format="qza" label="table: FeatureTable[Frequency | RelativeFrequency | PresenceAbsence | Composition]" help="[required]  Feature table containing all features that should be used for target prediction.">
             <options options_filter_attribute="metadata.semantic_type">
+                <filter type="add_value" value="FeatureTable[Frequency]"/>
+                <filter type="add_value" value="FeatureTable[PresenceAbsence]"/>
+                <filter type="add_value" value="FeatureTable[RelativeFrequency]"/>
                 <filter type="add_value" value="FeatureTable[Composition]"/>
-                <filter type="add_value" value="FeatureTable[Frequency]"/>
-                <filter type="add_value" value="FeatureTable[RelativeFrequency]"/>
-                <filter type="add_value" value="FeatureTable[PresenceAbsence]"/>
             </options>
             <validator type="expression" message="Incompatible type">hasattr(value.metadata, "semantic_type") and value.metadata.semantic_type in ['FeatureTable[Composition]', 'FeatureTable[Frequency]', 'FeatureTable[PresenceAbsence]', 'FeatureTable[RelativeFrequency]']</validator>
         </param>