| Previous changeset 5:a400ec06bae3 (2024-10-30) |
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Commit message:
planemo upload for repository https://github.com/qiime2/galaxy-tools/tree/main/tools/suite_qiime2__sample_classifier commit b1fccfb38b4873cd4699743033449014a2978e7d |
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modified:
qiime2__sample_classifier__regress_samples.xml |
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| diff -r a400ec06bae3 -r 028961beb681 qiime2__sample_classifier__regress_samples.xml --- a/qiime2__sample_classifier__regress_samples.xml Wed Oct 30 19:56:06 2024 +0000 +++ b/qiime2__sample_classifier__regress_samples.xml Mon May 05 19:03:25 2025 +0000 |
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| @@ -1,22 +1,22 @@ <?xml version='1.0' encoding='utf-8'?> <!-- -Copyright (c) 2024, QIIME 2 development team. +Copyright (c) 2025, QIIME 2 development team. Distributed under the terms of the Modified BSD License. (SPDX: BSD-3-Clause) --> <!-- This tool was automatically generated by: - q2galaxy (version: 2024.10.0) + q2galaxy (version: 2025.4.0) for: - qiime2 (version: 2024.10.1) + qiime2 (version: 2025.4.0) --> -<tool name="qiime2 sample-classifier regress-samples" id="qiime2__sample_classifier__regress_samples" version="2024.10.0+q2galaxy.2024.10.0" profile="22.05" license="BSD-3-Clause"> +<tool name="qiime2 sample-classifier regress-samples" id="qiime2__sample_classifier__regress_samples" version="2025.4.0+q2galaxy.2025.4.0" profile="22.05" license="BSD-3-Clause"> <description>Train and test a cross-validated supervised learning regressor.</description> <xrefs> <xref type="bio.tools">qiime2</xref> </xrefs> <requirements> - <container type="docker">quay.io/qiime2/amplicon:2024.10</container> + <container type="docker">quay.io/qiime2/amplicon:2025.4</container> </requirements> <version_command>q2galaxy version sample_classifier</version_command> <command detect_errors="exit_code">q2galaxy run sample_classifier regress_samples '$inputs'</command> @@ -26,10 +26,10 @@ <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[Composition]"/> <filter type="add_value" value="FeatureTable[RelativeFrequency]"/> <filter type="add_value" value="FeatureTable[Frequency]"/> <filter type="add_value" value="FeatureTable[PresenceAbsence]"/> - <filter type="add_value" value="FeatureTable[Composition]"/> </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> |