Mercurial > repos > q2d2 > qiime2__feature_classifier__classify_sklearn
changeset 3:863bb205e6d1 draft default tip
planemo upload for repository https://github.com/qiime2/galaxy-tools/tree/main/tools/suite_qiime2__feature_classifier commit 389df0134cd0763dcf02aac6e623fc15f8861c1e
| author | q2d2 |
|---|---|
| date | Thu, 25 Apr 2024 21:06:11 +0000 |
| parents | 8aa82af30760 |
| children | |
| files | qiime2__feature_classifier__classify_sklearn.xml |
| diffstat | 1 files changed, 6 insertions(+), 7 deletions(-) [+] |
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--- a/qiime2__feature_classifier__classify_sklearn.xml Thu Jun 08 19:43:29 2023 +0000 +++ b/qiime2__feature_classifier__classify_sklearn.xml Thu Apr 25 21:06:11 2024 +0000 @@ -1,24 +1,24 @@ <?xml version='1.0' encoding='utf-8'?> <!-- -Copyright (c) 2023, QIIME 2 development team. +Copyright (c) 2024, 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: 2023.5.0) + q2galaxy (version: 2024.2.1) for: - qiime2 (version: 2023.5.1) + qiime2 (version: 2024.2.0) --> -<tool name="qiime2 feature-classifier classify-sklearn" id="qiime2__feature_classifier__classify_sklearn" version="2023.5.0+q2galaxy.2023.5.0.2" profile="22.05" license="BSD-3-Clause"> +<tool name="qiime2 feature-classifier classify-sklearn" id="qiime2__feature_classifier__classify_sklearn" version="2024.2.0+q2galaxy.2024.2.1" profile="22.05" license="BSD-3-Clause"> <description>Pre-fitted sklearn-based taxonomy classifier</description> <requirements> - <container type="docker">quay.io/qiime2/core:2023.5</container> + <container type="docker">quay.io/qiime2/amplicon:2024.2</container> </requirements> <version_command>q2galaxy version feature_classifier</version_command> <command detect_errors="exit_code">q2galaxy run feature_classifier classify_sklearn '$inputs'</command> <configfiles> - <inputs name="inputs" data_style="paths"/> + <inputs name="inputs" data_style="staging_path_and_source_path"/> </configfiles> <inputs> <param name="reads" type="data" format="qza" label="reads: FeatureData[Sequence]" help="[required] The feature data to be classified."> @@ -46,7 +46,6 @@ <param name="reads_per_batch" type="integer" min="1" value="" label="reads_per_batch: Int % Range(1, None)" help="[required] Number of reads to process in each batch. If "auto", this parameter is autoscaled to min( number of query sequences / n_jobs, 20000)."/> </when> </conditional> - <param name="n_jobs" type="integer" value="1" label="n_jobs: Int" help="[default: 1] The maximum number of concurrently worker processes. If -1 all CPUs are used. If 1 is given, no parallel computing code is used at all, which is useful for debugging. For n_jobs below -1, (n_cpus + 1 + n_jobs) are used. Thus for n_jobs = -2, all CPUs but one are used."/> <param name="pre_dispatch" type="text" value="2*n_jobs" label="pre_dispatch: Str" help="[default: '2*n_jobs'] "all" or expression, as in "3*n_jobs". The number of batches (of tasks) to be pre-dispatched."> <sanitizer> <valid initial="string.printable"/>