Mercurial > repos > q2d2 > qiime2__longitudinal__maturity_index

comparison qiime2__longitudinal__maturity_index.xml @ 3:915a49001f9b draft

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planemo upload for repository https://github.com/qiime2/galaxy-tools/tree/main/tools/suite_qiime2__longitudinal commit 389df0134cd0763dcf02aac6e623fc15f8861c1e
author q2d2
date Thu, 25 Apr 2024 21:15:33 +0000
parents 65eb20bd61f1
children ae21a4eac775
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2:65eb20bd61f1 3:915a49001f9b
1 <?xml version='1.0' encoding='utf-8'?> 1 <?xml version='1.0' encoding='utf-8'?>
2 <!-- 2 <!--
3 Copyright (c) 2023, QIIME 2 development team. 3 Copyright (c) 2024, QIIME 2 development team.
4 4
5 Distributed under the terms of the Modified BSD License. (SPDX: BSD-3-Clause) 5 Distributed under the terms of the Modified BSD License. (SPDX: BSD-3-Clause)
6 --> 6 -->
7 <!-- 7 <!--
8 This tool was automatically generated by: 8 This tool was automatically generated by:
9 q2galaxy (version: 2023.5.0) 9 q2galaxy (version: 2024.2.1)
10 for: 10 for:
11 qiime2 (version: 2023.5.1) 11 qiime2 (version: 2024.2.0)
12 --> 12 -->
13 <tool name="qiime2 longitudinal maturity-index" id="qiime2__longitudinal__maturity_index" version="2023.5.0+q2galaxy.2023.5.0.2" profile="22.05" license="BSD-3-Clause"> 13 <tool name="qiime2 longitudinal maturity-index" id="qiime2__longitudinal__maturity_index" version="2024.2.0+q2galaxy.2024.2.1" profile="22.05" license="BSD-3-Clause">
14 <description>Microbial maturity index prediction.</description> 14 <description>Microbial maturity index prediction.</description>
15 <requirements> 15 <requirements>
16 <container type="docker">quay.io/qiime2/core:2023.5</container> 16 <container type="docker">quay.io/qiime2/amplicon:2024.2</container>
17 </requirements> 17 </requirements>
18 <version_command>q2galaxy version longitudinal</version_command> 18 <version_command>q2galaxy version longitudinal</version_command>
19 <command detect_errors="exit_code">q2galaxy run longitudinal maturity_index '$inputs'</command> 19 <command detect_errors="exit_code">q2galaxy run longitudinal maturity_index '$inputs'</command>
20 <configfiles> 20 <configfiles>
21 <inputs name="inputs" data_style="paths"/> 21 <inputs name="inputs" data_style="staging_path_and_source_path"/>
22 </configfiles> 22 </configfiles>
23 <inputs> 23 <inputs>
24 <param name="table" type="data" format="qza" label="table: FeatureTable[Frequency]" help="[required] Feature table containing all features that should be used for target prediction."> 24 <param name="table" type="data" format="qza" label="table: FeatureTable[Frequency]" help="[required] Feature table containing all features that should be used for target prediction.">
25 <options options_filter_attribute="metadata.semantic_type"> 25 <options options_filter_attribute="metadata.semantic_type">
26 <filter type="add_value" value="FeatureTable[Frequency]"/> 26 <filter type="add_value" value="FeatureTable[Frequency]"/>
92 <param name="n_estimators" type="integer" min="1" value="100" label="n_estimators: Int % Range(1, None)" help="[default: 100] Number of trees to grow for estimation. More trees will improve predictive accuracy up to a threshold level, but will also increase time and memory requirements. This parameter only affects ensemble estimators, such as Random Forest, AdaBoost, ExtraTrees, and GradientBoosting."/> 92 <param name="n_estimators" type="integer" min="1" value="100" label="n_estimators: Int % Range(1, None)" help="[default: 100] Number of trees to grow for estimation. More trees will improve predictive accuracy up to a threshold level, but will also increase time and memory requirements. This parameter only affects ensemble estimators, such as Random Forest, AdaBoost, ExtraTrees, and GradientBoosting."/>
93 <param name="test_size" type="float" min="0.0" max="0.999999" value="0.5" label="test_size: Float % Range(0.0, 1.0)" help="[default: 0.5] Fraction of input samples to exclude from training set and use for classifier testing."/> 93 <param name="test_size" type="float" min="0.0" max="0.999999" value="0.5" label="test_size: Float % Range(0.0, 1.0)" help="[default: 0.5] Fraction of input samples to exclude from training set and use for classifier testing."/>
94 <param name="step" type="float" min="1e-06" max="0.999999" value="0.05" label="step: Float % Range(0.0, 1.0, inclusive_start=False)" help="[default: 0.05] If optimize_feature_selection is True, step is the percentage of features to remove at each iteration."/> 94 <param name="step" type="float" min="1e-06" max="0.999999" value="0.05" label="step: Float % Range(0.0, 1.0, inclusive_start=False)" help="[default: 0.05] If optimize_feature_selection is True, step is the percentage of features to remove at each iteration."/>
95 <param name="cv" type="integer" min="1" value="5" label="cv: Int % Range(1, None)" help="[default: 5] Number of k-fold cross-validations to perform."/> 95 <param name="cv" type="integer" min="1" value="5" label="cv: Int % Range(1, None)" help="[default: 5] Number of k-fold cross-validations to perform."/>
96 <param name="random_state" type="integer" optional="true" label="random_state: Int" help="[optional] Seed used by random number generator."/> 96 <param name="random_state" type="integer" optional="true" label="random_state: Int" help="[optional] Seed used by random number generator."/>
97 <param name="n_jobs" type="integer" value="1" label="n_jobs: Int" help="[default: 1] Number of jobs to run in parallel."/>
98 <param name="parameter_tuning" type="boolean" truevalue="__q2galaxy__::literal::True" falsevalue="__q2galaxy__::literal::False" label="parameter_tuning: Bool" help="[default: No] Automatically tune hyperparameters using random grid search."/> 97 <param name="parameter_tuning" type="boolean" truevalue="__q2galaxy__::literal::True" falsevalue="__q2galaxy__::literal::False" label="parameter_tuning: Bool" help="[default: No] Automatically tune hyperparameters using random grid search."/>
99 <param name="optimize_feature_selection" type="boolean" truevalue="__q2galaxy__::literal::True" falsevalue="__q2galaxy__::literal::False" label="optimize_feature_selection: Bool" help="[default: No] Automatically optimize input feature selection using recursive feature elimination."/> 98 <param name="optimize_feature_selection" type="boolean" truevalue="__q2galaxy__::literal::True" falsevalue="__q2galaxy__::literal::False" label="optimize_feature_selection: Bool" help="[default: No] Automatically optimize input feature selection using recursive feature elimination."/>
100 <param name="stratify" type="boolean" truevalue="__q2galaxy__::literal::True" falsevalue="__q2galaxy__::literal::False" label="stratify: Bool" help="[default: No] Evenly stratify training and test data among metadata categories. If True, all values in column must match at least two samples."/> 99 <param name="stratify" type="boolean" truevalue="__q2galaxy__::literal::True" falsevalue="__q2galaxy__::literal::False" label="stratify: Bool" help="[default: No] Evenly stratify training and test data among metadata categories. If True, all values in column must match at least two samples."/>
101 <param name="missing_samples" type="select" label="missing_samples: Str % Choices('error', 'ignore')" display="radio"> 100 <param name="missing_samples" type="select" label="missing_samples: Str % Choices('error', 'ignore')" display="radio">
102 <option value="error" selected="true">error</option> 101 <option value="error" selected="true">error</option>