comparison qiime2__feature_classifier__classify_sklearn.xml @ 3:863bb205e6d1 draft

planemo upload for repository https://github.com/qiime2/galaxy-tools/tree/main/tools/suite_qiime2__feature_classifier commit 389df0134cd0763dcf02aac6e623fc15f8861c1e

2:8aa82af30760

<?xml version='1.0' encoding='utf-8'?>
<!--
Copyright (c) 2023, 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)
for:
    qiime2 (version: 2023.5.1)
-->
<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">
    <description>Pre-fitted sklearn-based taxonomy classifier</description>
    <requirements>
        <container type="docker">quay.io/qiime2/core:2023.5</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"/>
    </configfiles>
    <inputs>
        <param name="reads" type="data" format="qza" label="reads: FeatureData[Sequence]" help="[required]  The feature data to be classified.">
            <options options_filter_attribute="metadata.semantic_type">
                <filter type="add_value" value="FeatureData[Sequence]"/>

                </when>
                <when value="__q2galaxy__::control::Int X Range(1__comma__ None)">
                    <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 &quot;auto&quot;, 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']  &quot;all&quot; or expression, as in &quot;3*n_jobs&quot;. The number of batches (of tasks) to be pre-dispatched.">
                <sanitizer>
                    <valid initial="string.printable"/>
                </sanitizer>
            </param>

3:863bb205e6d1

<?xml version='1.0' encoding='utf-8'?>
<!--
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: 2024.2.1)
for:
    qiime2 (version: 2024.2.0)
-->
<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/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="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.">
            <options options_filter_attribute="metadata.semantic_type">
                <filter type="add_value" value="FeatureData[Sequence]"/>

                </when>
                <when value="__q2galaxy__::control::Int X Range(1__comma__ None)">
                    <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 &quot;auto&quot;, this parameter is autoscaled to min( number of query sequences / n_jobs, 20000)."/>
                </when>
            </conditional>
            <param name="pre_dispatch" type="text" value="2*n_jobs" label="pre_dispatch: Str" help="[default: '2*n_jobs']  &quot;all&quot; or expression, as in &quot;3*n_jobs&quot;. The number of batches (of tasks) to be pre-dispatched.">
                <sanitizer>
                    <valid initial="string.printable"/>
                </sanitizer>
            </param>