annotate qiime2__sample_classifier__scatterplot.xml @ 4:fcd6d3d308b7 draft

planemo upload for repository https://github.com/qiime2/galaxy-tools/tree/main/tools/suite_qiime2__sample_classifier commit c7e80dcda727ce63b42aa8a946e9330310929797

<?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: 2024.5.0)
for:
    qiime2 (version: 2024.5.0)
-->
<tool name="qiime2 sample-classifier scatterplot" id="qiime2__sample_classifier__scatterplot" version="2024.5.0+q2galaxy.2024.5.0" profile="22.05" license="BSD-3-Clause">
    <description>Make 2D scatterplot and linear regression of regressor predictions.</description>
    <requirements>
        <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 scatterplot '$inputs'</command>
    <configfiles>
        <inputs name="inputs" data_style="staging_path_and_source_path"/>
    </configfiles>
    <inputs>
        <param name="predictions" type="data" format="qza" label="predictions: SampleData[RegressorPredictions]" help="[required]  Predicted values to plot on y axis. Must be predictions of numeric data produced by a sample regressor.">
            <options options_filter_attribute="metadata.semantic_type">
                <filter type="add_value" value="SampleData[RegressorPredictions]"/>
            </options>
            <validator type="expression" message="Incompatible type">hasattr(value.metadata, "semantic_type") and value.metadata.semantic_type in ['SampleData[RegressorPredictions]']</validator>
        </param>
        <conditional name="truth">
            <param name="type" type="select" label="truth: MetadataColumn[Numeric]" help="[required]  Metadata column (true values) to plot on x axis.">
                <option value="tsv" selected="true">Metadata from TSV</option>
                <option value="qza">Metadata from Artifact</option>
            </param>
            <when value="tsv">
                <param name="source" type="data" format="tabular,qiime2.tabular" label="Metadata Source"/>
                <param name="column" type="data_column" label="Column Name" data_ref="source" use_header_names="true">
                    <validator type="expression" message="The first column cannot be selected (they are IDs).">value != "1"</validator>
                </param>
            </when>
            <when value="qza">
                <param name="source" type="data" format="qza" label="Metadata Source"/>
                <param name="column" type="text" label="Column Name">
                    <validator type="empty_field"/>
                </param>
            </when>
        </conditional>
        <section name="__q2galaxy__GUI__section__extra_opts__" title="Click here for additional options">
            <param name="missing_samples" type="select" label="missing_samples: Str % Choices('error', 'ignore')" display="radio">
                <option value="error" selected="true">error</option>
                <option value="ignore">ignore</option>
            </param>
        </section>
    </inputs>
    <outputs>
        <data name="visualization" format="qzv" label="${tool.name} on ${on_string}: visualization.qzv" from_work_dir="visualization.qzv"/>
    </outputs>
    <tests/>
    <help>
QIIME 2: sample-classifier scatterplot
======================================
Make 2D scatterplot and linear regression of regressor predictions.


Outputs:
--------
:visualization.qzv: &lt;no description&gt;

|  

Description:
------------
Make a 2D scatterplot and linear regression of predicted vs. true values for a set of samples predicted using a sample regressor.


|  

</help>
    <citations>
        <citation type="doi">10.21105/joss.00934</citation>
        <citation type="bibtex">@article{cite2,
 author = {Pedregosa, Fabian and Varoquaux, Gaël and Gramfort, Alexandre and Michel, Vincent and Thirion, Bertrand and Grisel, Olivier and Blondel, Mathieu and Prettenhofer, Peter and Weiss, Ron and Dubourg, Vincent and Vanderplas, Jake and Passos, Alexandre and Cournapeau, David and Brucher, Matthieu and Perrot, Matthieu and Duchesnay, Édouard},
 journal = {Journal of machine learning research},
 number = {Oct},
 pages = {2825--2830},
 title = {Scikit-learn: Machine learning in Python},
 volume = {12},
 year = {2011}
}
</citation>
        <citation type="doi">10.1038/s41587-019-0209-9</citation>
    </citations>
</tool>