annotate 2d_filter_segmentation_by_features.xml @ 3:9d47aabda459 draft default tip

planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/2d_filter_segmentation_by_features/ commit c86a1b93cb7732f7331a981d13465653cc1a2790

<tool id="ip_2d_filter_segmentation_by_features" name="Filter label map by rules" version="0.0.1-4" profile="20.05">
    <description></description>
    <macros>
        <import>creators.xml</import>
        <import>tests.xml</import>
    </macros>
    <creator>
        <expand macro="creators/bmcv" />
    </creator>
    <edam_operations>
        <edam_operation>operation_3443</edam_operation>
    </edam_operations>
    <xrefs>
        <xref type="bio.tools">galaxy_image_analysis</xref>
    </xrefs>
    <requirements>
        <requirement type="package" version="0.18.1">scikit-image</requirement> 
        <requirement type="package" version="2.2.2">pandas</requirement>
        <requirement type="package" version="2020.10.1">tifffile</requirement>
        <requirement type="package" version="0.1">giatools</requirement>
    </requirements>
    <command detect_errors="aggressive"><![CDATA[

        python '$__tool_directory__/2d_filter_segmentation_by_features.py'

        '$input'
        '$output'
        '$feature_file'
        '$rule_file'

    ]]></command>
    <inputs>
        <param name="input" type="data" format="tiff" label="Label map" /> 
        <param name="feature_file" type="data" format="tabular" label="Features" /> 
        <param name="rule_file" type="data" format="tabular" label="Rules" /> 
    </inputs>
    <outputs>
       <data format="tiff" name="output" />
    </outputs>
    <tests>
        <test>
            <param name="input" value="in.tif"/>
            <param name="feature_file" value="features.tabular"/>
            <param name="rule_file" value="rules.tabular"/>
            <expand macro="tests/label_image_diff" name="output" value="out.tif" ftype="tiff"/>
        </test>
    </tests>
    <help>

        **Filters a label map by rules (e.g., remove large or deformed objects).**

        The properties of the labeled image regions (features) must be provided in a specific tabular format
        (columns: ``label``, ``feature1``, ``feature2``, and so on, where ``feature1`` and ``feature2`` can be arbitrary strings).
        Each row corresponds to a labeled image region.
        An example is given below.

        +-------+-------+---------------------+
        | label | area  | eccentricity        |
        +-------+-------+---------------------+
        | 1     | 344   | 0.42521053699241596 |
        +-------+-------+---------------------+
        | 2     | 434   | 0.47679001553231926 |
        +-------+-------+---------------------+
        | 3     | 907   | 0.9973539531125177  |
        +-------+-------+---------------------+
        | 4     | 14320 | 0.17131009631035327 |
        +-------+-------+---------------------+

        The rules also must be supplied in a specific tabular format with three rows.
        The top-left cell is empty, and the rest of the first row corresponds to the feature names (such as ``feature1`` or ``feature2``, see above).
        The rest of the first column corresponds to the two values ``min`` and ``max``.
        Each of the rows defines the minimum and maximum values for the corresponding features.
        A labeled image region is retrained if and only if it passes all checks with repsect to the given ``min`` and ``max`` values.
        An example is given below.

        +-----+--------+--------------+
        |     | area   | eccentricity |
        +-----+--------+--------------+
        | min | 500    | 0.           |
        +-----+--------+--------------+
        | max | 100000 | 0.5          |
        +-----+--------+--------------+

    </help>
    <citations>
        <citation type="doi">10.1016/j.jbiotec.2017.07.019</citation>
    </citations>
</tool>