<tool id="ip_points_association_nn" name="Association of points" version="0.0.3" profile="20.05"> 
    <description>in consecutive frames (slices) using the nearest neighbor algorithm</description>
    <requirements>
        <requirement type="package" version="1.20.2">numpy</requirement>
        <requirement type="package" version="3.0.7">openpyxl</requirement>
        <requirement type="package" version="1.2.4">pandas</requirement>
        <requirement type="package" version="0.18.1">scikit-image</requirement>
    </requirements>
    <command>
    <![CDATA[
    python '$__tool_directory__/points_association_nn.py'
         '$fn_in'
         ./output.xlsx
         '$nbpx'
         '$thres'
         '$minlen'
    ]]>
    </command>
    <inputs>
        <param name="fn_in" type="data" format="tabular" label="Coordinates (and intensities) of input points (tsv tabular)" />
        <param name="nbpx" type="integer" value="6" optional="true" min="1" max="30" label="Neighborhood size (in pixel) for associating points" />
        <param name="thres" type="float" value="25" optional="true" min="0.0" max="99.9" label="Tracks with all intensities lower than certain percentage (%) of the global maximal intensity will be discarded" />
        <param name="minlen" type="float" value="50" optional="true" min="1.0" max="100.0" label="Minimum length of tracks (% of sequence length)" />
    </inputs>
    <outputs>
        <data format="xlsx" name="fn_out" from_work_dir="output.xlsx" />
    </outputs>
    <tests>
        <test>
            <param name="fn_in" value="spots_detected.tsv"/>
            <param name="nbpx" value="6"/>
            <param name="thres" value="25"/>
            <param name="minlen" value="50"/>
            <output name="fn_out" value="spots_linked.xlsx" ftype="xlsx" compare="sim_size"/>
        </test>
    </tests>
    <help>
    **What it does**

    This tool associates points in consecutive frames (slices) using the nearest neighbor algorithm.
    </help>
    <citations>
        <citation type="doi">10.1097/j.pain.0000000000002642</citation>
    </citations>
</tool>