comparison auto_threshold.xml @ 3:0c777d708acc draft

"planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/2d_auto_threshold/ commit b1b3c63ab021aa77875c3b04127f6836024812f9"

2:81f0cbca04a7

<tool id="ip_threshold" name="Auto Threshold" version="0.0.4">
   <description>applies a standard threshold algorithm to an image</description>
   <requirements> 
        <requirement type="package" version="0.14.2">scikit-image</requirement>
        <requirement type="package" version="1.15.4">numpy</requirement>
        <requirement type="package" version="5.3.0">pillow</requirement>
        <requirement type="package" version="0.15.1">tifffile</requirement>
   </requirements>
   <command detect_errors="aggressive">
   <![CDATA[
   python '$__tool_directory__/auto_threshold.py' '$input' '$output' $thresh_type $dark_background
   ]]>
   </command>
   <inputs>
        <param name="input" type="data" format="tiff" label="Source file" />
        <param name="thresh_type" type="select" label="Threshold Algorithm">
          <option value="otsu" selected="True">Otsu</option>
          <option value="li">Li’s Minimum Cross Entropy</option>
          <option value="isodata">Isodata</option>
          <option value="gaussian_adaptive">Adaptive (Gauss)</option>
          <option value="mean_adaptive">Adaptive (Mean)</option>
          <option value="yen">Yen</option>
        </param>
        <param name="dark_background" type="boolean" checked="true" truevalue="True" falsevalue="False" label="Dark Background" />
    </inputs>
    <outputs>
       <data format="tiff" name="output" />
    </outputs>
    <tests>
        <test>
            <param name="input" value="sample.tif"/>
            <output name="output" value="out.tif" ftype="tiff" compare="sim_size"/>
            <param name="thresh_type" value="gaussian_adaptive"/>
            <param name="dark_backgroud" value="True"/>
        </test>
        <test>
            <param name="input" value="sample.tif"/>
            <output name="output" value="out2.tif" ftype="tiff" compare="sim_size"/>
            <param name="thresh_type" value="otsu"/>
            <param name="dark_backgroud" value="True"/>
        </test>
    </tests>
    <help>
        Applies a standard threshold algorithm to an image.
    </help>
    <citations>
        <citation type="doi">10.1016/j.jbiotec.2017.07.019</citation>
    </citations>
</tool>

3:0c777d708acc

<tool id="ip_threshold" name="Auto Threshold" version="0.0.5" profile="20.05">
   <description>applies a standard thresholding algorithm to an image</description>
   <requirements> 
        <requirement type="package" version="0.18.1">scikit-image</requirement>
        <requirement type="package" version="2020.10.1">tifffile</requirement>
   </requirements>
   <command detect_errors="aggressive">
   <![CDATA[
   python '$__tool_directory__/auto_threshold.py'
   '$input'
   ./out.tif
   '$th_method'
   '$block_size'
   '$dark_bg'
   ]]>
   </command>
   <inputs>
        <param name="input" type="data" format="tiff,png" label="Input image" />
        <param name="th_method" type="select" label="Thresholding method">
          <option value="otsu" selected="True">Otsu</option>
          <option value="li">Li's Minimum Cross Entropy</option>
          <option value="isodata">Isodata</option>
          <option value="yen">Yen</option>
          <option value="loc_gaussian">Adaptive (Gaussian)</option>
          <option value="loc_median">Adaptive (Median)</option>
          <option value="loc_mean">Adaptive (Mean)</option>
        </param>
        <param name="block_size" type="integer" value="5" label="Odd size of pixel neighborhood for determining the threshold (only valid for adaptive thresholding methods)" />
        <param name="dark_bg" type="boolean" checked="true" truevalue="True" falsevalue="False" label="Dark Background" />
    </inputs>
    <outputs>
       <data format="tiff" name="output" from_work_dir="out.tif" />
    </outputs>
    <tests>
        <test>
            <param name="input" value="sample.tif"/>
            <output name="output" value="out.tif" ftype="tiff" compare="sim_size"/>
            <param name="th_method" value="loc_gaussian"/>
            <param name="block_size" value="3"/>
            <param name="dark_bg" value="True"/>
        </test>
        <test>
            <param name="input" value="sample.tif"/>
            <output name="output" value="out2.tif" ftype="tiff" compare="sim_size"/>
            <param name="th_method" value="otsu"/>
            <param name="block_size" value="5"/>
            <param name="dark_bg" value="True"/>
        </test>
    </tests>
    <help>
        Applies a standard thresholding algorithm to an image.
    </help>
    <citations>
        <citation type="doi">10.1016/j.jbiotec.2017.07.019</citation>
    </citations>
</tool>