Add voronoi_tessellation tool (#108)

Squashed commit of the following:

commit 3cf5e31
Author: Leonid Kostrykin <[email protected]>
Date:   Sat Mar 9 19:04:19 2024 +0100

    Fix test results

commit c7c193a
Author: Leonid Kostrykin <[email protected]>
Date:   Sat Mar 9 18:29:04 2024 +0100

    Fix bugs

commit e67e183
Author: Leonid Kostrykin <[email protected]>
Date:   Sat Mar 9 17:19:02 2024 +0000

    Fix bug

commit 91c0f8b
Author: Leonid Kostrykin <[email protected]>
Date:   Sat Mar 9 17:15:47 2024 +0000

    Fix citation

commit 6d96123
Author: Leonid Kostrykin <[email protected]>
Date:   Sat Mar 9 17:05:34 2024 +0000

    Add tests

commit c2531b3
Author: Leonid Kostrykin <[email protected]>
Date:   Sat Mar 9 17:54:11 2024 +0100

    Fix XML

commit a0a9b16
Author: Leonid Kostrykin <[email protected]>
Date:   Sat Mar 9 16:20:50 2024 +0000

    Implement `voronoi_tessellation` tool

commit 05b5849
Author: Leonid Kostrykin <[email protected]>
Date:   Sat Mar 9 16:02:43 2024 +0000

    Add `voronoi_tesselation` tool

tools/voronoi_tessellation/.shed.yml

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+categories:
+  - Imaging
+description: Compute Voronoi tesselation
+long_description: Compute Voronoi tesselation for labeled images.
+name: voronoi_tesselation 
+owner: imgteam
+homepage_url: https://github.com/bmcv
+remote_repository_url: https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/voronoi_tesselation

tools/voronoi_tessellation/voronoi_tessellation.py

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+import argparse
+
+import numpy as np
+import scipy.ndimage as ndi
+import skimage.io
+from skimage.segmentation import watershed
+
+
+if __name__ == '__main__':
+
+    parser = argparse.ArgumentParser()
+    parser.add_argument('input')
+    parser.add_argument('output')
+    args = parser.parse_args()
+
+    im = skimage.io.imread(args.input)
+    im = im.squeeze()
+    assert im.ndim == 2
+
+    distances = np.full(im.shape, np.inf)
+    for label in np.unique(im):
+        if label == 0:
+            continue
+
+        label_distances = ndi.distance_transform_edt(im != label)
+        distances = np.min((distances, label_distances), axis=0)
+
+    result = watershed(
+        image=distances,
+        markers=im,
+    )
+
+    skimage.io.imsave(args.output, result)

tools/voronoi_tessellation/voronoi_tessellation.xml

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+<tool id="voronoi_tessellation" name="Compute Voronoi tessellation" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="23.0">
+    <description>with scikit-image</description>
+    <macros>
+        <token name="@TOOL_VERSION@">0.22.0</token>
+        <token name="@VERSION_SUFFIX@">0</token>
+    </macros>
+    <edam_operations>
+        <edam_operation>operation_3443</edam_operation>
+    </edam_operations>
+    <xrefs>
+        <xref type="bio.tools">scikit-image</xref>
+        <xref type="biii">scikit-image</xref>
+    </xrefs>
+    <requirements>
+        <requirement type="package" version="1.26.4">numpy</requirement>
+        <requirement type="package" version="1.12.0">scipy</requirement>
+        <requirement type="package" version="0.22.0">scikit-image</requirement>
+    </requirements>
+    <command><![CDATA[
+    
+    ## Inputs
+    
+    python '$__tool_directory__/voronoi_tessellation.py' '$input'
+    
+    ## Outputs
+    
+    ./result.tiff
+    
+    ]]>
+    </command>
+    <inputs>
+        <param name="input" type="data" format="png,tiff" label="Labeled image" />
+    </inputs>
+    <outputs>
+       <data format="tiff" name="result" from_work_dir="result.tiff" />
+    </outputs>
+    <tests>
+        <test>
+            <param name="input" value="input1.tiff" />
+            <output name="result" value="input1_result.tiff" ftype="tiff" compare="sim_size" delta="0" />
+        </test>
+    </tests>
+    <help>
+
+        This tool computes Voronoi tessellations for labeled images.
+        Voronoi tessellations are also known as Vornoi diagrams, or Dirichlet tessellations.
+        Zero labels are treated as image background.
+
+    </help>
+    <citations>
+        <citation type="doi">10.7717/peerj.453</citation>
+    </citations>
+</tool>