# HG changeset patch
# User imgteam
# Date 1549740757 18000
# Node ID 8aa6e767f7375edff1b552229ae9400bab06470c

planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/color-deconvolution/ commit c3f4b766f03770f094fda6bda0a5882c0ebd4581

diff -r 000000000000 -r 8aa6e767f737 color-deconvolution.xml
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/color-deconvolution.xml	Sat Feb 09 14:32:37 2019 -0500
@@ -0,0 +1,92 @@
+<tool id="ip_color_deconvolution" name="Color Deconvolution" version="0.7">
+    <description>Color deconvolution</description>
+    <requirements>
+        <requirement type="package" version="0.14.2">scikit-image</requirement>
+        <requirement type="package" version="4.0.0">pillow</requirement>
+        <requirement type="package" version="0.18.1">scikit-learn</requirement>
+        <requirement type="package" version="1.12">numpy</requirement>
+    </requirements>
+    <command>
+        <![CDATA[
+        python '$__tool_directory__/color_deconvolution.py' '$input' '$output' '$convtype'
+        ]]>
+    </command>
+    <inputs>
+        <param name="input" type="data" format="tiff,png,jpg,bmp" label="Image file with 3 channels"/>
+        <param name="convtype" type="select" label="Transformation type">
+            <option value="ica" selected="True">ica</option>
+            <option value="pca">pca</option>
+            <option value="nmf">nmf</option>
+            <option value="fa">fa</option>
+            <option value="xyz2rgb">xyz2rgb</option>
+            <option value="rgb_from_rbd">rgb_from_rbd</option>
+            <option value="rgb_from_hdx">rgb_from_hdx</option>
+            <option value="rgb2hsv">rgb2hsv</option>
+            <option value="rgb_from_bro">rgb_from_bro</option>
+            <option value="bpx_from_rgb">bpx_from_rgb</option>
+            <option value="hed_from_rgb">hed_from_rgb</option>
+            <option value="rgbcie2rgb">rgbcie2rgb</option>
+            <option value="hdx_from_rgb">hdx_from_rgb</option>
+            <option value="xyz2luv">xyz2luv</option>
+            <option value="rgb2lab">rgb2lab</option>
+            <option value="hpx_from_rgb">hpx_from_rgb</option>
+            <option value="rgb_from_fgx">rgb_from_fgx</option>
+            <option value="rgb_from_gdx">rgb_from_gdx</option>
+            <option value="lab2xyz">lab2xyz</option>
+            <option value="rgb_from_hpx">rgb_from_hpx</option>
+            <option value="lab2rgb">lab2rgb</option>
+            <option value="rgb2rgbcie">rgb2rgbcie</option>
+            <option value="bex_from_rgb">bex_from_rgb</option>
+            <option value="xyz2lab">xyz2lab</option>
+            <option value="rgb_from_bex">rgb_from_bex</option>
+            <option value="fgx_from_rgb">fgx_from_rgb</option>
+            <option value="rbd_from_rgb">rbd_from_rgb</option>
+            <option value="rgb2hed">rgb2hed</option>
+            <option value="hed2rgb">hed2rgb</option>
+            <option value="luv2rgb">luv2rgb</option>
+            <option value="luv2xyz">luv2xyz</option>
+            <option value="lch2lab">lch2lab</option>
+            <option value="rgb2luv">rgb2luv</option>
+            <option value="ahx_from_rgb">ahx_from_rgb</option>
+            <option value="rgb_from_hax">rgb_from_hax</option>
+            <option value="hax_from_rgb">hax_from_rgb</option>
+            <option value="rgb_from_bpx">rgb_from_bpx</option>
+            <option value="rgb2xyz">rgb2xyz</option>
+            <option value="gdx_from_rgb">gdx_from_rgb</option>
+            <option value="rgb_from_ahx">rgb_from_ahx</option>
+            <option value="lab2lch">lab2lch</option>
+            <option value="rgb_from_hed">rgb_from_hed</option>
+            <option value="bro_from_rgb">bro_from_rgb</option>
+            <option value="hsv2rgb">hsv2rgb</option>
+        </param>
+    </inputs>
+    <outputs>
+        <data format="tiff" name="output"/>
+    </outputs>
+    <tests>
+        <test>
+            <param name="input" value="galaxyIcon_noText.png" />
+            <param name="convtype" value="rgb2hsv" />
+            <output name="output" ftype="tiff" />
+        </test>
+    </tests>
+    <help>
+    **What it does**
+
+    This tools performs several color deconvolution techniques.</help>
+    <citations>
+      <citation type="doi">10.7717/peerj.453</citation>
+      <citation type="bibtex">@inproceedings{sklearn_api,
+  author    = {Lars Buitinck and Gilles Louppe and Mathieu Blondel and
+               Fabian Pedregosa and Andreas Mueller and Olivier Grisel and
+               Vlad Niculae and Peter Prettenhofer and Alexandre Gramfort
+               and Jaques Grobler and Robert Layton and Jake VanderPlas and
+               Arnaud Joly and Brian Holt and Ga{\"{e}}l Varoquaux},
+  title     = {{API} design for machine learning software: experiences from the scikit-learn
+               project},
+  booktitle = {ECML PKDD Workshop: Languages for Data Mining and Machine Learning},
+  year      = {2013},
+  pages = {108--122},
+}</citation>
+    </citations>
+</tool>
diff -r 000000000000 -r 8aa6e767f737 color_deconvolution.py
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/color_deconvolution.py	Sat Feb 09 14:32:37 2019 -0500
@@ -0,0 +1,87 @@
+import argparse
+import sys
+import warnings
+import numpy as np
+import skimage.io
+import skimage.color
+import skimage.util
+from sklearn.decomposition import PCA, NMF, FastICA, FactorAnalysis
+
+convOptions = {
+           'hed2rgb' : lambda img_raw: skimage.color.hed2rgb(img_raw),
+           'hsv2rgb' : lambda img_raw: skimage.color.hsv2rgb(img_raw),
+           'lab2lch' : lambda img_raw: skimage.color.lab2lch(img_raw),
+           'lab2rgb' : lambda img_raw: skimage.color.lab2rgb(img_raw),
+           'lab2xyz' : lambda img_raw: skimage.color.lab2xyz(img_raw),
+           'lch2lab' : lambda img_raw: skimage.color.lch2lab(img_raw),
+           'luv2rgb' : lambda img_raw: skimage.color.luv2rgb(img_raw),
+           'luv2xyz' : lambda img_raw: skimage.color.luv2xyz(img_raw),
+           'rgb2hed' : lambda img_raw: skimage.color.rgb2hed(img_raw),
+           'rgb2hsv' : lambda img_raw: skimage.color.rgb2hsv(img_raw),
+           'rgb2lab' : lambda img_raw: skimage.color.rgb2lab(img_raw),
+           'rgb2luv' : lambda img_raw: skimage.color.rgb2luv(img_raw),
+           'rgb2rgbcie' : lambda img_raw: skimage.color.rgb2rgbcie(img_raw),
+           'rgb2xyz' : lambda img_raw: skimage.color.rgb2xyz(img_raw),
+           #'rgb2ycbcr' : lambda img_raw: skimage.color.rgb2ycbcr(img_raw),
+           #'rgb2yiq' : lambda img_raw: skimage.color.rgb2yiq(img_raw),
+           #'rgb2ypbpr' : lambda img_raw: skimage.color.rgb2ypbpr(img_raw),
+           #'rgb2yuv' : lambda img_raw: skimage.color.rgb2yuv(img_raw),
+           #'rgba2rgb' : lambda img_raw: skimage.color.rgba2rgb(img_raw),
+           'rgbcie2rgb' : lambda img_raw: skimage.color.rgbcie2rgb(img_raw),
+           'xyz2lab' : lambda img_raw: skimage.color.xyz2lab(img_raw),
+           'xyz2luv' : lambda img_raw: skimage.color.xyz2luv(img_raw),
+           'xyz2rgb' : lambda img_raw: skimage.color.xyz2rgb(img_raw),
+           #'ycbcr2rgb' : lambda img_raw: skimage.color.ycbcr2rgb(img_raw),
+           #'yiq2rgb' : lambda img_raw: skimage.color.yiq2rgb(img_raw),
+           #'ypbpr2rgb' : lambda img_raw: skimage.color.ypbpr2rgb(img_raw),
+           #'yuv2rgb' : lambda img_raw: skimage.color.yuv2rgb(img_raw),    
+    
+           'rgb_from_hed' : lambda img_raw: skimage.color.combine_stains(img_raw, skimage.color.rgb_from_hed),
+           'rgb_from_hdx' : lambda img_raw: skimage.color.combine_stains(img_raw, skimage.color.rgb_from_hdx),
+           'rgb_from_fgx' : lambda img_raw: skimage.color.combine_stains(img_raw, skimage.color.rgb_from_fgx),
+           'rgb_from_bex' : lambda img_raw: skimage.color.combine_stains(img_raw, skimage.color.rgb_from_bex),
+           'rgb_from_rbd' : lambda img_raw: skimage.color.combine_stains(img_raw, skimage.color.rgb_from_rbd),
+           'rgb_from_gdx' : lambda img_raw: skimage.color.combine_stains(img_raw, skimage.color.rgb_from_gdx),
+           'rgb_from_hax' : lambda img_raw: skimage.color.combine_stains(img_raw, skimage.color.rgb_from_hax),
+           'rgb_from_bro' : lambda img_raw: skimage.color.combine_stains(img_raw, skimage.color.rgb_from_bro),
+           'rgb_from_bpx' : lambda img_raw: skimage.color.combine_stains(img_raw, skimage.color.rgb_from_bpx),
+           'rgb_from_ahx' : lambda img_raw: skimage.color.combine_stains(img_raw, skimage.color.rgb_from_ahx),
+           'rgb_from_hpx' : lambda img_raw: skimage.color.combine_stains(img_raw, skimage.color.rgb_from_hpx),
+    
+           'hed_from_rgb' : lambda img_raw: skimage.color.separate_stains(img_raw, skimage.color.hed_from_rgb),
+           'hdx_from_rgb' : lambda img_raw: skimage.color.separate_stains(img_raw, skimage.color.hdx_from_rgb),
+           'fgx_from_rgb' : lambda img_raw: skimage.color.separate_stains(img_raw, skimage.color.fgx_from_rgb),
+           'bex_from_rgb' : lambda img_raw: skimage.color.separate_stains(img_raw, skimage.color.bex_from_rgb),
+           'rbd_from_rgb' : lambda img_raw: skimage.color.separate_stains(img_raw, skimage.color.rbd_from_rgb),
+           'gdx_from_rgb' : lambda img_raw: skimage.color.separate_stains(img_raw, skimage.color.gdx_from_rgb),
+           'hax_from_rgb' : lambda img_raw: skimage.color.separate_stains(img_raw, skimage.color.hax_from_rgb),
+           'bro_from_rgb' : lambda img_raw: skimage.color.separate_stains(img_raw, skimage.color.bro_from_rgb),
+           'bpx_from_rgb' : lambda img_raw: skimage.color.separate_stains(img_raw, skimage.color.bpx_from_rgb),
+           'ahx_from_rgb' : lambda img_raw: skimage.color.separate_stains(img_raw, skimage.color.ahx_from_rgb),
+           'hpx_from_rgb' : lambda img_raw: skimage.color.separate_stains(img_raw, skimage.color.hpx_from_rgb),    
+    
+           'pca' : lambda img_raw: np.reshape(PCA(n_components=3).fit_transform(np.reshape(img_raw, [-1, img_raw.shape[2]])), 
+                              [img_raw.shape[0],img_raw.shape[1],-1]),    
+           'nmf' : lambda img_raw: np.reshape(NMF(n_components=3, init='nndsvda').fit_transform(np.reshape(img_raw, [-1, img_raw.shape[2]])), 
+                              [img_raw.shape[0],img_raw.shape[1],-1]),
+           'ica' : lambda img_raw: np.reshape(FastICA(n_components=3).fit_transform(np.reshape(img_raw, [-1, img_raw.shape[2]])), 
+                              [img_raw.shape[0],img_raw.shape[1],-1]),
+           'fa' : lambda img_raw: np.reshape(FactorAnalysis(n_components=3).fit_transform(np.reshape(img_raw, [-1, img_raw.shape[2]])), 
+                              [img_raw.shape[0],img_raw.shape[1],-1])
+}
+
+parser = argparse.ArgumentParser()
+parser.add_argument('input_file', type=argparse.FileType('r'), default=sys.stdin, help='input file')
+parser.add_argument('out_file', type=argparse.FileType('w'), default=sys.stdin, help='out file (TIFF)')
+parser.add_argument('conv_type', choices=convOptions.keys(), help='conversion type')
+args = parser.parse_args()
+
+img_in = skimage.io.imread(args.input_file.name)[:,:,0:3]
+res = convOptions[args.conv_type](img_in)
+res[res<-1]=-1
+res[res>1]=1
+
+with warnings.catch_warnings():
+	warnings.simplefilter("ignore")
+	res = skimage.util.img_as_uint(res) #Attention: precision loss
+	skimage.io.imsave(args.out_file.name, res, plugin='tifffile')
diff -r 000000000000 -r 8aa6e767f737 test-data/galaxyIcon_noText.png
Binary file test-data/galaxyIcon_noText.png has changed