diff imagej2_noise_jython_script.py @ 0:ab54024c0a88 draft

"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/image_processing/imagej2 commit b08f0e6d1546caaf627b21f8c94044285d5d5b9c-dirty"

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/imagej2_noise_jython_script.py	Tue Sep 17 17:02:18 2019 -0400
@@ -0,0 +1,84 @@
+import sys
+from ij import IJ
+from ij import ImagePlus
+import jython_utils
+
+# Fiji Jython interpreter implements Python 2.5 which does not
+# provide support for argparse.
+error_log = sys.argv[ -19 ]
+input = sys.argv[ -18 ]
+image_datatype = sys.argv[ -17 ]
+noise = sys.argv[ -16 ]
+standard_deviation = sys.argv[ -15 ]
+radius = sys.argv[ -14 ]
+threshold = sys.argv[ -13 ]
+which_outliers = sys.argv[ -12 ]
+randomj = sys.argv[ -11 ]
+trials = sys.argv[ -10 ]
+probability = sys.argv[ -9 ]
+# Note the spelling - so things don't get confused due to Python lambda function.
+lammbda = sys.argv[ -8 ]
+order = sys.argv[ -7 ]
+mean = sys.argv[ -6 ]
+sigma = sys.argv[ -5 ]
+min = sys.argv[ -4 ]
+max = sys.argv[ -3 ]
+insertion = sys.argv[ -2 ]
+tmp_output_path = sys.argv[ -1 ]
+
+error = False
+
+# Open the input image file.
+image_plus = IJ.openImage( input )
+bit_depth = image_plus.getBitDepth()
+image_type = image_plus.getType()
+# Create an ImagePlus object for the image.
+image_plus_copy = image_plus.duplicate()
+# Make a copy of the image.
+image_processor_copy = image_plus_copy.getProcessor()
+
+# Perform the analysis on the ImagePlus object.
+if noise == 'add_noise':
+    IJ.run( image_plus_copy, "Add Noise", "" )
+elif noise == 'add_specified_noise':
+    IJ.run( image_plus_copy, "Add Specified Noise", "standard=&standard_deviation" )
+elif noise == 'salt_and_pepper':
+    IJ.run( image_plus_copy, "Salt and Pepper", "" )
+elif noise == 'despeckle':
+    IJ.run( image_plus_copy, "Despeckle", "" )
+elif noise == 'remove_outliers':
+    IJ.run( image_plus_copy, "Remove Outliers", "radius=&radius threshold=&threshold which=&which_outliers" )
+elif noise == 'remove_nans':
+    if bit_depth == 32:
+        IJ.run( image_plus_copy, "Remove NaNs", "" )
+    else:
+        # When Galaxy metadata for images is enhanced to include information like this,
+        # we'll be able to write tool validators rather than having to stop the job in
+        # an error state.
+        msg = "Remove NaNs requires a 32-bit image, the selected image is %d-bit" % bit_depth
+        jython_utils.handle_error( error_log, msg )
+        error = True
+elif noise == 'rof_denoise':
+    if image_type == ImagePlus.GRAY32:
+        IJ.run( image_plus_copy, "ROF Denoise", "" )
+    else:
+        msg = "ROF Denoise requires an image of type 32-bit grayscale, the selected image is %d-bit" % ( bit_depth )
+        jython_utils.handle_error( error_log, msg )
+        error = True
+elif noise == 'randomj':
+    if randomj == 'randomj_binomial':
+        IJ.run( image_plus_copy, "RandomJ Binomial", "trials=&trials probability=&probability insertion=&insertion" )
+    elif randomj == 'randomj_exponential':
+        IJ.run( image_plus_copy, "RandomJ Exponential", "lambda=&lammbda insertion=&insertion" )
+    elif randomj == 'randomj_gamma':
+        IJ.run( image_plus_copy, "RandomJ Gamma", "order=&order insertion=&insertion" )
+    elif randomj == 'randomj_gaussian':
+        IJ.run( image_plus_copy, "RandomJ Gaussian", "mean=&mean sigma=&sigma insertion=&insertion" )
+    elif randomj == 'randomj_poisson':
+        IJ.run( image_plus_copy, "RandomJ Poisson", "mean=&mean insertion=&insertion" )
+    elif randomj == 'randomj_uniform':
+        IJ.run( image_plus_copy, "RandomJ Uniform", "min=&min max=&max insertion=&insertion" )
+
+if not error:
+    # Save the ImagePlus object as a new image.
+    IJ.saveAs( image_plus_copy, image_datatype, tmp_output_path )