Mercurial > repos > imgteam > imagej2_bunwarpj_elastic_transform
diff imagej2_noise_jython_script.py @ 0:301f24849032 draft
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/image_processing/imagej2 commit b08f0e6d1546caaf627b21f8c94044285d5d5b9c-dirty"
author | imgteam |
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date | Tue, 17 Sep 2019 17:10:48 -0400 |
parents | |
children | 39b2bc251b2f |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/imagej2_noise_jython_script.py Tue Sep 17 17:10:48 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 )