diff --git a/myosoft-imcf_fibertyping.py b/myosoft-imcf_fibertyping.py
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+# this is a python rewrite of the original ijm published at
+# https://github.com/Hyojung-Choo/Myosoft/blob/Myosoft-hub/Scripts/central%20nuclei%20counter.ijm
+
+# IJ imports
+# TODO: are the imports RoiManager and ResultsTable needed when using the services?
+from ij import IJ, WindowManager as wm
+from ij.plugin import Duplicator, RoiEnlarger, RoiScaler
+from trainableSegmentation import WekaSegmentation
+from de.biovoxxel.toolbox import Extended_Particle_Analyzer
+
+# Bio-formats imports
+from loci.plugins import BF
+from loci.plugins.in import ImporterOptions
+
+# python imports
+import time
+import os
+
+#@ String (visibility=MESSAGE, value="<html><b> Welcome to Myosoft! </b></html>") msg1
+#@ File (label="Select fiber-ROIs zip-file", style="file") roi_zip
+#@ File (label="Select image file", description="select your image") path_to_image
+#@ Boolean (label="close image after processing", description="tick this box when using batch mode", value=False) close_raw
+#@ String (visibility=MESSAGE, value="<html><b> channel positions in the hyperstack </b></html>") msg5
+#@ Integer (label="Fiber staining 1 channel number (0=n.a.)", style="slider", min=0, max=5, value=1) fiber_channel_1
+#@ Integer (label="Fiber staining 2 channel number (0=n.a.)", style="slider", min=0, max=5, value=2) fiber_channel_2
+#@ Integer (label="Fiber staining 3 channel number (0=n.a.)", style="slider", min=0, max=5, value=3) fiber_channel_3
+#@ Integer (label="minimum fiber intensity (0=auto)", description="0 = automatic threshold detection", value=0) min_fiber_intensity_1
+#@ Integer (label="minimum fiber intensity (0=auto)", description="0 = automatic threshold detection", value=0) min_fiber_intensity_2
+#@ Integer (label="minimum fiber intensity (0=auto)", description="0 = automatic threshold detection", value=0) min_fiber_intensity_3
+#@ ResultsTable rt
+#@ RoiManager rm
+
+
+def fix_ij_options():
+ """put IJ into a defined state
+ """
+ # disable inverting LUT
+ IJ.run("Appearance...", " menu=0 16-bit=Automatic")
+ # set foreground color to be white, background black
+ IJ.run("Colors...", "foreground=white background=black selection=red")
+ # black BG for binary images and pad edges when eroding
+ IJ.run("Options...", "black pad")
+ # set saving format to .txt files
+ IJ.run("Input/Output...", "file=.txt save_column save_row")
+ # ============= DON’T MOVE UPWARDS =============
+ # set "Black Background" in "Binary Options"
+ IJ.run("Options...", "black")
+ # scale when converting = checked
+ IJ.run("Conversions...", "scale")
+
+
+def fix_ij_dirs(path):
+ """use forward slashes in directory paths
+
+ Parameters
+ ----------
+ path : string
+ a directory path obtained from dialogue or script parameter
+
+ Returns
+ -------
+ string
+ a more robust path with forward slashes as separators
+ """
+
+ fixed_path = str(path).replace("\\", "/")
+ fixed_path = fixed_path + "/"
+
+ return fixed_path
+
+
+def open_image_with_BF(path_to_file):
+ """ use Bio-Formats to opens the first image from an image file path
+
+ Parameters
+ ----------
+ path_to_file : string
+ path to the image file
+
+ Returns
+ -------
+ ImagePlus
+ the first imp stored in a give file
+ """
+ options = ImporterOptions()
+ options.setColorMode(ImporterOptions.COLOR_MODE_GRAYSCALE)
+ options.setAutoscale(True)
+ options.setId(path_to_file)
+ imps = BF.openImagePlus(options) # is an array of ImagePlus
+
+ return imps[0]
+
+
+def fix_BF_czi_imagetitle(imp):
+ image_title = os.path.basename( imp.getTitle() )
+ image_title = image_title.replace(".czi", "")
+ image_title = image_title.replace(" ", "_")
+ image_title = image_title.replace("_-_", "")
+ image_title = image_title.replace("__", "_")
+ image_title = image_title.replace("#", "Series")
+
+ return image_title
+
+
+def clear_ij_roi_manager(rm):
+ """delete all ROIs from the RoiManager
+
+ Parameters
+ ----------
+ rm : RoiManager
+ a reference of the IJ-RoiManager
+ """
+ rm.runCommand('reset')
+
+
+def get_threshold_from_method(imp, channel, method):
+ """returns the threshold value of chosen IJ AutoThreshold method in desired channel
+
+ Parameters
+ ----------
+ imp : ImagePlus
+ the imp from which to get the threshold value
+ channel : integer
+ the channel in which to get the treshold
+ method : string
+ the AutoThreshold method to use
+
+ Returns
+ -------
+ list
+ the upper and the lower threshold (integer values)
+ """
+ imp.setC(channel) # starts at 1
+ ip = imp.getProcessor()
+ ip.setAutoThreshold(method + " dark")
+ lower_thr = ip.getMinThreshold()
+ upper_thr = ip.getMaxThreshold()
+ ip.resetThreshold()
+
+ return lower_thr, upper_thr
+
+
+def measure_in_all_rois( imp, channel, rm ):
+ """measures in all ROIS on a given channel of imp all parameters that are set in IJ "Set Measurements"
+
+ Parameters
+ ----------
+ imp : ImagePlus
+ the imp to measure on
+ channel : integer
+ the channel to measure in. starts at 1.
+ rm : RoiManager
+ a reference of the IJ-RoiManager
+ """
+ imp.setC(channel)
+ rm.runCommand(imp,"Deselect")
+ rm.runCommand(imp,"Measure")
+
+
+def change_all_roi_color( rm, color ):
+ """change the color of all ROIs in the RoiManager
+
+ Parameters
+ ----------
+ rm : RoiManager
+ a reference of the IJ-RoiManager
+ color : string
+ the desired color. e.g. "green", "red", "yellow", "magenta" ...
+ """
+ number_of_rois = rm.getCount()
+ for roi in range( number_of_rois ):
+ rm.select(roi)
+ rm.runCommand("Set Color", color)
+
+
+def change_subset_roi_color( rm, selected_rois, color ):
+ """change the color of selected ROIs in the RoiManager
+
+ Parameters
+ ----------
+ rm : RoiManager
+ a reference of the IJ-RoiManager
+ selected_rois : array
+ ROIs in the RoiManager to change
+ color : string
+ the desired color. e.g. "green", "red", "yellow", "magenta" ...
+ """
+ rm.runCommand("Deselect")
+ rm.setSelectedIndexes(selected_rois)
+ rm.runCommand("Set Color", color)
+ rm.runCommand("Deselect")
+
+
+def show_all_rois_on_image(rm, imp):
+ """shows all ROIs in the ROiManager on imp
+
+ Parameters
+ ----------
+ rm : RoiManager
+ a reference of the IJ-RoiManager
+ imp : ImagePlus
+ the imp on which to show the ROIs
+ """
+ imp.show()
+ rm.runCommand(imp,"Show All")
+
+
+def save_all_rois(rm, target):
+ """save all ROIs in the RoiManager as zip to target path
+
+ Parameters
+ ----------
+ rm : RoiManager
+ a reference of the IJ-RoiManager
+ target : string
+ the path in to store the ROIs. e.g. /my-images/resulting_rois.zip
+ """
+ rm.runCommand("Save", target)
+
+
+def save_selected_rois( rm, selected_rois, target ):
+ """save selected ROIs in the RoiManager as zip to target path
+
+ Parameters
+ ----------
+ rm : RoiManager
+ a reference of the IJ-RoiManager
+ selected_rois : array
+ ROIs in the RoiManager to save
+ target : string
+ the path in to store the ROIs. e.g. /my-images/resulting_rois_subset.zip
+ """
+ rm.runCommand("Deselect")
+ rm.setSelectedIndexes(selected_rois)
+ rm.runCommand("save selected", target)
+ rm.runCommand("Deselect")
+
+
+def select_positive_fibers( imp, channel, rm, min_intensity ):
+ """For all ROIs in the RoiManager, select ROIs based on intensity measurement in given channel of imp.
+ See https://imagej.nih.gov/ij/developer/api/ij/process/ImageStatistics.html
+
+ Parameters
+ ----------
+ imp : ImagePlus
+ the imp on which to measure
+ channel : integer
+ the channel on which to measure. starts at 1
+ rm : RoiManager
+ a reference of the IJ-RoiManager
+ min_intensity : integer
+ the selection criterion (here: intensity threshold)
+
+ Returns
+ -------
+ array
+ a selection of ROIs which passed the selection criterion (are above the threshold)
+ """
+ imp.setC(channel)
+ all_rois = rm.getRoisAsArray()
+ selected_rois = []
+ for i, roi in enumerate(all_rois):
+ imp.setRoi(roi)
+ stats = imp.getStatistics()
+ if stats.mean > min_intensity:
+ selected_rois.append(i)
+
+ return selected_rois
+
+
+def open_rois_from_zip( rm, path ):
+ """open RoiManager ROIs from zip and adds them to the RoiManager
+
+ Parameters
+ ----------
+ rm : RoiManager
+ a reference of the IJ-RoiManager
+ path : string
+ path to the ROI zip file
+ """
+ rm.runCommand("Open", path)
+
+
+def preset_results_column( rt, column, value):
+ """pre-set all rows in given column of the IJ-ResultsTable with desired value
+
+ Parameters
+ ----------
+ rt : ResultsTable
+ a reference of the IJ-ResultsTable
+ column : string
+ the desired column. will be created if it does not yet exist
+ value : string or float or integer
+ the value to be set
+ """
+ for i in range( rt.size() ):
+ rt.setValue(column, i, value)
+
+ rt.show("Results")
+
+
+def add_results( rt, column, row, value ):
+ """adds a value in desired rows of a given column
+
+ Parameters
+ ----------
+ rt : ResultsTable
+ a reference of the IJ-ResultsTable
+ column : string
+ the column in which to add the values
+ row : array
+ the row numbers in which too add the values.
+ value : string or float or integer
+ the value to be set
+ """
+ for i in range( len( row ) ):
+ rt.setValue(column, row[i], value)
+
+ rt.show("Results")
+
+
+def enhance_contrast( imp ):
+ """use "Auto" Contrast & Brightness settings in each channel of imp
+
+ Parameters
+ ----------
+ imp : ImagePlus
+ the imp on which to change C&B
+ """
+ for channel in range( imp.getDimensions()[2] ):
+ imp.setC(channel + 1) # IJ channels start at 1
+ IJ.run(imp, "Enhance Contrast", "saturated=0.35")
+
+
+def renumber_rois(rm):
+ """rename all ROIs in the RoiManager according to their number
+
+ Parameters
+ ----------
+ rm : RoiManager
+ a reference of the IJ-RoiManager
+ """
+ number_of_rois = rm.getCount()
+ for roi in range( number_of_rois ):
+ rm.rename( roi, str(roi + 1) )
+
+
+def setup_defined_ij(rm, rt):
+ """set up a clean and defined Fiji user environment
+
+ Parameters
+ ----------
+ rm : RoiManager
+ a reference of the IJ-RoiManager
+ rt : ResultsTable
+ a reference of the IJ-ResultsTable
+ """
+ fix_ij_options()
+ rm.runCommand('reset')
+ rt.reset()
+ IJ.log("\\Clear")
+
+
+execution_start_time = time.time()
+setup_defined_ij(rm, rt)
+
+# open image using Bio-Formats
+path_to_image = fix_ij_dirs(path_to_image)
+raw = open_image_with_BF(path_to_image)
+
+# get image info
+raw_image_calibration = raw.getCalibration()
+raw_image_title = fix_BF_czi_imagetitle(raw)
+
+# take care of paths and directories
+output_dir = os.path.dirname(str(roi_zip))
+output_dir = fix_ij_dirs(output_dir)
+
+# open ROIS and show on image
+open_rois_from_zip( rm, str(roi_zip) )
+change_all_roi_color(rm, "blue")
+show_all_rois_on_image( rm, raw )
+
+# update the log for the user
+IJ.log( "Now working on " + str(raw_image_title) )
+if raw_image_calibration.scaled() == False:
+ IJ.log("Your image is not spatially calibrated! Size measurements are only possible in [px].")
+IJ.log( " -- settings used -- ")
+IJ.log( "Selected fiber-ROIs zip-file = " + str(roi_zip) )
+IJ.log( "Fiber staining 1 channel number = " + str(fiber_channel_1) )
+IJ.log( "Fiber staining 2 channel number = " + str(fiber_channel_2) )
+IJ.log( "Fiber staining 3 channel number = " + str(fiber_channel_3) )
+IJ.log( " -- settings used -- ")
+
+# measure size & shape,
+IJ.run("Set Measurements...", "area perimeter shape feret's redirect=None decimal=4")
+IJ.run("Clear Results", "")
+measure_in_all_rois( raw, fiber_channel_1, rm )
+
+# loop trhough the fiber channels, check if positive, add info to results table
+all_fiber_channels = [fiber_channel_1, fiber_channel_2, fiber_channel_3]
+all_min_fiber_intensities = [min_fiber_intensity_1, min_fiber_intensity_2, min_fiber_intensity_3]
+roi_colors = ["green", "orange", "red"]
+all_fiber_subsets =[ [], [], [] ]
+
+for index, fiber_channel in enumerate(all_fiber_channels):
+ if fiber_channel > 0:
+ preset_results_column( rt, "channel " + str(fiber_channel) + " positive (" + roi_colors[fiber_channel-1] + ")", "NO" )
+ if all_min_fiber_intensities[index] == 0:
+ all_min_fiber_intensities[index] = get_threshold_from_method(raw, fiber_channel, "Mean")[0]
+ IJ.log( "fiber channel " + str(fiber_channel) + " intensity threshold: " + str(all_min_fiber_intensities[index]) )
+ positive_fibers = select_positive_fibers( raw, fiber_channel, rm, all_min_fiber_intensities[index] )
+ all_fiber_subsets[index] = positive_fibers
+ if len(positive_fibers) > 0:
+ change_subset_roi_color(rm, positive_fibers, roi_colors[index])
+ save_selected_rois( rm, positive_fibers, output_dir + "positive_fiber_rois_c" + str( fiber_channel ) + ".zip")
+ add_results( rt, "channel " + str(fiber_channel) + " positive (" + roi_colors[fiber_channel-1] + ")", positive_fibers, "YES")
+
+# single positive
+positive_c1 = all_fiber_subsets[0]
+positive_c2 = all_fiber_subsets[1]
+positive_c3 = all_fiber_subsets[2]
+# double positive
+positive_c1_c2 = list( set(all_fiber_subsets[0]).intersection(all_fiber_subsets[1]) )
+positive_c1_c3 = list( set(all_fiber_subsets[0]).intersection(all_fiber_subsets[2]) )
+positive_c2_c3 = list( set(all_fiber_subsets[1]).intersection(all_fiber_subsets[2]) )
+# triple positive
+positive_c1_c2_c3 = list( set(positive_c1_c2).intersection(all_fiber_subsets[2]) )
+
+# update ROI color & results table for double and triple positives
+if len(positive_c1_c2) > 0:
+ preset_results_column( rt, "channel 1,2 positive (magenta)", "NO" )
+ change_subset_roi_color(rm, positive_c1_c2, "magenta")
+ save_selected_rois( rm, positive_c1_c2, output_dir + "positive_fiber_rois_c1_c2.zip")
+ add_results( rt, "channel 1,2 positive (magenta)", positive_c1_c2, "YES")
+
+if len(positive_c1_c3) > 0:
+ preset_results_column( rt, "channel 1,3 positive (yellow)", "NO" )
+ change_subset_roi_color(rm, positive_c1_c3, "yellow")
+ save_selected_rois( rm, positive_c1_c3, output_dir + "positive_fiber_rois_c1_c3.zip")
+ add_results( rt, "channel 1,3 positive (yellow)", positive_c1_c3, "YES")
+
+if len(positive_c2_c3) > 0:
+ preset_results_column( rt, "channel 2,3 positive (cyan)", "NO" )
+ change_subset_roi_color(rm, positive_c2_c3, "cyan")
+ save_selected_rois( rm, positive_c2_c3, output_dir + "positive_fiber_rois_c2_c3.zip")
+ add_results( rt, "channel 2,3 positive (cyan)", positive_c2_c3, "YES")
+
+if len(positive_c1_c2_c3) > 0:
+ preset_results_column( rt, "channel 1,2,3 positive (white)", "NO" )
+ change_subset_roi_color(rm, positive_c1_c2_c3, "white")
+ save_selected_rois( rm, positive_c1_c2_c3, output_dir + "positive_fiber_rois_c1_c2_c3.zip")
+ add_results( rt, "channel 1,2,3 positive (white)", positive_c1_c2_c3, "YES")
+
+# save all results together
+save_all_rois( rm, output_dir + "all_fiber_type_rois_color-coded.zip" )
+rt.save(output_dir + "fibertyping_results.csv")
+
+# dress up the original image, save a overlay-png, present original to the user
+raw.show()
+show_all_rois_on_image( rm, raw )
+raw.setDisplayMode(IJ.COMPOSITE)
+enhance_contrast( raw )
+IJ.run("From ROI Manager", "") # ROIs -> overlays so they show up in the saved png
+qc_duplicate = raw.duplicate()
+IJ.saveAs(qc_duplicate, "PNG", output_dir + raw_image_title + "_fibertyping")
+qc_duplicate.close()
+wm.toFront( raw.getWindow() )
+IJ.run("Remove Overlay", "")
+raw.setDisplayMode(IJ.GRAYSCALE)
+show_all_rois_on_image( rm, raw )
+total_execution_time_min = (time.time() - execution_start_time) / 60.0
+IJ.log("total time in minutes: " + str(total_execution_time_min))
+IJ.log( "~~ all done ~~" )
+IJ.selectWindow("Log")
+IJ.saveAs("Text", str(output_dir + raw_image_title + "_fibertyping_Log"))
+if close_raw == True:
+ raw.close()
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