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Commit 9c2ad26f authored by Laurent Guerard's avatar Laurent Guerard
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Formatting and correction

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2c_fibertyping.py
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# @ String (visibility=MESSAGE, value="<html><b> Welcome to Myosoft! </b></html>") msg1 # @ 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 fiber-ROIs zip-file", style="file") roi_zip
# @ File (label="Select image file", description="select your image") path_to_image # @ File (label="Select image file", description="select your image") path_to_image
#@ File (label="Select directory for output", style="directory") output_dir # @ File (label="Select directory for output", style="directory") output_dir
#@ Boolean (label="close image after processing", description="tick this box when using batch mode", value=False) close_raw # @ 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 # @ 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 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 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="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_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_2
#@ Integer (label="minimum fiber intensity (0=auto)", description="0 = automatic threshold detection", value=0) min_fiber_intensity_3 # @ Integer (label="minimum fiber intensity (0=auto)", description="0 = automatic threshold detection", value=0) min_fiber_intensity_3
# @ ResultsTable rt # @ ResultsTable rt
# @ RoiManager rm # @ RoiManager rm
...@@ -50,7 +50,7 @@ def get_threshold_from_method(imp, channel, method): ...@@ -50,7 +50,7 @@ def get_threshold_from_method(imp, channel, method):
A list containing the upper and the lower threshold (integer values). A list containing the upper and the lower threshold (integer values).
""" """
# Set the channel of the imp to the desired channel # Set the channel of the imp to the desired channel
imp.setC(channel) # starts at 1 imp.setC(channel) # starts at 1
# Get the processor of the imp # Get the processor of the imp
ip = imp.getProcessor() ip = imp.getProcessor()
# Set the AutoThreshold method to the desired method # Set the AutoThreshold method to the desired method
...@@ -159,28 +159,35 @@ if __name__ == "__main__": ...@@ -159,28 +159,35 @@ if __name__ == "__main__":
roimanager.load_rois_from_zip(rm, input_rois_path) roimanager.load_rois_from_zip(rm, input_rois_path)
roimanager.change_roi_color(rm, "blue") roimanager.change_roi_color(rm, "blue")
# update the log for the user # update the log for the user
IJ.log( "Now working on " + str(raw_image_title) ) IJ.log("Now working on " + str(raw_image_title))
if raw_image_calibration.scaled() == False: if not raw_image_calibration.scaled():
IJ.log("Your image is not spatially calibrated! Size measurements are only possible in [px].") IJ.log(
IJ.log( " -- settings used -- ") "Your image is not spatially calibrated! Size measurements are only possible in [px]."
IJ.log( "Selected fiber-ROIs zip-file = " + str(input_rois_path) ) )
IJ.log( "Fiber staining 1 channel number = " + str(fiber_channel_1) ) IJ.log(" -- settings used -- ")
IJ.log( "Fiber staining 2 channel number = " + str(fiber_channel_2) ) IJ.log("Selected fiber-ROIs zip-file = " + str(input_rois_path))
IJ.log( "Fiber staining 3 channel number = " + str(fiber_channel_3) ) IJ.log("Fiber staining 1 channel number = " + str(fiber_channel_1))
IJ.log( " -- settings used -- ") IJ.log("Fiber staining 2 channel number = " + str(fiber_channel_2))
IJ.log("Fiber staining 3 channel number = " + str(fiber_channel_3))
# measure size & shape, IJ.log(" -- settings used -- ")
IJ.run("Set Measurements...", "area perimeter shape feret's redirect=None decimal=4")
IJ.run("Clear Results", "") # measure size & shape,
measure_in_all_rois( raw, fiber_channel_1, rm ) IJ.run(
"Set Measurements...", "area perimeter shape feret's redirect=None decimal=4"
)
IJ.run("Clear Results", "")
roimanager.measure_in_all_rois(raw, fiber_channel_1, rm) roimanager.measure_in_all_rois(raw, fiber_channel_1, rm)
# loop through the fiber channels, check if positive, add info to results table # loop through the fiber channels, check if positive, add info to results table
all_fiber_channels = [fiber_channel_1, fiber_channel_2, fiber_channel_3] 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] all_min_fiber_intensities = [
roi_colors = ["green", "orange", "red"] min_fiber_intensity_1,
all_fiber_subsets =[ [], [], [] ] 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): for index, fiber_channel in enumerate(all_fiber_channels):
if fiber_channel > 0: if fiber_channel > 0:
...@@ -242,24 +249,28 @@ all_fiber_subsets =[ [], [], [] ] ...@@ -242,24 +249,28 @@ all_fiber_subsets =[ [], [], [] ]
"YES", "YES",
) )
# single positive # single positive
positive_c1 = all_fiber_subsets[0] positive_c1 = all_fiber_subsets[0]
positive_c2 = all_fiber_subsets[1] positive_c2 = all_fiber_subsets[1]
positive_c3 = all_fiber_subsets[2] positive_c3 = all_fiber_subsets[2]
# double positive # double positive
positive_c1_c2 = list( set(all_fiber_subsets[0]).intersection(all_fiber_subsets[1]) ) 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_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]) ) positive_c2_c3 = list(set(all_fiber_subsets[1]).intersection(all_fiber_subsets[2]))
# triple positive # triple positive
positive_c1_c2_c3 = list( set(positive_c1_c2).intersection(all_fiber_subsets[2]) ) positive_c1_c2_c3 = list(set(positive_c1_c2).intersection(all_fiber_subsets[2]))
# update ROI color & results table for double and triple positives # update ROI color & results table for double and triple positives
channels = [ channels = [
(positive_c1_c2, [fiber_channel_1, fiber_channel_2], "magenta"), (positive_c1_c2, [fiber_channel_1, fiber_channel_2], "magenta"),
(positive_c1_c3, [fiber_channel_1, fiber_channel_3], "yellow"), (positive_c1_c3, [fiber_channel_1, fiber_channel_3], "yellow"),
(positive_c2_c3, [fiber_channel_2, fiber_channel_3], "cyan"), (positive_c2_c3, [fiber_channel_2, fiber_channel_3], "cyan"),
(positive_c1_c2_c3, [fiber_channel_1, fiber_channel_2, fiber_channel_3], "white") (
] positive_c1_c2_c3,
[fiber_channel_1, fiber_channel_2, fiber_channel_3],
"white",
),
]
for positives, ch_nums, color in channels: for positives, ch_nums, color in channels:
if positives: if positives:
...@@ -289,13 +300,13 @@ channels = [ ...@@ -289,13 +300,13 @@ channels = [
# dress up the original image, save a overlay-png, present original to the user # dress up the original image, save a overlay-png, present original to the user
raw.show() raw.show()
roimanager.show_all_rois_on_image(rm, raw) roimanager.show_all_rois_on_image(rm, raw)
# raw.setDisplayMode(IJ.COMPOSITE) # raw.setDisplayMode(IJ.COMPOSITE)
enhance_contrast( raw ) enhance_contrast(raw)
IJ.run("From ROI Manager", "") # ROIs -> overlays so they show up in the saved png IJ.run("From ROI Manager", "") # ROIs -> overlays so they show up in the saved png
qc_duplicate = raw.duplicate() qc_duplicate = raw.duplicate()
IJ.saveAs(qc_duplicate, "PNG", output_dir + "/" + raw_image_title + "_fibertyping") IJ.saveAs(qc_duplicate, "PNG", output_dir + "/" + raw_image_title + "_fibertyping")
qc_duplicate.close() qc_duplicate.close()
wm.toFront( raw.getWindow() ) wm.toFront(raw.getWindow())
IJ.log( IJ.log(
"Script finished. Total runtime [HH:MM:SS.ss]: " "Script finished. Total runtime [HH:MM:SS.ss]: "
......
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