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Commit d34dc6c3 authored by Kai Schleicher's avatar Kai Schleicher
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Remove unused function, its execution and associated import

parent 0b133811
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......@@ -30,7 +30,7 @@ from loci.formats import ImageReader, MetadataTools, Memoizer
# MorpholibJ imports
from inra.ijpb.binary import BinaryImages
# BIOP imports
from ch.epfl.biop.ij2command import Labels2Rois, Rois2Labels
from ch.epfl.biop.ij2command import Labels2Rois
# python imports
import os
......@@ -330,7 +330,7 @@ def measure_intensity_sum(imp, rm):
Example
-------
>>> labels, intensities = measure_intensity_sum(image, roi_manager)
>>> labels, intensities = measure_intensity_sum(imp, roi_manager)
"""
rt_ = ResultsTable()
......@@ -428,17 +428,6 @@ def load_rois_from_zip(path):
rm.runCommand("Open", path)
def convert_rois_to_labelimage(imp):
rm = RoiManager.getInstance()
if not rm:
rm = RoiManager()
label_imp = command.run( Rois2Labels , False , 'imp' , imp , 'rm', rm).get().getOutput("label_imp")
rm.reset() # TODO: should be optional but can be default
return label_imp
def close_images(list_of_imps):
"""Close given ImagePlus images
......@@ -468,11 +457,6 @@ if threshold <= 0:
threshold = get_threshold_from_method(dapi_channel, "otsu")
dapi_binary = convert_to_binary(dapi_channel, threshold)
# Get the fiber segmentation from ij roizip and convert to labelimage
load_rois_from_zip(fiber_segmentation_roiset)
fibers_label_imp = convert_rois_to_labelimage(dapi_channel)
dapi_channel.close()
# detect spots and count them per fiber
results_table = ResultsTable()
for index, channel in enumerate(processing_channels):
......@@ -480,7 +464,7 @@ for index, channel in enumerate(processing_channels):
quality_threshold = float(quality_thresholds[index])
spots_channel = BFopen_image(path_to_image, channel, series_number)
spots_label_imp = run_trackmate_dog_spot_detector(spots_channel, spot_diameter, quality_threshold)
save_image_as_IJtif(spots_label_imp, filename, "spots_ch" + str(channel), parent_dir)
# save_image_as_IJtif(spots_label_imp, filename, "spots_ch" + str(channel), parent_dir)
save_labelimage_as_ijroiset(spots_label_imp, filename, "spots_ch" + str(channel), parent_dir)
spots_binary_imp = convert_labelimage_to_binary(spots_label_imp)
dapi_positive_spots_binary = ImageCalculator.run(spots_binary_imp, dapi_binary, "Multiply create")
......
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