def main():
DEBUG = False
CN = [c.strip() for c in channel_names.split(",")]
if DEBUG:
imp1, imp2, imp3 = open_test()
else:
imp1, imp2, imp3 = open_msr(str(msr_fn))
msr_fn_base = os.path.basename(str(msr_fn))
signed2unsigned16(imp1)
signed2unsigned16(imp2)
signed2unsigned16(imp3)
imp1.updateAndDraw()
imp2.updateAndDraw()
imp3.updateAndDraw()
IJ.run(imp1, "Enhance Contrast", "saturated=0.35")
IJ.run(imp2, "Enhance Contrast", "saturated=0.35")
IJ.run(imp3, "Enhance Contrast", "saturated=0.35")
cal = imp1.getCalibration()
IMAGE_AREA_UM = cal.pixelWidth * imp1.getWidth() * cal.pixelHeight * imp1.getHeight()
t1 = apply_mask(imp1, sigma, CN[0], is_auto_thresh)
t2 = apply_mask(imp2, sigma, CN[1], is_auto_thresh)
t3 = apply_mask(imp3, sigma, CN[2], is_auto_thresh)
results = ResultsTable()
results.setHeading(0, "Channel")
results.setHeading(1, "Count")
results.setHeading(2, "Surface area (um)")
results.setHeading(3, "Surface area (%)")
results.setHeading(4, "Surface signal")
#results.setHeading(5, "Threshold used")
def add_to_table(channel, c, a, s):
results.incrementCounter()
results.setValue(0, results.getCounter()-1, channel)
results.addValue(1, c)
results.addValue(2, a)
results.addValue(3, 100 * a /IMAGE_AREA_UM)
results.addValue(4, s)
#results.setLabel(msr_fn_base, results.getCounter()-1)
imp1_mask, c,a,s = analyze(imp1, min_area)
add_to_table(CN[0], c, a, s)
#results.addValue(4, t1)
imp2_mask, c,a,s = analyze(imp2, min_area)
add_to_table(CN[1], c, a,s)
#results.addValue(4, t2)
imp3_mask, c,a,s = analyze(imp3, min_area)
add_to_table(CN[2], c, a,s)
#results.addValue(4, t3)
# IJ.run(imp1, "Enhance Contrast", "saturated=0.35")
# IJ.run(imp2, "Enhance Contrast", "saturated=0.35")
# IJ.run(imp3, "Enhance Contrast", "saturated=0.35")
imp_raw = RGBStackMerge.mergeChannels([imp1, imp2, imp3], True)
luts = list(imp_raw.getLuts())
imp_raw.setLuts([luts[2], luts[0], luts[1]] )
imp_raw.setTitle(msr_fn_base )
imp_raw.show()
if save_raw:
save_base_fn = os.path.splitext(str(msr_fn))[0]
IJ.save(imp_raw, save_base_fn + ".tif")
IJ.run(imp1, "Convert to Mask", "")
IJ.run(imp2, "Convert to Mask", "")
IJ.run(imp3, "Convert to Mask", "")
ic = ImageCalculator()
imp12 = ic.run("Muliply create", imp1, imp2)
imp13 = ic.run("Muliply create", imp1, imp3)
imp23 = ic.run("Muliply create", imp2, imp3)
imp123 = ic.run("Muliply create", imp12, imp3)
imp12_mask, c,a,s = analyze(imp12, min_area)
add_to_table("{}+{}".format(CN[0],CN[1]), c, a, -1)
imp13_mask, c,a,s = analyze(imp13, min_area)
add_to_table("{}+{}".format(CN[0],CN[2]), c, a, -1)
imp23_mask,c,a,s = analyze(imp23, min_area)
add_to_table("{}+{}".format(CN[1],CN[2]), c, a, -1)
imp123_mask,c,a,s = analyze(imp123, min_area)
add_to_table("{}+{}+{}".format(CN[0],CN[1], CN[2]), c, a, -1)
title = "Coloco3surf {}".format(msr_fn_base)
results.show(title)
imp_merge = RGBStackMerge.mergeChannels([imp1_mask, imp2_mask, imp3_mask, imp12_mask, imp13_mask, imp23_mask, imp123_mask], False)
luts = list(imp_merge.getLuts())
imp_merge.setLuts([luts[2], luts[0], luts[1]] + luts[3:])
imp_merge.setTitle(title)
imp_merge.show()
if save_surf:
save_base_fn = os.path.splitext(str(msr_fn))[0]
IJ.save(imp_merge, save_base_fn + "_surfaces.tif")
IJ.log("Done")
## set pixel calibration based on the entry on top cal = imp.getCalibration() cal.pixelHeight = pixelsize cal.pixelWidth = pixelsize pixelWidth = imp.getCalibration().pixelWidth print pixelWidth coordinates = [] ### setting up the results tables #### ort = ResultsTable() ort.setPrecision(0) #print ort.getCounter ort.setHeading(0, "Cell") ort.setHeading(1, "Point_C1") ort.setHeading(2, "Point_C2") ort.setHeading(3, "Distance in um") ort.setHeading(4, "Distance in pixel") ort.setHeading(5, "Area in um") ort.setHeading(6, "Feret in um") #pixelWidth = imp.getCalibration().pixelWidth ort2 = ResultsTable() ort2.setPrecision(3) ort2.setHeading(0, "Cell") ort2.setHeading(1, "Channel") ort2.setHeading(2, "Point #") ort2.setHeading(3, "Coordinates")
Returns
-------
the_sample double
The random sample from the distribution
"""
my_gmd = Log().value(gmd_nm)
my_gsd = Log().value(gsd)
distn = LogNormalDistribution(my_gmd, my_gsd)
the_sample = distn.sample()
return(the_sample)
tic = time.time()
n_samples = 2500
rt = ResultsTable(n_samples)
rt.setHeading(0, "num")
rt.setHeading(1, "ECD nm")
for x in range(0, n_samples):
my_sample = gen_random_lognormal_particle(50.0, 1.2)
rt.setValue(0, x, x+1)
rt.setValue(1, x, my_sample)
rt.show("Results")
IJ.saveAs("Results", csv_out)
toc = time.time()
elapsed = toc - tic
print("generated %g particles" % n_samples)
print("completed in %g sec" % elapsed )
