def myResults(results):
myResultsTable = ResultsTable()
for idx, graph in enumerate(results.getGraph()):
for edge in graph.getEdges():
edgeLength = edge.getLength()
v1 = edge.getV1()
v2 = edge.getV2()
dist = euclideanDistance(v1, v2)
#print('v1:', type(v1), v1.getPoints())
#
myResultsTable.incrementCounter() # add a row to results table
myResultsTable.addValue('graphID', idx)
myResultsTable.addValue('length_3d', edgeLength)
myResultsTable.addValue('dist', dist)
if dist > 0:
myResultsTable.addValue('tort', edgeLength / dist)
else:
myResultsTable.addValue('tort', 'inf')
myResultsTable.setPrecision(6)
myResultsTable.show('samiSkel_results')
Channel4 = Generate_segmented_manual(imp1, 4, "Moments", 2)
# # # # Generate ROIs by "Analyse Particles"
IJ.run(Channel4, "Analyze Particles...",
"size=5-Infinity pixel add exclude stack")
IJ.run("Clear Results", "")
Channel4_count = RoiManager.getInstance().getCount()
print Channel4_count
time.sleep(0.5)
rm.runCommand("reset")
time.sleep(0.5)
ort = ResultsTable()
ort.setPrecision(2)
ort.incrementCounter()
ort.addValue("Channel1", Channel1_count)
ort.addValue("Channel2", Channel2_count)
ort.addValue("Channel3", Channel3_count)
ort.addValue("Channel4", Channel4_count)
ort.show("Results")
if automatic_save_results:
dataname = imp1.getTitle()
filename = dataname + ".csv"
#files = glob.glob(savepath+"/"+dataname+"*.csv")
savename = savepath + "/" + filename
ort.saveAs(savename)
Channel1.changes = False
imp_height = imp.getHeight()
imp_width = imp.getWidth()
channelnumber = imp.getNChannels()
slicenumber = imp.getNSlices()
ExtractedChannel = Duplicator().run(imp, channel, channel, 1, slicenumber, timepoint, timepoint)
return ExtractedChannel
# identifying spots
def mean(numbers):
return float(sum(numbers)) / max(len(numbers), 1)
timepoints = imp1.getNFrames()
ort = ResultsTable()
ort.setPrecision(3)
IJ.run(imp1, "Select All", "")
stats_all = imp1.getStatistics( Measurements.AREA)
print str(stats_all.area)
IJ.run(imp1, "Select None", "")
WaitForUserDialog("Select cell-free region","select background free of cells").show()
stats_background = imp1.getStatistics( Measurements.AREA)
print str(stats_background.area)
IJ.run(imp1, "Select None", "")
for i in range (1, timepoints+1):
C2_Filtered_Cells_Spots = [] # Number of spots in Channel 2 ## End of list initialisation ## 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")
# def maxZprojection(stackimp):
# """ from EMBL python / Fiji cookbook"""
# allTimeFrames = Boolean.TRUE
# zp = ZProjector(stackimp)
# zp.setMethod(ZProjector.MAX_METHOD)
# zp.doHyperStackProjection()
# zpimp = zp.getProjection()
# return zpimp
imp2 = Generate_segmented_image(imp1, 2)
# # # # Generate ROIs by "Analyse Particles"
IJ.run(imp2, "Analyze Particles...",
"size=5-Infinity pixel add exclude stack")
IJ.run("Clear Results", "")
ort = ResultsTable()
ort.setPrecision(1)
imp_measure = ExtractChannel(imp1, Measure_Channel)
imp_measure.show()
for i, roi in enumerate(RoiManager.getInstance().getRoisAsArray()):
roi2 = rm.getRoiIndex(roi)
rm.select(imp_measure, roi2)
stats = imp_measure.getStatistics(Measurements.MEAN | Measurements.AREA
| Measurements.FERET
| Measurements.CENTROID)
ort.incrementCounter()
#ort.addValue("ROI", str(i))
ort.addValue("Mean intensity", str(stats.mean))
ort.addValue("Area", str(stats.area))
ort.addValue("Compartment", (channel2_name))
