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))