Python measure.ResultsTable类代码示例

def anaParticles(imp, minSize, maxSize, minCirc, bHeadless=True):
  """anaParticles(imp, minSize, maxSize, minCirc, bHeadless=True)
  Analyze particles using a watershed separation. If headless=True, we cannot
  redirect the intensity measurement to the original immage becuae it is never
  displayed. If we display the original, we can and get the mean gray level. We
  may then compute the particle contrast from the measured Izero value for the image.
  No ability here to draw outlines on the original."""
  strName = imp.getShortTitle()
  imp.setTitle("original")
  ret = imp.duplicate()
  IJ.run(ret, "Enhance Contrast", "saturated=0.35")
  IJ.run(ret, "8-bit", "")
  IJ.run(ret, "Threshold", "method=Default white")
  IJ.run(ret, "Watershed", "")
  rt = ResultsTable()
  # strSetMeas = "area mean modal min center perimeter bounding fit shape feret's redirect='original' decimal=3"
  # N.B. redirect will not work without a displayed image, so we cannot use a gray level image
  if bHeadless == True:
    strSetMeas = "area mean modal min center perimeter bounding fit shape feret's decimal=3"
  else:
    imp.show()
    strSetMeas = "area mean modal min center perimeter bounding fit shape feret's redirect='original' decimal=3"
  IJ.run("Set Measurements...", strSetMeas)
  # note this doies not get passed directly to ParticleAnalyzer, so
  # I did this, saved everything and looked for the measurement value in ~/Library/Preferences/IJ_Prefs.txt
  # measurements=27355
  # meas = Measurements.AREA + Measurements.CIRCULARITY + Measurements.PERIMETER + Measurements.SHAPE_DESCRIPTORS
  # didn't work reliably
  meas = 27355
  pa = ParticleAnalyzer(0, meas, rt, minSize, maxSize, minCirc, 1.0);
  pa.analyze(ret);
  rt.createTableFromImage(ret.getProcessor())
  return [ret, rt]

 def containsRoot_(self):
     IJ.run("Clear Results")
     IJ.run("Measure")
     table = RT.getResultsTable()
     if RT.getValue(table, "Max", 0) == 0:
         return False
     return True

def run_straighten(roiWindowsize = 4):
    """ Original straightening function based on Nick's macro. Used in final version.
    Returns coordinate string used to make centerline. """
    IJ.run("Set Measurements...", "mean min center redirect=None decimal=3")
    IJ.runMacro("//setTool(\"freeline\");")
    IJ.run("Line Width...", "line=80");
    numPoints = 512/roiWindowsize
    xvals = []
    yvals = []
    maxvals = []
    counter = 0

    for i in range(0, 512, roiWindowsize):
        IJ.run("Clear Results")
        IJ.makeRectangle(i, 0, roiWindowsize, 512)
        IJ.run("Measure")
        table = RT.getResultsTable()
        xvals.append(i + roiWindowsize/2)
        yvals.append(RT.getValue(table, "YM", 0))
        maxvals.append((RT.getValue(table, "Max", 0)))

        if maxvals[counter] == 0 and counter > 0:
            yvals[counter] = yvals[counter - 1]

        counter += 1

    coords = ""
    for i in range(numPoints - 1):
        coords += str(xvals[i]) + ", " + str(yvals[i]) +", "
    coords += str(xvals[numPoints-1]) + ", " + str(yvals[numPoints-1])

    IJ.runMacro("makeLine("+coords+")")
    IJ.run("Straighten...", "line = 80")
    return coords

def measure_growth(imgDir, filename = "Fiji_Growth.txt"):
    """ Collects measurement data in pixels and writes to a file. Uses straightened binary images"""
    f = open(imgDir + filename, 'w')
    f.write("Img number\tEnd point (pixels)\n")
    IJ.run("Set Measurements...", "area mean min center redirect=None decimal=3")
    index = "000000000"
    filename = imgDir + "/binary" + "/img_" + index + "__000-padded.tif"
    while path.exists(filename):
		imp = IJ.openImage(filename)
		imp.show()
		IJ.run("Clear Results")
		for i in xrange(800): #hard coded to target length for now
			IJ.makeRectangle(i, 0, 1, 80)
			IJ.run("Measure")
			table = RT.getResultsTable()
			#print "i:", i, "counter:", table.getCounter()
			maxi = RT.getValue(table, "Max", i)
			if maxi == 0:
				f.write(str(int(index)) + "\t" + str(i) + "\n")
				break

		IJ.runMacro("while (nImages>0) {selectImage(nImages);close();}")
		index = to_9_Digits(str(int(index)+1))
		filename = imgDir + "/padded" + "/img_" + index + "__000-padded.tif"
    f.close()

def new_Table():
    """Creates a new ResultsTable padded with float("nan"), ie, all
       empty cells will be filled with Java's String.valueOf(Double.NaN)
    """
    new_rt = RT()
    new_rt.setNaNEmptyCells(True);
    new_rt.showRowNumbers(False);
    return new_rt

def writeCSV(filePath, results, header):
	""" Write a table as an csv file """
	rt = ResultsTable()
	for i in range(len(results[1])): 
		rt.incrementCounter()
		for j in range(len(results)):
			rt.addValue(str(header[j]), results[j][i])
	rt.show("Results")
	rt.saveAs(filePath); 

    def measure(self):
        imp = IJ.openImage(self.filename)
        IJ.log("Input file: %s" % self.filename)

        ImageConverter(imp).convertToGray8()

        res = Auto_Threshold().exec(imp, self.myMethod, self.noWhite, self.noBlack, self.doIwhite, self.doIset, self.doIlog, self.doIstackHistogram)

        rt = ResultsTable()
        rt.showRowNumbers(False)
        pa = PA(self.options, PA.AREA + PA.PERIMETER + PA.CIRCULARITY, rt, self.MINSIZE, self.MAXSIZE)
        pa.analyze(imp)
        self.result = self.rtToResult(rt)
        self.mask = imp

	def __localwand(self, x, y, ip, seuil, method, light):
		self.__image.killRoi()
		ip.snapshot()
		if method == "mean" : 
			peak=ip.getPixel(x,y)
			tol = (peak - self.getMean())*seuil
			w = Wand(ip)
			w.autoOutline(x, y, tol, Wand.EIGHT_CONNECTED)
			#print "method=", method, tol, peak
			
		elif method == "background" : 
			radius = self.getMinF()/4 
			bs = BackgroundSubtracter()
			#rollingBallBackground(ImageProcessor ip, double radius, boolean createBackground, boolean lightBackground, boolean useParaboloid, boolean doPresmooth, boolean correctCorners) 
			bs.rollingBallBackground(ip, radius, False, light, False, True, False)
			peak=ip.getPixel(x,y)
			tol = peak*seuil
			w = Wand(ip)
			w.autoOutline(x, y, tol, Wand.EIGHT_CONNECTED)
			ip.reset()
			#print "method=", method, tol, radius, peak
			
		else : 
			peak=ip.getPixel(x,y)
			tol = peak*seuil
			w = Wand(ip)
			w.autoOutline(x, y, tol, Wand.EIGHT_CONNECTED)
			#print "method=", method, tol

		peak=ip.getPixel(x,y)
		temproi=PolygonRoi(w.xpoints, w.ypoints, w.npoints, PolygonRoi.POLYGON)
		self.__image.setRoi(temproi)
		#self.__image.show()
		#time.sleep(1)
		#peakip=self.__image.getProcessor()
		#stats=peakip.getStatistics()
		temprt = ResultsTable()
		analyser = Analyzer(self.__image, Analyzer.AREA+Analyzer.INTEGRATED_DENSITY+Analyzer.FERET, temprt)
		analyser.measure()
		#temprt.show("temprt")
		rtValues=temprt.getRowAsString(0).split("\t")
		area=float(rtValues[1])
		intDen=float(rtValues[4])
		feret=float(rtValues[2])
		mean=intDen/area
		#time.sleep(2)
		temprt.reset()
		self.__image.killRoi()
		return [peak, area, mean, intDen, feret]

	def __NbFoci(self):
		self.__boolFoci=True
		self.__image.killRoi()
		self.__image.setRoi(self.__contour)
		self.__ip=self.__image.getProcessor()
		rt=ResultsTable.getResultsTable()
		rt.reset()
		mf=MaximumFinder()
		mf.findMaxima(self.__ip, self.__noise, 0, MaximumFinder.LIST, True, False)
		self.__listMax[:]=[]
		
		#feret=self.getFercoord()
		#xc=feret[0]-((feret[0]-feret[2])/2.0)
		#yc=feret[1]-((feret[1]-feret[3])/2.0)

		#print xc, yc

		xc=self.getXC()
		yc=self.getYC()

		#print xc, yc
		
		for i in range(rt.getCounter()):
			x=int(rt.getValue("X", i))
			y=int(rt.getValue("Y", i))
			size=self.__localwand(x, y, self.__ip, self.__seuilPeaks, self.__peaksMethod, self.__light)
			coord=[(1, xc, x), (1, yc, y)]
 			d=self.distMorph(coord,"Euclidean distance")
 			d=( d / (self.getMaxF()/2) )*100
 			self.__listMax.append((x, y, size[0], size[1], size[2], size[3], size[4], d))
		rt.reset()

	def __Measures(self):

		self.__boolmeasures=True
		if (self.__contour is not None) and  (self.__contour.getType() not in [9,10]):
			self.__image.killRoi()
			self.__image.setRoi(self.__contour)
			self.__ip=self.__image.getProcessor()
			self.__rt= ResultsTable()
			analyser= Analyzer(self.__image, Analyzer.AREA+Analyzer.CENTER_OF_MASS+Analyzer.CENTROID+Analyzer.ELLIPSE+Analyzer.FERET+Analyzer.INTEGRATED_DENSITY+Analyzer.MEAN+Analyzer.KURTOSIS+Analyzer.SKEWNESS+Analyzer.MEDIAN+Analyzer.MIN_MAX+Analyzer.MODE+Analyzer.RECT+Analyzer.SHAPE_DESCRIPTORS+Analyzer.SLICE+Analyzer.STACK_POSITION+Analyzer.STD_DEV, self.__rt)
			analyser.measure()
			#self.__rt.show("myRT")
		else:
			self.__rt = ResultsTable()
			analyser = Analyzer(self.__image, Analyzer.AREA+Analyzer.CENTER_OF_MASS+Analyzer.CENTROID+Analyzer.ELLIPSE+Analyzer.FERET+Analyzer.INTEGRATED_DENSITY+Analyzer.MEAN+Analyzer.KURTOSIS+Analyzer.SKEWNESS+Analyzer.MEDIAN+Analyzer.MIN_MAX+Analyzer.MODE+Analyzer.RECT+Analyzer.SHAPE_DESCRIPTORS+Analyzer.SLICE+Analyzer.STACK_POSITION+Analyzer.STD_DEV, self.__rt)
			analyser.measure()
			#self.__rt.show("myRT")
			maxValues=self.__rt.getRowAsString(0).split("\t")
			heads=self.__rt.getColumnHeadings().split("\t")
			for val in heads: self.__rt.setValue(val, 0, Float.NaN)

def measureSkeletonTotalLength(imp, root):
  IJ.run(imp,"Analyze Skeleton (2D/3D)", "prune=none")
  totalLength = 0
  nBranches = 0
  rt = ResultsTable.getResultsTable()
  avgLengths = rt.getColumn(rt.getColumnIndex("Average Branch Length"))
  for i in range(len(avgLengths)):
    totalLength = totalLength + rt.getValue("# Branches", i) * rt.getValue("Average Branch Length", i)
    nBranches = nBranches + rt.getValue("# Branches", i)	
  print root,",",imp.getTitle(),",",totalLength,",",nBranches

def countParticles(imp, roim, minSize, maxSize, minCircularity, maxCircularity):
	# Create a table to store the results
	table = ResultsTable()
	
	# Create the particle analyzer
	pa = ParticleAnalyzer(ParticleAnalyzer.ADD_TO_MANAGER, Measurements.AREA|Measurements.MEAN, table, minSize, maxSize, minCircularity, maxCircularity)
	#pa = ParticleAnalyzer(ParticleAnalyzer.ADD_TO_MANAGER, Measurements.AREA|Measurements.MEAN, table, 10, Double.POSITIVE_INFINITY, 0.5, 1.0)
	#pa = ParticleAnalyzer(ParticleAnalyzer.ADD_TO_MANAGER, Measurements.AREA|Measurements.MEAN, table, 5, 6, 0.5, 1.0)
	pa.setRoiManager(roim)
	pa.setHideOutputImage(True)

	if pa.analyze(imp):
		print "All ok"
	else:
 		print "There was a problem in analyzing", blobs

 	areas = table.getColumn(0)
	intensities = table.getColumn(1)

	if ( (areas!=None) and (intensities!=None)):
 		for area, intensity in zip(areas,intensities): print str(area)+": "+str(intensity)

def getParticleCenters(imp):
    # Create a table to store the results
    rt = ResultsTable()
    paOpts = PA.SHOW_OUTLINES \
            + PA.INCLUDE_HOLES \
            + PA.EXCLUDE_EDGE_PARTICLES
    measurements = PA.CENTROID + PA.CENTER_OF_MASS
    MINSIZE = 1000
    MAXSIZE = Double.POSITIVE_INFINITY
    pa = PA(paOpts,measurements, rt, MINSIZE, MAXSIZE)
    pa.setHideOutputImage(True)
     
    if not pa.analyze(imp):
        print "There was a problem in analyzing", imp

    # The measured centroids are listed in the first column of the results table, as a float array:
    centroids_x = rt.getColumn(rt.X_CENTROID)
    centroids_y = rt.getColumn(rt.Y_CENTROID)
    coms_x = rt.getColumn(rt.X_CENTER_OF_MASS)
    coms_y = rt.getColumn(rt.Y_CENTER_OF_MASS)

    return (centroids_x,centroids_y, coms_x, coms_y)

	def __init__(self):
		self.imp = None
		self.preview = None
		self.createMainWindow()
		self.cells = None
		self.files = []
		self.results = ResultsTable()
		ImagePlus.addImageListener(self)
		self.selectInputDir()
		self.selectOutputDir()
		self.pairs = []
		self.methods = []
		self.processNextFile()

def straighten_roi_rotation(roiWindowsize = 8):
    """ Root straightening function that rotates ROI to follow root slope.
    Does not work properly.
    """
    IJ.run("Set Measurements...", "mean standard min center redirect=None decimal=3")
    IJ.runMacro("//setTool(\"freeline\");")
    IJ.run("Line Width...", "line=80");
    #numPoints = 512/roiWindowsize
    xvals = []
    yvals = []
    maxvals = []
    counter = 0
    maxIters = 800/roiWindowsize
    minIters = 10

    imp = IJ.getImage().getProcessor()

    rm = RoiManager()
    if find_first_pixel(0,imp) == None or find_last_pixel(0,imp)[1] == None:
        return
    y = (find_first_pixel(0,imp)[1]+find_last_pixel(0,imp)[1])/2
    roi = roiWindow_(imp, center = (roiWindowsize/2,y), width = roiWindowsize, height = 512)
    xvals.append(roiWindowsize/2)
    yvals.append(y)
    maxvals.append(0)
    roi.findTilt_()
    i = 0
    while i < maxIters and roi.containsRoot_():
    	roi.advance_(roiWindowsize)
        IJ.run("Clear Results")
        IJ.run("Measure")
        table = RT.getResultsTable()

        x  = RT.getValue(table, "XM", 0)
        y = RT.getValue(table, "YM", 0)
        if imp.getPixel(int(x),int(y)) != 0:
            xvals.append(x)
            yvals.append(y)
            maxvals.append((RT.getValue(table, "Max", 0)))


        #roi.advance_(roiWindowsize)
        print "here"
        roi.unrotateRoot_()
        IJ.run("Clear Results")
        IJ.run("Measure")
        roi.restoreCenter_(RT.getValue(table, "XM", 0), RT.getValue(table, "YM", 0))
        #exit(1)
        sleep(.5)
        roi.findTilt_()
        i += 1
    coords = ""
    for i in range(len(xvals)-1):
        coords += str(xvals[i]) + ", " + str(yvals[i]) +", "
    coords += str(xvals[len(xvals)-1]) + ", " + str(yvals[len(xvals)-1])

    IJ.runMacro("makeLine("+coords+")")
    IJ.run("Straighten...", "line = 80")