def analyze(imp, min_area):
MAXSIZE = 1000000000000
MINCIRCULARITY = 0.0
MAXCIRCULARITY = 1.
options = PA.SHOW_MASKS
temp_results = ResultsTable()
p = PA(options, PA.AREA + PA.MEAN, temp_results, min_area, MAXSIZE, MINCIRCULARITY, MAXCIRCULARITY)
p.setHideOutputImage(True)
p.analyze(imp)
if temp_results.getCounter() == 0:
areas = []
signals = []
else:
areas = list(temp_results.getColumn(0))
signals = list(temp_results.getColumn(1))
count = len(areas)
area = sum(areas)
total = 0
if area > 0:
total = sum([a*s for a,s in zip(areas, signals)]) / area
return p.getOutputImage(), count, area, total
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 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 containsRoot_(self):
IJ.run("Clear Results")
IJ.run("Measure")
table = RT.getResultsTable()
if RT.getValue(table, "Max", 0) == 0:
return False
return True
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 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 pixel_collector(rm, channel_imp, channel_name, impname, folder):
# define new Results table
rt = ResultsTable()
IndRois = rm.getIndexes()
for index in IndRois:
ROI = rm.getRoi(index)
ROI_name = ROI.getName()
coords = ROI.getContainedPoints()
row = 0
for pixel in coords:
x_coord = pixel.getX()
y_coord = pixel.getY()
rt.setValue(ROI_name + "_X_pos", row, int(x_coord))
rt.setValue(ROI_name + "_Y_pos", row, int(y_coord))
pixel_2 = channel_imp.getProcessor().getPixel(
int(x_coord), int(y_coord))
rt.setValue(ROI_name + "_" + channel_name, row, pixel_2)
row = row + 1
rt.show("Results")
rt.save(os.path.join(folder, impname + '_' + channel_name + "_pixels.csv"))
print "Pixel collection done!"
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 geometrical_measure_3D(imp_label):
# remove results table if exists:
close_non_image_window("Results")
# measure
#imp_label.show()
rt = ResultsTable.getResultsTable()
IJ.run(imp_label, "3D Geometrical Measure", "");
rt = ResultsTable.getResultsTable()
return rt
def geometrical_measure_3D(imp_label):
# remove results table if exists:
close_non_image_window("Results")
# measure
#imp_label.show()
rt = ResultsTable.getResultsTable()
IJ.run(imp_label, "3D Geometrical Measure", "");
rt = ResultsTable.getResultsTable()
return 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 showRoiSummary(table):
res=ResultsTable()
for i,val in table.items():
res.setValue('id',i,i+1)
valInd=val.keys()
valInd.remove('Class')
for ind in valInd:
res.setValue(ind,i,val[ind])
res.setValue('Class',i,val['Class'])
res.show('[ROI Summary]'+imgName)
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 process(inputpath, outputpath):
imp = IJ.openImage(inputpath)
IJ.run(
imp, "Properties...",
"channels=1 slices=1 frames=1 unit=um pixel_width=0.8777017 pixel_height=0.8777017 voxel_depth=25400.0508001"
)
IJ.setThreshold(imp, t1, 255)
#imp.show()
#WaitForUserDialog("Title", "Look at image").show()
IJ.run(imp, "Convert to Mask", "")
IJ.run(imp, "Watershed", "")
# Counts and measures the area of particles and adds them to a table called areas. Also adds them to the ROI manager
table = ResultsTable()
roim = RoiManager(True)
ParticleAnalyzer.setRoiManager(roim)
pa = ParticleAnalyzer(ParticleAnalyzer.ADD_TO_MANAGER, Measurements.AREA,
table, 50, 9999999999999999, 0.2, 1.0)
pa.setHideOutputImage(True)
pa.analyze(imp)
imp.changes = False
imp.close()
areas = table.getColumn(0)
summary = {}
if areas:
summary['Image'] = filename
summary['Nuclei.count'] = len(areas)
summary['Area.Covered'] = sum(areas)
fieldnames = list(summary.keys())
with open(outputpath, 'a') as csvfile:
writer = csv.DictWriter(csvfile,
fieldnames=fieldnames,
extrasaction='ignore',
lineterminator='\n')
if os.path.getsize(outputDirectory + "/" + outputname + ".csv") < 1:
writer.writeheader()
writer.writerow(summary)
def measure_roi_set(roi_set, imp, set_measure=MEAS_ALL) :
"""requires imp because it won't measure without one
note.. side effects: ResultsTable and RoiManager cleared"""
# imp.show()
rt = ResultsTable.getResultsTable()
rt.reset()
rm = RoiManager.getRoiManager()
rm.reset()
if roi_set is not None :
for roi in roi_set :
add_roi(roi)
rm.setSelectedIndexes([x for x in range(rm.getCount())])
setMeasurementInt(set_measure)
print("before rm measure")
# IJ.setActiveImage(imp)
# IJ.selectWindow(imp.getTitle())
# imp.show()
try :
# input()
# for roi in roi_set :
# imp.
rm.runCommand(imp, "Measure")
except :
input()
print("after rm measure")
results = rt_to_col_dict()
# imp.hide()
return results
def delete(imp, roiMan, roiTotal):
# set results table
rt = ResultsTable.getResultsTable()
# set up analyzer
analyzer = Analyzer(imp, 1, rt)
totalPixels = 0
# Set the color and line options for erasing
IJ.run("Colors...", "foreground=black background=black selection=magenta")
if roiMan is not None:
# Iterate through the ROIs
for roi in xrange(roiTotal):
# Select the ROI
roiMan.select(roi)
selectRoi = roiMan.getRoi(roi)
# measure
analyzer.measure()
meas = rt.getRowAsString(0)
newLine = meas.split(" ", 1)
pixels = float(newLine[1])
totalPixels = totalPixels + pixels
# Tag the ROI
IJ.run(imp, "Fill", "slice")
# end for loop
return totalPixels
else:
return 0
def run():
global srcFile, ext, numberOfWidthMeasurements
IJ.run("Set Measurements...", "area mean standard modal min centroid center perimeter bounding fit shape feret's integrated median skewness kurtosis area_fraction display redirect=None decimal=3");
IJ.setForegroundColor(255,255,255);
IJ.setBackgroundColor(0,0,0);
IJ.run("Options...", "iterations=1 count=1 black");
table = ResultsTable()
srcDir = srcFile.getAbsolutePath()
for root, directories, filenames in os.walk(srcDir):
for filename in filenames:
# Check for file extension
if not filename.endswith(ext):
continue
# Check for file name pattern
process(srcDir, root, filename, table, numberOfWidthMeasurements)
table.save(os.path.join(srcDir, 'Results.xls'))
def roiAnalysisToWrite(self, roiTableName):
#I can't figure out the syntax to preallocate memory,
#this will not scale to many speckles
try:
RT = ResultsTable.getResultsTable(roiTableName)
headings = RT.getHeadings()
labelCol = RT.getColumnAsVariables(headings[0])
headers = headings[1:]
numCols = len(headers)
numRows = len(labelCol)
out = []
for col in range(numCols):
out.append([])
column = RT.getColumnAsVariables(headers[col])
for row in range(numRows):
out[col].append(column[row].getValue())
outT = []
for i in range(numRows):
lis = []
lis.append(labelCol[i].getString())
for j in range(numCols):
lis.append(out[j][i])
outT.append(lis)
return outT
except:
print("failed roi read")
return []
def relabel():
import re
from ij.measure import ResultsTable
rt = ResultsTable.getResultsTable()
nResults = rt.size()
for result in range(nResults):
oldLabel = rt.getLabel(result)
delimiters = []
keywords = ["series"]
for keyword in keywords:
if keyword in oldLabel:
delimiters.append(oldLabel.index(keyword))
channel = oldLabel[0:2]
try:
series = "FOV" + oldLabel[(delimiters[0] + 7):(delimiters[0] + 9)]
except IndexError:
series = "FOV?"
foundColons = [m.start() for m in re.finditer(':', oldLabel)]
cell = oldLabel[foundColons[0] + 1:foundColons[1]]
newLabel = channel + "_" + series + "_" + cell
rt.setLabel(newLabel, result)
rt.show("Results")
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 opencsv(self, name):
# Return if the csv object was not set.
# if self.trackscsv == None: return None TODO: some errorchecking for false csv input.
# Open the csv file and return it as ResultsTable object.
try:
csv = IJ.getFilePath("Choose the {} file".format(name))
if csv.endswith(".csv"):
rt = ResultsTable.open(csv)
else:
IJ.log("{} was not a .csv file".format(csv))
raise ValueError
columns = rt.getHeadings()
table = [{column: rt.getValue(column, row)
for column in columns} for row in range(rt.size())]
if rt.columnExists("Label"):
for i in range(len(table)):
table[i]["Label"] = rt.getStringValue("Label", i)
IJ.log("Read {} rows in {}.".format(len(table), name))
return table
except Exception as ex:
IJ.log("Something in opencsv() went wrong: {}".format(
type(ex).__name__, ex.args))
def make_nucs(hseg):
"""given an hseg, assumed to have a nuc_bin_imp, creates the nuc"""
rm = RoiManager.getRoiManager()
rm.reset()
if UPDATE1:
IJ.run(hseg.nuc_bin_imp, "Invert", "")
rt = ResultsTable.getResultsTable()
rt.reset()
IJ.run(hseg.nuc_bin_imp, "Analyze Particles...", "add")
rois = rm.getRoisAsArray()
problem_nucs = []
for roi in rois:
nuc_cent = roi_cent(roi, integer=True)
found_cell = False
for cell in hseg.cells.values():
if cell.roi.contains(*nuc_cent):
cell.add_nuc(roi)
found_cell = True
break
if not found_cell:
IJ.log('Nuc not in any cell for hemisegment {}'.format(hseg.name))
problem_nucs.append(roi)
return problem_nucs
def getTable():
''' Check if a table exists otherwise open a new one'''
## Check if we can get a table window
if IJ.getFullVersion() >= "1.53g":
# try to get any active table
tableWindow = WindowManager.getActiveTable(
) # this function requires 1.53g (or at least not working with 1.53c), return None if no table
else:
# Fallback on fetching either a window called Annotations or Annotations.csv as in previous plugin version
win = WindowManager.getWindow("Annotations")
win2 = WindowManager.getWindow(
"Annotations.csv") # upon saving it adds this extension
if win:
tableWindow = win
elif win2:
tableWindow = win2
else:
tableWindow = None
## If a table window then get its table, otherwise new table. In this case, its name is set later
return tableWindow.getResultsTable() if tableWindow else ResultsTable()
def main():
features = ["Area"]
numberOfClusters = 2
features, numberOfClusters = getArguments(features, numberOfClusters)
rt = RT.getResultsTable()
if (rt.size() < 2):
exit("No data found")
attributes = featuresToAttributes(features)
data = readDataFromResultsTable(attributes, rt)
clusterer = createClusterer(numberOfClusters)
clusterer.buildClusterer(data)
(mu1, sig1, mu2, sig2, prior1,
prior2) = getClusterInformationFrom(clusterer)
threshold = intersection(mu2, sig2, mu1, sig1)
print(clusterer.toString())
print "intersection at: ", threshold
if (mu1 > mu2):
mu1, sig1, mu2, sig2, prior1, prior2 = mu2, sig2, mu1, sig1, prior2, prior1
writeToTable(mu1, sig1, prior1, mu2, sig2, prior2, threshold)
def getColumnIndex(column):
rt = ResultsTable.getResultsTable()
headings = rt.getHeadings()
for i, heading in enumerate(headings, start=1):
if heading == column:
return i
return None
def create_nucs(self) :
""" """
for cell in self.cells() :
cell._nucs = []
rm = RoiManager.getRoiManager()
rm.reset()
IJ.run(self.nuc_bin(), "Invert", "")
rt = ResultsTable.getResultsTable()
rt.reset()
IJ.run(self.nuc_bin(), "Analyze Particles...", "add")
rois = rm.getRoisAsArray()
IJ.run(self.nuc_bin(),"Remove Overlay", "");
problem_nucs = []
for roi in rois :
nuc_cent = futils.roi_cent(roi, integer=True)
found_cell = False
for cell in self.cells() :
if cell.roi().contains(*nuc_cent) :
cell.add_nuc(roi)
found_cell = True
break
if not found_cell :
self.exper.log('Nuc not in any cell for hemisegment {}'.format(self.name))
problem_nucs.append(roi)
return problem_nucs
def nuclei_processor(imp_particles, thresh_type, folder, impname,
channel_name):
rm = RoiManager.getInstance()
if not rm:
rm = RoiManager()
rm.reset()
# define a results table
rt = ResultsTable.getResultsTable()
imp_particles.show()
# generate thresholded image for ROI
nuclei = imp_particles.duplicate()
nuclei.show()
IJ.run("Gaussian Blur...", "sigma=3")
IJ.setAutoThreshold(nuclei, thresh_type)
IJ.run("Convert to Mask")
IJ.run("Fill Holes")
# IJ.run("Watershed")
# select thresholded image (to set ROIs)
IJ.run(
"Set Measurements...",
"area mean standard min area_fraction limit display add redirect=[" +
imp_particles.title + "] decimal=3")
IJ.run("Analyze Particles...",
"size=30-Infinity show=Outlines display clear add")
# get the ROI manager and save
rm.runCommand(
"save selected",
os.path.join(folder, impname + '_' + channel_name + "_ROIs.zip"))
def linkSpots():
rt = ResultsTable.getResultsTable()
X = rt.getColumn(ResultsTable.X_CENTROID)
Y = rt.getColumn(ResultsTable.Y_CENTROID)
D = rt.getColumn(ResultsTable.FERET)
SLICE = rt.getColumn(ResultsTable.SLICE)
spotsByScale = getRoisBySlice(SLICE)
print(spotsByScale)
## set objects of spots i scale 1 to the id of the spot
spots = spotsByScale[1]
for spot in spots:
spot['object']=spot['id']
for s in range(2, len(spotsByScale)+1):
spots = spotsByScale[s]
for spot in spots:
spot['object']=spot['id'] # initially set the object to which the spot belong to the spot id
spotsLastScale = spotsByScale[s-1]
minDist = float("inf")
minObject = None
for spotLastScale in spotsLastScale:
# for each spot on the next scale
deltaX = X[spotLastScale['id']]-X[spot['id']]
deltaY = Y[spotLastScale['id']]-Y[spot['id']]
dist = math.sqrt((deltaX * deltaX) + (deltaY*deltaY))
print("spot", spot['id'], "spot s-1", spotLastScale['id'], dist)
if (dist<(D[spot['id']])/2.0):
if (dist<minDist):
minDist = dist
minObject = spotLastScale['object']
print('hit', minDist, minObject)
if minObject is not None:
spot['object'] = minObject
print("minObject", minObject)
return spotsByScale
def run_comdet(image):
IJ.run(
image, "Detect Particles",
" two=[Detect in both channels independently] ch1a=" + str(ch1size) +
" ch1s=" + str(ch1thresh) + " ch2a=" + str(ch2size) + " ch2s=" +
str(ch2thresh) + " calculate max=" + str(coloc) + " add=Nothing")
rt = ResultsTable.getResultsTable()
return rt
def intensity_measure_3D(imp_intens, imp_label): imp_intens.show() imp_label.show() IJ.run(imp_intens, "3D Intensity Measure", "objects=[%s] signal=[%s]" % (imp_label.getTitle(), imp_intens.getTitle()) ); imp_intens.hide() imp_label.hide() rt = ResultsTable.getResultsTable() return rt
def intensity_measure_3D(imp_intens, imp_label): imp_intens.show() imp_label.show() IJ.run(imp_intens, "3D Intensity Measure", "objects=[%s] signal=[%s]" % (imp_label.getTitle(), imp_intens.getTitle()) ); imp_intens.hide() imp_label.hide() rt = ResultsTable.getResultsTable() return rt
def analyzeImage(passImage, passModel, passChannel, passProbability,
passPixels, passOutput):
retResults = list()
windows = set()
# Register current window
registerWindow(passImage.title, windows)
# Extract the requested channel
IJ.run("Z Project...", "projection=[Max Intensity]")
registerWindow("MAX_" + passImage.title, windows)
IJ.run("Duplicate...", "title=temp")
registerWindow("temp", windows)
# Apply WEKA training model to image
wekaSeg = WekaSegmentation(WindowManager.getCurrentImage())
wekaSeg.loadClassifier(passModel)
wekaSeg.applyClassifier(True)
# Extract first slice of probability map
wekaImg = wekaSeg.getClassifiedImage()
wekaImg.show()
registerWindow("Probability maps", windows)
IJ.setSlice(1)
IJ.run("Duplicate...", "title=temp2")
registerWindow("temp2", windows)
# Apply threshold and save
IJ.setThreshold(passProbability, 1, "Black & White")
fileParts = passImage.getTitle().split(".")
IJ.save(
os.path.join(
passOutput, "{0}-probmap.png".format(fileParts[0],
'.'.join(fileParts[1:]))))
# Perform particle analysis and save
IJ.run("Analyze Particles...",
"size={0}-Infinity show=Outlines pixel clear".format(passPixels))
registerWindow("Drawing of temp2", windows)
IJ.save(
os.path.join(
passOutput, "{0}-particles.png".format(fileParts[0],
'.'.join(fileParts[1:]))))
# Get measurements
tableResults = ResultsTable.getResultsTable()
for rowIdx in range(tableResults.size()):
retResults.append(tableResults.getRowAsString(rowIdx).split())
retResults[-1].insert(
0,
WindowManager.getCurrentImage().getCalibration().unit)
retResults[-1].append(
float(retResults[-1][4]) / float(retResults[-1][3]))
# Close windows
closeWindows(windows)
return retResults
def auto_resize_angle_measure(img, two_sarcomere_size):
"""Resizes and measures angle of offset for img based on T-tubules."""
# Run Fast Fourier Transform on Image to get Power Spectral Density
IJ.run(img, "FFT", "")
# Select PSD image.
fft_title = "FFT of " + img.getTitle()
fft_img = WindowManager.getImage(fft_title)
# Threshold the image and create binary mask.
IJ.setThreshold(151, 255)
#IJ.setThreshold(135, 255)
IJ.run(fft_img, "Convert to Mask", "")
# Set measurements for fitting an ellipse and fit them to data.
IJ.run(fft_img, "Set Measurements...",
"area centroid fit redirect=None decimal=2")
if dev_options:
args = "size=10-Infinity show=Ellipses display"
else:
args = "size=10-Inifinity"
IJ.run(fft_img, "Analyze Particles...", args)
results = ResultsTable.getResultsTable()
angle_column = results.getColumnIndex("Angle")
area_column = results.getColumnIndex("Area")
centroid_x_column = results.getColumnIndex("X")
centroid_y_column = results.getColumnIndex("Y")
# Sort by area since we need the largest two ellipses.
results.sort("Area")
# Grab info for the largest two ellipses.
areas = results.getColumnAsDoubles(area_column)
angles = results.getColumnAsDoubles(angle_column)
c_xs = results.getColumnAsDoubles(centroid_x_column)
c_ys = results.getColumnAsDoubles(centroid_y_column)
# Calculate offset angle from main ellipse.
rotation_angle = angles[-1] - 90.
# Measure distance between centroids of two largest ellipses using distance measurement tool to get spatial frequency of T-tubules.
# Note: This needs to be in pixels since the filter size is in pixels.
c_x_0 = c_xs[-1]
c_y_0 = c_ys[-1]
c_x_1 = c_xs[-2]
c_y_1 = c_ys[-2]
dist_gap = ((c_x_0 - c_x_1)**2 + (c_y_0 - c_y_1)**2)**0.5
old_two_sarcomere_size = 2 * fft_img.getDimensions()[0] / dist_gap
# Resize based on measured two sarcomere size
resize_ratio = float(two_sarcomere_size) / float(old_two_sarcomere_size)
old_width = img.width
old_height = img.height
new_width = resize_ratio * old_width
new_height = resize_ratio * old_height
resize_args = "width={} height={} depth=1 constrain average interpolation=Bicubic".format(
new_width, new_height)
IJ.run(img, "Size...", resize_args)
return rotation_angle
def show_as_table(title, data, order=[]):
"""Helper function to display group and data information as a ResultsTable"""
table = ResultsTable()
for d in data:
table.incrementCounter()
order = [k for k in order]
order.extend([k for k in d.keys() if not d in order])
for k in order:
table.addValue(k, d[k])
table.show(title)
def getColumn(aC):
rt = ResultsTable.getResultsTable()
anIndex = getColumnIndex(aC)
column = []
for i in range(0, rt.size()):
columns = rt.getRowAsString(i).split('\t')
v = float(columns[anIndex])
column.append(v)
return column
def analyzeParticles(imp, minsize, maxsize, mincirc, maxcirc,
filename='Test.czi',
addROIManager=True,
headless=True,
exclude=True):
if addROIManager is True:
if exclude is False:
options = PA.SHOW_ROI_MASKS \
+ PA.SHOW_RESULTS \
+ PA.DISPLAY_SUMMARY \
+ PA.ADD_TO_MANAGER \
+ PA.ADD_TO_OVERLAY \
if exclude is True:
options = PA.SHOW_ROI_MASKS \
+ PA.SHOW_RESULTS \
+ PA.DISPLAY_SUMMARY \
+ PA.ADD_TO_MANAGER \
+ PA.ADD_TO_OVERLAY \
+ PA.EXCLUDE_EDGE_PARTICLES
if addROIManager is False:
if exclude is False:
options = PA.SHOW_ROI_MASKS \
+ PA.SHOW_RESULTS \
+ PA.DISPLAY_SUMMARY \
+ PA.ADD_TO_OVERLAY \
if exclude is True:
options = PA.SHOW_ROI_MASKS \
+ PA.SHOW_RESULTS \
+ PA.DISPLAY_SUMMARY \
+ PA.ADD_TO_OVERLAY \
+ PA.EXCLUDE_EDGE_PARTICLES
measurements = PA.STACK_POSITION \
+ PA.LABELS \
+ PA.AREA \
+ PA.RECT \
results = ResultsTable()
p = PA(options, measurements, results, minsize, maxsize, mincirc, maxcirc)
p.setHideOutputImage(True)
particlestack = ImageStack(imp.getWidth(), imp.getHeight())
for i in range(imp.getStackSize()):
imp.setSliceWithoutUpdate(i + 1)
ip = imp.getProcessor()
#IJ.run(imp, "Convert to Mask", "")
p.analyze(imp, ip)
mmap = p.getOutputImage()
particlestack.addSlice(mmap.getProcessor())
return particlestack, results
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 __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 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 analyse(imp, root, filename, thresholds):
closeAllImageWindows()
imp.show()
print ""
print(imp.getTitle())
print "**********************************"
IJ.run("Set Measurements...", "integrated redirect=None decimal=2");
# get image calibration info
IJ.run(imp, "Properties...", "unit=pixel pixel_width=1 pixel_height=1");
# convert to 8-bit
IJ.setMinAndMax(imp, 0, 65535);
IJ.run(imp, "8-bit", "");
thresholds = [(x / 65535 * 255) for x in thresholds]
# Nuclei
#closeAllNoneImageWindows()
iChannel = 1
imp.setSlice(iChannel)
IJ.run(imp, "Gaussian Blur...", "sigma=2 slice");
IJ.setThreshold(imp, thresholds[iChannel-1], 1000000000)
IJ.run(imp, "Convert to Mask", "method=Default background=Dark only black");
IJ.run(imp, "Measure", "");
rt = ResultsTable.getResultsTable()
values = rt.getColumnAsDoubles(rt.getColumnIndex("RawIntDen"))
print("Area Nuclei (pixel^2) =",values[-1]/255)
# Dots
#closeAllNoneImageWindows()
iChannel = 3
imp.setSlice(iChannel)
IJ.run(imp, "Gaussian Blur...", "sigma=1 slice");
IJ.run(imp, "Find Maxima...", "noise="+str(thresholds[iChannel-1])+" output=Count");
rt = ResultsTable.getResultsTable()
values = rt.getColumnAsDoubles(rt.getColumnIndex("Count"))
print("Number of Dots =",values[-1])
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")
def anaParticles(imp, minSize, maxSize, minCirc):
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
strSetMeas = "area mean modal min center perimeter bounding fit shape feret's 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 run():
srcDir = srcFile.getAbsolutePath()
IJ.run("Set Measurements...", "integrated limit redirect=None decimal=3")
for dirName, subdirs, filenames in os.walk(srcDir):
if len(subdirs)==0:
finalResults = []
for filename in filenames:
# Check for file extension
if not filename.endswith(ext):
continue
process(srcDir, dirName, filename)
rt = ResultsTable.getResultsTable()
colRaw = rt.getColumnIndex("IntDen")
colRatio = rt.getColumnIndex("RawIntDen")
finalResults.append(rt.getColumn(colRaw))
finalResults.append(rt.getColumn(colRatio))
with open(os.path.join(dirName, dirName+'.csv'), 'wb') as csvfile:
writer = csv.writer(csvfile, delimiter=",")
for row in zip(*finalResults):
writer.writerow(row)
def process(srcDir, currentDir, fileName):
image = IJ.openImage(os.path.join(currentDir, fileName))
IJ.run("Clear Results")
#set lowerbound threshold here
IJ.setThreshold(image, 200, 10000)
# Change (1,25) below to (1,n+1) where n is the number of frames
for slice in range(1,(image.getNSlices()+1),1):
image.setSlice(slice)
IJ.run(image, "Select All", "")
IJ.run(image, "Measure", "")
rt = ResultsTable.getResultsTable()
# this line calculates the baseline
baseline = (rt.getValue("IntDen",1) + rt.getValue("IntDen",2) + rt.getValue("IntDen",3))/3.0
for result in range(0,rt.getCounter()):
cur_intensity = rt.getValue("IntDen",result)
ratio = cur_intensity/baseline
rt.setValue("RawIntDen",result,ratio)
rt.updateResults()
image.close()
options = "radius=%d cutoff=%d percentile=%f" % (radius, cutoff, percentile)
thread = thr.currentThread()
original_name = thread.getName()
thread.setName("Run$_my_batch_process")
Macro.setOptions(thr.currentThread(), options)
pt = IJ.runPlugIn(imp, "de.embl.cmci.pt3d.Dot_Detector_3D", "")
impdimA = imp.getDimensions()
ims = imp.createEmptyStack()
for i in range(impdimA[3]):
ims.addSlice(None, ByteProcessor(impdimA[0], impdimA[1]))
imp2 = ImagePlus("test", ims)
nSlices = imp2.getNSlices()
rt = ResultsTable.getResultsTable()
xindex = rt.getColumnIndex("x")
yindex = rt.getColumnIndex("y")
zindex = rt.getColumnIndex("z")
xA = rt.getColumn(xindex)
yA = rt.getColumn(yindex)
zA = rt.getColumn(zindex)
neighbornumA = NeighborChecker(xA, yA, zA, True)
for i in range(len(xA)):
print xA[i], yA[i], zA[i], " .. Neighbor", neighbornumA[i]
# if xA[i] > 0:
if neighbornumA[i] == 0:
cslice=Math.round(zA[i])+1
if cslice > 0 and cslice <= nSlices:
from ij import IJ
from ij.measure import ResultsTable
# Get current ImagePlus
image = IJ.getImage()
IJ.run("Clear Results")
IJ.setThreshold(200, 10000)
for slice in range(1,image.getNSlices()+1,1):
image.setSlice(slice)
IJ.run("Select All")
IJ.run("Measure")
rt = ResultsTable.getResultsTable()
baseline = (rt.getValue("IntDen",0) + rt.getValue("IntDen",1) + rt.getValue("IntDen",2) + rt.getValue("IntDen",3))/4.0
for result in range(0,rt.getCounter()):
cur_intensity = rt.getValue("IntDen",result)
ratio = cur_intensity/baseline
rt.setValue("RawIntDen",result,ratio)
rt.updateResults()
binorg = binimp.duplicate()
if VERBOSE:
binorg.show()
# Count nucleus setting
MAXSIZE = imp3.getWidth()*imp3.getHeight();
MINSIZE = 100;
#options = PA.SHOW_ROI_MASKS \
# + PA.EXCLUDE_EDGE_PARTICLES \
# + PA.INCLUDE_HOLES \
# + PA.SHOW_RESULTS \
options = PA.INCLUDE_HOLES \
+ PA.CLEAR_WORKSHEET \
# + PA.SHOW_RESULTS \
rt = ResultsTable()
p = PA(options, PA.AREA + PA.STACK_POSITION, rt, MINSIZE, MAXSIZE)
p.setHideOutputImage(True)
# Morphological dilate
binner.setup('dilate', None)
clusters = 0
initialCells = 0
# dilate by 'SAMPLEITER'
for i in range(SAMPLEITER+1):
p.analyze(binimp)
cellcounts = rt.getCounter()
if i == 0:
def process(self,imp):
# extract nucleus channel, 8-bit and twice binned
imp.setC(self.nucleusChannel)
ip = imp.getChannelProcessor().duplicate()
ip = ip.convertToByteProcessor()
ip = ip.bin(4)
nucleus = ImagePlus("nucleus_channel", ip)
# threshold image and separate clumped nuclei
IJ.run(nucleus, "Auto Threshold", "method=Otsu white setthreshold show");
IJ.run(nucleus, "Make Binary", "thresholded remaining black");
IJ.run(nucleus, "Watershed", "");
directory = imp.getTitle()
directory = directory.replace(" ", "_")\
.replace(",", "_")\
.replace("#", "_series")\
.replace("...", "")\
.replace(".","_")
directory = os.path.join(self.exportDir, directory)
sliceDirectory = os.path.join(directory, "slices")
print directory
print sliceDirectory
if not os.path.exists(sliceDirectory):
os.makedirs(sliceDirectory)
# Create a table to store the results
table = ResultsTable()
# Create a hidden ROI manager, to store a ROI for each blob or cell
#roim = RoiManager(True)
# remove small particles and border particles
pa = ParticleAnalyzer(\
ParticleAnalyzer.ADD_TO_MANAGER | ParticleAnalyzer.EXCLUDE_EDGE_PARTICLES,\
Measurements.CENTER_OF_MASS,\
table,\
self.minArea, self.maxArea,\
0.0,1.0)
if pa.analyze(nucleus):
print "All ok, number of particles: ", table.size()
else:
print "There was a problem in analyzing", imp, nucleus
table.save(os.path.join(directory, "rt.csv"))
# read the center of mass coordinates
cmx = table.getColumn(0)
cmy = table.getColumn(1)
if self.debug:
imp.show()
i=0
for i in range(0, min(self.nCells,table.size())):
# ROI around the cell
cmx = table.getValue("XM",i)
cmy = table.getValue("YM",i)
x = 4 * cmx - (self.boxSize - 1) / 2
y = 4 * cmy - (self.boxSize - 1) / 2
if (x < self.edge or y < self.edge or x > imp.getWidth() - self.edge or y > imp.getHeight() - self.edge):
continue
roi = Roi(x,y,self.boxSize,self.boxSize)
imp.setRoi(roi, False)
cellStack = ImageStack(self.boxSize, self.boxSize)
for z in range(1, imp.getNSlices() + 1):
imp.setSlice(z)
for c in range(1, imp.getNChannels() + 1):
imp.setC(c)
# copy ROI to stack
imp.copy()
impSlice = imp.getClipboard()
cellStack.addSlice(impSlice.getProcessor())
if self.slices:
sliceTitle = "cell_%s_z%s_c%s" % (str(i).zfill(4), str(z).zfill(3), str(c))
print sliceTitle
IJ.saveAsTiff(impSlice, os.path.join(sliceDirectory, sliceTitle))
impSlice.close()
title = "cell_" + str(i).zfill(4)
cell = ImagePlus(title, cellStack)
# save ROI image
IJ.saveAsTiff(cell, os.path.join(directory, title))
cell.close()
if self.debug:
imp.updateAndDraw()
wait = Wait("particle done")
wait.show()
def updatepressed(event):
self.__image=IJ.getImage()
rm = RoiManager.getInstance()
if (rm==None): rm = RoiManager()
rm.runCommand("reset")
self.__image.killRoi()
IJ.run("Threshold...")
IJ.setAutoThreshold(self.__image, "MaxEntropy")
rt=ResultsTable()
pa=ParticleAnalyzer(ParticleAnalyzer.ADD_TO_MANAGER+ParticleAnalyzer.CLEAR_WORKSHEET , Measurements.AREA+Measurements.ELLIPSE+Measurements.MEAN, rt, 0.00, 10000.00, 0.00, 1.00)
pa.analyze(self.__image)
self.__roisArray=[]
self.__roisArray=rm.getRoisAsArray()
#for i in range(rm.getCount()) :
# rm.select(i)
# rm.runCommand("Set Color", "0000FF", 2)
IJ.resetThreshold(self.__image)
rt.show("tempRT")
areas=rt.getColumn(ResultsTable.AREA)
means=rt.getColumn(ResultsTable.MEAN)
majors=rt.getColumn(ResultsTable.MAJOR)
minors=rt.getColumn(ResultsTable.MINOR)
#print 0
if self.__slidersDict["Area_max"].getMaximum() < int(max(areas)+1):
# print 1
self.__slidersDict["Area_max"].setMaximum(int(max(areas))+1)
if self.__slidersDict["Area_min"].getMaximum() < int(max(areas)+1):
# print 2
self.__slidersDict["Area_min"].setMaximum(int(max(areas))+1)
if self.__slidersDict["Mean_max"].getMaximum() < int(max(means)+1):
# print 3
self.__slidersDict["Mean_max"].setMaximum(int(max(means))+1)
if self.__slidersDict["Mean_min"].getMaximum() < int(max(means)+1):
# print 4
self.__slidersDict["Mean_min"].setMaximum(int(max(means))+1)
if self.__slidersDict["Major_max"].getMaximum() < int(max(majors)):
# print 5
self.__slidersDict["Major_max"].setMaximum(int(max(majors))+1)
if self.__slidersDict["Major_min"].getMaximum() < int(max(majors)+1):
# print 6
self.__slidersDict["Major_min"].setMaximum(int(max(majors))+1)
if self.__slidersDict["Minor_max"].getMaximum() < int(max(minors)+1):
# print 7
self.__slidersDict["Minor_max"].setMaximum(int(max(minors))+1)
if self.__slidersDict["Minor_min"].getMaximum() < int(max(minors)+1):
# print 8
self.__slidersDict["Minor_min"].setMaximum(int(max(minors))+1)
if self.__slidersDict["AR_max"].getMaximum() < int((max(majors)+1)/min(minors)+1):
# print 9
self.__slidersDict["AR_max"].setMaximum(int((max(majors)+1)/(min(minors))))
if self.__slidersDict["AR_min"].getMaximum() < int((max(majors)+1)/min(minors)):
# print 10
self.__slidersDict["AR_min"].setMaximum(int((max(majors)+1)/(min(minors))))
#print 11
for sb in self.__slidersDict.values():
sb.repaint()
#rm.runCommand("reset")
#temprois=self.getIncludeRois()
#IJ.run(self.__image, "Remove Overlay", "")
#o=Overlay()
#for roi in temprois:
# o.addElement(roi)
#self.__image.killRoi()
#self.__image.setOverlay(o)
self.__image.updateAndDraw()
class MandersPlugin(ImageListener, WindowAdapter):
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 selectInputDir(self):
inputDialog = DirectoryChooser("Please select a directory contaning your images")
inputDir = inputDialog.getDirectory()
for imageFile in os.listdir(inputDir):
self.files.append(inputDir + imageFile)
def selectOutputDir(self):
outputDialog = DirectoryChooser("Please select a directory to save your results")
self.outputDir = outputDialog.getDirectory()
def closeImage(self):
if self.imp is not None:
self.imp.close()
self.imp = None
if self.preview is not None:
self.preview.close()
self.preview = None
def openImage(self, imageFile):
try:
images = BF.openImagePlus(imageFile)
self.imp = images[0]
except UnknownFormatException:
return None
if self.imp.getNChannels() < 2:
IJ.error("Bad image format", "Image must contain at lease 2 channels!")
return None
if not self.pairs or \
not self.methods:
self.getOptionsDialog(self.imp)
title = self.imp.title
self.imp.title = title[:title.rfind('.')]
return self.imp
def getOptionsDialog(self, imp):
thr_methods = ["None", "Default", "Huang", "Intermodes", "IsoData", "Li", "MaxEntropy","Mean", "MinError(I)", "Minimum", "Moments", "Otsu", "Percentile", "RenyiEntropy", "Shanbhag" , "Triangle", "Yen"]
gd = GenericDialog("Please select channels to collocalize")
for i in range(1, imp.getNChannels() + 1):
gd.addChoice("Threshold method for channel %i" % i, thr_methods, "None")
gd.showDialog()
if gd.wasCanceled():
self.exit()
channels = []
for i in range(1, imp.getNChannels() + 1):
method = gd.getNextChoice()
self.methods.append(method)
if method != "None":
channels.append(i)
for x in channels:
for y in channels:
if x < y:
self.pairs.append((x, y))
def processNextFile(self):
if self.files:
imageFile = self.files.pop(0)
return self.processFile(imageFile)
else:
return False
def processFile(self, imageFile):
imp = self.openImage(imageFile)
if imp is not None:
cell = Cell(imp.NSlices, 1)
self.cells = DelegateListModel([])
self.cells.append(cell)
self.showMainWindow(self.cells)
if self.checkbox3D.isSelected():
self.displayImage(imp)
else:
self.displayImage(imp, False)
self.preview = self.previewImage(imp)
self.displayImage(self.preview)
return True
else:
return self.processNextFile()
def displayImage(self, imp, show = True):
imp.setDisplayMode(IJ.COMPOSITE)
enhancer = ContrastEnhancer()
enhancer.setUseStackHistogram(True)
splitter = ChannelSplitter()
for c in range(1, imp.getNChannels() + 1):
imp.c = c
enhancer.stretchHistogram(imp, 0.35)
if show:
imp.show()
def previewImage(self, imp):
roi = imp.getRoi()
splitter = ChannelSplitter()
channels = []
for c in range(1, imp.getNChannels() + 1):
channel = ImagePlus("Channel %i" % c, splitter.getChannel(imp, c))
projector = ZProjector(channel)
projector.setMethod(ZProjector.MAX_METHOD)
projector.doProjection()
channels.append(projector.getProjection())
image = RGBStackMerge.mergeChannels(channels, False)
image.title = imp.title + " MAX Intensity"
image.luts = imp.luts
imp.setRoi(roi)
return image
def getCroppedChannels(self, imp, cell):
splitter = ChannelSplitter()
imp.setRoi(None)
if cell.mode3D:
cropRoi = cell.getCropRoi()
else:
cropRoi = cell.roi
if cropRoi is None:
return None
crop = cropRoi.getBounds()
channels = []
for c in range(1, imp.getNChannels() + 1):
slices = ImageStack(crop.width, crop.height)
channel = splitter.getChannel(imp, c)
for z in range(1, channel.getSize() + 1):
zslice = channel.getProcessor(z)
zslice.setRoi(cropRoi)
nslice = zslice.crop()
if cell.mode3D:
oroi = cell.slices[z - 1].roi
else:
oroi = cell.roi
if oroi is not None:
roi = oroi.clone()
bounds = roi.getBounds()
roi.setLocation(bounds.x - crop.x, bounds.y - crop.y)
nslice.setColor(Color.black)
nslice.fillOutside(roi)
slices.addSlice(nslice)
channels.append(ImagePlus("Channel %i" % c, slices))
return channels
def getThreshold(self, imp, method):
thresholder = Auto_Threshold()
duplicator = Duplicator()
tmp = duplicator.run(imp)
return thresholder.exec(tmp, method, False, False, True, False, False, True)
def getContainer(self, impA, impB):
imgA = ImagePlusAdapter.wrap(impA)
imgB = ImagePlusAdapter.wrap(impB)
return DataContainer(imgA, imgB, 1, 1, "imageA", "imageB")
def getManders(self, imp, cell):
### Crop channels according to cell mask
channels = self.getCroppedChannels(imp, cell)
if channels is None:
return None
### Calculate channel thresholds
thrs = []
thrimps = []
for c, method in enumerate(self.methods):
if method != "None":
thr, thrimp = self.getThreshold(channels[c], method)
else:
thr, thrimp = None, None
thrs.append(thr)
thrimps.append(thrimp)
### Calculate manders colocalization
manders = MandersColocalization()
raws = []
thrds = []
for chA, chB in self.pairs:
container = self.getContainer(channels[chA - 1], channels[chB - 1])
img1 = container.getSourceImage1()
img2 = container.getSourceImage2()
mask = container.getMask()
cursor = TwinCursor(img1.randomAccess(), img2.randomAccess(), Views.iterable(mask).localizingCursor())
rtype = img1.randomAccess().get().createVariable()
raw = manders.calculateMandersCorrelation(cursor, rtype)
rthr1 = rtype.copy()
rthr2 = rtype.copy()
rthr1.set(thrs[chA - 1])
rthr2.set(thrs[chB - 1])
cursor.reset()
thrd = manders.calculateMandersCorrelation(cursor, rthr1, rthr2, ThresholdMode.Above)
raws.append(raw)
thrds.append(thrd)
return (channels, thrimps, thrs, raws, thrds)
def saveMultichannelImage(self, title, channels, luts):
tmp = RGBStackMerge.mergeChannels(channels, False)
tmp.luts = luts
saver = FileSaver(tmp)
saver.saveAsTiffStack(self.outputDir + title + ".tif")
tmp.close()
def createMainWindow(self):
self.frame = JFrame('Select cells and ROIs',
defaultCloseOperation = JFrame.DISPOSE_ON_CLOSE
)
self.frame.setLayout(GridBagLayout())
self.frame.addWindowListener(self)
self.frame.add(JLabel("Cells"),
GridBagConstraints(0, 0, 1, 1, 0, 0,
GridBagConstraints.CENTER, GridBagConstraints.NONE,
Insets(5, 2, 2, 0), 0, 0
))
self.cellList = JList(DelegateListModel([]),
selectionMode = ListSelectionModel.SINGLE_SELECTION,
cellRenderer = MyRenderer(),
selectedIndex = 0,
valueChanged = self.selectCell
)
self.frame.add(JScrollPane(self.cellList),
GridBagConstraints(0, 1, 1, 5, .5, 1,
GridBagConstraints.CENTER, GridBagConstraints.BOTH,
Insets(0, 2, 2, 0), 0, 0
))
self.frame.add(JButton('Add cell', actionPerformed = self.addCell),
GridBagConstraints(1, 2, 1, 2, 0, .25,
GridBagConstraints.CENTER, GridBagConstraints.NONE,
Insets(0, 0, 0, 0), 0, 0
))
self.frame.add(JButton('Remove cell', actionPerformed = self.removeCell),
GridBagConstraints(1, 4, 1, 2, 0, .25,
GridBagConstraints.CENTER, GridBagConstraints.NONE,
Insets(0, 5, 0, 5), 0, 0
))
self.frame.add(JLabel("Slices"),
GridBagConstraints(0, 6, 1, 1, 0, 0,
GridBagConstraints.CENTER, GridBagConstraints.NONE,
Insets(5, 2, 2, 0), 0, 0
))
self.sliceList = JList(DelegateListModel([]),
selectionMode = ListSelectionModel.SINGLE_SELECTION,
cellRenderer = MyRenderer(),
selectedIndex = 0,
valueChanged = self.selectSlice
)
self.frame.add(JScrollPane(self.sliceList),
GridBagConstraints(0, 7, 1, 5, .5, 1,
GridBagConstraints.CENTER, GridBagConstraints.BOTH,
Insets(0, 2, 2, 0), 0, 0
))
self.frame.add(JButton('Update ROI', actionPerformed = self.updateSlice),
GridBagConstraints(1, 8, 1, 2, 0, .25,
GridBagConstraints.CENTER, GridBagConstraints.NONE,
Insets(0, 0, 0, 0), 0, 0
))
self.frame.add(JButton('Done', actionPerformed = self.doneSelecting),
GridBagConstraints(1, 10, 1, 2, 0, .25,
GridBagConstraints.CENTER, GridBagConstraints.NONE,
Insets(0, 0, 0, 0), 0, 0
))
self.checkbox3D = JCheckBox('3D selection mode', True, actionPerformed=self.toggle3D)
self.frame.add(self.checkbox3D,
GridBagConstraints(0, 13, 2, 1, 0, 1,
GridBagConstraints.WEST, GridBagConstraints.NONE,
Insets(0, 0, 0, 0), 0, 0
))
def showMainWindow(self, cells = None):
if cells is not None:
self.cellList.model = cells
if cells:
self.cellList.selectedIndex = 0
self.frame.pack()
self.frame.visible = True
def hideMainWindow(self):
self.frame.visible = False
def closeMainWindow(self):
self.frame.dispose()
def toggle3D(self, event):
mode3D = self.checkbox3D.isSelected()
if mode3D:
self.sliceList.enabled = True
if self.imp is not None:
self.imp.show()
if self.preview is not None:
self.preview.hide()
else:
self.sliceList.enabled = False
if self.preview is None:
self.preview = self.previewImage(self.imp)
self.displayImage(self.preview)
else:
self.preview.show()
if self.imp is not None:
self.imp.hide()
selectedCell = self.cellList.selectedIndex
if selectedCell >= 0:
cell = self.cells[selectedCell]
self.sliceList.model = cell.slices
self.sliceList.selectedIndex = 0
def addCell(self, event):
size = len(self.cells)
if (size > 0):
last = self.cells[size - 1]
n = last.n + 1
else:
n = 1
self.cells.append(Cell(self.imp.NSlices, n))
self.cellList.selectedIndex = size
def removeCell(self, event):
selected = self.cellList.selectedIndex
if selected >= 0:
self.cells.remove(self.cells[selected])
if (selected >= 1):
self.cellList.selectedIndex = selected - 1
else:
self.cellList.selectedIndex = 0
def selectCell(self, event):
selected = self.cellList.selectedIndex
if selected >= 0:
cell = self.cells[selected]
self.sliceList.model = cell.slices
self.sliceList.selectedIndex = 0
else:
self.sliceList.model = DelegateListModel([])
if self.preview is not None:
self.preview.setRoi(cell.roi)
def selectSlice(self, event):
selectedCell = self.cellList.selectedIndex
selectedSlice = self.sliceList.selectedIndex
if selectedCell >= 0 and selectedSlice >= 0:
cell = self.cells[selectedCell]
image = self.imp
mode3D = self.checkbox3D.isSelected()
if image is not None and cell is not None and mode3D:
roi = cell.slices[selectedSlice].roi
if (image.z - 1 != selectedSlice):
image.z = selectedSlice + 1
image.setRoi(roi, True)
if self.preview is not None and not mode3D:
self.preview.setRoi(cell.roi, True)
def updateSlice(self, event):
if self.checkbox3D.isSelected():
self.updateSlice3D(self.imp)
else:
self.updateSlice2D(self.preview)
def updateSlice3D(self, imp):
selectedCell = self.cellList.selectedIndex
selectedSlice = self.sliceList.selectedIndex
if selectedCell >= 0 and selectedSlice >= 0 and imp is not None:
cell = self.cells[selectedCell]
impRoi = imp.getRoi()
if cell is not None and impRoi is not None:
index = selectedSlice + 1
roi = ShapeRoi(impRoi, position = index)
cell.mode3D = True
cell.name = "Cell %i (3D)" % cell.n
cell.slices[selectedSlice].roi = roi
if (index + 1 <= len(cell.slices)):
imp.z = index + 1
self.cellList.repaint(self.cellList.getCellBounds(selectedCell, selectedCell))
self.sliceList.repaint(self.sliceList.getCellBounds(selectedSlice, selectedSlice))
def updateSlice2D(self, imp):
selectedCell = self.cellList.selectedIndex
if selectedCell >= 0 and imp is not None:
cell = self.cells[selectedCell]
impRoi = imp.getRoi()
if cell is not None and impRoi is not None:
roi = ShapeRoi(impRoi, position = 1)
cell.mode3D = False
cell.name = "Cell %i (2D)" % cell.n
cell.roi = roi
self.cellList.repaint(self.cellList.getCellBounds(selectedCell, selectedCell))
def imageOpened(self, imp):
pass
def imageClosed(self, imp):
pass
def imageUpdated(self, imp):
if self.checkbox3D.isSelected():
if imp is not None:
selectedCell = self.cellList.selectedIndex
selectedSlice = imp.z - 1
if imp == self.imp and selectedSlice != self.sliceList.selectedIndex:
self.sliceList.selectedIndex = selectedSlice
def doneSelecting(self, event):
oluts = self.imp.luts
luts = []
channels = []
for c, method in enumerate(self.methods):
if method != "None":
luts.append(oluts[c])
channels.append(c)
for cell in self.cells:
manders = self.getManders(self.imp, cell)
if manders is not None:
chimps, thrimps, thrs, raws, thrds = manders
index = self.cells.index(cell) + 1
title = "Cell_%i-" % index + self.imp.title
self.saveMultichannelImage(title, chimps, oluts)
title = "Cell_%i_thrd-" % index + self.imp.title
self.saveMultichannelImage(title, thrimps, luts)
self.results.incrementCounter()
row = self.results.getCounter() - 1
for i, thr in enumerate(thrs):
if thr is not None:
self.results.setValue("Threshold %i" % (i + 1), row, int(thr))
for i, pair in enumerate(self.pairs):
self.results.setValue("%i-%i M1 raw" % pair, row, float(raws[i].m1))
self.results.setValue("%i-%i M2 raw" % pair, row, float(raws[i].m2))
self.results.setValue("%i-%i M1 thrd" % pair, row, float(thrds[i].m1))
self.results.setValue("%i-%i M2 thrd" % pair, row, float(thrds[i].m2))
self.closeImage()
if not self.processNextFile():
print "All done - happy analysis!"
self.results.show("Manders collocalization results")
self.exit()
def windowClosing(self, e):
print "Closing plugin - BYE!!!"
self.exit()
def exit(self):
ImagePlus.removeImageListener(self)
self.closeImage()
self.closeMainWindow()
class Morph(object):
"""
Fourni les mesures principales pour l'analyse des cellules bacteriennes:
proprietes:
1-MaxFeret
2-MinFeret
3-AngleFeret
4-XFeret
5-YFeret
6-Area
7-Mean
8-StdDev
9-IntDen
10-Kurt
11-Skew
12-Angle
13-Major
14-Minor
15-Solidity
16-AR
17-Round
18-Circ.
19-XM
20-YM
21-X
22-Y
23-FerCoord: tuple contenant x1, y1, x2, y2 du MaxFeret
24-Fprofil: list contenant les valeurs du profil le long de MaxFeret
25-FerAxis: Line ROI
26-MidAxis: Polyline ROI de l'axe median par skeletonize
27-MidProfil: list contenant les valeurs du profil le long de MidAxis
28-nb Foci
29-ListFoci: liste des positions des foci par cellule
30-ListAreaFoci: liste des area des foci
31-ListPeaksFoci: liste des int max des foci
32-ListMeanFoci liste des int mean des foci
toute les proprietes mettent a jour l'image cible par: object.propriete=imp
Methodes:
getFeretSegments(n segments)
getMidSegments(n segments, radius, tool 0= ligne perpendiculaire, 1= cercle, 2= ligne tangente)
selectInitRoi: active la ROI initiale
Statics:
distMorph(liste de coordonees a mesurer= (coefficient, valeur initiale, valeur finale))
setteurs:
setImage(ImagePlus)
setImageMeasures(imagePlus) met a jours les mesures avec imagePlus
setImageMidprofil(imagePlus) met a jours le profil avec imagePlus
setLineWidth(width) afecte la largeur de ligne pour le profil pour Fprofile et MidProfil defaut = 0
setshowFprof(True) affiche le graphique de profil Fprofil defaut = False
setMidParams(longueur mesurer l'angle de l'extremite en pixels defaut=10, coefficient pour prolonger et trouver l'intersection avec le contour defaut=1.3
"""
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)
#self.__rt.show("myRT")
# calculate the 1/2 , 1/4 ... 1/n positions for a liste while 1/n >= 1 returns a dict = 0: (0, [0, 0, pos(1/2)]) 1: (1, [-1, -0.5, -pos(1/4)], [0, 0, pos(1/2)], [1, 0.5, pos(1/2)])
def __Centers(self, line) :
L=len(line)
l2=L//2
l=L
pos={}
for i in range(self.log2(L)) :
l = l//2
pos[i]=l
l=L
dicPos={}
jtot=1
for i in range(self.log2(L)) :
s=[]
j=1
while (l2-j*pos[i])>0 or (l2+j*pos[i])<L :
s.append((-j,(l2-j*pos[i])))
s.append((j,(l2+j*pos[i])))
j=j+1
s.append((0,l2))
s.sort()
if ((len(s)+1)*pos[i]-L)//pos[i] > 0 :
del s[0]
del s[-1]
else : pass
if len(s) - 1 != 0 : jtot= (( len(s) - 1 ) / 2.00)+1
else : jtot=1
centers=[[v[0], v[0]/jtot, v[1]] for v in s]
dicPos[i]=(i, centers)
del(s)
return dicPos
#calculate angle from the center of the midline to ends
def __flexAngle(self) :
try :
p1 = self.__midLine[0]
p3 = self.__midLine[-1]
except AttributeError :
self.__midline()
p1 = self.__midLine[0]
p3 = self.__midLine[-1]
icenter = self.__midCenters[0][1][0][2]
p2 = self.__midLine[icenter]
#xpoints = (429,472,466)
#ypoints = (114,133,99)
xpoints = [int(p1[0]), int(p2[0]), int(p3[0])]
ypoints = [int(p1[1]), int(p2[1]), int(p3[1])]
#print ypoints
#return ""
r = PolygonRoi(xpoints, ypoints, 3, Roi.ANGLE)
return r.getAngle()
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 __FeretAxis(self):
__boolFL=True
if (self.__contour is not None) and (self.__contour.getType() in range(1,11)):
self.__image.killRoi()
self.__image.setRoi(self.__contour)
if self.__contour.getType() in [1,5,9,10]:
self.__polygon=self.__contour.getPolygon()
else:
self.__polygon=self.__contour.getFloatPolygon()
points = self.__polygon.npoints
self.__polx = self.__polygon.xpoints
self.__poly = self.__polygon.ypoints
diameter=0.0
for i in range(points):
for j in range(i, points):
dx=self.__polx[i]-self.__polx[j]
dy=self.__poly[i]-self.__poly[j]
d=math.sqrt(dx*dx+dy*dy)
if d>diameter:
diameter=d
i1=i
i2=j
tempDictY={ self.__poly[i1]:(self.__polx[i1],self.__poly[i1],self.__polx[i2],self.__poly[i2]), self.__poly[i2]:(self.__polx[i2],self.__poly[i2],self.__polx[i1],self.__poly[i1]) }
minY=min((self.__poly[i1],self.__poly[i2]))
maxY=max((self.__poly[i1],self.__poly[i2]))
lineTuple=tempDictY[maxY]
self.__x1=lineTuple[0]
self.__y1=lineTuple[1]
self.__x2=lineTuple[2]
self.__y2=lineTuple[3]
self.__line= Line(self.__x1,self.__y1,self.__x2,self.__y2)
elif (self.__contour is not None) and (self.__contour.getType()==0):
self.__x2=self.__contour.getBounds().x
self.__y2=self.__contour.getBounds().y
self.__x1=self.__contour.getBounds().x+self.__contour.getBounds().width
self.__y1=self.__contour.getBounds().y+self.__contour.getBounds().height
self.__line= Line(self.__x1,self.__y1,self.__x2,self.__y2)
else:
self.__x1="NaN"
self.__y1="NaN"
self.__x2="NaN"
self.__y2="NaN"
self.__fprofArray="NaN"
def __FeretProfile(self):
"""
genere le profile le long du diametre de Feret
"""
self.__line.setWidth(self.__lw)
self.__image.setRoi(self.__line, True)
self.__fprof= ProfilePlot(self.__image)
self.__fprofArray=self.__fprof.getProfile()
if self.__showFpro: self.__fprof.createWindow()
self.__image.killRoi()
self.__line.setWidth(0)
self.__image.setRoi(self.__contour)
return self.__fprofArray
def __midline(self):
debug=False
#print "line 251", self.__boolML
if self.__boolML :
ordpoints=self.__midLine[:]
npoints=len(ordpoints)
xpoints=[point[0] for point in ordpoints]
ypoints=[point[1] for point in ordpoints]
polyOrd=PolygonRoi(xpoints, ypoints, npoints, PolygonRoi.POLYLINE)
return polyOrd
#if self.getMaxF()<15 : return None
#self.__FeretAxis()
#return self.__line
self.__boolML=True
self.__image.killRoi()
self.__image.setRoi(self.__contour)
boundRect=self.__contour.getBounds()
boundRoi=Roi(boundRect)
xori=boundRect.x
yori=boundRect.y
wori=boundRect.width
hori=boundRect.height
ip2 = ByteProcessor(self.__image.getWidth(), self.__image.getHeight())
ip2.setColor(255)
ip2.setRoi(self.__contour)
ip2.fill(self.__contour)
skmp=ImagePlus("ip2", ip2)
skmp.setRoi(xori-1,yori-1,wori+1,hori+1)
ip3=ip2.crop()
skmp3=ImagePlus("ip3", ip3)
skmp3.killRoi()
#-------------------------------------------------------------
if debug :
skmp3.show()
IJ.showMessage("imp3 l287")
#-------------------------------------------------------------
IJ.run(skmp3, "Skeletonize (2D/3D)", "")
#IJ.run(skmp3, "Skeletonize", "")
#-------------------------------------------------------------
if debug :
skmp3.show()
IJ.showMessage("imp3 l294")
#-------------------------------------------------------------
IJ.run(skmp3, "BinaryConnectivity ", "white")
ip3.setThreshold(3,4, ImageProcessor.BLACK_AND_WHITE_LUT)
IJ.run(skmp3, "Convert to Mask", "")
#-------------------------------------------------------------
if debug :
skmp3.show()
IJ.showMessage("imp3 l302")
#-------------------------------------------------------------
#IJ.run(skmp3, "Skeletonize", "")
#-------------------------------------------------------------
if debug :
skmp3.updateAndDraw()
skmp3.show()
IJ.showMessage("imp3 l308")
#-------------------------------------------------------------
rawPoints=[]
w=ip3.getWidth()
h=ip3.getHeight()
rawPoints=[(x+xori,y+yori,self.__sommeVals(x,y,ip3)) for x in range(w) for y in range(h) if ip3.getPixel(x,y)==255]
tempbouts=[val for val in rawPoints if val[2]==2]
if len(tempbouts)!=2 : return None
# test
#if len(tempbouts)!=2 :
#
# IJ.run(skmp3, "BinaryConnectivity ", "white")
# ip3.setThreshold(3,3, ImageProcessor.BLACK_AND_WHITE_LUT)
# IJ.run(skmp3, "Convert to Mask", "")
# #-------------------------------------------------------------
# if debug==debug :
# skmp3.updateAndDraw()
# skmp3.show()
# IJ.showMessage("if test l 328")
##-------------------------------------------------------------
# rawPoints=[(x+xori,y+yori,self.__sommeVals(x,y,ip3)) for x in range(w) for y in range(h) if ip3.getPixel(x,y)==255]
# tempbouts=[val for val in rawPoints if val[2]==2]
ip3.setRoi(boundRect)
if rawPoints==[]: return None
npoints=len(rawPoints)
xpoints=[point[0] for point in rawPoints]
ypoints=[point[1] for point in rawPoints]
valpoints=[point[2] for point in rawPoints]
bouts={}
if tempbouts==[]: return None
if tempbouts[0][1]>tempbouts[1][1]:
bouts["A"]=tempbouts[0]
bouts["B"]=tempbouts[1]
else:
bouts["A"]=tempbouts[1]
bouts["B"]=tempbouts[0]
rawPoints.remove(bouts["A"])
rawPoints.remove(bouts["B"])
rawPoints.append(bouts["B"])
tempList=[val for val in rawPoints]
p=bouts["A"]
Dist={}
ordPoints=[]
for j in range(len(rawPoints)):
Dist.clear()
for i in range(len(tempList)):
dx=p[0]-tempList[i][0]
dy=p[1]-tempList[i][1]
d=math.sqrt(dx*dx+dy*dy)
Dist[d]=tempList[i]
distList=Dist.keys()
mind=min(distList)
nextpoint=Dist[mind]
ordPoints.append(nextpoint)
tempList.remove(nextpoint)
p=nextpoint
ordPoints.insert(0, bouts["A"])
npoints=len(ordPoints)
if npoints < 4 : return None
xpoints=[point[0] for point in ordPoints]
ypoints=[point[1] for point in ordPoints]
polyOrd1=PolygonRoi(xpoints, ypoints, npoints, PolygonRoi.POLYLINE)
f=min(self.__midParams[0], len(xpoints)//2)
angleA1=polyOrd1.getAngle(xpoints[0],ypoints[0], xpoints[1],ypoints[1])
angleA2=polyOrd1.getAngle(xpoints[1],ypoints[1], xpoints[2],ypoints[3])
angleA = (angleA1+angleA2)/2.00
angleA=polyOrd1.getAngle(xpoints[0],ypoints[0], xpoints[f],ypoints[f])
angleA=angleA*(math.pi/180)
angleB1=polyOrd1.getAngle(xpoints[-2],ypoints[-2], xpoints[-1],ypoints[-1])
angleB2=polyOrd1.getAngle(xpoints[-3],ypoints[-3], xpoints[-2],ypoints[-2])
angleB = (angleB1+angleB2)/2.00
angleB=polyOrd1.getAngle(xpoints[-f],ypoints[-f], xpoints[-1],ypoints[-1])
angleB=angleB*(math.pi/180)
coef=self.__midParams[1]
xa = xpoints[0]-coef*f*math.cos(angleA)
ya = ypoints[0]+coef*f*math.sin(angleA)
xb = xpoints[-1]+coef*f*math.cos(angleB)
yb = ypoints[-1]-coef*f*math.sin(angleB)
lineA=Line(xpoints[0],ypoints[0], xa, ya)
lineB=Line(xpoints[-1],ypoints[-1], xb, yb)
lineA.setWidth(0)
lineB.setWidth(0)
lineA.setStrokeWidth(0)
lineB.setStrokeWidth(0)
ip2.setColor(0)
ip2.fill()
ip2.setColor(255)
ip2.setRoi(lineA)
lineA.drawPixels(ip2)
ip2.setRoi(lineB)
lineB.drawPixels(ip2)
ip2.setRoi(self.__contour)
ip2.setColor(0)
ip2.fillOutside(self.__contour)
ip2=ip2.crop()
imb=ImagePlus("new-ip2", ip2)
#-------------------------------------------------------------
if debug :
imb.show()
IJ.showMessage("imb l416")
#-------------------------------------------------------------
w2=ip2.getWidth()
h2=ip2.getHeight()
ip4 = ByteProcessor(w2+2, h2+2)
im4=ImagePlus("im4", ip4)
for i in range(w2):
for j in range(h2):
ip4.set(i+1,j+1,max([ip2.getPixel(i,j),ip3.getPixel(i,j)]))
#im4.show()
#-------------------------------------------------------------
if debug :
im4.show()
IJ.showMessage("im4 l430")
#-------------------------------------------------------------
im4.killRoi()
#IJ.run(im4, "Skeletonize (2D/3D)", "")
#IJ.run(skmp3, "Skeletonize", "")
#-------------------------------------------------------------
if debug :
imb.show()
IJ.showMessage("imb l300")
#-------------------------------------------------------------
#IJ.run(skmp3, "Skeletonize", "")
ip4=im4.getProcessor()
rawPoints2=[]
w4=ip4.getWidth()
h4=ip4.getHeight()
rawPoints2=[(x+xori-2,y+yori-2,self.__sommeVals(x,y,ip4)) for x in range(w4) for y in range(h4) if ip4.getPixel(x,y)==255]
self.__MidBouts=[val for val in rawPoints2 if val[2]==2]
# test
if len(self.__MidBouts)!=2 :
IJ.run(im4, "BinaryConnectivity ", "white")
ip4.setThreshold(3,3, ImageProcessor.BLACK_AND_WHITE_LUT)
IJ.run(im4, "Convert to Mask", "")
rawPoints2=[(x+xori-2,y+yori-2,self.__sommeVals(x,y,ip4)) for x in range(w4) for y in range(h4) if ip4.getPixel(x,y)==255]
self.__MidBouts=[val for val in rawPoints2 if val[2]==2]
ordpoints=[]
p0=self.__MidBouts[0]
rawPoints2.remove(p0)
c=0
while p0!=self.__MidBouts[1]:
if c<len(rawPoints2):
point=rawPoints2[c]
else: break
if abs(point[0]-p0[0])<2 and abs(point[1]-p0[1])<2:
p0=point
ordpoints.append(point)
rawPoints2.remove(point)
c=0
else: c=c+1
ordpoints.insert(0, self.__MidBouts[0])
self.__midLine=ordpoints[:]
self.__midCenters = self.__Centers(self.__midLine)
npoints=len(ordpoints)
xpoints=[point[0] for point in ordpoints]
ypoints=[point[1] for point in ordpoints]
polyOrd=PolygonRoi(xpoints, ypoints, npoints, PolygonRoi.POLYLINE)
#print self.__midLine
#print self.__MidBouts
#print xpoints
#print ypoints
return polyOrd
def __sommeVals(self, x, y, ip):
return (ip.getPixel(x,y)+ip.getPixel(x-1,y-1)+ip.getPixel(x,y-1)+ip.getPixel(x+1,y-1)+ip.getPixel(x-1,y)+ip.getPixel(x+1,y)+ip.getPixel(x-1,y+1)+ip.getPixel(x,y+1)+ip.getPixel(x+1,y+1))/255
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 __MidProfil(self):
if not self.__boolML : self.__midline()
ip=self.__image.getProcessor()
line=Line(self.__midLine[0][0],self.__midLine[0][1],self.__midLine[-1][0],self.__midLine[-1][1])
line.setWidth(self.__lw)
self.__MprofArray=[]
self.__MprofArray[:]=[]
for i in range(0,len(self.__midLine)-1):
templine=Line(self.__midLine[i][0],self.__midLine[i][1],self.__midLine[i+1][0],self.__midLine[i+1][1])
templine.setWidth(self.__lw)
self.__image.setRoi(templine)
#time.sleep(0.5)
temprof= ProfilePlot(self.__image)
temparray=temprof.getProfile()
self.__MprofArray+=temparray
templine.setWidth(0)
#if self.__showMidpro: self.__fprof.createWindow()
return
def getFeretSegments(self, n):
self.__boolFS=True
if(not self.__boolFL):
self.__FeretAxis()
radius=self.getMinF()
lsegment=self.__line.getLength()/((n-1)*2)
xo=self.__x1
yo=self.__y1
xf=self.__x2
yf=self.__y2
angle1=self.getAngF()*(math.pi/180)
angle2=self.getAngF()*(math.pi/180)+(math.pi/2)
avancex=(lsegment*2)*math.cos(angle1)
avancey=(lsegment*2)*math.sin(angle1)
delta90x=(radius)*math.cos(angle2)
delta90y=(radius)*math.sin(angle2)
self.__line.setWidth(int(lsegment*2))
#self.__image.setRoi(self.__line)
tempcontour=self.__contour.clone()
shapeContour=ShapeRoi(tempcontour)
segsRoi=[]
for i in range(n):
tempLine=Line(xo-delta90x, yo+delta90y, xo+delta90x, yo-delta90y)
tempLine.setWidth(int(lsegment*2))
poly=tempLine.getPolygon()
roipol=PolygonRoi(poly, Roi.POLYGON)
shapePoly= ShapeRoi(roipol)
interShape=shapePoly.and(shapeContour)
segsRoi.append(interShape.shapeToRoi())
xo=xo+avancex
yo=yo-avancey
#self.__image.setRoi(self.__contour, True)
#time.sleep(0)
self.__line.setWidth(0)
#self.__image.setRoi(tempcontour)
#self.__image.updateAndDraw()
return segsRoi # return Roi array
def getMidSegments(self, n=10, r=5, tool=0):
self.__boolMS=True
if(not self.__boolML):
self.__midline()
lsegment=int(len(self.__midLine)/n)
if lsegment<2:lsegment=2
ls2=int(len(self.__midLine)/(2*n))
if ls2<1: ls2=1
ip=self.__image.getProcessor()
#print(len(self.__midLine), lsegment, ls2)
xo=self.__MidBouts[0][0]
yo=self.__MidBouts[0][1]
xf=self.__MidBouts[1][0]
yf=self.__MidBouts[1][1]
line1=Line(xo,yo,xf,yf)
line1.setWidth(0)
angles=[line1.getAngle(self.__midLine[i][0], self.__midLine[i][1], self.__midLine[i+lsegment][0], self.__midLine[i+lsegment][1]) for i in range(0,len(self.__midLine)-lsegment,lsegment)]
points=[self.__midLine[i] for i in range(0,len(self.__midLine),lsegment)]
lastangle=line1.getAngle(self.__midLine[-ls2][0],self.__midLine[-ls2][1],self.__midLine[-1][0],self.__midLine[-1][1])
angles.append(lastangle)
tempcontour=self.__contour.clone()
shapeContour=ShapeRoi(tempcontour)
angles=[angle*(math.pi/180)+(math.pi/2) for angle in angles]
line1.setWidth((ls2+1)*2)
segsRoi=[]
linesRois=[]
cRois=[]
for i in range(len(angles)):
x=points[i][0]
y=points[i][1]
cRois.append(PointRoi(x,y))
if tool==0: # ligne perpendiculaire d'epaiseur (ls2+1)*2
line1.setWidth((ls2+1)*2)
x1=x+r*math.cos(angles[i])
y1=y-r*math.sin(angles[i])
x2=x-r*math.cos(angles[i])
y2=y+r*math.sin(angles[i])
#print(x, y, x1, y1, x2, y2)
tempLine=Line(x1,y1,x2,y2)
linesRois.append(tempLine)
tempLine.setWidth((ls2+1)*2)
#self.__image.setRoi(tempLine, True)
#time.sleep(0.3)
poly=tempLine.getPolygon()
roipol=PolygonRoi(poly, Roi.POLYGON)
shapePoly= ShapeRoi(roipol)
elif tool==1:
#r1=r*0.7
x1=x+r
y1=y-r
x2=x-r
y2=y+r
ellipse=EllipseRoi(x1, y1, x2, y2, 1)
linesRois.append(ellipse)
#print(x, y, x1, y1, x2, y2)
#self.__image.setRoi(ellipse, True)
shapePoly= ShapeRoi(ellipse)
#time.sleep(0.3)
else:
x1=x
y1=y
line1.setWidth(r)
if (i+1)<len(points):
x2=points[i+1][0]
y2=points[i+1][1]
else:
#x1=x+lsegment*math.cos(angles[i]-(math.pi/2))
#y1=y-lsegment*math.sin(angles[i]-(math.pi/2))
x2=x+lsegment*math.cos(angles[i]-(math.pi/2))
y2=y-lsegment*math.sin(angles[i]-(math.pi/2))
#x2=xf
#y2=yf
tempLine=Line(x1,y1,x2,y2)
linesRois.append(tempLine)
tempLine.setWidth(r)
#self.__image.setRoi(tempLine, True)
#time.sleep(0.5)
poly=tempLine.getPolygon()
roipol=PolygonRoi(poly, Roi.POLYGON)
shapePoly= ShapeRoi(roipol)
interShape=shapePoly.and(shapeContour)
interRoi=interShape.shapeToRoi()
segsRoi.append(interShape.shapeToRoi())
line1.setWidth(0)
return (segsRoi, linesRois, cRois)
def selectInitRoi(self):
self.__image.killRoi()
self.__image.setRoi(self.__contour)
time.sleep(0)
@staticmethod
def distMorph(coord,distmethod="Euclidean distance"):
if distmethod == "Euclidean distance" :
s=[val[0]*(val[2]-val[1])*(val[2]-val[1]) for val in coord]
#print s
#print sum(s)
return math.sqrt(sum(s))
if distmethod == "Logarithm distance" :
s=[val[0]*abs(math.log(val[2]/val[1])) for val in coord]
return sum(s)
@staticmethod
def log2(n) : return math.log(n)/math.log(2)
def Out(self): print("out")
#------ end methodes---------------
#------ constructeur -------------
def __init__(self, imp, roi):
self.__lw=0
self.__showFpro=False
self.__Feret=[]
self.__image=imp
self.__cal=imp.getCalibration()
self.__contour=roi.clone()
self.__boolmeasures=False
self.__boolFP=False
self.__boolFL=False
self.__boolML=False
self.__boolMP=False
self.__boolFS=False
self.__boolMS=False
self.__boolFoci=False
self.__midParams=[10, 1.3]
self.__listMax=[]
self.__noise=150
self.__seuilPeaks=0.75
self.__peaksMethod="mean"
self.__light=False
self.__distot=0.00
self.__flexangle=0.00
#print "dropbox MorphoBactProject"
#---------- end constructor---------
#---------- getteurs----------------
def getMaxF(self):
if(not self.__boolmeasures): self.__Measures()
return self.__rt.getValue("Feret", 0)
def getMinF(self):
if(not self.__boolmeasures): self.__Measures()
return self.__rt.getValue("MinFeret", 0)
def getXF(self):
if(not self.__boolmeasures): self.__Measures()
return self.__rt.getValue("FeretX", 0)
def getYF(self):
if(not self.__boolmeasures): self.__Measures()
return self.__rt.getValue("FeretY", 0)
def getAngF(self):
if(not self.__boolmeasures): self.__Measures()
return self.__rt.getValue("FeretAngle", 0)
def getArea(self):
if(not self.__boolmeasures): self.__Measures()
return self.__rt.getValue("Area", 0)
def getMean(self):
if(not self.__boolmeasures): self.__Measures()
return self.__rt.getValue("Mean", 0)
def getKurt(self):
if(not self.__boolmeasures): self.__Measures()
return self.__rt.getValue("Kurt", 0)
def getSkew(self):
if(not self.__boolmeasures): self.__Measures()
return self.__rt.getValue("Skew", 0)
def getIntDen(self):
if(not self.__boolmeasures): self.__Measures()
return self.__rt.getValue("IntDen", 0)
def getStdDev(self):
if(not self.__boolmeasures): self.__Measures()
return self.__rt.getValue("StdDev", 0)
def getAngle(self):
if(not self.__boolmeasures): self.__Measures()
return self.__rt.getValue("Angle", 0)
def getMajor(self):
if(not self.__boolmeasures): self.__Measures()
return self.__rt.getValue("Major", 0)
def getMinor(self):
if(not self.__boolmeasures): self.__Measures()
return self.__rt.getValue("Minor", 0)
def getSolidity(self):
if(not self.__boolmeasures): self.__Measures()
return self.__rt.getValue("Solidity", 0)
def getAR(self):
if(not self.__boolmeasures): self.__Measures()
return self.__rt.getValue("AR", 0)
def getRound(self):
if(not self.__boolmeasures): self.__Measures()
return self.__rt.getValue("Round", 0)
def getCirc(self):
if(not self.__boolmeasures): self.__Measures()
return self.__rt.getValue("Circ.", 0)
def getXM(self):
if(not self.__boolmeasures): self.__Measures()
return self.__rt.getValue("XM",0)
def getYM(self):
if(not self.__boolmeasures): self.__Measures()
return self.__rt.getValue("YM",0)
def getXC(self):
if(not self.__boolmeasures): self.__Measures()
return self.__rt.getValue("X",0)
def getYC(self):
if(not self.__boolmeasures): self.__Measures()
return self.__rt.getValue("Y",0)
def getNfoci(self):
if(not self.__boolFoci):self.__NbFoci()
return len(self.__listMax)
def getListFoci(self):
if(not self.__boolFoci):self.__NbFoci()
xy=[]
for val in self.__listMax:
xy.append((val[0], val[1]))
return xy
def getListPeaksFoci(self):
if(not self.__boolFoci):self.__NbFoci()
peaks=[]
for val in self.__listMax:
peaks.append(val[2])
return peaks
def getListAreaFoci(self):
if(not self.__boolFoci):self.__NbFoci()
areas=[]
for val in self.__listMax:
areas.append(val[3])
return areas
def getListMeanFoci(self):
if(not self.__boolFoci):self.__NbFoci()
means=[]
for val in self.__listMax:
means.append(val[4])
return means
def getListIntDenFoci(self):
if(not self.__boolFoci):self.__NbFoci()
ints=[]
for val in self.__listMax:
ints.append(val[5])
return ints
def getListFeretFoci(self):
if(not self.__boolFoci):self.__NbFoci()
ferets=[]
for val in self.__listMax:
ferets.append(val[6])
return ferets
def getListDistsFoci(self):
if(not self.__boolFoci):self.__NbFoci()
dists=[]
for val in self.__listMax:
dists.append(val[7])
return dists
def getFercoord(self):
"""
FerCoord: tuple contenant x1, y1, x2, y2 du MaxFeret
"""
if (not self.__boolFL): self.__FeretAxis()
return (self.__x1,self.__y1,self.__x2,self.__y2)
def getFprofil(self):
"""
Fprofil: list contenant les valeurs du profil le long de MaxFeret
"""
if (not self.__boolFL): self.__FeretAxis()
self.__FeretProfile()
return self.__fprofArray
def getFerAxis(self):
"""
FerAxis: Line ROI
"""
if(not self.__boolFL): self.__FeretAxis()
return self.__line
def getMidAxis(self):
"""
MidAxis: Polyline ROI de l'axe median par skeletonize
"""
if(not self.__boolML): return self.__midline()
def getMidSegs(self, n, r, tool):
"""
Rois des segments 0 = rois , 1 = points, 2 = lines ou ellipses
"""
if(not self.__boolMS): return self.getMidSegments(n, r, tool)
def getMidProfil(self):
"""
MidProfil: list contenant les valeurs du profil le long de MidAxis
"""
self.__MidProfil()
return self.__MprofArray
def getMidPoints(self) :
"""
MidPoints : list of two extreme points of mid Axis
"""
if(not self.__boolML): self.__midline()
return self.__MidBouts
def getCenters(self) :
if(not self.__boolML): self.__midline()
return self.__midCenters
def getFlexAngle(self) :
return self.__flexAngle()
#------ setteurs --------
def setImage(self, imp):
self.__image=imp
def setImageMeasures(self, imp):
self.__image=imp
self.__Measures()
def setImageFprofil(self, imp):
self.__image=imp
self.__FeretProfile()
def setImageMidprofil(self, imp):
self.__image=imp
self.__MidProfil()
def setLineWidth(self, lw):
self.__lw=lw
def setshowFpro(self, fpshow):
self.__showFpro=fpshow
def setMidParams(self, lseg, coeff):
self.__midParams[:]=[]
self.__midParams.append(lseg)
self.__midParams.append(coeff)
def setNoise(self, noise):
self.__noise=noise
def setSeuilPeaks(self, seuil):
self.__seuilPeaks=seuil
def setpeaksMethod(self, method):
self.__peaksMethod=method
def setlight(self, light):
self.__light=light
#------- properties -----------------------
MaxFeret=property(getMaxF, setImageMeasures, doc="caliper max Feret=")
MinFeret=property(getMinF, setImageMeasures, doc="caliper min Feret=")
AngleFeret=property(getAngF, setImageMeasures, doc="angle Feret=")
XFeret=property(getXF, setImageMeasures, doc="X Feret=")
YFeret=property(getYF, setImageMeasures, doc="Y Feret=")
Area=property(getArea, setImageMeasures, doc="Area=")
Mean=property(getMean, setImageMeasures, doc="Mean=")
Kurt=property(getKurt, setImageMeasures, doc="Kurtosis=")
Skew=property(getSkew, setImageMeasures, doc="Skewness=")
IntDen=property(getIntDen, setImageMeasures, doc="Integrated Intensity=")
StdDev=property(getStdDev, setImageMeasures, doc="Standard Deviation=")
Angle=property(getAngle, setImageMeasures, doc="Angle=")
Major=property(getMajor, setImageMeasures, doc="Major ellipse axis=")
Minor=property(getMinor, setImageMeasures, doc="Minor ellipse axis=")
Solidity=property(getSolidity, setImageMeasures, doc="Solidity area/convexHull=")
AR=property(getAR, setImageMeasures, doc="Major axis/Minor axis=")
Round=property(getRound, setImageMeasures, doc="Area/(pi*Major*Major)=1/AR=")
Circ=property(getCirc, setImageMeasures, doc="(4*pi*Area)/(perimeter*perimeter)=")
XM=property(getXM, setImageMeasures, doc="X center of Mass=")
YM=property(getYM, setImageMeasures, doc="Y center of Mass=")
XC=property(getXC, setImageMeasures, doc="X of centroid=")
YC=property(getYC, setImageMeasures, doc="Y of centroid=")
NFoci=property(getNfoci, setImageMeasures, doc="nb foci in the roi=")
ListFoci=property(getListFoci, setImageMeasures, doc="list of foci coordinates=")
ListPeaksFoci=property(getListPeaksFoci, setImageMeasures, doc="list of foci peaks=")
ListAreaFoci=property(getListAreaFoci, setImageMeasures, doc="list of foci areas=")
ListMeanFoci=property(getListMeanFoci, setImageMeasures, doc="list of foci means=")
ListIntDenFoci=property(getListIntDenFoci, setImageMeasures, doc="list of foci IntDen=")
ListFeretFoci=property(getListFeretFoci, setImageMeasures, doc="list of foci Ferets=")
ListDistsFoci=property(getListDistsFoci, setImageMeasures, doc="list of foci distances=")
FerCoord=property(getFercoord, doc="x1, y1, x2, y2 of Feret diameter =")
Fprofil=property(getFprofil, setImageFprofil, doc="Profil along Feret diameter") # return array values
FerAxis=property(getFerAxis, doc="ROI along Feret diameter") # return Roi
MidAxis=property(getMidAxis, doc="ROI along the median axis") # return Roi
MidProfil=property(getMidProfil, setImageMidprofil, doc="profile values of mid axis") # return array values
MidPoints=property(getMidPoints, doc= "extreme points of mid line")
Centers=property(getCenters, doc= "list of positions (tuples) of 1/2 of the midaxis, 1/4, 1/8 ...") # return a list of tuples
FlexAngle=property(getFlexAngle, doc="angle of the center of midline to ends")
loadmethod = "de.embl.cmci.io.ResultsTableLoader"
# Path to the partcile analysis results
path = "/Users/miura/Dropbox/people/Giogia_Stefano/toJoe/coords.csv"
# Path to the binary image, to be plotted with area.
# binimgpath = '/Users/miura/Dropbox/people/Giogia_Stefano/toJoe/mask10frames.tif'
binimgpath = "/Users/miura/Dropbox/people/Giogia_Stefano/toJoe/mask20framesOrg.tif"
# binimgpath = '/Users/miura/Dropbox/people/Giogia_Stefano/toJoe/mask_z4_furrowSeg1.0.6_threshOffest5e-04_closingSize3_200f.tif'
imp = IJ.openImage(binimgpath)
# paOpt = PA.CLEAR_WORKSHEET +\
paOpt = PA.SHOW_OUTLINES + PA.EXCLUDE_EDGE_PARTICLES # +\
# PA.INCLUDE_HOLES #+ \
# PA.SHOW_RESULTS
measOpt = PA.AREA + PA.CENTROID + PA.SLICE # + PA.SHAPE_DESCRIPTORS + PA.INTEGRATED_DENSITY
rt = ResultsTable()
MINSIZE = 2
MAXSIZE = 10000
pa = PA(paOpt, measOpt, rt, MINSIZE, MAXSIZE)
pa.setHideOutputImage(True)
# pa.processStack = True
for i in range(imp.getStackSize()):
imp.setSlice(i + 1)
pa.analyze(imp)
# pa.getOutputImage().show()
rt.show("cells")
# rt = ResultsTable.open2(path)
dotlinker = DotLinker(loadmethod, rt) # better there is a constructor also with linkkost function object.
dotlinker.setTrajectoryThreshold(5)
dotlinker.setShowTrackTable(False)
# Process list of images
for (counter, f) in enumerate(files):
# Display progress
IJ.showStatus("Processing file "+ str(counter+1) +"/"+ str(len(files)))
# Open each image and process it
imp = IJ.openImage(f)
myRoutines(imp)
# Save processed image in out_dir (enforcing .tif extension)
newpath = os.path.splitext(out_dir + imp.getTitle())[0] +".tif"
IJ.saveAsTiff(imp, newpath)
imp.close()
# Log paths of processed files
csvWriter.writerow([f, newpath])
# Display CSV log
csvFile.close()
rt = ResultsTable.open(csvPath)
rt.show("_ProcessedFileList.csv")
# Proudly inform that processing terminated
if IJ.showMessageWithCancel("All done","Reveal output directory?"):
Utils.revealFile(out_dir);
else:
# Inform no filtered files were found
IJ.error("No matches for the selected extension(s).")
