def keep_largest_blob(imp):
"""remove all blobs other than the largest by area"""
rt = ResultsTable()
mxsz = imp.width * imp.height
roim = RoiManager(False)
pa = ParticleAnalyzer(ParticleAnalyzer.ADD_TO_MANAGER,
ParticleAnalyzer.AREA | ParticleAnalyzer.SLICE, rt,
0, mxsz)
pa.setRoiManager(roim)
for idx in range(1, imp.getImageStackSize() + 1):
roim.reset()
rt.reset()
imp.setPosition(idx)
pa.analyze(imp)
rt_areas = rt.getColumn(rt.getColumnIndex("Area")).tolist()
mx_ind = rt_areas.index(max(rt_areas))
indices_to_remove = [
a for a in range(0, len(rt_areas)) if a != mx_ind
]
indices_to_remove.reverse()
for rem_idx in indices_to_remove:
roim.select(imp, rem_idx)
IJ.run(imp, "Set...", "value=0 slice")
imp.killRoi()
roim.reset()
roim.close()
def keep_blobs_bigger_than(imp, min_size_pix=100):
"""remove all blobs other than the largest by area"""
imp.killRoi()
rt = ResultsTable()
if "Size_filtered_" in imp.getTitle():
title_addition = ""
else:
title_addition = "Size_filtered_"
out_imp = IJ.createImage("{}{}".format(title_addition, imp.getTitle()),
imp.getWidth(), imp.getHeight(), 1, 8)
out_imp.show()
IJ.run(out_imp, "Select All", "")
IJ.run(out_imp, "Set...", "value=0 slice")
mxsz = imp.width * imp.height
roim = RoiManager()
pa = ParticleAnalyzer(ParticleAnalyzer.ADD_TO_MANAGER,
ParticleAnalyzer.AREA | ParticleAnalyzer.SLICE, rt,
min_size_pix, mxsz)
pa.setRoiManager(roim)
roim.reset()
rt.reset()
pa.analyze(imp)
rt_areas = rt.getColumn(rt.getColumnIndex("Area")).tolist()
# print("Number of cells identified: {}".format(len(rt_areas)));
for idx in range(len(rt_areas)):
roim.select(out_imp, idx)
IJ.run(out_imp, "Set...", "value=255 slice")
mx_ind = rt_areas.index(max(rt_areas))
roim.reset()
roim.close()
imp.changes = False
imp.close()
return out_imp
"size=5000-Infinity pixel circularity=0.3-1.00 add exclude stack")
IJ.run("Tile", "")
time.sleep(0.2)
name1 = imp1.getTitle()
nuclei_count = rm.getCount()
if rm.getCount() != 0:
rois = rm.getIndexes()
rm.setSelectedIndexes(rois)
if rm.getCount() > 1:
rm.runCommand("Combine")
rm.runCommand("Delete")
rm.runCommand("Add")
rois1 = rm.getIndexes()
for roi in rois1:
rm.select(imp1, roi)
imp1.setC(1)
IJ.run(imp1, "Draw", "slice")
IJ.selectWindow(name1)
IJ.run("Select None")
print nuclei_count
nuclei_count_sum = nuclei_count_sum + nuclei_count
if nuclei_count < 1:
Nuclei.changes = False
Nuclei.close()
imp1.changes = False
imp1.close()
continue
rm.reset()
rm.runCommand("Open", os.path.join(folder, "selected.zip"))
# rename the remaining ROIs so that VSI can deal with them
# i is the index within ROI Mgr. i+1 is the number given by VSI Reader
# get base name of ROIs
# searching the last 5 characters for the hashmark because there are usually 2 in the ROI name
oldname = rm.getName(0)
hashPos = oldname.find("#",-5) + 1
# print hashPos
basename = oldname[0:hashPos]
# print "Basename is " + basename
nROIs = rm.getCount()
for i in range(0, nROIs):
roiNum = i + 1
rm.select(i)
rm.runCommand("Rename", basename + str(roiNum))
rm.deselect()
rm.runCommand("Save", os.path.join(folder, "renamed.zip"))
# finally, user should select all the ROIs and click Extract Current Image
# and save a copy with the overlay of ROIs
# for serial sections, use a large thumbnail to make ROIs.
# Re-open the "renamed" file and the 2nd series, activate ROIs on the other series image, adjust positions, RENAME TO SERIES 2 and extract
def __displayCells(self, nameimage, methodeleon=False):
"""
Displays all the ROIs of the cells with different colors
"""
# we define a list of colors that will be used.
colors = []
ncells= len(self.__dict[nameimage])
if ncells > 0 :
step=200/ncells
if step<1 : step=1
for i in range(ncells) :
r = random.randrange(5,205,step)
g = random.randrange(10,210,step)
b = random.randrange(30,230,step)
#r = int(0+i*step)
#g = random.randrange(10, 190, 30)
#b = int(250-i*step)
colors.append(Color(r, g, b))
else : colors=[Color.blue, Color.green, Color.magenta, Color.orange, Color.yellow]
tempcolors=list(colors)
# we try to have random and different colors for each cell.
for cellname in self.__dict[nameimage].keys() :
if len(tempcolors)>0 :
self.__dict[nameimage][cellname].setColor(tempcolors.pop(0))
else :
tempcolors=list(colors)
self.__dict[nameimage][cellname].setColor(tempcolors.pop(0))
self.__SaveCells(nameimage)
rm = RoiManager.getInstance()
if (rm==None): rm = RoiManager()
rm.runCommand("reset")
# if the user wants to save files, .zip for the ROIs are saved.
#if self.__optionSave == True :
#os.mkdir(self.__pathdir+"ROIs/", mode=0777)
os.makedirs(self.__pathdir+"ROIs/", mode=0777)
tempimp = IJ.createImage("tempimp", "8-bit Black", self.__dictImages[nameimage].getWidth(), self.__dictImages[nameimage].getHeight(), 1)
tempimp.show()
for cellname in self.__dict[nameimage].keys() :
for numslice in range(self.__dictImages[nameimage].getImageStackSize()) :
r = self.__dict[nameimage][cellname].getRoi(numslice)
try :
name=r.getName()
except AttributeError : continue
else :
s = "%04i" % (numslice+1)
#name=s+"-"+name.split("-", 1)[1]
name=s+"-cell"+name.split("cell")[1]
r.setName(name)
try :
rm.addRoi(r)
rname=rm.getName(rm.getCount()-1)
#rm.select(self.__dictImages[nameimage], rm.getCount()-1)
rm.select(tempimp, rm.getCount()-1)
rm.runCommand("Rename", name)
except TypeError : continue
#if isinstance(self.__dict[nameimage][cellname].getRoi(numslice),Roi) == True :
# s = "%04i" % (numslice)
# #rm.add(self.__dictImages[nameimage], self.__dict[nameimage][cellname].getRoi(numslice) , numslice)
# name=self.__dict[nameimage][cellname].getRoi(numslice).getName()
# name=s+name
# self.__dict[nameimage][cellname].getRoi(numslice).setName(name)
# rm.addRoi(self.__dict[nameimage][cellname].getRoi(numslice))
rm.runCommand("Save", self.__pathdir+"ROIs/"+cellname+".zip")
rm.runCommand("reset")
tempimp.close()
def __settings(self, imgName) :
"""
Lets the user to choose different measures to make, and displays it following the choice of the user.
"""
try : dico=self.__dictCells[imgName]
except KeyError :
try : dico=self.__dictCells[imgName[:-4]]
except KeyError : return False
else : imgName=imgName[:-4]
dico=self.__dictCells[imgName]
for cellname in dico.keys() :
self.__dictMeasures[dico[cellname]]={}
# Represents the datas on a diagram
def diagrambuttonPressed(event) :
IJ.showMessage("Push 'Auto' button each time you want to see the diagram")
x1=10
y1=20
x2=100
y2=50
x3=60
y3=30
xr=10
yr=20
wr=20
hr=20
rect=Rectangle(xr,yr,wr,hr)
#img=IJ.getImage()
#nbslices=self.__img.getImageStackSize()
nbslices=self.__maxLife
IJ.run("Hyperstack...", "title=Diagram type=32-bit display=Color width="+str(x2+(nbslices+1)*x3)+" height="+str(y2+y3*len(dico))+" channels=1 slices="+str(len(self.__measures))+" frames=1")
im=IJ.getImage()
ip=im.getProcessor()
for i in range(len(self.__measures)) :
indiceligne=0
maxvalue=0
minvalue=1000000
im.setPosition(1,i+1,1)
for cellname in self.__listcellname :
indiceligne+=1
for indicecolonne in range(1,nbslices+1):
rect.setLocation(x2+indicecolonne*x3+int(x3/6),(y1+indiceligne*y3-int(y3/2)))
# we create at the first iteration a dictionary with the rectangles (for a future use)
if i==0 :
self.__gridrectangle[(indiceligne,indicecolonne)]=Rectangle(rect)
im.setRoi(rect)
ipr=im.getProcessor()
# we find the min and max values of the datas for a measure given.
if self.__dictMeasures[dico[cellname]][self.__measures[i]][indicecolonne-1]>maxvalue :
maxvalue=self.__dictMeasures[dico[cellname]][self.__measures[i]][indicecolonne-1]
if self.__dictMeasures[dico[cellname]][self.__measures[i]][indicecolonne-1]<minvalue :
minvalue=self.__dictMeasures[dico[cellname]][self.__measures[i]][indicecolonne-1]
# we fill the rectangle with the value of the measure
ipr.setValue(self.__dictMeasures[dico[cellname]][self.__measures[i]][indicecolonne-1])
ipr.fill()
# we write the names and the n of slices on the image with the maxvalue.
ip.setValue(maxvalue)
ip.moveTo(x1,y1)
ip.drawString(self.__measures[i])
for j in range(1,nbslices+1) :
ip.moveTo(x2+j*x3,y1)
ip.drawString("Slice "+str(j))
j=0
for cellname in self.__listcellname :
ip.moveTo(x1,y2+j*y3)
ip.drawString(cellname)
j+=1
im.killRoi()
im=IJ.run(im,"Fire","")
IJ.run("Brightness/Contrast...", "")
#im.setMinAndMax(minvalue,maxvalue)
#im.updateImage()
#we add a mouse listener in order to be able to show the roi corresponding to a rectangle when the user clicks on it.
listener = ML()
listener.name=imgName
for imp in map(WindowManager.getImage, WindowManager.getIDList()):
if imp.getTitle().startswith("Diagram") :
win = imp.getWindow()
if win is None:
continue
win.getCanvas().addMouseListener(listener)
# Represents the datas on a series of graphs.
def graphbuttonPressed(event) :
colors=[]
#img=IJ.getImage()
#nbslices=self.__img.getImageStackSize()
nbslices=self.__maxLife
acell=dico.values()[0]
if self.__useTime :
x = acell.getListTimes()
namex="Time sec"
else :
x = range(1,nbslices+1)
namex = "Frame"
maxx=max(x)
minx=min(x)
#x=[i for i in range(1,nbslices+1)]
font=Font("new", Font.BOLD, 14)
tempname = WindowManager.getUniqueName(self.__img.getShortTitle())
for i in range(len(self.__measures)) :
#print "i", i, self.__measures[i]
yarray=[]
flag=True
miny=10000000000
maxy=-1000000000
#we find the min and max values in order to set the scale.
for cellname in self.__listcellname :
colors.append(dico[cellname].getColor())
yarray.append(self.__dictMeasures[dico[cellname]][self.__measures[i]])
#for meas in self.__dictMeasures[dico[cellname]][self.__measures[i]] :
for meas in yarray[-1] :
if (meas<miny) and (Double.isNaN(meas)==False) :
miny=meas
if max(yarray[-1])>maxy : maxy=max(yarray[-1])
miny-=0.1*miny
maxy+=0.1*maxy
count=0.05
for j in range(len(yarray)) :
if j==0 :
if len(self.__measures)>1 :
plot=Plot("Plots-"+str(self.__measures[i]),namex,str(self.__measures[i]),x,yarray[j])
else :
plot=Plot("Plot-"+tempname,namex,str(self.__measures[i]),x,yarray[j])
plot.setLimits(minx,maxx,miny,maxy)
plot.setColor(colors[j])
plot.changeFont(font)
plot.addLabel(0.05, count, self.__listcellname[j])
else :
plot.setColor(colors[j])
plot.setLineWidth(3)
plot.addPoints(x,yarray[j],Plot.LINE)
plot.addLabel(0.05, count, self.__listcellname[j])
count+=0.05
plot.setColor(colors[0])
plot.show()
if len(self.__measures)>1 :
IJ.run("Images to Stack", "name="+tempname+"-plots title=Plots- use")
#def histbuttonPressed(event) :
#
# pass
# Represents the values in a tab.
def tabbuttonPressed(event) :
tab="\t"
headings=[]
measures=[]
#img=IJ.getImage()
#for i in range(self.__img.getImageStackSize()+1) :
for i in range(self.__maxLife+1) :
headings.append("Slice "+str(i))
headings[0]=WindowManager.getUniqueName(self.__img.getShortTitle())
#for m in self.__measurescompl :
for m in self.__dictMeasures[dico[self.__listcellname[0]]].keys() :
headstring=""
for head in headings:
headstring+=head+tab
tw=TextWindow(self.__listfiles[0]+"-"+m,headstring,"",800,600)
tp=tw.getTextPanel()
#for cellname in dico.keys() :
for cellname in self.__listcellname :
line=[]
line=[str(meas)+tab for meas in self.__dictMeasures[dico[cellname]][m]]
line.insert(0, cellname+tab)
linestr=""
for s in line: linestr+=s
tp.appendLine(linestr)
tp.updateDisplay()
if self.__measuresparambool_global[0] :
tw=TextWindow("Latency","cell\tLatency", "",800,600)
tp=tw.getTextPanel()
for i in range(len(self.__listcellname)) :
#if latencies[i][0] : line=self.__listcellname[i]+"\t"+str(latencies[i][1])
#else : line=self.__listcellname[i]+"\t"+"NaN"
line=self.__listcellname[i]+"\t"+str(latencies[i][1])
tp.appendLine(line)
tp.updateDisplay()
def helpbuttonPressed(event) :
IJ.showMessage("TO DO")
def newsetPressed(event) :
gd0.dispose()
self.__settings()
def alignbuttonPressed(event) :
IJ.showMessage("TO DO")
def mergebuttonPressed(event) :
IJ.showMessage("TO DO")
def saveResults() :
#if len(self.__listcellname) == 0 :
nbslices=self.__maxLife
acell=dico.values()[0]
if self.__useTime :
x = acell.getListTimes()
namex="Time_sec"
else :
x = range(1,nbslices+1)
namex = "Frame"
if not path.exists(self.__rootpath+"Results"+os.path.sep) : os.makedirs(self.__rootpath+os.path.sep+"Results"+os.path.sep, mode=0777)
tab="\t"
nl="\n"
measures=[]
headstring=""
#if self.__savemode : mode = "a"
#else : mode ="w"
mode = "a"
#for i in range(1, self.__maxLife+1) :headstring += "Slice_"+str(i)+tab
for i in range(self.__maxLife) :headstring += str(x[i])+tab
#for m in self.__measurescompl :
for m in self.__dictMeasures[dico[self.__listcellname[0]]].keys() :
f = open(self.__rootpath+"Results"+os.path.sep+m+".txt", mode)
#f.write(m+nl)
f.write(imgName+"-"+self.__time+"-"+m+"-"+namex+tab+headstring+nl)
if len(self.__listcellname) == 0 : f.write("no cells")
else :
for cellname in self.__listcellname :
linestr=cellname+tab
for measure in self.__dictMeasures[dico[cellname]][m] :
#print m, cellname, measure
linestr += str(measure)+tab
linestr+=nl
f.write(linestr)
f.close()
if self.__measuresparambool_global[0] :
m = "Latency"
f = open(self.__rootpath+"Results"+os.path.sep+m+".txt", mode)
f.write(imgName+"-"+self.__time+"-"+m+nl)
for i in range(len(self.__listcellname)) :
#if latencies[i][0] : line=self.__listcellname[i]+"\t"+str(latencies[i][1])
#else : line=self.__listcellname[i]+"\t"+"NaN"
line=self.__listcellname[i]+"\t"+str(latencies[i][1])
line+=nl
f.write(line)
f.close()
#
# ----------- main measures dialog -------------------------
#
# Allows the user to choose the measures to make, etc..
measureslabels_indep=["MaxFeret","MinFeret","AngleFeret","XFeret","YFeret","Area","Angle","Major","Minor","Solidity","AR","Round","Circ","XC","YC","FerCoord","FerAxis","MidAxis"]
measureslabels_dep=["Mean","StdDev","IntDen","Kurt","Skew","XM","YM","Fprofil","MidProfil","NFoci","ListFoci","ListAreaFoci","ListPeaksFoci","ListMeanFoci"]
measureslabels_global=["Latency", "velocity", "cumulatedDist"]
measureslabels_dep_tabonly=set(["MidAxis","FerCoord","FerAxis","Fprofil","MidProfil","ListFoci","ListAreaFoci","ListPeaksFoci","ListMeanFoci"])
ens_measures_global=set(measureslabels_global)
ens_measures_indep=set(measureslabels_indep)
ens_measures_dep=set(measureslabels_dep)
measureslabels=[]
for label in measureslabels_indep :
measureslabels.append(label)
for label in measureslabels_dep :
measureslabels.append(label)
#self.__defaultmeasures=[False for i in range(len(measureslabels))]
#self.__defaultmeasures_global=[False for i in range(len(measureslabels_global))]
gdmeasures=NonBlockingGenericDialog("MeasuresChoice")
gdmeasures.setFont(Font("Courrier", 1, 10))
gdmeasures.addMessage("******* TIME SETTINGS *******")
gdmeasures.addCheckbox("Only starting at begining :", self.__onlystart) # 1 only start
gdmeasures.addNumericField("Minimal Lifetime : ",self.__minLife,0)
gdmeasures.addNumericField("Maximal Lifetime : ",self.__maxLife,0)
#gdmeasures.addNumericField("Maximal Lifetime : ",self.__img.getImageStackSize(),0)
gdmeasures.addCheckbox("x axis in seconds", self.__useTime) # 2 use time
gdmeasures.addMessage("")
gdmeasures.addMessage("")
gdmeasures.addMessage("Choose the measures to make on the cells : ")
gdmeasures.addMessage("******* TIME MEASURES *******")
gdmeasures.addCheckboxGroup(4,8,measureslabels,self.__defaultmeasures)
gdmeasures.addMessage("")
gdmeasures.addMessage("******* GLOBAL MEASURES *******")
gdmeasures.addMessage("PLEASE : If you have selected movement parameters you MUST to select XC and YC !")
gdmeasures.addCheckboxGroup(3,1,measureslabels_global,self.__defaultmeasures_global)
gdmeasures.addNumericField("Noise value for maxima finder: ",self.__noise,0)
gdmeasures.addMessage("")
gdmeasures.addMessage("******* OPTIONS *******")
gdmeasures.addCheckbox("Select the cells in next dialog ?", self.__onlyselect) # 3 only select
gdmeasures.addCheckbox("Save results to text files ?", self.__savetables) # 4 save files
#gdmeasures.addCheckbox("Append mode ?", self.__savemode) # 5 append mode
gdmeasures.addCheckbox("Analyse in batch mode ?", self.__batchanalyse) # 6 analysis batch mode
gdmeasures.addCheckbox("Update overlay ?", self.__updateoverlay) # 7 update overlay
gdmeasures.addMessage("")
gdmeasures.addMessage("")
help_panel=Panel()
helpbutton=Button("HELP")
helpbutton.actionPerformed = helpbuttonPressed
help_panel.add(helpbutton)
gdmeasures.addPanel(help_panel)
gdmeasures.hideCancelButton()
if not self.__batchanalyse :
gdmeasures.showDialog()
self.__onlystart=gdmeasures.getNextBoolean() # 1 only start
self.__minLife=gdmeasures.getNextNumber()
self.__maxLife=gdmeasures.getNextNumber()
self.__useTime=gdmeasures.getNextBoolean() # 2 use time
self.__measuresparambool=[]
self.__measuresparambool_global=[]
for i in range(len(measureslabels)) :
self.__measuresparambool.append(gdmeasures.getNextBoolean())
self.__defaultmeasures[i]=self.__measuresparambool[-1]
for i in range(len(measureslabels_global)) :
self.__measuresparambool_global.append(gdmeasures.getNextBoolean())
self.__defaultmeasures_global[i] = self.__measuresparambool_global[i]
self.__noise=gdmeasures.getNextNumber()
self.__onlyselect=gdmeasures.getNextBoolean() # 3 only select
self.__savetables = gdmeasures.getNextBoolean() # 4 save files
#self.__savemode = gdmeasures.getNextBoolean() # 5 append mode
self.__batchanalyse = gdmeasures.getNextBoolean() # 6 analyse mode
self.__updateoverlay = gdmeasures.getNextBoolean() # 7 update overlay
# we update a list of all cells that have a lifetime corresponding to what the user chose.
if len (self.__allcells) == 0 :
for cellname in dico.keys() :
if dico[cellname].getLifeTime()>=self.__minLife : #and dico[cellname].getLifeTime()<=self.__maxLife :
if self.__onlystart :
if dico[cellname].getSlideInit()<2 : self.__allcells.append(cellname)
else : self.__allcells.append(cellname)
if self.__noise == 0 : self.__noise = None
if self.__batchanalyse : self.__onlyselect = False
if self.__onlyselect :
try :
self.__gw
except AttributeError :
if not path.exists(self.__pathdir+"Selected-Cells"+os.path.sep) : os.makedirs(self.__pathdir+os.path.sep+"Selected-Cells"+os.path.sep, mode=0777)
self.__gw = CellsSelection()
self.__gw.setTitle(imgName)
self.__gw.run(self.__allcells, self.__pathdir+"ROIs"+os.path.sep)
self.__gw.show()
self.__gw.setSelected(self.__allcells)
while not self.__gw.oked and self.__gw.isShowing() :
self.__gw.setLabel("Validate selection with OK !!")
self.__listcellname = list(self.__gw.getSelected())
self.__gw.resetok()
self.__gw.setLabel("...")
self.__gw.hide()
else :
if self.__gw.getTitle() == imgName :
self.__gw.show()
self.__gw.setSelected(self.__listcellname)
self.__listcellname[:]=[]
while not self.__gw.oked and self.__gw.isShowing() :
self.__gw.setLabel("Validate selection with OK !!")
self.__listcellname = list(self.__gw.getSelected())
self.__gw.resetok()
self.__gw.setLabel("...")
self.__gw.hide()
else :
self.__gw.dispose()
if not path.exists(self.__pathdir+"Selected-Cells"+os.path.sep) : os.makedirs(self.__pathdir+os.path.sep+"Selected-Cells"+os.path.sep, mode=0777)
self.__gw = CellsSelection()
self.__gw.setTitle(imgName)
self.__gw.run(self.__allcells, self.__pathdir+"ROIs"+os.path.sep)
self.__gw.show()
self.__gw.setSelected(self.__allcells)
self.__listcellname[:]=[]
while not self.__gw.oked and self.__gw.isShowing() :
self.__gw.setLabel("Validate selection with OK !!")
self.__listcellname = list(self.__gw.getSelected())
self.__gw.resetok()
self.__gw.setLabel("...")
self.__gw.hide()
filestodelet=glob.glob(self.__pathdir+"Selected-Cells"+os.path.sep+"*.cell")
for f in filestodelet : os.remove(f)
for cell in self.__listcellname :
sourcestr = self.__pathdir+"Cells"+os.path.sep+cell+".cell"
deststr = self.__pathdir+"Selected-Cells"+os.path.sep+cell+".cell"
#os.system("copy "+sourcestr+", "+deststr)
#shutil.copy(self.__pathdir+"Cells"+os.path.sep+cell+".cell",self.__pathdir+"Selected-Cells"+os.path.sep+cell+".cell")
shutil.copy(sourcestr,deststr)
self.__dictNcells[imgName] = len(self.__listcellname)
else :
self.__listcellname = list(self.__allcells)
self.__dictNcells[imgName] = len(self.__listcellname)
if len(self.__listcellname) == 0 :
self.__dictNcells[imgName] = 0
return False
self.__img.hide()
# we make the measures.
for i in range(len(measureslabels)) :
IJ.showProgress(i, len(measureslabels))
if self.__measuresparambool[i]==True :
self.__measurescompl.append(measureslabels[i])
if (measureslabels[i] in measureslabels_dep_tabonly)==False :
self.__measures.append(measureslabels[i])
if (i<18) and (measureslabels[i] in ens_measures_indep) :
self.__measureAll(self.__img,measureslabels[i],False, imgName, self.__noise)
ens_measures_indep.discard(measureslabels[i])
if i>=18 :
self.__measureAll(self.__img,measureslabels[i],True, imgName, self.__noise)
if self.__measuresparambool_global[0] : # calculate latency
latencies=[]
for i in range(len(self.__listcellname)) :
IJ.showProgress(i, len(self.__listcellname))
latencies.append(self.latencie(self.__listcellname[i], self.__img, imgName, self.__useTime))
if self.__measuresparambool_global[1] : # calculate velocity
self.__measures.append("velocity")
#velocities=[]
for i in range(len(self.__listcellname)) :
IJ.showProgress(i, len(self.__listcellname))
self.__measureVelocity(self.__img,imgName)
if self.__measuresparambool_global[2] : # calculate cumulatedDistance
self.__measures.append("cumulatedDist")
#velocities=[]
for i in range(len(self.__listcellname)) :
IJ.showProgress(i, len(self.__listcellname))
self.__measurecumulDist(self.__img,imgName)
self.__img.show()
self.__img.getProcessor().resetThreshold()
if self.__updateoverlay :
if self.__img.getOverlay() is not None : self.__img.getOverlay().clear()
outputrois=[]
cellnames=[]
self.__img.hide()
for cellname in self.__listcellname :
for r in dico[cellname].getListRoi():
if isinstance(r,Roi) :
pos=r.getPosition()
#print "MC overlay", cellname, r.getName(), pos
#r.setPosition(0)
#overlay.add(r)
outputrois.append(r)
if "cell" in r.getName() : cellnames.append(r.getName())
else : cellnames.append(str(pos)+"-"+cellname)
#print cellnames[-1]
rm = RoiManager.getInstance()
if (rm==None): rm = RoiManager()
rm.show()
self.__img.show()
IJ.selectWindow(self.__img.getTitle())
rm.runCommand("reset")
for i in range(len(outputrois)) :
outputrois[i].setName(cellnames[i])
rm.addRoi(outputrois[i])
rm.select(rm.getCount()-1)
rm.runCommand("Rename", cellnames[i])
IJ.run("Show Overlay", "")
rm.runCommand("UseNames", "true")
rm.runCommand("Associate", "true")
IJ.run(self.__img, "Labels...", "color=red font=12 show use")
IJ.run(self.__img, "From ROI Manager", "")
rm.runCommand("Show None")
rm.runCommand("Show All")
# ----------- batch analyse ------------------------
if self.__batchanalyse :
if self.__savetables : saveResults()
self.__dictMeasures.clear()
self.__allcells[:]=[]
self.__measurescompl[:]=[]
self.__measures[:]=[]
return False
# ---------- display methodes dialog ----------------
# Allows the user to choose how to see the results of the measures.
gd0=NonBlockingGenericDialog("Display")
gd0.addMessage("How do you want to see the results ?")
panel0=Panel()
diagrambutton=Button("Diagram")
diagrambutton.actionPerformed = diagrambuttonPressed
panel0.add(diagrambutton)
graphbutton=Button("Graph")
graphbutton.actionPerformed = graphbuttonPressed
panel0.add(graphbutton)
tabbutton=Button("Tab")
tabbutton.actionPerformed = tabbuttonPressed
panel0.add(tabbutton)
gd0.addPanel(panel0)
gd0.addCheckbox("Analyse next stack ?", self.__nextstack)
gd0.hideCancelButton()
gd0.showDialog()
self.__nextstack = gd0.getNextBoolean()
# ---------- save tables ---------------------------
if self.__savetables : saveResults()
# --------- re-start analysis -------------------
self.__dictMeasures.clear()
#self.__listcellname[:]=[]
self.__allcells[:]=[]
self.__measurescompl[:]=[]
self.__measures[:]=[]
if self.__nextstack : return False
else : return True
def __ImportCells(self, imagesnames) :
#self.__dictCells[imgName]={}
rm = RoiManager.getInstance()
if (rm==None): rm = RoiManager()
rm.runCommand("reset")
listpaths = []
listfilescells=[]
if self.__optionImages :
IJ.showMessage("Select the folder 'Cells' containing the cells to import")
selectdir=IJ.getDirectory("image")
selectdir=IJ.getDirectory("")
listfilescells.extend(glob.glob(selectdir+os.path.sep+"*"))
listpaths.append("")
else :
IJ.showMessage("Select the text file containing the list cell paths (listpaths.txt)")
selectdir=IJ.getDirectory("current")
frame = Frame("Text file settings ?")
fd = FileDialog(frame)
fd.setDirectory(selectdir)
fd.show()
selectdir = fd.getDirectory()
textfile = fd.getFile()
fichier = open(selectdir+textfile,"r")
listpaths=[ glob.glob(f.split("\n")[0]+"Selected-Cells"+os.path.sep+"*") for f in fichier.readlines()]
#for f in templist :
# listpaths.append(f.split("\n")+"Cells")
listfilescells.append("")
if listfilescells[0]=="" : importmode = True
else : importmode = False
for j in range(len(listpaths)) :
self.__dictCells[imagesnames[j]]={}
if importmode : listfilescells = listpaths[j]
pathtemp = []
for cellfile in listfilescells :
filetemp = open(cellfile,"r")
linestemp=filetemp.readlines()
for line in linestemp :
params=line.split("=")
values=params[1].split("\n")
if params[0] == "NAMECELL" :
celltemp=Bacteria_Cell(str(values[0]))
self.__dictCells[imagesnames[j]][values[0]]=celltemp
self.__dictMeasures[self.__dictCells[imagesnames[j]][values[0]]]={}
if params[0] == "PATHROIS" :
pathtemp.append(str(values[0]))
if params[0] == "NSLICES" :
for i in range(int(values[0])) :
celltemp.getListRoi().append("")
if params[0] == "SLICEINIT" :
celltemp.setSlideInit(int(values[0]))
for i in range(int(values[0])-2) :
celltemp.setRoi("NOT HERE YET",i)
if params[0] == "SLICEEND" :
celltemp.setSlideEnd(int(values[0]))
for i in range(int(values[0])) :
celltemp.setRoi("LOST",i)
if params[0] == "COLOR" :
colorstemp=values[0].split(";")
celltemp.setColor(Color(int(colorstemp[0]),int(colorstemp[1]),int(colorstemp[2])))
indiceroi=0
ind=0
tempimp = WindowManager.getImage(imagesnames[j])
if tempimp is not None :
IJ.selectWindow(imagesnames[j])
tempimp.show()
else :
if imagesnames[j][-4:]==".tif" :
IJ.selectWindow(imagesnames[j][:-4])
tempimp = IJ.getImage()
else :
IJ.selectWindow(imagesnames[j]+".tif")
tempimp = IJ.getImage()
rm.runCommand("reset")
for cellname in self.__dictCells[imagesnames[j]].keys() :
rm.runCommand("Open", pathtemp[ind])
ind+=1
nbtemp=self.__dictCells[imagesnames[j]][cellname].getLifeTime()
for i in range(nbtemp) :
rm.select(tempimp, indiceroi)
roi=rm.getSelectedRoisAsArray()[0]
self.__dictCells[imagesnames[j]][cellname].setRoi(roi,i+self.__dictCells[imagesnames[j]][cellname].getSlideInit()-1)
indiceroi+=1
IJ.run("Show Overlay", "")
rm.runCommand("UseNames", "true")
rm.runCommand("Associate", "true")
IJ.run(tempimp, "Labels...", "color=red font=12 show use")
if rm.getCount()>0 : IJ.run(tempimp, "From ROI Manager", "")
rm.runCommand("Show None")
rm.runCommand("Show All")
roipath = os.path.split(pathtemp[0])[0]+os.path.sep
rootpath = roipath.rsplit(os.path.sep, 2)[0]+os.path.sep
self.__listpaths[j] = rootpath
self.__rootpath=rootpath
from ij import IJ
from ij.gui import OvalRoi
from ij.plugin.frame import RoiManager
imp = IJ.getImage()
rm = RoiManager() # instantiate manager # throws exception if it doesn't exist
#rm = RoiManager.getInstance() # if manager exists
roi = OvalRoi(75, 75, 50, 50); # define and add ROI
imp.setRoi(roi) # make active on image
rm.addRoi(roi) # add
rm.select(0) # select the zeroth ROI and rename it
rm.runCommand("Rename", "roi");
#----------------------------
# Some of the parameters we configure below need to have
# a reference to the model at creation. So we create an
# empty model now.
model = Model();
# Send all messages to ImageJ log window.
model.setLogger(Logger.IJ_LOGGER);
model.setPhysicalUnits(Calib.getUnit(), Calib.getTimeUnit());
#------------------------
# Prepare settings object
#------------------------
settings = Settings();
rm.select(imp,idx);
actual_roi = rm.getRoi(idx);
imp.setRoi(actual_roi);
settings.setFrom(imp);
settings.tstart = Initial_frames;
settings.tend = imp.getNFrames() - Final_frames -1;
#settings.roi = rm.getSelectedRoisAsArray();
# Configure detector - We use the Strings for the keys
settings.detectorFactory = LogDetectorFactory();
settings.detectorSettings = {
'DO_SUBPIXEL_LOCALIZATION' : Subpixel_localization,
'RADIUS' : Spot_radius,
'TARGET_CHANNEL' : 1,
'THRESHOLD' : Intensity_threshold,
'DO_MEDIAN_FILTERING' : Median_filtering,
imp2 = Generate_segmented_image(imp1, 2)
# # # # Generate ROIs by "Analyse Particles"
IJ.run(imp2, "Analyze Particles...", "size=5-Infinity pixel add exclude stack")
IJ.run("Clear Results", "")
#generating results table
ort = ResultsTable()
ort.setPrecision(1)
imp_measure = ExtractChannel(imp1, Measure_Channel)
imp_measure.show()
for i, roi in enumerate(RoiManager.getInstance().getRoisAsArray()):
roi2 = rm.getRoiIndex(roi)
rm.select(imp_measure, roi2)
stats = imp_measure.getStatistics(Measurements.MEAN | Measurements.AREA
| Measurements.FERET
| Measurements.CENTROID)
ort.incrementCounter()
ort.addValue("Compartment", (channel2_name))
ort.addValue("Mean intensity", str(stats.mean))
ort.addValue("Area", str(stats.area))
ort.addValue("X_Coordinate", str(stats.xCentroid))
ort.addValue("Y_Coordinate", str(stats.yCentroid))
time.sleep(0.5)
rm.runCommand("reset")
# segment and measure second Compartment
def segmentation(imp, spot_data, channel, diameter_init, ES_tolerance, ES_area_max, ES_ctrl_pts, ES_iteration, repeat_max):
# Open files
cal = imp.getCalibration()
manager = RoiManager.getInstance()
if manager is None:
manager = RoiManager()
# Prepare log files for output
options = IS.MEDIAN | IS.AREA | IS.MIN_MAX | IS.CENTROID | IS.PERIMETER | IS.ELLIPSE | IS.SKEWNESS
convergence = []
Sintensity = []
for spot in spot_data:
repeat = 0
flag = False
spotID = int(spot[0])
Xcenter = (float(spot[1]) / cal.pixelWidth)
Ycenter = (float(spot[2]) / cal.pixelHeight)
Quality = float(spot[3])
diameter_init = float(spot[4] / cal.pixelWidth) * 2.0
while True:
manager = RoiManager.getInstance()
if manager is None:
manager = RoiManager()
Xcurrent = int(Xcenter - diameter_init / 2.0)
Ycurrent = int(Ycenter - diameter_init / 2.0)
Dcurrent1 = int(diameter_init * (1.2 - repeat / 10.0))
Dcurrent2 = int(diameter_init * (0.8 + repeat / 10.0))
roi = OvalRoi(Xcurrent, Ycurrent, Dcurrent1, Dcurrent2)
imp.setPosition(channel)
imp.setRoi(roi)
Esnake_options1 = "target_brightness=Bright control_points=" + \
str(ES_ctrl_pts) + " gaussian_blur=0 "
Esnake_options2 = "energy_type=Contour alpha=2.0E-5 max_iterations=" + \
str(ES_iteration) + " immortal=false"
IJ.run(imp, "E-Snake", Esnake_options1 + Esnake_options2)
roi_snake = manager.getRoisAsArray()
roi_ind = len(roi_snake) - 1
stats = IS.getStatistics(
imp.getProcessor(), options, imp.getCalibration())
perimeter = roi_snake[roi_ind].getLength() * cal.pixelWidth
circularity = 4.0 * 3.1417 * (stats.area / (perimeter * perimeter))
if stats.area > 17.0 and stats.area < ES_area_max and stats.skewness < -0.01 and circularity > 0.01 and stats.minor > 2.0 and boundaries(Xcenter, Ycenter, stats.xCentroid / cal.pixelWidth, stats.yCentroid / cal.pixelHeight, ES_tolerance):
Sintensity = stats.median
convergence.append(True)
break
if stats.median > 6000 and stats.area > 17.0 and stats.area < ES_area_max:
Sintensity = stats.median
convergence.append(True)
break
elif repeat > repeat_max:
manager.select(imp, roi_ind)
manager.runCommand(imp, 'Delete')
roi = OvalRoi(Xcenter + 1.0 - diameter_init / 2.0, Ycenter +
1.0 - diameter_init / 2.0, diameter_init, diameter_init)
imp.setRoi(roi)
manager.add(imp, roi, spotID)
roi_snake.append(roi)
stats = IS.getStatistics(
imp.getProcessor(), options, imp.getCalibration())
Sintensity = stats.median
convergence.append(False)
break
else:
IJ.log('Area=' + str(stats.area) + ' Skewness=' + str(stats.skewness) +
' circularity=' + str(circularity) + ' Minor=' + str(stats.minor))
manager.select(imp, roi_ind)
manager.runCommand(imp, 'Delete')
repeat += 1
# End Spot-segmentation
# End all Spots-segmentation
manager.runCommand(imp, 'Show All')
imp.setPosition(channel)
color = imp.createImagePlus()
ip = imp.getProcessor().duplicate()
color.setProcessor("segmentation" + str(channel), ip)
color.show()
IJ.selectWindow("segmentation" + str(channel))
manager.moveRoisToOverlay(color)
spot_optimal = manager.getRoisAsArray()
manager.reset()
for i in xrange(0, len(spot_optimal)):
spot = spot_optimal[i]
spot.setStrokeWidth(2)
if convergence[i]:
spot.setStrokeColor(Color.GREEN)
else:
spot.setStrokeColor(Color.MAGENTA)
imp.setRoi(spot)
manager.add(imp, spot, i)
manager.runCommand(imp, 'Show All')
imp.setPosition(channel)
from ij import IJ
from ij.gui import OvalRoi
from ij.plugin.frame import RoiManager
imp = IJ.getImage()
rm = RoiManager() # instantiate manager # throws exception if it doesn't exist
#rm = RoiManager.getInstance() # if manager exists
roi = OvalRoi(75, 75, 50, 50)
# define and add ROI
imp.setRoi(roi) # make active on image
rm.addRoi(roi) # add
rm.select(0) # select the zeroth ROI and rename it
rm.runCommand("Rename", "roi")
def tethered_cell(image_path, frame_number=100, frame_rate=100.0, CCW=1):
"""
parameter setting; frame rate (frame/sec)
CCW = 1 : the motor rotation direction and the cell rotation direction on the image are same
CCW = -1: the motor rotation direction and the cell rotation direction on the image are different
"""
opener = Opener()
imp = opener.openImage(image_path)
image_slice_number = imp.getNSlices()
rm = RoiManager().getInstance()
if image_slice_number < frame_number: # too short movie
IJ.log('Number of frame of the movie is fewer than the number of frame that you selected')
return False
# create result directory
result_path = image_path + '_tethered_cell_result'
if os.path.lexists(result_path) is False:
os.mkdir(result_path)
#z projection; standard deviation, tethered cell shorws circle
IJ.run(imp, 'Subtract Background...', 'rolling=5 light stack')
IJ.run(imp, 'Median...', 'radius=2 stack')
IJ.run(imp, 'Z Project...', 'stop=500 projection=[Standard Deviation]')
zimp = IJ.getImage()
IJ.saveAs(zimp, 'bmp', os.path.join(result_path,'STD_DEV.bmp'))
# pick up tethered cell
IJ.setAutoThreshold(zimp, 'MaxEntropy dark')
IJ.run(zimp, 'Convert to Mask', '')
IJ.run('Set Measurements...', "area centroid bounding shape feret's limit redirect=None decimal=3")
IJ.run(zimp, 'Analyze Particles...', 'size=30-Infinity circularity=0.88-1.00 show=Nothing display exclude clear include')
zrt = ResultsTable.getResultsTable()
IJ.saveAs('Results', os.path.join(result_path,'RoiInfo.csv'))
#tcX and tcY are xy coordinates of tethered cell, tcdia is outer diameter of rotating tethered cell
#add ROI into stack image
for i in range(zrt.getCounter()):
tcX = zrt.getValue('X', i)
tcY = zrt.getValue('Y', i)
tcdia = zrt.getValue('Feret', i)
rm.add(imp, OvalRoi(tcX - tcdia/2.0, tcY - tcdia/2.0, tcdia + 1, tcdia + 1), i)
#calculate rotation speed by ellipse fitting
IJ.setAutoThreshold(imp, 'Li')
for roi_number in range(rm.getCount()):
t = []
XM = []
YM = []
theta = []
rotation_speed = []
area = []
imp.setRoi(rm.getRoi(roi_number))
cropped_imp = Duplicator().run(imp)
IJ.run('Set Measurements...', 'area mean center fit limit redirect=None decimal=3')
rm.select(roi_number)
rt = rm.multiMeasure(imp)
# check cell is present while analysis. Don't a cell gose anywhare?
for i in range(frame_number):
area.append(rt.getValue('Area1', i))
if 0 in area:
continue
for i in range(frame_number):
t.append((1/frame_rate)*i)
XM.append(rt.getValue('XM1', i))
YM.append(rt.getValue('YM1', i))
theta.append(rt.getValue('Angle1', i)/180.0*math.pi) # convert to radian
if i == 0:
rotation_speed.append(0)
else:
# phase treatment, theta should be -pi ~ pi
temp_rotation_speed = [theta[i] - theta[i-1],
theta[i] - theta[i-1] + math.pi,
theta[i] - theta[i-1] - math.pi,
theta[i] - theta[i-1] + 2*math.pi,
theta[i] - theta[i-1] - 2*math.pi]
temp_rotation_speed = sorted(temp_rotation_speed, key = lambda x :abs(x) )[0]
rotation_speed.append(CCW*temp_rotation_speed/(2.0*math.pi)*frame_rate)
# write csv
# earch columns indicate 1:index, 2:time(sec), 3:X-coordinate of center of mass(pixel), 4:Y-coordinate of center of mass (pixel), 5:Angle(Radian), 6:Rotation Speed(Hz)
with open(os.path.join(result_path,'Roi' + str(roi_number) + '.csv'), 'w') as f:
writer = csv.writer(f)
writer.writerow(['Index', 'time(s)', 'X', 'Y', 'Angle(rad)', 'Rotation Speed(Hz)'])
for i in range(len(t)):
writer.writerow([i, t[i], XM[i], YM[i], theta[i], rotation_speed[i]])
# plot x-y, t-x, t-y, t-rotation speed, save plot as bmp
plotRotation(roi_number, result_path, t, XM, YM, rotation_speed)
IJ.saveAs(cropped_imp, 'tiff', os.path.join(result_path,'Roi' + str(roi_number) + '.tiff'))
rt.reset()
# get analysis date and time
dt = datetime.datetime.today()
dtstr = dt.strftime('%Y-%m-%d %H:%M:%S')
# wtite analysis setting
with open(os.path.join(result_path,'analysis_setting.csv'), 'w') as f:
writer = csv.writer(f)
writer.writerow(['Analysis Date','frame number','frame rate','CCW direction', 'Method','Auto threshold', 'Subtruct Background', 'Median filter'])
writer.writerow([dtstr, frame_number, frame_rate, CCW, 'Ellipse', 'Li', '5.0', '2'])
# save roi
if rm.getCount() != 0:
rm.runCommand('Save', os.path.join(result_path, 'Roi.zip'))
zimp.close()
imp.close()
rm.close()
zrt.reset()
print "ATP, Exclude edges"
else:
IJ.run(
"Analyze Particles...", "size=" + str(uGsize) +
"-Infinity pixel circularity=" + str(uGshape) + "-" +
str(uGshapemax) + " show=[Overlay Masks] clear summarize add")
print "ATP, include all"
# ROI management
rm.runCommand("Combine")
rm.runCommand("Add")
rct = rm.getCount()
fullTitle = ImagePlus.getTitle(thisImage)
shortTitle = ImagePlus.getShortTitle(thisImage)
IJ.run("Invert LUT") ### Invert LUT
rm.rename(rct - 1, str(shortTitle))
rm.select(rct - 1)
if image == newPaths[0]:
rm.runCommand(
"Save",
analysisOut + File.separatorChar + "ROIindividual_wt" + ".zip")
if image == newPaths[1]:
rm.runCommand(
"Save",
analysisOut + File.separatorChar + "ROIindividual_dic" + ".zip")
if image == newPaths[2]:
rm.runCommand(
"Save",
analysisOut + File.separatorChar + "ROIindividual_mut" + ".zip")
if image == newPaths[3]:
rm.runCommand(
"Save",
def run():
IJ.run("Close All", "")
IJ.log("\\Clear")
IJ.log("Find_close_peaks")
imp = IJ.run("Bio-Formats Importer")
imp = IJ.getImage()
Channel_1, Channel_2, radius_background, sigmaSmaller, sigmaLarger, minPeakValue, min_dist = getOptions()
IJ.log("option used:" \
+ "\n" + "channel 1:" + str(Channel_1) \
+ "\n" + "channel 2:"+ str(Channel_2) \
+ "\n" + "Radius Background:"+ str(radius_background) \
+ "\n" + "Smaller Sigma:"+ str(sigmaSmaller) \
+ "\n" + "Larger Sigma:"+str(sigmaLarger) \
+ "\n" + "Min Peak Value:"+str(minPeakValue) \
+ "\n" + "Min dist between peaks:"+str(min_dist))
IJ.log("Computing Max Intensity Projection")
if imp.getDimensions()[3] > 1:
imp_max = ZProjector.run(imp,"max")
#imp_max = IJ.run("Z Project...", "projection=[Max Intensity]")
#imp_max = IJ.getImage()
else:
imp_max = imp
ip1, ip2 = extract_channel(imp_max, Channel_1, Channel_2)
imp1, imp2 = back_substraction(ip1, ip2, radius_background)
imp1.show()
imp2.show()
IJ.log("Finding Peaks")
ip1_1, ip2_1, peaks_1, peaks_2 = find_peaks(imp1, imp2, sigmaSmaller, sigmaLarger, minPeakValue)
# Create a PointRoi from the DoG peaks, for visualization
roi_1 = PointRoi(0, 0)
roi_2 = PointRoi(0, 0)
roi_3 = PointRoi(0, 0)
roi_4 = PointRoi(0, 0)
# A temporary array of integers, one per dimension the image has
p_1 = zeros(ip1_1.numDimensions(), 'i')
p_2 = zeros(ip2_1.numDimensions(), 'i')
# Load every peak as a point in the PointRoi
for peak in peaks_1:
# Read peak coordinates into an array of integers
peak.localize(p_1)
roi_1.addPoint(imp1, p_1[0], p_1[1])
for peak in peaks_2:
# Read peak coordinates into an array of integers
peak.localize(p_2)
roi_2.addPoint(imp2, p_2[0], p_2[1])
# Chose minimum distance in pixel
#min_dist = 20
for peak_1 in peaks_1:
peak_1.localize(p_1)
for peak_2 in peaks_2:
peak_2.localize(p_2)
d1 = distance(p_1, p_2)
if d1 < min_dist:
roi_3.addPoint(imp1, p_2[0], p_2[1])
break
for peak_2 in peaks_2:
peak_2.localize(p_2)
for peak_1 in peaks_1:
peak_1.localize(p_1)
d2 = distance(p_2, p_1)
if d2 < min_dist:
roi_4.addPoint(imp1, p_2[0], p_2[1])
break
rm = RoiManager.getInstance()
if not rm:
rm = RoiManager()
rm.reset()
rm.addRoi(roi_1)
rm.addRoi(roi_2)
rm.addRoi(roi_3)
rm.addRoi(roi_4)
rm.select(0)
rm.rename(0, "ROI neuron")
rm.runCommand("Set Color", "yellow")
rm.select(1)
rm.rename(1, "ROI glioma")
rm.runCommand("Set Color", "blue")
rm.select(2)
rm.rename(2, "ROI glioma touching neurons")
rm.runCommand("Set Color", "red")
rm.select(3)
rm.rename(3, "ROI neurons touching glioma")
rm.runCommand("Set Color", "green")
rm.runCommand(imp1, "Show All")
#Change distance to be in um
cal = imp.getCalibration()
min_distance = str(round((cal.pixelWidth * min_dist),1))
table = ResultsTable()
table.incrementCounter()
table.addValue("Numbers of Neuron Markers", roi_1.getCount(0))
table.addValue("Numbers of Glioma Markers", roi_2.getCount(0))
table.addValue("Numbers of Glioma within %s um of Neurons" %(min_distance), roi_3.getCount(0))
table.addValue("Numbers of Neurons within %s um of Glioma" %(min_distance), roi_4.getCount(0))
table.show("Results Analysis")
# addAndDeleteROI_.py
# Add and delete a ROI from an image
#
# Modifications
# Date Who Ver What
# ---------- --- ------ -------------------------------------------------
# 2014-10-21 JRM 0.1.00 Initial prototype
from ij import WindowManager
from ij import IJ
from ij.plugin.frame import RoiManager
raw = IJ.openImage("D:\\Data\\images\\tmp\\sis-efi-sc.png")
raw.show()
IJ.makeRectangle(0, 190, 1600, 260)
wbROI = raw.getRoi()
if (wbROI==None):
exit("you must draw region first")
print(wbROI)
rm = RoiManager()
rm.select(raw, 0)
rm.runCommand("Show All")
rm.runCommand("Draw")
print("done")
