def ij_macro_processor(fus_tiffs_dict, py_file_loc):
"""
Uses a specified ImageJ macro to process the fused tiffs located in the
FUSED_TIFFS directory and then saves the processed output in
PROCESSED_TIFFS directory.
"""
stitch_path = os.path.dirname(os.path.abspath(py_file_loc))
for key in fus_tiffs_dict:
if fus_tiffs_dict[key][0] == '':
logging.info('Companion file not available for' + key)
logging.info('Running imageJ macro on ' + key)
IJ.runMacroFile(stitch_path + r"\stitch_macro.ijm")
IJ.saveAs("tiff",
fus_tiffs_dict[key][1] + '/' + os.path.basename(key))
IJ.run("Close All")
else:
logging.info('Running imageJ macro on ' + key)
IJ.runMacroFile(stitch_path + r"\stitch_macro.ijm",
key + "<>" + fus_tiffs_dict[key][0])
IJ.saveAs("tiff", fus_tiffs_dict[key][1] + '/'
+ os.path.basename(key))
IJ.run("Close All")
def straighten(stackName):
'''
IJ.run("Set Measurements...", "area mean min center redirect=None decimal=3")
IJ.open(stackName)
imp = IJ.getImage()
stack = imp.getImageStack()
for i in xrange(1, imp.getNSlices()+1):
image = ImagePlus(str(i), stack.getProcessor(i))
xvals = []
yvals = []
maxvals = []
j = 0
for k in xrange(0, 512, 2):
IJ.makeRectangle(k, 0, 4, 512)
IJ.run("Measure")
table = RT.getResultsTable()
x = table.getValue("XM", 0)
y = table.getValue("YM", 0)
#maxi = IJ.getResult("Max")
table = []
xvals.append(k)
yvals.append(y)
#maxvals.append(maxi)
#if maxvals[j] == 0 and j > 0:
#yvals[j] = yvals[j-1]
j += 1
print "xvals:", xvals
print "yvals:", yvals
mr = MR()
IJ.run("Make Selection...", "freeline, "+str(xvals)+" ,"+ str(yvals))
#IJ.runMacro("makeSelection...", "freeline, "+str(xvals)+" ,"+ str(yvals));
#IJ.run("makeSelection(\"freeline\", xvals, yvals);")
#IJ.run("Straighten...", "line = 80")
'''
IJ.open(stackName)
imp = IJ.getImage()
stack = imp.getImageStack()
print imp.getNSlices()
for i in range(1, imp.getNSlices() + 1):
image = ImagePlus(str(i), stack.getProcessor(i))
IJ.runMacroFile(
"/Users/juliansegert/repos/Bio119_root_tracking/straightenOneImage.ijm"
)
newImp = WM.getCurrentImage()
fs = FileSaver(newImp)
fs.saveAsTiff(
"/Users/juliansegert/Documents/Roots/Four_root_image_stacks/Pos01/"
+ str(i) + ".tif")
newImp.close()
def straighten(stackName):
'''
IJ.run("Set Measurements...", "area mean min center redirect=None decimal=3")
IJ.open(stackName)
imp = IJ.getImage()
stack = imp.getImageStack()
for i in xrange(1, imp.getNSlices()+1):
image = ImagePlus(str(i), stack.getProcessor(i))
xvals = []
yvals = []
maxvals = []
j = 0
for k in xrange(0, 512, 2):
IJ.makeRectangle(k, 0, 4, 512)
IJ.run("Measure")
table = RT.getResultsTable()
x = table.getValue("XM", 0)
y = table.getValue("YM", 0)
#maxi = IJ.getResult("Max")
table = []
xvals.append(k)
yvals.append(y)
#maxvals.append(maxi)
#if maxvals[j] == 0 and j > 0:
#yvals[j] = yvals[j-1]
j += 1
print "xvals:", xvals
print "yvals:", yvals
mr = MR()
IJ.run("Make Selection...", "freeline, "+str(xvals)+" ,"+ str(yvals))
#IJ.runMacro("makeSelection...", "freeline, "+str(xvals)+" ,"+ str(yvals));
#IJ.run("makeSelection(\"freeline\", xvals, yvals);")
#IJ.run("Straighten...", "line = 80")
'''
IJ.open(stackName)
imp = IJ.getImage()
stack = imp.getImageStack()
print imp.getNSlices()
for i in range(1, imp.getNSlices()+1):
image = ImagePlus(str(i), stack.getProcessor(i))
IJ.runMacroFile("/Users/juliansegert/repos/Bio119_root_tracking/straightenOneImage.ijm")
newImp = WM.getCurrentImage()
fs = FileSaver(newImp)
fs.saveAsTiff("/Users/juliansegert/Documents/Roots/Four_root_image_stacks/Pos01/"+str(i)+".tif")
newImp.close()
def run_macro(script_dir, script_fname):
""" Run any IJ macro
Parameters
----------
script_dir : str
Directory of script to run
script_fname : str
Name of script to run
"""
IJ.runMacroFile(os.path.join(script_dir, script_fname))
def __calRois(self, imp, indice) :
"""
Returns the ROIs of a slice given (identified with its n°) in a stack
"""
##imp=self.__dictImages[nameimages] # IL FAUT RÉCUPÉRER L'IMAGE DU STACK !!!!!
#if self.__batch : imp.hide()
#else : imp.show()
#imp.hide()
imp.show()
if self.__batch : imp.hide()
imp.setSlice(indice)
imp.killRoi()
ip = imp.getProcessor()
bs=BackgroundSubtracter()
#if str(self.__subback) == "0" or str(self.__subback) == "1" : self.__subback = bool(int(self.__subback))
#if self.__subback == True : IJ.run(imp, "Subtract Background...", "rolling="+str(self.__radius)+" light")
if self.__subback == True : bs.rollingBallBackground(ip, self.__radius, False, True, False, True, False)
if self.__runmacro :
imp.show()
imp.setSlice(indice)
imp.updateAndDraw()
IJ.runMacroFile(self.__macropath, imp.getTitle())
imp.updateAndDraw()
#if str(self.__manthresh) == "0" or str(self.__manthresh) == "1" : self.__manthresh = bool(int(self.__manthresh))
#if self.__manthresh : IJ.setThreshold(imp, self.__minthr, self.__maxthr)
if self.__manthresh :
ip.setThreshold(self.__minthr, self.__maxthr, ImageProcessor.RED_LUT)
else : self.__setThreshold(imp, indice)
rt=ResultsTable()
pa1=ParticleAnalyzer(ParticleAnalyzer.SHOW_MASKS+ParticleAnalyzer.EXCLUDE_EDGE_PARTICLES , Measurements.AREA, rt, self.__minArea, self.__maxArea, self.__minCirc, self.__maxCirc)
pa1.setHideOutputImage(True)
pa1.analyze(imp)
masks=pa1.getOutputImage()
masks.getProcessor().erode()
masks.getProcessor().dilate()
masks.getProcessor().invertLut()
masks.getProcessor().threshold(1)
rm = RoiManager.getInstance()
if (rm==None): rm = RoiManager()
rm.runCommand("reset")
#rm.hide()
pa2=ParticleAnalyzer(ParticleAnalyzer.ADD_TO_MANAGER+ParticleAnalyzer.CLEAR_WORKSHEET+ParticleAnalyzer.EXCLUDE_EDGE_PARTICLES , Measurements.AREA, rt, self.__minArea, self.__maxArea, self.__minCirc, self.__maxCirc)
pa2.analyze(masks)
masks.close()
temparray=rm.getRoisAsArray()
for r in temparray :
tempnameroi=r.getName()
r.setPosition(indice)
r.setName(str(indice)+"-"+tempnameroi)
r.setStrokeWidth(1)
if len(self.__params) > 0 :
for k in self.__params:
#if k[0]=="Area": self.__minArea, self.__maxArea = str(k[1]), str(k[2])
if k[0]=="Area": self.__minArea, self.__maxArea = k[1], k[2]
for k in self.__params:
#if k[0]=="Circ": self.__minCirc, self.__maxCirc = str(k[1]), str(k[2])
if (k[0]=="Circ") and k[3] : self.__minCirc, self.__maxCirc = k[1], k[2]
else : self.__minCirc, self.__maxCirc = 0, 1
self.__rr.setRoisarray(temparray, imp)
self.__rr.setRange(indice, self.__params)
return self.__rr.includeRois
else : return temparray
USERNAME = myvars['username']
PASSWORD = myvars['password']
# Prototype analysis example
gateway = omeroConnect()
imageIds = getImageIds(gateway,datasetId);
imageIds.sort()
for imageId in imageIds:
# imageId = imageIds[2]
print imageId
openImagePlus(HOST,USERNAME,PASSWORD,groupId,imageId)
IJ.run("Enhance Contrast", "saturated=0.35");
#Plug Your analysis here#
IJ.runMacroFile(macroFilePath)
# Save resultant image using Bio-Formats
imp = IJ.getImage();
path = paths + imp.getTitle() + operation + ".ome.tiff";
print(path)
options = "save=[" + path + "] export compression=Uncompressed"
IJ.run(imp, "Bio-Formats Exporter", options);
imp.changes = False
imp.close()
# Upload image to OMERO
str2d = java.lang.reflect.Array.newInstance(java.lang.String,[1])
str2d [0] = path
success = uploadImage(str2d, gateway)
from ij import IJ
values = [
str(0),
r"C:\Users\John Cooper\Box Sync\Finkelstein-Matouschek\byc_data\example_byc_expts\20200221_byc_analysis\pJC069_rpn4d\image.tif",
"another path", "death", "measurement"
]
arg = ' '.join(values)
IJ.runMacroFile('runpyscript.ijm', arg)
from ij import IJ
#this code should run following the command code to search for
#new directory and create registered/stitched folder
"""
running the motion correction automatically with input directory
"""
#dir_path = getArgument()
#prepare the reference image
dir_path = "/Users/phoenix/Documents/Kwanlab/dataanalysis/discrimination/161013_try/"
imp = IJ.openImage(dir_path + "raw/161013_task3079.tif")
IJ.run(imp, "32-bit", "") #convert the image to 32 bit
ave_imp = IJ.run(imp, "Z Project...",
"projection=[Average Intensity]") #acquire average intensity
IJ.run(imp, "Close", "")
IJ.run("Save", "save=[" + dir_path +
"refFrame.tif]") #save the reference file to be used later
IJ.run(
ave_imp, "Close", ""
) #close all the files and open the reference file in the batchTurboReg_forPy.ijm file
#run the ijm (modified to a little to suit the python code
macroFileDir = "/Users/phoenix/Documents/Kwanlab/dataanalysis/batchTurboReg_forPy.ijm"
IJ.runMacroFile(macroFileDir, dir_path)
#for imageId, imageName in imageIds[1:], imageNames[1:]:
# imageId = imageIds[2]
imageId = imageIds[counter]
imageName = imageNames[counter]
print imageId, imageName
if imageName != imageNames[counter+1]:
#print("this is a new image")
#print(done)
openImagePlus(HOST,USERNAME,PASSWORD,groupId,imageId)
#print("opened image")
#IJ.run("Enhance Contrast", "saturated=0.35");
#Plug Your analysis here#
imp = w.getImage(imageName);
IJ.runMacroFile(str(macroFilePath))
#print("ran macro")
imp.close()
#print("closed image")
done.append(imageName)
counter += 1
# Save resultant image using Bio-Formats
#
#path = paths + imp.getTitle() + operation + ".ome.tiff";
#print(path)
#options = "save=" + path + " export compression=Uncompressed"
#IJ.run(imp, "Bio-Formats Exporter", options);
#imp.changes = False
#
# Upload image to OMERO
USERNAME = myvars['username']
PASSWORD = myvars['password']
# Prototype analysis example
gateway = omeroConnect()
imageIds = getImageIds(gateway,datasetId);
imageIds.sort()
#openImagePlus(HOST,USERNAME,PASSWORD,groupId,imageIds[0])
for imageId in imageIds[1:]:
# imageId = imageIds[2]
print imageId
openImagePlus(HOST,USERNAME,PASSWORD,groupId,imageId)
#IJ.run("Enhance Contrast", "saturated=0.35");
#Plug Your analysis here#
imp = IJ.getImage();
IJ.runMacroFile(str(macroFilePath))
imp.close()
# Save resultant image using Bio-Formats
#
#path = paths + imp.getTitle() + operation + ".ome.tiff";
#print(path)
#options = "save=" + path + " export compression=Uncompressed"
#IJ.run(imp, "Bio-Formats Exporter", options);
#imp.changes = False
#
# Upload image to OMERO
#str2d = java.lang.reflect.Array.newInstance(java.lang.String,[1])
#str2d [0] = path
#success = uploadImage(str2d, gateway)
USERNAME = myvars['username']
PASSWORD = myvars['password']
# Prototype analysis example
gateway = omeroConnect()
imageIds = getImageIds(gateway,datasetId);
imageIds.sort()
for imageId in imageIds:
# imageId = imageIds[2]
print imageId
openImagePlus(HOST,USERNAME,PASSWORD,groupId,imageId)
IJ.run("Enhance Contrast", "saturated=0.35");
#Plug Your analysis here#
IJ.runMacroFile(macroFilePath)
# Save resultant image using Bio-Formats
imp = IJ.getImage();
path = paths + imp.getTitle() + operation + ".ome.tiff";
print(path)
options = "save=" + path + " export compression=Uncompressed"
IJ.run(imp, "Bio-Formats Exporter", options);
imp.changes = False
imp.close()
# Upload image to OMERO
str2d = java.lang.reflect.Array.newInstance(java.lang.String,[1])
str2d [0] = path
success = uploadImage(str2d, gateway)
