def copyMatrixToImage2D(matrix,imageName,sizeX = -1,sizeY = -1): if sizeX == -1: sizeX = len(matrix) if sizeY == -1: sizeY = len(matrix[0]) imp = ImageStack.create(sizeX, sizeY, 1,16) processor = imp.getProcessor(1) for indexX in range(sizeX): for indexY in range(sizeY): processor.set(indexX,indexY,int(matrix[indexX][indexY])) ImagePlus(imageName, imp).show()
def run(imagefile, verbose=False):
# open image file and get a specific series
log.log(LogLevel.INFO, 'Opening Image: ' + imagefile)
imp, MetaInfo = ImportTools.openfile(imagefile)
# output of image metadata in log window
if verbose:
for k, v in MetaInfo.items():
log.log(LogLevel.INFO, str(k) + ' : ' + str(v))
log.log(LogLevel.INFO, 'File Extension : ' + MetaInfo['Extension'])
if 'ResolutionCount' in MetaInfo:
log.log(LogLevel.INFO,
'Resolution Count : ' + str(MetaInfo['ResolutionCount']))
if 'SeriesCount' in MetaInfo:
log.log(LogLevel.INFO,
'SeriesCount : ' + str(MetaInfo['SeriesCount']))
if 'SizeC' in MetaInfo:
log.log(LogLevel.INFO, 'Channel Count : ' + str(MetaInfo['SizeC']))
# do the processing
log.log(LogLevel.INFO, 'Start Processing ...')
# create empty image list
imglist_t_c = []
imglist_t = []
numch = imp.getNChannels()
# do the processing
for t in range(MetaInfo['SizeT']):
# get the timepoint
imp_t = getstackfrom5d(imp,
MetaInfo,
firstC=1,
lastC=MetaInfo['SizeC'],
firstZ=1,
lastZ=MetaInfo['SizeZ'],
firstT=t + 1,
lastT=t + 1)
# calc the focus values for the different channels
for ch in range(numch):
# get a stack for a channel
imp_t_c = getstackfrom5d(imp_t,
MetaInfo,
firstC=ch + 1,
lastC=ch + 1,
firstZ=1,
lastZ=MetaInfo['SizeZ'],
firstT=1,
lastT=1)
# create a name for the plane
#name = os.path.basename(imagefile) + 'T=' + str(t+1) + '_CH=' + str(ch+1)
name = 'T=' + str(t + 1) + '_CH=' + str(ch + 1)
# get the plane with the bst focus to the current timepoint and current channel
sp_c, fv, fv_max, fv_max_index = calc_focus(imp_t_c, name)
log.log(LogLevel.INFO, 'Processing TimePoint : ' + str(t + 1))
log.log(LogLevel.INFO, 'Processing Channel : ' + str(ch + 1))
log.log(LogLevel.INFO, 'Max. Value : ' + str(fv_max))
log.log(LogLevel.INFO,
'Max. Value Slice : ' + str(fv_max_index))
# set correct image properties
sp_c = MiscTools.setproperties(sp_c,
scaleX=MetaInfo['ScaleX'],
scaleY=MetaInfo['ScaleY'],
scaleZ=MetaInfo['ScaleZ'],
unit='micron',
sizeC=1,
sizeZ=1,
sizeT=1)
imglist_t_c.append(sp_c)
print 'List CH Stacks :', len(imglist_t_c)
for i in range(len(imglist_t_c)):
print str(i) + ' : ', type(imglist_t_c[i])
# in case of more than one channel use an jarray
if numch > 1:
# create an array
imgarray_c = jarray.array(imglist_t_c, ImagePlus)
# create an ImageStack from the array
print 'Type imgarray_c : ', type(imgarray_c)
for i in range(numch):
print type(imgarray_c[i])
imgstack_c = ImageStack.create(imgarray_c)
# create an ImagePlus object from the jarray
new_name = os.path.splitext(os.path.basename(imagefile))[0]
imp_sp_c = ImagePlus(new_name + '_SHARPEST_C', imgstack_c)
# in case of exactly one channel directly use the ImgPlus
if numch == 1:
imp_sp_c = imglist_t_c[0]
# set correct image properties for the final image
imp_sp_c = MiscTools.setproperties(imp_sp_c,
scaleX=MetaInfo['ScaleX'],
scaleY=MetaInfo['ScaleY'],
scaleZ=MetaInfo['ScaleZ'],
unit='micron',
sizeC=numch,
sizeZ=1,
sizeT=1)
# concatenate the timepoints
imglist_t.append(imp_sp_c)
if numch > 1:
# create an array
imgarray = jarray.array(imglist_t, ImagePlus)
# create an ImageStack from the array
imgstack = ImageStack.create(imgarray)
# create an ImagePlus object from the jarray
new_name = os.path.splitext(os.path.basename(imagefile))[0]
imp_sp_t = ImagePlus(new_name + '_SHARPEST_CT', imgstack)
# in case of exactly one channel directly use the ImgPlus
if numch == 1:
imp_sp_t = imglist_t[0]
return imp_sp_t
nucIp, cmIp = openStitched(group, rowNo, colNo) if stitched else openUnstitched(group)
if nucIp is None or cmIp is None: continue
nucStack, cmStack = nucIp.getStack(), cmIp.getStack()
nucIpMedian = calcMedian(nucIp)
IJ.run(nucIp, "Subtract...", "value=" + str(nucIpMedian) + " stack")
nucIpForMeasure = nucIp.duplicate()
nucMaskIp = generateNucleusMask(nucIp, nucMethod, analyzeNucStack, nucMinSize)
cmIp, cmMaskIp = generateCardiomyocyteMask(cmIp, cmMethod, analyzeCmStack, cmMinSize, brightfield)
nucMaskIp.show()
nucIpForMeasure.show()
rm = RoiManager.getRoiManager()
rm.runCommand("Associate", "true")
rm.runCommand("Show All without labels")
#This fits ellipses to the nuclear mask
IJ.run(nucMaskIp, "Ellipse Split", "binary=[Use standard watershed] add_to_manager add_to_results_table merge_when_relativ_overlap_larger_than_threshold overlap=95 major=0-Infinity minor=0-Infinity aspect=1-Infinity stack")
nucMaskStack2 = ImageStack.create(nucIp.width, nucIp.height, nucStack.size(), cmStack.getProcessor(1).getBitDepth())
rois = rm.getRoisAsArray()
#This loop is used to setup an image for the voronoi diagram nucelar splitting, setting pixels which
#are contested between two neighboring nuclei to 0
for roi in rois:
z = roi.getZPosition()- 1
try:
for p in roi.getContainedPoints():
try:
val = nucMaskStack2.getVoxel(p.x, p.y, z)
if val == 1: pass
elif val == 2:
nucMaskStack2.setVoxel(p.x, p.y, z, 1)
else: nucMaskStack2.setVoxel(p.x, p.y, z, 2)
except: pass
except: pass
def run(imagefile, verbose=False):
# open image file and get a specific series
log.log(LogLevel.INFO, 'Opening Image: ' + imagefile)
imp, MetaInfo = ImportTools.openfile(imagefile)
# output of image metadata in log window
if verbose:
for k, v in MetaInfo.items():
log.log(LogLevel.INFO, str(k) + ' : ' + str(v))
log.log(LogLevel.INFO, 'File Extension : ' + MetaInfo['Extension'])
if 'ResolutionCount' in MetaInfo:
log.log(LogLevel.INFO,
'Resolution Count : ' + str(MetaInfo['ResolutionCount']))
if 'SeriesCount' in MetaInfo:
log.log(LogLevel.INFO,
'SeriesCount : ' + str(MetaInfo['SeriesCount']))
if 'SizeC' in MetaInfo:
log.log(LogLevel.INFO, 'Channel Count : ' + str(MetaInfo['SizeC']))
# do the processing
log.log(LogLevel.INFO, 'Start Processing ...')
# create empty image list
imglist = []
numch = imp.getNChannels()
# do the processing
for ch in range(numch):
# get a channel
imp_c = MiscTools.splitchannel(imp, ch)
name = os.path.basename(imagefile) + '_CH=' + str(ch)
sp, fv, fv_max, fv_max_index = calc_focus(imp_c, name)
log.log(LogLevel.INFO, 'Processing Channel : ' + str(ch))
log.log(LogLevel.INFO, 'Max. Value : ' + str(fv_max))
log.log(LogLevel.INFO, 'Max. Value Slice : ' + str(fv_max_index))
# set correct image properties
sp = MiscTools.setproperties(sp,
scaleX=MetaInfo['ScaleX'],
scaleY=MetaInfo['ScaleY'],
scaleZ=MetaInfo['ScaleZ'],
unit='micron',
sizeC=1,
sizeZ=1,
sizeT=1)
imglist.append(sp)
# in case of more than one channel use an jarray
if numch > 1:
# create an array
imgarray = jarray.array(imglist, ImagePlus)
# create an ImageStack from the array
imgstack = ImageStack.create(imgarray)
# create an ImagePlus object from the jarray
new_name = os.path.splitext(os.path.basename(imagefile))[0]
imp_sp = ImagePlus(new_name + '_SHARPEST', imgstack)
# ic case of exactly one channel directly use the ImgPlus
if numch == 1:
imp_sp = imglist[0]
# set correct image properties for the final image
imp_sp = MiscTools.setproperties(imp_sp,
scaleX=MetaInfo['ScaleX'],
scaleY=MetaInfo['ScaleY'],
scaleZ=MetaInfo['ScaleZ'],
unit='micron',
sizeC=numch,
sizeZ=1,
sizeT=1)
return imp_sp
num_window_x = int(round(width/width_sub)) #int(width-width_sub+1)
num_window_y = int(round(height/width_sub)) #int(height-width_sub+1)
center_px = int(round(width_sub/2))
new_rois = []
for i in range(0,num_window_x):
for j in range(0,num_window_y):
new_roi = Roi(i*width_sub, j*width_sub, width_sub, width_sub)
new_rois.append(new_roi)
for new_roi in new_rois:
rm.addRoi(new_roi)
#new_img = IJ.createHyperStack("Time Correlation",width,height,1,1,num_frames, 32)
result_stack = ImageStack.create(width,height, max_cycle_length, 32)
#empty = imp2.getProcessor().createProcessor(width, height)
#for i in range(max_cycle_length):
#result_stack.addSlice("",empty)
for i, roi in enumerate(rm.getRoisAsArray()):
assert roi.getTypeAsString() == 'Rectangle', "ROI needs to be a rectangle"
x_pos = roi.getPolygon().xpoints[0] + int(round(width_sub/2))
y_pos = roi.getPolygon().ypoints[0] + int(round(width_sub/2))
imp3 = imp2.duplicate()
imp3.show()
#imp3 = IJ.getImage()
imp3.setRoi(roi)
IJ.run(imp3, "Crop", "")
