def maxProject(image, chan):
proj = ShortProcessor(image.getWidth(), image.getHeight())
stack = image.getStack()
for z in range(1, imp.getNSlices() + 1):
ip = stack.getProcessor(image.getStackIndex(chan, z, 1))
proj.copyBits(ip, 0, 0, Blitter.MAX)
return proj
def extract_stack_under_arealist():
# Check that a Display is open
display = Display.getFront()
if display is None:
IJ.log("Open a TrakEM2 Display first!")
return
# Check that an AreaList is selected and active:
ali = display.getActive()
if ali is None or not isinstance(ali, AreaList):
IJ.log("Please select an AreaList first!")
return
# Get the range of layers to which ali paints:
ls = display.getLayerSet()
ifirst = ls.indexOf(ali.getFirstLayer())
ilast = ls.indexOf(ali.getLastLayer())
layers = display.getLayerSet().getLayers().subList(ifirst, ilast + 1)
# Create a stack with the dimensions of ali
bounds = ali.getBoundingBox()
stack = ImageStack(bounds.width, bounds.height)
# Using 16-bit. To change to 8-bit, use GRAY8 and ByteProcessor in the two lines below:
type = ImagePlus.GRAY16
ref_ip = ShortProcessor(bounds.width, bounds.height)
for layer in layers:
area = ali.getArea(layer)
z = layer.getZ()
ip = ref_ip.createProcessor(bounds.width, bounds.height)
if area is None:
stack.addSlice(str(z), bp)
continue
# Create a ROI from the area of ali at layer:
aff = ali.getAffineTransformCopy()
aff.translate(-bounds.x, -bounds.y)
roi = ShapeRoi(area.createTransformedArea(aff))
# Create a cropped snapshot of the images at layer under ali:
flat = Patch.makeFlatImage(type, layer, bounds, 1.0,
layer.getDisplayables(Patch), Color.black)
b = roi.getBounds()
flat.setRoi(roi)
ip.insert(flat.crop(), b.x, b.y)
# Clear the outside of ROI (ShapeRoi is a non-rectangular ROI type)
bimp = ImagePlus("", ip)
bimp.setRoi(roi)
ip.setValue(0)
ip.setBackgroundValue(0)
IJ.run(bimp, "Clear Outside", "")
# Accumulate slices
stack.addSlice(str(z), ip)
imp = ImagePlus("AreaList stack", stack)
imp.setCalibration(ls.getCalibrationCopy())
imp.show()
def extract_stack_under_arealist():
# Check that a Display is open
display = Display.getFront()
if display is None:
IJ.log("Open a TrakEM2 Display first!")
return
# Check that an AreaList is selected and active:
ali = display.getActive()
if ali is None or not isinstance(ali, AreaList):
IJ.log("Please select an AreaList first!")
return
# Get the range of layers to which ali paints:
ls = display.getLayerSet()
ifirst = ls.indexOf(ali.getFirstLayer())
ilast = ls.indexOf(ali.getLastLayer())
layers = display.getLayerSet().getLayers().subList(ifirst, ilast +1)
# Create a stack with the dimensions of ali
bounds = ali.getBoundingBox()
stack = ImageStack(bounds.width, bounds.height)
# Using 16-bit. To change to 8-bit, use GRAY8 and ByteProcessor in the two lines below:
type = ImagePlus.GRAY16
ref_ip = ShortProcessor(bounds.width, bounds.height)
for layer in layers:
area = ali.getArea(layer)
z = layer.getZ()
ip = ref_ip.createProcessor(bounds.width, bounds.height)
if area is None:
stack.addSlice(str(z), bp)
continue
# Create a ROI from the area of ali at layer:
aff = ali.getAffineTransformCopy()
aff.translate(-bounds.x, -bounds.y)
roi = ShapeRoi(area.createTransformedArea(aff))
# Create a cropped snapshot of the images at layer under ali:
flat = Patch.makeFlatImage(type, layer, bounds, 1.0, layer.getDisplayables(Patch), Color.black)
b = roi.getBounds()
flat.setRoi(roi)
ip.insert(flat.crop(), b.x, b.y)
# Clear the outside of ROI (ShapeRoi is a non-rectangular ROI type)
bimp = ImagePlus("", ip)
bimp.setRoi(roi)
ip.setValue(0)
ip.setBackgroundValue(0)
IJ.run(bimp, "Clear Outside", "")
# Accumulate slices
stack.addSlice(str(z), ip)
imp = ImagePlus("AreaList stack", stack)
imp.setCalibration(ls.getCalibrationCopy())
imp.show()
def __end(self, event):
if len(self.__iplist)==0 :
IJ.showMessage("", "Stack is empty")
return
self.__iplist.sort(key = lambda ip : ip.width)
self.__ipw=[ ip.getWidth() for ip in self.__iplist ]
self.__iph=[ ip.getHeight() for ip in self.__iplist ]
maxw=max(self.__ipw)
maxh=max(self.__iph)
if self.__enlarge :
resizelist = [ ip.resize(maxw, maxh, True) for ip in self.__iplist ]
else :
resizelist = []
for ip in self.__iplist :
tempip = ShortProcessor(maxw, maxh)
xloc = int(math.floor((maxw/2.00) - (ip.width/2.00)))
yloc = int(math.floor((maxh/2.00) - (ip.height/2.00)))
tempip.copyBits(ip, xloc, yloc, Blitter.COPY)
resizelist.append(tempip)
ims = ImageStack(maxw, maxh)
#for ip in resizelist : ims.addSlice("", ip)
for i in range(len(resizelist)) :
ims.addSlice(self.__labels[i], resizelist[i])
self.__impRes = ImagePlus(self.__name, ims)
self.__impRes.show()
self.__sens = [1 for i in range(len(self.__iplist)) ]
if self.__appmedian : IJ.run(self.__impRes, "Median...", "radius=1 stack")
if self.__align : self.__falign()
if self.__avg : self.__favg()
if self.__mosa : self.__fmosa()
if self.__maxfinder : self.__fmaxfinder()
if self.__fire : IJ.run(self.__impRes, "Fire", "")
if self.__measures : self.__fmeasures()
self.__sens[:] = []
self.__listrois[:] = []
self.__iplist[:] = []
self.__cellsrois[:] = []
self.__ipw[:] = []
self.__iph[:] = []
self.__init = False
def createLabelColorBar():
imp7 = ImagePlus("labelColorBar", ShortProcessor(180, 20))
ip7 = imp7.getProcessor()
pix = ip7.getPixels()
n_pixels = len(pix)
# catch width
w = imp7.getWidth()
# create a ramp gradient from left to right
for i in range(len(pix)):
pix[i] = int((i % w) / 18) + 1
# adjust min and max
ip7.setMinAndMax(0, 255)
font = Font("SansSerif", Font.PLAIN, 12)
overlay = Overlay()
for i in range(len(pix)):
roi = TextRoi(i * 18 + 2, 2, str(i + 1), font)
roi.setStrokeColor(Color.black)
overlay.add(roi)
imp7.setOverlay(overlay)
imp7.show()
IJ.run("glasbey_on_dark")
imp7 = imp7.flatten()
return imp7
def readFIBSEMdat(path, channel_index=-1, header=1024, magic_number=3555587570, asImagePlus=False, toUnsigned=True):
""" Read a file from Shan Xu's FIBSEM software, where two or more channels are interleaved.
Assumes channels are stored in 16-bit.
path: the file path to the .dat file.
channel_index: the 0-based index of the channel to parse, or -1 (default) for all.
header: defaults to a length of 1024 bytes
magic_number: defaults to that for version 8 of Shan Xu's .dat image file format.
isSigned: defaults to True, will subtract the min value when negative.
asImagePlus: return a list of ImagePlus instead of ArrayImg which is the default.
"""
ra = RandomAccessFile(path, 'r')
try:
# Check the magic number
ra.seek(0)
magic = ra.readInt() & 0xffffffff
if magic != magic_number:
msg = "magic number mismatch: v8 magic " + str(magic_number) + " != " + str(magic) + " for path:\n" + path
System.out.println(msg)
print msg
# Continue: attempt to parse the file anyway
# Read the number of channels
ra.seek(32)
numChannels = ra.readByte() & 0xff # a single byte as unsigned integer
# Parse width and height
ra.seek(100)
width = ra.readInt()
ra.seek(104)
height = ra.readInt()
# Read the whole interleaved pixel array
ra.seek(header)
bytes = zeros(width * height * 2 * numChannels, 'b') # 2 for 16-bit
ra.read(bytes)
# Parse as 16-bit array
sb = ByteBuffer.wrap(bytes).order(ByteOrder.BIG_ENDIAN).asShortBuffer()
bytes = None
finally:
ra.close()
#
shorts = zeros(width * height * numChannels, 'h')
sb.get(shorts)
sb = None
# Deinterleave channels and convert to unsigned short
# Shockingly, these values are signed shorts, not unsigned! (for first popeye2 squid volume, December 2021)
# With ASM: fast
channels = DAT_handler.deinterleave(shorts, numChannels, channel_index)
shorts = None
#
if toUnsigned:
for s in channels:
DAT_handler.toUnsigned(s)
# With python array sampling: very slow, and not just from iterating whole array once per channel
#seq = xrange(numChannels) if -1 == channel_index else [channel_index]
#channels = [shorts[i::numChannels] for i in seq]
if asImagePlus:
return [ImagePlus(str(i), ShortProcessor(width, height, s, None)) for i, s in enumerate(channels)]
else:
return [ArrayImgs.unsignedShorts(s, [width, height]) for s in channels]
def renderPreview(self, runStats):
try:
self.labelPreviewImp.close()
self.maxZPreviewImp.close()
self.maxYPreviewImp.close()
except:
print "imps already closed"
fp = ShortProcessor(len(self.labelValues), 1, self.labelValues, None)
labelerImp = ImagePlus("labeler", fp)
src2 = clij2.push(labelerImp)
dst = clij2.create(self.src)
labelerImp.close()
clij2.replaceIntensities(self.src, src2, dst)
self.labelPreviewImp = clij2.pull(dst)
previewDisplaySettings(self.labelPreviewImp, "label preview", 100,
self.cal)
try:
self.labelPreviewImp.setSlice(self.current)
except:
pass
if runStats:
clij2.statisticsOfBackgroundAndLabelledPixels(
dst, self.src, self.results)
dst2 = clij2.create(width, height, 1)
clij2.maximumZProjection(dst, dst2)
self.maxZPreviewImp = clij2.pull(dst2)
previewDisplaySettings(self.maxZPreviewImp, "maxZ label preview", 50,
self.cal)
dst3 = clij2.create(width, depth, 1)
clij2.maximumYProjection(dst, dst3)
self.maxYPreviewImp = clij2.pull(dst3)
previewDisplaySettings(self.maxYPreviewImp, "maxY label preview", 50,
self.cal)
dst3.close()
dst.close()
dst2.close()
src2.close()
labelWindow = self.labelPreviewImp.getWindow()
x = labelWindow.getLocation().x
y = labelWindow.getLocation().y
maxZPreviewWindow = self.maxZPreviewImp.getWindow()
maxZPreviewWindow.setLocation(x, y + height + 50)
maxYPreviewWindow = self.maxYPreviewImp.getWindow()
maxYPreviewWindow.setLocation(x + width / 2, y + height + 50)
print labelWindow
def getProcessor(self, n):
return ShortProcessor(self.dimensions[0], self.dimensions[1],
self.getPixels(n), None)
s = 300
pathh = "C:\\Users\\USER\\Documents\\studia\\zaklad\\EC_rainbow\\"
segmentator = WekaSegmentation()
segmentator.loadClassifier(pathh)
for i in range(len(channels)):
channel = channels[i]
pix = channel.getProcessor().getPixels()
cm = channel.getProcessor().getColorModel()
pix1 = pix[:((lim1 + s) * d1)]
pix2 = pix[((lim1 - s) * d1):((lim2 + s) * d1)]
pix3 = pix[((lim2 - s) * d1):((lim3 + s) * d1)]
pix4 = pix[((lim3 - s) * d1):]
imps = [
ImagePlus("Random", ShortProcessor(d1, (lim1 + s), pix1, cm)),
ImagePlus("Random", ShortProcessor(d1, (lim2 - lim1 + 2 * s), pix2,
cm)),
ImagePlus("Random", ShortProcessor(d1, (lim3 - lim2 + 2 * s), pix3,
cm)),
ImagePlus("Random",
ShortProcessor(d1, (dimentions[1] - lim3 + s), pix4, cm))
]
subsub = sub + "\\C" + str(i + 1)
del pix1
del pix2
del pix3
del pix4
if not os.path.exists(subsub):
os.mkdir(subsub)
pixels = []
except:
print i
rt.show(resultsName+ " with labels")
clij2.clear()
labelColorBarImp.close()
imp1Stats=imp1.getStatistics()
print imp1Stats.max
tracked=[11]*int(65535)
for i,v in enumerate(test.labelValues):
if value not in test.errors:
tracked[i]= v
else:
tracked[i]= 11
print test.labelValues
fp= ShortProcessor(len(tracked), 1,tracked , None)
labelerImp= ImagePlus("labeler", fp)
src2=clij2.push(labelerImp)
conLabeledStack=ImageStack(imp1.width, imp1.height)
if frames>1:
for nFrame in range(1,frames+1):
imp3=extractFrame(imp1, nFrame)
src=clij2.push(imp3)
dst=clij2.create(src)
clij2.replaceIntensities(src, src2, dst)
LabeledImp=clij2.pull(dst)
conLabeledStack = concatStacks( conLabeledStack, LabeledImp)
fmin.append(65536)
if f[i] > fmax[i]:
fmax[i] = f[i]
if f[i] < fmin[i]:
fmin[i] = f[i]
sphere = {'cx': cx, 'cy': cy, 'cz': cz, 'r': r, 'f': f}
spheres.append(sphere)
# Plot spheres
channelImages = []
if flat == True:
for i in range(0, channels):
imageProcessor = ShortProcessor(sx*4, sy*4)
imageStack = ImageStack(sx*4, sy*4)
for sphere in spheres:
fnorm = int(round((sphere['f'][i] - fmin[i]) / (fmax[i] - fmin[i]) * 65536.0))
x = sphere['cx'] * 4 - sphere['r']
y = sphere['cy'] * 4 - sphere['r']
d = sphere['r'] * 2
imageProcessor.setValue(fnorm)
imageProcessor.fillOval(x, y, d, d)
imageStack.addSlice(imageProcessor)
channelImages.append(ImagePlus("Rendering C" + "%i" % (i + 1), imageStack))
imageO = RGBStackMerge.mergeChannels(channelImages, False)
elif pixels == True:
for i in range(0, channels):
imageProcessor = ShortProcessor(width, height)
ranges = [[0, ((lim1 + s) * d1)], [(lim1 - s) * d1, ((lim2 + s) * d1)],
[(lim2 - s) * d1, (lim3 + s) * d1],
[(lim3 - s) * d1, dimensions[1] * d1]]
image_frags = []
for i in range(len(channels)):
channel_frags = []
channel = channels[i]
pix = channel.getProcessor().getPixels()
cm = channel.getProcessor().getColorModel()
for r in range(len(ranges)):
frag_pix = pix[ranges[r][0]:ranges[r][1]]
channel_frags.append(
ImagePlus(
"Frag",
ShortProcessor(d1, (ranges[r][1] - ranges[r][0]) / d1,
frag_pix, cm)))
image_frags.append(channel_frags)
out_frags = []
for r in range(len(ranges)):
channel_array = [
image_frags[0][r], image_frags[1][r], image_frags[2][r],
image_frags[3][r]
]
imp = VesselFinder(channel_array, classifier_path)
imp = imp.getStack()
imp = imp.getProcessor(1)
cm = imp.getColorModel()
out_frags.append(imp)
cm = out_frags[0].getColorModel()
mranges = [[0, (-s * d1)], [s * d1, (-s * d1)], [s * d1, (-s * d1)],
