def asNormalizedUnsignedByteArrayImg(interval, invert, blockRadius, n_bins,
slope, matrices, index, imp):
sp = imp.getProcessor() # ShortProcessor
# Crop to interval if needed
x = interval.min(0)
y = interval.min(1)
width = interval.max(0) - interval.min(0) + 1
height = interval.max(1) - interval.min(1) + 1
if 0 != x or 0 != y or sp.getWidth() != width or sp.getHeight(
) != height:
sp.setRoi(x, y, width, height)
sp = sp.crop()
if invert:
sp.invert()
CLAHE.run(
ImagePlus("", sp), blockRadius, n_bins, slope, None
) # far less memory requirements than NormalizeLocalContrast, and faster.
minimum, maximum = autoAdjust(sp)
# Transform and convert image to 8-bit, mapping to display range
img = ArrayImgs.unsignedShorts(
sp.getPixels(), [sp.getWidth(), sp.getHeight()])
sp = None
imp = None
# Must use linear interpolation for subpixel precision
affine = AffineTransform2D()
affine.set(matrices[index])
imgI = Views.interpolate(Views.extendZero(img),
NLinearInterpolatorFactory())
imgA = RealViews.transform(imgI, affine)
imgT = Views.zeroMin(Views.interval(imgA, img))
# Convert to 8-bit
imgMinMax = convert2(imgT,
RealUnsignedByteConverter(minimum, maximum),
UnsignedByteType,
randomAccessible=False) # use IterableInterval
aimg = ArrayImgs.unsignedBytes(Intervals.dimensionsAsLongArray(img))
# ImgUtil copies multi-threaded, which is not appropriate here as there are many other images being copied too
#ImgUtil.copy(ImgView.wrap(imgMinMax, aimg.factory()), aimg)
# Single-threaded copy
copier = createBiConsumerTypeSet(UnsignedByteType)
LoopBuilder.setImages(imgMinMax, aimg).forEachPixel(copier)
img = imgI = imgA = imgMinMax = imgT = None
return aimg
def readUnsignedShorts(path, dimensions, header=0, return_array=False, byte_order=ByteOrder.LITTLE_ENDIAN):
""" Read a file as an ArrayImg of UnsignedShortType """
size = reduce(operator.mul, dimensions)
ra = RandomAccessFile(path, 'r')
try:
if header < 0:
# Interpret from the end: useful for files with variable header lengths
# such as some types of uncompressed TIFF formats
header = ra.length() + header
ra.skipBytes(header)
bytes = zeros(size * 2, 'b')
ra.read(bytes)
shorts = zeros(size, 'h') # h is for short
ByteBuffer.wrap(bytes).order(byte_order).asShortBuffer().get(shorts)
return shorts if return_array else ArrayImgs.unsignedShorts(shorts, dimensions)
finally:
ra.close()
def twoStep(index=0):
# The current way:
img = klb.readFull(filepaths[index]) # klb_loader.get(filepaths[index])
imgE = Views.extendZero(img)
imgI = Views.interpolate(imgE, NLinearInterpolatorFactory())
imgT = RealViews.transform(imgI, cmIsotropicTransforms[index])
imgB = Views.zeroMin(Views.interval(imgT, roi[0],
roi[1])) # bounded: crop with ROI
imgBA = ArrayImgs.unsignedShorts(Intervals.dimensionsAsLongArray(imgB))
ImgUtil.copy(ImgView.wrap(imgB, imgBA.factory()), imgBA)
imgP = prepareImgForDeconvolution(
imgBA,
affine3D(fineTransformsPostROICrop[index]).inverse(),
FinalInterval([0, 0, 0], [imgB.dimension(d) - 1 for d in xrange(3)]))
# Copy transformed view into ArrayImg for best performance in deconvolution
imgA = ArrayImgs.floats(Intervals.dimensionsAsLongArray(imgP))
ImgUtil.copy(ImgView.wrap(imgP, imgA.factory()), imgA)
IL.wrap(imgA, "two step").show()
def projectLastDimension(img, showEarly=False):
"""
Project the last dimension, e.g. a 4D image becomes a 3D image,
using the provided reducing function (e.g. min, max, sum).
"""
last_dimension = img.numDimensions() - 1
# The collapsed image
imgC = ArrayImgs.unsignedShorts(
[img.dimension(d) for d in xrange(last_dimension)])
if showEarly:
showStack(
imgC,
title="projected") # show it early, will be updated progressively
if img.dimension(last_dimension) > 10:
# one by one
print "One by one"
for i in xrange(img.dimension(last_dimension)):
print i
compute(maximum(imgC, Views.hyperSlice(img, last_dimension,
i))).into(imgC)
else:
# Each sample of img3DV is a virtual vector over all time frames at that 3D coordinate:
imgV = Views.collapseReal(img)
# Reduce each vector to a single scalar, using a Converter
# The Converter class
reduce_max = makeCompositeToRealConverter(
reducer_class=Math,
reducer_method="max",
reducer_method_signature="(DD)D")
img3DC = convert(imgV, reduce_max.newInstance(),
img.randomAccess().get().getClass())
ImgUtil.copy(ImgView.wrap(imgV, img.factory()), imgC)
return imgC
def getPixels(self, n):
# 'n' is 1-based
# Target 2D array img to copy data into
aimg = ArrayImgs.unsignedShorts(self.dimensions[0:2])
# The number of slices of the 3D volume of a single timepoint
nZ = self.img4d.dimension(2)
# The slice_index if there was a single channel
slice_index = int((n - 1) / 2) # 0-based, of the whole 4D series
local_slice_index = slice_index % nZ # 0-based, of the timepoint 3D volume
timepoint_index = int(slice_index / nZ) # Z blocks
if 1 == n % 2:
# Odd slice index: image channel
fixedT = Views.hyperSlice(self.img4d, 3, timepoint_index)
fixedZ = Views.hyperSlice(fixedT, 2, local_slice_index)
w.copy(fixedZ.cursor(), aimg.cursor())
else:
# Even slice index: spheres channel
sd = SpheresData(self.kdtrees[timepoint_index], radius, inside,
outside)
volume = Views.interval(Views.raster(sd), self.dimensions3d)
plane = Views.hyperSlice(volume, 2, local_slice_index)
w.copy(plane.cursor(), aimg.cursor())
#
return aimg.update(None).getCurrentStorageArray()
from random import random
from net.imglib2.algorithm.math import ImgMath
from net.imglib2.util import ImgUtil
from net.imglib2.img import ImgView
import sys
sys.path.append("/home/albert/lab/scripts/python/imagej/IsoView-GCaMP/")
from lib.util import timeit
roi = (
[1, 228, 0], # top-left coordinates
[1 + 406 - 1, 228 + 465 - 1,
0 + 325 - 1]) # bottom-right coordinates (inclusive, hence the -1)
dimensions = [maxC - minC + 1 for minC, maxC in zip(roi[0], roi[1])]
imgU = ArrayImgs.unsignedShorts(dimensions)
imgF = ArrayImgs.floats(dimensions)
#c = imgF.cursor()
#while c.hasNext():
# c.next().set(random() * 65535)
ImgMath.compute(ImgMath.number(17)).into(imgF)
ImgMath.compute(ImgMath.img(imgF)).into(imgU)
aff = AffineTransform3D()
"""
aff.set(1, 0, 0, 0,
0, 1, 0, 0,
0, 0, 1, 0)
"""
aff.set(*[
0.9999949529841275, -0.0031770224721305684, 2.3118912942710207e-05,
-1.6032353998500826, 0.003177032139125933, 0.999994860398559,
from net.imglib2.realtransform import RealViews, AffineTransform3D
from net.imglib2.interpolation.randomaccess import NLinearInterpolatorFactory
from net.imglib2.util import Intervals
img = IL.wrap(IJ.getImage())
# Cut out a cube
img1 = Views.zeroMin(
Views.interval(img, [39, 49, 0], [39 + 378 - 1, 49 + 378 - 1, 378 - 1]))
print[img1.dimension(d) for d in xrange(img1.numDimensions())]
# Rotate the cube on the Y axis to the left
img2 = Views.rotate(img1, 2, 0)
# copy into ArrayImg
img1a = ArrayImgs.unsignedShorts([378, 378, 378])
ImgMath.compute(ImgSource(img1)).into(img1a)
img2a = ArrayImgs.unsignedShorts([378, 378, 378])
ImgMath.compute(ImgSource(img2)).into(img2a)
img1 = img1a
img2 = img2a
IL.wrap(img1, "cube").show()
IL.wrap(img2, "cube rotated").show()
# Now register them
# IMPORTANT PARAMETERS
raw_calibration = [1.0, 1.0, 1.0] # micrometers per pixel
# 2022 I2K example
# Albert Cardona 2022
# Create an ImgLib2 ArrayImg
# 1. With ArrayImgs: trivial
from net.imglib2.img.array import ArrayImgs
img = ArrayImgs.unsignedShorts([512, 512])
# Or reusing the pixel array from e.g., an open ImageJ image:
from net.imglib2.img.array import ArrayImgs
from ij import IJ
from ij.process import ShortProcessor
imp = IJ.getImage() # most recently activated ImageJ image window
ip = imp.getProcessor()
if isinstance(ip, ShortProcessor):
width, height = imp.getWidth(), imp.getHeight()
pixelsU16 = ip.getPixels()
img = ArrayImgs.unsignedShorts(pixelsU16, [width, height])
# Or creating a new pixel array from scratch
from net.imglib2.img.array import ArrayImgs
from jarray import zeros
pixelsU16 = zeros(512 * 512, 'h') # 'h' means short[]
img = ArrayImgs.unsignedShorts(pixelsU16, [512, 512])
# 2. With ArrayImgFactory: unnecessary, use ArrayImgs
from net.imglib2.img.array import ArrayImgFactory
from net.imglib2.type.numeric.integer import UnsignedShortType
def maxProjectLastDimension(img, strategy="1by1", chunk_size=0):
last_dimension = img.numDimensions() -1
if "1by1" == strategy:
exe = newFixedThreadPool()
try:
n_threads = exe.getCorePoolSize()
imgTs = [ArrayImgs.unsignedShorts(list(Intervals.dimensionsAsLongArray(img))[:-1]) for i in xrange(n_threads)]
def mergeMax(img1, img2, imgT):
return compute(maximum(img1, img2)).into(imgT)
def hyperSlice(index):
return Views.hyperSlice(img, last_dimension, index)
# The first n_threads mergeMax:
futures = [exe.submit(Task(mergeMax, hyperSlice(i*2), hyperSlice(i*2 +1), imgTs[i]))
for i in xrange(n_threads)]
# As soon as one finishes, merge it with the next available hyperSlice
next = n_threads
while len(futures) > 0: # i.e. not empty
imgT = futures.pop(0).get()
if next < img.dimension(last_dimension):
futures.append(exe.submit(Task(mergeMax, imgT, hyperSlice(next), imgT)))
next += 1
else:
# Run out of hyperSlices to merge
if 0 == len(futures):
return imgT # done
# Merge imgT to each other until none remain
futures.append(exe.submit(Task(mergeMax, imgT, futures.pop(0).get(), imgT)))
finally:
exe.shutdownNow()
else:
# By chunks
imglibtype = img.randomAccess().get().getClass()
# The Converter class
reduce_max = makeCompositeToRealConverter(reducer_class=Math,
reducer_method="max",
reducer_method_signature="(DD)D")
if chunk_size > 0:
# map reduce approach
exe = newFixedThreadPool()
try:
def projectMax(img, minC, maxC, reduce_max):
imgA = ArrayImgs.unsignedSorts(Intervals.dimensionsAsLongArray(imgC))
ImgUtil.copy(ImgView.wrap(convert(Views.collapseReal(Views.interval(img, minC, maxC)), reduce_max.newInstance(), imglibtype), img.factory()), imgA)
return imgA
# The min and max coordinates of all dimensions except the last one
minCS = [0 for d in xrange(last_dimension)]
maxCS = [img.dimension(d) -1 for d in xrange(last_dimension)]
# Process every chunk in parallel
futures = [exe.submit(Task(projectMax, img, minCS + [offset], maxCS + [min(offset + chunk_size, img.dimension(last_dimension)) -1]))
for offset in xrange(0, img.dimension(last_dimension), chunk_size)]
return reduce(lambda f1, f2: compute(maximum(f1.get(), f2.get())).into(f1.get(), futures))
finally:
exe.shutdownNow()
else:
# One chunk: all at once
# Each sample of img3DV is a virtual vector over all time frames at that 3D coordinate
# Reduce each vector to a single scalar, using a Converter
img3DC = convert(Views.collapseReal(img), reduce_max.newInstance(), imglibtype)
imgA = ArrayImgs.unsignedShorts([img.dimension(d) for d in xrange(last_dimension)])
ImgUtil.copy(ImgView.wrap(imgV, img.factory()), imgA)
return imgA
from net.imglib2.type.numeric.real import FloatType from net.imglib2.view import Views imp = IJ.getImage() dimensions = [imp.getWidth(), imp.getHeight()] ip = imp.getProcessor() pixels = ip.getPixels() # In practice, you never want to do this below, # and instead you'd use the built-in wrapper: ImageJFunctions.wrap(imp) # This is merely for illustration of how to use ArrayImgs with an existing pixel array if isinstance(ip, ByteProcessor): img1 = ArrayImgs.unsignedBytes(pixels, dimensions) elif isinstance(ip, ShortProcessor): img1 = ArrayImgs.unsignedShorts(pixels, dimensions) elif isinstance(ip, FloatProcessor): img1 = ArrayImgs.floats(pixels, dimensions) else: print "Can't handle image of type:", type(ip).getName() # An empty image of float[] img2 = ArrayImgs.floats(dimensions) # View it as RandomAccessibleInterval<FloatType> by converting on the fly # using a generic RealType to FloatType converter floatView = Converters.convertRAI(img1, RealFloatConverter(), FloatType()) # The above 'floatView' can be used as an image: one that gets always converted on demand. # If you only have to iterate over the pixels just once, there's no need to create a new image.
def loadUnsignedShort(filepath):
imp = loadImp(filepath)
return ArrayImgs.unsignedShorts(
imp.getProcessor().getPixels(),
[imp.getWidth(), imp.getHeight()])
def asArrayImg(img1): dimensions1 = [img1.dimension(d) for d in xrange(img1.numDimensions())] img2 = ArrayImgs.unsignedShorts(dimensions1) ImgMath.compute(ImgSource(img1)).into(img2) return img2
def loadUnsignedShort(filepath):
imp = loadImp(filepath) # an instance of an ij.ImagePlus
return ArrayImgs.unsignedShorts(
imp.getProcessor().getPixels(),
[imp.getWidth(), imp.getHeight()])
