def get(self, index):
img = CellLoader.klb.readFull(timepoint_paths[index]).getImg()
# Each cell has "1" as its dimension in the last axis (time)
# and index as its min coordinate in the last axis (time)
return Cell(
Intervals.dimensionsAsIntArray(img) + array([1], 'i'),
Intervals.minAsLongArray(img) + array([index], 'l'),
extractArrayAccess(img))
aff = AffineTransform3D()
aff.set(*matrix)
return aff
# Transform the kernel for each view
kernels = [kernel,
transformPSFKernelToView(kernel, affine3D(matrices["imgB0-imgB1"])),
transformPSFKernelToView(kernel, affine3D(matrices["imgB0-imgB2"])),
transformPSFKernelToView(kernel, affine3D(matrices["imgB0-imgB3"]))]
def deconvolve(images, kernels, name, n_iterations):
# Bayesian-based multi-view deconvolution
exe = newFixedThreadPool(Runtime.getRuntime().availableProcessors() -2)
try:
mylambda = 0.0006
blockSize = Intervals.dimensionsAsIntArray(images[0]) # [128, 128, 128]
cptf = ComputeBlockSeqThreadCPUFactory(exe, mylambda, blockSize, ArrayImgFactory(FloatType()))
psiInitFactory = PsiInitBlurredFusedFactory() # PsiInitAvgPreciseFactory() fails with type mismatch: UnsignedByteType (?) vs FloatType
weight = Views.interval(ConstantRandomAccessible(FloatType(1), images[0].numDimensions()), FinalInterval(images[0]))
filterBlocksForContent = False # Run once with True, none were removed
decon_views = DeconViews([DeconView(exe, img, weight, kernel, PSFTYPE.INDEPENDENT, blockSize, 1, filterBlocksForContent)
for img in images],
exe)
#n_iterations = 10
decon = MultiViewDeconvolutionSeq(decon_views, n_iterations, psiInitFactory, cptf, ArrayImgFactory(FloatType()))
if not decon.initWasSuccessful():
print "Something went wrong initializing MultiViewDeconvolution"
else:
decon.runIterations()
img = decon.getPSI()
imp = IL.wrap(img, name + "_deconvolved_" + str(n_iterations) + "_iterations")
