t1 = System.currentTimeMillis()
for peak in peaks:
sphere = sphereFactory.create(
[int(peak[0]), int(peak[1]), int(peak[2])], radius, ra)
s = sum(imap(FloatType.getRealFloat, sphere.cursor()))
intensities1.append(float(s) / sphere.size())
t2 = System.currentTimeMillis()
print "Elapsed time:", (t2 - t1), "ms"
#print intensities1
# Try now with HyperSphereCursor
hs = HyperSphere(copy2, Point(3), radius)
size = hs.size()
intensities2 = []
hsc = hs.cursor()
t3 = System.currentTimeMillis()
for peak in peaks:
hsc.updateCenter([int(peak[0]), int(peak[1]), int(peak[2])])
s = sum(imap(FloatType.getRealFloat, hsc))
intensities2.append(float(s) / size)
t4 = System.currentTimeMillis()
print "Elapsed time:", (t4 - t3), "ms"
from net.imglib2 import Point
from net.imglib2.algorithm.region.hypersphere import HyperSphere
# create an empty image
phantom = ops.create().img(array([xSize, ySize], 'l'))
# use the randomAccess interface to place points in the image
randomAccess = phantom.randomAccess()
randomAccess.setPosition(array([xSize / 2, ySize / 2], 'l'))
randomAccess.get().setReal(255.0)
randomAccess.setPosition(array([xSize / 4, ySize / 4], 'l'))
randomAccess.get().setReal(255.0)
location = Point(phantom.numDimensions())
location.setPosition(array([3 * xSize / 4, 3 * ySize / 4], 'l'))
hyperSphere = HyperSphere(phantom, location, 5)
for value in hyperSphere:
value.setReal(16)
display.createDisplay("phantom", phantom)
# create psf using the gaussian kernel op (alternatively PSF could be an input to the script)
psf = ops.create().kernelGauss(array([10, 10], 'd'))
# convolve psf with phantom
convolved = ops.filter().convolve(phantom, psf)
display.createDisplay("convolved", convolved)
