def test_meshgrid():
nx, ny = (3, 2)
x2 = numpy.linspace(0, 1, nx)
y2 = numpy.linspace(0, 1, ny)
x1 = afnumpy.array(x2)
y1 = afnumpy.array(y2)
iassert(afnumpy.meshgrid(x1, y1), numpy.meshgrid(x2, y2))
def test_meshgrid():
nx, ny = (3, 2)
x2 = numpy.linspace(0, 1, nx)
y2 = numpy.linspace(0, 1, ny)
x1 = afnumpy.array(x2)
y1 = afnumpy.array(y2)
iassert(afnumpy.meshgrid(x1, y1), numpy.meshgrid(x2, y2))
#data_fourier = np.zeros((1024,1024)).astype(np.complex64)
# True image
true_image = fft.fftshift(fft.ifftn(data_fourier))
#import arrayfire
#print arrayfire.backend.name
#print type(true_image)
#print true_image.dtype
#print intensities.dtype
#print data_fourier.dtype
# Initial image
image = (1j + np.random.random(intensities.shape)).astype(np.complex64)
# Define support
yy,xx = np.meshgrid(np.arange(image.shape[0]), np.arange(image.shape[1]))
rr = np.sqrt((xx-image.shape[1]/2)**2 + (yy-image.shape[0]/2)**2)
support = rr < 24
#support = np.abs(true_image)>1
# Define Nr. of iterations
nr_iterations = 500
# Define data constraint
def data_constraint(fourier, intensities):
return (fourier / np.abs(fourier)) * np.sqrt(intensities)
# Define support constraint
def support_constraint(img, support):
img = img.flatten()
img[support == 0] = 0
