def test_2D():
import pkg_resources
DATA_PATH = pkg_resources.resource_filename('pynufft', 'src/data/')
# PHANTOM_FILE = pkg_resources.resource_filename('pynufft', 'data/phantom_256_256.txt')
import numpy
import matplotlib.pyplot
from pynufft import NUFFT_cpu
# load example image
# image = numpy.loadtxt(DATA_PATH +'phantom_256_256.txt')
image = scipy.misc.ascent()
image = scipy.misc.imresize(image, (256, 256))
image = image.astype(numpy.float) / numpy.max(image[...])
#numpy.save('phantom_256_256',image)
matplotlib.pyplot.imshow(image, cmap=matplotlib.cm.gray)
matplotlib.pyplot.show()
print('loading image...')
Nd = (256, 256) # image size
print('setting image dimension Nd...', Nd)
Kd = (512, 512) # k-space size
print('setting spectrum dimension Kd...', Kd)
Jd = (6, 6) # interpolation size
print('setting interpolation size Jd...', Jd)
# load k-space points
# om = numpy.loadtxt(DATA_PATH+'om.txt')
om = numpy.load(DATA_PATH + 'om2D.npz')['arr_0']
print('setting non-uniform coordinates...')
matplotlib.pyplot.plot(om[::10, 0], om[::10, 1], 'o')
matplotlib.pyplot.title('non-uniform coordinates')
matplotlib.pyplot.xlabel('axis 0')
matplotlib.pyplot.ylabel('axis 1')
matplotlib.pyplot.show()
NufftObj = NUFFT_cpu()
NufftObj.plan(om, Nd, Kd, Jd)
y = NufftObj.forward(image)
print('setting non-uniform data')
print('y is an (M,) list', type(y), y.shape)
W = numpy.ones(Kd, dtype=numpy.complex64)
for pp in range(0, 200):
W2 = NufftObj.xx2k(NufftObj.adjoint(NufftObj.forward(
NufftObj.k2xx(W))))
W2 = W2 * W2.conj()
W2 = W2**0.5
W = (W + 0.9) / (W2 + 0.9)
matplotlib.pyplot.subplot(1, 2, 1)
matplotlib.pyplot.imshow(W2.real)
matplotlib.pyplot.subplot(1, 2, 2)
matplotlib.pyplot.imshow((W / W2).real)
matplotlib.pyplot.show()
# kspectrum = NufftObj.xx2k( NufftObj.solve(y,solver='bicgstab',maxiter = 100))
image_restore = NufftObj.solve(y, solver='cg', maxiter=10)
shifted_kspectrum = numpy.fft.fftshift(
numpy.fft.fftn(numpy.fft.fftshift(image_restore)))
print('getting the k-space spectrum, shape =', shifted_kspectrum.shape)
print('Showing the shifted k-space spectrum')
matplotlib.pyplot.imshow(shifted_kspectrum.real,
cmap=matplotlib.cm.gray,
norm=matplotlib.colors.Normalize(vmin=-100,
vmax=100))
matplotlib.pyplot.title('shifted k-space spectrum')
matplotlib.pyplot.show()
image2 = NufftObj.solve(y, 'dc', maxiter=25)
# image3 = NufftObj.solve(y, 'L1TVLAD',maxiter=100, rho= 1)
image3 = NufftObj.k2xx(NufftObj.xx2k(NufftObj.adjoint(y)) * W)
print(image3.shape)
image4 = NufftObj.solve(y, 'L1TVOLS', maxiter=100, rho=1)
matplotlib.pyplot.subplot(1, 3, 1)
matplotlib.pyplot.imshow(image,
cmap=matplotlib.cm.gray,
norm=matplotlib.colors.Normalize(vmin=0.0,
vmax=1))
matplotlib.pyplot.subplot(1, 3, 2)
matplotlib.pyplot.imshow(image3.real,
cmap=matplotlib.cm.gray,
norm=matplotlib.colors.Normalize(vmin=0.0,
vmax=1))
matplotlib.pyplot.subplot(1, 3, 3)
matplotlib.pyplot.imshow(image4.real,
cmap=matplotlib.cm.gray,
norm=matplotlib.colors.Normalize(vmin=0.0,
vmax=1))
matplotlib.pyplot.show()
# matplotlib.pyplot.imshow(image2.real, cmap=matplotlib.cm.gray, norm=matplotlib.colors.Normalize(vmin=0.0, vmax=1))
# matplotlib.pyplot.show()
maxiter = 25
counter = 1
for solver in ('dc', 'bicg', 'bicgstab', 'cg', 'gmres', 'lgmres', 'lsmr',
'lsqr'):
print(counter, solver)
if 'lsqr' == solver:
image2 = NufftObj.solve(y, solver, iter_lim=maxiter)
else:
image2 = NufftObj.solve(y, solver, maxiter=maxiter)
# image2 = NufftObj.solve(y, solver='bicgstab',maxiter=30)
matplotlib.pyplot.subplot(2, 4, counter)
matplotlib.pyplot.imshow(image2.real,
cmap=matplotlib.cm.gray,
norm=matplotlib.colors.Normalize(vmin=0.0,
vmax=1))
matplotlib.pyplot.title(solver)
# print(counter, solver)
counter += 1
matplotlib.pyplot.show()
shifted_kspectrum = numpy.fft.fftshift(
numpy.fft.fftn(numpy.fft.fftshift(image0)))
# print('getting the k-space spectrum, shape =',shifted_kspectrum.shape)
print('Showing the shifted k-space spectrum')
matplotlib.pyplot.imshow(shifted_kspectrum.real,
cmap=matplotlib.cm.gray,
norm=matplotlib.colors.Normalize(vmin=-100, vmax=100))
matplotlib.pyplot.title('shifted k-space spectrum')
matplotlib.pyplot.show()
W0 = numpy.ones((NufftObj.st['M'], ))
# W_x = NufftObj.xx2k( NufftObj.adjoint(NufftObj.forward(NufftObj.k2xx(W0))))
# W_y = NufftObj.xx2k(NufftObj.x2xx(NufftObj.adjoint(NufftObj.k2y(W0))))
W = NufftObj.xx2k(NufftObj.adjoint(W0))
# W = NufftObj.y2k(W0)
# matplotlib.pyplot.subplot(1,)
matplotlib.pyplot.imshow(numpy.real((W * W.conj())**0.5))
matplotlib.pyplot.title('Ueckers inverse function (real)')
# matplotlib.pyplot.subplot(1,2,2)
# matplotlib.pyplot.imshow(W.imag)
# matplotlib.pyplot.title('Ueckers inverse function (imaginary)')
matplotlib.pyplot.show()
p0 = NufftObj.adjoint(NufftObj.forward(image))
p1 = NufftObj.k2xx((W.conj() * W)**0.5 * NufftObj.xx2k(image))
print('error between Toeplitz and Inverse reconstruction',
numpy.linalg.norm(p1 - p0) / numpy.linalg.norm(p0))
def test_init():
# cm = matplotlib.cm.gray
# load example image
import pkg_resources
DATA_PATH = pkg_resources.resource_filename('pynufft', 'src/data/')
# PHANTOM_FILE = pkg_resources.resource_filename('pynufft', 'data/phantom_256_256.txt')
import numpy
# import matplotlib.pyplot
import scipy
image = scipy.misc.ascent()[::2,::2]
image=image.astype(numpy.float)/numpy.max(image[...])
Nd = (256, 256) # image space size
Kd = (512, 512) # k-space size
Jd = (6,6) # interpolation size
# load k-space points
om = numpy.load(DATA_PATH+'om2D.npz')['arr_0']
nfft = NUFFT_cpu() # CPU
nfft.plan(om, Nd, Kd, Jd)
try:
NufftObj = NUFFT_hsa('cuda',0,0)
except:
NufftObj = NUFFT_hsa('ocl',0,0)
# NufftObj2 = NUFFT_hsa('cuda',0,0)
NufftObj.debug = 1
NufftObj.plan(om, Nd, Kd, Jd, radix=2)
# NufftObj2.plan(om, Nd, Kd, Jd)
# NufftObj.offload(API = 'cuda', platform_number = 0, device_number = 0)
# NufftObj2.offload(API = 'cuda', platform_number = 0, device_number = 0)
# NufftObj2.offload('cuda')
# NufftObj.offload(API = 'cuda', platform_number = 0, device_number = 0)
# print('api=', NufftObj.thr.api_name())
# NufftObj.offload(API = 'ocl', platform_number = 0, device_number = 0)
y = nfft.k2y(nfft.xx2k(nfft.x2xx(image)))
NufftObj.x_Nd = NufftObj.thr.to_device( image.astype(dtype))
gx = NufftObj.thr.copy_array(NufftObj.x_Nd)
print('x close? = ', numpy.allclose(image, gx.get() , atol=1e-4))
gxx = NufftObj.x2xx(gx)
print('xx close? = ', numpy.allclose(nfft.x2xx(image), gxx.get() , atol=1e-4))
gk = NufftObj.xx2k(gxx)
k = nfft.xx2k(nfft.x2xx(image))
print('k close? = ', numpy.allclose(nfft.xx2k(nfft.x2xx(image)), gk.get(), atol=1e-3*numpy.linalg.norm(k)))
gy = NufftObj.k2y(gk)
k2 = NufftObj.y2k(gy)
print('y close? = ', numpy.allclose(y, gy.get() , atol=1e-3*numpy.linalg.norm(y)), numpy.linalg.norm((y - gy.get())/numpy.linalg.norm(y)))
y2 = y
print('k2 close? = ', numpy.allclose(nfft.y2k(y2), k2.get(), atol=1e-3*numpy.linalg.norm(nfft.y2k(y2)) ), numpy.linalg.norm(( nfft.y2k(y2)- k2.get())/numpy.linalg.norm(nfft.y2k(y2))))
gxx2 = NufftObj.k2xx(k2)
# print('xx close? = ', numpy.allclose(nfft.k2xx(nfft.y2k(y2)), NufftObj.xx_Nd.get(queue=NufftObj.queue, async=False) , atol=0.1))
gx2 = NufftObj.xx2x(gxx2)
print('x close? = ', numpy.allclose(nfft.adjoint(y2), gx2.get() , atol=1e-3*numpy.linalg.norm(nfft.adjoint(y2))))
image3 = gx2.get()
import time
t0 = time.time()
# k = nfft.xx2k(nfft.x2xx(image))
for pp in range(0,50):
# y = nfft.k2y(nfft.xx2k(nfft.x2xx(image)))
y = nfft.forward(image)
# y = nfft.k2y(k)
# k = nfft.y2k(y)
# x = nfft.adjoint(y)
# y = nfft.forward(image)
# y2 = NufftObj.y.get( NufftObj.queue, async=False)
t_cpu = (time.time() - t0)/50.0
print(t_cpu)
# del nfft
gy2=NufftObj.forward(gx)
# gk = NufftObj.xx2k(NufftObj.x2xx(gx))
t0= time.time()
for pp in range(0,20):
# pass
gy2 = NufftObj.forward(gx)
# gy2 = NufftObj.k2y(gk)
# gx2 = NufftObj.adjoint(gy2)
# gk2 = NufftObj.y2k(gy2)
# del gy2
# c = gx2.get()
# gy=NufftObj.forward(gx)
NufftObj.thr.synchronize()
t_cl = (time.time() - t0)/20
print(t_cl)
print('gy close? = ', numpy.allclose(y, gy.get(), atol=numpy.linalg.norm(y)*1e-3))
print("acceleration=", t_cpu/t_cl)
maxiter =100
import time
t0= time.time()
# x2 = nfft.solve(y2, 'cg',maxiter=maxiter)
x2 = nfft.solve(y2, 'L1TVOLS',maxiter=maxiter, rho = 2)
t1 = time.time()-t0
# gy=NufftObj.thr.copy_array(NufftObj.thr.to_device(y2))
t0= time.time()
# x = NufftObj.solve(gy,'cg', maxiter=maxiter)
x = NufftObj.solve(gy,'L1TVOLS', maxiter=maxiter, rho=2)
t2 = time.time() - t0
print(t1, t2)
print('acceleration=', t1/t2 )
# k = x.get()
# x = nfft.k2xx(k)/nfft.st['sn']
# return
try:
import matplotlib.pyplot
matplotlib.pyplot.subplot(1, 2, 1)
matplotlib.pyplot.imshow( x.get().real, cmap= matplotlib.cm.gray, vmin = 0, vmax = 1)
matplotlib.pyplot.title("HSA reconstruction")
matplotlib.pyplot.subplot(1, 2,2)
matplotlib.pyplot.imshow(x2.real, cmap= matplotlib.cm.gray)
matplotlib.pyplot.title("CPU reconstruction")
matplotlib.pyplot.show(block = False)
matplotlib.pyplot.pause(3)
matplotlib.pyplot.close()
# del NufftObj.thr
# del NufftObj
except:
print("no graphics")