time_1 = time.clock()
NufftObj = NUFFT_hsa()
time_2 = time.clock()
# mem_usage = memory_usage((NufftObj.plan,(om, Nd, Kd, Jd)))
# print(mem_usage)
NufftObj.plan(om, Nd, Kd, Jd)
time_3 = time.clock()
# NufftObj.offload('cuda') # for GPU computation
NufftObj.offload('ocl') # for multi-CPU computation
time_4 = time.clock()
dtype = np.complex64
time_5 = time.clock()
print("send image to device")
NufftObj.x_Nd = NufftObj.thr.to_device(image.astype(dtype))
print("copy image to gx")
time_6 = time.clock()
gx = NufftObj.thr.copy_array(NufftObj.x_Nd)
time_7 = time.clock()
print('total:', time_7 - time_1, '/Decl obj: ', time_2 - time_1, '/plan: ', \
time_3 - time_2, '/offload: ', time_4 - time_3, '/to_device: ', time_6 - time_5, '\copy_array: ', time_7 - time_6)
else:
NufftObj = NUFFT_cpu()
# mem_usage = memory_usage((NufftObj.plan,(om, Nd, Kd, Jd)))
# print(mem_usage)
NufftObj.plan(om, Nd, Kd, Jd)
# Compute F_hat
if gpu == True:
time_comp = time.clock()
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")