header['radius'] = 1.2 obj = siddon.simu.object_from_header(header) obj[:] = siddon.phantom.shepp_logan(obj.shape) # data image_header = {'n_images':60, 'SIMPLE':True, 'BITPIX':-64, 'NAXIS1':128, 'NAXIS2':128, 'CRPIX1':64, 'CRPIX2':64, 'CDELT1':6e-5, 'CDELT2':6e-5, 'CRVAL1':0., 'CRVAL2':0., } image_header['radius'] = 200. data = siddon.simu.circular_trajectory_data(**image_header) data[:] = np.zeros(data.shape) # projector P = siddon.siddon_lo(data.header, obj.header) # projection t = time.time() data = siddon.projector(data, obj) print("projection time : " + str(time.time() - t)) # data y = data.flatten() # backprojection t = time.time() x0 = P.T * y bpj = x0.reshape(obj.shape) print("projection time : " + str(time.time() - t)) # coverage map weights = (P.T * np.ones(y.size)).reshape(obj.shape) # priors Ds = [lo.diff(obj.shape, axis=i) for i in xrange(3)]
# data path = os.path.join(os.getenv('HOME'), 'data', '171dec08') obsrvtry = 'STEREO_A' time_window = ['2008-12-01T00:00:00.000', '2008-12-03T00:00:00.000'] # one image every time_step seconds time_step = 4 * 3600. data = siddon.secchi.read_data(path, bin_factor=4, obsrvtry=obsrvtry, time_window=time_window, time_step=time_step) # cube shape = 3 * (128,) header = {'CRPIX1':64., 'CRPIX2':64., 'CRPIX3':64., 'CDELT1':0.0234375, 'CDELT2':0.0234375, 'CDELT3':0.0234375, 'CRVAL1':0., 'CRVAL2':0., 'CRVAL3':0.,} cube = fa.zeros(shape, header=header) # model P = siddon.siddon_lo(data.header, cube.header) D = [lo.diff(cube.shape, axis=i) for i in xrange(cube.ndim)] hypers = cube.ndim * (1e0, ) # inversion t = time.time() A = P.T * P + np.sum([h * d.T * d for h, d in zip(hypers, D)]) b = P.T * data.flatten() #callback = lo.iterative.CallbackFactory(verbose=True) #x, info = spl.bicgstab(A, b, maxiter=100, callback=callback) x, info = lo.acg(P, data.flatten(), D, hypers, maxiter=100,) sol = cube.copy() sol[:] = x.reshape(cube.shape) print(time.time() - t)