misc.mkdir('{}/pics'.format(folder_main))
misc.mkdir('{}/py'.format(folder_main))
misc.mkdir('{}/logs'.format(folder_main))
folder_today = '{}/nepochs{}'.format(folder_main, nepoch)
misc.mkdir(folder_today)
misc.mkdir('{}/npy'.format(folder_today))
misc.mkdir('{}/pics'.format(folder_today))
misc.mkdir('{}/figs'.format(folder_today))
# load real data
file_data = '{}/data_{}.npy'.format(folder_data, data_suffix)
data, background, factors, image, image_mr, image_ct = np.load(file_data)
# convert to odl
Y = mMR.operator_mmr().range
factors = Y.element(factors)
data = Y.element(data)
background = Y.element(background)
# define operator
K = mMR.operator_mmr(factors=factors)
X = K.domain
KL = misc.kullback_leibler(Y, data, background)
obj_fun = KL * K
# set smoothing
fwhm = np.array([4, 4, 4]) # in mm
sd_smoothing = fwhm / (2 * np.sqrt(2 * np.log(2)) * X.cell_sides)
def smoothing(x):
alphas = [1]
clim = [0, 10] # colour limits for plots
data_suffix = 'rings0-64_span1'
def save_image(x, n, f):
misc.save_image(x.asarray(), n, f, planes=planes, clim=clim)
folder_main = '{}/{}_{}'.format(folder_out, filename, dataset)
misc.mkdir(folder_main)
misc.mkdir('{}/py'.format(folder_main))
misc.mkdir('{}/logs'.format(folder_main))
# load real data and convert to odl
file_data = '{}/data_{}.npy'.format(folder_data, data_suffix)
(data, background, factors, image, image_mr, image_ct) = np.load(file_data)
Y = mMR.operator_mmr().range
data = Y.element(data)
background = Y.element(background)
factors = Y.element(factors)
# define operator
K = mMR.operator_mmr(factors=factors)
X = K.domain
norm_K = misc.norm(K, '{}/norm_1subset.npy'.format(folder_norms))
KL = misc.kullback_leibler(Y, data, background)
for alpha in alphas:
print('<<< <<< alpha = {}'.format(alpha))
folder_param = '{}/alpha{:.2g}'.format(folder_main, alpha)