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)