'probe_type': 'gaussian',
'probe_mag_sigma': 6,
'probe_phase_sigma': 6,
'probe_phase_max': 0.5,
'forward_algorithm': 'fresnel',
'object_type': 'phase_only',
'probe_pos': [(y, x) for y in (np.arange(66) * 5) - 36 for x in (np.arange(68) * 5) - 36],
'finite_support_mask': None,
'free_prop_cm': 'inf',
'optimizer': 'adam',
'two_d_mode': True,
'shared_file_object': False,
'use_checkpoint': False
}
params = params_2d_cell
# n_ls = ['nonoise', 'n1e9', 'n1e8', 'n1e7', 'n1e6', 'n1e5', 'n1e4']
n_ls = ['comp_n1e4', 'comp_n4e4', 'comp_n1e5', 'comp_n4e5', 'comp_n1e6', 'comp_n1.75e6', 'comp_n4e6', 'comp_n1e7', 'comp_n1.75e7', 'comp_n4e7', 'comp_n1e8', 'comp_n1.75e8', 'comp_n4e8']
# n_ls = ['nonoise', 'dss_comp_n1e4', 'dss_comp_n4e4', 'dss_comp_n1e5', 'dss_comp_n4e5', 'dss_comp_n1e6', 'dss_comp_n1.75e6', 'dss_comp_n4e6', 'dss_comp_n1e7', 'dss_comp_n1.75e7', 'dss_comp_n4e7', 'dss_comp_n1e8', 'dss_comp_n1.75e8', 'dss_comp_n4e8']
# n_ls = ['nonoise', 'mix_comp_n1e4', 'mix_comp_n4e4', 'mix_comp_n1e5', 'mix_comp_n4e5', 'mix_comp_n1e6', 'mix_comp_n1.75e6', 'mix_comp_n4e6', 'mix_comp_n1e7', 'mix_comp_n1.75e7', 'mix_comp_n4e7', 'mix_comp_n1e8', 'mix_comp_n1.75e8', 'mix_comp_n4e8']
n_ls = [x + '_ref' for x in n_ls]
for n_ph in n_ls:
if 'nonoise' in n_ph:
params['fname'] = 'data_cell_phase.h5'
else:
params['fname'] = 'data_cell_phase_{}.h5'.format(n_ph)
params['output_folder'] = n_ph
reconstruct_ptychography(**params)
reconstruct_ptychography(fname=params['fname'],
probe_pos=params['probe_pos'],
probe_size=params['probe_size'],
theta_st=0,
theta_end=params['theta_end'],
theta_downsample=params['theta_downsample'],
obj_size=params['obj_size'],
n_epochs=params['n_epochs'],
crit_conv_rate=0.03,
max_nepochs=200,
alpha_d=params['alpha_d'],
alpha_b=params['alpha_b'],
gamma=params['gamma'],
learning_rate=params['learning_rate'],
output_folder=params['output_folder'],
minibatch_size=params['batch_size'],
save_intermediate=params['save_intermediate'],
full_intermediate=params['full_intermediate'],
energy_ev=params['energy_ev'],
psize_cm=params['psize_cm'],
cpu_only=params['cpu_only'],
save_path=params['save_folder'],
phantom_path=params['phantom_path'],
multiscale_level=params['multiscale_level'],
n_epoch_final_pass=params['n_epoch_final_pass'],
initial_guess=params['initial_guess'],
n_batch_per_update=params['n_batch_per_update'],
dynamic_rate=True,
probe_type=params['probe_type'],
probe_initial=None,
probe_learning_rate=1e-3,
pupil_function=None,
probe_circ_mask=None,
n_dp_batch=params['n_dp_batch'],
finite_support_mask=params['finite_support_mask'],
forward_algorithm=params['forward_algorithm'],
object_type=params['object_type'],
**params['probe_options'])