Closed jbrage closed 1 year ago
just an example ....
import pyamtrack.libAT as libam E_MeV_u = [10] a0_m = 1e-7 particle_no = [libam.AT_particle_no_from_particle_name_single(p_particle_name="4He")] fluence_cm2_or_dose_Gy = [-0.25] material_no = libam.AT_material_number_from_name("Aluminum Oxide") stopping_power_source_no = 2 # PSTAR rdd_model = libam.RDDModels.RDD_CucinottaExtTarget.value er_model = libam.AT_ERModels.ER_Tabata.value r_min_m = 1e-11 d_min_Gy = 1e-20 rdd_parameters = [r_min_m, a0_m, d_min_Gy, 0.0] gamma_model = libam.AT_GammaResponseModels.GR_GeneralTarget.value gamma_parameters = [1.0, 30, 1, 1, 0] # (k, D1, c, m, 0), tuple? N2 = 10 fluence_factor = 1.0 write_output = True shrink_tails = False shrink_tails_under = 0.0 adjust_N2 = True lethal_events_mode = False relative_efficiency = [0] d_check = [0] S_HCP = [0] S_gamma = [0] mean_number_of_tracks_contrib = [0] start_number_of_tracks_contrib = [0] n_convolutions = [0] lower_Jensen_bound = [0] upper_Jensen_bound = [0] libam.AT_run_CPPSC_method( p_E_MeV_u =E_MeV_u , p_particle_no=particle_no, p_fluence_cm2_or_dose_Gy=fluence_cm2_or_dose_Gy, p_material_no=material_no, p_stopping_power_source_no=stopping_power_source_no, p_rdd_model=rdd_model, p_rdd_parameters=rdd_parameters, p_er_model=er_model, p_gamma_model=gamma_model, p_gamma_parameters=gamma_parameters, p_N2=N2, p_fluence_factor=fluence_factor, p_write_output=write_output, p_shrink_tails=shrink_tails, p_shrink_tails_under=shrink_tails_under, p_adjust_N2=adjust_N2, p_lethal_events_mode=lethal_events_mode, p_relative_efficiency=relative_efficiency, p_d_check=d_check, p_S_HCP=S_HCP, p_S_gamma=S_gamma, p_mean_number_of_tracks_contrib=mean_number_of_tracks_contrib, p_start_number_of_tracks_contrib=start_number_of_tracks_contrib, p_n_convolutions=n_convolutions, p_lower_Jensen_bound=lower_Jensen_bound, p_upper_Jensen_bound=upper_Jensen_bound ) print("relative efficiency = {:0.3f}".format(relative_efficiency[0]))
solved; example to be uploaded
just an example ....