res_robust = least_squares(_loss_gaussian_citrate_4_dof, popt_default, loss='huber', f_scale=1., bounds=param_bounds, args=(ppm_interp, f(ppm_interp))) return res_robust.x path_mrsi = '/data/prostate/experiments/Patient 1036/MRSI/CSI_SE_3D_140ms_16c.rda' rda_mod = RDAModality(1250.) rda_mod.read_data_from_path(path_mrsi) phase_correction = MRSIPhaseCorrection(rda_mod) rda_mod = phase_correction.transform(rda_mod) freq_correction = MRSIFrequencyCorrection(rda_mod) rda_mod = freq_correction.fit(rda_mod).transform(rda_mod) baseline_correction = MRSIBaselineCorrection(rda_mod) rda_mod = baseline_correction.fit(rda_mod).transform(rda_mod) # x = 0 # y = 0 # z = 0 # out = _citrate_fitting(rda_mod.bandwidth_ppm[:, 5, 9, 5], # np.real(rda_mod.data_[:, 5, 9, 5]))
np.inf, delta_2_bounds[1], 8*10e-2, np.inf, delta_3_bounds[1], 8*10e-2]) res_robust = least_squares(_loss_gaussian_citrate_4_dof, popt_default, loss='huber', f_scale=1., bounds=param_bounds, args=(ppm_interp, f(ppm_interp))) return res_robust.x path_mrsi = '/data/prostate/experiments/Patient 1036/MRSI/CSI_SE_3D_140ms_16c.rda' rda_mod = RDAModality(1250.) rda_mod.read_data_from_path(path_mrsi) phase_correction = MRSIPhaseCorrection(rda_mod) rda_mod = phase_correction.transform(rda_mod) freq_correction = MRSIFrequencyCorrection(rda_mod) rda_mod = freq_correction.fit(rda_mod).transform(rda_mod) baseline_correction = MRSIBaselineCorrection(rda_mod) rda_mod = baseline_correction.fit(rda_mod).transform(rda_mod) # x = 0 # y = 0 # z = 0 # out = _citrate_fitting(rda_mod.bandwidth_ppm[:, 5, 9, 5], # np.real(rda_mod.data_[:, 5, 9, 5]))