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]))