def misfit(m):
"""
Objective function to minimize: misfit between
modelled and observed group velocities
"""
# vector of parameters = [vs of crustal layers]
# + [dz of sediment and crustal layers]
vs_crust = m[:nb_crust_layers]
# building the model
vsmodel = psdepthmodel.VsModel(vs=np.r_[vs_sediments, vs_crust,
vs_mantle],
dz=m[nb_crust_layers:],
ratio_vp_vs=ratio_vp_vs,
ratio_rho_vs=ratio_rho_vs)
return vsmodel.misfit_to_vg(periods=PERIODS,
vg=meanvg,
sigmavg=sigmavg)
'fun':
lambda m: vs_mantle - m[nb_crust_layers - 1] - VS_MIN_INCREMENT
}
constraints.append(constr)
# constrained optimization
mopt = minimize(misfit, x0=m0, method='COBYLA',
constraints=constraints)['x']
vscrustopt, dzsedopt, dzcrustopt = (mopt[:nb_crust_layers],
mopt[nb_crust_layers],
mopt[nb_crust_layers + 1:])
# using the best-fitting model as initial model of the MC exploration
vsmodelinit = psdepthmodel.VsModel(vs=np.r_[vs_sediments, vscrustopt,
vs_mantle],
dz=np.r_[dzsedopt, dzcrustopt],
ratio_vp_vs=ratio_vp_vs,
ratio_rho_vs=ratio_rho_vs,
name='Initial model')
# =======================
# Monte-Carlo exploration
# =======================
# initializing parameters
vscrustlayers = []
dzcrustlayers = []
for i in range(nb_crust_layers):
vscrustlayer = psmcsampling.Parameter(
name='Vs of crustal layer #{}'.format(i + 1),
minval=vs_crust_bounds[0],
maxval=vs_crust_bounds[1],