def std_boxcar_mesh(
n_upper_mantle=20, n_mtz=10, n_lower_mantle=12, n_dpp=6,
types=[ParameterType.VSH], verbose=0):
'''Boxcar mesh using ak135 as reference model for the structure of
the upper mantle and transition zone down to 1000 km depth.
'''
model_ref = SeismicModel.prem()
# model parameters
depth_moho = 6371. - 6336.6
depth_410 = 410.
depth_660 = 660.
depth_dpp = 2491.
depth_cmb = 2891.
rs_upper_mantle = np.linspace(depth_410, depth_moho, n_upper_mantle)
rs_mtz = np.linspace(depth_660, depth_410, n_mtz,
endpoint=(n_upper_mantle==0))
rs_lower_mantle = np.linspace(
depth_dpp, depth_660, n_lower_mantle, endpoint=(n_mtz==0))
rs_dpp = np.linspace(
depth_cmb, depth_dpp, n_dpp, endpoint=(n_lower_mantle==0))
radii = 6371. - np.round(
np.hstack((rs_lower_mantle, rs_mtz, rs_upper_mantle, rs_dpp)), 4)
if verbose > 1:
print('dr_um={}, dr_mtz={}, dr_lm={}'.format(
rs_upper_mantle[1] - rs_upper_mantle[0],
rs_mtz[1] - rs_mtz[0],
rs_lower_mantle[1] - rs_lower_mantle[0]))
model_params = ModelParameters(types, radii, mesh_type='boxcar')
# mesh
# model, mesh = ak135.boxcar_mesh(model_params)
return model_ref, model_params
def get_model_syntest1_prem():
types = [ParameterType.VSH]
radii = np.array([3480. + 100 * i for i in range(5)])
model_params = ModelParameters(types, radii, mesh_type='boxcar')
model = SeismicModel.prem().boxcar_mesh(model_params)
values = np.array(
[.2 * (-1)**i if i < 2 else 0.
for i in range(model_params.get_n_grd_params())])
values_dict = {param_type: values for param_type in types}
values_mat = model_params.get_values_matrix(values_dict)
model_updated = model.multiply(values_mat)
return model_updated
def get_model_syntest_vshvsv_4():
model_ref = SeismicModel.prem()
types = [ParameterType.VSH, ParameterType.VSV]
radii = np.linspace(3480., 3980., 3, endpoint=True)
model_params = ModelParameters(
types, radii, mesh_type='lininterp')
model = model_ref.lininterp_mesh(
model_params)
values = np.zeros(model_params.get_n_grd_params())
values[2] = model_ref.get_value_at(radii[1], ParameterType.VSH) * 0.03
value_dict = {
ParameterType.VSH: values,
ParameterType.VSV: -values
}
model_updated = model.build_model(
model, model_params, value_dict)
return model_updated
def get_model_syntest1_prem_vshvsv():
types = [ParameterType.VSH, ParameterType.VSV]
radii = np.array([3480. + 20 * i for i in range(21)])
model_params = ModelParameters(types, radii, mesh_type='boxcar')
model = SeismicModel.prem().boxcar_mesh(model_params)
values_vsh = np.array(
[0.2 * (-1)**(i//5) if i <= 9 else 0.
for i in range(model_params.get_n_grd_params())])
values_vsv = np.array(
[-0.2 * (-1) ** (i // 5) if i <= 4 else 0.
for i in range(model_params.get_n_grd_params())]
)
values_dict = {
ParameterType.VSH: values_vsh,
ParameterType.VSV: values_vsv
}
values_mat = model_params.get_values_matrix(values_dict)
model_updated = model.multiply(values_mat)
return model_updated
return variance, corr, ratio
def check_data(data, syn, var, corr, ratio):
var_, corr_, ratio_ = misfits(data, syn)
return (np.isfinite(var_) and np.isfinite(corr_) and np.isfinite(ratio_)
and var_ <= var and corr_ >= corr and 1 / ratio <= ratio_ <= ratio)
if __name__ == '__main__':
types = [ParameterType.VSH]
radii = [3480. + 20 * i for i in range(41)]
model_params = ModelParameters(types=types,
radii=radii,
mesh_type='boxcar')
model = SeismicModel.prem().boxcar_mesh(model_params)
n_param = model_params.get_n_params()
its, itypes, igrds = model_params.get_free_all_indices()
order_types = [model_params.get_types()[itypes[i]] for i in its]
order_radii = [model_params.get_grd_params()[igrds[i]] for i in its]
# sac_files = glob.glob(os.path.join(root_sac, '*[RZT]'))
# dataset = Dataset.dataset_from_sac(
# sac_files, headonly=False)
t_before = 20.
t_after = 40.
sampling_hz = 20
window_npts = int((t_before + t_after) * 20)
tlen = 1638.4
shifts = [i * np.pi / 10 for i in range(11)]
arrs = [np.sin(x + s) for s in shifts]
roll_vars = [
rolling_variance(arr1, arrs[i], 500,
250) for
i in range(len(arrs))]
vars = [variance(arr1, arrs[i]) for
i in range(len(arrs))]
plt.plot(shifts, roll_vars)
plt.plot(shifts, vars)
plt.show()
types = [ParameterType.VSH, ParameterType.VPH]
radii = np.array([5701., 5971.])
model_params = ModelParameters(types, radii)
model = SeismicModel.prem()
range_dict = {ParameterType.VSH: [-0.15, 0.15],
ParameterType.VPH: [-0.1, 0.1]}
umc = UniformMonteCarlo(
model, model_params, range_dict,
mesh_type='triangle', seed=0)
sample_models = umc.sample_models(50)
fig, ax = sample_models[0].plot(
types=[ParameterType.VSH, ParameterType.VPH])
for sample in sample_models[1:]:
sample.plot(
ax=ax, types=[ParameterType.VSH, ParameterType.VPH])
ax.get_legend().remove()
plt.show()
from mpi4py import MPI
import os
import sys
comm = MPI.COMM_WORLD
n_core = comm.Get_size()
rank = comm.Get_rank()
input_file = sys.argv[1]
# model parameters
n_nodes = 3
types = [ParameterType.VSH, ParameterType.VSV, ParameterType.RADIUS]
radii = np.linspace(3480., 3980., n_nodes, endpoint=True)
model_params = ModelParameters(types, radii, mesh_type='lininterp')
model = SeismicModel.prem().lininterp_mesh(model_params)
# set D'' layer to constant velocity and density
for r in radii[:-1]:
izone = model.get_zone(r)
for p_type in ParameterType.structure_types():
v_dpp = model.get_value_at(radii[-1], p_type)
model.set_value(
izone, p_type, np.array([v_dpp, 0., 0., 0.]))
# constraints to parameters
mask_dict = dict()
for p_type in ParameterType.structure_types():
mask_dict[p_type] = np.zeros(
model_params.get_n_grd_params(), dtype='bool')
for p_type in types: