Input parameter file¶
The input parameter file is in the yaml
format. The input parameter file should contain the following sections with parameters for the inversion:
data
¶
src_rec_file_ph
: path to the travel-time data file of phase velocitysrc_rec_file_gr
: path to the travel-time data file of group velocityiwave
: type of surface wave (1 Love wave (not included in the current version), 2 Rayleigh wave )vel_type
: Bool list with 2 elements, indicating the type of velocity model e.g.,[True, False]
for phase velocity only.weights
: Float list with 2 elements, indicating the weight of phase and group velocity data e.g.,[1.0, 0.0]
for phase velocity only.
domain
¶
depth
: List with 2 elements, indicating depth range of the model.interval
: List with 3 elements, indicating the interval of the model along longitude, latitude, and depth.num_grid_margin
: Int, indicating the grid number of margin area for the domain.
topo
¶
is_consider_topo
: Bool, indicating whether to consider the model with topography.topo_file
: path to the surface topography file innetcdf
format.wavelen_factor
: Float, indicating the smoothing factor of the topography.
Note
We assume the wavelen_factor
as \(\alpha\) and the wavelength of the surface wave is \(\lambda\). A gaussian smoothing filter with a standard deviation of \(\sigma = \alpha \lambda\) is applied to the topography.
output
¶
output_path
: path to the output files.format
: output format of the model file (available forhdf5
orcsv
).log_level
: log level of the output (available for 0:DEBUG
, 1:INFO
).
inversion
¶
Initial model¶
init_model_type
: type of initial model (0:1D
, 1:3D
).0
: Increase fromvel_range[0]
tovel_range[1]
linearly.1
: Do 1-D inversion first using the average surface wave velocity data.2
: Specify the 3-D initial model file with the same format as the output model file in hdf5 format.
vel_range
: List with 2 elements, indicating the range of the initial model.init_model_path
: Path to the 3-D initial model file.
Kernel Regularization¶
kdensity_coe
: Coefficient to rescale the final kernel
Note
we assume the kdensity_coe
as \(\alpha\). The kernel \(K\) is rescaled as \(\frac{1}{K_{den}^\alpha}\), where the \(K_{den}\) is the total kernel density. The kdensity_coe
is usually set between 0.0 and 1.0.
ncomponents
: number of components of the inversion grids.n_inv_grid
: Int list with 3 elements, indicating number of inversion grids along longitude, latitude, and depth.
Inversion parameters¶
niter
: maximum iteration number of the inversion.min_derr
: minimum error change of the inversion.
Optimization parameters¶
optim_method
: Optimization method of the inversion (0:Grad_descent
, 1:Non-linear Conjugate Gradient
, 2:L-BFGS
).
Note
The L-BFGS
method is recommended, due to its fast convergence.
step_length
: Step length of the inversion.max_sub_niter
: Maximum sub-iterations for line search.maxshrink
: Maximum step length descent.