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 innetcdfformat.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 forhdf5orcsv).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.