# 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 velocity`src_rec_file_gr`

: path to the travel-time data file of group velocity`iwave`

: 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 in`netcdf`

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 for`hdf5`

or`csv`

).`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 from`vel_range[0]`

to`vel_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.