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pytomoatt.model

This content is for v0.3.0. Switch to the latest version for up-to-date documentation.

Create initial model from external models

Constructor

__init__(para_fname='input_params.yml')

Parameters

Name Type Description
para_fname (str, optional) Path to parameter file, defaults to ‘input_params.yml’ (default: 'input_params.yml')
ATTModel.calc_dv(ref_mod_fname: str)

calculate anomalies relative to another model

Parameters

Name Type Description
ref_mod_fname str Path to reference model

ATTModel.calc_dv_avg()

calculate anomalies relative to average velocity at each depth


ATTModel.copy()

Copy the model


ATTModel.grid_data_ascii(model_fname: str, **kwargs)

Grid data from custom model file in ASCII format

Parameters

Name Type Description
model_fname str Path to model file
usecols list | tuple Columns order by longitude, latitude, depth and velocity, defaults to [0, 1, 2, 3]

ATTModel.grid_data_crust1(type='vp', rotate=None)

Grid data from CRUST1.0 model

Parameters

Name Type Description
type (str, optional) Specify velocity type of vp or vs, defaults to ‘vp’ (default: 'vp')
rotate Rotation parameters [central_lat, central_lon, rotation_angle] in degrees, defaults to None (default: None)

ATTModel.read(model_fname: str, para_fname='input_params.yml')

Read an exists model

Parameters

Name Type Description
model_fname str Path to the exists model
para_fname (str, optional) Path to parameter file, defaults to ‘input_params.yml’ (default: 'input_params.yml')

ATTModel.read_param()

Read n_rtp, min_max_dep, min_max_lat and min_max_lon from para_fname


ATTModel.smooth(sigma=5.0, unit_deg=False, smooth_ani=False, **kwargs)

Gaussian smooth the 3D velocity model

Parameters

Name Type Description
sigma scalar | sequence of scalars Standard deviation for Gaussian kernel. If scalar, apply to all dimensions. If sequence of 3, apply to [depth, lat, lon]. Depth is always in km. Horizontal dimensions depend on unit_deg. (default: 5.0)
unit_deg bool If True, horizontal sigma is in degrees. If False, horizontal sigma is in km. Defaults to False. (default: False)
smooth_ani bool If True, also smooth anisotropic parameters (xi, eta, zeta). Defaults to False. (default: False)
kwargs Additional arguments passed to scipy.ndimage.gaussian_filter .. rubric:: Examples To smooth with 5 km in depth and 0.2 degrees in horizontal directions:: >>> model.smooth(sigma=[5.0, 0.2, 0.2], unit_deg=True) To smooth with 5 km in depth and 20 km in horizontal directions:: >>> model.smooth(sigma=[5.0, 20.0, 20.0], unit_deg=False) (default: {})

ATTModel.to_ani()

Convert to anisotropic strength (epsilon) and azimuth (phi)


ATTModel.to_xarray()

Convert to xarray

Returns

Type Description
pytomoatt.attarray.Dataset attarray dataset

ATTModel.write(out_fname=None)

Write to h5 file with TomoATT format.

Parameters

Name Type Description
fname (str, optional) file name of output model, defaults to ‘model_crust1.0.h5’